core.ac.uk · 4 department of business administration dr feza tabassum azmi faculty of management...
TRANSCRIPT
OLE OF INTERNAL AND. EXTERNAL AGENTS IN MANAGEMENT OF HUMAN RESOURCES: AN
EMPIRICAL STUDY OF SELECTED COMPANIES IN INDIA
THESIS SUBMITTED FOR THE AWARD OF THE 0EQ.RfE OF
~nttur of ftil000vbp IN
BUSINESS ADMINISTRATION
By
SHAHID MUSHTAQ
UNDER THE SUPERVISION OF # S
DR. FEZA TABASSUM AZMI D
DEPARTMFN`I OF BUSINESS ADMINIS?RA?ION F~IGUUTY OF MANAGEMENT S1UDIES & RESEARGH
Ab1GARE MU.SbINt UNIVERSI°IY bIGARS -- 202002 [INDIA]
2012
9061
I DEDICATE THIS WORK TO MY REVERED SUPERVISOR Dr. FEZA TABASSUM AZM!
AND PARENTS THEIR INSPIRATION, LOVE AND SUPPORT HAS MADE
THIS WORK POSSIBLE
4 Department of Business Administration Faculty of Management Studies & Research
Dr Feza Tabassum Azmi '~ Aligarh Muslim University, Aligarh-202002 India Ph: +91 9411802120
Assistant Professor E-Mail: [email protected]
CERTIFICATE
Certified that Mr. SHAHID MUSHTAQ, PhD scholar in this Department, has
completed his thesis entitled "ROLE OF INTERNAL AND EXTERNAL
AGENTS IN MANAGEMENT OF HUMAN RESOURCES: AN
EMPIRICAL STUDY OF SELECTED COMPANIES IN INDIA" under my
supervision.
To the best of my knowledge and belief, the research work carried out by him is
based on the investigations made, data collected and analyzed by him, and has not
been submitted in any other university or institution for the award of any degree or
diploma.
(Dr. Feza Tabassum Azmi)
PhD Supervisor
ACKNOWEDGEMENTS
My first and foremost humble gratitude to "ALLAH" the ALMIGHTY for giving
me the strength to remain dedicated to complete this thesis.
I express my sincere gratitude to my supervisor Dr. Feza Tabassum Azmi for her
scholarly guidance, unflinching support and constant encouragement towards the
successful completion of this work. Her abiding commitment to scholarship and
academics has been an inspiring example and I am grateful to her for her
supervision and mentorship.
I owe my gratitude to Prof. Kaleem Mohd Khan for his invaluable suggestions
and help related to instrument/questionnaire development. I shall remain ever
grateful to Prof. M. Khalid Azam, Chairman, Department of Business
Administration and Dean, Faculty of Management Studies and Research, Aligarh
Muslim University, Aligarh, India, for his support and encouragement in the
completion of this thesis work.
I am also grateful to Prof. Javaid Akhtar, Prof. M. Israrul Haque, Prof. Valeed
Ahmad Ansari, Prof. Jamal Ahmad Farooqui, Prof. Parvaiz Talib, Dr. Salma
Abmad for their constant encouragement and support for the completion of this -
work. I am also thankful to all other teaching and non-teaching staff at the
Department of Business Administration, Aligarh Muslim University, Aligarh,
India, for always being very co-operative and supportive during this research.
I am sincerely grateful to Dr. Mohd Naved Khan, Department of Business
Administration, AIigarh Muslim University, Aligarh, India for reviewing the draft
questionnaire and promptly replying to all my queries as well as providing me
guidance from time to time.
I am grateful to Dr. Yasser Mahfooz for his co-operation during the course of this
study. I am also thankful to Late. Prof. Venkat Ratnam, IMI, New Delhi, India,
Dr. G. P Raman, Presidency College, Chennai, India, Prof. K. Prabhakar,
Velammal Engineering College, Velammal Nagar, Ambattur-Red Hills Road,
Chennai, India for reviewing the preliminary draft questionnaire/instrument and
providing their invaluable inputs and suggestions through their experience and
ii
knowledge of the subject. I am deeply thankful to Ratnakar Misra, Ex-HR Head
Hindustan Unilever Ltd. for his feedback on the earlier draft of
questionnaire/instrument.
I am grateful to Dr. M. Srimannarayana, XLRI, Jamshedpur, India; Dr. Rakesh
Agrawal, Assistant Professor IMT Ghaziabad, India, for providing necessary
reference material. I am thankful to Dr. Andrew F. Hayes, The Ohio State
University, USA, Prof. Dag Sorbom, Uppsala University, Sweden, Prof. Athar
All Khan, Prof. Qazi Mazhar Ali, from Aligarh Muslim University, Aligarh,
India and Dr. Pravasini Sahoo, IIT, Kharagpur, India for providing useful insights
regarding data analysis and structural equation modeling as well as providing the
reference material.
I am thankful to staff of Computer Centre and librarian of the Aligarh Muslim
University, Aligarh, India for their cooperation during the course of the study.
Special thanks are also due to Ratan Tata Library, Librarian, Delhi University,
Delhi, India, library staff of American Centre Library and NCERT Library,
New Delhi, India, for providing me access to all the research books, articles,
periodicals, reviews and other reference materials in these libraries.
I am grateful to Dr. Fareed Mehadi, Training and Placement Officer, Zakir
Hussain College of Engineering and Technology, Aligarh Muslim University,
Aligarh, India, Suresh Tripathi, President National HRD Network Delhi Chapter
and President (Human Resources) SRF Ltd, S. C. Bahuguna, Director, Indian Society For Training & Development (ISTD), New Delhi, India, S. Y. Siddiqui,
National President, NHRDN and Managing Executive Officer Admn (HR, Finance,
IT & COSL) Maruti Suzuki India Ltd, S. Ramesh, General Manager CPCL,
Chennai, India, Mohit Gandhi, Executive Director National HRD Network,
Della, Sham Sunder Singh, HR Consultant Chennai, India, Narender Kumar
Gupta, HR Consultant, Delhi, India, Satyanarayana Kunamneni, National HRD
Network for extending their support in data collection,
I am thankful to National HRD Network, New Delhi, Indian Society for
Training & Development, Confederation of Indian Industry, New Delhi, Associated Chambers of Commerce and Industry of India, New Delhi and
Federation of Indian Chamber of Commerce Industry, New Delhi, Delhi
iii
Management Association, New Delhi and CII, Chennai for providing me the
much needed opportunity to collect the data during the industry interaction
programs organized by different industry bodies as well as for providing the
databases of the member organizations to obtain the information from the selected
organizations. I will like to acknowledge the cooperation extended by the
responding organizations in providing their responses.
I owe my special thanks to my teachers and mentors Prof. Irshad Ahmed Hamal,
Dr. Sayeed Hasan Rizvi, Prof. S. H. Shah Jafri, Prof. J. A. Qazi, Prof. Ghulam
Abas, Prof. B. C Sharma, for their constant encouragement, support and good
wishes. I am thankful to alumni of our Department and University for their support
in data collection. I would like to thank Abdul Gafoor Danish, alumnus of the
department for his help in data collection. I am also thankful to my friends Zareen
Hussain and Javed Ghaffar for always being very helpful. My sincere thanks are
also due to fellow Research Scholars for their stimulation, support and good
wishes.
I am indebted to my family members who have been a constant source of
encouragement and moral support for rriy academic accomplishment. Last but not
the least, I would like to thank my father and mother for teaching me to work hard
and believe I could do anything.
(Shahid Mushtaq)
PREFACE
Business organizations are striving to maintain their competitive edge by
effectively managing their human capital. Managers at different levels have
realized that critical source of competitive advantage comes from having systems
and processes for managing human talent. Several researchers have highlighted the
dynamic nature of HR functions and its importance to the success of an
organization. Consequently, researchers and practitioners have recognised the
importance of strategic thinking vis-a-vis Human Resource Management (HRM).
These developments in HRM scenario have significantly changed the roles of the
HR professionals as well as the way people are managed in the organizations.
Several researchers have reported that besides HR departments, many other
people/entities are involved in management of HR. It is opined that there are
several agents-internal and external- who are involved in human resource
management activities owing to the increasing importance of people related issues
in business organizations.
Thus, it implies that agents other than the HR department may be involved in the
management of people in organizations. Primarily, research talks about three
important agents in HRM viz. top management, line managers and external service
providers. In the present study, the use of the term `agents' refers to the internal
and external entities/persons involved in HRM activities. It implies that these
entities/persons are not intrinsically part of an organization's HR department, but
are nevertheless, involved in different HR activities in varying capacities. Their
involvement has been mandated out of the growing need of business organizations
to involve non HR managers in HRM activities since human resource is seen as the
most vital organizational asset. Further, the need to share HRM - activities with
internal and external entities is necessary in order to enable HR managers to focus
their attention on strategic matters. The scope of studies on role of internal and
external agents in HRM has varied from being generic in nature to studies on
specific HR areas. The domain and focus of prior studies has been on the different
HRM functions of recruitment & selection, training and development, performance
v
appraisal, pay, reward management, human resource development and industrial
relations.
There are several reasons identified in the literature for the growing involvement
and participation of the.above agents in HRM. The involvement of these agents in
HRM helps business organizations to enhance their competence in managing
people, thereby, positively contributing to organizational change and enhancing
organizational effectiveness. Also, the involvement of agents is useful to close the
gap between organizational performance and individual performance and getting
long-lasting competitive advantage. The participation of these agents in HRM
helps in leveraging strategic competencies in order to survive the competition.
Keeping in mind the fact that the role of agents in HRM is increasing and their
involvement in HEM has significant consequences for the management of people
in organizations, a study on the role of these agents is expected to be both timely
and essential. Thus, a need was felt to develop an understanding on the prevailing
role of internal and external agents in HRM. The study attempts to develop a
reliable and valid instrument for measuring the role of internal and external agents
in management of human resources and to investigate the impact of the roles on the
status and effectiveness of HRM in selected companies in India.
This thesis is structured in the form of seven chapters. The first chapter begins with
an introduction of the importance of people management in organizations and
presents the definition of internal and external agents vis-a-vis HRM. It highlights
the role of internal agents viz, top management and line managers and external
agents viz, external service providers in HRM. Thereafter, the rationale behind the
present research and the objectives of the study are presented. This is followed by
the significance of the present research. In the end, the chapter provides an outline
of the research framework.
The second chapter provides a review of the existing literature on the role of
internal agents (line managers and top management) and external agents (external
service providers) in HRM. This chapter begins with a discussion of the role of the
agents in HRM. Thereafter, it gives an overview of different constructs used to
measure the above roles. Finally, it gives an insight into the status of empirical
researches undertaken on these roles in the Indian context.
vi
The chapter three seeks to identify the research gaps in the existing literature on the
role of internal and external agents in HRM. It focuses on indicating the problem
areas existing in the available literature. These problem areas and gaps relate to
both theoretical and empirical studies on role of agents and apply to both Indian
and global studies.
The fourth chapter provides a brief description of the need for research and study
objectives. It gives details of the research design and methodology. A discussion on
study constructs and items, instrument development and validity concerns,
sampling procedure and questionnaire administration is done which is followed by
specification of conceptual research models considered for the study along with
research hypotheses. The chapter ends with a brief outline of the methods of
analysis and the limitations of the study.
The fifth chapter begins with a discussion of the plan of analysis followed by a
flow chart depicting the same. Subsequently, it provides details of the profile of
responding firms and the respondents. The first part of the analysis deals with an
estimation of response rate, non-response bias, and common' method bias. After
that, measurement model and structural model fit are estimated and path analysis
carried out for testing of research hypotheses of three alternate research models.
This is followed by the assessment and comparison of alternate models on the basis
of fit measures. The chapter comes to an end with tests of comparison and
association with respect to company type and agents' involvement in HRM.
The sixth chapter provides a brief description of the findings based on the
analysis carried out. A discussion of the findings of the current research is carried
out in the light of prior research studies by other researchers. The last part deals
with the conclusions of the present study.
The seventh chapter highlights the managerial implications and contributions of the
study and puts forward directions for future research.
. I,cJ%, Shahid Mushtaq
vii
LIST OF PUBLICATIONS
Azmi, F. T. & Mushtaq, S. (2010). Charting the devolution landscape: Rhetoric and
reality Integral Review A Journal of Management, 3(1), 3-20
Azmi, F. T. & Mushtaq, S. (2011). Assessing the role of internal and external
agents in HRM: Scale development and validation. South Asian Journal of
Management, (Under review).
Azmi, F. T. & Mushtaq, S. (2012). Role of line managers in HRM: Empirical
evidences from India. International Journal of Human Resource Management,
(Under review).
Mushtaq, S. & Azmi, F. T. (6-7 June, 2011). Human resource outsourcing:
Emerging paradigm and research agenda. Paper accepted for Third Annual
American Business Research Conference Adelphi University, Long Island,
New York, USA.
viii
LIST OF ABBREVIATIONS
Abbreviations Expressions AIC Akaike Information Criterion AGFI Adjusted Goodness of Fit Index CAIC Consistent Akaike Information Criterion CFA Confirmatory Factor Analysis CFI Comparative Fit Index df Degrees of freedom
EBU External Service Providers Involvement in Budgeting vis-a-vis HRM
EDM External Service Providers involvement in Decision-making vis-a-Vis HRM
EFA Exploratory Factor Analysis EFF Effectiveness of HRM
EPA External Service Providers Involvement in Process/Activities vis-a-vis HRM
GFI Goodness of Fit Index HRM Human Resource Management HRO Human Resource Outsourcing IF! Incremental Fit Index IR Industrial Relation LBU Line Managers Involvement in Budgeting vis-a-vis HRM LDM Line Managers Involvement in Decision-making vis-a-vis •HRM LISREL Linear Structural Relationship LPA Line Managers Involvement in Process/Activities vis-a-vis HRM MI Model 1: Direct Effect Model M2 Model 2: Partially Mediated Model M3 Model 3: Fully Mediated Model MLE Maximum Likelihood Estimation NFI Normed fit Index NNFI Non-Normed fit Index PGFI Parsimony Goodness- of-fit Index PNFI Parsimony Normed- of-fit Index RFI Relative Fit Index RMSR Root Mean S uare Residual RMSEA Root Mean Square Error of Approximation SEM Structural equation Modeling SRMSR Standardized Root Mean Square Residual STA Status of HRM TBU Top Management Involvement in Budgeting vis-a-vis HRM TDM Top Management Involvement in Decision-making vis-a-vis HRM TPA Top Management Involvement in Process/Activities vis-a-vis HRM
ix
LIST OF EXHIBITS
CHAPTER 1: INTRODUCTION Page No
Exhibit 1.1: Research Framework 15
CHAPTER 2: REVIEW OF LITERATURE
Exhibit 2.1: Typology of Line Manager Roles 24 Exhibit 2.2: Mapping Perspectives on Line Managers as
Developers (LMaD) 26 Exhibit 2.3: A Framework for Line Manager HR Involvement 27 Exhibit 2.4: Typology of Middle Manager Influence 28 Exhibit 2.5: Proposed Influences on Strategic HRM Integration 39 Exhibit 2.6: Factors Influencing the Strategic Role of HR Department 41
Exhibit 2.7: A Model for Outsourcing 58 Exhibit 2.8: A Model for Successful HR Outsourcing 58
Exhibit 2.9: Moderation and Mediation 68
CHAPTER 4: RESEARCH METHODOLOGY
Exhibit 4.1: Classification of Research Design 87 Exhibit 4.2: Flowchart Illustrating the Questionnaire Development Process 94 Exhibit 4.3: Flow Chart Representing the Sampling Procedure 100 Exhibit 4.4a: Direct Effect Conceptual Model of Research (M1) 107 Exhibit 4.4b: Partially Mediated Conceptual Model of Research (M2) 107
Exhibit 4.4c: Fully Mediated Conceptual Model of Research (M3) 108
CHAPTER 5: ANALYSIS AND INTERPRETATION
Exhibit 5.1: Flow Chart Depicting the Sequence of Analysis 123
Exhibit 5.2: Nomological Validity: Measurement Model with Correlations 150
Exhibit 5.3: Classification of Fit Measures 152
Exhibit 5.4: Direct Effect Structural Model (M1) 157
Exhibit 5.5: Partially Mediated Structural Model (M2) 161
Exhibit 5.6: Fully Mediated Structural Model (M3) 167
x
LIST OF TABLES
CHAPTER 2: Page No
Table 2.1: Characteristics of Devolution of HRM to Line 20
Table 2.2: Key HR Domains vis-a-vis Line Manager Roles 31
Table 2.3: Key HR Domains vis-a-vis HRO 50
Table 2.4: Key Benefits vis-a-vis HRO 55
Table 2.5: Constructs Used to Measure Role of Internal and
External Agents 62
Table 2.6: Performance Measures from Literature on Role of Agents 70
Table 2.7: Moderating Variables Identified in Literature 71
CHAPTER 5: Analysis and Interpretation
Table 5.1: Responding Organizations — Sector 124
Table 5.2: Responding Organizations — Ownership 124
Table 5.3: Responding Organizations — Nationality 124
Table 5.4: Responding Organizations — Size 124
Table 5.5: Respondent Profile —Designation 125
Table 5.6: Respondent Profile — Experience in Present Position 125
Table 5.7: Respondent Profile -- Total Experience in the Organization 126
Table 5.8: Group Statistics for Non-response Error 128
Table 5.9: Independent Samples Test for Non-response Error 128
Table 5.10: Common Method Bias — Total Variance Explained 131
Table 5.11: Variables/Measures Considered for the Study 132
Table 5.12: KMO and Bartlett's Test of Sphericity 134
Table 5.13A: TDM Scale —Total Variance Explained 134
Table 5.13B: TDM Scale —Component Matrix 135
Table 5.14A: TPA Scale —Total Variance Explained 135
Table 5.14B: TPA Scale — Component Matrix 135
Table 5.15A: TBU Scale —Total Variance Explained 136
Table 5.15B: TBU Scale —Component Matrix 136
Table 5.16A: LDM Scale —Total Variance Explained I36
xi
Table 5.16B: LDM Scale —Component Matrix 137
Table 5.17A: LPA Scale —Total Variance Explained 137
Table 5.17B: LPA Scale —Component Matrix 137
Table 5.18A: LBU Scale —Total Variance Explained 138
Table 5.18B: LBU Scale — Component Matrix 138 Table 5.19A: EDM Scale—Total Variance Explained 138
Table 5.19B: EDM Scale —Component Matrix 139 Table 5.20A: EPA Scale —Total Variance Explained 139
Table 5.20B: EPA Scale —Component Matrix 139 Table 5.21A: EBU Scale —Total Variance Explained 140 Table 5.21B: EBU Scale —Component Matrix 140 Table 5.22A: STA Scale —Total Variance Explained 140 Table 5.22B: STA Scale —Component Matrix 141 Table 5.23A: EFF Scale —Total Variance Explained 141 Table 5.23B: EFF Scale —Component Matrix 141 Table 5.24: Indicator Reliability of the Scales 143 Table 5.25: Scale Reliability Estimates 144 Table 5.26: 1-values of Scale Items 146 Table 5.27: Bentler-Bonett Coefficient and GFI Values 147 Table 5.28: Discriminant Validity-Total Variance Explained 148 Table 5.29: Discriminant Validity of Scales 149 Table 5.30: Nomological Validity of Scales: Correlation Values 149 Table 5.31: Fit Indices, Recommended Values and Descriptions 153 Table 5.32: Moderating Variables - Correlation Values Matrix 154 Table 5.33: Ml-Fit Indices from LISREL 8.50 155 Table 5.34:M1-Hypotheses Testing through SEM .159 Table 5.35: M2-Fit Indices from LISREL 8.50 159 Table 5.36: M2-Hypotheses Testing through SEM 164 Table 5.37: M3-Fit Indices from LISREL 8.50 165 Table 5.38: M3-Hypotheses Testing through SEM 169 Table 5.39: Comparision of Fit Indices of Alternate Models 171 Table 5.40A: Group Statistics 174 Table 5.40B: Independent Samples T- Test 175 Table 5.41A: ANOVA Descriptives 178
xii
Table 5.41B: ANOVA Results 179 Table 5.42: Tests of Differences 179 Table 5.43: Chi-Square Tests 180 Table 5.44: Chi-Square Tests 180 Table 5.45: Chi-Square Tests 181 Table 5.46: Chi-Square Tests 181
Table 5.47: Chi-Square Tests 182
Table 5.48: Chi-Square Tests 182
Table 5.49: Chi-Square Tests 183 Table 5.50: Chi-Square Tests 183 Table 5.51: Chi-Square Tests 183 Table 5.52: Chi-Square Tests 184
Table 5.53: Chi-Square Tests 184
Table 5.54: Chi-Square Tests 185
Table 5.55: Chi-Square Tests 185
Table 5.56: Chi-Square Tests 186
Table 5.57: Chi-Square Tests 186
Table 5.58: Chi-Square Tests 186
Table 5.59: Chi-Square Tests 187
Table 5.60: Chi-Square Tests 187
Table 5.61: Tests of Association 187
CHAPTER 6: Findings, Discussion and Conclusion
Table 6.1: Results of Hypotheses Testing: Direct Effect Model (M1) 195
Table 6.2: Results of Hypotheses Testing: Partially Mediated Model (M2) 196
Table 6.3: Results of Hypotheses Testing: Fully Mediated Model (M3) 197
Table 6.4: Results of Tests of Difference and Association 200
TABLE OF CONTENTS
PAGE NO.
Certificate Acknowledgements Preface v List of Publications viii List of Abbreviations ix List of Exhibits x List of Tables xi
Table of Contents xis
Chapter 1: INTRODUCTION 1-15 1.1 Background of the Study I 1.2 Agents in HRM: Meaning and Definitions 4 1.3 Indian Scenario: A Snapshot 8 1.4 Rationale of the Study 9 1:5 Research Objectives 12 1.6 Significance of the Study 14 1.7 Research Framework 15
Chapter 2: REVIEW OF LITERATURE 16-77 2.1 Role of Internal and External Agents in HRM: Brief Overview 16 2.2 Role of Internal Agents in HRM 18
2.2.1 Role of Line Managers in HRM 19 2.2.1.1 Dimensions of Line Manager Roles 21 2.2.1.2 Line Manager Roles: Key HRM Domains 28 2.2.1.3 Rationale for Role of Line Managers in HRM 31 2.2.1.4 Role of Line Managers in HRM: Barriers and
Constraints 34 2.2.2 Role of Top Management in HRM 37
2.2.2.1 Dimensions of Top Management Roles 38
xiv
2.2.2.2 Top Management Roles: Key HRM Domains 42
2.2,2.3 Rationale for Role of Top Management in HRM 43
2.3 Role of External Agents in HRM 44
2.3.1 External Service Providers : HR Outsourcing 44
2.3.2 Dimensions of Human Resource Outsourcing 45
2.3.3 Human Resource Outsourcing: Key HRM Domains 48
2.3.4 Rationale for Human Resource Outsourcing 51
2.3.5 Human Resource Outsourcing: Barriers and
Constraints 56
2.4 Constructs to Measure Role of Agents in HRM 59
2.5 Alternate Variables to Measure Role of Agents in HRM 67
2.5.1 Performance Measures as Outcome Variables 68
2.5.2 Moderating Variables 71
2.5.3 Mediating Variables 73
2.6 Internal and External Agents in HRM: An Indian Perspective 74
Chapter 3: PROBLEM AREAS AND RESEARCH GAP 78-82
3.1 Focus on the Role of Individual Agents 78
3.2 Focus an Prescriptive Studies. 79
3.3 Lack of Studies on Outcomes of Role of Agents in HRM 79
3.4 Focus on Qualitative Methodology 80
3.5 Paucity of Empirical Studies 80
3.6 Small Sample Size-Based Studies 81
3.7 Low Response Rate in Existing Studies 81
3.8 Focus on Manufacturing Sector 81
3.9 Lack of Reliability and Validity of Research Instruments 82
3.10 Paucity of Studies in the Indian Context 82
Chapter 4: RESEARCH METHDOLOGY 83-119
4.1 Need for Research 83
4.2 Research Objectives 84
4.3 Research Design 87
4.4 Research Constructs and Measures 88
4.4.1 Independent Variables: Measures of Role 88
4.4.2 Dependent Variable: Effectiveness of HRM 91
xv
4.4.3 Mediating Variable: Status of HRM 92
4.4.4 Moderating Variable: Organizational Profile 93
4.5 Questionnaire Development Process 93
4.5.1 Stages of Questionnaire Development 94
4.5.2 Translation Validity: Face and Content Validity 97
4.6 Research Instrument/Questionnaire 98
4.7 Sampling Procedure 100
4.7.1 Target Population 100
4.7.1.1 Sampling Unit 101
4.7.1.2 Sampling Element 101
4.7.2 Sampling Frame 102
4.7.3 Sampling Approach and Sample Size 103
4.8 Questionnaire Administration and Data Collection 103
4.9 Conceptual Models of Research 106
4.10 Research Hypotheses 109.
4.11 Methods of Analysis 118
4.12 Limitations of the Study 119
Chapter 5: ANALYSIS AND INTERPRETATION 120-187
5.1 Plan of Analysis 120
5.2 Profile of Responding Firms and Respondents 123
5.3 Estimation of Response Rate 126
5.4 Estimation of Non-response Bias 127
5.5 Estimation of Common Method Bias 129
5.6 Measurement Model 131
5.6.1 Factor Analysis 132
5.6.2 Assessment of Reliability 142
5.6.3 Assessment of Validity 145
5.7 Structural Model 151
5.7.1 Structural Model Fit 151
5.7.2 Fit Indices, Path Coefficients and
Hypotheses Testing 155
5.8 Criterion Validity 169
5.9 Comparison of Alternate Models 170
xvz
I
5.10 Tests of Differences
172
5.11 Tests of Association
179
CHAPTER 6: FINDINGS, DISCUSSIONS AND CONCLUSIONS 188-204
6.1 Findings and Discussions 188
6.2 Conclusions 201
Chapter 7: MANAGERIAL IMPLICATIONS AND FUTURE 205-208 RESEARCH DIRECTIONS
7.1 Managerial Implications and Contributions of the study 205 7.2 Future Research Directions 207
REFERENCES
209-237 Appendix : Questionnaire
xvii
CHAPTER 1: INTRODUCTION
1.1 Background of the Study
1.2 Agents in HRM: Meaning and Definitions
1.3 Indian Scenario: A Snapshot
1.4 Rationale of the Study
1.5 Research Objectives
1.6 Significance of the Study
1.7 Research Framework
CHAPTER 1: INTRODUCTION
Chapter Overview
This chapter begins with an introduction of the importance of people management
in organizations and presents the definition of internal and external agents vis-a-vis
Human Resource Management (HRM). It highlights the role of internal agents viz.
top management and line managers and external agents viz, external service
providers in HRM. Thereafter, the rationale behind the present research and the
objectives of the study are presented. This is followed by the significance of the
present research. In the end, the chapter provides an outline of the research
framework.
1.1 Background of the Study
Business organizations are striving to maintain their competitive edge by
effectively managing their human capital. Mello (2011) argued that managers at
different levels have realized that critical source of competitive advantage comes
from having systems and processes for managing human talent. Several researchers
have highlighted the dynamic nature of HR functions and its importance to the
success of an organization (Lengnick-Hall & Lengnick-Hall, 1988; Schuler, 1992).
For instance, Boxall (1994) reported that HR functions have moved from being
administrative and reactive to being executive and proactive. The competitive
business environment has led to massive restructuring in business organizations.
Consequently, human resource researchers and practitioners have recognised the
importance of strategic thinking vis-a-vis HRM (Brewster & Larsen, 1992;
Brewster & Soderstrom, 1994; Budhwar, 2000a, 2000b; Budhwar & Sparrow,
1997; Lengnick-Hall & Lengnick-Hall, 1988; Schuler, 1992; Schuler et al., 1993;
Storey, 1992; Storey & Sisson, 1994).
These developments in HRM scenario have significantly changed the roles of the
HR professionals as well as the way people are managed in the organizations.
Several researchers have reported that besides HR departments, many other
people/entities are involved in management of HR (Khatri & Budhwar, 2002;
1
PapaIexandris & Panayotopoulou, 2005; Whittaker, 1990). In this context,
Valverde et al. (2006) argued in favour of the role of agents in management of HR
and highlighted the contribution that the different HR agents make to the HR
function. It is opined that there are several agents-internal and external- who are
involved in human resource management activities owing to the increasing
importance of people related issues in business organizations.
Thus, it implies that agents other than the HR department may be involved in the
management of people in organizations. Primarily research talks about three
important agents viz.
■ Top management, who make strategic decisions (including HRM strategic
decisions), establish the organization's values and philosophy (Guest, 1997;
Lepak & Snell, 1999a; Schuler & Jackson, 1999) and influence its whole
approach to managing people (Sisson & Storey, 2000; Stanton et al., 2010).
■ Line managers, who traditionally have been given responsibility for some
operational aspects of managing people, but whose role in this function has
continued to increase since the advent of HRM (Hutchinson & Wood 1995;
Keen & Vickerstaff, 1997; Lowe, 1992; Schuler 1992; Storey, 1992).
■ External HR service providers or HR outsourcing agencies usually
contracted by organizations to provide administrative HRM services or
professional, specialised HRM solutions (Cook, 1999; Young, 2000). The
outsourcing of these activities has also been found to be on the increase..
(Hall & Torrington, 1998).
Various research studies have -highlighted the role of internal agents viz, top
management (Schuler & Jackson, 1999; Valverde et al., 2006), line managers
(Brewster & Larsen, 2000; Brewster et al., 2004; Harris et al., 2002; Hoogendoorn
& Brewster, 1992; Larsen & Brewster, 2003; Legge, 1995; Thornhill & Saunders,
1998) and external agents viz. external HR service providers (Cook, I999;
Cunningham & Hyman, 1999; Delmotte & Sels, 2008; Klass et al., 2001; Valverde
et al., 2006) in people management activities. The scope of studies on role of
internal and external agents in HRM has varied from .being generic in nature to
studies on specific HR areas (Casco"n-Pereira et al., 2006). The studies which are
general in nature provide insights about the sharing of HRM function with agents
N
(e.g. Armstrong, 1998; Hall & Torrington, 1998; Sparrow et al., 1994; Valverde,
2001), while the studies on specific areas focus on precise HR activities being
carried out by other agents (e.g. Bond & Wise, 2003; Currie & Procter, 2001;
Heraty & Morley, 1995; Hope-Hailey et al., 1997). Both types of studies focus on
the fact that HR activities are shared with other agents.
The domain and focus of prior studies has been on the different HRM functions of
recruitment & selection, training and development, performance appraisal, pay,
reward management, human resource development and industrial relations
(Andersen et al., 2007; Ardichvili & GasparishviIi, 2001; Brown & Purcell, 2007;
Budhwar, 2000a; Casco'n-Pereira et al., 2006; Cook, 1999; Cunningham &
Hyman, 1995; Currie & Procter, 2001; Gautam & Davis, 2007; Hall & Torrington,
1998; Heraty & Morley, 1995; Hope-Hailey et al., 1997; Mahoney & Brewster,
2002; Murty, 2007; Papalexandris et al., 2001; Redman, 2001; Smith et al., 2006;
Srimannarayana, 2010; Watson & Maxwell, 2007; Watson et al., 2007; Woodall et
al., 2002). Theses HRM functions have been considered by previous researchers to
study the involvement of internal and external agents in light of individual as well
as groups of HR activities.
There are several reasons identified in the literature for the growing involvement
and participation of the above agents in HRM. The involvement of these agents in
HRM helps them to enhance their competence in managing people, thereby,
positively contributing to organizational change and enhancing organizational
effectiveness (Buyens & De Vos, 2001; Gibb, 2003; Macneil, 2001; McCracken &
Wallace, 2000; Siug2diniene, 2008). Also, the involvement of agents is useful to
close the gap between organizational performance and individual performance and
getting long-lasting competitive advantage (Gibb, 2003; Macneil, 2001;
5iugzdiniene, 2008). The participation of these agents in HRM helps in leveraging
strategic competencies in order to survive the competition (Keen & Vickerstaff,
1997; Stanton etal., 2010).
Keeping in mind the fact that the role of agents in HRM is increasing and their
involvement in HRM has significant consequences for the management of people
in organizations, a study on the role of these agents is expected to be both timely
and essential. Thus, a need was felt to develop an understanding on the prevailing
role of internal and external agents in HRM.
3
1.2 Agents in HRM: Meaning and Definitions
The Cambridge Advanced Learner's Dictionary & Thesaurus defines the word
`agent' as a person who acts for or represents another. According to the Oxford
Dictionary, the term `agent' is derived from Latin word agere- 'doing', meaning a
person who acts on behalf of another to produce an effect. Further, it goes on to
define an `agent' as a person who helps in managing business, financial, or
contractual matters for another. These definitions of the term `agent' signify the
involvement of other entities/persons in a particular activity.
In the present study, the use of the term `agents' refers to the internal and external
entities/persons involved in HRM activities. It implies that these entities/persons
are not intrinsically part of an organization's HR department, but are nevertheless,
involved in different HR activities in varying capacities. Their involvement has
been mandated out of the growing need of business organizations to involve non
HR managers in HRM activities since human resource is seen as the most vital
organizational asset (Keen & Vickerstaff, 1997; Kulik & Bainbridge, 2006; Lawler
& Mohrman, 2000; Ulrich 1997). Further, the need to share HRM activities with
internal and external entities is necessary in order to enable HR managers to focus
their attention on strategic matters (Kulik & Bainbridge, 2006; Valverde et al.,
2006; Valverde, 2001).
According to Valverde et al. (2006), agents other than the HR department may be
involved in the management of people in organizations. These are both external and internal agents. Internal agents include top management and line managers
whereas external agents include external service providers or HR outsourcing
agencies. The HR function is not understood simply as a set of activities performed
by the HR department but all managerial actions regarding the organization of
work and the entry, development and exit of people in the organization (Valverde,
2001). The idea of HRM as a partnership of multiple agents or stakeholders is
beginning to be more widely employed (Valverde et al., 2006). Researches in the
area have recognized the role of these agents in HRM with varying levels of
contribution (e.g. Kulik & Bainbridge, 2006; Valverde et al., 2006).
4
Internal Agents in HRM
Top Management
Top management has been considered as an important internal agent in HRM
(Valverde et al., 2006), as they make crucial strategic decisions and influence the
whole approach to managing people (Guest, 1997; Lepak & Snell, 1999a; Sisson &
Storey, 2000; Stanton et al., 2010). A number of research studies have explored the
significance and contribution of top management teams in the organization. In this
context, the role of chief executive officers, top management teams and board of
directors as strategic assets has been identified (Fisher & Dowling, 1999;
Hambrick & Mason,1984).
Several researchers have acknowledged the influence of top management on HRM
policies and practices (e.g. Heneman et al. 2000; Khilji, 2002; Tsui & Milkovich,
1987). Researchers (e.g. Green et al., 2006; Valverde et al., 2006) have opined that
some form of involvement of top managers in HR is vital for attaining business
objectives. When top executives are sensitized to human resource issues, it tends to
support greater HR-strategy integration, leading to favourable outcomes for the
organization (Bae & Lawler, 2000; Bennett et al., 1998). Top managers should
offer transformational leadership by sharing their vision with employees. An HR
function that is perceived by key actors in the corporation to have a high degree of
reputational effectiveness is more likely to succeed in enacting strategic roles. Top
management is recognized as the most powerful force facilitating HRM (Boxall &
Purcell, 2003; Macky & Boxall, 2007; Stanton et al., 2010; Wright et al., 1994).
Line Managers
The role of line managers vis-a-vis HRM has received ample research attention
(Agrawal, 2010; Budhwar, 2000a, 200b; Budhwar & Sparrow, 1997; Gibb, 2003;
Keen & Vickerstaff, 1997; Kulik & Bainbridge, 2006; Macneil, 2001; McCracken
& Wallace, 2000; Siug2diniene, 2008; Srimannarayana; 2010; Valverde et al.,
2006). Line managers or middle managers are placed below the top managers and
are responsible for supervising other managers. The scope of these managers has
traditionally been limited to establishing and meeting the goals in their respective
departments.
5
In this context, researchers have used the term devolution to define the role of line
managers. Devolution means reallocation of personnel tasks to line managers
(Brewster & Larsen, 2000; Hall & Torrington, 1998; Renwick, 2000; Storey,
1992). Devolution as a subject of inquiry has received considerable research
attention (e.g. Azmi & Mushtaq, 2010; Currie & Procter, 2001; Poole & Jenkins,
1997; Tsui & Milkovich, 1987 among others). Devolution to the line implies that
line managers should become more involved in HRM so that HR staff can take on
a greater strategic and change management roles (Finegold & Frenkel 2006; Sisson
& Storey 2000; Teo & Rodwell, 2007). A number of scholars have carried out
studies dealing with specific areas of HR devolution, for instance, Fenton-
O'Creevy's (2001) and Marchington's (2001) studies of middle managers attitudes
towards employee involvement, Redman's (2001) study about devolvement of
performance appraisal function, Currie and Procter's (2001) work on the area of
pay and Dunn and Wilkinson's (2002) study in the area of absence management.
Of late, the line managers' role have been reorganised in the organizations and
they are now responsible for core HRM functions. Line managers play an
important role in producing the synergy between physical and human resources for
the development of their subordinates (Brewster & Larsen, 1992). Line managers
are responsible for achieving the HRM goals and making sure that their
subordinates show commitment, quality and flexibility (Lowe, 1992). Legge
(1989) reported that HRM is "vested in line management as business managers
responsible for co-ordinating and directing all resources in the business unit in
pursuit of bottom line profits".
In addition to this, several HR responsibilities viz, pay and benefits, recruitment
and selection, training and development, industrial relations, health and safety, and
workforce expansion and reduction are shared between HR managers and Iine
managers (Brewster & Larsen, 2000; Larsen & Brewster, 2003). Line managers are
responsible for the implementation of these HR practices at the operational level
(Grafton & Truss, 2003; Marchington, 2001). Participation between HR and line
helps in enhancing organizational performance,(Gennard & Kelly, 1997). Further,
the effective implementation of these HR practices is dependent on line managers"
capability and commitment regarding their HR role (Guest, 1987; Purcell &
Hutchinson, 2007; Storey, 1992). Line management has been identified as the
0
perfect location to position HR responsibilities as it would make HR more
effective (Hope Hailey et al., 2005; McGovern et al., 1997). As a result of line
managers involvement in HRM, the status and effectiveness of HRM is enhanced
(Larsen & Brewster, 2003; Schuler, 1990).
External Agents in HRM
External HR Service Providers
The third important agent in HRM is external HR service providers or HR
outsourcing agencies (Cook, 1999; Hall & Torrington, 1998; Kulik & Bainbridge,
2006; Valverde et al., 2006; Young, 2000). It involves hiring a third-party service
provider or vendor for the administration of an HRM activity that would normally
be performed in-house. Many organizations find the use of external service
providers as more efficient and less costly than hiring staff to handle HRM
functions in-house. Given that HRM service vendors specialize in the services they
provide to their clients, they benefit from economy of scale effects and these
benefits are transferred to their clients. In addition to this, some organizations turn
to outsourcing either because they do not have the necessary knowledge, or their
knowhow is so outdated that they need to make significant investments. Many
vendors make investments in HRM tools and techniques and later spread their
costs over many clients. In this sense, outsourcing provides competencies that do
not exist in-house (Galanaki & Papalexandris, 2005).
Although, various researchers have put forward their view points on role of top
management, line managers and external service providers, yet there is no clear
consensus on the definition of these agents. However, certain common
terminologies and descriptions can be identified from the extant literature.
Researchers (e.g. Dale & Cooper, 1992; Fisher & Dowling, 1999; Hall &
Torrington, 1998; Hambrick & Mason, 1984; Storey, 1992,; Valverde et al., 2006;
Whittaker & Marchington, 2003) have frequently used the term top management,
upper echelons, senior managers, board level line managers, chief executive
officers, general managers, board of directors as well as senior line manager for
referring to top management. Similarly, terms such as supervisors, first line
managers, lower-level line managers, front-line manager, operational managers,
7
junior line managers, middle managers are used synonymously for line managers
(Bond & Wise, 2003; Budhwar, 2000a, 2000b; Budhwar & Sparrow, 1997;
Conway & Monks, 2010; Hales, 2005; Hall & Torrington, 1998; Heraty & Morley,
1995; KuIik & Bainbridge, 2006; Larsen & Brewster, 2003; Lowe, 1992;
Siug2diniene, 2008; Storey, 1992; Valverde et al., 2006; Whittaker &
Marchington; 2003). Likewise, for external agents the commonly used terms are
external service providers, outsourced consultants, HR outsourcing agencies,
external HR specialist agencies and external consultants (e.g. Hall & Torrington,
1998; Kulik & Bainbridge, 2006; Redman & Allen, 1993; Valverde et al., 2006).
1.3 Indian Scenario: A Snapshot
During the last twenty years, the Indian economy has undergone radical changes
from a predominantly government-controlled to a market-based economy and is
growing at a rapid pace (Grossman, 2008). Consequently, international firms are
investing in India to tap the business opportunities offered by its expanding
market. In order to extend the scope of their business operations in India, these
organizations have located their offices in India and are relying on more localized
management to develop an understanding of local management practices (Dowling
et al., 1994; Haire et al., 1996; Tayeb, 1994).
This shift has also changed the nature of competition for Indian organizations.
Globalization and internationalization of domestic businesses, concerns for total
quality management, shifts in the employee profile and de-skilling, re-skilling and
multi-skilling as well as issues related to work-force reduction have opened many
opportunities as well as challenges for the business organizations (Rao et al., 1994;
Sodhi, 1994; Venkata Ratnam, 1995). The paradigm shift in the economy has
direct implications for HRM in India (Krishna & Monappa, 1994).
Of late, Indian industry has realised the importance of effectively managing human
resources for long-lasting competitive advantage. Subsequently, studies in the
Indian context have highlighted the changing nature of HR policies, practices and
roles in Indian organizations (e.g. Bhatnagar & Sharma, 2004; Jain, 1991; Lawler
et al., 1995; Stening, 1994; Sharma & Khandekar, 2006). As the roles of HR
managers are becoming strategic in nature and they are now increasingly taking
part in board rooms, many HR tasks and responsibilities are getting reallocated to
other stakeholders such as line managers and external service providers. For
instance, Bhatnagar and Sharma's (2005) study have explored changing strategic
HR roles. Gopalakrishnan (2008) makes a case for placing HR on line managers'
schedule. However, there is dearth of empirical research on role of internal and
external agents in HRM in the Indian context.
In addition to this, focus in the Indian context has remained on the reallocation of
HR responsibilities to line managers (Budhwar & Sparrow, 1997), while in some
studies the impact of supervisor-subordinate relationships on organizational and
individual performance was investigated by researchers such as Varma et al. (2005), Varma et al. (2007). Azmi (2011) investigated the role of top management
as well as devolution vis-a-vis HRM in the Indian context. In case of external
agents, generally the focus of research has been on different forms of HR
outsourcing and cost benefit analysis of HR outsourcing (Seth & Sethi, 2011).
Keeping in view the significance of human resources in the success of an
organization, it is important to explore the role of key agents in people
management. Most researches have been undertaken in the western world and that
too primarily on devolution of HRM to line managers (e.g. Brewster & Larsen,
1992; Hall & Torrington, 1998; Schuler, 1992; Sparrow & Hiltrop, 1994; Storey,
1992). As a result of this, there are limited number of studies in this area. There is
no consolidated literature incorporating the study of all agents. Although some
studies have explored the role of agents in HRM but the focus remained on just
one of the agents. Thus, in the Indian context, this area remains Iargely unexplored,
barring a few exceptions (Agrawal, 2010; Budhwar, 2000a, 2000b; Budhwar &
Sparrow, 1997; Budhwar et al., 2006; Seth & Sethi, 2011; Srimannarayana, 2010).
Moreover, the focus of studies conducted in India remained mostly on single agent.
Thus, an investigation into the role of internal and external agents in HRM in the
Indian context is an issue that merits research attention.
1.4 Rationale of the Study
HRM is gaining increasing importance because employees are considered to be a
primary component for attaining competitive advantage (Barney & Wright, 1998).
6
With the changing economic scenario and rising challenges in the business
environment, the corporate world is fast realizing the worth of human resource as
an inimitable strength for attaining long-lasting competitive advantage. Human
resources constitute an important source of competitive advantage for the
organization (Wright & McMahan, 1992) and are the potential contributor to the
creation and realization of the organization's goals (Jackson & Schuler, 2000).
Consequently, the performance of human resource function has turned out to be
more important than ever.
Schuler (1990) pointed out that the status of HR managers has grown and as a
result of the growing importance of HRM, business organizations are realizing the
role of various other entities in HR related issues. According to Valverde et al. (2006), agents other than the HR department may be involved in the management
of people in organizations. These are both internal and external agents. Internal
agents includes top management and line management where as external agents
includes external service providers. Some researchers have argued that all
managers are people managers (Papalexandris & Panayotopoulou, .2005;
Whittaker, 1990) and the involvement of both internal and external agents in
carrying out the HR function is recognized in various studies (e.g. Budhwar,
2000a, 2000b; Budhwar & Sparrow, 1997; Finegold & Frenkel 2006; Gratton et al., 1999; Khatri & Budhwar, 2002; Mahoney & Brewster, 2002).
The shifting of traditional HRM responsibilities to line management have been
reported by different researchers (e.g. Larsen & Brewster, 2003; Renwick &
McNeil, 2002). Top managers are also increasingly getting involved in HRM as
they evolve strategies to attract, motivate, and retain the best talent in the
organization ((hung et al., 1987; Harper, 1993; Jonas et al., 1990). At the same time, HR outsourcing has also gained prominence of late, engendering a new genre
of research on the role of external service providers in HR (e.g. Banham, 2003;
Cook, 1999; Mahoney & Brewster, 2002). Of late, both internal and external
agents are seen to be participating in management of HR, albeit with differing
degrees of involvement. However, the focus of previous studies on HR has been on
traditional HRM activities and the role of different agents in HRM in particular has
been relatively under researched.
10
Studies on agents role in HRM usually focus on just one or at most two agents.
There are no studies incorporating the role of all agents (Valverde et al., 2006).
Additionally, the limited scope of previous studies has made it difficult to clearly
define the different agents in HRM and necessitates incorporating the scattered
viewpoints of researchers regarding the role of internal and external agents in HR.
Therefore, it is important to clearly define the role of key actors in HRM.
Although prior studies have recognized the key role of both internal and external
agents in HRM, yet there is limited empirical research on the role of these actors in
HRM and their relationship in operationalising an effective HR strategy
(Mayrhofer et al., 2004; Stanton et al., 2010; Teo & Rodwell, 2007). There are few
empirical evidences on the outcomes of roles of agents in HRM. Thus, there is no
clarity on impact of involvement of internal and external agents.
While the opening of Indian economy to world markets has attracted a large
number of foreign players to expand the scope of their businesses, global
institutions like the Word Bank have predicted that India will become the fourth
largest economy by 2020 (Budhwar & Varma, 2010). Consequently, it has
prompted top managers of business organizations to find out the nature of HR
practices existing in India, thus, driving the need to explore the role of internal and
external agents in HRM.
Although a number of studies have explored the involvement of internal and
external agents in HRM in India (e.g. Agrawal, 2010; Budhwar & Sparrow, 1997;
Seth & Sethi, 2011; Srimannarayana, 2010), the focus of these studies has
remained limited in nature. Furthermore, in the Indian context, the focus of the
research studies has remained on a single agent. There is no comprehensive study
incorporating the role of both internal and external agents. Besides, the impact of
the involvement of internal and external agents in HRM in India has remained
largely unexplored: Hence, research attention is required to uncover the prevailing
scenario. This gap in the extant researches in the Indian context has prompted the
need to explore the role of both internal and external agents simultaneously.
Thus, it can be safely asserted that there is dearth of empirical research that can
help the researchers and practitioners to understand the role of internal and external
agents in HRM in the Indian context. Therefore, the focus of the present study was
11
to explore the role of both internal (top management and line managers) and
external agents (HR outsourcing agencies or external service providers) in HRM in
the Indian context as well as to study the outcomes of these roles.
1.5 Research Objectives
The study endeavors to address the following broad objective:
To develop a reliable and valid instrument for measuring the role of top
management, line managers (i.e. internal agents) and external service providers
(i.e. external agents) in management of HR and to investigate the impact of their
role on the effectiveness of HRM and status of HRM. The study also seeks to
establish differences as well as association between organizational profile and
various dimensions of the above roles.,
The broad objective can be divided into four categories of sub-objectives:
Category I: Developing an instrument for measuring the role of internal and
external agents in HRM
•:• TQ develop a reliable and valid instrument for measuring various
dimensions of role of top management, line managers and external service
providers in management of HR.
Category II: Investigating the impact of role of internal and external agents in
HRM
(a) Investigating the impact of role of top management in HRM
•:• To investigate the impact of role of top management in HRM on the
effectiveness of HRM.
❖ To investigate the impact of role of top management in HRM on the status
of HRM
b) Investigating the impact of role of line managers in HRM
❖ To investigate the impact of role of line managers in HRM on the
effectiveness of HRM
12
❖ To investigate the impact of role of line managers in HRM on the status of
HRM
(c) Investigating the impact of role of external agents in HRM
❖ To investigate the impact of role of external service providers in HRM on
the effectiveness of HRM
•3 To investigate the impact of role of external service providers in HRM on
the status of HRM
(d) Investigating the impact of status of HRM on the effectiveness of HRM
•2+ To investigate the impact of the status of HRM on the effectiveness of
Category III: Assessing the differences between company type i.e. sector
(manufacturing and service) and company size (small, medium and large
organizations) on the role of internal and external agents in HRM
•S To assess differences in role of top management in HRM on the basis of
company sector (i.e. manufacturing and service).
❖ To assess differences in role of line managers in HRM on the basis of
company sector (i.e. manufacturing and service).
❖ To assess differences in role of external service providers in HRM on the
basis of company sector (i.e. manufacturing and service).
❖ To assess differences in role of top management in HRM on the basis of
company size (small, medium and large organizations).
❖ To assess differences in role of line managers in HRM on the basis of
company size (small, medium and large organizations).
❖ To assess differences in role of external service providers in HRM on the
basis of company size (small, medium and large organizations).
Category IV: Establishing, association between company type i.e. sector
(manufacturing and service) and company size (small, medium and large
organizations) with the role of internal and external agents in HRM
13
•3 To establish association between the role of top management in HRM and
company sector (i.e. manufacturing and service).
❖ To establish association between the role of line managers in HRM and
company sector (i.e. manufacturing and service).
❖ To establish association between the role of external service providers in
HRM and company sector (i.e. manufacturing and service).
❖ To establish association between the role of top management in HRM and
company size (i.e. small, medium and large organizations).
+ To establish association between the role of line managers in HRM and
company size (i.e. smalI, medium and large organizations).
•3 To establish association between the role of external service providers in
HRM and company size (i.e. small, medium and large organizations).
1.6 Significance of the Study
The study has both theoretical as well as practical significance. As far as
theoretical significance is concerned, the study has several contributions to make to
the existing literature. The present research tries to consolidate the existing
scattered viewpoints in the area. Further, a reliable and valid research instrument is
developed to simultaneously measure the role of internal and external agents in
HRM. This instrument can serve as a useful tool for future researchers in the area.
In the current study, the role of internal and external agents vis-a-vis HRM is
explored in the Indian context. The impact of involvement of these agents on status
and effectiveness of HRM is also explored. The findings of the study will guide
practitioners in understanding the present scenario of role of internal and external
agents in HRIVI in India. The findings may further aid them in understanding how
these roles impact the overall functioning of human resource management
departments. In addition to this, the study also addresses the specific differences
and association between company type viz, sector to which the company belongs
(manufacturing/service) as well as size of the company determined by number of
employees (small/medium/large) and the role of internal and external agents in
14
I
a
I
HRM. The findings are useful to determine specific HR process based on sector
and size of the organization.
1.7 Research Framework
The research outline followed in the current research is presented in Exhibit 1.1.
Exhibit 1.1: Research Framework
Preliminary Conceptualization
Literature Review
Research Gap
Identification of Research Constructs/Items
Instrument Development
Pilot Study
Primary Data Collection
Data Cleaning &Tabulation
Analysis
Reporting of Findings
Conclusions
Managerial Implications
Directions for Future Research
15
CHAPTER 2: REVIEW OF LITERATURE
2.1 Role of internal and External Agents in HRM: Brief
Overview
2.2 Role of Internal Agents in HRM
2.2.1 Role of Line Managers in HRM
2.2.1.1 Dimensions of Line Manager Roles
2.2.1.2 Line Manager Roles: Key HRM Domains
2.2.1.3 Rationale for Role of Line Managers in HRM
2.2.1.4 Role of Line Managers in HRM: Barriers
and Constraints
2.2.2 Role of Top Management in HRM
2.2.2.1 Dimensions of Top Management Roles
2.2.2.2 Top. Management Roles: Key HRM Domains
2.2.2.3 Rationale for Role of Top Management in HRM
2.3 Role of External Agents in HRM
2.3.1 External Service. Providers : HR Outsourcing
2.3.2 Dimensions of Human Resource Outsourcing
2.3.3 Human Resource Outsourcing: Key HRM Domains
2.3.4 Rationale for Human Resource Outsourcing
2.3.5 Human Resource Outsourcing: Barriers and
Constraints
2.4 Constructs to Measure Role of Agents in HRM
2.5 Alternate Variables to Measure Role of Agents in HRM
2.5.1 Performance Measures as Outcome Variables
2.5.2 Moderating Variables
2.5.3 Mediating Variables
2.6 Internal and External Agents in HRM: An Indian
Perspective
CHAPTER 2: REVIEW OF LITERATURE
Chapter Overview
This chapter provides a review of the existing literature on the role of internal
agents (line managers and top management) and external agents (external service
providers) in HRM. This chapter begins with a discussion of role of internal agents
in HRM. Thereafter, it elaborates on the role of external agents in HRM followed
by an overview of different constructs used to measure the above roles. Finally, it
gives an insight into the status of empirical researches undertaken on these roles in
the Indian context.
2.1 Role of Internal and External Agents in HRM: Brief Overview -
The rapid changes in the business environment have substantially transformed the
roles of the HR professionals as well as the way people are managed in business
organizations. In this context, Valverde et al. (2006) have recognized the
contribution of internal agents viz, line managers and top management and
external agents viz, external service providers in HRM.
Thus, it implies that agents other than the HR department may be involved in the
management of people in organizations. Primarily research talks about two
important categories of agents viz, internal and external agents.
Internal Agents: In today's organizations, role of internal agents have changed
and it continues to evolve with the changing needs of the organizations. Both line
managers and top management are seen to be participating in management of HR,
albeit with differing degrees of involvement (Valverde et al., 2006). Internal
agents include:
■ Line managers, who traditionally have been given responsibility for some
operational aspects of managing people, but whose role in HRM has
continued to increase (Hutchinson & Wood 1995; Keen & Vickerstaff,
1997; Perry & Kulik, 2008; Schuler, 1992; Storey, 1992).
16
■ Top management, who make strategic decisions (including HRM strategic
decisions), establish the organization's values and philosophy (Guest, 1997;
Lepak & Snell, 1999a; Schuler & Jackson, 1999) and influence its whole
approach to managing people (Stanton et al., 2010; Sisson & Storey, 2000).
External Agents: External agents include external HR service providers or HR
outsourcing agencies usually contracted by organizations to provide administrative
HRM services or professional, specialised HRM solutions (Cook, 1999; Young,
2000). The outsourcing of these activities has also been found to be on the increase
(Hall & Torrington, 1998).
Valverde et al. (2006: 618-9) opine strongly in favour of distributing FIRM
responsibilities across agents:
"The HR function is not understood simply as the set of activities performed by the HR department, but as all managerial actions carried out at any level regarding the organization of work and the entry, development and exit of people in the organisation so that their competencies are used at their best in order to achieve corporate. objectives............ In this sense, agents other than the HR department may be involved in the management of people in organizations".
Morley et al. (2006) noted that in recent times, more and more HR role is carried
out in the organizations through internal and external devolution. Internal
devolution involves transfer of HR responsibilities to line managers while external
devolution deals with outsourcing of HR activities to external contractors. The
concept of internal devolution is discussed in detail in sub-section 2.2 while
description of external devolution is provided in section 2.3. '
Several researchers have reported the role of internal agents viz. line managers and
top management (Brewster et al., 2004; Harris et al., 2002; Larsen & Brewster,
2003; Legge, 1995; Morley et al., 2006; Schuler & Jackson, 1999; Thornhill &
Saunders, 1998; Valverde et al., 2006) and external agents viz, external service providers (Delmotte & Sels, 2008; Klass et al., 2001; Morley et al., 2006;
Valverde et al., 2006) in HRM.
The focus of scholars on role of internal and external agents in HRM is mixed.
Generally, two types of studies are reported from literature viz, general studies on
sharing of HR responsibilities and secondly, studies on specific HR areas
(Casco'n-Pereira et al., 2006). The general studies talk about the role of agents in
1'1
• ___ _____________it of numan resources (Hall & Torrington, 1998; Sparrow et al.,
1994), while in case of specific studies role of agents in specific HR areas has been
explored (e.g. Currie & Procter, 2001; Dick & Hyde, 2006; McCarthy et al., 2010).
Various reasons are cited for the increasing involvement and participation of the
above agents in HRM such as emergence of flatter, organization structures,
changing division of labour, strategic integration, transaction costs, high quality,
flexibility and high commitment (Guest, 1989; Morley et al., 2006).
2.2 Role of Internal Agents in HRM
The involvement of internal agents in HRM is becoming a global trend. The role of
both types of internal agents viz., line managers and top management is growing.
Maxwell et al. (2004) identified the potential enablers of line managers'
involvement in HR activities such as top management support for HR, integration
of HR activities with organizational goals and benchmarking of HR.
Researchers in the area have reported that internal agents can be given more
control of HRM strategy by allowing their involvement in decision making at the policy formation level as well as developing strategic partnerships between HRM,
senior and line managers (Hall & Torrington, 1998; McCracken & Wallace, 2000),
The involvement of top management ensures that HRM is given due consideration
at top level and there is integration of HR policies and practices with the
organizational strategy. As HR polices cascade down, line managers become
important stakeholders in influencing how HR polices are interpreted and enacted.
revious research studies in the area suggest that the involvement of these two
roups of managers in HRM is critical to the effectiveness of HR (Currie &
'octer, 2001; Mayrhofer et al., 2004; Purcell & Hutchinson, 2007).
for literature also suggests that the role of internal agents in HRM is analysed on
lividual and separate basis (McCarthy et al., 2010). Moreover, research also
[icates that internal agents understand the important role of HR in helping their
anizations to gain competitive advantage (Papalexandris & Panayotopoulou,
'3). Research evidences reveal the positive implications of involvement of
:mal agents in HRM (Bond & Wise, 2003; Perry & Kulik, 2008). In addition to
, several potential benefits are linked with internal agents involvement such as
faster decision making (Budhwar, 2000a; Whittakker & Marchington, 2003), and
facilitating individual and organizational performance (Watson & Maxwell, 2007).
2.2.1 Role of Line Managers in HRM
During the last three decades, considerable changes have influenced the roles of
line managers when it comes to managing people. Line managers play an
important role in HRM, since they are expected to create a synergy between
human, financial and physical resources by allocating time, money and energy to
the development of their subordinates (Brewster & Larsen, 1992). A number of
research studies have indicated the significance of involvement of line and middle
managers in HRM (e.g. Qadeer et al., 2011; Nonaka, 1988; Smith, 1997). Transfer
of HR responsibilities to the line denotes that Iine managers should become more
involved in HRM so that HR staff can take on a greater strategic role (Finegold &
Frenkel, 2006; Legge, 1995; Sisson & Storey, 2000). Teo and Rodwell (2007)
reported the importance of line managers in operationalization of HRM goals and
further add that line or middle managers' involvement in HR processes and
activities release the HR managers from day-to-day functional roles.
Various descriptions have been used to explain the relationship between line and
HR managers such as "the filling-in-the sandwich" (McConville & Holden, 1999),
"partnership" (Hutchinson & Wood, 1995; Hall & Torrington, 1998), "piggy-in-
the-middle" (McConville, 2006), "linking pins" (Likert, 1961). In this context,
several researchers have used the term devolution and devolvement to define the
role of line manager in HRM (Brewster & Soderstrom, 1994; Conway & Monks,
2010; McGovren et al., 1997; Morley et al., 2006). The word devolution means
reallocation of personnel tasks to line managers (Armstrong & Cooke, 1992;
Brewster & Larsen, 2000; Cunningham et al., 1996; Storey, 1992, Thornhill &
Saunders, 1998). Morley et al. (2006) have used. the term internal devolution' to
describe role of line managers and argued that in case of internal devolution, line
managers should play larger role in policy development besides carrying out the
operational HR processes and activities.
The decentralization of HR responsibilities to the line is an important aspect of
strategic HRM. Line management has been viewed as increasingly taking HR
19
responsibility (Clark, 1998). In many organizations today, line managers carry out
activities which were traditionally performed by HR specialists. Line management
traditionally have been given responsibility for some operational aspects of
managing people, but their role in the HRM function has continued to increase in
the present times (Storey, 1992). According to Green et al. (2006), partnership
between FIRM and line is getting acceptance in business organizations.
As suggested by Casco'n-Pereira et al. (2006), two types of studies on devolution
can be identified: (1) general studies on HR areas being devolved (e.g. Budhwar,
2000a; Gautam & Davis, 2007; Hall & Torrington, 1998; Torrington & Hall, 1996)
and (2) specific studies focusing on one single area (e.g. Bond & McCracken,
2005; Cunningham & Hyman, 1995; Currie & Procter, 2001; Dunn & Wilkinson,
2002; Marchington, 2001; Redman, 2001). The general studies on devolution focus
on the HR functions that are devolved and provide an insight on how devolution
can be undertaken in terms of what middle managers do. The studies impinge on
the range of activities performed by middle managers in Iine function while the
specific studies focus on precise HR activities. Some of the specific HR activities
that have been explored by researchers include training and development,
recruitment and selection, industrial relations, pay and reward and performance
appraisal (Currie and Procter, 2001; Heraty & Morley, 1995; Hope-Hailey et al.,
1997; Redman, 2001; Wood, 1995). On the basis of existing perspectives, a
summary of characteristics of devolution is presented in Table 2.1.
Table 2.1: Characteristics of Devolution of HRM to Line Researchers Characteristic
Khatri (2000) Free information flow between HR and line Casco'n-Pereira et al. (2006) Devolvement of decision-making power
, Green et al. (2006) Partnership between HRM and line Green et al. (2006) Identification of HR problems done jtly Nixon and Carroll (1994) Developing soft skills among line managers
Mayne and Brewster (1995) Devolvement is driven by both organizational and effectiveness criteria
Budhwar and Sparrow (1997), Harris et al. (2002) Line managers given training in HRM
Budhwar and Boyne (2004), Budhwar and Sparrow (1997), Brewster and Larsen (2000), Wood (1995)
Transfer of responsibility for HRM to line
Source: Prepared by the Researcher
20
One of the major changes in HRM that affect the line managers is the advancement
of technology. The growth in the field of information technology can simplify HR
processes and deliver HR advice and services to the line managers (Papalexandris
& Panayotopoulou, 2003). Renwick & McNeil (2002) noted that the use of
information technology tools have made it possible for line managers to deal with
some HR tasks without the assistance of the HR department, while in software
industry line managers perform all the HR tasks on their own (Brewster & Larsen,
2000). Qadeer et al. (2011) have presented a detailed review of the relevant
literature in the area and identified the supports and barriers for the tine managers
to take on HR responbilities.
2.2.1.1 Dimensions of Line Manager Roles
Hall and Torrington (1998) studied the distribution of HR tasks between personnel
specialists and middle managers. They found evidence of devolution of day-to-day
personnel matters to line managers in UK. Valverde (2001) compared the
contribution that the different HR agents make to the HR function. Findings of the
study show middle managers' involvement in operational level HR decisions and
daily people management activities such as identifying training needs, carrying out
performance appraisal and service delivery functions such as acting as trainers or
interviewing candidates in a selection process.
Watson and Maxwell (2007) on the basis of case study evidence, argued that line
managers' knowledge on the basis of their involvement in HR tasks may improve
their performance in HR activities. Cascon-Pereira et al. (2006) identified the tasks
that are devolved and degree of devolution along a number of dimensions.
Cunningham and Hyman (1995) studied the changes in employee relation practices
in UK and found that the organizations are adopting both hard and soft approaches
for managing people as a result of which line manager are experiencing significant
changes in their role.
Storey (1995) proposes that line managers should be closely involved as both the
deliverers and drivers of HR policies. Gennard and Kelly (1997) concluded that
with the emergence of SHRM, the line-personnel relationship has changed. The
third Workplace Industrial Relations Survey (WIRS 3) puts forward that line
21
managers were spending more of their time on HR activities during 1980s
(Millward et al., 1992).
Cunningham and Hyman (1999) reported that many organizations are increasingly
devolving personnel responsibility to line managers. This has been attributed to
growing competition. The study finds that devolved responsibilities of personnel
are formally geared to securing commitment from employees by promoting an
integrative culture of employee management through line managers. Renwick
(2000) pointed out that both costs as well as benefits are associated with the
involvement of line managers in HRM. The benefit includes willingness and
flexibility of line managers to take on increased responsibility in HRM and feel it
as a career-enhancing work, while organizational costs involve the line feeling
under pressure to complete HR tasks owing to their involvement in HRM.
Bond and McCracken (2005) drawing on case studies research in four financial
sector companies in Scotland proposed a model for line manager decision-making
for dealing with requests for time off at short notice. The model outlined the
important factors such as extent of devolution, company polices, type of
emergency, operational constraints and employee commitment that effect the line
managers decisions and leads to good and poor decision-making. However, these
factors are mediated by line managers' common sense or tacit knowledge in
dealing with these areas.
Kulik and Bainbridge (2006) found evidence of a trend within Australian
organizations to devolve people management activities to the line. Results revealed
that human resource managers and line managers have different views of the trend,
with HR managers being more optimistic that the trend has had positive
organizational outcomes and anticipating more devolution to occur in the future.
Hutchinson and Purcell (2010) analyzed the human resource management
responsibilities of ward managers and paramedic supervisors in NHS trust. The
results of the study reveal that the roles of these front-line managers have been
enlarged without support from senior managers and the HR function due to which
issues of role conflict and ambiguity, heavy workloads and stress increased.
Whittaker and Marchington (2003) explored the relationship between line
managers and their HR counterparts. Findings of the study reveals that line
22
managers are satisfied with the support they receive in performing the devolved
HR responsibilities and are keen to take on the responsibilities that are explicitly
related to the development of their team. Most line managers report working
closely with their HR counterparts. Cantrell and Miele (2007) report that line
managers are now involved in various people management activities like staff
planning, recruitment, performance management, staff development, pay, career
development and communications.
Harris et al. (2002) studied the transfer of HR responsibilities in regulated
environment in UK public sector organizations and revealed that line managers and
HR specialists shared the responsibility of effectiveness and long-term
sustainability with respect to increased regulatory environment. Larsen and
Brewster (2003) reported that the HR tasks are increasingly transferred to line
managers but the degree of involvement in such tasks differs across European
nations.
Hsu & Leat's (2000) study indicated the role of line managers in HRM decision-
making. They revealed that line managers are influential in decision-making
regarding training and development, recruitment and selection and workforce
expansion and reduction. Conway and Monks (2010) analyzed the impact of
organizational restructuring on the devolution of HRM to middle managers in the
Irish health service. Results of the study pointed out that increased layers of
bureaucracy brought about by the centralisation process create problems of
decision-making by HR and middle managers.
Storey (1992) proposed a typology of senior and middle line managers which
provides insights about the role that line managers can adopt in organizations. Two
key dimensions of line managers' role is identified which is integrated in a matrix.
The first dimension reveals the extent to which a manager is commercially or
technically oriented. The second dimension measures the degree to which a
manager takes proactive or reactive decision. The integrated matrix presents four
types of line managers i.e. Production manager, Manufacturing manager, Business
manager and Sales manager.
The typology presents the responsibility for HR will vary according to the role that
line managers will perform. Production manager is the traditional interpretation of
23
the role. Thus it is. likely that training and development responsibilities would
largely be the remit of the specialists in this situation. The manufacturing managers
actively seek to find innovative ways. This type of line managers are more
generalists, they have greater responsibility and they undertake a wide range of
tasks.Under this typology, HR responsibility could be expected to be shared
responsibility between the specialist and the manufacturing manager. The business
manager has an awareness of the total organization and how it fits within its wider
environment. Here, HR might again be a shared responsibility, but in this the line
assumes the greater ownership. The fourth type of line manager is the sales
manager. This type of manager continues to operate in a reactive environment but
shifts in orientation from technical aspects of production to commercial aspects.
While conceptually possible, Storey (1992) found little evidence of this type of line
manager. The above typology of Storey (1992) is depicted in Exhibit 2.1
Exhibit 2.1: Typology of Line Manager Roles
Proactive
Business Manufacturing Manager Manager
Commercially oriented
Sales Administrative
Manager Manager
Technically oriented
Reactive
Source: Adapted from Storey, J. (1992). Developments in the management of human resources. Oxford: Blackwell.
24
Tulgan (2001) remarks that line manager roles in learning and development at
work matters in the milieu of boundery-less careers. There are five non-monetary
factors that are relevant to the boundry-less careers, where the career paths
followed by people are no longer restricted to old pathways in one organization or
one area of work:
■ When they work — offer relief from gruelling schedules.
■ Where they work —the options of elements of home working.
• What they do — downshifting as well as career advancement.
• Who they work with — the quality of networks and teams.
• What they are learning — not just for performance, but also for employability.
Gibb (2003) carried out a study on line manager involvement in learning and
development at work. The benefits of increasing line involvement in learning and
development at work is negated by the disadvantages in involving line manager.
The study presented two explanations in the form of a continuum to justify the
trend of line manager involvement in learning and development at work. The first
continuum plots significance of line managers' involvement from minimal to
profound significance. The second continuum addresses the question of whether
devolution is aligned with control or commitment systems.
According to minimal significance perspective greater line management
involvement in learning and development is simply an extension of conventional
management control. On the other hand, profound significance supports the shift to
commitment systems with the re-invention of management that involve the growth
of new HRM practices. The study concluded that although there are apprehensions
about greater line involvement in Iearning and development at work which is
negated by the greater anxiety to reaffirm work organization and management in
an era of knowledge management.
Exhibit 2.2 presents the typology of different perspectives that can be used to map
the role of line manager as developers. As evident from Exhibit 2.2, there are
levels of correlation between line manager and the employer as descriptions of
roles and careers for management change with changing organizational contexts.
0461
Exhibit 2.2: Mapping Perspectives on Line Managers as Developers (LMaD)
Sceptical Perspective
Greater LMaD is Greater LMaD is inappropriate due to inappropriate as need is
organizational change for L&D specialists
Escalating Analysis
Greater LMaD is needed Greater LMaD is needed to achieve organizational to deal with L&D more
change effectively
Championing Perspective
Source: Adapted from Gibb, S. (2003). Line manager involvement in learning and development Small beer or big deal? Employee Relations, 25(3), 289
Casco'n-Pereira et al. (2006) identified the following dimensions of devolution:
a) tasks/responsibilities b) decision-making power c) financial power and d) expertise power
The authors assessed the transfer of each of these dimensions in each personnel
area. It is presumed that these four dimensions are likely to play a role in HR
function's devolvement to line managers. As some studies suggest, the reality of
devolution is not simple and the transfer of HR functions to middle managers
appear in a great variety of forms, not only in terms of different HR areas or
activities but also in terms of different degrees — tasks, knowledge and expertise,
financial power and decision-making power. The devolution of each of these
dimensions may have a distinctive impact on middle managers perceptions.
McGuire et al. (2008) concluded that commercialization of the public sector has
led to the enhanced staff performance and in this context the role of line managers
become imperative. Exhibit 2.3 presents a framework for Iine managers' HR
involvement, the success of which depends on striking a balance between factors
favoring devolvement and those inhibiting HR involvement.
Exhibit 2.3: A Framework for Line Manager-HR Involvement
Enablers of line manager HR involvement • Greater degrees of responsibility & task variation • HR information systems • Close relationships with employees • Formation of strategic partnerships
Public sector change driven by: • Commercialisation Line manager Degree of change • High quality service involvement in experienced in HR
delivery HR process processes & quality • Greater financial and of service delivery
public accountability • Cost rationalisation
Inhibitors of line manager HR involvement • Lack of training & support • Excess Workload • Short-term priorities surpassing long-term
development initiatives • PoIitical pressures
Source: Adapted from Mcguire, D. Stoner, L. and Mylona, S. (2008). The role of line managers as human resource agents in fostering organizational change in public services. Journal of Change Management, 8(1), 73-84
In order to illustrate the divergent view points of the researchers regarding the role
of middle managers in strategic change, Floyd and Wooldridge. (1992), (1994),
(1997) and Wooldridge and Floyd (1990) have developed a typology that helps us
to recognize the role of middle managers to the realization of strategy and the
conditions necessary for this to take place. The framework is outlined in Exhibit
2.4 and it reveals the upward and downward influence of middle managers in the
strategic change process allowing for a consideration of an enhanced role of
middle or line managers in acting as change agents for employees.
27
In upward influence, middle managers are engaged in `championing alternatives'
and `synthesising information' roles. In championing alternatives role, middle
managers conceive business opportunities that fall outside an organization's
current concept of strategy. In their synthesising information role, middle
managers also supply executive management with information about emerging
issues, e.g. internal or external developments, and events and trends viewed as
consequential to the organization. In doing this, middle managers serve an
important role in identifying strategic issues. In downward influence, middle
managers carry out the roles of `facilitating adaptability' and `implementing
deliberate strategy'. Middle managers may stimulate emergent strategic change
from employees which may not be anticipated in the deliberate strategy set out by
executive management.
Exhibit 2.4 Typology of Middle Manager Influence
Behavioural Activity
Upward Influence Downward Influence Divergent
Championing Facilitating Strategy Adaptability
Cognitive Activity
Integrative Synthesising Information
Implementing Deliberate Strategy
Source: Adopted from Floyd, S. W. and Wooldridge, B. (1992). Middle management involvement in. strategy and its association with strategic type: A research note. Strategic Management Journal, 13, 153-167.
2.2.1.2 Line Manager Roles: Key HRM Domains
A number of scholars have carried out studies dealing with specific areas of HR
devolution. For instance, Marchington's (2001) and Fenton-O'Creevy's (2001)
studies of middle managers attitudes towards employee involvement, Redman's
(2001) study about devolvement of performance appraisal function, Currie and
28
Procter's (2001) work on the area of pay and Dunn and Wilkinson's (2002) study
in the area of absence management.
Bond and Wise (2003) carried out a study to know the familiarity of line managers
in executing the legal and company family leave policies as well as the training
support provided to them. The result obtained from the case studies of four
financial sector organizations found that line mangers' training on the above stated
area is limited, as a consequence of which, HR specialists' role is to provide
information and training to line managers for effectiveness. Heraty and Morley
(1995) carried out a study to find out the issues involved in devolving training and
development to line and the resultant consequences. The result of the study
concluded that there is evidence of devolvement of operational issues and concerns
but it found little evidence of devolvement of strategic issues like policy
development. Factors such as importance of the activity from a strategic
perspective, the issue of ownership, differing perspectives between line managers
and specialists and the organizational support for Iine managers to conduct training
and development activities in a competent manner were responsible for complete
devolvement to the line.
Rockart (1988) found that the growth in information technology has increased the
business opportunities so is the role of line managers in system formation and
execution. Siugzdiniene (2008) points out that as organizations are striving to
make HRD function leaner and more strategic; line managers are increasingly
becoming responsible for performing HRD activities in order to facilitate
employee learning and development. The increased expectation about line
managers' role in HRD has necessitated substantial investments in capacity
development of line managers. Study by Industrial Relations Services (1994) found
different perceptions depending on the different HR areas devolved. In this study it
was found that line managers would be most likely to have responsibility for issues
related to departmental performance and least responsible for issues that required a
singular stance and homogeneity of policy.
Andolsek and Stebe (2005) studied the influence of organizational characteristics
(size, age, numerical flexibility, HRM strategies, HRM policies) and situational
factors (sector, state) on devolution of HRM in five European countries. The focus
of the study was on the following HR areas: recruitment, pay, training, industrial
29
relations and workforce reduction. The results of the study revealed that devolution
is dependent on external institutional factors and institutional environment is the
main factor that encourages or limits the devolution.
Renwick and MacNeil (2002) studied the role of line managers in developing
employee careers, the change that is expected from them and the impact of such
changes on their careers. It was concluded that in the competitive business
environment, line mangers are Iooking for the ways and means to enhance the
performance of their employees as well as their own performance in both problem
solving and goal achievement.
Watson and Maxwell's (2007) study focused on the areas where line managers are
involved in HRD activities, their knowledge of HRD roles and responsibilities and
the underlying difficulties they face in discharging such activities. Findings reveal
that line manager through assistance from HRD professionals have started
adopting HRD roles.
Wood (1995) measured line management responsibility focusing specifically on
selection. Respondents were asked if in their plant line management takes
responsibility for initiating and carrying out their own selection, with personnel as
a support. Selection was chosen as the focus because of its centrality to personnel
management. Moreover, it is likely to be the first element in any delegation of
personnel matters to line managers.
Gautam and Davis (2007) studied the devolvement of pay and reward, recruitment
and selection, training and development, industrial relations and workforce an
increasing line management responsibility for the above stated HR areas. MacNeil
(2003) explored the role of line managers in facilitating creation and transfer of
tacit knowledge in teams as well as the barriers concerning the transfer of tacit
knowledge between individuals and teams and finally emphasized the importance
of developing line managers as facilitators. MacNeil (2003) highlighted that as
competitive business pressures results in centralized structures, flatter management
layers, adoption of team-working processes and employee empowerment, line
managers offers key role in contributing to strategic HRM outcomes by
encouraging knowledge sharing in teams. Table 2.2 presents a summary of key HR
domains explored by researchers in this area.
30
Table 2.2: Key HR Domains vis-a-vis Line Manaaer Roles HR Domain Researchers
Employee engagement Marchington (2001), Fenton-O'Creevy's (2001) Identification of training needs Green et al. (2006), Watson et al. (2007) Performance appraisal Redman (2001), Andersen et al. (2007) Counseling Nixon and Carroll (1994) Compensation Currie and Procter (200I), Hoe-Haile etal. (1997) Absence management Dunn and Wilkinson's (2002) Legal and family leave policies Bond and Wise (2003) Training and development Heraty and Morley (1995) System formation and execution Rockart (1988) Employee learning Siu zdiniene (2008) Knowledge management MacNeil (2003) Career management Renwick and MacNeil (2002) HRD Watson and Maxwell (2007) Industrial relations; health & safety Hope-Hailey etal. (1997) Recruitment & selection Hope-Halley et al. (1997), Wood (1995) Workforce expansion & reduction Kramar and Lake (1998) Managing change Cunningham and Hyman 1995) Reward management Brown and Purcell (2007) HR planning, recruitment, selection Srimannarayana (2010) Recruitment, pay, training, industrial relations and workforce reduction
Andols`ek and Stebe (2005), Gautam and Davis (2007)
Quality circles, appraisal, discipline, staffing levels, empowerment, team briefing, recruitment and dismissal
Cunningham and Hyman (1995), Hall and Torrington (1998)
Source: Prepared by the Researcher
Hope-Hailey et al. (1997) have found that Line-HR responsibilities differ according
to the specific HRM area. The HR function, for example, may still retain certain
areas such as IR, pay and benefits, organizational health and safety, recruitment
and selection whereas line managers take more responsibility for work force
expansion and reduction (Hope-Halley et al., 1997; Kramar & Lake, 1998).
2.2.1.3 Rationale for Role of Line Managers in HRM
The concept of shared responsibility for HRM by both line management and HR
specialists is being recognized within the literature and there is constant debate
about the same. A number of reasons are cited about the same ranging from the
requirement for speed, adaptability and flexibility of HRM offerings in dynamic
and changing environments (Renwick, 2000), the plan of cost reduction, increased
31
utilization of HR capital (Budhwar, 2000a, Renwick, 2003) and the adherence of
SHRM philosophy of integrating HRM policy and practice with the needs of
business (Ulrich & Brockbank, 2005).
Positioning the HRM responsibility at a local level through line management
provides managers the opportunity to be directly involved in the HRM issues
affecting their own staff and department. The logic behind this rationale is that an
employee's line managers may be more properly placed to interact, translate and
disseminate HR policy and practice to bring out commitment and performance
(Larsen & Brewster, 2003; Renwick, 2000). The reallocation of HR responsibilities
results in motivating employees through nurturing effective control as line
managers are in regular contact with the employees. In addition to this the
reallocation of HR function to line managers has a positive effect on organizational
performance (Harrison, 2005). Gibb (2003) has associated devolvement with
increase in quality at work, development of a wide range of people related
capabilities, alignment of HRD with broader organization's strategic goals and
transformation of managers as better people managers.
With the line managers assuming an increased role in the transactional delivery of
people processes, HR managers may be released from this task thus, enabling them
to focus on strategic value adding activities (Cunningham & Hayman, 1999). The
decision to devolve HRM to line management may increase the speed of decision-
making on HRM issues as evidenced in the findings of Larsen and Brewster (2003)
and Renwick (2000). Their studies established that devolution may limit the
repetition of effort within HRM delivery and reduce financial costs through
reducing headcounts of HR and by enabling them to focus on strategic value
adding activities as opposed to those of a transactional nature.
Research findings on the extent of devolution to the line have been mixed
(Brewster & Larsen, 2000; Budhwar, 2000b; Harris et al., 2002). However, a
number of studies support the positive impact of devolution on different measures
of organizational performance. Participation between HR and line helps , in
enhancing organizational performance (Gennard & Kelly, 1997; Guest, 1987;
Thornhill & Saunders, 1998). Budhwar (2000b) revealed the positive implications
of the devolvement of HRM to line managers on a firm's performance.
32
0-
Renwick (2003), based on interviews with line managers on their experiences in
handling HR work that has been devolved to them in three different work
organizations located in UK, found that significant organizational benefits exist
from involving the line in HR work like. -line willingness and flexibility to take on
increased responsibility and accountability in HR work. Adams' (1991) research
indicated that innovations in HR occurred where personnel is decentralized to line
managers.
Andersen et al. (2007) revealed that strategic integration and devolvement of HRM
is accomplished to a fair level in the organizations and the amount of configuration
of HRM with business objectives and strategies is associated with firm
performance. In this context, line management training in HR practices had an
optimistic association with firm performance. The condition of HRM in Australian
organizations can be improved by enhancing training and support of line managers
in the devolvement of HR practices.
Hutchinson and Purcell (2003) indicated that line manager involvement in
coaching, guidance and communication positively influences organizational
performance. Mcguire et al (2008) found that devolvement of HR responsibilities
to line managers has enhanced the public services as well as improved employee
performance as a result of swiftly dealing with the workplace problems and faster
decision-making.
Dopson and Stewart's (1990) and Kanter's (1982) studies revealed that an
organization's competitive advantage will increasingly depend on the degree to
which middle managers have a greater input into the strategy and policy arena.
Middle managers make vital contribution to organizational performance (Currie &
Proctor, 2005; Floyd & Wooldridge, 1994, 1997; Huy, 2001). Hutchinson and
Purcell (2010) on the basis of case study research in NHS trust reported that front-
line managers are important to the delivery of effective HRM and thus strongly
influence organizational performance and service delivery.
Research studies have stressed the importance of organization of HRM within the
company in order to improve the organizational performance (Brewster et al.,
1997; Budhwar & Sparrow, 1997). In this context, the main features of HRM
organization as highlighted in different studies includes integration of HRM and
33
business strategy (Boswell, 2006; Truss & Gratton, 1994) and distribution of roles
and influence of HRM specialists and line managers (Andolsek & Stebe, 2005;
Hall & Torrington, 1999). Results of the Dany et al. (2008) study pointed out the
moderating impact of distribution of roles and influence between HRM specialists
and line managers on the link between HRM integration and organizational
performance. Further, the results reveal that level of integration and distribution of
roles and influence between HRM specialists and line managers has positive
performance implications only in particular situations.
Brown and Purcell (2007) study reported the positive impact of line manager
involvement in reward management on organizational performance. Many
researchers have indicated that line participation and decision-making in HR
activities helps in enhancing organizational performance (Azmi, 2010; Gennard &
Kelly, 1997; Guest, 1987; Thornhill & Saunders, 1998). Line manager
involvement in communication, guidance and coaching, positively influences
organizational performance (Hutchinson & Purcell, 2003). Purcell and Hutchinson
(2007) reported that front-line managers act as agents in the HRM performance
chain and the quality of leadership behaviour and satisfaction with HR practises
have a strong effect on employee attitudes. Mitsuhashi et al. (2000) analysed the
line and HR executives' perceived effectiveness and importance of HR
departments. The results of the study revealed the differences between the
perceived effectiveness of the entire HR function as rated by HR and line
" - executives.
2.2.1.4 Role of Line Managers in HRM: Barriers and Constraints
There is a clear difference between the rhetoric of devolution and what actually
happens in practice (Casco'n-Pereira et al., 2006). Although there is evidence of
increased line involvement in the management of human resources, there is still
some resistance to the uptake of HR responsibilities at the line level (Cunningham
& Hyman, 1995, 1999; Currie & Procter, 2001; Poole & Jenkins, 1997; Renwick,
2000). Cunningham and Hyman (1995) pointed out that organizations are finding it
difficult to transfer the HR vision of senior management down to the line since line
managers lacked the necessary skills as well as resources. Further, Cunningham
M
and Hyman (1999) reported that many organizations have devolved personnel
responsibility to line managers as a result of restructuring of personnel activity but
line managers are not satisfied with the training provided to them by personnel
department to deal with HR matters. Tensions exist between line managers and
personnel and the function appears to be vulnerable to further contraction.
There is still some concern that several barriers remain to the adoption of general
joint arrangements. Within the process of devolution, the configuration of
responsibilities is still to be resolved (Renwick, 2000). Marchington (1999) has
explained that leaving too much to the line may result in inattention and
inconsistencies in approach and retaining too much control with HR runs the risk
that problems will not be dealt with using an appropriate business focus.
McGovern et al. (1997) reported in their study that line managers are disinclined in
taking HR tasks viewing it as illogical. As a consequence of this, HR departments
are hesitant to transfer responsibilities to line owing to their knowledge, skill and
capability to bear these tasks. Renwick (2003) pointed out that devolution involves
significant organizational costs like the line feeling under pressure to complete HR
tasks amongst other duties and not seeing themselves as experts in HR work.
Harris et al (2002) too concur with this view and point out that lack of specialist
knowledge among the line managers was a hurdle in performing HR tasks
effectively in the UK. Francis and Keegan (2006), Purcell and Hutchinson (2007)
and Renwick (2000) pointed out that line manager involvement in HRM needs
substantial improvement.
Thornhill and Saunders (1998) have argued that the absence of a designated human
resource specialist role actually results in quite negative consequences where the
scope for strategic integration is significantly impaired. Line managers may resist
empowerment initiatives and fail to see the benefits of the changes. McConville
(2006) reported that apprehensions do exist regarding the new role of line
managers. The study suggests that middle managers intention to be proactive in
HRM enhances their role but adds substantial workload as a result of which
problems inflate. As a result, counseling line managers may be important since
driven by budgetary pressures, line managers generally choose to concentrate more
on production matters (Armstrong, 1998; Cunningham & Hyman, 1999). On the
35
other hand, HR specialists consider that line managers may not have the skills to
take on personnel responsibilities effectively (Torrington & Hall, 1996).
Several scholars found that authority to make final decisions on HR by line was
missing (e.g. Armstrong, 1998; Cunningham & Hyman, 1995; McConviIle &
Holden, 1999; Patton, 2003). Schuler and Huselid (1997) consider HR-line
partnership is not happening in all companies. Hope-Hailey et al. (1997) concluded
that devolution to line remains problematic. .
It has been noted that little has changed in the inimical attitudes of Iine
management towards personnel (Legge, 1978). Many researchers have reported
low degrees of devolution (Cunningham & Hyman, 1995, 1999). There has been
Iittle training of line managers dealing with HR issues (Renwick, 2003).The ability
and willingness of line managers to carry out HR tasks remains a challenge (Bond
& Wise, 2003; Currie & Procter, 2001). Hall and Torrington (1998) point to
making sustained efforts to vest HRM responsibility with line. Watson et al.
(2007) observed that reducing the workloads of line managers and good relations
with HR are means to develop greater devolution. Line managers should be given
more decision-making power (McCracken & Wallace, 2000).
In this context, McGovern et al. (1997: 26) concluded:
"the prospects for full-blown devolvement to the line are not promising given the current priorities of these businesses. Attempts to devolve HRM to the line may be possible but only if accompanied by increased monitoring on the part of the HR specialists".
Rather than devolution of responsibilities, what is in fact needed is a partnership
between HR and line managers as suggested by Currie and Proctor (2001). Kinnie
(1990) studied - the multi-dimensional aspect of devolution and argued that
devolving authority necessarily involves devolving decision-making capacity in
financial terms. McConville and Holden (1999) opine that if associated budgets are
not devolved along with the responsibilities and tasks then what is being devolved
is actually a liability.
Armstrong (1998) adds that if authority involves personal influence arising from
knowledge or position then the devolution of expertise must be another dimension
of devolution. The devolution of expertise extends devolving not only the tasks but
the skills and knowledge to perform these tasks. Given the critical role of
36
counseling, (Nixon & Carroll, 1994) managers need to develop their counseling
skills to turn out to be completely successful in their management roles. Gennard
and Kelly (1997) have suggested that extensive participation between HR and line
managers can create mutual benefit for both as they jointly contribute to solve
business problems. Hence, organizations need to undertake a thorough examination
of factors that enable successful adoption of devolution.
2.2.2 Role of Top Management in HRM
Globalization has ushered a new era in business world where national boundaries
become irrelevant and organizations are competing with each other across border
(Ansoff, 1991). In a knowledge driven global economy, it is intellectual and social
capital rather than natural resources, financial or physical capital that is the key
source of competitive advantage (Fine gold & Frenkel, 2006).
In the face of this increasing international competition, Beer et al. (1984) stressed
the need to focus on the value of investments in human resources as it provides a
major source of competitive advantage. It is important for the top.. managers to
evolve strategies to attract, motivate, and retain the best talent in the organization.
Researchers in the area of HRM have contributed a significant amount of literature
on the role and the job of top managers in an organization vis-a-vis people related
issues (Chung et al., 1987; Harper, 1993; Jonas et al., 1990). Valverde et al. (2006)
reported the contribution of top management in HRM. They indicate that top
management make strategic decisions (including HRM strategic decisions),
establish the organization's values, goals and philosophy and influence its
approach and ideology to managing people. As a result of this, top management
have been identified as an important agent in HRM.
On the basis of empirical analysis Valverde et al. (2006) found evidence that top
management is involved in variety of HR activities at different levels of HRM
decision-making ranging from operational decision making, daily people
management to a smaller degree even in administrative and technical activities.
Researchers in the area have recognized the contribution of senior management in
developing and implementing the strategic direction of the HR function (Guest
1997; Lepak & Snell 1999; Macky & Boxall, 2007; Stanton et al., 2010).
37
2.2.2.1 Dimensions of Top Management Roles
Studies in the field of HRM have reported the role of top management in the
management of people in organizations (Finegold & Frenkel, 2006; Storey, 1992;
Valverde et al., 2006). Recent research has examined the importance of the chief
executive officer, top management team and board of directors as strategic assets
(Fisher & Dowling, 1999). Hambrick and Mason (1984) term it as the upper-
echelon. The upper echelons contribute to the firm's awareness of the competitive
environment. The top management team comprises of key functional heads where
top executives play a key role in selecting, training, evaluating, and rewarding their
immediate subordinates. -
The influence of top management on HRM policies and practices is acknowledged
by several writers (Heneman et al. 2000; Khilji, 2002; Tsui & Milkovich, 1987).
Upper echelons notion also make out that certain traits of top managers may be
related to firm performance (Hambrick & Mason, 1984). Khilji (2002) recognized
the pivotal role of top managers in modifying the HR image of their organizations.
Top managers should offer transformational leadership by sharing their vision with
employees. An HR function that is perceived by key actors in the corporation to
have a high degree of reputational effectiveness is more likely to succeed in
enacting strategic roles. Top management is recognized as the most powerful force
facilitating HRM and serve as a key to attain and sustain competitive advantage
(Porter, 1991; Tracey, 2002).
Finegold and Frenkel (2006) conducted a study in eight biotech firms of USA and
Australia and cited a number of factors that are responsible for top management
involvement in people management. Generally four approaches viz, no in-house
HR, tactical HR, strategic HR and hybrid: evolving from tactical to strategic HR,
are followed across these eight firms depending on the size of the firm and
financial resources available with the firm. It was found that in knowledge driven
industries, top management plays a key role in people management and are directly
or indirectly involved in a number of HR related tasks in their organizations.
Kirkpatrick & Locke (1991) reported the executive human resource management
responsibilities of CEOs are vital because having the right managers in place has a
real impact on organizational performance. Senior managers who are ineffective
38
can keep a company from reaching its goals (Finkelstein, 1992). Novicevic and
Harvey (2001) speak out that the top management has to look for suitable ways to
generate a sustainable competitive advantage through HR efforts. Thornhill and
Saunders (1998) reported the role of top manager in establishing the organizational
structures that support adaptability and policies to promote optimistic employee
relations.
Sheehan (2005) reported that the role of the CEO is crucial in the realization of
expected HRM outcomes. Examples of such roles include decision to make HR a
part of the senior committee and direct HR reporting relationship to the CEO.
Moreover, CEOs involvement ensures that all these activities receive due
consideration and present an integrative approach to HRM. Various researchers
(e.g. Golden & Ramanujam, 1985; Lawler et al., 1995) have also argued the
importance of direct access to the CEO through a formal reporting relationship.
Sparrow and Marchington (1998) pointed out the importance of informal
interaction of HR managers with senior management executives and the
association that is developed between them. Exhibit 2.5 presents the proposed
influences on strategic HRM integration.
HKm integration Extlibit Z.5: F'roposed influences on u-
Organizational Recognition Responses of the need to apply • HR representation at the strategic HR senior committee level principles • Direct HR reporting
relationship to CEO 4 Increase in line managers
HR responsibilities
Expected Outcomes
• FuIl integration of HRM with business strategy
• Integrated HR policy design • Integration of HR
responsibilities within line management activities
Moderating Influences
• HR manager's commitment to strategic HR initiatives
• HR manager's commitment to business values
• Business acumen
• Top management commitment to HR initiatives
• Corporate culture commitment to HR initiatives
Source: Adapted fror Sheehan, C (2005). A model for HRM strategic integration. Personnel Review, 34(2),192-209.
Researchers in the area of HRM (Budhwar, 2000a; Kane et al., 1999) have
recognized the role of top management direction and support as an important
determinant of HRM success. In this context, analysts have mentioned the
importance of direct access to the CEO through formal reporting relationship
(Golden & Ramanujam, 1985; Nininger, 1980). Welbourne and Cyr (1999)
revealed the role of CEO in developing the competence of employees. Buyens and
De Vos (2001) recognized the importance of HR function in translating the
business strategies and top managers' perceptions of HRM. Further, reported that
integration of HRM with business strategies was comparatively higher in the
organizations where top management considered employees as strategic assets.
Brown and Purcell (2007) opined that senior management is involved in
development of reward strategy and final approval of rewards to employees.
Martell and Carroll (1995) conducted a study in specific firms affiliated with
Fortune 500 companies on the role of the top management team in executive
human resource management vis-a-vis organizational performance. Organizational
performance was considered as dependent variable where as executive human
resource management practices (i.e. staffing, compensation, performance appraisal
and training) were considered as independent variable and strategic business unit
competitive strategy (using Michael Porter's generic strategies) was a control
variable. The results revealed in the light of the role of top management several
executive human resource management practices associated with firm
performance.
Truss et al (2002) presented the results of a longitudinal study conducted between
1992 and 2000 within two organizations viz. Chelsea and Westminster NHS trust
and Citibank, an investment bank. In both organizations, the study reveals the key
role of senior managers in influencing the HR department's role. In case of Trust,
the chief executive owed a place for HR director as well as was made a member of
the Trust's strategic executive group to discuss strategic HR issues where as in
case of bank similar type of role is played senior managers.
Based on the findings of the study, a model is presented in Exhibit 2.6 to extricate
the different factors that control the HR department's role. In the model various
organizational environment factors are presented which have an impact on HR
department's main role set members viz. senior managers and line managers. The
40
signals sent to the HR department regarding the role to be played which in turn
affects the resources allocated to the function. Further, within the HR department
certain attributes and behaviour are differentiated and finally the output is in the
form of HR reputational effectiveness.
Exhibit 2.6: Factors Influencing the Strategic Role of HR Department
External Context
Organizational Context • Size • Centralisation • Sector/industry • Diversity • Culture • Shocks • Workforce characteristics • Shared meaning of SHRM
.._.._L...,.... . .,_+.................... Senior Managers Line Managers
• HR role expectations i • HR role expectations
Human Resource Allocation ] I HR Department's Role
Attributes Behaviour • Perceived role • Role behavior • HR leadership • Strength of will to act strategically • HR managers type A /B • Resource deployment • HR expertise • Structure of HR dept • Business Knowledge • Focus of activities • Power • Communication and visibility
External Context
Source: Adapted from Truss, C., Gratton, L., Hope-Harley, v, Stiles, P. & Zaleska, J. (2002). Paying the piper: Choice and constraint in changing HR functional roles. Human Resource Management Journal, 12('2.), 39-63.
Hutchinson and Purcell (2010) conducted study on HRM responsibilities of front-
line managers such as ward managers and paramedic supervisors in NHS trust and
concluded that support of senior managers is important for these managers to carry
out HR function.
41
Ohtaki (2005) reported the changing role of CEO in HRM in line with the changes
in HRM. The study further talks of integration of HRM into the organization's
business planning process. This new role puts forward the new challenges for
CEOs to build sustainable businesses
2.2.2.2 Top Management Roles: Key HRM Domains
Armstrong and Brown (2008) noted that top management has a central role to play
in implementation of performance management. They have to communicate that
performance management is an essential part of the managerial practices of the
business organizations and the effectiveness with which line managers executes
their performance management responsibilities is one of the measure used when
appraising their performance. Top management should ensure that line managers
do not feel pressurized in this exercise and view this as an innovative and
developmental approach. Moreover, line managers should be involved in the
design, development and evaluating the effectiveness of performance management
processes.
In Buyens and De Vos's (2001) study revealed that top management viewed HR
function as important way through which change management programmes can be
developed and carried out effectively. Further, research indicates that other HRM
functions such as employment relationship, motivation of employees are
considered equally important by top managers. Martell and Carroll (1995)
conducted a study on top management team from HRM perspective and concluded
that top executives are involved in selection, training, performance evaluation and
compensation of their subordinates. Moreover, Carroll and Gillen's (1987) study
also found evidence of CEO's involvement in selection and appraisal of managers.
Cunningham and Hyman's (1995) study reveals that the control of senior
management on HR planning decisions is more in comparision with line managers.
Whittaker and Marchington (2003) on the basis of case study research found
evidence of involvement of senior managers in different HRM areas such training
and development, recruitment, selection, performance appraisal. Moreover, senior
managers involvement ensures that people management issues are given due
consideration at board level. Valverde et al. (2006) reported the involvement of top
42
management across a wide range of HR processes and activities such as training
and development, staff reduction, health and safety, collective bargaining and
performance appraisal. Ohtaki (2005) carried out a study on the role of CEO in
HRM and found that involvement of CEO is important for compensation,
performance appraisal, career development and talent management.
2.2.2.3 Rationale for Role of Top Management in HRM
Papalexandris and Panayotopoulou (2005) reported that CEO's participation and
decision-making in HR activities have helped the organizations to gain competitive
advantage. Collins and Clark's (2003) study reveals that top managers' social
networks intervenes the relationship between HR practices and firm performance.
Senior managers' involvement in HRM activities enhances the HR effectiveness
and firm performance (Andersen et al., 2007).
Drawing on case study research, Stanton et al. (2010) pointed out the important
role of CEO in providing leadership and resources to create distinctive HR
systems. in addition to this, senior managers also play a crucial role in translating
the HR messages across the management hierarchy. In this perspective, researchers
(e.g. Bowen & Ostroff, 2004; Macky & Boxall, 2007) have argued that the
involvement of senior management contributes in achieving business goals and
enhance organizational effectiveness.
Klein et al. (2001) and Lado and Wilson (1994) reported that CEO's involvement
in HRM ensures close interaction between different groups of managers which
encourages the sharing of information which is important for the formulation and
implementation of HRM infrastructure for achieving the goals of the organization.
Papalexandris and Panayotopoulou (2003) reported that CEOs acknowledge the
crucial role of HR to gain competitive advantage over domestic and foreign
players.
Pfeffer and Davis-Blake (1987) noted that senior managers play a key role in
managing the crucial resources such as financial support and people to HR
departments therefore, increasing the HR department's capacity to carry out HR
processes.. Ohtaki (2005) reported that the contribution of CEO in HRM is
important since it articulates the vision of the company and its HR policies.
43
2.3 Role of External Agents in HRM
External agents are often involved in the management of people in organizations
(Valverde- et al., 2006). External agents include external HR service providers or
HR outsourcing agencies which are hired by the business organizations to provide
professional HRM solutions (Cook, 1999). Human Resource Outsourcing (HRO)
has emerged as global phenomenon indicating the wide spread use of external
agents in HRM.
In this context, Morley et al. (2006) have used the term "external devolution"
which implies outsourcing HR activities to external contractors. External
devolution is based on transaction cost model. The transaction cost model places
substantial importance on make or buy decisions (Gunnigle, 1998). It is pointed
out that if organization is not able provide a particular HR service at cheaper rate
when compared with external HR service providers, then organizations should buy
such services from HR outsourcing agencies. In addition to this, some other factors
such as demand and supply contribute to HR outsourcing.
Moreover, the dynamic business environment of the new age economy has
completely changed the nature of competition faced by business organizations. In
order to compete in the market place, business organizations need access to latest
technology which requires huge investments as well as time for establishing the
same in-house. That is why most companies decide to outsource some of their
HRM functions. Also, it provides opportunity to invest in the core areas and
enhance the competitiveness of the firm.
2.3.1 External Service Providers: HR Outsourcing
Human resources are the most valuable assets of any organization as the
organization's success lies in their hands and constitute an important source of
competitive advantage (Khatri, 2000; Wright & McMahan, 1992). Jackson and
Schuler (2000) identify HR as the potential contributor to the creation and
realization of the organization's goals. Consequently, HR practices have the
potential to be key drivers of overall firm success. In order to ensure that its
employees remain satisfied, the company has to have a specialized human
resources department that most of times proves to be a costly affair. Business
44
organizations are realizing the role of various other entities such as external service
providers in HRM providing services so as to save cost and time.
Valverde et al. (2006) argued in favour of the role of external service providers or outsourcing agencies in HRM. There are many entities involved in management of
HR function (Khatri & Budhwar, 2002). Human resource outsourcing has
completely transformed the landscape of HRM practices in organizations.
As a result of this transformation, organizations are fast realizing the importance of
focusing on core HR activities and outsourcing their non-core, administrative
activities. The role of external HR service providers is becoming increasingly
popular and the number of companies outsourcing their HR activities continues to
rise (Kosnik et al., 2006). Various researchers have explored the role of external
consultants in HRM (e.g. Kitay & Wrght, 1999; Redman & Allen, 1993;
Torrington & Mack, 1986). Analyzing the role of external service providers such
as consultants is critical for passing on new management practices between
industries (Littler, 1982). Moreover, the role of external service providers in HRM
has emerged as a popular subject of inquiry in the academic literature in the past
few years.
2.3.2 Dimensions of Human Resource Outsourcing
Bryce and Useem (1998) described outsourcing as the contracting out of a
company's major functions and activities to an external service or goods provider.
In other words, outsourcing consists in conducting one or more organizational
activities, using external agents (Lacity & Hirschheim, 1993). Adler (2003) defined
it as a process in which a company contracts with a vendor and rents its skills,
knowledge, technology, service and manpower for an agreed-upon price and
period to perform functions for a client. Lever (1997) defined it as a long-term
contract relationship that the enterprise received business services from the
outsourcing vendor.
Outsourcing is a historical and well recognized practice and HRM outsourcing
itself is a quite traditional practice (Kakabadse & Kakabadse, 2002). Different
studies have revealed that HRM outsourcing continued to rise in the areas of HRM
consulting and the design of HRM tools (Banham, 2003; Cook, 1999). Gay and
45
Essinger (2000) and Mehrotra (2005) have identified HRO as the fastest growing
area of outsourcing. Turnbull (2002) defined HR outsourcing as placing
responsibility for various elements of the HR function with a third-party provider.
History of HRO can be traced back to more than five decades, when Automatic
Data Processing set up its payroll processing services in the US. Now, the
company has more than $7 billion annual revenues and 40,000 associates
(www.citehr.com). External service providers such as Hewitt and Exult are
offering solutions to meet HRO needs of the organizations in a big way thus,
enabling them to focus on their core business activities. The services offered by
these companies in the HR area, includes training, legal advice, consulting,
headhunting, audit of HR policies and procedures, labour relations, maintenance of
personnel records, employee development program, HR information systems,
benefits, job description process, exit interviews, performance management
process and compensation (Alewell et al., 2009; Tremblay et al., 2008).
Although different researchers have defined the concept in their own words but the
underplaying assumption remains the same. It can be concluded that HRO is a
process in which a company utilizes the services of a third party (HR outsourcing
agency or external HR service provider or consultants) to take care of its HR
functions. External HR service providers or HR outsourcing agencies are part of
outsourcing industry which are usually contracted by organizations to provide
administrative HRM services or professional, specialized 14RM solutions (Cook,
1999; En-shun, 2007).
A company may outsource a few or all of its HR related activities to a single or
combination of service providers located anywhere in the world. According to Seth
and Sethi (2011), HR outsourcing service providing firms can be divided into five
categories depending on the services they offer as:
> Professional Employer Organization (PEOs), > Business Process Organization (BPOs), > Application Service Providers (ASPs),
E-services and > Hybrid Outsourcing Firms
In the above mentioned categories, the PEOs are the ones that assume full
responsibility of a company's HR functions where as others such a BPOs, ASPs
and e-services provide web based HR solutions like database maintenance, HR
46
data warehousing, maintaining records, developing and maintaining HR software's
etc. In case of hybrid outsourcing firms, if organizations are having apprehensions
of outsourcing all their HR tasks to a PEO then it considers outsourcing of labor-
intensive HR functions. For instance, several business organizations use
recruitment agencies to find suitable candidates while prefer to retain control of
other HR activities such as salary negotiation, hiring and firing employees.
Traditionally, HR activities have been performed in-house; however, gradually HR
activities are being outsourced to external service providers (Jamrog et al., 1997; Stewart, 1996). The concept of HRO has grown in popularity since the early
1990s, particularly in the USA, where up to 90 per cent of the companies outsource
some HRM activity (Cook, 1999; Mahoney & Brewster, 2002). For instance, one
of major development in HRO is the 1999's deal involving BP and Exult in which
Exult was contracted to take up ownership and management of all global
transactional and administrative HR services for BP (Adler, 2003). Since then
HRO has grown with external HR service providers focusing on more complex HR
solutions than simply processing of routine HR services. The results of the 2004
survey conducted by the Society for Human Resource Management revealed that
60% of the business organizations participating in the survey had outsourced at
least one HR service (Esen, 2004).
It is generally observed that transition from internally managed HR functions to
externally managed HR functions, is a sensitive issue as the culture of the service
provider and that of the organization may be different. Organizations create teams
to facilitate this transition and monitor the agency over a period and evaluate their
performance. As a result of outsourcing of HR process and activities, HR managers
get more involved in strategic decision-making (Khatri & Budhwar, 2002)
Nowadays, most organizations prefer to focus on their core competencies and
choose to outsource their non-core activities to external service providers. Trends
point towards increased outsourcing in the new and emerging technology area,
with focus on the application service provider model where enterprises outsource
their entire HR-related processes, including recruitment, retention and related areas
(Klass et al., 1999; Klass et al., 2001).
47
2.3.3 Human Resource Outsourcing: Key HRM Domains
The prior literature on HRO can be clubbed into the two types of studies viz.
general studies on HRM being outsourced and studies focusing on specific HR
areas. The general studies on HRO talk about the reasons and rationale for the
growth of HRO while in case of specific studies, the focus of the researchers
remained on specific HR areas outsourced. Given that HRM service vendors
specialise in the services they provide to their clients, they benefit from economy
of scale results and these benefits are transferred to their clients (Galanaki &
Papalexandris, 2005; Galanaki & Papalexandris, 2007). Another reason why some
companies may turn to outsourcing is the requirement for know-how. Many
vendors have already made major investments, in HRM tools and techniques and
can spread their costs over many clients. Outsourcing offers knowledge and
competencies that may not exist in-house (Galanaki & Papalexandris, 2005).
Different types of activities may be outsourced by an organization e.g.
administrative and regulatory, transactional activities (like pay-roll administration,
healthcare, pension, administration of training, retirement, relocation
administration and other benefits), developmental, advisory and change
management (Alewell et al., 2009; Gilley et al., 2004;Tremblay et al., 2008). Kitay
and Wrght (1999) conducted a study to explore the relationship between
management consulting industry and .management of human resource in Australia.
The findings of the study reveal that the use of management consultants in
management of human resource has increased significantly.
Kodwani (2007) studied the underlying reasons that are encouraging business
organizations to outsource HR tasks. In order to cut costs and fully focus on the
core business activities, business organizations are reducing manpower from their
payrolls. As a consequence of which HRO is becoming the buzzword for the
corporate world. Outsourcing of HR tasks is adopted by different organizations
irrespective of size. Embleton and Wright (1998) identified the issues relevant to
successful outsourcing. They concluded that organizations where outsourcing is
part of an overall corporate strategy and employees are aware of the overall
situation are successful. Coggburn (2007) investigated HRO in public sector. The
study provides a conceptual framework that helps to analyze the appropriateness of
HR outsourcing.
48
Galanaki and Papalexandris (2005) opined that the continuous development of
HRM services market goes hand-in-hand with the development of the HRM
practice in general. Lawler et al. (2004) and O'Brien (2005) reported the popular
HRO contract of British Petroleum in 1999 with Exult. Since then HRO activity
has amplified to the point of being persistent and decisively ingrained facet of
private sector HR strategy. Several researchers have stated that HRO has increased
considerably over the years (e.g. Andersen, 1996; Harkins et al. 1995; Woodall et al., 2002). Both qualitative and quantitative reports from various sources provide
proof of this growth (Maurer & Mobley, 1998; Mobley, 2000; Pricewaterhouse
Coopers, 2002).
Various research studies have reported that training is one of the commonly
outsourced HR function (e.g. Cook, 1999; Cooke et al., 2005; Galanaki &
Papalexandris 2005; Vernon et al., 2000). Galanaki et al. (2008) studied
outsourcing of training function and proposed two types of training models viz.
generic and specific. Generic models deals with the generic training for
development of competencies while in case of specific models, job-or-company
specific training such as induction training, job specialization is provided to
employees.
Mahoney and Brewster (2002), Papalexandris et al. (2001) have recognized that
HR that are outsourced can fall ' into one of the following categories viz.
recruitment and selection, training and development, pay and benefits etc. In
addition to the above mentioned functions, following categories have also been
constantly mentioned in the literature viz. HR planning, performance appraisal
systems, and organizational climate and culture (Cook, 1999). Shaw and Fairhurst
(1997) study found that training and development along with facilities
management were the most likely areas to be outsourced, while industrial relations
expertise was the least likely area.
Hall and Torrington (1998) in their study established the probable HR activities to
be outsourced i.e. recruitment and selection, training and management
development, outplacement, health and safety, quality initiatives, job evaluation
and reward strategies. These activities are considered for outsourcing ' either
because they were considered non-core or because the organization may not have
the expertise to handle them internally. Vernon et al. (2000) conducted a study on
J
four different areas of HR outsourcing such as training and development,
recruitment and selection, pay and benefits, and workplace
outplacement/reduction.
Galanaki and Papalexandris (2005) studied the practice of outsourcing human
resource management functions such as training, staffing, rewards and
restructuring in Greece. Primarily outsourcing activities include small portion of
HRM such as payroll functions (Adler, 2003), however, it has steadily developed
to cover several human resource functions (Lever, 1997). Table 2.3 presents a
summary of key HR area being outsourced.
Table 2.3: Key HR Domains vis-a-vis HRO Researchers HR Domain
Training and development, legal advice, temporary agency work, HR consulting, headhunting, payroll
AIeweIl et al. (2009) accounting, placement services, selection of personnel, outplacement services, interim management, complete outsourcing of HR HR planning, recruitment and selection, employee
Chiang et al. (2010), Kulik and relations, HRIS, payroll, compensation and reward, Bainbridge (2006), Woodall et al. performance appraisal, benefits administration, (2009) training and development, health and safety,
employee services
Cook, (1999) Performance appraisal systems, HR planning, organizational climate and culture,
Delmotte and Sels (2008), Tremblay Training, payroll, recruitment and selection, career
et al. (2008), Vernon et al. (2000) guidance, appraisal, outplacement, labour relations, benefits
Mahoney and Brewster (2002), Recruitment and selection, pay and benefits, training Papalexandris et al. 2001) and development, merger- outplacement-downsizing
Payroll administration, training/development,
Smith et al. (2006) executive coaching, HRMIS, healthcare benefits administration, recruitment (executive & non- executive), strategic business planning Recruitment and selection, training and
Galanaki and Papalexandris (2007), development, pay and benefits, merger-outplacement-downsizing Galanaki and Papalexandris (2005) performance appraisal systems, HR planning, or anizational climate and culture Training and management development, recruitment
Shaw and Fairhurst (1997) and selection, outplacement, health and safety, quality initiatives, job evaluation, reward strategies and systems HR planning, EEO/diversity, recruitment and
Klaas etal. (1999) selection, organizational development, safety & health, performance appraisal
Source: Prepared by the Researcher
50
Gainey et al. (2002) study reported that companies outsource approximately 30
percent of their HRM training functions directly allied to core capabilities but
mainly this has led to enhanced performance with improved training design. Greer
et al. (1999) study emphasized not to outsource the employee relations and
performance management that are sometimes outsourced along with some related
functions such as payroll administration and benefits concurrently as a bundle.
2.3.4 Rationale for Human Resource Outsourcing
Studies on HRO have provided substantial support to companies for pursuing the
same (e.g. Dell, 2004; Greer et. al, 1999).There are a number of financial issues
that induce business organizations to adopt HRO. HRO is considered by
organizations to accomplish operational costs savings through economies of scale
provided by external HR service providers, avoid investment for HR technology
upgrades or permanent HR staff on company pay rolls into variable costs
(Fernandez et al., 2006; Koch et al., 2004; Lawther, 2003).
Several studies highlighted the outsourcing benefits such as . decreased costs, a
better focus on HRM issues which are immediately associated with the company's
success and higher quality customer service (Csoko, 1995; Greer et al., 1999;
Simmonds and Gibson, 2008 Woodall et.al., 2002). Outsourcing can be a key
value-added activity when pooled with effective restructuring. Marinaccio (1994),
asserts that outsourcing along with improved engineering processes may increase
the efficiency of business processes while retain product quality. Lever (1997)
argued that the value-added activity that outsourcing brings should finally
augment strategic capabilities and benefit the firm's performance with regard to
gaining a competitive edge, managing market risks, maximizing returns and
strengthening internal capabilities. Lever (1997) claimed that benefits that
outsourcing brings should ultimately increase strategic capabilities and firm
performance.
HRO provides the organizations flexibility to purchase the best available talent or
technology, thus, offering employees more ease through self-service applications
(Fernandez et al., 2006; Koch et al., 2004; Wilson, 2003). Marinaccio (1994) adds
that outsourcing enhances organizational efficiency. Greer et al. (1999) and Rainey
51
(2005) have identified the underlying principle for HRO. The important instances
include building stronger internal focus on core HRM functions and delivering
more strategic value for the organization.
Hirschman's (2000) study reported that reducing cost while at the same time
maintaining at-least equal levels of quality and strategic focus will enhance the
competitive advantage of an organization. This has led to expansion in the use
of external service providers for HRM functions. In the perspective of this
fact, there is significant growth in academic research which provides a strong list
of factors that support the decision to outsource human resource activities (e.g.
Greer et al., 1999; Hendry, 1995; Klaas, 2003; Klaas et al., I999; Klaas et al., 2000; Klaas et al., 2001; Lepak et al., 2005; Lepak & Snell, 1999b; Lever, 1997).
According to the transaction cost theory, activities that are not firm-specific are
more likely to be outsourced, whereas the resource-based viewpoint advocates that
activities not critical to core competencies should be outsourced (Williamson,
1975). Lepak and Snell's (1998) model of virtual HR based on transaction cost
economics (Williamson, 1975, 1985; Coase, 1937) and resource-based perspective
offers a useful framework to select the HR activities that should be outsourced.
Researchers in the area of HR outsourcing have mostly based their studies on
transaction cost economics theory to delineate the conditions under which HR
outsourcing is useful for the organizations (Hart, 1988) and apparent benefits
associated with such outsourcing (Klaas et al., 1999). Ulrich (1996) reported that
outsourcing of HR practices can be helpful to the development of the core
competence of organizations and integrating HR practices with corporate strategy.
Greer et al.'s (1999) study pointed out that occasionally HR outsourcing is driven
by the evolution of the HR function within the organizations. Baron and Kreps'
(1999) analytical model emphasized that activities of low strategic importance and
low task should be outsourced. Besides the conceptual logic offered by transaction
cost economics and the strategic HR perspective, other underlying principles for
HRO are cost savings, decrease in risk, specific expertise and brief expansion of
HR capabilities to meet extraordinary circumstances (Greer et al., 1999).
Adler (2003), Oshima et al. (2005) concluded that HRO provided the time to HR
professionals to support business activities. Gilley et at. (2004) conducted an
52
empirical study to establish the relationship between the outsourcing of activities
such as training and payroll, and firm performance as well as the outsourcing-
performance relationship and firm's size. Results of the study revealed that
outsourcing of training and payroll have positive influence on firm performance
where as the outsourcing-performance relationship and firm's size were
unconvincing.
Gilley and Rasheed (2000) studied the extent of outsourcing across a wide range of
business activities as well as depth of outsourcing within each activity and found
no direct effect of outsourcing on performance. However, outsourcing had positive
influence on firm's performance following cost leadership and innovative
differentiation strategies, as well as for firms operating in stable environments.
Klaas et al. (1999) based their study on transaction cost economics to examine the
relationship between organizational characteristics and the degree of reliance on
HR outsourcing. Results of the study revealed that perceived benefits from HR
outsourcing will vary with a number of organizational characteristics. Klaas (2003)
studied the relationship between small and medium-sized enterprises and the
professional employer organizations and outlined a structure to examine the HRO
factors in small and medium-sized enterprises.
According to the U.S. General Accounting Office (U.S. G.A.O, 2004), whether the
drivers are mundane or elegant, it likely depends upon the specific HR activity
being outsourced. Lower-tiered activities such as payroll are mostly allied with
cost savings whereas higher-tiered activities like performance management
systems, workforce planning are related to gain expertise or to respond quickly.
Some studies on HRO indicated that most of HRO tends to be for the lower-tiered,
transactional activities, thus, reflecting the large number of mundane as different to
elegant drivers (Rainey, 2005, McClendon et al, 2002).
Outsourcing HR functions has positive bearing on employee satisfaction,
motivation and efficiency. These facets of HRO make it essential for considering
the effects of HRO on firm performance. In this context, Gainey and Klass (2002)
reported that outsourcing of FIRM training function has led to better training
design with enhanced performance. HRO is highlighted as a cost-saving strategy
by external consultants and HR service providers. Usually, the external HR service
53
providers which specialize in HR services, offers lower costs than client because of
economies of scale, greater efficiency and higher levels of expertise.
Greer et al. (1999) identified five factors that facilitate HR outsourcing viz.
downsizing, rapid growth or decline, globalization, increased competition, and
restructuring, based on the extant literature and interviews with senior HR
executives. HRO is carried out for both operational and strategic reasons. Based on
the results of the study, procedure for selecting vendors, managing the outsourcing
transition, managing vendor relations and monitoring vendor performance is
proposed. HRO can enhance the HR worth as well as reinforce the growth of HR
as a business partner and strategic contributor to the organization's goals.
According to Csoko (1995), outsourcing carries benefits such as cost reduction,
increased service quality and increased access to experts in specialized areas. The
key considerations following HR outsourcing is the need for increased focus on
core business and cost reductions (Van Hoek, 1999), greater business flexibility
and need for specialized expertise (Bettis et al. 1992; Jennings 1996; Quinn et al.
1990). Outsourcing, decisions usually target a minimum of 15 per cent cost saving
and sometimes in the range of 20-25 per cent (Bounfour, 1999; Jennings, 2002).
Several researchers have highlighted HRO as advantageous in terms of both
service delivery and the enhancement of the strategic position of HR
(Brenner, 1996; Laabs, 1993; Switser, 1997). Both the resource-based view of the
firm (Barney, 1991) and the transaction-cost economics model (Williamson, 1985)
seem to influence firms' HR outsourcing decisions.
A number of studies have evaluated the make-or-buy decisions in favour of
outsourcing of HR functions (Autor 2003; Belcourt, 2006; Cooke et al., 2005;
Gainey & Klaas 2003; Greer et al., 1999; Klaas et al., 2001). The extent of
outsourcing HR tasks varies between firms and sectors (Cooke et al., 2005). Cost
and quality are the focal points of outsourcing research and make-or-buy decisions
of the firms are based on transaction cost theory (Williamson et al., 1975).
Klein (2004) reviewed the empirical researches on make-or-buy decisions which
have been conducted on the basis of transaction cost theory. The results of the
study revealed that many important determinants which describe firm structure
and environment as well as underlying relation between outsourcing effects and
54
make-or-buy decisions have been overlooked. Structural and contingency factors
such as firm size may have a strong impact on outsourcing decisions (Jack et al., 2006; Marlow, 2006; Mayson & Barrett 2006). Becker and Gerhart (1996)
discussed about cost vis-a-vis value aspect of HR outsourcing. This viewpoint
points out that organizations should assess both cost centres (e.g., benefits
administration) and value aspect (e.g. recruitment and hiring) of HR outsourcing.
Klass (2003) concluded that cost has major influence on the decision to outsource
HR activities as it is difficult for many companies to maintain professional HR
staff for internally developing required HR services. Moreover, outsourcing of HR
activities offers an organization unique edge over competitors and save the
resources for other operations. . Saha (2005) reported that organizations are
looking for HR service offerings to integrate process management with strategic
human capital. Klaas et al. (2001) and Lepak etal. (2005) based their viewpoint on
resource based view and concluded that organizations should deliver those services
in-house that are core to their competitiveness and outsource those services that
are considered peripheral. Table 2.4 presents the summary of key benefits of HRO.
Table 2,4. Key Benefits vis-a-vis HRO Researchers Benefits of HRO
Babcock (2004), Fernandez et al. Costs savings through economies of scale (2006), Koch et al. (2004) Lawther (2003), Marinaccio (1994) , Increases organizational efficiency and flexibility Wilson (2003) Quinn and Hilmer (1994) Helps focus on core competencies Becker and Gerhart (1996) Cost vis-a -vis value aspect of HR outsourcing Ulrich (1996) Hel s in integrating HRM with corporate strategy Greer et al. 1999) Operational and strategic benefits Baturina (2003) Benefits through expertise and reliabilityof vendors Csoko (1995), Simmonds and Cost reduction, increased service quality and access Gibson(2008, Woodall et al. (2002), to ex erts competency in specialized areas Bettis et.al. (1992), Jennings (1996), Cost reductions, greater business flexibility and Quinn et. al. (1990) need for specialized expertise En-shun (2007) Access to latest technology and critical expertise
Belcourt (2006), Benson and Littler Cost reduction, improvement in quality, focus on
(2002), Galanaki et al. (2008) core and excluding non-core training tasks, reduces head count, improves labour flexibility
Saba (2005) Helps in linking process management with strategic human capital
Gainey and Klass (2002), Cost saving and better administration Gilley et al. (2004) Source: Prepared by the Researcher
55
Cooke (2004) viewed the rising intricacy of the technology, legal environment and
organizational changes as the key features encouraging the decision to outsource.
Adler (2003) appends to the list the factors such as intense competition,
globalization, downsizing, industry changes and restructuring as the major reason
for outsourcing. Moreover, outsourcing is also guided by the need for specific
expertise, a new developmental stage of organizational HRM that has exceeded
the firm's existing capacity, advances in HR information systems, increased
risk exposure (Greer et al., 1999; Klaas, 2003) and cost savings (Babcock, 2004).
2.3.5 Human Resource Outsourcing: Barriers and Constraints
HR outsourcing has received ample research attention, however, very few studies
have addressed issues like the conditions that promote or hinder the outsourcing
decision processes. Although HRO offers significant organizational benefits, it
suffers from low quality of service, high transaction costs and loss of control over
outsourced HRM function. Quinn's (1999) study revealed that outsourcing can fail
owing to the wrong assessment of need for outsourcing. The study fizrther adds that
lack of interest of managers to analyze outsourcing need can also lead to its failure.
Although HRO helps organizations to focus on their core business but outsourcing
frequently fails short of anticipation (Barthelemy & Adsit, 2003).
Khatri and Budhwar (2002) found that competency level of external HR service
providers and poor quality of service inhibit organizations in outsourcing human
resource activities. Moreover, HR strategy and organizational culture are other
important factors that influence the organizational tendency to outsource HR
activities (e.g. Khatri & Budhwar, 2002; Ulrich, 1996). Since organizational
culture is developed over period of time, it is difficult for external consultants to
comprehend the same immediately and perform the HR tasks in light of
organizational culture.
Barthelemy and Adsit (2003: 87) analyzed the outsourcing deals in Europe and US
and delineated the "seven deadly sins" responsible for unsuccessful outsourcing. It
includes outsourcing core activities, selecting the wrong vendor, writing a poor
contract, overlooking personnel issues, losing control over the outsourced activity,
overlooking the hidden costs of outsourcing and failing to plan an exit strategy.
56
P.
Ulrich (1996) highlighted that outsourcing restricts the organizations to develop
unique expertise within the employees and therefore gives rise to incompetence.
Klass et al.'s (2001) revealed that external HR service providers need considerable
investment to identify the requirement of the organization which increases the cost,
therefore, making outsourcing less attractive. Barney (1991) pointed out that it is
difficult to communicate the tacit knowledge and experience of employees to
external service providers, thus, making the case for providing training in-house.
Enshun (2007) identified different types of risks faced by organizations while
outsourcing HRM functions (i.e. strategic; contractual and operational risks). In
strategic risk, outsourcing of core HRM functions results in short-term benefits
while in the long run, organizations may face problems due to loss of in-house
expertise (Greer, et al., 1999; Stroh & Treehuboff, 2003; Laabs; 1998). Contractual
risk is the result of fixed agreement between service provider and the organization
without any flexibility. The third type of risk is operational risk which includes
operational performance such as lower levels of service quality, unexpected
business interruptions, poor understanding with service providers and inadequate
monitoring of performance of vendors. Kodwani (2007) highlighted different types
of challenges for HRO. It includes political risk, resistance from employees in
accepting the change and vendor selection.
Lawler and Mohrman (2003) reported the general problems of HRO such as poor
service, loss of internal expertise, contractor not performing as expected and
unexpected resources required to manage outsourcing relationship. The problems
or risks associated with outsourcing are explained by Roberts (2001:239-49) as:
"Organizations are afraid of losing some control over the delivery of outsourced services and finding themselves overly dependent on the vendor or liable, for the vendor's actions. Outsourcing sensitive information, particularly confidential information, has inherent liability if information security is breached by the vendor".
A study by Simmonds and Gibson (2008) highlighted the roadblocks linked with
outsourcing HR functions. Exhibit 2.7 presents a two part model for managing the
outsourcing of HRD function. Part one of the model is based on four elements (i.e.
prioritize, select, trust and monitor) while part two of the model is important for
managers to chart the decisions of different aspects of outsourcing HRD against
specificity/complexity of training needs and risk/value of assets.
57
Exhibit 2.7: A Model for Outsourcing
Tailor-made In-house outsourcing training
Off-the-shelf Blended training In-and-out-sourcing
High
Specificity/ Complexity of training
needs
Low Risk/ Value of assets
High
Source: Simmonds, D. and Gibson, R. (2008). A model for outsourcing HRD. Journal of European Industrial Training, 32(1), p.10.
Stroh and Treehuboff (2003) presented a model that retaining some in-house
expertise for the function being outsourced and outsourcing only non-core
activities. Exhibit 2.8 presents the above model.
Exhibit 2.8: A Model for Successful HR Outsourcing
Audit the vendor annually
internally I, Communicate
the process .
Keep training internal
Keep the company culture
Successful outsourcing Offer a consistent
menu of service
Do not outsource a problem
Interview outsourcing agencies employees
Keep some expertise in-house
Never outsource core activities
Source: Stroh, L. K and Treehuboff, D. (2003). Outsourcing HR functions: When and when not to go outside. Journal of Leadership & Organizational Studies, )0(1), p.22
58
The following factors can be critical to making and implementing a successful
outsourcing decision (Laabs, 1993).
> Describing outsourcing objectives clearly before making an outsourcing
decision
> Organizations should consider who will manage outsourcing decision and why
> Looking into the short as well as long term objectives
> Determining the company's culture support for an outsourcing decision
Choosing the nature of operation viz, centralized or decentralized before
outsourcing
Paul (2003) opines that cost should not be considered as the only deciding factor to
outsource non-core HR activities but others factors such as cultural fit and a
commitment to quality shall be taken into consideration, Organizations must look
into the range of services which a vendor has to offer as well as its expertise and
experience in offering such services. Based on the type of function an organization
has to outsource, it can select an appropriate outsourcing firm. Baturina (2003)
focused on the reliability of service provider and its expertise in providing the HR
solutions as important facilitating factors for HR outsourcing,
2.4 Constructs to Measure Role of Agents in HRM
Constructs are latent or unobservable variables that cannot be measured directly
but can be measured by one or more indicators or items (Ahire et al., 1996; Hair et
al., 2008; Malhotra & Dash, 2011; Schumacker & Lomax, 2004). Researchers in
the area have identified several constructs to measure the role of internal and
external agents in HRM. Review of prior studies throws light on these constructs
and items used to measure them. At the same time, several researchers have related
the measures of role with measures of organizational performance and
effectiveness (Budhwar, 2000a; Budhwar & Sparrow, 1997; Hutchinson & Purcell,
2003; Mcguire et al., 2008; Valverde et al., 2006).
Since most studies in the area have focused on only one or at best two agents,
different measures exist to evaluate the roles of both internal and external agents in
HRM. For instance, Budhwar (2000a) studied the role of line managers through
devolvement of HRM responsibilities using items like primary responsibility with
59
line managers for HRM decision-making, change in the responsibility of line
managers for HRM vis-a-vis pay and benefits, recruitment and selection, work-
force expansion and reduction, training and development, health and safety and
industrial relations.
In other similar research studies, researchers have used different constructs to
measure the involvement of line managers in decision-making (e.g. Budhwar &
Boyne, 2004; Gautam & Davis, 2007). Andolsek and Stebe (2005) identified
devolution as a construct to study line managers' responsibility for HRM decisions
in European organizations. The extent of devolution was mapped in light of
different HRM functions like recruitment, training, industrial relations and
workforce reduction.
A number of researches carried out in the area have used items from Cranet survey
(e.g. Andolsek & Stebe, 2005; Brewester et al., 1997; Dany et al., 2008; Papalexandris & Panayotopoulou, 2003; Papalexandris & Panayotopoulou, 2005).
Cranet survey or Cranfield Network on European HRM is a comprehensive survey
of comparative HR practices across several countries. Broadly, the survey covered
two dimensions viz, integration and devolvement.
Valverde et al. (2006) studied the participation of internal and external agents in
HRM activities at various levels of HRM decision-making viz, strategic, policy,
operational and administrative. They investigated the distribution of HR
responsibilities among agents across wide range of HR areas such as training and
development, resourcing, change management etc. Dany et al. (2008) explored the
role of FIR specialists and line managers in five HRM areas such as pay and
benefits, recruitment and selection, training and development, industrial relations
and workforce expansion/reduction using the items developed in Cranet survey.
Casco'n-Pereira et al. (2006) identified various dimensions of devolution such as
decision-making power, task/responsibilities, financial power and expertise power.
These four dimensions were explored vis-a-vis different HRM functions viz.
recruitment and selection, training and development, compensation, leadership,
health and safety, communication, dismissals, motivation and team management.
Hope-Hailey et al. (1997) investigated the role of line managers in people
management practices in light of dimensions such as access to strategic decision-
making and HR functions.
Research studies on role top management in HRM have identified several issues to
measure the level of involvement of top level people in HR related issues. For
instance, Sheehan (2005) reported that CEOs play a key role in the involvement of
HR at the strategic decision-making level. In addition to this, CEO's involvement
in HRM decision-making ensures that HR strategy is integrated with the corporate
strategy. Drawing on the prior research studies, Azmi (2011) argued that training
and sensitization of top managers in HRM practices is important for determining
relationship with HR practices and strategy. The study further explored a number
of issues such as role of top management in HRM, consistency of HR activities
'T_ with organizational vision etc.
Role of external agents in HRM too has been explored from different perspective.
Gilley et al. (2004) studied the degree of outsourcing of HR activities viz, payroll
and training. Galanaki (2008) investigated different aspects of outsourcing training
to external service providers. Klass et al. (1999) explored HR outsourcing focusing
on four types of HR activities viz, transactional, generalist, human capital and
recruitment and selection as measures. Klass et al. (2001) investigated outsourcing
of HR practices by six measures such as idiosyncratic processes, HR strategic
involvement, positive HR outcomes, promotional opportunities, demand
uncertainty and outsourcing by competitors.
Tremblay et al, (2008) explored HR outsourcing in Canadian organizations using
organizational and strategic variables viz, management support, benchmarking,
outsourcing experience, HR strategic role, union, pay policy transaction attributes
such as specific complexity, HR variability, measurement problems , risks of
outsourcing (HR risks, provider risks and business risks).
Since most studies in the area focus on a single agent, therefore, a comprehensive
construct definition is not available in the extant literature. Assimilating the
scattered viewpoints, a list of constructs identified from the literature on role of
internal and external agents in HRM is presented in Table 2.5.
61
Table 2.5: Constructs Used to Measure Role of Internal and External Agents searchers Construct Items
Internal A ents viz. Line Managers and Top Management
> Line manager confidence in HR H&away k2010) Line HR relationship > Line-HR partnership
> Collaborative problem solving
Andersen eta!, (2007) Line management > Involvement of Gne managers in execution of HR practices devolvement ➢ Line managers training in the firm to execute I'JR practices
> Responsibility for FIRM decision to line Andolsek and Stebe (2005) Devolution > Changes in the process of devolution
➢ Levels of devolution
D Formulation of vision and strategy
Perceived importance of > Instructing and training, planning, staff development
Brandt eta!, (2009) managenallliR activities
➢ Communication of values and attitudes, handling conflicts, delegation handling information, supervision/coaching, negotiations
➢ Follow u /monitorin , roblem solver/expert, reporting ,staff well-bein
Brewster & Hegewisch (1994), > Primary responsibility with line managers for HRM decision-making
Budhwar (2000x; 2000b), Devolvement ➢ Change in the responsibility of line managers for HN
Budhwar & Sparrow (1997) > Percentage of line managers trained in HRM functions such as performance appraisal, training and development
Brewster & Larsen (1992) Devolvement ➢ Scope of }JR activities devolved to line managers > De ree to which HRM function is involved in co orate strategy
Brewster at al. (2004), Line manager y Level of participation in HR functions Nehles et al. 2006 involvement
Transfer of responsibility for FIRM to line
Line manager and top > HR department is represented at board level
Budhwar & Boyne (2004) managers' role
➢ Participation of HR department in managing change > HR participation in formation of corporate strategy4rom the outset
HRM considerations built into or anization strate
Researchers Construct Items
➢ Task/responsibilities
Casco'n-Pereira et al. (2006) Devolution ➢ Decision-making power > Financial power ➢ Expertise ower
Conway & Monks (2010) Middle manager ➢ Primary responsibility for HR activities (workforce practices, appraisal, perspective of HR training, development recruitment and selection, grievances
Distribution of influence between Hk specialis ts
> Responsibility for HRM decisions vis-a-vis recruitment and selection, Dany el al. (2008)
and line managers fn training and development, pay and benefits , industrial relations and
1 workforce expansion/reduction
Gautam & Davis (200 Devolvement ➢ Primary responsibility for implementing HR policy decisions > Direction of line management responsibility for HRM
Heraty & Morley (1995) Line managers' role > Responsibility for major policy decisions on training and development ➢ Res onsibili for aing trainingand development activities
Change in line managers role and responsibilities responsibilities,
➢ Transfer of people management responsibilities to the line Hope-Bailey et al (1997)
access to strategic ➢ Shift in responsibility for decision-making in HR issues to line managers
decision-making ➢ Integration with strategic direction
Responsibility for HRM
> Line management responsibility for pay and benefits, recruitment and Hsu & Leat (2000)
functions selection, training and development, industrial relations, health and safety, and work-force expansion/reduction
Kulik & Bainbridge (2006) Distribution of people management activities
➢ Primary responsibility for people management activities like HR planning,
among agents performance management, training, recruitment, industrial relation etc.
Line management > Responsibility for HR policy decisions (pay, training, industrial relations)
Larsen & Brewster (2003) responsibility for HRM
➢ Direction of change in HR responsibility of line management for pay, training , industrial relations etc,
Researchers Construct Items
➢ Line managers understanding of HR strategy Line managers i' Ownership of the HR strategy
Maxwell & Watson (2006) perspective on > Line managers involvement in HR activities involvement in HRM ➢ HR specialists' support of line managers in HR activities
➢ Com etence of line managers in HR activities
Papalexandris & Role of line managers
Major decisions on pay and benefits, recruitment and selection, training and Panayoto ulou (2003) development, labour relations, downsizin
Papalexandris & Line managers' HRM ➢ Involvement of line managers in decisions on pay and benefits, recruitment Panayotopoulou (2005) responsibility and selection, trainin and development, industrial relations
Devolution > Line management involvement in people management activities Perry & Kulik (2008)
Line Support
> Line managers were given support for their HR responsibilities > Line managers receive training for people management skills
Srimannarayana (2010) Line management > Extent of responsibility of line managers in HRM activities involvement in HRM > Variation in line mans ers' involvement in FIRM activities
Line managers' role in > Line managers' views on their role HR activities and line managers'. Watson & Maxwell (2007) H ranking of most important HR activities (like team briefings, identification
of training needs, perfonnance appraisal, evaluating training
> Line management responsibility for HR practices in the organization (like Zhu et al. (2008) Devolvement recruitment and selection, compensation, training, performance assessment
• > Percents a of line managers formally trained to perfonu HR activities
Valverde et al, (2006) Distribution of HR
s onsibiliti s > Participation in HRM activities
Rote of top management > HR managers viewed as partners in the management of the business Becker & Huselid (1998)
in HR strategy > Effort to align business and HR strategies p HR de artment's involvement in coruorate strate is lannin
Bowen et al (2002) Top managers role > Top manager consider HR department as important HR de artment works with senior management on key strategic issues
Researchers Construct Items
➢ Top management incorporates HR information (plans, activities etc.) when
Green eta!, (2006) Top management role in establishing the organization's direction HRM > Top-level managers are trained to integrate all functions into the decision-
makin rocess
➢ HR representation on the senior committee level Poole & Jenkins (1997) Top management role ➢ HR managers part of strategic planning process
➢ HR mans ers have appropriate in ut into strategic decisions,
➢ Direct reporting relationship with the CEO Schuler (1992) Linking HR•strategy ➢ Good informal relationship
> HR representation on the senior committee
> HR representation at the senior committee level Sheehan (2005) Top management role > HR part of the senior decision•mnaking processes
Direct reporting or informal relation between HR. manager and CEO
Top managers role in ➢ HR specialists participation at board level to strategy Wood (1995)
HR strategy ➢ Line manager initiates and carries out selection. > Personnel issues incorporated with business
External A eats viz. External Service Providers
Triggers of explicit HR Changes in manpower requirement
Alewell et a!, (2009) procurement decisions for different I
> Changes in manpower endowment
functions > Manpower balance in HR department
➢ Causes Decline in demand, increase in labour and non-labour costs
Benson & Littler (2002) Outsourcing and ➢ Objectives workforce reductions • Improve labour productivity, improve decision-making
' > Effects on employees
Employee job satisfaction, changes in employee duties
Researchers Construct Items
➢ Potential areas of HR outsourcing FIR planning, recruitment and selection, training and development, employee relations, performance appraisal, health and safety, payroll, compensation and reward, benefit administration, employee services
Idiosyncratic HR Practices
Chiang et al. (2010) HR outsourcing • Organization way of managing HR is unique • Organization manage HR like most other firms do Overall outsourcing emphasis
Organization outsource many staff functions ➢ HR Strategic Involvement
• Involvement of HR in ma or strategic decisions
HR outsourcing > Strategic involvement of HR
Delmotte & Sels (2008) 1 Focusing view Contribution of HRM to the strategic objectives of the organization
Efficiency view • Effi ➢ Devolution of'HR activities ➢ Evolution of the HR head count
Transactional, human ➢ Design and delivery of HR planning, employee relations, EEOldiversity,
capital, HR generalist, organizational development, safety & health, performance appraisal, 1 R10,
Klass eta! (1999) recruitment
payroll, training exempt employees, training non-exempt employees, employee assistance programs, recruiting exempt employees, recruiting non-
activities exempt eal 10 ees, selectin em to ees
• Idiosyncratic processes, HR strategic involvement, positive HR outcomes, Klass et al. (2001) HR outsourcing promotional opportunities, demand uncertainty and outsourcing by
competitors
Organizational and > Management support, benchmarking, outsourcing experience, HR strategic
Tremblay et al. (2008) strategic variables, role, outsourcing experience, union, pay policy transaction attributes, ➢ Specific complexity, HR variability, measurement problems risks of outsourcing ➢ HR risks, provider risks and business risks
Source: Compiled by the Researcher
2.5 Alternate Variables to Measure Role of Agents in HRM
Prior studies on role of internal and external agents have suggested the positive
implications of redistribution of HR activities among agents on certain outcome or
endogenous/dependent variables like overall performance and effectiveness (e.g.
Azmi, 2010; Bond & Wise, 2003; Dany et al., 2008; Gilley et al., 2004; Renwick;
2003; Valverde et al., 2006). Researchers Iike Perry and Kulik (2008) have linked
the role of internal agents with effectiveness of people management in
organizations
However, various studies on role of internal and external agents have indicated that
performance is not the direct outcome of this redistribution of roles but that
alternate variables affect this causal chain too. Alternate variable includes
moderating or interacting variables and mediating or intervening variables.
A moderating variable changes the relationship or strength of relationship between
two related variables viz, exogenous and endogenous variables (Frazier et al.,
2004; Hair et al., 2008). Hence, moderation effect is an interaction whereby the
effect of one variable depends on the level of another. Absence of significant
moderating effects makes the interpretation between the predictor and outcome
construct easy. Moreover, lack of relationship between moderator, predictor and
outcome variables helps to differentiate moderators from mediators.
Mediating variable is a third variable/construct that intervenes between two other
related constructs. In model testing, hypothesized mediating effect can produce
both direct and indirect effects (Hair et al., 2008). Direct effect relationships Iink
the two constructs with a single arrow while indirect effects involve series of
relationships with at least one intervening construct. Hence, indirect effect is a
sequence of two or more direct effects and is characterized by multiple arrows.
Exhibit 2.9 illustrates moderation and mediation effect.
67
Exhibit 2.9: Moderation and Mediation
Direct Effect
Exogenous variable Endogenous variable Di
e.g. role measures e.g. performance
Moderation Effect
Exogenous variable Endogenous variable
e.g. role measures e.g. effectiveness of HRM
Exogenous variable e.g. role measures
Moderating variable e.g. organizational profile
Mediation Effect
Mediating variable e.g. status of HRM
Endogenous variable e.g. effectiveness of HRM
Source: Adopted from Frazier, P. A., Tixi , A. P. & Barron, K. E. (2004). Testing moderator and mediator effects in counseling psychology. Journal of Counseling Psychology, 51 (1), 115-134
2.5.1 Performance. Measures as Outcome Variables
Several research studies have indicated the positive impact of internal and external
agents' involvement in HRM (Guest, 1987; Valverde et al., 2006). Internal
devolution entails the involvement of internal agents in HRM viz, line managers
and top management while in external devolution involvement of external agents'
viz. external HR service providers is assessed. In this context, researchers found
positive support of internal devolution on different measures of organizational
performance. Some studies have specifically established that participation between
HR and line helps in improving organizational performance (e.g. Azmi, 2010;
Gennard & Kelly, 1997; Thornhill & Saunders, 1998).
Budhwar (2000a) reported the positive implications of devolvement of HRM to
line managers on a firm's performance. Renwick (2003) argued in favour of
devolving HR tasks to line managers since significant organizational benefits exist
68
from involving the line in HR work. Moreover, devolvement of HR responsibilities
helps in configuration of HRM with business objectives and strategies associated
with the firm performance (Andersen et al., 2007). Various researchers have
reported the positive implications of line managers' involvement in HRM decision-
making on organizational performance (Hutchinson & Purcell, 2003; Mcguire et
al., 2008).
Hutchinson and Purcell's (2010) study revealed that front-line managers'
involvement is important for the delivery of effective HRM. The most important
features as highlighted in different studies is the roles and influence of HRM
specialists and line managers as defined and distributed within the firm (Andolsek
& Stebe, 2005; Hall & Torrington, 1998). Additionally, Dany et al. (2008) argued
in favour of the moderating impact of distribution of roles and influence between
HRM specialists and line managers on the link between HRM integration and
organizational performance. Hall and Torrington (1998) pointed out the need for
exploring the role of line managers in HRM and its impact on the effectiveness of
people management.
Azmi (2011) explored the role of top management in HRM and its relationship
with HRM effectiveness and organizational performance. The results revealed the
positive implications on the performance of the organization. Gilley et al. (2004) conducted a study to find out the link between HR outsourcing and firm
performance by investigating the influence of HRO processes on different types of
performance measures viz, innovation, financial and stakeholder performance. The
finding of the study revealed that outsourcing of some HR activities have positive
implications on firm performance.
Benson & Littler (2002) studied the outsourcing and workforce reductions to
establish the relationship between outsourcing and performance outcomes through
a number of indicators like reduction in labour costs, improvement in labour
flexibility, productivity, decision-making, customer service and job enrichment and
communications.
Table 2.6 presents the performance measures identified from internal and external
agents' literature.
Table 2.6: Performance Measures from Literature on Role of Aaents Researchers Construct Items
> Objective Performance • Sales
Azmi (2010, 2011) Organizational • Shareholder returns
performance • Return on capital employed > Subjective Performance
• Overall performance of the company > Return on equity
Andersen et al. Firm ➢ Return on assets (2007) performance ➢ Market growth
> Profitabily ➢ Profitability
Organizational
)> Product/service quality
Dany et al. (2008) performance > Level of productivity ➢ Rate of innovation 9 stock market erformance ➢ Financial Performance
• Return on assets • Return on sales • Overall financial performance
➢ Innovation Performance
Gilley et al.(2004) Firm • R&D outlays performance • Process innovations
• Product innovations ➢ Stakeholder Performance
• Employment growth/stability • Employee morale • Customer & supplier relations
> Reduce Iabour costs,
Benson & Littler Performance > Improve labour flexibility
(2002) outcomes > Improve labour productivity ➢ Improve decision-making > Improve customer service
People > Effectiveness of people management issues Perry and Kulik management in the organization (2008) effectiveness > Overall effectiveness of people management
activities in the or anization > Market Performance
• Profitability • Return on equity • Return on assets
➢ Organizational Effectiveness Zhu et al. (2008) Firm
performance performance • Timely adaptation of company products • and services • Timely adaptation of company strategy • Achievement of quality • Achievement of employee satisfaction • Achievement of customer satisfaction
Source: Compiled by the Researcher
70
2.5.2 Moderating Variables
Several researchers have explored the role of a number of interacting variables viz.
age of the organization, organizational size, sector, nature of the organization, life
cycle stage of the organization etc. in the relationship between role of agents and
performance (Andersen el al., 2007; Andolsek & Stebe, 2005; Budhwar, 2000b; Lawler et al., 1995; Perry & Kulik, 2008).
A number of scholars have identified organizational characteristics and contingent
variables such as size of the organization, technology adopted, age of organization,
ownership, life-cycle stage of organization as moderators in the studies on role of
agents (Budhwar, 2000a; Budhwar & Sparrow, 1997). Miller and Tolouse (1986)
have reported the impact of size of the firm on CEO role.
Gilley et al. (2004) studied the moderating effect of firm size on training and
payroll outsourcing vis-a-vis performance. Tremblay et al. (2008) studied the
relationship of HRO with size, industry and ownership structure (public versus
private). The results of the study revealed that smaller and larger organizations are
expected to outsource HR activities then medium-sized organizations. Galanaki et
al. (2008) studied the moderating effect of perceived benefits such as cost,
flexibility and quality benefits from outsourcing of training services on extent of
outsourcing in training services. The results revealed that availability of training
services in the external market moderates the perceived benefits from outsourcing
of training services. Chiang et al. (2010) reported the influence of organizational
characteristics such as ownership on degree and type of HR outsourcing. Table
2.7 provides a list of moderating variables identified by different researchers in the
studies linking role of internal and external agents in HRM with performance and
effectiveness.
Table 2.7: Moderating Variables Identified in Literature Researchers Moderating Variables
➢ Organizational characteristics • Size • Age • Numerical flexibility
Andolsek and Stebe (2005) • HRM strategies • HRM policies
> Situational factors • Sector • State
71
Researchers Moderating Variables
Andersen et al, (2007) > >
Firm size Industry sector
➢ Contingent variables • Age of the organization • Size of the organization • Life cycle stage of the
Budhwar (2000) organization (growth or turnaround)'
• Nature of the organization (Private or Public sector)
• Presence of unions • Presence of HR strategies
➢ Contingent variables • HR strategy • Flexible form of employment
and ownership • Life cycle stage of organization • Size
Budhwar & Sparrow (1997) • Age • Union membership
➢ Non-contingent factors • Institutional factors • National culture • Dynamic business environment • Business sector
➢ Size ➢ Age
Dany et ad., (2008) > Characteristics of the markets (growing, stable or declining )
➢ Industry Sector (Primary, Secondary, Tertiary)
> Perceived benefits from outsourcing training services
Galanaki et al. (2008) • Cost benefits • FlexibiIity benefits • Quality benefits
Organizational size > Organizational age ➢ Manufacturing ➢ Public sector
Perry and Kulik (2008) > Organization strategy > Dynamic growth > Extract profit ➢ Public sector ➢ Manufacturing > Organizational performance
Miller and Tolouse (1986) > Size
72
Researchers Moderating Variables ➢ Contextual variables
• Sector • Organizational size • Structure
Valverde et al. (2006) • Culture • History or age of organization • Environment • Technological system • Employee characteristics • HR function characteristics
➢ Size of the organization Benson & Littler (2002) > Organization age
> Industry > Organizational characteristics
Chiang et al. (2010) • Size • Ownership • Industry type
Klass et al. (2001) ➢ Size of the organization ➢ industry
Gilley et al. (2004) ➢ ➢
Firm size Firm age
Gilley & Rasheed (2000) ➢ Organization age ➢ Size
Tremblay et al. (2008) ➢ Industry and 9 Ownership structure (public versus
private). Source: Compiled by the Researcher
a.5.3 Mediating Variables
Previous studies on role of internal and external agents have indicated the indirect
•elationship between the role of internal and external agents in HRM and
ffectiveness of HRM (Guest & ' Conway, 2011; Hope Hailey et al., 2005). For
nstance, Larsen and Brewster (2003) reported the possible outcome of line
nanagers' involvement in HR practices such as effects on the size and shape of
{R department; effects on the shape of the organization and effects on the shape
End role of HR department, besides enhancing organizational effectiveness
'Schuler, 1990).
ieveral indicators of status of HRM have been identified in different research
studies viz, position of HR departments, representation of HR department at board
.evel, position and responsibility of HR executives, HR executives' role in
73
strategic decisions, general managerial training to HR executives , relationship of
HR executives with CEO (e.g. Budhwar, 2000b; Budhwar & Boyne; 2004; Green
et al. 2006; Hope-Halley et al. 1997; Mayrhofer & Brewster, 2005; Sheehan, 2005;
Teo & Crawford, 2005; Truss, 2003; Wood, 1995).
2.6 Internal and External Agents in HRM: An Indian Perspective
While most of the studies on role of internal and external agents vis-a-vis HRM
have been conducted in the Western world (e.g. Finegold & Frenkel 2006; Gratton
et al., 1999; Larsen & Brewster, 2003; Mahoney & Brewster, 2002; Papalexandris
& Panayotopoulou, 2005; Renwick & McNeil, 2002; Shen, 2005; Valverde et al.,
2006; Whittaker, 1990), the role of these agents remains largely unexplored in Asia
and more specifically in India except for a few studies (e.g. Azmi, 2011; Budhwar
& Sparrow, 1997; Khatri & Budhwar, 2002; Saha, 2005; Singh, 2009; Zhu et al.,
2008).
Emerging markets across the globe are the drivers of economic growth, with lower
operating costs and rapidly growing markets that are hard to match in more
developed economies. The focus of multinational corporations- has been to move
business operations to Asian countries, particularly India. With a growing
consumer base and a rapidly advancing economy, India is regarded as one of the
most valuable emerging markets (Budhwar, 2001).
In India, economic reforms have attracted a Iarge number of multinationals as a
result of which there is paradigm shift in the HRM scenario. Moreover, India is
witnessing unparalleled growth and its economy is progressing at a rapid pace
(Budhwar & Varrna, 2010; Grossman, 2008). These developments in the Indian
economy have prompted global institutions like World Bank to depict that India
will turn out to be the world's fourth Iargest economy by 2020. This growth has
fuelled numerous HR challenges for business organizations in India (Sodhi, 1994;
Venkata Ratnam, 1995).
Owing to the changes in the business landscape in India, companies are shifting
their attention towards more and more HR-centric approaches. Consequently, the
role of agents in HRM is also becoming increasingly evident. A few empirical
evidences have emerged from time to time supporting this contention. Budhwar }
74
and Sparrow (1997) analyzed the degree of devolvement of responsibility for HRM
to line managers in India. A number of contingent measures and organizational
practices were found to determine the level of devolvement in Indian organizations
which showed similarities with UK, Italy and Germany.
Bhatnagar and Sharma (2004) investigated line managers' perception of strategic
HR roles. Findings of the study show that there was no difference in the perception
of the strategic partner role among line managers of public sector and multinational
firms. However significant difference existed in the perception of HR mangers and
line managers.
Srimannarayana (2010) conducted an empirical study to evaluate the level of
responsibility of line managers in HR activities. The results reveal that line
managers have moderate responsibility for all HR functions. The level of
responsibility of line management seems to be more in performance management
and training and development related activities and less in compensation related
activities. On the basis of ownership of the organizations, nature of business,
length of service and functional area of line managers significant differences exists
for certain HR activities.
Gopalakrishnan (2008) has argued for placing HR on line managers' agendas. He
contends that the line must understand that their main job is to manage people. HR
should help managers to rediscover how to manage. Managers would need
guidance to reconnect with the people and HR can help them fulfil this role.
Aggarwal (2010) analyzed the working relationship between line and human
resource in different organizations across variety of sectors in India. HR-line
relations are average to low in most organizations, however, there are areas where
both value the roles played by each other. Azmi (2010) explored the relationship
between devolution of HRM and organizational performance in India. The findings
of the study revealed that devolution of HRM had a significant, direct and positive
impact on organizational performance.
Azmi (2011) talked about importance of top managers' training in HRM practices
for exploring its relationship with HR practices and strategy. Additionally, Azmi's
study delves into a number of issues such as role of top management in HRM and
uniformity of HR activities with organizational vision etc.
f41
Budhwar and Sparrow (1997) reported the importance of personnel representation
at board level in the integration of personnel function with corporate strategy.
Moreover, they also stressed on greater interaction between top management and
HR department so as to ensure that people related matters are given priority.
Role of external agents in HRM has recently received ample research attention in
India. Across the globe the use and importance of HR outsourcing varies.
Variations may be because of the size of the businesses, the degree of
sophistication of the HR function, the extent of development of the HR
outsourcing market, cultural norms, employment regulations and labour market
characteristics in specific countries and regions. The general trends towards HRO
reveal that the use is much less in Asian countries than in Europe and USA. A
major reason for low uptake of HRO and shared service activities among Asian
countries is the perceived poor quality of service and competency level of
consultants in the market and the associated lack of options. Concerns about data
security and loss of management control are also important reasons for not
outsourcing. The majority of outsourcing user firms in the Asia region appears to
be MNCs.. HR outsourcing services providers' clients in India include GE Capital,
Ford Motors, Hyundai Motors, HSBC and other companies.
Result. of HR outsourcing in Asia-Pacific online survey by Hewitt way back in
June 2002 with respect to the Indian market reveals three models of outsourcing
viz.
a) Outsourcing of the complete HR function - more prevalent among foreign
companies that have established operations in India.
b) Outsourced expertise — where staff expertise is provided as an outsourced
service rather than processing services, observed particularly among small and
medium sized companies that find difficulty retaining skilled, senior HR staff.
c) The outsourcing of HR processes, including payroll (inclusive of timesheets
processing, salary, pay slips, issuance of checks, deduction, computation etc)
and benefits processing.
In the Indian context, the role of external agents in HRM is explored in several
studies. For instance, Saha (2005) conducted a study on HR outsourcing and
concluded that in order to gain competitive advantage, multinational corporations
76
are realizing the importance of outsourcing their entire HR function. In addition to
this, several operational and strategic rationales are identified for HR outsourcing
like need for specialised expertise, HR information technology, cost savings,
vendor efficiencies and service, firm's HR capacity, reduction of risk, to improve
the overall business performance to achieve competitive advantage.
Singh (2009) reviewed the scope and development of HRO in India. The study
further explored various types of HR outsourcing and rationale for outsourcing
human resource functions. In India, business organizations are outsourcing a range
of HR activities such as recruitment, compensation etc. Chiamsiri et al.'s (2005)
study focused on the concept of offshore outsourcing by giving an overview of key
information technology enabled services outsourced in India. In addition to this,
the study looks at the potential changes in nature of the services outsourced in
India and issues related to HRM approach.
Seth and Sethi (2011) studied various types of HR outsourcing and the factors that
should be considered before outsourcing of different HR activities. The results of
the study revealed that the decision of HR outsourcing is dependent on factors like
affordability, flexibility, availability of adequate resources and acceptability. In
addition to this, the study also suggests pre-requisites for successfully carrying out
HR outsourcing.
77
CHAPTER 3: PROBLEM AREAS AND RESEARCH GAP
3.1 Focus on the Role of Individual Agents 3.2 Focus on Prescriptive Studies 3.3 Lack of Studies on Outcomes of Role of Agents in HRWI 3.4 Focus on Qualitative Methodology 3.5 Paucity of Empirical Studies 3.6 Small Sample Size-Based Studies 3.7 Low Response Rate in Existing Studies 3.8 Focus on Manufacturing Sector 3.9 Lack of Reliability and Validity of Research Instruments 3.10 Paucity of Studies in the Indian Context
3
CHAPTER 3: PROBLEM AREAS AND RESEARCH GAP 1'
Chapter Overview
This chapter seeks to identify the research gaps in the existing literature on the role
of internal and external agents viz. Iine managers, top management and external
service providers in HRM. It tries to indicate the problem areas existing in the
available literature. These problem areas and gaps relate to both theoretical and
empirical perspectives on role of agents.
3.1 Focus on the Role of Individual Agents
Valverde et al. (2006) reported that HRIVI is not the sole responsibility of HR
departments but also of other agents. Thus, all managers are people managers and
there are many people involved in the HR function (Khatri & Budhwar, 2002;
Papalexandris & Panayotopoulou, 2005; Whittaker, 1990). These are both internal
and external agents. HRM is viewed as a partnership involving two or at most
three HRM agents (Mohrman & Lawler, 1999). Several research studies have
reported the role of line managers (Budhwar & Sparrow, 1997; Budhwar, 2000a,
2000b; Conway & Monks, 2010; Hutchison & Purcell, 2010; Srimannarayana,
2010; Valverde et al., 2006; Wood, 1995), top management (Finegold & Frenkel,
2006; Schuler & Jackson, 1999; Valverde et al., 2006) and external service providers (Cook, 1999; Cunningham & Hyman, 1999; Delmotte & Sels, 2008;
Klass et al., 2001; Redman & Allen, 1993; Valverde et al., 2006) in people
management activities.
Valverde et al. (2006) explored the role of both internal as well as external agents
in HRM. Barring this, the researcher did not come across any study in which the
role of all the three agents has been explored comprehensively. Most studies
usually focus on just one of the agents or, at most, on two agents. There is no
developed literature incorporating the study of all agents (Valverde et al., 2006).
Most researchers in the area have independently explored the role of a single agent
vis-a-vis HRM (e.g. Budhwar & Sparrow, 1997; Budhwar, 2000b; Cook, 1999;
78
Conway & Monks, 2010; Delmotte & Sels, 2008; Redman & Allen, 1993; Schuler
& Jackson, 1999; Srimannarayana, 2010). Despite this, even on individual basis,
there is a dearth of studies. Concurrently, the role of line managers, top
management and external service providers in FIRM has not been explored in an
in-depth manner in prior studies. For instance, different studies have reported the
scarcity of academic-oriented research on issues related to HR outsourcing in
comparison to the growing literature on outsourcing as well as exploratory
evidence of key drivers that influence organizations to resort to external providers
(Cooke et al., 2005; Shen, 2005). Thus, an investigation into the role of internal
and external agents in HRM is a research issue that needs to be addressed.
3.2 Focus on Prescriptive Studies
The literature is more prescriptive or normative than descriptive (Valverde et al.,
2006). Thus, there is greater emphasis on what various agents should do to manage
people, as opposed to establishing what they actually do (Grafton et al., 1999). There is a paucity of studies that can give a descriptive picture of the current
scenario of role of agents in HRM. Often this literature lacks any strong evidence
(Jackson & Schuler, 1999). Also, there is a tendency to concentrate on the wider
concept of "role" (including activities, responsibilities, power relationships,
influence and position etc.) with little focus on specifying which particular
responsibilities are allocated to each agent (Legge, 1995).
3.3 Lack of Studies on Outcomes of Role of Agents in HRM
Although some studies have linked the role of agents with performance outcomes,
there is still a dearth of empirical findings on outcomes of role of agents. Hall and
Torrington (1998) and Perry and Kulik (2008) opined that the need to study the
involvement of agents and effectiveness of people management as the focus of the
prior studies are on their role in HRM. Conway and Monks' (2010) study indicated
the role of line managers in HR activities and contribution to organizational
performance. However, these studies are few and far between. The focus of most
studies has remained on the role of agents and the impact of role of all the agents
has not been explored.
79
3.4 Focus on Qualitative Methodology
There is a paucity of empirical studies in the area since most of the previous
studies are based on qualitative methodology, primarily case-based studies (e.g.
Bond & McCracken, 2005; Bond & Wise, 2003; Cascon-Pereira et al., 2006;
Currie & Proctor, 2001; Finegold & FrenkeI, 2006; Gennard & Kelly, 1997; Harris
et al., 2002; Hutchison & Purcell, 2010; McConville, 2006; Renwick, 2000;
Renwick, 2003; Thornhill & Saunders, 1998; Whittaker & Marchington, 2003;
Watson et al., 2007). Consequently, there are no comprehensively developed
measures to study the role of line managers, top management and external service
providers in management of HR. The scarcity of studies in the area has led to
methodological problems in measuring the role of agents in FIRM. Dany et al.
(2008) pointed out the need for more empirical studies in the area.
3.5 Paucity of Empirical Studies
The role of internal and external agents in management of HR has been relatively
under researched both in developing theory and analyzing empirical data as most
of the studies are based on qualitative methodology (e.g. Bond & McCracken,
2005; Conway & Monks, 2010; Dick & Hyde, 2006; Finegold & Frenkel, 2006;
Harris et al., 2002). Empirical evidences are limited. (e.g. Budhwar, 2000b;
Budhwar & Sparrow, I997; Dany et al., 2008; Hsu & Leat, 2000; Srimannarayana,
2010), Busi and McIvor (2008) pointed out that there is dearth' of empirical
measures to analyze the business transformation activities with reference to
external service providers.
Since most of the studies are theoretical in nature, as a result of which, there are no
testable theoretical models that deal with examination of the roles of internal and
external agents in management of HR giving rise to various methodological issues.
The absence of models give rise to problems in developing strong measures since
models provides support to structure the scattered viewpoint. As Wright and
McMahan (1992) reported, a well-developed model allows for testing and revision
to increase its accuracy. Additionally, this would have implications for the
methodological design of the study. Thus, there is a need for more empirical
:1
evidences to unearth the actual roles being played by the three agents viz, line
managers, top management and external service providers in HRM,
3.6 Small Sample Size-Based Studies
Research in the area suffers from small sample size related problems that make the
study less generalizable. For example, the sample size in different studies has been
as low as nine (Gratton et al., 1999), thirteen (Whittaker & Marchington, 2003),
twenty-eight (Gennard & KeIly, 1997), thirty-eight (Cunningham et al., 1996),
forty-eight (Conway & Monks, 2010), ninety-three (Budhwar, 2000a), ninety-four
(Gilley et al., 2004), one hundred thirty five (Wood, 1995).
Small sample size provides a limited view of population and has an adverse effect
on the statistical results. It can lead to erroneous conclusions, thus, making the
study results less generalizable. Small sample size represents a Iimited number of
companies and therefore, provides a narrow view of cross-section of industries.
3.7 Low Response Rate in Existing Studies
One of the important issues in research in this area is related to response rate.
Research on role of agents usually suffers from low response rate. Review of
different researches in the area reveals response rate e.g. 18.6% (Budhwar, 2000a,
2000b), 25% (Fenton-O'Creevy, 2001), 17% (Gilley et al., 2004), 8,56% (Hall &
Torrington, 1998), 24% (Khatri, 2000), 22.7% (Klass et al., 1999, 2001), 17%
(Larsen & Brewster, 2003), 5% (Perry & Kulik, 2008), 19% (Tremblay et al., 2008),10.5% (Valverde et al., 2006), 16% (Wood,1995). Low response rate usually
leads to non response bias related problems.
3.8 Focus on Manufacturing Sector
Majority of the researchers in the area have focused on the manufacturing sector
(Chand & Katou, 2007; Hsu & Leat, 2000; Perry & Kulik, 2008). For instance,
Budhwar (2000a, 2000b) and Budhwar and Sparrow (1997) focused on six
industries viz, food processing, plastics, steel, textiles, pharmaceuticals and
footwear. Gilley et al. (2004) investigated HR outsourcing and its relation with
81
organizational performance in manufacturing units. Although some studies have
focused on the role of agents in the service sector, but these studies are only few
and far between (Sisson, 1993).
3.9 Lack of Reliability and Validity of Research Instruments
Rigorous research methodology is necessary for the development of a reliable and
valid instrument in order to enhance the process of theory building (Yin, 1994). As
most of the studies are based on qualitative methodology (Bond & McCracken,
2005; Conway & Monks, 2010; Dick & Hyde, 2006; Finegold & Frenkel, 2006;
Harris et al., 2002), the issue of reliability and validity are not addressed. Even in
the case of empirical studies (e.g. Budhwar, 2000a; Budhwar & Sparrow, 1997;
Dany et al., 2008; Hsu & Leat, 2000; Srimannarayana, 2010), the issue of
reliability and validity are not addressed appropriately.
3.10 Paucity of Studies in the Indian Context
There is a dearth of studies on the theme in the Indian context. Most of the studies
are based in Europe and the UK (e.g. Bond & Wise, 2003; Cunningham & Hyman,
1999; Harris et al., 2002; Hoogendoorn & Brewster, 1992; McGovern et al., 1997;
Renwick, 2003; Whittaker & Marchington, 2003). Very few studies have been
reported so far on role of agents in HRM in the Indian context. Except for certain
studies (Agrawal, 2010; Bhatnagar & Sharma, 2004; Budhwar & Sparrow, 1997;
Srimannarayana, 2010), most studies focus on the western context (Cantrell &
Miele, 2007; Cunningham & Hyman, 1995; Gibb, 2003; Larsen & Brewster, 2003;
MacNeil, 2003; Morley et al., 2006; Renwick, 2003; Thornhill & Saunders, 1908;
Whittaker & Marchington, 2003). Thus, there is a real need to explore the issue in Indian settings, keeping in mind the fact that India is a fast-growing economy with
an emerging HR landscape.
82
CHAPTER 4: RESEARCH METHODOLOGY
4.1 Need for Research 4.2 Research Objectives 4.3 Research Design 4.4 Research Constructs and Measures
4.4.1 Independent Variables: Measures of Role 4.4.2 Dependent Variable: Effectiveness of HRM 4.4.3 Mediating Variable: Status of HRM 4.4.4 Moderating Variable: Organizational Profile
4.5 Questionnaire Development Process 4.5.1 Stages of Questionnaire Development 4.5.2 Translation Validity: Face and Content Validity
4.6 Research Instrument/Questionnaire 4.7 Sampling Procedure
4.7.1 Target Population 4.7.1.1 Sampling Unit 4.7.1.2 Sampling Element
4.7.2 Sampling Frame 4.7.3 Sampling Approach and Sample Size
4.8 Questionnaire Administration and Data Collection 4.9 Conceptual Models of Research 4.10 Research Hypotheses 4.11 Methods of Analysis 4.12 Limitations of the Study
CHAPTER 4: RESEARCH METHODOLOGY
Chapter Overview
This chapter provides a brief description of the need for research and study
objectives. It gives details of the research design and methodology. A discussion on
study constructs and items, instrument development and validity concerns, sampling
procedure and questionnaire administration is done which is followed by
specification of conceptual research models considered for the study along with
research hypotheses. The chapter ends with a brief outline of the methods of analysis
and the limitations of the study.
4.1 Need for Research
There were several reasons that prompted this research:
❖ HR is seen as potential contributors to the creation and realization of the
organization's goals (Jackson & Schuler, 2000) and constitutes an
important source of competitive advantage for the organization (Wright &
McMahan, 1992). However, there are limited empirical studies on the role
of internal agents viz, top management (e.g. Fisher & Dowling, .1999;
Heneman et al., 2000; Khilji, 2002) and line managers (e.g. Brewster et al.,
1997; Budhwar, 2000a; Budhwar & Sparrow, 1997) as well as external
agents viz, external service providers (e.g. Galanaki & Papalexandris,
2005) in management of HR. As a result of this, no established measures
are available. Hence, a need was felt to empirically test a model that
incorporates the scattered viewpoints regarding the role of internal and
external agents in management of HR.
❖ The researcher was motivated by the fact that an empirical study on role of
different actors (i.e. internal and external agents) in management of HR will
be useful to organizations to gain an insight into restructuring the HR
processes and speeding up decision-making (Brewster & Larsen, 2000;
Cunningham & Hyman, 1995; Cunningham & Hyman, 1999; Gibb, 2003;
Renwick, 2000).
83
❖ An analysis of the literature in the field reveals only a few studies in the
Indian context e.g. Agrawal (2010), Bhatnagar and Sharma (2004), Budhwar
and Sparrow (1997), Srimannarayana (2010) and that too on single agents.
:• The researcher did not come across any study in the global context as well as
in the Indian context in which the role of all agents has been studied together
(Valverde et al., 2006) Thus, an investigation into the role of internal and
external agents in HRM is a research issue that is both timely and relevant.
•+• The researcher did not come across any study that explores both the
involvement of internal and external agents in HR and its relationship with
effectiveness and performance. Consequently, a need was felt to take up both
the issues for study.
•S Although some instruments have been developed to study the role of internal
and external agents in HRM independently, a need was felt to develop a
reliable and valid instrument to collectively study the internal and external
agents' level of involvement in different HR activities.
4.2 Research Objectives
The broad objective and sub-objectives of the study are as follows:
Broad Objective
The study endeavors to address the following broad objective:
To develop a reliable and valid instrument for measuring the role of top
management, line managers (i.e. internal agents) and external service providers
(i.e. external agents) in management of HR and to investigate the impact of their role
on the effectiveness of HRM and status of HRM. The study also seeks to establish
differences as well as association between organizational profile and various
dimensions of the above roles.
Sub-objectives
The broad objective can be divided into four categories of sub-objectives:
84
Category I: Developing an instrument for measuring the role of internal and
external agents in HRM
❖ To develop a reliable and valid instrument for measuring various
dimensions of role of top management, line managers and external service
providers in management of HR.
Category II: Investigating the impact of role of internal and external agents in
HRM
(a) Investigating the impact of role of top management in HRM
•:• To investigate the impact of role of top management in HRM on the
effectiveness of HRM.
❖ To investigate the impact of role of top management in HRM on the status
of HRM
(b) Investigating the impact of role of line managers in HRM
•.• To investigate the impact of role of line managers in HRM on the effectiveness of HRM
❖ To investigate the impact of role of line managers in HRM on the status of
HRM
(c) Investigating the impact of role of external agents in HRM
❖ To investigate the impact of role of external service providers in HRM. on
the effectiveness of HRM
❖ To investigate the impact of role of external service providers in HRM on
the status of HRM -
(d) Investigating the impact of status of HRM on the effectiveness of HRM
•,• To investigate the impact of the status of HRM on the effectiveness of HRM
Category III: Assessing the differences between company type i.e. sector
(manufacturing and service) and company size (small, medium and large
organizations) on the role of internal and external agents in HRM
85
•;+ To assess differences in role of top management in HRM on the basis of
company sector (i.e. manufacturing and service).
•.+ To assess differences in role of line managers in HRM on the basis of company sector (i.e. manufacturing and service).
❖ To assess differences in role of external servi* providers in HRM on the basis of company sector (i.e. manufacturing and service).
❖ To assess, differences in role of top management in HRM on the basis of company size (small, medium and Iarge organizations).
•,• To assess differences in role of line managers in HRM on the basis of company size (small, medium and large organizations).
W- ❖ To assess differences in role of external service providers in HRM on the
basis of company size (small, medium and large organizations).
Category IV: Establishing association between company type i.e. sector
(manufacturing and service) and company size (small, medium and large organizations) with the role of internal and external agents in HRM.
❖ To establish association between the role of top management in HRM and
company sector (i.e. manufacturing and service).
❖ To establish association between the role of line managers in HRM and
company sector (i.e. manufacturing and service).
•3 To establish association between the role of external service providers in
HRM and company sector (i.e. manufacturing and service).
•2• To establish association between the role of top management in HRM and
company size (i.e. small, medium and large organizations).
••• To establish association between the role of line managers in HRM and
company size (i.e. small, medium and large organizations).
❖ To establish association between the role of external service providers in
HRM and company size (i.e. small, medium and large organizations).
4.3 Research Design
Mainly research designs are of two types: conclusive research design and
exploratory research design (Cooper & Schindler, 2003). In conclusive research
design, information needed is clearly defined to test specific hypotheses and
analyze the relationships. Moreover, in conclusive research design; research
process is formal and structured. Exhibit 4.1 illustrates the classification of
research design as suggested by Maihotra and Dash (2011).
Exhibit 4.1 Classification of Research Design
Research Design
Coiichisive Research Design
'I
F Descx ti edteseare
Cass tional Design
1 ~~~~r~g eg~~~st~e~ha~nal Des k
Exploratory Research Design
Causal Research
Longitudinal Design I
Multi Crass-Sectivaal
* Shaded boxes represent the design followed for the present research Source: Adapted from Malhotra, N. H & Dash, S. (2011). Marketing Research: An applied orientation. New Delhi: Pearson Education.
The shaded boxes suggest the path followed for the present research. The present
research is conclusive, descriptive and based on single cross-sectional design. In
accordance with Yin's (1994) suggestions, the current research attempts to decrease
any divergence with the help of a rigorous research methodology which is
necessary for the development of a reliable and valid instrument in order to boost
87
up the process of theory building. Quantative data was generated to test the research
hypotheses.
In order to collect the data on the various dimensions of the study, a research
instrument was designed based on extensive literature review. The, questionnaire
was pilot tested and after required changes, it was administered on the study
sample. The reliability and validity of the research instrument were established.
Data generated was then subject to analysis.
4.4 Research Constructs and Measures
Research construct and items related to both dependent and independent variables
were identified. In addition, mediating and moderating variables were also
considered in the study.
4.4.1 Independent Variables: Measures of Role
Valverde et al. (2006) argued that HRM is not the sole responsibility of HR
departments but also of other agents. These are both external and internal agents.
Thus, all managers are people managers and there are many people involved in the
HR function (Khatri & Budhwar, 2002; Papalexandris & Panayotopoulou, 2005;
Whittaker, 1990). Research studies have indicated the role of line managers
(Brewester & Larsen, 1992; Budhwar, 2000a, 2000b; Budhwar & Sparrow, 1997;
Casco'n-Pereira et al., 2006; Clark, 1998; Hall & Torrington, 1998; Legge,1995;
Lemmergaard, 2009; Papalexandris & Panayotopoulou, 2005; Renwick, 2000;
Valverde et ad., 2006), top management (Chung et al., 1987; Finegold & Frenkel,
2006; Harper, 1993; Jonas et al., 1990; Papalexandris & Panayotopoulou, 2005;
Penrose, 1959; Welbourne & Cyr, 1999) and external agents (Cook, 1999;
Galanaki & Papalexandris, 2005; Mahoney & Brewster, 2002; Papalexandris &
Panayotopoulou, 2005) in HRM but their degree of involvement varies with
respect to decision-making, process/activities and budgeting for different HRM
functions. Researchers in the area have pointed out the need to explore the role of
internal and external service providers with respect to decision-making capacity,
process/activities and budgeting for management of human resources (Casco'n-
Pereira et al,, 2006; Valverde et al., 2006). Moreover in the individual HR areas
88
too, decision-making and process/activities (Budhwar, 2000a; Budhwar &
Sparrow, 1997; Currie & Procter, 2001; Hall & Tarrington, 1998; McConville,
2006; Poole & Jenkins, 1997) have been assessed. In addition to this, some
researchers such as McConville and Holden (1999) and Casco!n-Pereira et al. (2006) have also explored the dimension of financial power and pointed out its
importance in performing HR tasks. Hall and Tarrington (1998) opined that
budgetary controls have an important effect vis-a-vis involvement in HR activities.
Prior studies have recognized the role of line managers in decision-making (Bond
at al., 2002; Hall & Torrington, 1998; Larsen & Brewster, 2003) and
process/activities (Brewster et al., 2004; Fombrun et al. 1994; Guest, 1987; McConville, 2006; Nehles et al., 2006; Thornhill & Saunders, 1998). Hutchinson
(1995) and Industrial Relation Survey (1995) reported increasing line managers
involvement in recruitment, discipline and training decisions. Papalexandris &
Panayotopoulou (2005) opined that CEOs, line managers and external service
providers participation and decision-making in HR activities have helped the
organizations to gain competitive advantage. Thus, it can be seen from the above
discussion that decision-making, process/activities and budgeting vis-a-vis HRM
are the major dimensions of interest in the studies on the role of top management,
line managers and external service providers in HRM.
The above three dimensions have been explored in light of individual as well as
groups of HR activities. Some of the studies in the individual HR areas where there
is involvement of Iine managers, top management and external service providers
include performance appraisal (Andersen et al., 2007; Redman, 2001), pay (Currie
& Procter, 2001; Hope-Hailey at al., 1997), family leave policies (Bond & Wise,
2003), employee engagement (Fenton-O'Creevy, 2001; Marchington, 2001),
identification of training needs (Green at al., 2006), counseling (Nixon & Carroll,
1994), absence management (Dunn & Wilkinson, 2002), training and development
(Heraty & Morley,1995; Lever, 1997), training (Ardichvili & Gasparishvili, 2001;
Woodall at al., 2002), human resource development (Watson & MaxweIl, 2007),
industrial relations, health & safety (Hope-Hailey at al., 1997), recruitment &
selection (Hope-Hailey at al., 1997; Wood, 1995), workforce expansion &
reduction (Kramar & Lake, 1998) and reward management (Brown & Purcell,
2007). However, several studies have focused on more than one HRM function
(e.g. Alewell et al., 2009; Andolsek & Stebe, 2005; Budhwar, 2000b; Casco'n-
Pereira et al., 2006; Cook, 1999; Cunningham & Hyman, 1995; Gautam & Davis,
2007; Hall & Torrington, 1998; Mahoney & Brewster, 2002; Papalexandris et al.,
2001; Shaw & Fairhurst, 1997; Smith et al., 2006; Srimannarayana, 2010; Watson
et al., 2007). For instance, the main focus of the researchers are on the following
HRM functions i.e. HR planning, recruitment and selection, training &
development, pay and benefits, performance appraisal, workforce expansion or
reduction and industrial relations (e.g. Alewell et al., 2009; Budhwar, 2000a;
Casco'n-Pereira et al., 2006 ; Larsen & Brewster, 2003; Mahoney & Brewster,
2002; Papalexandris et al., 2001; Srimannarayana, 2010).
Thus, it can be concluded that most studies on role of internal and external agents
in HRM have explored the involvement of top management, line managers and
external service providers with respect to the dimensions decision-making,
budgeting and process/activities vis-a-vis HRM. Therefore in this research too; role
of internal and external agents was studied on the basis of their involvement in
decision-making, process/activities and budgeting vis-a-vis HRM. The dimension
decision-making seeks to explore the level of involvement of internal and external
agents in HRM decisions and policy making. The second dimension i.e.
process/activities aims at exploring the level of involvement of internal and
external agents in actual day-to-day HR activities. The third dimension i.e.
budgeting focuses on the level of involvement of internal and external agents in
financial issues vis-a-vis HRM.
The above three dimensions were explored in the present study with reference to
the HRM functions of HR planning, recruitment and selection, training and
development, pay management, performance appraisal and industrial relations.
Thus in the present study, the role of internal agents i.e. top management and line
managers and external agents i.e. external service providers was explored on the
following dimensions viz, decision-making, process/activities and budgeting vis-a-vis HRM functions of HR planning, recruitment and selection, training and
development, pay management, performance appraisal and industrial relations.
The independent variables considered for the study were:
❖ Top management involvement in decision-making vis-a-vis HRM
❖ Top management involvement in process/activities vis-a-vis HRM
❖ Top management involvement in budgeting vis-a-vis HRM
❖ Line managers involvement in decision-making vis-a-vis HRM
•:• Line managers involvement in process/activities vis-a-vis HRM ❖ Line managers involvement in budgeting vis-a-vis HRM
❖ External service providers involvement in decision-making vis-a-vis HRM
❖ External service providers involvement in process/activities vis-a-vis HRM
❖ External service providers involvement in budgeting vis-a-vis HRM
4.4.2 Dependent Variable: Effectiveness of HRM
As a result of changes in the business environment, people management issues are
becoming business issues and internal and external agents are reaching out to take
control over the HR function. A number of research studies have indicated the
positive impact of involvement of top management, line managers and external
service providers on the overall effectiveness of HRM (Budhwar, 2000a, 2000b;
Budhwar & Sparrow, 1997; Valverde et al_, 2006). The new role of line managers
has led to enhanced organizational effectiveness in addressing people management
issues (Schuler, 1990).
In order to study the influence of degree of involvement of top management, line
managers and external service providers in HR activities, the effectiveness of HR
function was considered as the dependent variable. Ferris et al. (1999) reveal that
there are two perspectives of effectiveness of HRM that are in need of theoretical
and empirical attention: (1) the effectiveness with which HRM policies and
practices are implemented; and (2) the effectiveness of these practices in producing
desired results. Effectiveness of HRM has been explored as a construct by several
researchers (Teo & Crawford, 2005; Yusoffet al:, 2009).
Teo and Crawford (2005) have tested three measures of effectiveness of HRM
which were used in this study too:
:• Influential Effectiveness: This item measures the influence of HR
department on the organization.
91
:• Relationship Effectiveness: This item measures the relationships of HR
department with major stakeholder.
4. Overall Effectiveness: This item measures the overall effectiveness of HR
department.
4.4.3 Mediating Variable: Status of HRM
Edwards and Lambert (2007) and Frazier et al. (2004) explained that mediator is
an intervening variable that explains the relation between exogenous and
endogenous variables. Mediating variable helps to identify the mechanism through
which the change occurs (Tang et al., 2009). Prior studies have indicated that there
is an indirect relationship between the role of internal (i.e. line managers and top
management) and external agents (i.e. external service providers) in management
of human resources and effectiveness of HRM (Guest & Conway, 2011; Hope
Hailey et al., 2005; Valverde et al., 2006). It is assumed that there are variables
that mediate the relationship between the role of internal and external agents in
HRM and effectiveness of HRM. For instance, Larsen and Brewster's (2003) study
have indicated the likely implications of line manager involvement in HRM as
effects on the size and shape of HR department; effects on the shape of the
organization and effects on the shape and role of HR department, besides
enhancing organizational effectiveness (Schuler, 1990).
In order to study the impact, of role of internal and external agents in HRM on
effectiveness of HRM, status of HRM was seen as a mediating variable. Various
indicators of status of HRM have been identified by researchers (e.g. Budhwar,
2000a, 2000b; Budhwar & Boyne; 2004; Budhwar & Sparrow, 1997; Green et al. 2006; Hope-Hailey et al. 1997; Kelly & Gennard, 1996; Mayrhofer & Brewster,
2005; Sheehan, 2005; Teo & Crawford, 2005; Truss, 2003; Wood, 1995).
In the current study, status of HRM was measured through six items focusing on
whether the HR function had an important place in strategic affairs. It focuses on
issues like position of HR departments, representation of HR department at board
level, position and responsibility of HR executives, HR executives' role in
strategic decisions, relationship of HR executives with CEO, general managerial
training to HR executives etc.
4.4.4 Moderating Variable: Organizational Profile
Researchers have investigated the role of a number of moderating variables such as
size, sector, technology, ownership, nationality, life cycle stage, unionization (e.g.
Cohen & Pfeffer, 1986; Lawler et al., 1995; Shaw et. al., 1993; Snell, 1992) in
similar kinds of studies. Andersen et al. (2007) and Huselid (1995) have used firm
size and industry sector as control variables to study HR link with performance.
Budhwar and Sparrow (1997) have considered the nature of organization (private
and public sector); age of the organization; life cycle stage of organization (growth
or maturity); size of the organization.
For the present study, four dimensions of organizational characteristics were
deemed to be moderating variables viz, sector to which the company belongs
(manufacturing/service), ownership pattern (public sector i.e. companies owned by
the government/private sector i.e. companies owned by private players), country of
origin (Indian/Foreign) and the size of the company determined by number of
employees (smalllmedium/large). For classification of small, medium and large
organizations, Budhwar and Sparrow's (1997) criteria was followed i.e.
organizations with less than 1000 employees were considered small, those between
1001-5000 employees were considered medium and those with more than 5001
employees were considered large.
4.5 Questionnaire Development Process
The process of questionnaire development encompasses various stages from
identification of constructs/items from the literature to identifying the information
that is needed, wording and sequence of questions, structuring of questionnaire,
development of draft questionnaire, re-examination of draft questionnaire to pilot
testing for finalization of items (Churchill & lacobucci, 2002; Malhotra, 2007;
Malhotra & Dash, 2011). Moreover, the issue of validity associated with the
questionnaire development needs to be addressed during this process.
The present research followed the guidelines recommended by Churchill and
Iacobucci (2002), Malhotra (2007), Malhotra and Dash (2011) and Sekaran (2006)
for generating the questionnaire. Exhibit 4.2 reveals the questionnaire development
process of the present study.
Exhibit: 4.2: Flowchart Illustrating the Questionnaire Development Process
Stage 1 j
Identification of constructs/items
[Stage 2 Wording of questions
Stage 3 Sequence & arrangement of questions
Lsta 4 Structuring of scales
Stage 5 Development of draft questionnaire
Stage 6 Re-examination of stage 1-5
Stage 7 Pilot Testing
TStage 8 Finalization of questionnaire items, layout and physical characteristics of the questionnaire
Prepared by the Researcher
4.5.1 Stages of Questionnaire Development
Stagel: Identification of constructs/items: On the basis of an extensive literature
review, study constructs/measures were identified to specify the information that is
needed. Relevant content of the items was determined to ensure that every item
included in the questionnaire contributes to the information required.
Stage 2: Wording of questions: Selecting question wording is the most important
and critical part of the questionnaire development process. Poorly worded items
increase non-response (Malhotra & Dash, 2011) and ambiguous question wording
can create confusion or even shift the meaning of the construct and its items
(Huselid & Becker, 2000; Podsakoff et al., 2003). Researchers should design the
questionnaire items that capture the specific substantive focus of the HR
component being assessed (Arthur & Boyles, 2007). Therefore, proper question
94
wording guidelines as suggested by Malhotra and Dash (2011) were followed to
keep the items as simple, specific and objective as possible.
Stage 3: Sequence/arrangement of questions: In order to avoid common method
bias, items related to the independent variables should precede the items related to
dependent variable of the survey instrument (Podsakoff & Organ, 1986; Salancik
& Pfeffer, 1977). Thus, the questionnaire was structured in such a way so that the
items related to the independent variables i.e. involvement of internal and external
agents in decision-making, process/activities and budgeting preceded the items
related to status of HRM and effectiveness of HRM items.
Stage 4: Structuring of scale: In the present research, structured questions were
used and the responses were obtained on 5-point Likert scale anchored with end
points labeled as No Involvement (1) to High Involvement (5). For certain items, 5-
point scale anchored with end points labeled as Strongly Disagree (1) to Strongly
Agree (5) was also used. Five point scale has been commonly used by other
researchers in the area too (Budhwar, 2000a; Budhwar & Sparrow, 1997; Heraty &
Morley, 1995; Valverde et al., 2006).
Stage 5: Development of draft questionnaire: A preliminary draft of the
questionnaire was prepared keeping in view the constructs/measures identified in
Stage I as well as the subsequent stages of the questionnaire development process.
Stage 6: Re-examination of stage 1-5: Modification in draft questionnaire on the
basis of inputs and suggestions from academicians/practitioners: Before moving
for pilot testing of the questionnaire/instrument, draft questionnaire was reviewed
in the light of the guidelines recommended by Churchill and Iacobucci (2002),
Malhotra (2007) and Malhotra and Dash (2011). This stage involved a re-
examination of stage 1-5 and the main objective was to incorporate the changes in
draft questionnaire if necessary, on the basis of inputs and suggestions from
academicians and practitioners as well as to ensure the translation validity (i.e.
content and face validity) of the instrument.
When the initial draft questionnaire was conceptually developed, the researcher
approached three other senior researchers in the area with a request to propose
items for the questionnaire which were then broadly compared with the items in
the draft questionnaire and modifications were made accordingly. After
incorporating the changes in the draft questionnaire, it was reviewed by four
researchers/academicians; two from HRM area and the other two who were
methodology experts. The purpose was to ensure that the questionnaire possessed
translation validity (discussed in detail in next sub-section). This re-examination of
the instrument provided useful insights in addressing the weaknesses of the
instrument and helped in addressing the issue of translation validity.
Stage 7: Pilot testing; This stage of the questionnaire development process deals
with the pilot testing or pretesting with actual respondents (i.e. HR managers in
this case). It is noted that languages used by people from different backgrounds
(i.e. academicians and potential informants) may be different, so the questionnaire
was administered on HR managers to assess their feedback. HR managers were
asked not only to give their responses but also to provide their critical feedback of
the questionnaire in general and scale items in particular. In all fifteen HR
managers were targeted at this stage. The basic objective was to capture any
ambiguities in questionnaire wording, question structure, sequence/arrangement of
questions, layout and physical characteristics of the questionnaire and other
difficulties encountered by the respondents in completing the questionnaire to
ensure the translation validity (i.e. content and face validity).
Stage 8: Finalization of questionnaire items, layout and physical characteristics
of the questionnaire: The last stage in the questionnaire development process
deals with the finalization of items based on the inputs obtained during pilot testing
stage. Consequently, necessary changes were incorporated mainly in question
structure and sequence/arrangement of questions. Suggestions of Podsakoff et al.
(2003) of separate scale formats for predictor variables (i.e. the role of internal and
external agents) and criterion variables (i.e. effectiveness of HRM) have been used
to reduce the biases. In addition to this, the researcher followed the instructions of
Malhotra, (2007) and Malhotra and Dash (2011) to address the. issue of formatting,
spacing and positioning of the questions. Besides, the questionnaire colour was
given due consideration to make the questionnaire attractive and distinct as the
questionnaire colour has an effect on the response rate (Bender, 1957; Fox et al.,
1988; Jobber & Sanderson, 1983; Phipps et al., 1991). Keeping this in view, the
researcher has used different colour combinations (Bender, 1957) for both
GIB
electronic and hard forms of the questionnaire. The hard form of the final
questionnaire was printed in card-form.
Assessing validity is an essential part of questionnaire/instrument development
process because it provides information about the accuracy of measurement,
stability and consistency of the results being obtained (Adams et al., 2007; Colton
& Covert, 2007; Cooper & Schindler, 2003; Hair et al., 2008; Malhotra, 2007;
Malhotra & Dash, 2011).
4.5.2 Translation Validity: Face and Content Validity
A scale has validity if it is measuring the concept that it was intended to measure
(Bagozzi, 1981; Sekaran, 2006). Broadly, there are two types of validity i.e.
theoretical and empirical validity. Empirical validity includes construct validity
(i.e. convergent, discriminant and nomological validity) and criterion validity and
is assessed after data collection (discussed in detail in next chapter) however,
translation validity includes face and content validity which was determined during
instrument development (Garver & Mentzer, 1999). Translation validity focuses on
the operationalization of the construct and aims to assess the degree to which
constructs are precisely translated into question items (Trochim, 2009). Translation
validity is of two types: 1) face and 2) content validity.
Face validity subjectively assesses the correspondence* between the individual
items and the concept to see if the operationalization of construct on its face
appears to be a good translation of the construct or not (Trochim, 2009) and if it
`looks like' it is going to measure what it is supposed to measure (Ahmad &
Schroeder, 2003; Colton & Covert, 2007).
Content - validity checks the operationalization against the related content domain
for the construct (Trochim, 2009) and depends on how well the researchers created
measurement items using the appropriate literature (Nunnally, 1978). An
instrument has content validity if the items sufficiently span the scope of the
construct (Churchill, 1979; Stratman & Roth, 2002) and items of an instrument are
derived from comprehensive analysis of literature and discussed with experts
(Bohrnstedt, 1983; Shin et al., 2000; Stratman & Roth, 2002). Since it is
judgemental in nature and not open to statistical evaluation, therefore, researcher
97
insight must be applied (Cooper & Schindler, 2006; Garver & Mentzer, 1999). The
scales must first be tested for content validity before any scale refinement is
undertaken (Ahire et al., 1996; Anderson & Gerbing, 1988).
On the basis of an extensive literature review, an initial draft of questionnaire was
prepared. As suggested by Ahmad and Schroeder (2003), face validity of the
questionnaire was insured by requesting three different researchers to propose
items for the questionnaire as discussed in Stage 6 of questionnaire development
process. The items proposed by them were compared with the items in the draft
questionnaire which was then modified accordingly. Thereafter, four other
researchers/academicians were asked to review the questionnaire items and guess
what the questionnaire was intended to measure in order to ensure that the
questionnaire appeared reasonable and acceptable. This has also been discussed in
the previous sub-section. Besides this, changes were made in the question
structure/form of response, sequencefarrangement of questions, layout and physical
characteristics of the questionnaire based on the inputs obtained from pilot testing.
Thus, translation validity of the instrument/questionnaire was ensured.
4.6 Research Instrument/Questionnaire
The final survey instrument contained the following variables:
Exogenous/Independent Variables: The survey instrument consists of nine
independent variables measuring the role of internal and external agents in HRM:
❑ Top management involvement in decision-making vis-a-vis HRM (TDM) ❑ Top management involvement in process/activities vis-a-vis HRM (TPA) U Top management involvement in budgeting vis-a-vis HRM (TBU) ❑ Line managers involvement in decision-making vis-a-vis HRM (LDM) ❑ Line managers involvement in process/activities vis-a-vis HRM (LPA) U Line managers involvement in budgeting vis-a-vis HRM (LBU) ❑ External service providers involvement in decision-making vis-a-vis HRM
(EDM) U External service providers involvement in process/activities vis-a-vis HRM
(EPA) ❑ External service providers involvement in budgeting vis-a-vis HRM (EBU)
All the nine exogenous variables were measured with six items scale each. The six
items scale comprised of six HRM - functions. Each HRM function was measured
with single item scale. Thus, each of the above nine variables were examined on a
six item scale with respect to following HRM functions:
■ HR Planning ■ Recruitment & Selection ■ Training & Development ■ Pay Management
■ Performance Appraisal Industrial Relations
Endogenous Variable/Dependent Variable: The endogenous/dependent variable
considered for the study was:
❑ Effectiveness of FIRM (EFF): Three-item scale
■ Influential Effectiveness ■ Relationship Effectiveness ■ Overall Effectiveness
Mediating Variable: The mediating variable considered for the study was:
❑ Status of HRM (STA): Six-item scale
Moderating Variable: The moderating variable considered for the study was:
❑ Organizational Profile
■ Sector (Service/Manufacturing)
■ Ownership (Public/Private sector) • Nationality/country of origin (Indian /Foreign) ■ Size/Number of employees (small/medium/large)
Respondents were also asked to mention their designation, experience in terms of
years in the present position and total experience in the organization. The
instrument utilized a 5-point Likert scale anchored with end points Iabeled as No
Involvement (1) to High Involvement (5) as well as Strongly Disagree (1) to
Strongly Agree (5) for certain items.
4.7 Sampling Procedure
This section provides a brief overview of the sampling procedure followed by the
researcher. The current research follows the sampling procedure as suggested by
Churchill and Iacobucci (2002), Malhotra (2007), Malhotra and Dash (2011),
Sekaran (2006) and Wilson (2006) and others. Sampling procedure begins with a
definition of target population followed by sampling frame, sampling approach and
sample size. The Exhibit 4.3 presents the sampling procedure adopted in this
research.
Exhibit 4.3: Flow Chart Representing the Sampling Procedure
Defining the target population
Identifying the sampling frame
Selecting sampling method
Determining the sample size
Collecting the data from the sample
Prepared by the Researcher
4.7.1 Target Population
Target population includes set of elements that contain the information needed by
the researcher and about which the inferences are to be made (Malhotra, 2007;
Malhotra & Dash, 2011). In other words, target population was defined in terms of
sampling unit and sample elements.
100
4.7.1.1 Sampling Unit
The present research is based on the study of selected leading business
organizations operating in India. The organizations covered in the study included
both Indian and foreign companies, public and private sector companies,
organizations of different sizes based on number of employees and companies
from both manufacturing and service sectors (The criteria for selecting the
sampling units suitable for the study is discussed in detail under sampling frame in
section 4.7.2).
4.7.1.2 Sampling Element
The respondents of the study were senior HR managers (one from each firm). The
use of single respondent is recommended when data is collected from senior HR
executives regarding human resource management (Huselid & Becker, 2000;
Klass et al, 1999). These are the subject matter, experts and believed to be in a
good position to provide the necessary information (Chan et al., 2004; Huselid &
Becker, 2000). Senior HR executives have been used as respondents in similar
other studies too (e.g. Andersen et. al., 2007; Andolsek & Stebe, 2005; Budhwar,
2000a, 2000b; Caldwell, 2003; Fisher & Dowling, 1999; Gautam & Davis, 2007;
Hsu & Leat, 2000; Huselid et al., 1997; Jones, 1996; KIass et al, 2001; Larsen &
Brewster, 2003; Perry & Kulik, 2008; Tremblay et al. 2008; Valverde et al., 2006;
Woodall et al., 2009). These studies considered the perception of senior HR
practitioners since they have direct responsibility for HR issues. Prior studies have
also considered the perceptions of a single respondent (HR executive) as
appropriate (Arthur & Boyles, 2007; Becker & Huselid, 2006; Katou, 2008; Teo,
2000). Selecting a familiar and knowledgeable respondent provides researchers
more valid and reliable data than that gathered from multiple respondents (Huselid
& Becker, 2000).
Senior level HR executives are believed to be suitable to provide information
concerning HR issues. Additionally, research in the area too has commonly
assumed human resource systems to be objective and recognizable characteristics
of organizations, not individuals and hence, the data does not suffer much from
101
subjectivity problems (Arthur & Boyles, 2007). Thus, keeping the above in mind,
senior HR managers were considered as sample elements for collecting data.
4.7.2 Sampling Frame
Following the footsteps of other researchers in the area (Budhwar, 2000a, 2000b;
Budhwar & Sparrow, 1997; Chan et al., 2004; Caldwell, 2003; Katou, 2008; Kydd
& Oppenheim, 1990) top ranking companies were considered in the present study.
The sampling frame for the study was derived from the ranking of Top 550
companies in India published in Business World (2009). It is to be noted that
when the survey for the present study began in 2010, the rankings of 2010 had not
come-out; hence, 2009 ranking list was considered for the present study. These
top-ranked organizations are believed to be at the leading edge of HR practices.
Studying such organizations that are high performing, researchers could assume
that HRM is at least nominally supported (McGovern et al., 1997; Sheehan, 2005).
Andolsek and Stebe (2005) conducted a study in the area of devolution in public
services and commercial companies having more than 200 employees. A similar
criteria for selecting the sample frame on the basis of number of employees (i.e.
more than 200) has been adopted by other researchers too (Budhwar, 2000a,
2000b; Budhwar & Sparrow, 1997; Deny etal., 2008; Mayne et al., 1996).
Perry and Kulik (2008) selected the organizations with 250 or more employees
operating across number of industries. Companies of this size are considered to
ensure that the recognized firms had HR departments in which HR practices were
more formalized (de Kok & Uhlaner, 2001). Green et al. (2006) who studied
organizations with more than 250 employees also suggested that large
organizations are likely to have well-established HR functions. In the present
research too, responding organization had more than 250 employees, thus, they
were found fit for inclusion.
} Business World and Centre for Monitoring Indian Economy (CMIE)-an independent research house-annually publish rankings of public limited companies in India. These companies have to file their annual accounts with the Registrar of Companies. The, published rankings are based on a number of parameters e.g. sales, ROCE, shareholder's return etc.
102
4.7.3 Sampling Approach and Sample Size
In order to collect the data from the companies identified through the above
mentioned sample frame, a census approach to sampling was used. All companies
(i.e. 550) in the sample frame were contacted. For obtaining the addresses of the
companies, professional bodies in India such as National HRD Network (NHRD),
Delhi Management Association (DMA), All India Management Association
(AIMA) and Indian Society for Training and Development (ISTD) were
approached as these bodies maintain lists of member companies and senior HR
executives. Some addresses were obtained from Directory of Senior Executives of
Central and States Public Sector Undertakings 2009-10, Handbook of Top Indian
Companies, Trainer and Training Institutions Directory 2009 and websites of the
companies as well. Certain contacts were obtained during HR meets organized by
industry bodies like Confederation of Indian Industry (CII), Associated Chambers
of Commerce and Industry of India (ASSOCHAM) and Federation of Indian
Chamber of Commerce Industry (FICCI). Moreover, .the researcher also visited the
corporate offices of some sample companies.
4.8 Questionnaire Administration and Data Collection
Data was collected from the sample organizations through e-mail, land mails, HR
meets, and personal visits. Mail methodology has been used by other researchers in
the area too e.g. Budhwar and Sparrow (1997), Caldwell, (2003), Klass et al.
(1999), Klass et al., (2001), Perry and Kulik (2008), Wood (1995). In order to
collect data from the respondents, questionnaires were sent through e-mail and in
some cases through postal mail. Follow-up reminders were sent to those who did
not respond after the initial mail. Besides, HR managers were approached during
HR meets and HR conclaves organized by HR wings of different industry bodies
like Confederation of Indian Industry (CII), Associated Chambers of Commerce
and Industry of India (ASSOCHAM), Federation of Indian Chamber of Commerce
Industry (FICCI), Delhi Management association (DMA) and professional HR
associations like ISTD and NHRD Delhi Chapter. These meets provided a good
platform for interaction with senior HR managers.
103
Techniques associated with higher response rate were adopted such as personalized
cover letters (Andersen et al., 2007; Bruvold et al., 1990; Duncan, 1979; Nowack,
1990; Perry & Kulik, 2008; Roth & Be Vier, 1998), the use of reminders and
follow-ups (Duncan, 1979; Harvey, 1987; Heberlein & Baumgartner, 1978; Hsu &
Leat, 2000; Kanuk & Berenson, 1975; Linsky, 1975; Perry & Kulik, 2008; Roth &
Be Vier, 1998), questionnaire colour (Bender, 1957; Crittenden et a1.,1985; Fox et
al., 1988; Jobber, 1986; Jobber & Sanderson, 1983; Matteson,1974; Phipps et al.,
1991) and assured anonymity of the respondents (Roth & Be Vier, 1998;
Yammarino et al., 1991). An affiliation with a professional organization increases
the response rate (Perry & Kulik, 2008).The researcher is a life member of several
leading HR associations and professional bodies in India. These associations
served as valuable gateways in contacting HR executives of several organizations
and increasing the response rate. Several measures were taken to improve the
response rate:
❑ Length of the questionnaire is generally assumed to reduce response rates
(Nowack, 1990). Yammarino et al. (1991) argued that surveys start to lose
responses after four pages. Roszkowksi and Bean's (1990) study pointed
out a 28% difference between a long (i.e. 4 pages) and short version of
questionnaire (i.e. large post card). The focus of the current study was
senior HR professionals, who were assumed to be time-pressed. Thus, the
researcher designed the questionnaire accordingly (i.e. 2 pages for e-mail
and an attractive printed card-form for personal visits).
U Return postage affect the response rates (Andersen et al., 2007; Duncan,
1979; Harvey, 1987; Linsky, 1975; Nowack, 1990). Yammarino et al.
(1991) argued that return postage is considered as requirement by
respondents. In case of postal mails, a self-addressed, stamped return
envelope was included by the researcher.
U Questionnaire colours have a positive effect on mail survey response rates
(Bender, 1957; Fox et al., 1988; Jobber, 1983; Jobber & Sanderson, 1983;
Phipps et al., 1991). Questionnaire colours appeal to the respondent's
sensory and emotional faculties (Bender, 1957). In an office environment,
colour might be more noticed than white papers (Phipps et al., 1991).
Bender (1957) tested the combinations of colours (i.e. blue, green and
104
pink,) to check the response rate and found that colour combinations
increased response rate. Keeping this in view researcher has used the colour
combinations i.e. green, blue, pink, yellow and red for both soft and hard
forms of the questionnaire.
❑ The questionnaire was designed in such a way so that it appeared user-
friendly and attractive. Besides, the questionnaire was closed ended (it
required responding on a five-point Likert scale), and therefore, it did not
require much time in filling.
❑ In some cases, where addresses of HR managers could not be arranged,
senior level managers were contacted with a request to forward the
questionnaire to concerned HR officials. In many cases, the request was
promptly acceded to.
❑ The university in which the researcher is working is running an Executive
PhD program in association with All India Management Association
(AIMA). Executives enrolled in the program, whose organizations were
part of the sample, were contacted. In many cases, these executives were
not in the HR department and were requested to forward the same to a
senior HR executive.
❑ The researcher contacted the alumni of the university if they were in the
sample. in case they were not part of the HR department, they too were
requested to forward the questionnaires to a senior HR executive.
❑ Respondents were assured anonymity in order to increase the response rate
(Roth & Be Vier, 1998; Yammarino et al., 1991) and to reduce the
evaluation apprehension (Podsakoff et al., 2003), since assured anonymity
increases the response rate.
The respondents accepted to participate with the understanding that at no stage
their companies would be identified, and this constraint was acceptable as the
research objectives of the present study were to identify general/sectoral trends
rather than the specific company policies. Moreover, researcher followed the
concept of social exchange theory which reveals that human behaviour is
motivated by psychological returns (i.e. whatever is pleasurable or gratifying to the
person) and psychological costs (i.e. factors that inhibit behaviours such as
105
physical or mental effort, pain) associated with behaviour (Emerson, 1987; Foa &
Foa, 1980; Greenberg, 1980). Individuals are thought to be motivated to engage in
behaviour associated with high returns and low costs (psychological costs). Hence,
following the social exchange theory, the researcher offered to share results of the
study to those who were interested. It was intended to minimize psychological and
other costs through questions designed to have a minimal chance of embarrassing a
respondent and providing stamped self-addressed envelopes to minimize cost for
those who were contacted through post.
4.9 Conceptual Models of Research
In order to test the relationship between the variables, alternative research models
were considered by the researcher. A research model may have both endogenous
and exogenous variables. Endogenous constructs have their casual antecedents
specified within the model under consideration, whereas the causes of exogenous
constructs are outside the model and not of interest (Anderson & Gerbing, 1991).
When structural models are specified, observed measures of exogenous constructs
are denoted as X, whereas observed measures of endogenous constructs are
denoted as Y. These are simultaneously estimated with the structural model to
ascertain if any relationship exists (Joreskog & Sorbom, 1993).
Following the approach followed by other researchers (e.g. Bontis et at 2007;
Knight et al., 1999; Mustapha et al., 2010), three alternative conceptual models
were considered for the current study i.e. Direct Effect Model, Partially Mediated
Model and Fully Mediated Model. Model specifications of all the three models are
discussed subsequently.
Direct Effect Model (Ml): Exhibit 4.4a illustrates the direct effect conceptual
model developed by the researcher for the study. In the exhibit 4.4a, the
hypothesized relationship between independent and dependent constructs is
depicted by arrows. The curved lines indicate correlation between two variables. In
this model, direct relationship between independent variables i.e. the role of the
three agents and dependent variable i.e. effectiveness of HRM is assessed. No
mediating variable is considered in this case.
106
Exhibit 4.4a: Direct Effect Conceptual Model of Research (Mt)
Partially Mediated Model (M2): Exhibit 4.4b represents M2, the partially
mediated model, in which both direct and indirect effects (through mediating
variable i.e. status of HRM) of the hypothesized relationship is depicted by arrows.
Exhibit 4.4b:
tiallv Mediated Conceptual Model of Research
107
Fully Mediated Model (M3): Exhibit 4.4c illustrates the fully mediated conceptual
model (M3) for the study. It assumes that independent variables will directly affect
the intervening variable or mediating variable i.e. Status of FIRM (STA) which, in
turn, will affect the dependent variable i.e. Effectiveness of FIRM (EFF).
Exhibit 4.4c Fully Mediated Conceptual Model of Research
The model specification for the three conceptual research models is as under:
Direct Effect Model (MI)
EFF;--- f (TDM, TPA, TBU, LDM, LPA, LBU, EDM, EPA, EBU)
Partially Mediated Model 2
STA= f {TDM, TPA, TBU, LDM, LPA, LBU, EDM, EPA, EBU);
EFF= f {TDM, TPA, TBU, LDM, LPA, LBU, EDM, EPA, EBU};
EFF=f [STA]
Fully Mediated Model (1113)
STA= f {TDM, TPA, TBU, LDM, LPA, LBU, EDM, EPA, EBU);
EFF= f {STA}
108
Where,
EFF = Effectiveness of HRM
STA = Status of HRM
TDM =Top management involvement in decision-making vis-a-vis HRM
TPA =Top management involvement in process/activities vis-a-vis HRM TBU =Top management involvement in budgeting vis-a-vis HRM
LDM=Line managers involvement in decision-making vis-a-vis HRM LPA= Line managers involvement in process/activities vis-a-vis HRM
LBU=Line managers involvement in budgeting vis-a-vis .HRM
EDM=External service providers involvement in decision-making vis-a-vis HRM EPA.=External service providers involvement in process/activities vis-a-vis HRM
EBU=External service providers involvement in budgeting vis-a-vis HRM
4.10 Research Hypotheses
Following three sets of hypotheses were considered in light of the study objectives.
First set of hypotheses deals with the three conceptual research models i.e. direct
effect model (Ml), partially mediated model (M2) and fully mediated model (M3).
The second and third set of hypotheses deal with assessing the differences and
establishing the association between company type and role of internal agents (i.e.
top management and line managers) and external agents (i.e. external service
providers) in management of HR.
Category 1: Hypotheses for Alternative Conceptual Research Models
Following other researchers (e.g. Bontis et al., 2007; Fried et al., 2008; Knight et
al., 1999; Mustapha et al., 2010), separate hypotheses were considered for all the
three models:
Hypotheses for Direct Effect Model (M1)
For the direct effect model (M1), nine hypotheses were considered to test all the
possible relationships between exogenous and endogenous variables. In model M1,
direct effect of independent variables (i.e. role of agents) on the dependent variable
(i.e. effectiveness of HRM) is studied:
109
H1TDM: Top management involvement in decision-making vis-a-vis HRM (TDM)
has a direct and positive impact on the Effectiveness of HRM (EFF).
H2TFA: Top management involvement in process/activities vis-a-vis HRM (TPA)
has a direct and positive impact on the Effectiveness of HRM (EFF).
H3TBu: Top management involvement in budgeting vis-a-vis HRM (TB U) has a
direct and positive impact on the Effectiveness of HRM (EFF).
H4LDM: Line managers involvement in decision-making vis-a-vis HRM (LDM) has
a direct and positive impact on the Effectiveness of HRM (EFF).
HSLpA: Line managers involvement in process/activities vis-a-vis HRM (LPA) has a
. direct and positive impact on the Effectiveness of HRM (EFF).
H6LBU: Line managers involvement in budgeting vis-a-vis HRM (LB U) has a direct
and positive impact on the Effectiveness of HRM (EFF)
H7EDM: External service providers involvement in decision-making vis-a-vis HRM
(EDM) has a direct and positive impact on the Effectiveness of HRM
(EFF)
H8EPA: External service providers involvement in process/activities vis-a-vis HRM
(EPA) has a direct and positive impact on the Effectiveness of HRM (EFF)
H9EBU: External service providers involvement in budgeting vis-a-vis HRM (LB U)
has a direct and positive impact on the Effectiveness of HRM, (EFF)
Hypotheses for Partially Mediated Model (M2)
In partially mediated model (M2) nineteen hypotheses were considered to test all
the possible relationships between exogenous and endogenous variables. In model
M2, first nine hypotheses deal with the indirect effect of independent variables on
the Status of HRM, while second set of nine hypotheses deal with the direct effect
of exogenous variables on the Effectiveness of HRM. Last hypothesis deals with
the impact of Status of HRM on the Effectiveness of HRM. Following hypotheses
were considered for partially mediated model (M2):
HIOTDM: Top management involvement in decision-making vis-a-vis HRM (TDM)
has a direct and positive impact on the Status of HRM (STA).
110
HJ1TpA: Top management involvement in process/activities vis-a-vis HRM (TPA)
has a direct and positive impact on the Status of HRM (STA).
HJ2TBU: Top management involvement in budgeting vis-a-vis HRM (TB U) has a
direct and positive impact on the on the Status of HRM (STA)
H13LDM: Line managers involvement in decision-making vis-a-vis HRM (LDM) has
a direct and positive impact on the Status of HRM (STA)
H14L PA: Line managers involvement in process/activities vis-a-vis HRM (LPA)
has a direct and positive impact on the Status of HRM (STA).
HI5LBU: Line managers involvement in budgeting vis-a-vis HRM (LB U) has a
direct and positive impact on the Status of HRM (STA).
H16EDM: External service providers involvement in decision-making vis-a-vis
HRM (EDM) has a direct and positive impact on the Status of HRM
(STA).
H17EpA: External service providers involvement in process/activities vis-a-vis
HRM (EPA) has a direct and positive impact on the Status of HRM (STA)
H18EBU: External service providers involvement in budgeting vis-a-vis HRM
(EBU) has a direct and positive impact on the Status of HRM (STA)
Hl9TDM: Top management involvement in decision-making vis-a-vis HRM (TDM)
has a direct and positive impact on the Effectiveness of HRM (EFF).
H2OTpA: Top management involvement in process/activities vis-a-vis HRM (TPA)
has a direct and positive impact on the Effectiveness of HRM (EFF).
H21TBU: Top management involvement in budgeting vis-a-vis HRM (TB U) has'a
direct and positive impact on the Effectiveness of HRM (EFF)
H22,1: Line managers involvement in decision-making vis-a-vis HRM (LDM)
has a direct and positive impact on the Effectiveness of HRM (EFF)
H23LpA: Line managers involvement in process/activities vis-a-vis HRM (LPA)
has a direct and positive impact on the Effectiveness of HRM (EFF)
H24LBU: Line managers - involvement in budgeting vis-a-vis HRM (LB U) has a
direct and positive impact on the Effectiveness of HRM (EFF)
111
H25EDM: External service providers involvement in decision-making (EDM) vis-a-
vis HRM has a direct and positive impact on the Effectiveness of HRM
(EFF)
H26EPA: External service providers involvement in process/activities (EPA) vis-a-
vis HRM has a direct and positive impact on the Effectiveness of HRM
(EFF)
H27EBU: External service providers involvement in budgeting vis-a-vis HRM
(EB U) has a direct and positive impact on the Effectiveness of HRM
(EFF)
H28STA: Status of HRM (STA) has a direct and positive impact on the Effectiveness
of HRM (EFF)
Hypotheses for Fully Mediated Model (M3)
In the fully mediated model (M3) ten hypotheses were considered to test the
indirect effect of exogenous variables on the mediating variable i.e. Status of HRM
and then the relationship between the mediating variable i.e. Status of HRM on
Effectiveness of HRM:
H29TDM: Top management involvement in decision-making vis-a-vis HRM (1DM)
has a direct and positive impact on the Status of HRM-(STA)
H30TpA: Top management involvement in process/activities vis-a-vis HRM (TPA)
has a direct and positive impact on the Status of HRM (STA)
H3ITBU: Top management involvement in budgeting vis-a-vis HRM (TB U) has a
direct and positive impact on the on the Status of HRM (STA)
H32LDM: Line managers involvement in decision-making vis-a-vis HRM (LDM) has
a direct and positive impact on the Status of HRM (STA)
H33LFA: Line manager involvement in process/activities vis-a-vis HRM (LPA) has
a direct and positive impact on the Status of HRM (STA)
H34r.Bu: Line managers involvement in budgeting vis-a-vis HRM (LB U) has a
direct and positive impact on the Status of HRM (STA)
112
H3SEOM: External service providers involvement in decision-making vis-a-vis
HRM (EDM) has a direct and positive impact on the Status of HRM (STA)
H36EpA: External service providers involvement in process/activities vis-a-vis
HRM (EPA) has a direct and positive impact on the Status of HRM (STA)
H37E5O: External service providers involvement in budgeting vis-a-vis HRM
(EB U) has a direct and positive impact on the Status of HRM (STA)
H38sr,4: Status of HRM (STA) has a direct and positive impact on the Effectiveness
ofHRM(EFF)
Category I[: Hypotheses for Establishing Differences
The hypotheses in this category deal with establishing differences on study
variables on the basis of company type. Company type was categorized as sector to
which the company belongs (service/manufacturing) and size of the company
determined on the basis of number of employees (small, medium and large). Poole
and Jenkins (1997) and Shaw et al. (1993) reported that size of the organization
plays an important role in determining the role of agents in HRM. Bennett et al.
(1998) described the industry's influence on human resource practices. Some
researchers maintained that business organizations in the service sector were more
likely to have a strategic approach to HRM than manufacturing organizations (e.g.
Marginson et al., 1988; Othman & Ismail, 1996). Srimannarayana (2010) reported
the differences between manufacturing and service sector companies. Following
hypotheses were considered to establish the differences on the basis of company
type vis-a-vis role of top management and line managers (internal agents) and
external service providers (external agents) in management of HR. The first nine
hypotheses deal with establishing the differences on the basis of sector and the next
nine hypotheses deal with establishing the differences on the basis of size.
On the basis of sector:
Ho.l: There is no significant difference in the mean scores of top management
involvement in decision-making vis-a-vis HRM (TDM) between companies
from manufacturing and service sectors.
113
Het: There is no significant difference in the mean scores of top management
involvement in process/activities vis-a-vis HRM (TPA) between companies
from manufacturing and service sectors.
Ho3: There is no significant difference in the mean scores of top management
involvement in budgeting vis-a-vis HRM (TB U) between companies from
manufacturing and service sectors.
H4: There is no significant difference in the mean scores of line managers
involvement in decision-making vis-a-vis HRM (LDM) between companies
from manufacturing and service sectors.
H5: There is no significant difference in the mean scores of line managers
involvement in process/activities vis-a-vis HRM (LPA) between companies
from manufacturing and service sectors
H6: There is no significant difference in the mean scores of line managers
involvement in budgeting vis-a-vis HRM (LB U) between companies from
manufacturing and service sectors
H7: There is no significant difference in the mean scores of external service
providers involvement in decision-making vis-a-vis HRM (EDM) between
companies from manufacturing and service sectors
H8: There is no significant difference in the mean scores of external service
providers involvement in process/activities vis-a-vis HRM (EPA) between
companies from manufacturing and service sectors
Hog: There is no significant difference in the mean scores of external service
providers involvement in budgeting vis-a-vis HRM (EBU) between
companies from manufacturing and service sectors
On the basis of size:
Ho10: There is no significant difference in the mean scores of top management
involvement in decision-making vis-a-vis HRM (TDA) between small,
medium and large organizations.
114
Holl: There is no significant difference in the mean scores of top management
involvement in process/activities vis-a-vis HRM (TPA) between small,
medium and large organizations.
H12: There is no significant difference in the mean scores of top management
involvement in budgeting vis-a-vis HRM (TB U) between small, medium and
large organizations.
H13: There is no significant difference in the mean scores of line managers
involvement in decision-making vis-a-vis HRM (LDM) between small,
medium and large organizations.
H14: There is no significant difference in the mean scores of line managers
involvement in process/activities vis-a-vis HRM (LPA) between small,
medium and large organizations.
11o15: There is no significant difference in the mean scores of line managers
involvement in budgeting vis-a-vis HRM (LB U) between small, medium and
large organizations.
H0!6: There is no significant difference in the mean scores of external service
providers involvement in decision-making vis-a-vis HRM (EDM) between
small, medium and large organizations.
H0!7: There is no significant difference in the mean scores of external service
providers involvement in process/activities vis-a-vis HRM (EPA) between
small, medium and large organizations.
Ho18: There is no significant difference in the mean scores of external service
providers involvement in budgeting vis-a-vis HRM (EBU) between small,
medium and large organizations.
Category III: Hypotheses for Establishing Association
The next set of hypotheses deal with establishing association between company
type viz. sector (service/manufacturing), and size of the organizations (small,
medium and large organizations) and role of top management and line managers
(internal agents) and external service providers (external agents) in management of
HR. On the basis of above, following hypotheses were considered to ascertain the
115
association between company type and role of top management, line managers and
external service providers in management of HR. The first nine hypotheses .deal
with. establishing the association on the basis of sector and the • next nine
hypotheses deal with establishing the association on the basis of size.
On the basis of sector:
Hot: There is no association between company's sector i.e. manufacturing and
service sector and top management involvement in decision-making vis-a-vis
HRM(IDf)
Hot: There is no association between company's sector i.e. manufacturing and
service sector and top management involvement in process/activities vis-a-
vis HRM (TPA)
H3: There is no association between company's sector i.e. manufacturing and
service sector and top management involvement in budgeting vis-a-vis HRM
(TBU)
H4: There is no association between company's sector i.e. manufacturing and
service sector and line managers involvement in decision-making vis-a-vis
HRM (LDM)
Ho5: There is no association between company's sector i.e. manufacturing and
service sector and line managers involvement in process/activities vis-a-vis
HRM (LPA)
H06: There is no association between company's sector i.e. manufacturing and
service sector and line managers involvement in budgeting vis-a-vis HRM
(LBU)
Ho7: There is no association between company's sector i.e. manufacturing and
service sector and external service providers involvement in decision-making
vis-a-vis HRM (ED*
H08: There is no association between company's sector i.e. manufacturing and
service sector and external service providers involvement in
process/activities vis-a-vis HRM (EPA)
116
H9: There is no association between company's sector i.e. manufacturing and
service sector and external service providers involvement in budgeting vis-a-
vis HRM (EBU)
On the basis of size:
H10: There is no association between company's size i.e. small, medium and
large organizations and top management involvement in decision-making
vis-a-vis HRM (TDM).
H0l1: There is no association between company's size i.e. small, medium and
large organizations and top management involvement in process/activities
vis-a-vis HRM (TPA)
H12: There is no association between company's size i.e. small, medium and
large organizations and top management involvement in budgeting vis-a-vis
HRM (TB U)
H13: There is no association between company's size i.e. small, medium and
large organizations and line managers involvement in decision-making vis-
a-vis HRM (LDM)
Halo: There is no association between company's size i.e. small, medium and
Iarge organizations and line -managers involvement in process/activities vis-
a-vis HRM (LPA)
H15: There is no association between company's size i.e. small, medium and
large organizations and line managers involvement in budgeting vis-a-vis
HRM (LBU)
H16: There is no association between company's size i.e. small, medium and
large organizations and external service providers involvement in decision-
making vis-a-vis HRM (EDM)
Ho17: There is no association between company's size i.e. small, medium and
large organizations and external service providers involvement in
process/activities vis-a-vis HRM (EPA)
E
117
H018: There is no association between company's size i.e. small, medium and
large organizations and external service providers involvement in budgeting
vis-a-vis HRM (EBU)
4.11 Methods of Analysis
Statistical methods are primary tools for data analysis in the social science research
(Nachmias & Nachmias 2008). But primarily multivariate methods share a
common constraint of investigating one relationship at one time (Hair et al. 2008;
Malhotra & Dash, 2011). Recognising the objectives of the present study to
examine the pattern and interrelationships of multiple exogenous variables,
moderating variables, mediating variable and endogenous variable, structural
equation modelling (SEM) is regarded as the most effective analytical instrument
(Byrne 2001; Hair et al., 2008) which is useful when assessing models that are
path analytic with mediating variables, and include underlying constructs that are
being measured with multiple items (Luna-Arocas & Camps, 2008).
Descriptive statistics of the responses were generated through SPSS 19.0. After
initial estimation of the response rate, non-response error and common method
bias, Exploratory Factor Analysis (EFA) was carried out to see if items in a scale
load on one single factor. After establishing the unidimensionality of the study
constructs, indicator and scale reliability were assessed. Various types of validity
were, also ascertained (e.g. construct validity i.e. convergent, discriminant,
nomological validity and criterion validity). The relationship between exogenous
and endogenous variables was measured using Structural Equation Modeling
(SEM) capabilities of LISREL 8.50. For proceeding with SEM, Maximum
Likelihood Estimation (MLE) method was employed.
Tests of differences (independent sample T-test and one way ANOVA) and test of
association (Chi-square Test) were also deployed in SPSS 19.0 to find out whether
differences as well as association existed between organizations on role of internal
and external agents in HRM vis-a-vis company type i.e. on the basis of sector
(service or manufacturing) and size (small, medium and large). All these methods
and procedures are explained in detail in Chapter 5.
118
4.12 Limitations of the Study
Although efforts were made to carry on a research that was theoretically and
empirically sound, the study does suffer from several limitations:
❑ In this study quantative research design is followed to analyze the data.
Although such a design has its own merits, if supplemented with a
qualitative research could have enabled in generating more comprehensive
and valid models. However, budget and time constraints do not permit this.
❑ The study was cross-sectional in design and hence suffers from the
limitations associated with cross-sectional designs. In the study both the
endogenous and exogenous variables are measured on one occasion only. A
longitudinal study design could have more accurately captured casual_
relationship between role of internal and external agent in management of
human resources and effectiveness of HRM.
❑ While in this study, a reliable and valid instrument has been developed for
measuring the role of internal and external agents in management of human
resources in the Indian context only, it needs to be cross-validated. for other
cultures and settings (Kelloway, 1998).
❑ The study is based on the responses provided by HR managers. However,
surveys administered on a single source may raise concerns of common
method bias. Thus, data collected from HR managers should be handled
with caution due to the multiple constituency nature of HRM function
(Tsui, 1984). Although the researcher tested for common method bias with
the results supporting the contention that the bias does not significantly
impact the study results; the research was not designed to be a multi-
respondent study and hence may be considered a limitation.
❑ The study is based on a limited sample. Hence, the study might have
suffered from small sampler size related problems. Larger number could
have given more generalizable results.
❑ The data for the study was obtained from HR managers only. Data from
other stakeholders such as internal and external agents would have an
impact on the final analysis.
119
CHAPTER 5: ANALYSIS AND INTERPRETATION
5.1 Plan of Analysis 5.2 Profile of Responding Firms and Respondents 5.3 Estimation of Response Rate 5.4 Estimation of Non-response Bias 5.5 Estimation of Common Method Bias 5.6 Measurement Model
5.6.1 Factor Analysis 5.6.2 Assessment of Reliability 5.6.3 Assessment of Validity
5.7 Structural Model 5.7.1 Structural Model Fit 5.7.2 Fit Indices, Path Coefficients & Hypotheses Testing
5.8 Criterion Validity 5.9 Comparison of Alternate Models 5.10 Tests of Differences 5.11 Tests of Association
i"
CHAPTER 5: ANALYSIS AND INTERPRETATION
Chapter Overview
The chapter begins with a discussion of the plan of analysis. Subsequently, it
provides details of the profile of responding firms and the respondents. The first
part of the analysis deals with an estimation of response rate, non-response bias,
and common method bias. After that, measurement model and structural model fit
are estimated and path analysis carried out for testing of research hypotheses of
three alternate research models. This is followed by the assessment and
comparison of alternate models on the basis of fit measures. The chapter comes to
an end with tests of difference and association with respect to company type and
agents' involvement in HRM.
5.1 Plan of Analysis
Data analysis begins with an account of the profile of the responding organizations
and respondents. This is followed by an estimation of response rate, non-response
error and common method bias. Subsequent section follows the two step approach
recommended by Anderson and Gerbing (1988) and Gerbing and Anderson (1988).
Two-step approach is considered as most appropriate for the present analysis due to the simultaneous estimation of both measurement and structural models. In the
present study, first the measurement model is estimated followed by structural
model. This two-step approach has been endorsed by several researchers (Garver
& Mentzer, 1999; Hennig-Thurau et al., 2002; Vieira, 2011 etc.). In this approach,
first the measurement model assesses the unidimensionality, reliability and validity
of each construct followed by structural model which involves path analysis and
comparison of alternate models on the basis of fit measures (Anderson & Gerbing,
1988). Separate measurement models are specified for each construct (Joreskog &
Sa rbom, 2002). The testing of the structural model may be meaningless unless it is
first established that the measurement model holds. If the chosen indicators for a
construct do not measure that construct, the specified theory cannot be tested. In
fact, the potential for interpretational confounding is minimized by prior estimation
120
of the measurement model followed by structural model (Anderson & Gerbing,
1991). Thus, the measurement model was estimated first to establish scale
unidimensionality, reliability and validity followed by structural model to establish
relation between exogenous, endogenous, mediating and moderating variables.
Exploratory factor analysis (EFA) followed by Confirmatory factor analysis (CFA)
were used for estimating the measurement model. The unidimensionality and
reliability of the scales were assessed. The scales were subject to different types of
construct validity that is convergent, discriminant and nomological validity. After
the measurement models were validated, the researcher advanced to the next step
that is the assessment of the structural relationships between latent variables. The
conceptual models were tested during this stage. The structural models were
analyzed and the standardized path coefficients of the structural models were
estimated followed by comparison of alternate models on the basis of fit indices.
Structural equation modeling (SEM) is one of the most powerful analytical
techniques for data analysis in the social sciences (Hair et al., 2008; Hooper et al., 2008; Shook et al., 2004; Widaman & Thompson, 2003). SEM can analyse a series
of dependence relationships among multiple variables (Hair et al., 2008; Malhotra
& Dash, 2011) as it combines the confirmatory factor analysis (measurement
model) and path or regression analysis (structural model) into simultaneous
statistical test. SEM programs such as LISREL (Joreskog & Sorbom, 1993, 1996)
make it easier and faster for the researcher to investigate the multifaceted structural
models (Cooper & Schindler, 2006; Hair et al., 2008; Malhotra & Dash, 2011;
Widaman & Thompson, 2003). Structural equation modeling capabilities of
LISREL 8.50 were deployed for assessment of measurement model and structural
model. One of the benefits of SEM is that a variety of methods may be used to
analyze the appropriateness of hypothesized models and to compare the fit among
alternate models (Knight et al., 1999). LISREL generates variety tests and fit
indices that can be used to assess model fit. For proceeding with SEM, use of
Maximum Likelihood Estimation (MLE) method was made. MLE is commonly
used estimation method (Anderson & Gerbing, 1988; Baumgartner & Homburg,
1996; Diamantopoulos & Siguaw, 2000), uniform at producing efficient estimation
contrary to moderate violations of the normality assumptions (Diamantopoulos &
Siguaw, 2000). MLE method is recommended if sample consist of I00 or more
121
observations (Anderson & Gerbing, 1988; Steenkamp & Van Trijp, 1991). The
MLE estimates are obtained by means of an iterative procedure that minimizes a
particular fit function by successively improving the parameter estimates (Joreskog
& Sorbom, 2002). SEM accounts for measurement error in latent variables when
estimating path relationships (Hair et al., 2008) as it estimates measurement error
variances from the data and model specification where as traditional statistical
techniques do not (Ahire et al., 1996). It is also useful when testing models that are
path analytic with mediating variables, and include latent constructs that are being
measured with multiple items (Luna-Arocas & Camps, 2008). SEM is ideal for
testing theoretical models, refining and testing validity (Graver & Mentzer, 1999).
Tests of differences (independent sample t-test and one-way ANOVA in SPSS
19.0) were deployed to find out whether differences existed between organizations
on role of internal and external agents in management of HR vis-a-vis company
type i.e. on the basis of sector (service or manufacturing) and size (small, medium
and large). A test of association was also deployed using Chi-square in SPSS 19.0
to explore if there existed any association between company type i.e. sector
(manufacturing or service), size (small, medium and large) and role of internal and
external agents in management of HR.
176 companies responded out of 550 companies contacted, two questionnaires
were found incomplete and dropped from further analysis. Hence, the final number
of usable questionnaires was 174. LISREL technique depends on large sample
properties so an important consideration is sample size required to obtain
meaningful estimates. For proceeding with SEM using MLE, minimum sample
size of 50 is required but in order to ensure stable MLE solutions, minimum
sample size is 100-150 (Hair el al., 2008). Similar sample size was reported in
studies with SEM using MLE with LISREL as for example 76 responses (Knight
et al., 1999) 100-200 responses (Lindquist et al., 2001). Following Joreskog and
Sorbom's (1993) formula [k (k - 1)/2; where k equals the number of variables], to
compute the minimum sample size for estimation of the asymptotic covariance
matrices; the total number of latent variables in this research was 11, resulting in a
recommended minimum sample size of 51 significantly smaller than our final
sample size of 174. Thus, it can be safely concluded that structural equation
modeling was appropriate for the present research.
122
Exhibit 5.1: Flow Chart Depicting the Sequence of Analysis
PROFILE OF RESPONDING FIRMS AND RESPONDENTS
ESTIMATION OF RESPONSE
NON-RESPONSE ERROR
COMMON METHOD BIAS
Structural Equation Modeling MLE (Estimation Technique)
Measurement Model Exploratory Factor Analysis ■ Scale Unidimensionality
Confirmatory Factor Analysis ■ Reliability (Indicator and Scale) ■ Validity (Convergent, Discriminant and Nomological)
Structural Model ■ Relationships (Moderation and Mediation) • Path coefficients (Hypotheses testing) • Validity (Criterion Validity) • Comparison of Alternate Models
5.2 Profile of Responding Firms and Respondents
A profile of both responding firms and respondents is presented below:
Profile of Responding Firms
Sector: The responding organizations were categorized into service and
manufacturing. While 47.1% of organizations belonged to the service sector,
52.9% belonged to the manufacturing sector. Table 5.1 presents the profile of the
responding organizations on the basis of these sectors.
123
Table 5.1: Resoondina Organizations- Sector Sector Frequency Percent Cumulative Percent Service 82 47.1 47.1
Manufacturing 92 52.9 100 Total 174 100.0
Ownership: On the basis of ownership, responding organizations were classified
into public (21.3%) and private sector organizations (78.7%). Table 5.2 shows the
ownership pattern of the responding organizations.
Table 5.2: Resnondina Orctanizations- Ownership Ownership Frequency Percent Cumulative Percent
Public sector 37 21.3 21.7 Private sector 137 78.7 100.0
Total 174 -100.0
Nationality: On the basis of country of origin, the organizations were classified as
Indian (85.1%) and foreign (14.9%). Table 5.3 illustrates the nationality of
responding firms.
Table 5.3: Resoondina Organizations- Nationality
Nationality Frequency Percent Cumulative Percent
Indian 148 85.1 85.1 Foreign 26 14.9 100.0
Total 174 100.0
Size: Responding organizations were classified into different sizes on the basis of
number of employees according to criteria suggested by Budhwar and Sparrow
(1997). Accordingly, organizations with less than 1000 employees were considered
small, those between 1001-5000 employees were considered medium and those
with more than 5001 employees were considered large. The break-up is presented
in Table 5.4
Table 5.4: Resnondina Organizations- Size
Size Frequency Percent Cumulative Percent
Small 34 19.5 19.5 Medium 43 24.7 44.3
Large 97 55.7 100.0 Total 174 100.0
124
Profile of Respondents
Designation: The respondents of the study were HR managers (one from each
responding fixm). About 64.4% of respondents occupied senior level HR positions (e.g. ED-HR, Director-HR, Chief People Officer, Vice President-HR, DGM HR, General Manager-HR, Assistant GM-HR etc.), while 35.6% occupied managerial
level HR positions (e.g. Senior Personnel Officer, Senior Officer HR, Senior Manager-HR, Deputy Manager-HR, Assistant Manager-HR, Personnel Manager,
Manager-HR etc). Table 5.5 gives a picture of the profile of the respondents on the basis of designation.
Table 5.5: Respondent Profile- Desianation Designation Frequency Percent Cumulative Percent
Senior Managerial Level HR positions 112 64.4 64.4
Managerial level HR positions 62 35.6 100
Total 174 100.0
Experience: Almost 79% of the respondents had an experience of 1-5 years in the current position, 13.8% had an experience of 6-10 years while nearly 5% had an experience of more than 11 years. Table 5.6 illustrates the profile on the basis of experience in the present position.
Table 5.6: Resaondent Profile- Experience in Present Position Experience Frequency Percent Cumulative Percent 1-5 years 139 79.9 79.9 6-10 years 24 13.8 93.7 11-15 years 11 6.3 100.0
Total 174 100.0
Total Experience: Approximately 34.5% of respondents had a total experience of 0-10 years, 30.5% had an experience of 11-20 years, 21.3% had an experience of
21-30 years while 13.8% had an experience of more than 30 years. Table 5.7 shows the profile of the respondents on the basis of total experience in the
organization.
125
Table 5.7: Respondent Profile- Total Experience in the Oraanization Total Experience Frequency Percent Cumulative Percent
0-10 years 60 34.5 34.5 11-20 years 53 30.5 64.9
21-30 years 37 21.3 86.2 More than 30 years 24 13.8 100.0
Total 174 100.0
5.3 Estimation of Response Rate
Usually low response rates are common in industrial research and conventional
mail methodology accounts 10.8% response rate (Harmon et al., 2002). In Indian
cultural context, postal surveys result in poor response rate (Budhwar & Sparrow,
1997). Response rates ranging from 5% (Perry & Kulik, 2008), 8.56% (Hall &
Torrington, 1998), 10.5% (Valverde et al., 2006), 16% (Wood, 1995), 17% (Larsen
& Brewster, 2003), 18.6% (Budhwar, 2000a, 2000b) 22.7 % (Klass et al., 1999;
Klass et al., 2001) were reported in different researches conducted in the area.
Out of the 550 organizations initially contacted by researcher, 176 organizations
provided their responses giving a response rate • of 32%. Since, in most research
studies response rate has been low hence, a response rate of 32% can be considered
to be high and gives a sizeable number of total respondents to generate consistent
statistical results.
In addition to response rate, item completion rate is used as another measure of
survey effectiveness (Klassen & Jacobs. 2001). Klassen and Jacobs (2001) define
item completion rate as "the proportion of survey items answered relative to all
applicable items" (p. 717). The item completion rate for this study was 98.86%,
suggesting high survey effectiveness. Responses with 50% or more missing data
should be deleted (Hair et al., 2008). Out of 176 responses, two responses were
found to be incomplete having more than 60% missing data and were eliminated as
suggested by Hair et al. (2008), Lopez et al. (2005) and Maihotra (2007). Finally,
the total number of usable questionnaires was 174.
126
5.4 Estimation of Non-response Bias
Non-response bias is checked to ascertain any potential bias due to the failure of
elements in the sample to respond. At the first sight, a visual comparision of the
characteristics of the responding organizations indicated that the firms were
representative of those surveyed since they represented a cross-section of
industries thus, indicating no evidence for non-response bias as suggested by Chan
et al. (2004) and Teo (2000).
Further, evidence for any possible non-response bias was also checked statistically.
It is usual to use late respondents as substitute for non-respondents to test for non-
response bias (Dean et al., 2007; Nwachukwv et al., 1997). Armstrong and
Overton (1977) have argued that non-respondents have been found to descriptively
resemble late respondents.
Lambert and Hanington (1990, p. 21) describe a common approach to assessment
by comparing early and late respondents and assuming that "non-response bias is
non-existent if no differences exist on the survey variables". Similar method of
comparing early and late respondents was followed to analyze the non-response
bias (Dalecki et al., 1993; Israel, 2009; Kellerman & Herold, 2001; Lahaut et al.,
2003; Lin & Schaeffer, 1995; Lopez et al., 2005).
Following this approach, respondents were classified into two groups as early and
late respondents. Early respondents (56.32%) are those that responded in first
contact and late respondent (43.67%) are those who responded after follow-ups. In
order to find out if there were any differences in the means of all the variables used
in this study between early and late respondents, independent sample t-test was
carried out for each construct. The comparison of responses of the two groups did
not reveal any significant differences. Since non-respondents are similar to late
respondents (Armstrong & Overton, 1977), it indicates that non-response bias was
not a serious issue in this study.
Table 5.8 and 5.9 present the group statistics and results of the independent sample
t-test.
127
Table 5.8: Group Statistics for Non-response Error
Constructs RESPT N Mean Std. Deviation
Std. Error Mean
TDM ER 98 24.36 4.419 .446 LR 76 24.72 4.048 .464
TPA ER 98 22.08 5.025 .508 LR 76 21.57 4.965 .569
TBU ER 98 22.57 5.868 .593 LR 76 23.33 5.493 .630
LDM ER 98 22.74 4.452 .450 LR 76 22.32 3.641 .418
LPA ER 98 19.47 3.503 .354 LR 76 19.29 3.417 .392
LBU ER 98 19.67 . 6.814 .688 LR 76 18.11 6.198 .711
EDM ER 98 11.02 5.223 .528 LR 76 10.96 4.611 .529
EPA ER 98 12.22 5.261 .531 LR 76 11.76 4.504 .517
EBU ER 98 9.98 4.831 .488 LR 76 9.59 4.570 .524
STA ER 98 24.48 4.765 .481 LR 76 24.00 4.956 .568
EFT ER 98 12.03 2.481 .251 LR 76 I1.82 2.667 .306
Key: RESPT--Respondent Timing, ER=Early Respondents, LR=Late Respondents
Table 5.9: Independent Samoles Test for Non-response Error
Construct Nature of Variance Levene's Test T-test Results F Sig. T df Sig.(2-tailed)
TDM Equal variances assumed .030 .862 -.563 172 .574 TPA Equal variances assumed .000 .985 .675 172 .500 TBU Equal variances assumed 1.377 .242 -.868 172 .386 LDM Equal variances assumed 3.076 .081 .682 172 .496 LPA Equal variances assumed .388 .534 .359 172 .720 LBU Equal variances assumed 1.592 .209 1.566 172 .119 EDM Equal variances assumed .196 .659 .079 172 .937 EPA Equal variances assumed .927 .337 .610 172 .542 EBU Equal variances assumed .000 .995 .537 172 .592 STA Equal variances assumed .089 .765 .647 172 .518 EFF Equal variances assumed .946 .332 .548 172 .584
128
5.5 Estimation of Common Method Bias
When data for the predictor and criterion variables are collected from same
respondent, common method bias may lead to inflated estimates of the relationships (Chang et al., 2010; Doty & Glick, 1998; Podsakoff & Organ, 1986;
Podsakoff et al., 2003). In addition to this, the correlations between variables
measured with the same methods are exaggerated owing to common method bias
(Bagozzi et al., 1991; Podsakoff et al. 2003; Spector, 2006). Common method bias
is a problem since it is one of the major sources of measurement error (Podsakoff
et al. 2003), which may in turn undermines the validity of the conclusions about
relationships between measures (Nunnally, 1978). The problem of common
method bias is mainly increased when cross-sectional, self-reported surveys are
employed as a research instrument (Spector, 2006). In order to address the problem
of common method bias, two types of remedies are available i.e. procedural and statistical as recommended by Chang et al. (2010), Malhotra et al. (2006), Podsakoff and Organ (1986), Podsakoff et al. (2003), Wall and Wood (2005).
Procedural Methods
Procedural method involves eliminating or minimizing the bias through the design
of the research instrument. Following procedural methods have been followed in
the present research to control the problem of common method bias:
1) Protecting respondent anonymity and reducing evaluation apprehension
Respondent axe allowed to respond anonymous and also assured that there are no
right or wrong answers and that they should answers the questions as honestly as
possible in order to protect respondent anonymity and reducing evaluation
apprehension as recommended by Podsakoff et al. (2003). Moreover, the cover
letter that was attached with the questionnaire addressed the above issues to ensure
that respondent apprehensions were adequately taken care of.
2) Scale reordering & improving scale items
Scale reordering is another procedural method for minimizing common method
variance which requires the reordering of the items on the questionnaire such that
the items related to the independent variable precede the dependent variable on the
survey instrument (Podsakoff & Organ, 1986; Salancik & Pfeffer, 1977; Williams
129
& Buckley, 1989). The survey instrument used in this study was structured such
that role related items for internal and external agents preceded the status of HRM
and effectiveness of HRM items. Similar procedure has been followed by other
researchers too (e.g. Camison & Villar-Lopez, 2010; Spanos & Lioukas, 2001).
Structuring scale items also reduces the common method bias. Following
Podsakoff et al., (2003) different scale formats for the predictor and criterion
measures have been used to reduce the biases. Additionally, efforts were made to
keep the items as simple, unambiguous and objective as possible to avoid bias as
suggested by Huselid and Becker (2000); Podsakoff et al., (2003).
Statistical Method
Statistical remedies are used to address the common method bias problem after the
variables in the study have already been measured. Harman's one-factor test
(Harman, 1967) was used to examine any bias. In this method all variables were
entered into exploratory factor analysis and the results are examined. Common
method variance is indicated by the emergence of either a single factor or one
general factor that explains a majority of the variance (Gibbons & O'Connor,
2005; Podsakoff & Organ, 1986; Podsakoff et al., 2003). This method has been
used and recommended by Takeuchi et al. (2003) too.
Results of the exploratory factor analysis on all variables revealed 15 factors. On
the basis of the Eigen value greater than I heuristic (Delgado-Ballester et al.,
2003), fifteen principal components were extracted that accounted for 72.29% of
the total variance. While the first factor accounted for 12.12 % of the total
variance, it did not account for a majority of the variance. Thus, the results indicate
that all the items did not load on a single construct, thereby negating presence of
common method bias. This suggests that although the responses to all items in a
questionnaire were provided by a single respondent, common method or common
source error of providing inflated or positive responses has not crept in. Based
upon these results, it can be said that study does not suffer from common method
bias. Table 5.10 presents the total variance explained by -fifteen principal
components having Eigen values greater than 1 heuristic.
130
Table 5.10: Common Method Bias-Total Variance Exnlained
Initial Eigen Values Extraction Sums of Squared Loadin s
Rotation Sums of Squared Loadin s Comp.
Total % of Var. Cum. % Total % of Var.
Cum. o % Total % of
Var. Cum.
o /o
1 11.894 18.879 18.879 11.894 18.879 18.879 7.637. 12.123 12.123
2 8.313 13.194 32.073 8.313 13.194 32.073 5.608 8.902 21.025
3 4.643 7.369 39.442 4.643 7.369 39.442 5.565 8.833 29.858
4 3.782 6.003 45.445 3.782 6.003 45.445 4.191 6.652 36.510
5 2.427 3.852 49.298 2.427 3.852 49.298 3.896 6.184 42.694
6 2.313 3.672 52.970 2.313 3.672 52.970 2.324 3.688 46.383
7 1.835 2.913 55.883 1.835 2.913 55.883 2.313 3.672 50.055
8 1.628 2.584 58.467 1.628 2.584 58.467 2.291 3.636 53.691
9 1.548 2.458 60.925 1.548 2.458 60.925 2.165 3.436 57.127
10 1.411 2.239 63.164 1.411 2.239 63.164 2.099 3.332 60.458
II 1.264 2.007 65.170 1.264 2.007 65.170 1.983 3.147 63.605
12 1.234 1.959 57.130 1.234 1.959 67.130 1.607 2.550 66.155
13 1.191 1.891 69.021 1.191 I.891 69.021 1.313 2.084 68.239
14 1.053 1.671 70.692 1.053 1.671 70.692 1.304 2.070 70.309
I5 1.001 1.589 72.282 1.001 1.589 72.282 1.243 1.973 72.282 Extraction Method: Principal Component Analysis Key: Comp. = Component, Var. = Variance, Cum. = Cumulative *Vote: Only the 15 factors that were generated are shown in the table
5.6 Measurement Model
Measurement model is the starting point to explain how well the observed
indicators serve as a measurement instrument for the latent variables. Measurement
model consists of identifying Iatent constructs and assigning indicator variables to
latent constructs (Graver & Mentzer, 1999; Hair et al., 2008). A comprehensive
measurement on research instrument is necessary because measurement model
offer methods in which the observed measurements can be improved (Joreskog &
Sorbom, 1993). Measurement model highlights the key issues of
unidimensionality, reliability i.e. indicator and scale reliability, construct validity
i.e. convergent, discriminant and nornological validity (Hair et al., 2008; Malhotra
& Dash, 2011). It gives support that the results appropriately indicate the intended
constructs. Besides, empirically validated scales can be used in other studies on
different populations. Measurement scales have to illustrate unidimensionality,
131
reliability, discriminant validity and convergent validity (Green et al., 2006). The
first test in the measurement model is to test the scales for unidimensionality. After
each scale is established as unidimensional and reliable, the next step is to test
convergent, discriminant and nomological validity (Anderson & Gerbing, 1982;
Anderson & Gerbing, 1991; Steenkam & Trijp, 1991; Vieira, 2011).
Measurement analysis was performed on all study scales. The effectiveness of
HRM scale (EFF) used in the study has been developed and tested in previous
research (Teo & Crawford, 2005). Moreover, it consisted of three single-item sub-
scales which cannot be subjected to a measurement analysis as suggested by
Hennig-Thurau et al. (2002) and Joreskog & Sorbom (2002). Table 5.11 shows the
exogenous, endogenous, mediating and moderating variables of the study.
Table 5.11: Variables/Measures Considered for the Study ■ Top management involvement in decision-making'
vis-a-vis HRM (TDM) ■ Top management involvement in process/activities
vis-a-vis HRM (TPA) N Top management involvement in budgeting vis-a-
vis HRM (TBU) • Line managers involvement in decision-making
vis-a-vis HRM (LDM) Exogenous Variables ■ Line managers involvement in process/activities
(Role of Agents) vis-a-vis HRM (LPA) • Line managers involvement in budgeting vis-a-vis
HRM (LBU) ■ External service provider involvement in decision-
making vis-a-vis HRM (EDM) ■ External service provider involvement in
process/activities vis-a-vis HRM (EPA) ■ External service -provider involvement budgeting
vis-a-vis HRM (EBU) Endogenous Variable ■ Effectiveness of HRM (EFF) Mediating Variable ■ Status of HRM (STA)
■ Sector (service/ manufacturing) Moderating Variable ■ Ownership pattern (public/private sector)
(Organizational Profile) ■ Country of origin (Indian/Foreign) ■ Size (small, medium and large)
5.6.1 Factor Analysis
Factor analysis tests the unidimensionality of the measurement scales to refine the
variables which are not related (Henson & Roberts, 2006) and therefore, helps to
eliminate multiple, overlapping constructs in research (Cascio, 2011). In general,
132
factor analysis is categorized as exploratory and confirmatory factor analysis. In
this study it was decided to apply exploratory factor analysis first followed by
confirmatory factor analysis. Principal component analysis with varimax rotation
was used in the exploratory factor analysis performed.
Exploratory Factor Analysis (EFA)
Exploratory factor analysis describes factors that are there among a group of data
and its main objective is to unfold the hidden factors which explain the covariance
between the measured data (Kahn, 2006). Eigen Values more than 1 is most often
used criteria in factor analysis (Delgado-Ballester et al., 2003; Fabrigar et. at, 1999; Henson & Roberts, 2006; Ritter et al., 2001). EFA was carried out to check
unidimensionality of each scale separately. Unidimensionality of the scale consists
of items loading highly on a single factor (Hair et. al., 2008). Unidimensionality is
an essential precondition for reliability and validity (Anderson & Gerbing, 1991;
Cascio, 2011).
Before proceeding with EFA, it is important to assess the factorability of the
overall set of variables and individual variables using Kaiser-Meyer-Olkin (KMO)
measure of sampling adequacy and the overall significance of correlation matrix
with Bartlett's Tests of Sphericity (Dziuban & Shirkey, 1974; Williams et al,
2010). KMO and Bartlett's tests, reveals the appropriateness of the. data for factor
analysis (Ang & Huan, 2006; Liu & Treagust, 2005; Peterson, at al., 2000). KMO
quantifies the degree of inter-correlations among the variables and thus, tests
appropriateness of factor analysis. KMO values must exceed 0.50 before
proceeding with the factor analysis (Hair at al., 2008; Malhotra, 2007). The KMO
values of all the scales were found to be acceptable acting as an indicator that data
was suitable for factor analysis. Another method is Bartlett's Test of Sphericity
which examines the presence of correlations among the variables. It provides the
statistical significance that the correlation matrix has significant correlations
among at least some of the variables. Thus, a significant Bartlett's Test of
Sphericity is required (Hair et al., 2008; Malhotra, 2007). Because p =0.000 (its
significance is less than 0.05) for all scales, we could proceed with factor analysis.
133
The results of KMO and Bartlett Test of Sphericity for all scales are given in Table
5.12.
Table 5.12: KMO and Bartlett's Test of Sphericitv
Measures Kaiser-Meyer-Olkin Measure of Sampling Adequacy (KMO)
Bartlett's Test of Sphericity
Approx. Chi-Square df Sig.
TDS 0.826 277.037 15 .000 TPA 0.816 353.622 15 .000 TBU 0.878 591.326 15 .000 LDM 0.750 178.826 10 .000 LPA 0.774 167.286 10 .000 LBU 0.874 731.853 15 .000 EDM 0.823 403.767 15 .000 EPA 0.786 322.318 15 .000 EBU 0.826 626.065 15 .000 STA 0.852 439.407 15 .000 EFF 0.694 159.844 03 .000
Results of Exploratory Factor Analysis
TDM Scale: Results of EFA revealed that the scale was unidimensional. Delgado-
Ballester et al. (2003) reported that on the basis of Eigen value greater than 1
heuristic; one component was extracted that accounted for 50.15% of the total
variance. Thus, EFA on the TDM scale yielded only one factor. The result is given
in Table 5.13A and Table 5.13B
Table 5.13A: TDM Scale-Total Variance Explained
Component Initial Eigen Values Extraction Sums of Squared
Loadin s
Total ~o of Variance % Cumulative
% Total ~o of % Variance
Cumulative °lo
1 3.009 50.153 50.I53 3.009 50.153 50.153 2 .758 12.633 62.786 3 .709 11.813 74.600 4 .655 10.924 85.523 5 .492 8.203 93.726 6 .376 6.274 100.000
Extraction Method: Principal Component Analysis
134
Table 6.138: TOM Scale-Component Matrix Items Component
TDM-1 .630 TDM-2 .752 TDM-3 .790 TDM-4 .654 TDM-5 .755 TDM-6 .652
Extraction Method: Principal Component Analysis Rotation Method: Varimax with Kaiser Normalization
TPA Scale: On the basis of Eigen value greater than 1, one principal component
was extracted that accounted for 53.01 % of the total variance. Thus, EFA on the
TPA scale gives one factor. The results are given in the Tables 5.14A and 5.14B.
Table 5.14A: TPA Scale-Total Variance Explained
Componen
t Initial Eigen Values Extraction Sums of Squared
Loadings
Total % of Variance
Cumulative °la Total % of
Variance Cumulative
1 3.181 53.013 53.013 3.181 53.0I3 53.013 2 .857 14.282 67.295 3 .696 11.605 78.900 4 .562 9.373 88.272 5 .432 7.208 95.480 6 .271 4.520 100.000
Extraction Method: Principal Component Analysis
Table 5.14B: TPA Scale-Component Matrix Items Component TPA-1 .682 TPA-2 .793 TPA-3 .858 TPA-4 .682 TPA-5 .748 TPA-6 .570
Extraction Method: Principal Component Analysis Rotation Met/sod: Varimax with Kaiser Normalization
TBU Scale: On the basis of Eigen value greater than 1, one principal component
was extracted that accounted for 65.45 % of the total variance. Thus, EFA on the
TBU scale gives one factor. The results are given in the Tables 5.15A and 5.15B.
r
Table 5.15A: TBU Scale-Total Variance Explained
Component Initial Eigen Values Extraction Sums of Squared
Loadings
Total % of Variance
Cumulative % Total % of
Variance Cumulative
1 3.927 65.455 65.455 3.927 65.455 65.455 2 .608 10.136 75.591 3 .508 8.465 84.056 4 .4I6 6.926 90.982 5 .379 6.317 97.299 6 .162 2.701 100.000
Extraction Method: Principal Component Analysis
Table 5.15B: TBU Scale-Component Matrix Items Component TBU-1 .816 TBU-2 .877 TBU-3 .886 TBU-4 .686 TBU-5 .811 TBU-6 .761
Extraction Method: Principal Component Analysis Rotation Method: Varimax with Kaiser Normalization
LDM Scale: On the basis of Eigen value greater than 1, one principal component
was extracted. Although, EFA on the LDM scale yielded one factor but the loading
of one item was less than 0.50. Loading value of 0.50 is considered necessary for
practical significance (Hair et al., 2008). Following this criterion, item with low
loading was deleted and EFA was again run on the remaining items. As a result of
this, factor loadings improved and accounted for 48.76 % of the total variance. The
results of EFA are given in the Tables 5.16A and 5.16B.
Table 5.16A: LDM Scale-Total Variance Explained
Component Initial Eigen Values Extraction Sums of Squared
Loadin
Total % of Variance
Cumulative % Total % of
Variance Cumulative
1 2.438 48.768 48.768 2.438 48.768 48.768 2 .878 17.552 66.320 3 .720 14.397 80.7I7 4 .553 11.051 91.767 5 .412 8.233 100.000
Extraction Method: Principal Component Analysis
I36
Table 5 Matrix .16B: LDM Scale-Component Items Component
LDM-I .724
LDM-2 .834 LDM-3 .702 LDM-4 .629 LDM-5 .575
Method.• Principal C m Extraction pal o ponent Analysis Rotation Method: Varimax with Kaiser Normalization
LPA Scale: On the basis of Eigen value greater than 1, two principal components
were extracted that accounted for 35.42% and 26.16 % of the total variance. All the
items load on component one except item no 1 and 6. Following the criteria of Hair
et al. (2008), deletion of one item in having low loading, was carried out. After
deleting item number 6 which had weak loading, one principal component was
extracted that accounted for 48.97 % of the total variance and all the loadings were
above 0.5. The results of EFA are given in the Tables 5.17A and 5.17B
Table 5.17A: LPA Scale-Total Variance Explained Extraction Sums of Squared Initial Eigen Values
Component Loadings
Total % of Cumulative Total % of Cumulative Variance % Variance
1 12.449 48.977 48.977 2.449 48.977 48.977 2 .826 16.510 65.487 3 .675 13.507 78.995 4 .560 11.190 90.185 5 .491 9.815 100.000
Extraction Met/sod: Principal Component Analysis
Table 5.17B: LPA Scale-Component Matrix
Items Component
LPA-1 .604 LPA-2 .682
LPA-3 .758 LPA-4 .739
LPA-5 .706. Extraction Method: Principal Component Analysis Rotation Method: Yarimax with Kaiser Normalization
137
LBU Scale: On the basis of Eigen value greater than 1, one principal component
was extracted that accounted for 71.17 % of the total variance. Thus, EFA on the
LBU scale yielded one factor. The results are given in the Tables 5.18A and 5.18B.
Table 5.18A: LBU Scale-Total Variance EYnlained
Component Initial Eigen Values Extraction Sums of Squared
Loadings
Total % of Variance
Cumulative % Total % of
Variance Cumulati
ve % 1 4.270 71.170 71.170 4.270 71.170 71.170 2 .522 8.698 79.868 3 .464 7.741 87.609 4 .324 5.400 93.009 5 .269 4.490 97.499 6 .150 2.501 100.000
Extraction Method: Principal Component Analysis
5.18B: LBU Scale-Component M Items Component
LBU-1 .815 LBU-2 .905 LBU-3 .867 LBU-4 .860 LBU-5 .820 LBU-6 .789
Extraction Method: Principal Component Analysis Rotation Method: Varirnax with Kaiser Normalization
EDM Scale: On the basis of Eigen value greater than 1, one principal component
was extracted that accounted for 56.30% of the total variance. Thus, EFA on the
EDM scale gives one factor. The results are given in the Tables 5.19A and 5.19B.
Table 5.19A: EDM Scale-Total Variance Exo1ained
Component Initial Eigen Values
Extraction Sums of Squared Loadings
Total % of Variance
Cumulative % Total % of
Variance Cumulative
% 1 3.378 56.301 56.301 3.378 56.301 56.301 2 .861 14.348 70.649 3 .657 10.952 81.601 4 .426 7.103 - 88.704 5 .358 5.971 94.675 6 .319 5.325 100.000
Extraction Method: Principal Component Analysis
Tabi atrix
138
'on d: PnWcfi al Com onent A Extractr Metho p p nalysis Rotation Method: Varimax with Kaiser Normalization
Tabl e 5.20B: EPA Scale-Component M Items Component EPA-1 .687 EPA-2 .665 EPA-3 .740 EPA-4 .806 EPA-5 .768 EPA-6 .597
atrix
Table 5.19b: EDM Scale-Component Ni
Items Component
EDM-1 .799 EDM-2 .762 EDM-3 .715 EDM-4 .707 EDM-5 .805 EDM-6 .708
Extraction Method: Principal Component Analysis Rotation Method: Varimax with Kaiser Normalization
EPA Scale: On the basis of Eigen value greater than 1, one principal component
was extracted that accounted for 50.94 % of the total variance. Thus, EFA on the
EPA scale yielded one factor. The results are given in the Tables 5.20A and
5.20B.
Table 5.20A: EPA Scale -Total Variance Exnlained
Component
Initial Eigen Values Extraction Sums of Squared Loadings
Total °
j'O of Variance
Cumulative % Total % of.
Variance Cumulative
1 3.057 50.949 50.949 3.057 50.949 50.949 2 .927 15.442 66.392 3 .691 11.515 77.907 . 4 .621 10.348 88.254 5 .371 6.178 94.432 6 .334 5.568 100.000
Extraction Method. Principal Component Analysis
atrix
139
EBU Scale: On the basis of Eigen value greater than 1, one principal component
was extracted that accounted for 63.80 % of the total variance. Thus, EFA on the
EBU scale yielded one factor. The results are given in the Tables 5,21A and 5.21 B.
Table 5.21 A: EBU Scale-Total Variance Exnlained
Component Initial Eigen Values Extraction Sums of Squared
Loadings
Total. Variance % /o of Cumulative
% Total % of Variance
Cumulative _
1 3.828 63.808 63.808 3.828 63.808 63.848 2 .946 15.766 79.573 3 .432 7.197 86.770 4 .379 6.320 93.090 5 .227 3.788 96.878 6 .187 3.122 100.000
Extraction Method: Principal Component Analysis
Table 5.21B: EBU Scale-Component Matrix Items Component EBU-1 .788 EBU-2 .795 EBU-3 .849 EBU-4 .798
EBU-5 .805 EBU-6 .755
Extraction Method: Principal Component Analysis Rotation Method: Varimax with Kaiser Normalization
STA Scale: On the basis of Eigen value greater than 1, one principal component
was extracted that accounted for 59.11 % of the total variance. Thus, EFA on the
STA scale gives one factor. The results are given in the Tables 5.22A and 5.22B.
Table 5.22A: STA Scale-Total Variance Exnlained
Component Initial Eigen Values Extraction Sums of Squared
Loading
Total % of Variance.
Cumulative % Total % of
Variance Cumulative
1 3.547 59.115 59.115 3.547 59.115 59.115 2 .749 12.478 71.593 3 .599 9.985 81.578 4 .457 7.618 89.196 5 .357 5.950 95.146 6 .291 4.854 100.000
Extraction Method: Principal Component Analysis
140
G-.
Table 5.22B: STA Scale-Component Matrix Items Component STA-1 .787 STA-2 .814 STA-3 .825 STA-4 .625 STA-5 .746 STA-6 .798
Extraction Method: Principal Component Analysis Rotation Method: Varimax with Kaiser Normalization
EFF Scale: On the basis of Eigen value greater than 1, one principal component
was extracted that accounted for 70.96 % of the total variance. Thus, EFA on the
EFF scale gives one factor. The results are given in the Tables 5.23A and 5.23B.
Table 5.23A: EFF Scale-Total Variance Explained
Initial Eigen Values Extraction Sums of Squared Loadings Component
Total % of Cumulative Total % of Cumulative Variance % Variance %
1 2.129 70.963 70.963 2.129 70.963 70.963 2 .507 16.897 87.860 3 .364 12.140 100.000
Extraction Method: Principal Component Analysis
Table 5.23B: EFF Scale-Component Matrix
Items Component
EFF-1 .876
EFF-2 .824 EFF-3 .826
Extraction Method: Principal Component Analysis Rotation Method: Varimax with Kaiser Normalization
Overall, the results of EFA revealed that all the scales were unidimensional with
items loading of all the scales exceeding the acceptable value of 0.5 as
recommended by different researchers such as Bagozzi et al (1991), Garver and
Mentzer (1999), Hair et al. (2008), Malhotra and Dash (2011). However, in LDM
and LPA scales, one item was deleted in each scale having low loadings (i.e. less
141
than 0.5), following the procedure recommended by Hair et al. (2008).
Consequently, loading of all other items improved.
Confirmatory Factor Analysis (CFA)
Researchers have opined that CFA provides a more stringent test of construct
validity compared to traditional methods (Medsker et al., 1994). Although the
results obtained in the EFA confirmed the unidimensionality of all the scales,
however, as a further check, CFA was performed using LISREL 8.50 to assess the
SEM based reliability and validity of the unidimensional scales. High loading
values obtained in CFA provided further strength to the fact that scales were
unidimensional. The fit indices of the scales obtained in CFA were also acceptable. The next sections on assessment of reliability and validity are based on the results
of CFA.
5.6.2 Assessment of Reliability
After the unidimensionality of the scales is ascertained, estimation of the statistical
reliability is essential prior to runningvalidity analysis (Anderson & Gerbing,
1991; Cooper & Schindler, 2006; Hair et al., 2008; Mentzer et al., 1999). Hair et
al. (2008) opine that for a scale to be valid, it must meet the necessary levels of
reliability. Reliability is an assessment of the degree of dependability, stability and
internal consistency of a scale. Theoretically, reliability is defined as the degree to
which measures are free from random or unstable error and therefore yield
consistent results. Two types of reliability estimates were computed: (1) Indicator
reliability and (2) Scale reliability.
Indicator Reliability
Indicators are items used to measure a particular construct or latent variable.
Indicator reliability presents the reliability of individual indicators. It is measured
for every single indicator (Wu, 2005). It generally ranges from 0 to I (Joreskog &
Sorbom, 2002). Indicator reliability should preferably be 0.5 or greater (Long,
1983; Schumacker & Lomax, 2004). Even values close to the recommended are
142
considered acceptable (Wu, 2005). In the present study, indicator reliability was
more than 0.5 or close to it in most cases. Table 5.24 reveals the indicator
reliability for indicators in each scale.
Table 5.24: Indicator Reliability of the Scales Item TDM TPA TBU LDM LPA LBU EDM EPA EBU STA EFF 1 0.39 0.46 0.66 0.52 0.36 0.66 0.63 0.47 0.62 0.61 076,; 2 0.56 0.62 0.76 069 `" 0.46 ''1 0;'.81<;f. 0.58 0.44 0.63 0,66 0.67 3 0 62.°r 073 078 0.49 0:57:{ 0.75 0.51 0.54 F 072 ;; ,0 68_' 0.68 4 0.42 0.46 0.47 0.39 0.54 0.73 0.49 064 ; 0.63 0,39 - 5 0.57 0.55 0.65 0.33 0.49 0.67 L4` 0.58 0.64 0.55 - 6 0.42 0.32 0.57 - - 0.62 0.50 0.35 0.57 0.63 -
Note: Shaded boxes represent indicator with highest reliability in each scale
Scale Reliability
Cronbach alpha is the most common measure used to assess the construct's
internal consistency (Cronbach, 1951). The generally agreed upon lower limit for
Cronbach alpha is 0.70 (Hair et al., 2008; NunnaIly, 1978; Nunnally & Bernstein,
1994; Werts et al., 1974), even values as low as 0.35 have been found acceptable
(Roberts & Wortzel, 1979). Reliability assessment of the study scales returned
Cronbach alpha values that are more than the lower limit of 0.70. Cronbach alpha
values given in Table 5.25 suggest high reliability of each scale.
However, Coefficient alpha may underestimate or overestimate scale reliability
(Graver & Mentzer, 1999; Hair et al., 2008). Thus, apart from Cronbach's alpha,
reliability measures derived from CFA using LISREL are also available such as
construct-reliability and variance extracted (Hair et al., 2008). Garver and Mentzer
(1999) recommend computing the SEM construct-reliability and variance extracted
measures for scale reliability. SEM construct reliability values do not assume that
the individual items have equal reliabilities. Fornell and Bookstein (1982), Garver
and Mentzer (1999) and Hair et al. (2008) have described construct-reliability and
variance-extracted measures as:
Construct Reliability (CR). Construct reliability is a LISREL-generated estimate
of internal consistency similar to Cronbach's alpha. It is calculated by a formula.
Let sli be the standardized loadings for the indicators for a latent variable. Let ei be
143
the corresponding error terms, where error is I minus the reliability of the
indicator. The formula for CR is:
n 12
sl ; CR= 1=1 2
n n
Esl ; +Ye;
Variance Extracted (VE): An equivalent measure of construct reliability is the
variance extraction measure. Variance extracted estimates assesses the amount of
variance captured by a construct in relation to variance due to random
measurement error. Its formula is given below:
n
~ sl r 2 VE= i=1
n n
~sl12 +~e~
f=1 i=t
Hair et al. (2008) suggested that CR value higher than 0.6 implies that there is high
internal consistency. Variance extracted at 0.5 or higher is generally considered
acceptable (Fornell & Larcker, 1981). The CR and VE values as computed by the
above formulae exceeded or were close to the recommended values. The Cronbach
alpha, CR and VE values of all the scales are given in Table 5.25.
Table 5.25: Scale Reliability Estimates Scale Cronbach Alpha Construct Reliability Variance Extracted TOM 0.799 0.79 0.40 TPA 0.820 0.82 0.44 TBU 0.892 0.89 0.58 LDM 0.726 0.74 0.37 LPA 0.728 0.73 0.36 LBU 0.919 0.91 0.65 EDM 0.841 0.84 0.47 EPA 0.801 0.80 0.41 EBU 0.886 0.88 0.56 STA 0.849 0.86 0.51 EFF 0.794 0.79 0.57
144
5.6.3 Assessment of Validity
Validity is the degree to which a scale or set of measures accurately represent the
concept of interest (Hair et al., 2008). Validity of a scale is checked if it is
unidimensionaI and meets the necessary level of reliability (Gerbing & Anderson,
1988; Hair et al., 2008). As unidimensionality and reliability of the scales have
been assessed, the next step involved is assessing validity. Translation validity
(i.e. content and face validity) was assessed during scale development and pilot
testing. After final data collection, construct validity such as convergent,
discriminant, nomological and criterion validity were assessed in line with the
approach of other researchers (e.g. Cooper & Schindler, 2006; Hair et al., 2008;
Malhotra, 2007; Trochim, 2009).
Construct Validity
Construct validity is the extent to which a set of measured items actually reflect the
theoretical latent construct. Hence, it deals with the accuracy of measurement.
Evidence of construct validity provides confidence that measures taken from a
sample represent the actual true score that exists in the population (Hair et al.,
2008). Following forms of construct validity viz, convergent, discriminant and
nomological validity were assessed.
Convergent Validity
Convergent validity assesses the degree to which two measures of the same
concept are correlated (Campbell & Fiske, 1959). A construct is said to possess
convergent validity if items that are indicators of a specific construct converge or
share a high proportion of variance in common (Hair et al., 2008; Kaplan &
Sacuzzo, 1993).Various techniques are available to estimate the convergent
validity:
On the basis of factor loadings: Convergent validity can be assessed on the basis
of factor loadings. The items of different scales should load or converge on their
respective constructs. Graver and Mentzer (1999) suggested parameter estimates
145
for the individual measurement items criteria to check the convergent validity. All
the items should load on their hypothesized dimensions and the estimates are
positive and significant (Bagozzi et al., 1988; Bagozzi et al., 1991). Item loading values within each construct should be greater than 0.50 for convergent validity
(Hair et al., 2008; Malhotra & Dash, 2011, Mentzer et al., 1999). Factor loading of all scales were more than 0.5, thus indicating presence of convergent validity.
On the basis of internal consistency: Reliability is another indicator of convergent
validity which seeks to assure that there is moderate correlation among the
indicators (Hair et al., 2008; Kaplan & Sacuzzo, 1993). In the present case, the
condition applied well. As unidimensionality and high internal consistency of the
scales has already been established, this is proof of moderate convergent validity.
On the basis oft- values of scale items: Convergent validity can also be examined
on the basis of t-values for the factor loadings (Anderson & Gerbing, 1988). For
convergent validity, Anderson and Gerbing (1988) recommended that all the t-
values should exceed 2 (p=0.001) whereas Mentzer et al. (1999) suggested that t-
values should be more than 1.96. In the present case too, the t-values of items in
each scale were more than the prescribed limit of 1.96 and 2, which is an indication
of high convergent validity. Table 5.26 shows the t-values for all the items of all
the scales.
Table 5.26: T-values of Scale Items Item TDM TPA TBU LDM LPA LBU EDM EPA EBU STA EFF
1 6.7 7.9 11.5 7.7 5.8 11.9 11.4 7.9 11.5 10.8 11.4 2 9.6 11.4 14.7 11.0 6.9 15.5 9.5 6.9 I2.2 11.6 9.3 3 10.6 13.6 15.1 7.1 8.5 13.7 8.5 8.7 13.7 11.8 9.3 4 7.0 7.4 8.1 6.4 8.2 13.2 . 8.2 11.5 10.6 7.0 - 5 9.3 9.4 10.9 5.8 7.7 11.4 11.5 10.3 10.0 9.2 - 6 7.3 5.7 9.7 - - 10.5 8.9 6.5 8.9 11.1 -
On the basis of CFA fit indices: The convergent validity of scales is also
computed using CFA fit indices viz. Bentler-Bonett Coefficient and GFI in SEM.
146
Ahire et al. (1996), Green et al. (2006) recommended Bentler-Bonett coefficient
(Nonmed Fit Index and Non-normed Fit Index) method of assessing convergent
validity. Bentler-Bonett coefficient values greater than 0.9 indicates strong validity
and in the present case too all the scales have a Bentler-Bonett coefficient of
greater than or close to 0.9, which is a proof of strong convergent validity.
GFI values of all the scales are either within the acceptable limits or close to
generally agreed upon limit of 0.90 which provides strong evidence of convergent
validity of study scales. Table 5.27 presents the results of Gentler-Bonett
coefficient and GFI values indicating high convergent validity of the scales.
Table 5.27: Bentler-Bonett Coefficient and GFI Values Scale TDM I TPA TBU LDM LPA J LBU EDM EPA EBU LsTA I EFF NFX .96 J .95 .97 .95 .96 .96 .91 .90 .84 L95 .95
NNFI 97 .94 .97 .95 .96 .94 .87 .86 .75 .94 .94 GFI J .97 1 .95 .96 .97 .98 .92 .90 .92 .78 .94 r 1.95
Discriminant Validity
Discriminant validity is the degree to which two theoretically alike concepts are
unrelated. In this case, low correlation confirms that the scale is acceptably
different from other related scales (Hair et al., 2008). In order to assess the
discriminant validity of the scales, a two-step approach is followed.
On the basis of Harman's one factor test: In the first method, Harman's one-
factor test was conducted that loaded all of the variables into a principal
component factor analysis. This method has been used by Wu & Sukoco (2010).
The results of the factor solution revealed that no single factor dominated, fourteen
factors were generated with 71.30% of the total variance, and factor 1 had only
12.70% of the variance. Thus, the results indicate that all the items did not load on
a single construct, thereby indicating the presence of discriminant validity of the
scales. Table 5.28 presents the components that were generated and the total
variance explained by EFA.
I47
Table 5.28: Discriminant Validity-Total Variance Explained
Initial Eigen Values Extraction Sums of S uared Loadin s
Rotation Sums of Squared Loadin s Comp.
Total % of Var. Cum. ©° Total % of Var. Cum. Q`° Total % of
Var. Cum.
o /° I 11.489 18.834 18.834 11.489 18.834 18.834 7.751 12.706 12.706 2 8.279 13.573 32.407 8.279 13.573 32.407 5.767 9.454 22.160 3 4.629 7.589 39.995 4.629 7.589 39.995 5.601 9.182 31.342 4 3.779 6.195 46.190 3.779 6.195 46.190 4.145 6.794 38.136 5 2.399 3.933 50.123 2.399 3.933 50.123 3.786 6.207 44.343 6 2.266 3.714 53.837 2.266 3.714 53.837 2.422 3.971 48.314 7 1.782 2.921 56.758 1.782 2.92I 56.758 2.349 3.852 52.166 8 1.592 2.6I0 59.368 1.592 2.610 59.368 2.300 3.771 55.936 9 1.482 2.430 61.798 1.482 2.430 61.798 2.182 3.578 59.514 10 1.276 2.092 63.890 1.276 2.092 63.890 2.116 3.469 62.984 11 1.253 2.054 65.944 1.253 2.054 65.944 1,312 2.151 65.134 12 1.193 1.956 67.900 1.193 1.956 67.900 1,270 2.083 67.217 13 1.074 1.761 69.661 1.074 1.761 69.661 1.258 2.062 69.279 14 1.001 1.642 71.303 1.001 1.642 71.303 1.235 2.024 71.303
Extraction Method: Principal Component Analysis Key: Comp. = Component, Var. = Variance, Cures = Cumulative *Note: Only the 14 factors fit at were generated are shown in the table
On the basis of variance extracted and squared correlations: While in the second
method, variance-extracted estimates for all possible pairs of constructs are
compared with the square of correlation estimate between these two constructs.
The variance extracted estimates were higher than the squared correlation
estimates in most of the cases. This indicates that the items of a latent construct
explain that construct better than they explain another construct which gives proof
of discriminant validity. In the second method, variance-extracted estimates for all possible pairs of
constructs are compared with the square of correlation estimate between these two
constructs. The variance extracted estimates of each scale should be higher than the
squared correlation estimate indicating that the Iatent construct explains its item
measures better than it explains another construct which gives evidence of
discriminant validity (Hair et al., 2008; Malhotra & Dash, 2011). The VE of most
of the scales are higher than the squared correlation estimates which provides
another evidence of discriminant validity. Table 5.29 presents the squared
correlation.
148
31
Table 5.29: Discriminant Validity of Scales Scale TDM TPA TBU LDM LPA LBU EDM EPA EBU 1 VE TDM 1 .600 .289 .04 .09 .066 .054 .0001 .0009 I'0 40r TPA 1 .303 .020 .064 .07I 0.01 .001 .0006 U.44 TBU 1 .017 .020 .073 .0003 .001 .0005 0.58 .
LDM 1 .77 .40 .012. .028 .012.03 LPA 1 .42 . .004 .01 .011 S0 36 LBU 1 .067 .046 .096 X0.65;;; EDM 1 .781 .64 4 0.4'1, EPA 1 .69 x.0.41. EBU 1 Q:56
*Note: Squared correlation estimates between the scales are given in the above table and shaded boxes represent the variance extracted values of each scale
Nomological Validity
Nomological validity refers to the degree to which the scale correlates in a
theoretically predicted ways with measures of different but related constructs (Hair
et al., 2008; Malhotra, 2007; Malhotra & Dash, 2011). Graver and Mentzer (1999)
recommend measuring nomological validity by determining whether the scales of
interest correlate as expected. Since the nine scales are part of role measures,
theoretically they are expected to correlate.
SEM capability of LISREL 8.50 was used to find out the correlation and establish
nomological validity. In the current study, Cohen's (1988) guidelines for the
interpretation' of the correlation coefficient have been followed. The correlation
values between the scales were positive and significant, hence giving a proof of
. nomological validity as presented in Table 5.30 and Exhibit 5.2.
Table 5.30: Nomoloalcal Validity of Scales: Correlation Values Scale TDM TPA TBU LDM LPA LBU EDM EPA EBU TDM I 0.775 0.538 0.208 0.258 0.234 0.I47 0.013 0.030 TPA - 1 0.551 0.143 0.253 0.267 0.033 0.025 0.033 TBU - - 1 0.132 0.143 0.271 0.019 0.035 0.023 LDM - - - 1 0.878 0.640 0.111 0.169 0.111 LPA - - - - 1 0.653 0.064 0.100 0.105 LBU - - - - - 1 0.260 0.215 0.310 EDM - - - - - - 1 0.884 0.800 EPA - - - - - - - 1 0.832 EBU - - - - - - - - 1
149
Exhibit 5.2: Nomological Validity: Measurement Model with Correlations
0.73 S1 0.48 S2
n c+- 0.53 S5 0 5~~ 0,6 S6 0,63 S7 0.38 SS 0.28 S9 n ►n 0,71 S10 n c't 0.55 S11 "A' 0.78 S12 0.42 S13 0.22 S14 n P7a 0.18 S15 nn 0.6 S16 n-7A 0.45 S17 0.68
0.54 518 0.57 S19 0.4 1 520 n '4 n ~-r 0.63 S21 n C ; - 0.72 S22 0.' 4 0.8I S23
0.54 S2fi 1rni~cn 0.61 S27 n AA 0. S28 ,0.56
0.18 532 n M 0.28 S33 n o,r w-1 0.31 S34 ~p 72
042-4 J.S37 0.53 S38 n a
0.62 S40 0.65 0,41 S41 O,S8 S42 0.57 S43
nICA 0.7 S44 ncl -
n en_ 0.65 S}5 0.42 S4G 0.57 0.46 2S47 0.68 S48 0.39 S49 n -sn 0.38 S50 no's` 0.29 S51 n '7' 4.~#8 S52 0.65 0.49 S53 0.58 S54 Ct~i-Square=2604.01, df-1238, P-value=0.00000, F-M SEA=0.080
150
5.7 Structural Model
As already discussed in section 4.9, three alternative conceptual research models
were proposed for the study viz, direct effect (Ml), partially mediated (M2) and
fully mediated (M3) structural models. In direct effect model, direct relationship
between exogenous and endogenous variables is considered. In case of partially
mediated model, both direct and indirect effects (through mediating variable i.e.
status of HRM) of exogenous variables on the endogenous variable is analysed.
Fully mediated model (M3) assumes that exogenous variables will have no direct
effect on the endogenous variable but will affect the intervening variable i.e. Status
of HRM (STA) which, in turn, will affect the endogenous i.e. Effectiveness of
HRM (EFF).
Structural Equation Modeling (SEM) using LISREL 8.50 was applied to find out
the pattern of relationships among the variables of the three alternative models
proposed. SEM is appropriate for testing theoretical models (Graver & Mentzer,
1999; Hair et al., 2008; Malhotra & Dash, 2011) and it offers several unique
advantages over other traditional statistical techniques (Bagozzi, 1981). SEM
assesses both measurement properties and tests the key theoretical relationships as
well as it takes into account measurement error by estimating measurement error
variances from the data and model specification and it also undertakes comparison
of alternate models (Ahire et al., 1996; Raykov & Marcoulides, 2006).
57.1 Structural Model Fit
Structural model fit was assessed to examine the statistical relationships between
the study variables.
Model Fit Indices
Fit measures or fit indices provide necessary information for evaluation of alternate
models. Fit measures aim at quantifying the differences between the observed and
estimated covariance matrices among the indicator items as well as how the model
that best represents the data reflects underlying theory. Model fit are of three types:
absolute, incremental and parsimony fit indices (Hair et al., 2008; Hooper et al.,
2008). In an absolute fit measure, each model is assessed separately of other
possible models (Hair et al., 2008; Malhotra & Dash, 2011) and an absolute fit
151
measure find out how well a priori model fits the sample data (Malhotra & Dash,
2011; McDonald & Ho, 2002). Incremental fit indices measure how well a
specified model fits relative to some alternative baseline models (Hair et al., 2008;
Malhotra & Dash, 2011) and is based on the assumption that the observed
variables are uncorrelated (Malhotra & Dash, 2011; McDonald & Ho, 2002).
Incremental fit indices are also known as comparative (Miles & Shevlin, 2007) or
relative fit indices (McDonald & Ho, 2002). Parsimony fit indices assess the
overall goodness-of-fit representing the degrees of model fit per estimated
coefficient (Hair et al., 2008). Parsimony fit indices aim to correct for any over-
fitting of the model and evaluates the parsimony ratio of the model compared to
goodness-of-fit. Exhibit 5.3 illustrates the classification of fit indices as suggested
by Malhotra & Dash (2011).
Exhibit 5.3: Classification of Fit Measures
Fit Measures
Absolute Fit Indices Incremental Fit Indices Parsimony Fit Indices
Goodness-of-fit
Badness-of-tit Goodness-of-fit
Goodness-of-fit GFI, AGFI
RMSEA, SRMR, NFI, NNFI, CFI, PGFI, PNFI RMSR TLI. RNI
Source: Adapted from Malhotra, N.K. and Dash, S. (2011). Marketing research: An applied orientation, New Dellti: Pearson Education.
Consistent with the suggestions of researchers (e.g. Hair et al., 2008; Jackson et al., 2009; MaIhotra & Dash, 2011), the researcher followed the criteria of reporting
one fit index from each fit measure for description and comparison of alternate
models. Table 5.31 provides a brief account of the fit indices chosen for analysis
and the recommended or acceptable threshold levels based on prior studies
(Baumgartner & Homburg 1996; Ping, 2004; Viera, 2011).
152
Table 5.31: Fit Indices, Recommended Values and Descriptions Fit Index AV Descriptions
A' p>0.05 It indicates the discrepancy between hypothesised model and data if any. Low values suggests better fitting models
CFI >
• It is used for comparison of alternate models and higher values indicates better fitting models
GFI >0.70 Used for model comparisons and better fitting models signify higher values GFI adjusted for the degrees of freedom. Generally penalizes more complex models and favors those with minimum number
AGFI <GFI of free paths. AGFI values are lower than the GFI values in proportion to model complexity. Higher values indicate better fitting models.
,eIdf <3 Low for better fitting models
RMSEA <0.1 It illustrates how well the model fits the population covariance matrix considering the number of df Helpful for comparing fit across models and easier to interpret SRMR <0.08 due to standardised nature. Lower values represent better fit. Measures fit relative to a baseline model which assumes no
NFl >0.90 covariance between the observed variables. Higher values indicates better fit
NNFI >0.80 Higher values reveal better fitting model No threshold levels have been recommended therefore it is
PGFI & 0.50 or possible to obtain parsimony fit indices within the 0.50 region PNFI >0.50 with other goodness-of-fit achieves values over 0.90. High value
indicates the better performance of the models
Note: Values close to recommended are also acceptable Key: A V=Acceptable Values, X' =Chi-Square, CFI=Comparative Fit Index, GFI= Goodness-of-fit Index, AGFI=Adjusted Goodness-of-fit Index, ,Id =Chi-SquarelDegrees of Freedom, RMSEA=Root Mean Square Error of Approximation, SRMR =Standardized Root Mean Square Residual, NFI=Nonmed Fit Index, NNFI=Non-Normed Fit Index, PGFI=Parsimony Goodness-of-fit Index, PNFI=Parsimony Normed Fit Index
Source: As recommended by Alden et aL, 2006; Bagozzi and Yi, 1988; Bender and Bonett, 1980; Cote et aL, 2001; Hair et aL, 2008; Hu and Bentler, 1999; Hart, 1994; Hooper of al., 2008; Joreskog and Sorbom, 1993; Judge and lIulin,1993; Kline, 2005; Loehlin, 2004; Malhotra and Dash, 2011; Mulaik et aL,1989; MacCallum et at, 1996; Ping, 2004; Pedhazur and Pedhazur-Schelkin, 1991; Schumacker and Lomar, 2004; Tabachnik and Fide11,2007; Vfeira, 2011.
Study Variables
All the exogenous, endogenous and mediating study variables included in the
structural models are given below:
❑ Top management involvement in decision-making vis-a-vis HRM (TDM)
❑ Top management involvement in process/activities vis-a-vis HRM (TPA)
153
❑ Top management involvement in budgeting vis-a-vis HRM (TBU) ❑ Line managers involvement in decision-making vis-a-vis HRM (LDM) ❑ Line managers involvement in process/activities vis-a-vis HRM (LPA) ❑ Line managers involvement in budgeting vis-a-vis HRM (LBU) ❑ External service providers involvement in decision-making vis-a-vis HRM
(EDM) ❑ External service providers involvement in process/activities vis-a-vis HRM
(EPA) U External service providers involvement in budgeting vis-a-vis HRM (EBU) U Effectiveness of HRM (EFF) ❑ Status of HRM (STA)
Moderating Variables
In the current study, organizational characteristics such as sector to which the company belongs (manufacturing/service), ownership (public/private sector), size of the company (number of employees) and nationality (Indian/foreign) were
analyzed as moderating variables. In order to check the need to control for the
effect of moderating variables in the structural analysis, correlation matrix of all
the moderating variables and the constructs of study were assessed for significance. Similar technique was adopted by Green et al. (2006). The results of
the correlation matrix are given in Table 5.32. As all the correlation values
indicate weak correlation between the study constructs and moderating variables, it
was established that the assumed moderating variables did not have a significant
influence on the relationships and consequently none of them was included in the
structural model. Thus, the structural model was assessed using exogenous variables (TDM, TPA, TBU, LDM, LPA, LBU, EDM, EPA and EBU), mediating
variable (STA) and endogenous variable (EFF).
Table 5.32: Moderatina Variables - Correlation Values Matrix TDM TPA TBU LDM LPA LBU EDM EPA EBU STA EFF
SEC .012 .101 .205 .037 .153 .208 .023 .020 .117 .097 .022 OWN .164 .207 .002 .482 .321 .288 .065 .116 .043 .221 .084 SIZE .021 .096 .092 .054 .041 .066 .145 .118 .006 .038 .064 NAT .099 .115 .076 .041 .026 .028 .110 .108 .095 .325 .437
154
5.7.2 Fit Indices,Path Coefficients and Hypotheses Testing
The standardized path coefficients of the three alternate models viz, direct effect
(MI), partially mediated (M2) and fully mediated (M3) structural models as
estimated by LISREL 8.50 are given in Exhibits 5.4, 5.5 and 5.6. The path
coefficients are used to assess the magnitude and direction of relationships and test
the study hypotheses.
Fit Indices of Direct Effect Model (M1)
In the direct effect model (MI), it was examined whether there is direct
relationship between independent variables viz, role measures and the dependent
variable viz, effectiveness of HRM (EFF). The fit indices of Ml as produced by
LISREL 8.50 are given in Table 5.33.
Table 5.33: Ml- Fit Indices from LISREL 8.50 Fit Indicators Value
Goodness- of-Fit Index GFI 0.732 Adjusted Goodness-of- fit Index (AGFI) 0.690 Chi-Square Goodness-of- fit test 2774.16 Root Mean Square Error of Approximation (RMSEA) 0:076 Root Mean S uare Residual (RMSR) 0.0948 Standardized Root Mean Square Residual SRMR 0.0763 Comparative fit Index (CFI) 0.992 Normed Fit Index(NF 0.912 Non-Normed fit Index(NNFI) 0.984 Relative Fit Index (RFI) 0.899 Incremental fit Index (IFI) 0.993 Parsimony Goodness- of-fit Index GFI) 0.668 Parsimony Normed- of-fit Index (PNFI) 0.857 Akaike's Information Criterion (AIC) 3080.165 Consistent Akaike's Information Criterion (CAIC) 3728.819 Chi-Square/Degrees of Freedom 2774.I6/1385=2.00
From the Table 5.33, it may be inferred that most of the fit indices of M1 are
within the acceptable limits or close to the recommended values. Therefore, it can
be concluded that MI represents satisfactory model fit.
155
Path Coefficients and Hypotheses Testing: Direct Effect Model
On the basis of standardized path coefficients of the direct effect structural model
(M1), the hypotheses were tested. Exhibit 5.4 presents the direct effect structural
model (M1). The results of hypotheses testing of direct effect model (M1) are
presented below:
Hl TDM: Top management involvement in decision-making vis-a-vis HRM (TDM)
has a direct and positive impact on the effectiveness of HRM (EFF).
TDM had no direct and positive impact on EFF as indicated by the structural path
coefficient (fl=-0.08) from TDM to EFF. Thus the hypothesis H1TDM was rejected.
H2rp4: Top management involvement in process/activities vis-a-vis HRM (TPA) has a direct and positive impact on the effectiveness of HRM (EFF)_
TPA had a direct and positive impact on EFF as indicated by the structural path
(8=0.20) from TPA to EFF. Thus the hypothesis H2jPA was not rejected.
H3mt- Top management involvement in budgeting vis-a-vis HRM (TBU) has a
direct and positive impact on the effectiveness of HRM (EFF).
TBU had a direct and positive impact on EFF as indicated by the structural path
(/3=0.22) from TBU to EFF. Thus the hypothesis H3TBU was not rejected.
H4LDi : Line managers involvement in decision-making vis-a-vis HRM (LDM) has
a direct and positive impact on the effectiveness of HRM (EFF).
LDM had a direct and positive impact on EFF as indicated by the structural path
(/3-0.07) from LDM to EFF. Thus the hypothesis H4LOM was not rejected.
156
Lci
t5S sco £SS
fJT. 6VQ
9L0'0=vasr'sni '00000"O=afie-1- ZSS 6ro
d'.36~=3P `9I'iLLZ~~~En~S-~iJ i5S 6Z'0
OSS SE'Q
OS 6E"0
sts 89.0
89'Q 9ts ZFO
StlS 59'0
V H'S sL-O V
£tS S'Q
'cts 85"0 L5'Q V
V OtS Z9'Q
V 6£S LS"0
SAS £S"Q
L u L£S Zt"Q
Y u 9£S sr•0
u S6S £t''4
rf8 i£'o
ZL"Q ££S SZ i7 SS" £9S t'Q'0 L v
6i'0 ~`aa~ v Z£S SI'0
&V u i£S S£'0 690 !/coo- 6%S59"Q
00'0 95.0 QS'0 Z9S ZL"0 X33 LG"4 1a~ V 8ZS 9"0
`er v LZS 9'Q
LQ-0 yr V 99,0
4Y V g~is •Q
ZZ'0 T SZS Z9"0
O0 t~'Q 9i 0 i9S Z" £ZS i8"0
80'0' ~yY ZZS £L'0 US ITT
\89 0 US ZVO o~ 6I S LS"0 w _ 0o SIS tS 0 \yL LIS 5vo
Lt"0 PIS 9"0 `: STS SI'Q o\\ ZZ'0
65• 1 lE silo a;' ITS SS"0 LL ols IL'4
8S S£'0
LS ~9"0
9S 99'0
SS £SO
tS iTo
ZS 8YQ
IS SL"Q
(6W) laPoW Ia1fI3n4 3 J43 walla :r'9 4!q!gx3
HSLPA: Line managers involvement in process/activities vis-a-vis HRM (LPA) has
a direct and positive impact on the effectiveness of HRM (EFF).
LPA had a direct and positive impact on EFF as indicated by the structural path
(8=0.27) from LPA to EFF. Thus the hypothesis HSLPA was not rejected.
H6LBU: Line managers involvement in budgeting vis-a-vis HRM (LB U) has a direct
andpositive impact on the effectiveness of HRM (EFF).
LBU had no direct and positive impact on EFF as indicated by the structural path
(8=0.00) from LBU to EFF. Thus, the hypothesis H6LBU was rejected.
H7EDM: External service providers involvement in decision-making vis-a-vis HRM
(EDM) has a direct and positive impact on the effectiveness of HRM (EFF).
EDM had no significant direct and positive impact on EFF as indicated by the
structural path (#=-0.06) from EDM to EFF. Thus the hypothesis H75DM was rejected.
H8EPA: External service providers involvement in process/activities vis-a-vis
HRM (EPA) has a direct and positive impact on the effectiveness of HRM (EFF).
EPA had a direct and positive impact on EFF (EFF) as indicated by the structural
path (/3=-0.19) from EPA to EFF. Thus, the hypothesis H8EPA was not rejected.
H9E&u: External service providers involvement in budgeting vis-a-vis LIRM
(EB U) has a direct andpositive impact on the effectiveness of HRM (EFF).
EBU bad a direct and positive impact on EFF as indicated by the structural path
(8=0.04) from EBU to EFF. Thus the hypothesis H9EBU was not rejected.
Table 5.34 presents a summary of results of Direct Effect Model (Ml) hypotheses
testing through SEM.
158
Table 5.34: MI-Hypotheses Testing through SEM M"Iee_Hpotbeses.a,.~_m . ~Results _ q
HI TDM Re ected H2 TPA Not Rejected H3TLu Not Rejected H4LDM Not Rejected HSLPA Not Rejected H6LBU Rejected H?EDM Rejected H8EPA Not Rejected
H9EBU Not Rejected
Fit Indices of Partially Mediated Model (M2)
In the partially mediated model (M2), first of all the relationship between role
measures as exogenous variables and status of HRM as endogenous was checked
which is followed by the relationship between role measures as exogenous
variables and effectiveness of HRM as endogenous variable and status of HRM as
exogenous variable and effectiveness of HRM (EFF) as endogenous variable. The
fit indices of M2 are given in Table 5.35.
Table 5.35: M2- Fit Indices from LISREL 8.50 Fit Indicators Value
Goodness- of-Fit Index GFI) 0.725 Adjusted Goodness-of- fit Index AG 0.686 Chi-Square Goodness-of- fit test 3171.99 Root Mean Square Error of Approximation (RMSEA) 0.070 Root Mean Square Residual (RMSR) 0.0910 Standardized Root Mean S uare Residual SRMR 0.0735 Comparative fit Index CFI 0.901 Normed Fit Index(NFI) 0917 Non-Normed fit Index(NNFI) 0.994 Relative Fit Index (RFI) 0.904 Incremental fit Index (IFI) 0.902 Parsimony Goodness- of-fit Index PGFJ) 0.666 Parsimy Normed- of-fit Index (PNFI) 0.865 Akaike's Information Criterion (AIC) 3525.995 Consistent Akaike's Information Criterion (CAIC) 4262.148 Chi-Square/Degrees of Freedom 3171.99/1714=1.85
It can be seen from the Table 5.35 that most of the fit indices of M2 are either
within the recommended range or close to it, hence signifying a good model fit.
159
Path Coefficients and Hypotheses Testing: Partially Mediated Model
In the partially mediated model (M2), both the direct and indirect relationships
between role measures, status of HRM (STA) and effectiveness of HRM (EFF)
were tested on the basis of standardized path coefficients. Partially mediated
structural model (M2) is presented in Exhibit 5.5. The results of hypotheses testing
of partially mediated model (M2) are presented below:
HIOTDM: Top management involvement in decision-making vis-a-vis HRM (TDM)
has a direct and positive impact on the status of HRM (STA).
TDM had no direct and positive impact on STA as indicated by the structural path
(/3=-0.03) from TDM to STA. Thus the hypothesis H10ThM was rejected.
H11 TpA: Top management involvement in process/activities vis-a-vis HRM (TPA)
has a direct and positive impact on the status of HRM (STA).
TPA had a direct and positive impact on the STA as indicated by the structural
path ((3=0.18) from TPA to STA. Thus the hypothesis H11TPA was not rejected.
H12TBU• Top management involvement in budgeting vis-a-vis HRM (BU) has a
direct and positive impact on the on the status of HRM (STA).
TBU had a direct and positive impact on STA as indicated by the structural path
(&0.12) from TBU to STA. Thus the hypothesis H12TBU was not rejected.
H13WM: Line managers involvement in decision-making vis-a-vis HRM (LDM)
has a direct and positive impact on the status of HRM (STA).
LDM had no direct and positive impact on STA as indicated by the structural path
(/3=-0.21) from LDM to STA. Thus the hypothesis H13LDM was rejected.
160
(ZW) I3PoW !$m1dHJ15 POIe1POW A1IBf J d :9'9;IQlgiX3
H14LP,A: Line managers involvement in process/activities vis-a-vis HRM (LPA)
has a direct and positive impact on the status of HRM (STA).
LPA had a direct and positive impact on STA as indicated by the structural path
(13=0.53) from LPA to STA. Thus the hypothesis H14LPA was not rejected.
H15LBU: Line managers involvement in budgeting vis-a-vis HRM (LB U) has a
direct and positive impact on the status of HRM (STA).
LBU had a direct and positive impact on STA as indicated by the structural path
(J3=0.02) from LBU to STA. Thus the hypothesis H15LBU was not rejected.
H16EDm.- External service providers involvement in decision-making vis-a-vis
HRM (EDM) has a direct and positive impact on the status of HRM (STA).
EDM had no direct and positive impact on STA as indicated by the structural path
(i=-O.24) from EDM to STA. Thus the hypothesis H16EDM was rejected.
H17EpA: External service providers involvement in process/activities vis-a-vis
HRM (EPA) has a direct and positive impact on the status of HRM (STA).
EPA had a direct and positive impact on STA as indicated by the structural path
(/3=0.43) from EPA to STA. Thus the hypothesis H17EPA was not rejected.
H18EBU: External. service providers involvement in budgeting vis-a-vis HRM
(EBU) has a direct and positive impact on the status of HRM (STA).
EBU had no direct and positive impact on STA as indicated by the structural path
(5=-0.07) from EBU to STA. Thus the hypothesis Hi8EBU was rejected.
H19TDM: Top management involvement in decision-making vis-a-vis HRM (TDM)
has a direct and positive impact on the effectiveness of HRM (EFF).
TDM had no direct and positive impact on EFF as indicated by the structural path
(J3=-4.06) from TDM to EFF. Thus the hypothesis H19TDM was rejected.
162
H2OTPA: Top management involvement in process/activities vis-a-vis HRM (TPA)
has a direct and positive impact on the effectiveness of HRM (EFF).
TPA had a direct and positive impact on EFF as indicated by structural path
(/3=0.02) from TPA to EFF. Thus the hypothesis H2OTPA was not rejected.
H21TBu: Top management involvement in budgeting vis-a-vis HRM (TBU) has a
direct and positive impact on the effectiveness of HRM (EFF).
TBU had a direct and positive impact on EFF as indicated by the structural path
(/j-0.10) from TBU to EFF. Thus the hypothesis H21TBU was not rejected.
H22LDM; Line managers involvement in decision-making vis-a-vis HRM (LDM)
has a direct and positive impact on the effectiveness of HRM (EFF).
LDM had a direct and positive impact on EFF as indicated by the structural path
(/3=0.25) from LDM to EFF. Thus the hypothesis H22LDM was not rejected.
H23LPA: Line managers involvement in process/activities vis-a-vis HRM (LPA)
has a direct and positive impact on the effectiveness of HRM (EFF).
LPA had no direct and positive impact on EFF as indicated by the structural path
(J3=-0.25) from LPA to EFF. Thus the hypothesis H23LPA was rejected.
H24LBU: Line managers involvement in budgeting vis-a-vis HRM (LBU) has a
direct and positive impact on the effectiveness of HRM (EFF).
LBU had no direct and positive impact on EFF as indicated by the structural path
(J3=-0.02) from LBU to EFF. Thus the hypothesis H24LBU was rejected.
H25EDM: External service providers involvement in decision-making vis-a-vis
HRM (EDM) has a direct and positive impact on the effectiveness of HRM (EFF).
EDM had a direct and positive impact on EFF as indicated by the structural path
(8=0.15) from EDM to EFF. Thus the hypothesis H25EDM was not rejected.
163
H26EpA: External service providers involvement in process/activities vis-a-vis
HRM (EPA) has a direct and positive impact on the effectiveness of HRM (EFF).
EPA had no direct and positive impact on EFF as indicated by the structural path
(3=-0.22) from EPA to EFF. Thus the hypothesis H26EpA was rejected.
H27EBu: External service providers involvement in budgeting vis-a-vis HRM
(EB U) has a direct and positive impact on the effectiveness of HRM (EFF).
EBU had a direct and positive impact on EFF (EFF) as indicated by the structural
path (8=0.12) from EBU to EFF. Thus the hypothesis H27EBU was not rejected.
H28STA: Status of HRM (STA) has a direct and positive impact on the
effectiveness of HRM (EFF)
STA had a direct and positive impact on EFF as indicated by the structural path
(8=1.01) from STA to EFF. Thus the hypothesis H28STA was not rejected.
Table 5.36 corresponds to the summary of results of Partially Mediated Model
(M2) hypotheses testing through SEM.
Table 5.36: M2-Hvootheses Testina throuah SEM
HIOTDM Rejected H2OTPA Not Rejected
HIlTPA Not Rejected H21 BU Not Rejected
H12T2c Not Rejected H22LDM Not Rejected
HI3LDM Rejected H23LPA Rejected
H14LPA Not Rejected H241BU Rejected
H15LBU Not Rejected H25EDM Not Rejected
Hl6EDM Rejected H26EPA Rejected
HI7Epq Not Rejected H27EBu Not Rejected
H18EBU Rejected H28STA Not Rejected
H19mM Rejected - -
164
Fit Indices of Fully Mediated Model (M3)
In the fully mediated model (M3), the direct effect of role measures on status of
HRM (STA) was tested. It also tests the effect of relationship between STA and
EFF. In this fully mediated model the effect of role measures on EFF was not
tested. Table 5.37 presents the fit indices of M3.
Table 5.37: M3-Fit Indices from LISREL 8.50 Fit Indicators Value
Goodness- of-Fit Index (GFI) 0.724 Adjusted Goodness-of- fit Index (AGFI) 0.688 Chi-Square Goodness-of- fit test 3175.60 Root Mean Square Error of Approximation (RMSEA) 0.070 Root Mean Square Residual (RMSR) 0.0912 Standardized Root Mean Square Residual SRMR 0.0737 Comparative fit Index (CFI) 0.901 Normed Fit Index(NFI) 0.916 Non-Normed fit lndex(NNFI) 0.995 Relative Fit Index (RFI) 0.905 Incremental fit Index (IFI) 0.902 Parsimony Goodness- of-fit Index (PGFI) 0.669 Parsimony Normed- of-fit Index (PNFI) 0.868 Akaike's Information Criterion (AIC) 3511.598 Consistent Akaike's Information Criterion (CAIC) 4210.319 Chi-Square/Degrees of Freedom 3175.6011723=1.84
Since most of the fit indicator values are within the recommended range or close to
the recommended values, it provides support to the model M3. Thus,'it can be said
that data fairly well supports the model.
Path Coefficients and Hypotheses Testing: Fully Mediated Model
In case of fully mediated model (M3), the different relationships between
exogenous and endogenous variables as discussed above were verified on the basis
of path coefficients. Exhibit 5.6 presents the fully mediated structural model (M3).
The results of hypotheses testing of fully mediated model (M3) are presented
below:
H29TDM: Top management involvement in decision-making vis-a-vis HRM (TDM) has a direct and positive impact on the status of HRM (STA).
TDM had no direct and positive impact on STA as indicated by the structural path
(5=-0.06) from TDM to STA. Thus, the hypothesis H29TDM was rejected.
H3OTPA: Top management involvement in process/activities vis-a-vis.HRM (TPA) has a direct and positive impact on the status of HRM (STA).
TPA had a direct and positive impact on STA as indicated by the structural path
(f3= 0.19) from TPA to STA. Thus, the hypothesis H30TPa was not rejected.
H31 mU: Top management involvement in budgeting vis-a-vis HRM (TBU) has a significant direct and positive impact on the on the status of HRM (STA).
TBU had a direct and positive impact on STA as indicated by the structural path
(/3=0.16) from TBU to STA. Thus the hypothesis H31TDM was not rejected.
H32LDM: Line managers involvement in decision-making vis-a-vis HRM (LDM) has a direct and positive impact on the status of FIRM (STA).
LDM had no direct and positive impact on STA as indicated by the as indicated by the structural path (Q=-0.10) from LDM to EFF. Thus, the hypothesis H32LDM was rejected
H33LPA: Line managers involvement in process/activities vis-a-vis HRM (LPA) has a direct and positive impact on the status of HRM (STA).
LPA had a significant direct and positive impact on STA as indicated by the
structural path (fi=0.43) from LPA to STA. Thus the hypothesis H33LPA was not
rejected.
Exhibit 5.6: Fully Mediated Structural Model (M3)
0.73 Si 0.48 S2 0.43 S3 0.74 S4 0.53 SS 0.66 S6 0.62 S7 0.38 SS 0.28 S9 0.71 SLO '7 0.54 Sll 'CO 0.78 S12 •gig 0.42 Sl3 ~l; .c, 022 514 ec 0.18 SLS "' R.6 0.66 S16 0.47 0.45 S17 ,
0.54 S18 ea 0.57 S19 -'p r ~
0.4'2 S?0 0.68\ -0.06 0.74 S6 .37
0.61 S21 0.73 S22 '71 0.19 0.79
S57 439 AAl 0.1 7
0.61 S25 0 '~ 1~ 0.10 0.5
S58 .69 0.65 S26 n .c~ 0.33 .66
0.74 S59 .56 0.67 328 0.]5 01
4.69 S29 7 03 0.99 S60 .36 0.38 S31 ^ ae -0.03 0.18 S32 n Oe~
0.28 S33 0 72 ~V. S61 .28 0.31 S34 0.85 0.$3 S35 n , X0.66 S62 _56 418 S36 "` EFF.
0.53 S3S 0.65 S63 15
0.57 S39 ^ A z
0.62 S40 A 0.41 S41 A 5?: 0.58 S42 0.56 S43 I?/
0.65 S45 A 0.42 S46 0.6, 4.-L6 S47 0.68 S48 0.39 S49 0.38 5S0 0.29 S51 0.47 552 Chi-Square=3175.60, dfL723, P-value=0.00000, RMSSEA 0.070
0.49 SS3 0.58 S54
167
H34L5u: Line managers involvement in budgeting vis-a-vis HRM (LBU) has a
direct and positive impact on the status of HRM (STA).
LBU had a significant direct and positive impact on STA as indicated by the
structural path (fl=0.02) from LBU to STA. Thus the hypothesis H34LBU was not
rejected.
H35EDM: External service providers involvement in decision-making vis-a-vis
HRM (EDM) has a direct and positive impact on the status of HRM (STA).
EDM had no direct and positive impact on STA as indicated by the structural path
(/3=-0.18) from EDM to STA. Thus the hypothesis H35EDM was rejected.
H36EPA: External service providers involvement in process/activities vis-a-vis
HRM (EPA) has a direct and positive impact on the status of HRM (STA).
EPA had a direct and positive impact on STA as indicated by the structural path
(&0.35) from EPA to STA. Thus the hypothesis H36EPA was not rejected.
H37EnU: External service providers involvement in budgeting vis-a-vis HRM
(EBU) has a direct and positive impact on the status ofHRM (STA).
EBU had no direct and positive impact on STA as indicated by the structural path
(fl=-0.03) from EBU to STA. Thus, the hypothesis. H37EBU was rejected.
H38STR: Status of HRM (STA) has a direct and positive impact on the
effectiveness of HRM function (EFF)
STA had a direct and positive impact on EFF as indicated by the structural path
(/3=0.99) from STA to EFF. Thus the hypothesis H38STA was not rejected.
1AQ
Table 5.38 depicts the summary of results of Fully Mediated Model (M3)
hypotheses testing through SEM.
Table 5.38: M3-Hypotheses Testing through SEM ~' Hypn~leses `" ' ~ Results
H297DM Rejected H30PPA Not Rejected
H31 mU Not Rejected
H32LDM Rejected
H33LPA Not Rejected
H34113u Not Rejected
H35EDM Rejected
H36Epg Not Rejected
H37EBU 'Rejected
H38 -A Not Rejected
5.8 Criterion Validity
Criterion-related validity is a measure of how well scales representing the various
exogenous variables are related to endogenous variables. To establish the criterion
validity of various constructs, the exogenous variables are correlated with the
endogenous construct. Ahire et al. (1996) recommended using SEM to estimate the
correlations between the various constructs because it takes into account
measurement error by estimating the measurement error variances from the data.
The relationship between exogenous and endogenous variables for direct effect
model (Ml), partially mediated model (M2) and fully mediated model (M3) as
measured by LISREL 8.50 are presented in Exhibits 5.4, 5.5 and 5.6 which
illustrate evidence of criterion-related validity. Further, from the tables 5.34, 5.36
and 5.38, it may be concluded that in cases where the hypotheses have not been
rejected, there is a direct and positive relationship between variables which is a
proof of criterion validity. Criterion-validity of direct effect model is high as
compared to partially mediated model and fully mediated model. Thus,
requirement of criterion validity is sufficiently well addressed.
169
5.9 Comparison of Alternate Models
Hair et al. (2008) suggested a competing models approach to SEM when
alternative formulations are suggested by the underlying theory. A model
comparison approach is consistent even if a given proposed model exhibits an
acceptable fit and cross-validates well, there may be alternative models, containing
different associations among the variables, which could show the same level of
goodness-of-fit. Thus, to compare one model to alternative models is a
fundamental practice in SEM (Bagozzi & Yi, 1988; Diamantopoulos & Siguaw,
2000; Hair et al. 2008). SEM generates variety of fit indices that can be used to
compare the alternate models. Appropriate indices close to the global fit are
obtained by estimating the structural models.
Graver and Mentzer (1999) pointed out that it is not possible to achieve perfect
values for all the fit indices as many fit indices are sensitive to sample size. It is
difficult to establish index values that differentiates good model from a poor model
across all situations (Hair et al., 2008). It is not necessary to report all the indices
of all the fit measures (Hooper et al., 2008; Hair et al., 2008) as there are no golden
rules for assessment of model fit, reporting a variety of indices is essential
(Crowley & Fan, 1997) since different indices indicate a different aspect of model
fit. Moreover, there is no agreement among researchers on the appropriate index
for assessing the overall goodness-of-fit of a model (Ping, 2004). However, it is
important to consider more than one fit measure (Jackson et al., 2009) and report at
least one goodness-of-fit index from both incremental and absolute index and one
badness-of-fit index besides, the chi-square value and associated degrees of
freedom (Hair et al., 2008; Malhotra & Dash, 2011). Even though many problems
are linked with the model chi-square, it is still important to recount chi-square
along with its degrees of freedom at all times (Hayduk et al., 2007). Chi-square is
one of the most commonly used fit index (Bagozzi & Heatherton, 1994;
Baumgartner & Homburg, 1996; Ping, 2004) and that is recommended with
moderate samples of 100 to 200 (Shook, et al., 2004).
Different researchers have recommended the use of different fit indices. CFI, GFI,
NFI and NNFI, are most commonly reported fit indices (McDonald & Ho, 2002).
CFI is one of the most popular fit index that is used for evaluation as it is the index
that is Ieast effected by sample size (Fan et al., 1999; Malhotra & Dash, 2011) and
170
the most stable fit index (Shook et al., 2004). RMSEA is also less affected by
sample size (Malhotra & Dash, 2011). Both AIC and CAIC indices are useful in
model comparison (Tabachnick & Fidell, 2007).
In the current study, structural models converge for all the three models (i.e. direct
effect model, partially mediated model and fully mediated model) but mixed
support is found for the hypothesized relationships between constructs. While in
some cases, direct and positive relationship existed between exogenous and
endogenous variables, in some cases the relationship was indirect through
mediating variables. In the present study, a number of fit indices were considered
to compare the alternate models (M1, M2 and M3).
As recommended by different researchers (e.g. Alden et al., 2006; Akaike, 1987;
Edelman, 2010; Hair et al., 2008; Hennig-Thurau et al., 2002; Knight et al., 1999;
Pajo et al., 2010; Rust et al. 1995; Tabachnick & Fidell, 2007; Vieira, 2011;
Williams & Holahan 1994), the fit indices used to compare the three models were
Xl, GFI, AGFI, AIC, CAIC, IFI, CFI. With the chi-square test, low values are
preferred. When using GFI, AGFI, or CFI, higher values signify better fit of the
model (Hair et al., 2008; Malhotra & Dash, 2011). With regard to the AIC and
CAIC, the lower the value, better the fit (Alden et al., 2006; Vieira, 2011).
Table 6.39: Comparison of Fit Indices of Alternate Models Alternate A2 GFI AGFI CFI IFI AIC CAIC models
Ml ' 274l6 J 732 0, 90 4 992 ` 0 993v. _3080 165 3728'81 M2 3171.99 0.725 0.686 0.901 0.902 - 3525.995 - 4262.14 M3 3175.60 0.724 0.688 0.901 0.902 3511.598 421031
Note: The shaded fit indices highlights the fit indices of the best model 1:e. the Direct Effect Model (M1) for the present research
Overall, the fit indices indicated that all three models fit the data. Although the
result supports both direct and indirect effect of role measures on status of HRM
and effectiveness of HRM. On the basis of fit indices values presented above, it
can be inferred that the direct effect model (MI) is the best alternative model. The
result strengthens the robustness of the direct effect model.
5.10 Tests of Differences
An independent sample t-test was carried out in order to test the hypotheses Hal to Hog. For hypotheses Ho10 to H018, one-way ANOVA was deployed since it
involved comparing three groups.
On the Basis of Sector (Manufacturing and Service)
11: There is no significant difference in the mean scores of top management involvement in decision-making vis-a-vis HRM (TDM between companies from manufacturing and service sectors.
Significant differences were not observed on the dimension TDM (t [172] =0.829,
p>0.05 between companies from manufacturing sector (Mean=24.48, SD=4.436)
and service sector (Mean=24.56, SD=4.065). Thus, the null hypothesis Holwas not rejected
H02: There is no sign ficant difference in the mean scores of top management involvement in process/activities vis-a-vis HRM (TPA) between companies from
manufacturing and service sectors.
Significant differences were not observed on the dimension TPA (t [172] =0.667,
p>0.05 between companies from manufacturing sector (Mean=22.26, SD=5.042) and service sector (Mean=21.40, SD=4.924). Thus, the null hypothesis H02 was
not rejected
Hai: There is no significant difference in the mean scores of top management
involvement in budgeting vis-a-vis HRM (TBU) between companies from
manufacturing and service sectors.
Significant differences were not observed on the dimension TBU (t [172] =0.675,
p>0.05 between companies from manufacturing sector (Mean= 22.74, SD=5.833)
and service sector (Mean= 23.09, SD=5.585). Thus, the null hypothesis H03was
not rejected.
172
Ho4: There is no significant difference in the mean scores of line managers
involvement in decision-making vis-a-vis HRM (LDAV between companies from manufacturing and service sectors.
Significant differences were not observed on the dimension LDM (t [172] =0.590, p>0.05 between companies from manufacturing sector (Mean=22.61, SD=4.269) and service sector (Mean=22.50, SD=3.989). Thus, the null hypothesis H04 was not rejected
Hoy: There is no significant difference in the mean scores of line managers involvement in process/activities vis-a-vis HRM (LPA) between companies from manufacturing and service sectors
Significant differences were not observed on the dimension LPA (t [172] =0.813,
p>0.05 between companies from manufacturing sector (Mean-23.32, SD=3.986) and service sector (Mean= 22.74, SD= 4.094). Thus, the null hypothesis H0 5was not rejected.
H6: There is no significant difference in the mean scores of line managers involvement in budgeting vis-a-vis HRM (LBO between, companies from manufacturing and service sectors
Significant differences were not observed on the dimension LBU (t [172] =0.987, p>0.05 between companies from manufacturing sector (Mean=18.98, SD= 6.650)
and service sector (Mean= 19.00, SD= 6.541). Thus, the null hypothesis Ho6 was
not rejected
H7: There is no significant difference in the mean scores of external service providers involvement in decision-making vis-a-vis HRM (8DM) between companies from manufacturing and service sectors
Significant differences were not observed on the dimension EDM (t [172] =0.819,
p>0.05 between companies from manufacturing sector (Mean=I 1.01, SD=5.107) and service sector (Mean=10.98, SD=4.802). Thus, the null hypothesis Ho7 was not
rejected
173
HQ8: There is no significant difference in the mean scores of external service
providers involvement in process/activities vis-a-vis HRM (EPA) between
companies from manufacturing and service sectors
Significant differences were not observed on the dimension EPA (t [172] =0.621,
p>0.05 between companies from manufacturing sector (Mean= 12.09, SD=4.736)
and service sector (Mean= 11.95, SD=5.180). Thus, the null hypothesis H08 was
not rejected
Ho9: There is no significant difference in the mean scores of external service
providers involvement in budgeting vis-a-vis HRM (EB U) between companies
from manufacturing and service sectors
Significant differences were not observed on the dimension EBU (t [172] =0.346,
p>0.05 between companies from manufacturing sector (Mean=9.75, SD=4.544)
and service sector (Mean=9.88, SD= 4.915). Thus, the null hypothesis H09 was
not rejected
Table 5.40A and 5.40B presents group statistics and results oft-test:
Table 5.40A: Group Statistics Construct Company type- sector N Mean Std. Deviation Std. Error Mean
TDM SER 82 24,56 4.065 .449 MAN 92 24.48 4.436 .463
,SPA SER 82 21.40 4.924 .544 MAN 92 22.26 5.042 .526
TBU SER 82 23.09 5.585 .617 MAN 92 22.74 5.833 .608
LDM SER 82 22.50 4.269 .471 MAN 92 22.61 3.989 -.416
LPA SER 82 22.74 4.094 .452 MAN 92 23.32 3.986 .416
LBU SER 82 19.00 6.541 .722 MAN 92 18.98 6.650 .693
EDM SER 82 10.98 4.802 .530 MAN 92 11.01 5.107 .532
EPA SER 82 11.95 5.180 .572 MAN 92 12.09 4.736 .494
EBU SER 82 9.88 4.915 .543 MAN 92 9.75 4.544 .474
174
Table 5.408: Indenendent Samnles T-Test
Construct Nature of Variance Levene's Test for
equality of variances t-test for equality of means
F • Sig. t df Si 2-tailed
TDM Equal variances assumed .047 .829 .I28 172 .899
TPA Equal variances assumed .185 .667 1.133 172 .259
TBU Equal variances assumed .177 .675 .399 172 .691
LDM Equal variances assumed .292 .590 -.174 172 .862
LPA Equal variances assumed .056 .813 -.932 172 353
LBU Equal variances assumed .000 .987 .022 172 .983
EDM Equal variances assumed .053 .819 -.047 172 .963
EPA Equal variances assumed .246 .621 -.181 172 .857
EBU Equal variances assumed .893 .346 .179 172 .859
On the Basis of Size (Small, Medium and Large)
H010: There is no significant difference in the mean scores of top management
involvement in decision-making vis-a-vis HAM (TDM) between small, medium
and large organizations.
Significant differences were not observed in the mean scores of small, medium
and large organizations on TDM (p>0.05). Thus, the null hypothesis Ho10 was not
rejected.
Holl: There is no significant difference in the mean scores of top management
involvement in process/activities vis-a-vis HRM (TPA) between small, medium
and large organizations.
Significant differences were not observed in the mean scores of small, medium
and large organizations on TPA (p>O.&5). Thus, the null hypothesis foil was not
rejected.
175
Ho12: There is no significant difference in the mean scores of top management
involvement in budgeting vis-a-vis HRM (TB U) between small, medium and large organizations.
Significant differences were not observed in the mean scores of small, medium
and large organizations on TBU (p>0.05). Thus, the null hypothesis H012 was not
rejected.
Ho13: There is no significant difference in the mean scores of line managers involvement in decision-making vis-a-vis HRM (LDM) between small, medium
and large organizations.
Significant differences were not observed in the mean scores of small, medium
and large organizations on LDM (p>0.05). Thus, the null hypothesis H013 was not
rejected.
H014: There is no significant difference in the mean scores of line managers
involvement in process/activities vis-a-vis HRM (LPA) between small, medium and large organizations.
Significant differences were not observed in the mean scores of small, medium
and Iarge organizations on LPA (p>0.05). Thus, the null hypothesis H014 was not rejected.
Ho1S: There is no significant difference in the mean scores of line managers involvement in budgeting vis-a-vis HRM (LBU) between small, medium and large
organizations.
Significant differences were not observed in the mean scores of small, medium
and large organizations on LBU (p>0.05). Thus, the null hypothesis HO15 was not
rejected.
176
Ho16: There is no significant difference in the mean scores of external service
providers involvement in decision-making vis-a-vis HRM (EDM) between small,
medium and large organizations.
Significant differences were not observed in the mean scores of small, medium
and large organizations on EDM (p>0.05). Thus, the null hypothesis H016 was not
rejected.
H01 7: There is no sign if cant difference in the mean scores of external service
providers involvement in process/activities vis-a-vis HRM (EPA) between small,
medium and large organizations.
Significant differences were not observed in the mean scores of small, medium
and large organizations on EPA (p>O.05). Thus, the null hypothesis Ho17 was not
rejected.
H0 18: There is no significant difference in the mean scores of external service
providers involvement in budgeting vis-a-vis HRM (EBU) between small, medium
and large organizations.
Significant differences were not observed in the mean scores of small, medium
and large organizations on EBU (p>0.05). Thus, the null hypothesis H01 was not
rejected.
Table 5.41A and 5.41B presents group statistics and results of independent
samples t-test respectively.
177
Table 5.41A: ANOVA Descriptives Constructs Size N Mean Std. Deviation
TDM
SMA 34 23.91 5.440 MED 43 24.91 3.778 LAR 97 24.56 3.997 Total 174 24.52 4.253
TPA
SMA 34 21.26 6.307 MED 43 22.33 4.951 LAR 97 21.86 • 4.502 Total 174 21.86 4.991
TBU
SMA 34 22.29 7.355 MED 43 22.67 5.899 LAR 97 23.22 4.954 Total 174 22.90 5.703
LDM
SMA 34 22.53 5.212 MED 43 22.02 4.601 LAR 97 22.80 3.418 Total 174 22.56 4.112
LPA
SMA 34 22.41 4.787 MED 43 23.05 3.786 LAR 97 23.27 3.874 Total 174 23.05 4.036
LBU
SMA 34 19.88 6.870 MED 43 17.07 7.350 LAR 97 I9.53 5.995 Total 174 18.99 6.580
EOM
SMA 34 I0.91 4.337 MED 43 10.16 4.348 LAR 97 I1.39 5.382 Total 174 . 10.99 4.951
EPA
SMA 34 11.79 4.721 MED 43 11,23 4.854 LAR 97 12.45 5.046 Total 174 I2.02. 4.937
EBU
SMA 34 9.82 4.026 MED 43 8.63 3.848 LAR 97 10.33 5.198 Total 174 9.81 4.709
178
Table 5.41B: ANOVA Results Construct Sum of Squares dl Mean Square F .Si .
TOM Between Group 19.147 2 9.573 .526 .592 Within Groups 3110.301 171 18.189
• Total 3129.448 173
TPA Between Groups 21.369 2 10.685 .426 .654 Within Groups 4288.039 171 25.076
Total 4309.408 173
TBU Between Groups 24.385 2 12.192 .372 .690 Within Groups 5602.954 171 32.766
Total 5627.339 173
LDM Between Groups 18.200 2 9.100 .535 .586 Within Groups 2906.726 171 16.998
Total 2924,925 173
LPA Between Groups 18.459 2 9.229 .564 .570 Within Grou s 2799,173 171 16.369
Total 2817.632 173
LBU Between Groups 213.471 2 106.736 2.508 .084 Within Groups 7276,506 171 42.553
Total 7489.977 173
EDM Between Groups 45.285 2 22.643 .923 .399 Within Groups 4195,709 171 24.536
Total 4240.994 173
EPA Between Groups 46.634 2 23.317 .956 .386 Within Groups 4169.274 171 24.382
Total 4215.908 173
EBU Between Groups 86.310 2 43.155 1.968 .143 Within Groups 3750.431 171 21.932
Total 3836.741 173
Table 5.42 presents a summary of results for independent samples t-test and one-
way ANOVA.
Table 5.42: Tests of Differences H 91a ses : ePerforrc ~~ Hol to Hog t-test Not Rejected
H070 to HIIS ANOVA Not Rejected Significant at p<0.05
5.11 Tests of Association
Chi-square test was performed in order to establish association, if any, between
company type and role measures. Scores on role measures were classified into
three categories viz, high, medium and low based on percentiles. Company type
I—
,(
was classified into two categories viz, on the basis of sector (manufacturing and
service) and size (small, medium and large). Following hypotheses were tested:
On the Basis of Sector (Manufacturing and Service)
Hol: There is no association between company's sector i.e. manufacturing and
service sector and top management involvement in decision-making vis-a-vis HRM (TDM).
Significant association does not exist between company type i.e. manufacturing and service organizations and top management involvement in decision-making
vis-a-vis HRM (TDM). Thus, the null hypothesis Hol was not rejected. The results
have been given in table 5.43.
Table 5.43: Chi-Square Tests Measures Value df Asymp. Sig. (2-sided)
earson Chi-Square 26.804 17 .061 Likelihood Ratio 29.458 17 .031 inear-by-Linear Association .016 1 .898 of Valid Cases 174
H02: There is no association between company's sector i.e. manufacturing and service sector and top management involvement in process/activities vis-a-vis
HRM (TPA).
Significant association does not exist between company type i.e. manufacturing
and service organizations and top management involvement in process/activities
vis-a-vis HRM (TPA). Thus, the null hypothesis Hot was not rejected. The results
have been given in table 5.44.
Table 5.44: Chi-Sauare Tests Measures Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 17.490 20 .621 Likelihood Ratio 21.140 20 .389 Linear-by-Linear Association 1.283 1 .257 N of Valid Cases 174
180
H03: There is no association between company's sector i.e. manufacturing and
service sector and top management involvement in budgeting vis-a-vis HRM
(TBU)
Significant association does not exist between company type i.e. manufacturing
and service organizations and top management involvement in budgeting vis-a-vis
HRM (TBU). Thus, the null hypothesis H03 was not rejected. The results have
been given in table 5.45.
Table 5.45: Chi-Sauare Tests Measures Value df Asymp. Sig.(2-sided)
Pearson Chi-Square 9.735 22 .989 Likelihood Ratio - 11.032 22 .974 Linear-by-Linear Association .160 1 .689 N of Valid Cases 174
Ho4: There is no association between company's sector i.e. manufacturing and
service sector and line managers involvement in decision-making vis-a-vis HRM
(LDM)
Significant association does not exist between company type i.e. manufacturing
and service organizations and line managers' involvement in decision-making vis-
a-vis HRM (LDM). Thus, the null hypothesis Ho4 was not rejected. The results
have been given in table 5.46.
Table 5.46: Chi-Sauare Tests Measures Value df Asymp. Sig.(2-sided)
Pearson Chi-Square 17.073 18 .518 Likelihood Ratio 19.341 18 .371 Linear-by-Linear Association .030 1 .862 N of Valid Cases 174
H05: There is no association between company's sector i.e. manufacturing and
service sector and line managers involvement in process/activities vis-a-vis HRM
(LPA)
181
Significant association does not exist between company type i.e. manufacturing
and service organizations and line managers involvement in process/activities vis-
a-vis HRM (LPA). Thus, the null hypothesis Ho5 was not rejected. The results
have been given in table 5.47.
Table 5.47: Chi-Sauare Tests Measures Value df' Asymp. Sig. (2-sided)
Pearson Chi-Square 16.942 18 .527 Likelihood Ratio 20.537 18 .303. Linear-by-Linear Association .869 1 .351 N of Valid Cases 174
H6: There is no association between company's sector i.e. manufacturing and
service sector and line managers involvement in budgeting vis-a-vis HRM (LBU)
Significant association does not exist between company type i.e. manufacturing
and service organizations and line manager involvement in budgeting vis-a-vis
HRM (LBU). Thus, the null hypothesis Hob was not rejected. The results have
been given in table 5.48.
Table 5.48: Chi-Square Tests
Measures Value df Asymp. Sig. (2-sided) Pearson Chi-Square 28.449 24 .242 Likelihood Ratio 33.319 24 .098 Linear-by-Linear Association .000 1 .983
N of Valid Cases 174
H7: There is no association between company's sector i.e. manufacturing and
service sector and external service providers involvement in decision-making vis-
a-vis HRM (EDM)
Significant association does not exist between company type i.e. manufacturing
and service organizations and external service providers invdlvement decision-
making vis-a-vis HRM (EDM). Thus, the null hypothesis Ho7 was not rejected.
The results have been given in table 5.49.
182
Table 5.49: Chi-Sauare Tests Measures Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 24.114 20 .237 Likelihood Ratio 28.940 20 .089 Linear-by-Linear Association .002 1 .963 N of Valid Cases 174
Hob: There is no association between company's sector i.e. manufacturing and
service sector and external service providers involvement in process/activities
vis-a-vis HRM (EPA)
Significant association does not exist between company type i.e. manufacturing
and service organizations and external service providers involvement in
process/activities vis-a-vis HRM (EPA). Thus, the null hypothesis H08 was not
rejected. The results have been given in table 5.50.
Table 5.50: Chi-Square Tests Measures Value df Asymp. Sig-sided)
Pearson Chi-Square 19.321 20 .501 Likelihood Ratio 23.280 20 .275 Linear-by-Linear Association .033 1 .856 N of Valid Cases 174
H09: ' There is no association between company's sector i.e. manufacturing and
service sector and of external service providers involvement in budgeting vis-a-
vis HRM (EBU)
Significant association does not exist between company type i.e. manufacturing
and service organizations and external service providers involvement in budgeting
vis-a-vis HRM (EBU). Thus, the null hypothesis Hog was not rejected. The results
have been given in table 5.51.
Table 5.51: Chi-Sauare Tests Measures Value df Asymp. Si (2-sided)
Pearson Chi-Square 13.344 19 .821 Likelihood Ratio 16.905 I9 .596 Linear-by-Linear Association .032 1 .858 N of Valid Cases 174
183
On the Basis of Size (Small, Medium and Large)
Ha10: There is no association between company's size i.e. small, medium and
large organizations and top management involvement in decision-making vis-a-
vis HRM (TDM.
Significant association does not exist between company type i.e. small, medium
and large organizations and top management involvement in decision-making vis-
a-vis HRM (TDM). Thus, the null hypothesis HoI0 was not rejected. The results
have been given in table 5.52.
Table 5.52: Chi-Square Tests Measures Value df As m . Si 2-sided
Pearson Chi-Square 40.055 34 .219 Likelihood Ratio 43.568 34 .126 Linear-by-Linear Association .305 1 .581 N of Valid Cases 174
Hall: There is no association between company's size i.e. small, medium and
large organizations and top management involvement in process/activities vis-a-
vis HRM (TPA)
Significant association does not exist between company type i.e. small, medium
and large organizations and top management involvement in process/activities vis-
a-vis FIRM (TPA).Thus, the null hypothesis Hell was not rejected. The results
have been given in table 5.53.
Table 5.53: Chi-Sauare Tests Measures Value df As m . Si (2-sided)
Pearson Chi-Square 42.957 40 .346 Likelihood Ratio 49.839 40 .137 Linear-by-Linear Association .149 1 .699 N of Valid Cases 174
H012: There is no association between company's size i.e. small, medium and
large organizations and top management involvement in budgeting vis-a-vis HRM
(TBU)
184
Significant association does not exist between company type i.e. small, medium
and large organizations and top management involvement in budgeting vis-a-vis
HRM (TBU). Thus, the null hypothesis Ho12 was not rejected. The results have
been given in table 5.54.
Table 5.54: Chi-Sauare Tests Measures Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 54.889 44 .126 Likelihood Ratio 60.870 44 .047 Linear-by-Linear Association .744 1 .389 N of Valid Cases 174
HQ13: There is no association between company's size i.e. small, medium and
large organizations and top line managers involvement in decision-making vis-
a-vis HRM (LDM)
Significant association does not exist between company type i.e. small, medium
and large organizations and line managers involvement in decision-making vis-a-
vis HRM (LDM). Thus, the null hypothesis H013 was not rejected. The results
have been given in table 5.55.
Table 5.55: Chi-Square Tests Measures Value df Asymp. Si.(2-sidç4)
Pearson Chi-Square 45.790 36 .127 Likelihood Ratio 46.569 36 .112 Linear-by-Linear Association .338 1 .56I N of Valid Cases 174
Ho14: There is no association between company's size i.e. small, medium and
large - organizations and line managers involvement in process/activities vis-a-
vis HRM (LPA).
Significant association does not exist between company type i.e. small, medium
and large organizations and line managers involvement in process/activities vis-a-
vis HRM (LPA). Thus, the null hypothesis Ho14 was not rejected. The results
have been given in table 5.56.
185
Table 5.56: Chi-Square Tests
Measures Value df Asymp. Sig. (2- sided)
Pearson Chi-Square 35.478 36 .493 Likelihood Ratio 36.499 36 .445 Linear-by-Linear Association 1.054 1 .304 N of Valid Cases 174
H915: There is no association between company's size i.e. small, medium and
large organizations and line managers involvement in budgeting vis-a-vis HRM
(LBU).
Significant association does not exist between company type i.e. small, medium
and large organizations and line managers involvement in budgeting vis-a-vis
HRM (LBU). Thus, the null hypothesis H015 was not rejected. The results have
been given in table 5.57.
Table 5.57: Chi-Sauare Tests Measures Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 39.734 48 .796 Likelihood Ratio 43.656 48 .651 Linear-by-Linear Association .101 1 .751 N of Valid Cases 174
H016: There is no association between company's size i.e. small, medium and
large organizations and external service providers involvement in decision-
making vis-a-vis HRM (ED.M).
Significant association does not exist between company type i.e. small, medium
and large organizations and external service providers involvement in decision-
making vis-a-vis HRM (EDM).Thus, the null hypothesis H016 was not rejected.
The results have been given in table 5.58.
Table 5.58: Chi-Sauare Tests Measures Value df Asymp. Sig.(2-siIed)
Pearson Chi-Square 46.825 40 .213 Likelihood Ratio 50.624 40 .121 Linear-by-Linear Association .645 1 .422 N of Valid Cases 174
186
H017: There is no association between company's size i.e. small, medium and
large organizations and external service providers involvement in
process/activities vis-a-vis HRM (EPA)
Significant association does not exist between company type i.e. small, medium
and large organizations and external service providers involvement in
process/activities vis-a-vis HRM (EPA).Thus, the null hypothesis Holz was not
rejected. The results have been given in table 5.59.
Table 5.59: Chi-Square Tests Measures Value df Asymp. Si (2-sided)
earson Chi-Square 35.127 40 .689 Likelihood Ratio 38240 40 .550 Linear-by-Linear Association .931 I .335
of Valid Cases 174
Ho18: There is no association between company's size i.e. small, medium and
large organizations and external service providers involvement in budgeting
vis-a-vis HKM (EBU)
Significant association does not exist between company type i.e. small, medium
and large organizations and external service providers involvement in budgeting
vis-a-vis HRM (EBU). Thus, the null hypothesis H018 was not rejected. The
results have been given in table 5.60.
Table 5.60: Ghi-Sauare Tests Measures Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 47.035 38 .149 Likelihood Ratio 55.748 38 .032 Linear-by-Linear Association 1.040 1 .308 N of Valid Cases 174
Table 5.61 presents a summary of results for chi-square test.
Table 5.61: Tests of Association
Hof to Ho18 Chi-square Not Rejected -Significant at p<0.05
187
CHAPTER 6: FINDINGS, DISCUSSIONS AND CONCLUSIONS
6.1 Findings and Discussions 6.2 Conclusions
CHAPTER 6: FINDINGS, DISCUSSIONS AND CONCLUSIONS
Chapter Overview
This chapter begins with a brief description of the findings based on the analysis
carried out. A discussion of the findings of the current research is carried out in
the light of prior research studies by other researchers. The last part deals with the
conclusions of the present study.
6.1 Findings and Discussions
Respondent/Responding Firm Profile
The respondents of the study were HR executives i.e. one from each organization
with around 64% of them occupying senior- level positions (e.g. Director-HR,
Chief People Officer, Vice President-HR etc.). Senior level HR executives are
believed to be suitable to provide information concerning HR issues. Since
research in the area too has commonly assumed human resource systems to be
objective and recognizable characteristics of organizations and not individuals,
therefore, the use of single respondent is justified. Prior studies in the area have
also considered the perceptions of a single. respondent as appropriate (Becker &
Huselid, 2006; Katou, 2008; Teo, 2000), Additionally, HR managers have been
used as respondents in other similar studies too (e.g. Andersen et. al., 2007;
Andolsek & Stebe, 2005; Budhwar, 2000a, 2000b; Budhwar & Sparrow, 1997;
Cunningham & Hyman, 1995; Fisher & Dowling, 1999; Gautam & Davis, 2007;
Hsu & Leat, 2000; Klass et. al., 1999; Larsen & Brewster, 2003; Perry & Kulik,
2008; Valverde et al., 2006).
The responding organizations represent a cross-section of industries, belonging to
companies of Indian and foreign origin, private and public sectors, service and
manufacturing sectors and companies of different sizes based on number of
employees. Cook and Ferris (1986), Dyer and Reeves (1995) and Purcell (1999)
have opined that the use of multiple industries can help to expand the scope of the
findings. All the responding organizations were relatively large in size having
more than 250 employees which is in line with suggestions of other researchers
188
such as Andolsek and Stebe (2005), Budhwar and Sparrow (1997), Dany et al.
(2008), Green et al. (2006), Mayne et al. (1996) and Perry and Kulik (2008).
Companies of this size are considered to ensure that the recognized firms had HR
departments in which HR practices were more formalized (de Kok & Uhlaner,
2001). Green et al. (2006) who studied organizations with more than 250
employees also suggested that large organizations are likely to have well-
established HR functions.
Therefore, the selection of respondents and responding organizations in the
current research was appropriate for a study on role of internal and external
agents in management of HR.
Response Rate
The response rate of the study was 32% which is high as compared to other
studies conducted in the area. The response rate of other similar studies have been
as low as 5% (Perry & Kulik, 2008), 8.56% (Hall & Torrington, 1998), 10.5%
(Valverde et al., 2006), 16% (Wood, 1995); 17% (Larsen & Brewster,
2003),18.6% (Budhwar, 2000a, 2000b) to 22.7% (Klass et al. ,1999). In the
current study, the response rate of 32% gives a considerable number of
respondents in absolute terms to produce consistent statistical results. Moreover,
item completion rate of 98.86% is another indication of the interest of the
participants in providing the response.
In order to proceed with SEM capabilities of LISREL using Maximum
Likelihood Estimation (MLE), the recommended minimum sample size is 50 but
in order to ensure stable MLE solutions, preferable sample size is 100-150 (Hair et
al., 2008). Joreskog and Sorbom (1993) suggested a formula [k (k - 1)12; where k
equals the number of variables] to compute the minimum sample size for SEM.
Following this, the minimum acceptable sample size for the present study would
be 51 since K=11.
In view of the fact that the present study had a sample of 174 companies, it well
exceeds the minimum requirement suggesting that SEM capabilities of LISREL
could be utilized. The sample size as reported in other similar studies with SEM
I89
using MLE with LISREL was 76 (Knight et al., 1999) and 100-200 (Lindquist et
al., 2001).
Non-response Bias
A comparison of responses of the two groups i.e. early and late respondents using independent sample T-test did not reveal any significant differences. Since non-
respondents are more similar to late respondents (Armstrong & Overton, 1977), it
points out that non-response bias has not affected the current study. Comparision
of firm characteristics indicated that the firms were representative of those
surveyed since they represented a cross-section of industries thus, also indicating
no evidence for non-response bias as suggested by Chan et al. (2004) and Teo (2000).
Since non-response bias has not affected the study results, thus, responses may be considered as suitable and representative of the target population.
Common Method Bias
Common method bias issue is addressed following the procedural and statistical
remedies as recommended by different researchers (e.g. Chang et al., 2010; Malhotra et al., 2006; Podsakoff & Organ, 1986; Podsakoff et al., 2003). In case of procedural methods, bias is minimized through design of the research
instrument such as protection of respondent anonymity and scale reordering.
While in statistical method, Harman's one-factor test was deployed. The results of EFA on all the variables revealed 15 factors with Eigen values greater than 1,
which accounted for 72.28% of the total variance. Since the first factor accounted
for 12.12 % of the total variance, it did not account for a majority of the variance.
Therefore, common method bias, which is one of the major sources of
measurement error in cross-sectional studies when data for exogenous and
endogenous variables are obtained from single respondent, had not crept in the
survey.
Hence, the results of the study reveal that all the items did not load on a single construct, thus, negating the presence of common method bias.
Measurement Model
Measurement model is assessed to explain how well the items represent
measurement instrument for the latent variables. Measurement analysis using EFA
and CFA was performed on all the scales viz. TDM, TPA, TBU, LDM, LPA,
LBU, EDM, EPA, EBU, STA and EFF used in the study.
Exploratory Factor Analysis (EFA): A principal components factor analysis
with varimax rotation was carried out on all items in each scale without placing
any restriction on number of factors to be extracted. EFA was conducted on each
scale independently to check the unidimensionality of constructs. To find out if the
data is appropriate for factor analysis, before proceeding with EFA, Kaiser-Meyer-
Olkin (KMO) Measure of Sampling Adequacy and Bartlett's Tests of Sphericity
were performed which were found acceptable in all the cases. Results of EFA
revealed that all the scales were unidimensional except LPA scale. EFA results for
LPA scale generated two factors whereas in case of LDM only one factor was
generated but the factor loading for. one of the items was less than the desirable
limit of 0.50. Thus in both the cases, EFA was again carried out and one item was
deleted which had the lowest loading. As a result, unidimensionality of both the
scales was achieved with strong item loadings.
The results of EFA revealed that in all cases the scales were unidimensional
except LPA scale. Moreover, loading values of the items for all the scales were
high except for LDM scale. Unidimensionality of LPA and LDM scales was
achieved after deleting an item with lowest loading and running the EFA again
on the remaining scale items to obtain improved loadings.
Confirmatory Factor Analysis (CFA): Although unidimensionality of all the
scales was achieved after running EFA, however, as a further check, CFA was
conducted to measure the SEM based reliability and validity of the scales.
Reliability
After unidimensionality of the scales was established, two types of statistical
reliability were computed viz, indicator reliability and scale reliability.
191
Indicator Reliability
The results of the study revealed that most indicators had loadings of more than 0.5
or close to it on the latent variables. Indicator reliability greater than 0.5 or close to
it is considered acceptable (Long, 1983; Schumacker & Lomax, 2004; Wu, 2005).
The indicator reliability in case of all the scales was found to be satisfactory in
light of the suggested values.
Scale Reliability
Cronbach's Coefficient Alpha: Reliability estimates of all the scales returned
Cronbach alpha values higher than the suggested 0.70.
Construct. Reliability (CR): The construct reliability values as calculated by the
recommended formulae were over 0.70 which is more than the suggested value of
0.6 for all the scales.
Variance Extracted (VE): The variance extracted values as obtained from the
prescribed formulae exceeded or were close to the recommended value of 0.5.
The researcher did not find any study in the area in which both indicator and
scale reliability were measured. Therefore, the current study addresses this gap.
All the scales demonstrated satisfactory indicator and scale reliability.
Validity
Different forms of translation (content and face validity) and construct validity
(convergent, discriminant, nomological and criterion validity) were determined in
the current study. Translation validity was addressed during instrument
development stage as reported in section 4.5 whereas construct validity was
assessed after final data collection. Results of construct validity are discussed
below:
Convergent Validity: Convergent validity was measured using various methods.
As all the scales of the present study possessed unidimensionality and high internal
consistency, proof of at least moderate convergent validity existed. Additionally,
192
all items were found to load on their hypothesized dimensions and the estimates
were positive and significant. Most of the parameter estimates in case of different
scales had loadings more than 0.60 or were close to 0.60, thus also indicative of
relatively high convergent validity. Moreover, all t-values were over 2 (p=0.001),
hence, signifying that convergent validity was high. In addition to this, convergent
validity of scales is computed using CFA fit indices viz. Bentler-Bonett Coefficient
and GFI in SEM. In the current study, Bentler-Bonett coefficient and GFI values of
all the scales were more than 0.9 or close to it, which provides strong evidence of
convergent validity of study scales.
Discriminant Validity: All the scales were tested for discriminant validity
following a two-step approach. In the first method, Harman's one-factor test was
conducted and the results of the study revealed that fourteen factors were generated
with 71.30% of the total variance, and factor 1 had only 12.70% of the variance.
Thus, the results indicate that all the items did not load on a single construct,
thereby indicating the presence of discriminant validity of the scales. While in the
second method, variance-extracted estimates for all possible pairs of constructs are
compared with the square of correlation estimate between these two constructs.
The variance extracted estimates were higher than the squared correlation
estimates in most of the cases. This indicates that the items of a latent construct
explain that construct better than they explain another construct which gives proof
of discriminant validity.
Nomological Validity; Since TDM, TPA, .TBU, LDM, LPA, LBU, EDM, EPA
and EBU are measures depicting role of internal and external agents' vis-a-vis
HRM, theoretically they are expected to correlate. All correlation values were
found to be positive and significant giving proof of nomological validity.
A number of empirical studies on the role of agents in HRM have methodological.
limitations. While most of the studies are case based (e.g. Bond & McCracken,
2005; Bond & Wise, 2003; Cascon-Pereira et al., 2006; Finegold & Frenkel, 2006;
Gennard & Kelly, 1997; Harris et al., 2002; Renwick, 2000; Thornhill & Saunders,
1998; Watson et al., 2007), a few empirical studies in the area do exist (e.g.
Andolsek & Stebe, 2005; Budhwar, 2000a, 2000b; Budhwar & Sparrow, 1997;
193
Dany et al., 2008; Srimannarayana, 2010; Valverde et al., 2006). However, most of
the empirical studies conducted in the area have not addressed the issue of scale
reliability and validity. Thus, the current study is distinct as it addresses the
different forms of validity such as translation (content and face validity) and construct validity (convergent, discriminant nomological and criterion validity)
issues.
All the scales exhibited high convergent, discriminant and nomological validity. Criterion validity was assessed along with the structural model
Structural Model
SEM capabilities of LISREL 8.50 software was used to evaluate the conceptual
research -models viz. Direct Effect Model (Ml), Partially Mediated Model (M2)
and Fully Mediated Model (M3) illustrated in Exhibit 4.4a, 4.4b and 4.4c. Since,
none of the moderating variables were found to be significantly correlated with the
study variables (i.e. all correlation values indicate weak correlations), they were
not included in the structural models.
Structural Model Fit Indices: M1, M2, M3
The three alternate models viz. Direct Effect Model (M1), Partially Mediated
Model (M2) and Fully Mediated Model (M3) were assessed on the basis of fit
measures. In the present study, as depicted in Exhibit 5.3, classification of fit measures as suggested by Malhotra & Dash (2011) was followed. Following other
researchers (e.g. Baumgartner & Homburg 1996; Hair et al., 2008; Jackson et al., 2009; Malhotra & Dash, 2011; Ping, 2004; Viera, 2011), the researcher followed
the criteria of reporting one fit index from each fit measure for description of
alternate models. In the present study, the results revealed that fits indices of the
three structural models represent the data well. The values of fit indices are
presented in Table 5.33, 5.35 and 5.37. All the values of fit indices are either
within the recommended range or close to the recommended values, indicating
good fit. ,
194
The three alternate structural models were assessed on the basis off! measures. Overall, the fit indices of alternate structural models indicated that all the three
models fit the data well, since most of the fit indices of all the three models are either within the recommended range or close to the recommended values.
Path Coefficients and Hypotheses Testing: Direct Effect Model Table 6.1 presents a summary of results of hypotheses testing of Direct Effect
Model (Ml) through SEM.
Table 6.1 Results of Hypotheses Testing: Direct Effect Model (M1)
ypotheses Results ! ,~ remarks ~ ~ ~:
H1TDM Rejected TDM has no direct and positive impact on EFF
H2rpA Not Rejected TPA has a direct and positive impact on EFF
H3TBU Not Rejected TBU has a direct and positive impact on EFF
H4LDM Not Rejected LDM has a direct and positive impact on EFF
H5LpA Not Rejected LPA has a direct and positive impact on EFF
H61u Rejected LBU has no direct and positive impact on EFF
H7EDM Rejected EDM has no direct and positive impact on EFF
HSEpg Not Rejected EPA has a direct and positive impact on EFF
H9EBU Not Rejected EBU has a direct and positive impact on EFF
The results for Direct Effect Model (M1) may be summarized as follows:
❖ TDM had no direct and positive impact on EFF but TPA and TBU have a
direct and positive impact on EFF.
•,'• LDM and LPA had a direct and positive impact on EFF but LBU has no
direct and positive impact on EFF.
❖ EDM had no direct and positive impact on EFF but EPA and EBU have a
direct and positive impact on EFF.
Path Coefficients and Hypotheses Testing: Partially Mediated Model
Table 6.2 presents a summary of results of hypotheses testing of Partially Mediated
Model (M2) through SEM.
Table 6.2 Results of Hypotheses Testing: Partially Mediated Model (M2)
Bypothescs fReul[t ~s yS S v n .y,-.d,. Remarksi"u
HIOTDM Rejected TDM has no direct and positive impact on STA HII TPA Not Rejected TPA has a direct and positive impact on STA H12Tvu Not Rejected TBU has a direct and positive impact on STA H13LDU Rejected LDM has no direct and positive impact on STA H14L,A Not Rejected LPA has a direct and positive impact on STA H1511 Not Rejected LBU has direct and positive impact on STA HI6EDU Rejected EDM has no direct and positive impact on STA H17EPA Not Rejected EPA has a direct and positive impact on STA H18EBU Rejected EBU has no direct and positive impact on STA H19 r, Rejected TDM has no direct and positive impact on EFF
H20TPA Not Rejected TPA has direct and positive impact on EFF
H21TBU Not Rejected TBU has a direct and positive impact on EFF H22LDM Not Rejected LDM had a direct and positive impact on EFF H23LPA Rejected LPA has no direct and positive impact on EFF H24LBu Rejected LBU has no direct and positive impact on EFF
H25EDM Not Rejected EDM has a direct and positive impact on EFF. H26EPA Rejected EPA has no direct and positive impact on EFF
H27EBU Not Rejected EBU has a direct and positive impact on EFF H28STA Not Rejected STA has a direct and positive impact on EFF
The results for Partially Mediated Model (M2) may be summarized as
follows:
❖ TDM had no direct and positive impact on STA but TPA and TBU do have
a direct and positive impact on STA.
❖ LDM had no direct and positive impact on STA, however, LPA and LBU
do have a direct and positive impact on STA.
❖ EDM and EBU had no direct and positive impact on STA but EPA has a
direct and positive impact on STA.
❖ TDM had no direct and positive impact on EFF but TPA and TBU do have
a direct and positive impact on EFF.
:• LPA and LBU had no direct and positive impact on EFF but LDM has a
direct and positive impact on EFF.
❖ EDM and EBU had a direct and positive impact on EFF but EPA has no
direct and positive impact on EFF.
❖ STA had a direct and positive impact on EFF.
196
Path Coefficients and Hypotheses Testing: Fully Mediated Model
Table 6.3 presents a summary of results of hypotheses testing of Fully Mediated Model (M3) through SEM.
Table 6.3 Results of Hvootheses Testina: Fully Mediated Model [M3l V013'Potheses Results ~Rek irt a !Cs ,.
H29TDM Rejected TDM has no direct and positive impact on STA H30TPA Not Rejected TPA has a direct and positive impact on STA H31TBU Not Rejected TBU has a direct and positive impact on STA H32LDM Rejected LDM has no direct and positive impact on STA H33LPA Not Rejected LPA has a direct and positive impact on. STA H34LBU Not Rejected LBU has direct and positive impact on STA H35EDM Rejected EDM has no direct and positive impact on STA H36EPA Not Rejected EPA has a direct and positive impact on STA H37EBu Rejected EBU has no direct and positive impact on STA H38STR Not Rejected STA has a direct and positive impact on EFF
The results for Fully Mediated Model (M3) may be summarized as follows:
❖ TDM had no direct and positive impact on STA but TPA and TBU do have
a direct and positive impact on STA. ❖ LDM had no direct and positive impact on STA although LPA and LBU do
have a direct and positive impact STA. •• EDM and EBU had no direct and positive impact on STA but EPA" had a
direct and positive impact on STA. :• STA had a direct and positive impact on EFF.
Due to paradigm shift in the business environment, people management issues are becoming business issues and internal and external agents are reaching out
to take control over the HR function. In this context, several researchers have maintained the role of internal and external agents in HRM decision-making,
process/activities and budgeting for different HRM functions (e.g. Casco'n-
Pereira et al., 2006; Cook, 1999; Chung et al., 1987; Finegold & Frenkel, 2006;
Galanaki & Papalexandris, 2005; Hall & Tarrington, 1998; Harper, 1993; Jonas et al., 1990; Khatri & Budhwar, 2002.; Mahoney & Brewster, 2002; McConville
197
& Holden, 1999; Papalexandris & Panayotopoulou, 2005; Valverde et al., 2006;
Whittaker, 1990).
The involvement of agents in HRM has led to the enhanced organizational
effectiveness in addressing people management issues (Schuler, 1990). Some
research studies have indicated the positive impact of involvement of agents on
the overall effectiveness of HRM (Budhwar, 2000a; Budhwar & Sparrow, 1997;
Valverde et al., 2006). Ferris et al.'s (1999) study reported the two perspectives
of effectiveness of HRM that need empirical attention that is the effectiveness
with which HRM policies and practices are implemented and the effectiveness
of these practices in producing desired results. In addition to this, some studies
have indicated that there is an indirect relationship between the role of internal
and external agents in management of human resources and effectiveness of
HRM (e.g. Guest & Conway, 2011; Hope Hailey et al., 2005; Valverde et al.,
2006). The involvement of agents in HRM depends on the size and shape of
HR department, organization and role of HR department (Larsen & Brewster,
2003). The involvement of agents in HR practices lead to better HR outcomes
which in turn affect the effectiveness of HRM and firm performance (e.g.
Andersen et al., 2007; Chand & Katou, 2007; Wan et al., 2002).
In the Iight of prior studies as discussed above, mixed support was found for the
findings of the present study. The result of the present study partially
corroborates with the finding of the previous researchers. In case of all the three
models, direct and positive -relationship was found between the study variables
in most cases (results presented in tables 6.1, 6.2, 6.3), however, in some cases
direct and positive relationship could not be established between the study
variables owing to the fact that there is variations in the work environment of
India and other countries.
Even though the structural models did converge in all the three cases, mixed
support was found for the hypothesized relationships between the constructs.
198
Criterion Validity
The relationship between exogenous and endogenous variables in the current
study shows that there is a direct and positive linkage. It is notable that in most
cases the hypotheses were not rejected. This provides sufficient evidence of
criterion validity. However, criterion-validity of direct effect model is high as
compared to partially mediated model and fully mediated model.
Hence, the requirementfor criterion validity is satisfactorily addressed.
Comparison of Alternate Models
Several fit indices generated in LISREL were used to compare the alternate
models viz. Direct Effect Model (MI), Partially Mediated Model (M2) and
Fully Mediated Model (M3). In line with the suggestions of researchers (e.g.
Akaike, 1987; Edelman, 2010; Hennig-Thurau et al., 2002; Knight et al., 1999;
Rust et al. 1995; Vieira, 2011), model fit indices viz. x2, GFI, AGFI, AIC,
CAIC, IFI, CFI were considered to compare and select the best possible model
for the present study. Table 5.39 presents the values of fit indices used in the
current study. On the basis of fit indices presented in Table 5.39, one conclusion
that could be drawn is that among the three alternate models the fit indices of
Ml are better than M2 and M3. AIthough the results provide mixed support for
both the direct and indirect effect of role measures on the effectiveness of IIRM
but the direct effect of role measures as indicated by the path coefficients was
more as compared to the indirect effect of role measures on effectiveness of
HRM. The role of the mediator was not as strong as the direct effect.
The result of comparision of fit indices suggests that among the three
alternate models, M1 is the best possible model since the fit indices of Ml are
better than the other models.
Tests of Differences and Association
Company type was classified into two categories viz. sector
(manufacturing/service), and size (small/medium/large) of organization. An
independent sample t-test was deployed in order to compare differences in
199
company type on TDM, TPA, TBU, LDM, LPA, LBU, EDM, EPA and EBU
for sector (manufacturing/service) and one-way ANOVA for comparision of
differences between three groups based on size. Chi-square test was performed
in order to establish association, if any, between company type and TDM, TPA,
TBU, LDM, LPA, LBU, EDM, EPA and EBU. Scores on role measures were
classified into three categories viz, high, medium and low based on percentiles.
Table 6.4 presents the summary results.
Table 6.4: Results of Tests of Difference and Association
Significant differences were not observed
Hol to Hag T-test Not on the dimensions TDM, TPA, TBU, LDM, Rejected LPA, LBU, EDM, EPA, EBU between
manufacturing and service companies Significant differences were not observed
Not on the dimensions TDM, TPA, TBU, HHo18o ANOVA Rejected LDM, LPA, LBU, EDM, EPA, EBU
between small, medium and large organizations
Significant association does not exist Chi- Not between company type i.e. manufacturing
Hol to Hog square Rejected and service organizations and TDM, TPA, TBU, LDM, LPA, LBU, EDM, EPA, EBU dimensions Significant association does not exist
Ho'0 to Chi- Not between company type i.e. small, medium
H018 square Rejected and large organizations . and TDM, TPA, TBU, LDM, LPA, LBU, EDM, EPA, EBU dimensions
-Significant at p<0.05
Some researchers have pointed out that size of the organization plays an
important role in determining the involvement of agents in HRM (Poole &
Jenkins, 1997; Shaw et al., 1993). Various research studies have indicated the
effect of size of an organization and the involvement of internal agents on the
human resource practices of organizations (Budhwar, 2000a; Shaw et al., 1993).
For instance, Iarge organizations tend to have more formal HR practices
(Budhwar, 2000b). Bennett et al. (1998) explained the influence of industry on
human resource . practices. Several researchers argued that business
organizations in the service sector were more likely to have a strategic approach
to HRM than manufacturing organizations thereby affecting the role of agents
200
(e.g. Marginson et al., 1988; Othman & Ismail, 1996). Srimannarayana (2010)
reported the differences between manufacturing and service sector companies
on the role of line managers in HRM.
From the results presented in Table 6.4, it can be concluded that significant
differences were not observed between company type and different study scales.
The results do not corroborate with the findings of the previous researchers.
Thus, it can be inferred that sector and size do not have any impact on the role
of internal and external agents in management of HR.
Hence, significant differences as well as association were not observed
between company type (i.e. manufacturing and service companies and small,
medium and large organizations) and role of internal and external agents (i.e.
TDM, TPA, TBU, LDM, LPA, LBU, EDM, EPA and EBU) in HRM.
6.2 Conclusions
The conclusion drawn from the findings of the study are given below:
Respondents
❖ Most of , the respondents of the study were senior HR executives (e.g.
Director-HR, Chief People Officer, Vice President-HR etc.).
Responding Firms
❖ The responding organizations represent a cross-section of industries,
belonging to companies of Indian and foreign origin, private and public
sectors, service and manufacturing sectors and companies of different sizes
based on number of employees. All the responding organizations were
relatively large in size having more than 250 employees.
Response Rate
•'r The response rate of the study was 32% which is high as compared to other
studies conducted in the area.
❖ Item completion rate of 98.86% indicates the interest of the participants in
providing the response and therefore, effectiveness of the survey.
201
Non-response Bias
❖ The results of independent sample T-test did not reveal any significant
differences which points out that non-response bias has not affected the
current study.
Common Method Bias
❖ The results of Harman's one-factor test revealed that all the items did not
load on a single construct. Consequently, indicating that common method
bias has not crept in the survey.
Measurement Model
In measurement model, scales unidimensionality, reliability and validity issues
were addressed. Both EFA and CFA were carried out to assess the study scales.
❖ Unidimensionality: Measurement model analysis was performed on all the
study scales. The results obtained in EFA showed that most of the study
scales were unidimensional in nature except LPA (i.e. two factors were
generated) and LDM (i.e. one item was having low loading). Following the
pro cedüre recommended by Hair et al., 2008, EFA was again run on LDM
and LPA to obtain unidimensional scales having statistically strong
loadings. In both LDM and LPA scales, one item each was deleted having low loading after which strong loading values were obtained.
+ Confirmatory factor Analysis: After obtaining the unidimensional scales,
CFA were performed to assess the SEM based reliability and validity.
❖ Reliability: Different types of reliability were assessed:
■ Indicator reliability for most of the indicators was found to be
satisfactory.
■ Scale reliability was assessed by means of Cronbach's coefficient
alpha, construct reliability and variance extracted. All the scales exhibited acceptable scale reliability.
❖ Validity: Two types of validity (translation and construct validity) were
considered in the present research. Translation validity includes content and
face validity and was assessed during instrument development and pilot
testing. After final data collection, construct validity was estimated.
Construct validity includes convergent, discriminant and nomological
validity which were part of measurement model, the last form of validity
was part of structural model. Support for all forms of validity was
established in the current study.
Structural Model
In structural model, SEM capabilities of LISREL were used to find out the
relationship between different variables. The three alternate models were
assessed on the basis of model fit indices and path coefficients to test the
hypothesized relationships. The testing of relationships between the study
variables is followed by criterion validity and comparision of alternate models.
❖ Model Fit Indices: Appropriate indices close to the global fit were obtained
by estimating the structural models. Most of the fit indices of all the three
alternate models were either within the acceptable limits or close to it.
+ Path Coefficients and Hypotheses Testing: In the current study, structural
models converge for all the three models (Ml, M2 and M3) but mixed support
was found for the hypothesized relationships between constructs.. While in
some cases, direct and positive relationship existed between exogenous and
endogenous variables, in some cases the relationship was indirect through
mediating variables.
❖ Criterion Validity: In present study, sufficient support was found for criterion
validity.
❖ Comparision of Alternate Models: All the alternate models were compared
on the basis of select fit indices. The comparision of models revealed that M1
had the best fit indices. It signifies that the direct effect of role measures on
effectiveness of HRM is more as compared to indirect effect of role measures
on effectiveness of HRM.
203
Test of Differences and Association
❖ Companies were classified into two categories viz. sector (manufacturing
and service) and size (small, medium and large). Results of independent
sample T-test and one way ANOVA revealed that significant differences
did not exist between company type (sector and size) and role measures.
❖ Results of Chi-square test revealed that significant association did not exist
between company type (sector and size) and role measures.
CHAPTER 7: MANAGERIAL IMPLICATIONS AND FUTURE
RESEARCH DIRECTIONS
7.1 Managerial Implications and Contributions of the Study 7.2 Future Research Directions
CHAPTER 7: MANAGERIAL IMPLICATIONS AND FUTURE
RESEARCH DIRECTIONS
Chapter Overview
This chapter highlights the managerial implications and contributions of the study
based on the findings and also puts forward the likely directions for future
research.
7.1 Managerial implications and Contributions of the Study
In today's fast changing business environment, HR is a key element in the growth
of an organization. Only effective & efficient HR gives an organization
competitive edge over its competitors. The involvement of top management, line
managers & external, service providers in decision making, process/activities and
budgeting vis-a-vis HRM ensures strategic management of HR issues. The current
study has implications for both academicians and practitioners in the management
of human resources. Some of the contributions of the present study to existing
theory and practice are mentioned below:
U The present study has significant theoretical contributions to make. Since
most of the previous studies have focused on just one of the agents or, at
most, on two agents, there is no developed literature incorporating the study
of all agents. Thus, the present study, by investigating into the role of
internal and external agents in HRM, contributes to the existing theory and
provides useful insights for both academicians and practitioners.
❑ The study offers and tests three alternate conceptual models of role of
internal and external agents vis-a-vis HRM and their linkage with status
and effectiveness of HRM. The results of the study have implications for
both practitioners and human resource researchers in understanding the
contribution of these agents in HRM in organizations in the Indian context.
U The role of internal and external agents vis-a-vis HRM has been a relatively
under researched area. Moreover, most previous studies in the area are
qualitative in nature thus, raising methodological issues. The current study
is based on empirical data and therefore addresses this problem.
❑ An outcome of the study is the development of a reliable and valid
instrument for measuring the various dimensions of role of internal and
external agents vis-a-vis HRM. Thus, the research instrument is expected to
assist HR researchers and practitioners in the analysis of role of these
agents.
U While most of studies on role of agents have been conducted in the Western
world, the current research adds to the literature by drawing its sample from
India, where economic reforms have attracted a large number- of multinationals, due to which there is paradigm shift in the HRM scenario.
❑ The study explores the role of internal and external agents vis-a-vis HRM
and its relationship with status and effectiveness of HRM. The findings of
the study are expected to fill the missing link as most previous studies have
focused on the role of these agents in HRM only without establishing any
relationship with HRM outcomes.
❑ Since the present research investigates the link between role of agents and
status and effectiveness of HRM in Indian context, the results of the
research are likely to throw light on the present scenario of role of agents in
FIRM in India. The findings will be of use to researchers in providing
insights of the Indian corporate terrain.
❑ By linking the various dimensions of role of internal and external agents
vis-a-vis HRM with status and effectiveness of HRM, the results of the
present study provide support to the idea that involvement of agents in
HRM has positive implications. Thus, it can be inferred from the findings
of the study that the involvement of internal and external agents vis-a-vis
HRM has favourable outcomes.
❑ In the current research, structural equation modeling is deployed which is a
robust technique for examining multiple relationships simultaneously in a
single model (e.g. Anderson & Gerbing, 1988; Graver & Mentzer, 1999;
Hair er al., 2008; Malhotra & Dash, 2011). Thus, the current research is
expected to contribute methodologically to the existing stream of research.
❑ The study also throws light on the role of internal and external agents in
HRM with respect to company type (sector and size). The findings on the
basis of company type offer useful insight into the HR landscape in India.
7.2 Future Research Directions
Every research is a small effort in the journey to build theory. Each researcher
starts from where the previous researchers have left, a researcher contributes his
efforts, and finally leaves the matter for future researchers. Based on the present
study, some directions for future research may be forwarded:
❑ Through the present research, an effort was made to develop an instrument
for measuring the role of internal and external agents vis-a-vis HRM. Since
the scope of current study is limited to India, this research instrument can
be replicated in other parts of the world to cross-validate it on other
samples. Wherever necessary, changes can be incorporated in the
instrument and the modified instrument must be tested to further check its
unidimensionality, reliability and validity.
U In the present study, survey methodology was adopted to collect the data
from the respondents. The survey yielded 32% response rate which is high
as compared to other similar researches conducted in the area. However, an
intensive follow-up on non-respondents would enhance the response rate
and would provide further support to the study.
❑ The current study is based on data obtained from HR managers through a
structured instrument. Future researchers may .also include other
stakeholders such as internal and external agents in data collection. This
will help in getting a more comprehensive and a richer view of things.
U The current research attempts to establish the link between role measures
with status and effectiveness of HRM. Although, results provide positive
support for the relationship between role measures, status of HRM and
effectiveness of HRM, there is need to cross-validate the findings of current
study in other countries.
207
❑ In the present study, most findings support the direct and positive
relationship between exogenous and endogenous variables. However, direct
and positive relationship could not be established between some variables.
It is believed that the relationship between the measures may be affected by
the interplay of other mediating variables which needs to be explored in
future researches.
U In the current study, the sample frame consists of 550 business
organizations operating across India. Future researchers can take up more
comprehensive sample frames having organizations operating across the
globe which may help to generate more generalizable results and may also
help in comparing the organizations operating in different countries.
❑ In the current study, data was collected through mail methodology and
personal visits. In future researches, data collection process can be
improved by supplementing with other data collection methods following
Podsakoff and Organ (1986) and Podsakoff et al. (2003).
❑ Since in the present research, the researcher relied on the data obtained
through structured questionnaire, the same may be supplemented with
qualitative methodology to further strengthen the study as suggested by
Becker and Gerhart (1996).
U In the current study, data for both exogenous and endogenous variables
r
were collected simultaneously. In order to further strengthen the study, to
ascertain better relationship between exogenous and endogenous variables,
data for both exogenous and endogenous variables may be collected
following longitudinal research design.
❑ Data for both role measures (exogenous variables) and effectiveness of
HRM (endogenous variable) were collected from the same respondent in
the study. Although, the responses were checked for any possible biases
that may have crept in due to common source problems, future researchers
may obtain the data for role measures and effectiveness of HRM from
different respondents to further eliminate chances of any such bias.
208
REFERENCES
Adams, K. (1991). Externalisation versus specialisation: What is happening to personnel? Human Resource Management Journal, 1(4), 40-54.
Adams, J„ Khan, H. T. A., Raeside, R. & White, D. (2007). Research Methods for Graduate Business and Social Science Students. New Delhi; Sage Publication Inc.
Adler, P. S. (2003). Making the HRM outsourcing decision. MIT Sloan Management Review, 45, 53-60.
Agrawal, R. K. (2010). Relationship between line and human resource executives in Indian organisations. Int. J. Indian Culture and Business Management, 3(3), 285-306.
Ahire, S., Golhar, D. & Waller, M. (1996). Development and validation of TQM implementation constructs. Decision Sciences, 27 (1), 23-56.
Ahmad, S. & Schroeder, R. G. (2003). The impact of human resource management practices on operational performance: Recognizing country and industry differences. Journal of Operations Management, 21, 19-43.
Akaike, H. (1987). Factor Analysis and AIC. Psychometrika, 52, 317-332.
Alden, D., Steenkamp, J., & Batra, R. (2006). Consumer attitudes toward marketplace globalization: Structure, antecedents and consequences. International Journal of Research in Marketing, 23, 227-239.
Alewell, D., Hauff, S., Thommes, K. & Weiland, K. (2009). Triggers of HR outsourcing decisions -an empirical analysis of German firms. The International Journal of Human Resource Management, 20(7), 1599-1617.
Andersen, A. (1996). Outsourcing human resource functions. Supervision, 57, 3.
Anderson, J. C. & Gerbing, D. W. (1982). Some methods for respecifying measurement models to obtain unidimensional construct measurement. Journal of Marketing Research, 19(4), 453-460.
Anderson, J. C. & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, I03(3), 411-423.
Anderson, J. C. & Gerbing, D. W. (1991). Predicting the performance of measures in a confirmatory factor analysis with a pretest assessment of their substantive validities. Journal ofApplied Psychology, 76(5), 732-740.
Andersen, K. K., Cooper, B. K. & Zhu, C. J. (2007). The effect of SHRM practices on perceived firm financial performance: Some initial evidence from Australia. Asia PaciftcJournal ofHuman Resources, 45(2), 168-179.
Andolsek, D. M. & Stebe, J. (2005). Devolution or (de)centralization of HRM function in European organizations, The International Journal of Human Resource Management, 16 (3), 311-329.
Ang, R. P. & Huan, V. S. (2006). Academic expectations stress inventory. Educational and Psychological Measurement. 66(3), 522-539.
Ansoff, I. H. (1991). Strategic management in a historical perspective. International Review of Strategic Management, 2(l), 3-69.
209
Ardichvili, A. & Gasparishvili, A. (2001). Human resource development in an industry in transition: The case of the Russian banking sector. Human Resource Development International, 4(1), 47-63.
Armstrong, M. (1998). Managing People: A Practical Guide for Line Managers. London: Kogan Page.
Armstrong, M. & Brown, D. (2008). Strategic Reward Making it Happen. (First Edition), New Delhi: Kogan Page India, 193-206.
Armstrong, M. & Cooke, R. (1992). Human resource management in action: A joint approach, in Armstrong, M. (Ed.), Strategies for Human Resource Management: A Total Business Approach, London: Kogan Page.
Armstrong, J. S. & Overton, T. S. (1977). Estimating nonresponse bias in mail surveys. Journal of Marketing Research, 14(3), 396-402.
Arthur, J. B., & Boyles, T. (2007).Validating the human resource system structure: A levels-based strategic I-IRM approach. Human Resource Management Review, 17, 77-92.
Autor, D. H. (2003). Outsourcing at will: The contribution of unjust dismissal doctrine to the growth of employment outsourcing. Journal of Labor Economics, 21(1), 1-42.
Azmi, F. T. (2008). From picnic organizers to strategists: Turn of the wheel for human resource managers. Eurasian Journal of Business and Economics, 1 (1), 37-60.
Azmi, F. T. (2010). Devolution of HRM and organizational performance: Evidence from India. International Journal of Commerce and Management, 20(3), 217-231.
Azmi, F. T. (2011). Strategic human resource management and its linkage with FIRM effectiveness and organizational performance: Evidence from India. The International Journal of Human Resource Management, 22(18), 3888-3912.
Azmi, F. T. & Mushtaq, S. (2010). Charting the devolution landscape: Rhetoric and reality. Integral Review A Journal of Management, 3(1), 3-20.
Babcock, P..(2004). SIicing off pieces of HRM. HR Magazine 49, 70-78.
Bae, -J. & Lawler, J. J. (2000). Organizational and HRM strategies in Korea: Impact on firm performance in an emerging economy. Academy of Management Journal, 43(3), 502-517.
Bagozzi, R. P. (1981). An examination of the validity of two models of attitude. Multivariate Behavioral Research. 18, 133-145.
Bagozzi, R. P., & Heartherton, T. F. (1994). A general approach. to representing multifaceted personality constructs: application to state self-esteem. Structural Equation Modeling 1(1), 35-67.
Bagozzi, R. P. & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16, 74-94.
Bagozzi, R. P., Yi, Y. & Phillips, L. W. (1991). Assessing construct validity in organisational research. Administrative Science Quarterly. 36, 421-458.
Banham, R. (2003). HR Outsourcing Leads the Way', Outsourcing essentials, 1, online at: http://www.outsourcinginstitute.comlmmrldefault.asp.
Barney, J. (1991). Firm resources and sustained competitive - advantage. Journal of Management, 17, 99-120.
Barth6lemy, J. & Adsit, D. (2003). The seven deadly sins of outsourcing. The Academy of Management Executive, 17(2), 87-100.
210
Baron J. N. & Kreps, D. M. (1999). Strategic human resources:. frameworks for general managers. New York: Wiley.
Barney, J. B. & Wright, P. M. (1998). On becoming a strategic partner: The role of human resources in gaining competitive advantage. Human Resource Management, 37(1), 31-46.
Baturina, O. (2003). Outsourcing in human resource management. Personnel Management, 7, 11.
Baumgartner, H. & Homburg, C. (1996). Applications of structural equation modeling in marketing and consumer research: A review. International Journal Research Marketing. 13, 139-161.
Becker, B. E. & Gerhart, B. (1996). The impact of human resource management on organizational performance: Progress and prospects. Academy of Management Journal, 3 9(4), 779-801.
Becker, B. E. & Huselid, M. A. (1998). High performance work systems and firm performance: A synthesis of research And managerial applications. In G. R. Ferris (Ed.). Research in Personnel and Human Resource Management. 53-101, Greenwich: CT JAI Press.
Becker, B. E. & Huselid, M. A. (2006). Strategic human resources management: Where do we go from here? Journal of Management, 32(6) 898-925.
Beer, M., Spector, B., Lawrence, R. P., Mills, D. Q. & Walton, R. E. (1984). Managing Human Assets. New York: The Free Press.
Belcourt, M. (2006). Outsourcing-the benefits and risks. Human Resource Management Review, 16(2), 269-279.
Bender, D. H. (1957). Coloured stationery in direct-mail advertising. Journal of Applied Psychology, 41 (3); 161-164.
Bentler, P. M. & Bonnet, D. C. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88 (3), 588-606.
Bennett, N., Ketchen, D. J. & Schultz, E. B. (1998). An examination of factors associated with the integration of human resource management and strategic decision-making. Human Resource Management, 37(1), 3-16.
Benson, J. & Littler, C. (2002). Outsourcing and workforce reductions: An empirical study of Australian organizations. Asia Pacific Business Review, 8(3), 16 -30.
Bettis, R.A., Bradley, S. P., & Hamel, G. (1992). Outsourcing and industrial decline. Academy of Management Executive, 6(1), 7-22.
Bhatnagar, J. & Sharma, A. (2004). Strategic HR roles in India: HR-Dares to be the think tank? Management and Labour Studies, 29(3), 153-163.
Bhatnagar, J. & Sharma, A. (2005). The Indian perspective of strategic HR roles and organisational learning capability. International Journal of Human Resource Management, 16(9), I711-1739.
Bohrnstedt, G. (1983). Measurement In P Rossi, J. Wright, & A. Anderson (Eds.), A handbook of survey research. San Diego, CA: Academy Press.
Bond, S. & McCracken, M. (2005). The importance of training in operationalising HR policy. Journal ofEuropean Industrial Training, 29 (3), 246-260.
Bond, S. & Wise, S. (2003). Family leave policies and devolution to the line. Personnel Review, 32(1), 58-72.
211
Bond, S., Hyman, J., Summers, J. & Wise, S. (2002). Family friendly working? From policy to practice, New York: Joseph Rowntree Foundation.
Bontis, N., Booker, L. D., & Serenko, A. (2007). The mediating effect of organizational reputation on customer loyalty and service recommendation in the banking industry. Management Decision, 45(9), 1426-I445.
Boswell, W.R. (2006). Aligning employees with the organization's strategic objectives: Out of "Line of Sight," out of Mind. International Journal of Human Resource Management, 17 (9), 1489-1511.
Bounfour, A. (1999). Is Outsourcing of intangibles a real source of competitive advantage? International Journal ofApplied Quality Management, 2, 127-151.
Bowen, D. E., Galang, C. & Pillai, R. (2002). The role of human resource management: An exploratory study of cross-country variance. Human Resource Management, 41(1), 103-127.
Bowen, D. & Ostroff, C. (2004). Understanding HRM-firm performance linkages: The role of the strength of the FIRM system. Academy of Management Review, 29(2), 203-221.
Boxall, P. J. (1994). Placing HR strategy at the heart of business success. Personnel Management, July, 32-35.
Boxall, P., & Purcell, J. (2003). Strategy and Human Resource Management. Basingstoke: Palgrave Macmillan.
Brandl, J., Madsen, M. T. & Madsen, H. (2009). The perceived importance of HR duties to Danish line managers. Human Resource Management Journal, 19(2), 194-210.
Brenner, L. (1996). The disappearing HR department. CFO: The Magazine for Senior Financial Executives, 61-64.
Brewster, C. and Hegewisch, A. (Eds) (1994), Policy and practice in European human resource Management: The Price Waterhouse Cranfield Survey, London: Routledge.
Brewester, C. & Larsen, H. H. (1992). Human resource management in Europe: Evidence from ten countries. International Journal of Human Resource Management, 3(3), 409-434.
Brewster, C. & Larsen, H. H. (2000). Responsibility in human resource management: The role of the line, In Brewster, C. and Larsen, H. H. (Eds.) Human resource management in Northern Europe: Trends, dilemmas, and strategy, Oxford: Blackwell.
Brewster. C. & Soderstrom, M. (1994). Human resources and line management. In Brewster, C. and Hegewisch, A. (edition) Policy and Practice in European Human Resource Management. London and New York: Routledge.
Brewster, C., Larsen, H. H. & Mayrhofer, C. (1997). Integration and assignment: A paradox in human resource management. Journal of International Management, 3 (3), 409-433.
Brewster C., Mayrhofer W. & MorIey M., (2004). Human Resource Management in Europe, Evidence of Convergence? Oxford: EIsevier/Butterworth-Heinemann
Brown, D. & Purcell, J. (2007). Reward management: On the line. Compensation & Benefits Review, 28-34.
Bruvold, N. T., Comer, J. M., & Rospert, A. M. (1990). Interactive effects of major response facilitators. Decision Sciences, 21, 551-562.
212
Bryce, D. J., & Useem, M. (1998). The impact of corporate outsourcing on company value. European Management Journal, 16(6), 635-643.
Budhwar, P. S. (2000a). Evaluating levels of strategic integration and devolvement of human resource management in UK. Personnel Review, 29(2), 141-161.
Budhwar, P.S. (2000b). Strategic integration and devolvement of human resource management in the UK manufacturing sector. British Journal of Management, 11, 285-302.
Budhwar, P. S. (2001). Doing business in India. Thunderbird International Business Review, 43(4), 549-568.
Budhwar, P. S. & Boyne, G. (2004). Human resource management in the Indian public and private sectors: An empirical comparision. The International Journal of Human Resource Management, 15(2), 346-370.
Budhwar, P.S. & Sparrow, P. R. (1997). Evaluating levels of strategic integration and devolvement of human resource management in India. The International Journal of Human Resource Management, 8(4), 476-494.
Budhwar, P. & Varma, A. (2010). Guest Editors' Introduction: Emerging patterns of HRM in the new Indian economic environment. Human Resource Management, 49, (3), 345-351.
Budhwar, P., Varma, A., Singh, V., & Dhar, R. (2006). HRM systems of Indian call centers in India: An exploratory study.. International Journal of Human Resource Management, 17(5), 881-897.
Busi, M. & Melvor, R. (2008). Setting the outsourcing research agenda: The top-10 most urgent outsourcing areas. Strategic Outsourcing: An International Journal, 1(3), 185-197.
Business World (2009). The BW Rea1500. Special Issue Business World, 29(24), 54-71 Buyens, D. & De Vos, A. (2001). Perceptions of the value of the HR function. Human
Resource Management Journal, 11(3), 70-89. Byrne, B. M. (2001). Structural equation modeling with AMOS: Basic concepts,
applications, and programming. New Jersey: Lawrence Eribaum.
Caldwell, R. (2003).The changing roles of personnel managers: Old ambiguities, new uncertainties. Journal ofManagement Studies, 40(4), 983-1003.
Campbell, D. T. & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56(1), 81-105.
Camison, C. & Villar-Lopez, A. (2010). Effect of SMEs' international experience on foreign intensity and economic performance: The mediating role of internationally exploitable assets and competitive strategy. Journal of Small Business Management, 42(20), 116-151.
Cantrell, S. & Miele, S. (2007). Workforce of One: The role of the line manager: Research note of Accenture Institute for High Performance Business, 10.
Carroll, S. J. & Gillen, D. A. (1987). Are the classical management functions useful in describing managerial work? Academy of Management Review, I2, 38-5 1.
Cascon-Pereira, R., Valverde, M. & Ryan, G. (2006). Mapping out devolution: An exploration of the realities of devolution. Journal of European Industrial Training, 30(2), I29-151.
213
Cascio, W. F. (2011): Methodological issues in international HR management research. The International Journal of Human Resource Management, DOI: 10.1080 /09585192. 2011.561242
Chand, M. & Katou, A. A. (2007). The impact of HRM practices on organisational performance in the Indian hotel industry. Employee Relations, 29(6), 576-594.
Chan, L. L. M., Shaffer, M. A. & Snape, E. (2004). In search of sustained competitive advantage: The impact of organizational culture, competitive strategy and human resource management practices on firm performance. International Journal of Human Resource Management, 15(1), 17-35.
Chang, S., Witteloostuijn, A. V. & Eden, L. (2010). From the Editors: Common method variance in international business research. Journal of International Business Studies, 41, 178-184.
Chiamsiri, S., Bulusu, S. D. & Agarwal, M. (2005). Information technology offshore outsourcing in India: A human resources management perspective. Research and Practice in Human Resource Management, 13(2), 105-114.
Chiang, F. F. T., Chou, I. H. & Birtch, T. A. (2010). Examining human resource management outsourcing in Hong Kong. The International Journal of Human Resource Management, 12(15), 2762-2777.
Chung, K. H., Lubatkin, M., Rogers, R. C. & Owens, J. E. (1987). Do insiders make better CEOs than outsiders? The Executive, 1(43), 325-331.
Churchill, G. A. (1979). A paradigm for developing better measures of marketing constructs. Journal of Marketing Research, 16(3), 64-73.
Churchill, G. A. & Iacobucci, D. (2002). Marketing research: Methodological foundations. (8th Ed.), Orlando: Harcourt College Publishers.
Clark, I. (1998). Designing and sustaining an entrepreneurial role for the human function: Strategic choice or competitive conditions? Evidence from engineering process plant contracting. International Journal of Entrepreneurial Behavior & Research, 4(1), 51-70.
Coase, R. (1937). The nature of the firm. Economica, 4 (16), 386-405.
Coggburn, J. D. (2007).Outsourcing human resources: The case of the Texas health and human services commission. Review of Public Personnel Administration, 27(4), 315-335.
Cohen, Y. (1988). Statistical power analysis_ for the behavioral sciences (2°d- Edition). Hillsdale, NJ: Lawrence Erlbaum Associates.
Cohen, Y. & Pfeffer, J. (1986). Organisational hiring standards. Administrative Science Quarterly, 31, 1-24.
Collins, C. J. & Clark, K. D. (2003). Strategic human resource practices, top management team social networks, and firm performance: The role of human resource practices in creating organizational competitive advantage. The Academy of Management Journal, 46(6), 740-751.
Colton, D. & Covert, R. W. (2007). Designing and Constructing Instruments for Social Research and Evaluation. (First Edition), United States of America: John Wiley & Sons.
Conway, E. & Monks, K. (2010). The devolution of HRM to middle managers in the Irish health service. Personal Review, 39 (3), 361-374.
Cook, M. (1999). Outsourcing human resources functions. Strategies for providing enhanced HR services at lower cost. New York: AMACOM.
214
Cooke, B. (2004). HR/Benefits outsourcing: Updating the conventional thinking. Employee Benefit Plan Review, 58, 18-21.
Cook, D. S. & Ferris, G. R. (1986). Strategic human resource management and firm effectiveness in industries experiencing decline. Human Resource Management, 25(3), 441-458.
Cooke, F. L., Shen, J., & McBride, A. (2005). Outsourcing HR as a competitive strategy? A literature review and an assessment of implications. Human Resource Management, 44(4), 413-432.
Cooper, D. R., & Schindler, P. S. (2003). Business Research Methods. (Eighth Edition), New Delhi: Tata McGraw-Hill.
Cooper, D. R., & Schindler, P. S. (2006). Business Research Methods. (Ninth Edition), New Delhi: Tata McGraw-Hill.
Cote, J., Netemeyer, R., & Bentler, P. (2001). Structural equation modelling-improving model fit by correlating errors. Journal of Consumer Psychology. 10(1, 2), 87-88.
Crowley, S. L. & Fan, X. (1997). Structural equation .modeling: Basic concepts and applications in personality assessment research. Journal of Personality Assessment, 68 (3), 508-31.
Crittenden, W. F., Crittenden, V. L. & Hawes, J. M. (1985). Examining the effects of questionnaire color and print font on mail survey response rates. Akron Business and Economic Review, 16; 51-56.
Cronbach, L.J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16,297-334.
Csoko, L. S. (1995). Rethinking human resources: A research report. The Conference Board, Report No: 1124-95-RR.
Cunningham, 1. & Hyman, I. (1995).Transforming HRM vision into reality: The role of line managers and supervisors in implementing change. Employee Relations, 17 (8), 5-20.
Cunningham, I. & Hyman, J. (1999). Devolving human resource responsibilities to the line: Beginning of the end or a new beginning for personnel? Personnel Review, 28(l/2),9-27.
Cunningham, I., Hyman, J. & Baldry, C. (1996). Empowerment: The power to do what? Industrial Relations Journal, 27(2), 143-54.
Currie, G. & Procter, S. (2001). Exploring the relationship between HR and middle managers. Human Resource Management Journal, 11(1), 53-69.
Currie, G. & Procter, S. (2005). The antecedents of middle managers' strategic contribution: the case of a professional bureaucracy. Journal of Management Studies, 42(7), 1325-1356.
Dany, F., Guedri, Z., & Hatt, F. (2008). New insights into the link between HRM integration and organizational performance: The moderating role of influence distribution between HRM specialists and line managers. The International Journal ofHuman Resource Management, 19 (11), 2095- 2112.
Dale, B. and Cooper, C. (1992). Total Quality and Human Resource Management: An Executive Guide, Oxford: Blackwell.
Dalecki, M. G., Whitehead, J. C. & Blomquist, G. C. (1993). Sample non-response bias and aggregate benefits in contingent valuation: An examination of early, late and non-respondents. Journal of Environmental Management, 38, 133-143.
215
Dean, M. A., Shook, C. L. & Payne, G. T. (2007). The past, present and future of entrepreneurship research: Data analytic trends and training. Entrepreneurship Theory and Practice, 31(4), 601-618.
de Kok, J. M. P., & Uhlaner, L.M. (200I). Organization context and human resource management in the small firm. Small Business Economics, 17, 273-291.
Delmotte, J. & Sels, L. (2008). HR outsourcing: Threat or opportunity? Personnel Review, 37 (5), 543-563.
Dell, D. J. (2004). HR outsourcing: Benefits, challenges, and trends. Research Report R-1347-04-RR). New York: The Conference Board.
Delgado-Ballester, E., Munuera-Aleman, J. L., Yague-Guillen, M. J., (2003). Development and validation of a brand trust scale. International Journal of Market Research, 45 (1), 35-53.
Diamantopoulos, A. & Siguaw, J. (2000). Introducing LISREL. London: Sage.
Dick, P. & Hyde, R. (2006). Line manager involvement in work-life balance and career development: Can't manage, won't manage? British Journal of Guidance & Counselling, 34(3), 345-364.
Dunn, C. & Wilkinson, A. (2002). Wish you were here: Managing absence. Personnel Review, 31(2), 228-46.
Duncan, W. J. (1979). Mail questionnaires in survey research: A review of response inducement techniques. Journal ofManagement, 5, 39-55.
Dopson, S. & Stewart, R. (1990). What is happening to middle management? British Journal of Management, 1(3), 3-16.
Doty, D. H. & Glick, W. H. (1998). Common methods bias: Does common methods variance really bias results? Organizational Research Methods, 1(4), 374-406.
Dowling, P. J., Schuler, R. S. and Welch, D. E. (1994). International Dimensions of HRM. New York: Wadsworth.
Dyer, L. & Reeves, T. (1995). Human resource strategies and firm performance: What do we know and where do we need to go? The International Journal of Human Resource Management, 6(3), 656-670.
Dziuban, C. D. & Shirkey, E. C. (1974).When is a correlation matrix appropriate for factor analysis? Psychological Bulletin; 81(3), 58-61.
Edelman, L. F., Brush, C. G., Manolova, T. S. and Greene, P. G. (2010). Start-up motivations and growth intentions of minority nascent entrepreneurs. Journal of Small Business Management. 48(2), 174-196.
Edwards, J. R. & Lambert, L. S. (2007). Methods for integrating moderation and mediation: A general analytical framework using moderated path analysis. Psychological Method, 12(1), 1-22.
Embleton, P. R. & Wright, P. C. (1998). A practical guide to successful outsourcing. Empowerment in Organizations, 6(3), 94-106.
Emerson. R. M. (1987). Toward a theory of value in social exchange. In K. S. Cook (Ed.), Social Exchange Theory (pp. 11-46). Newbury Park. CA: Sage.
En-shun, T. (2007). Management of risks posed by human resource outsourcing. Chinese Business Review, 6(3) 55-58.
Esen, E. (2004). SHRM Human Resource Outsourcing Survey Report, Alexandria, VA: Society for Human Resources, July.
216
Fabrigar, L. R., Wegener, D. T., MacCallum, R. C., & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 3, 272-299.
Fan, X., Thompson, B., & Wang, L. (1999). Effects of sample size, estimation methods, and model specification on structural equation modeling fit indexes. Structural Equation Modeling, 6 (1), 56-83.
Fenton-O'Creevy, M. (2001). Employee involvement and the middle management: saboteur or scapegoat? Human Resource Management Journal, 11(1), 24-40.
Ferris, G. R., Hochwarter, W. A., Buckley, M. R., HarelI-Cook, G. & Frink, D. D. (1999). Human resources management: Some new directions. Journal of Management, 25(3), 385-415.
Fernandez, S., Rainey, H. G. & Lowman, C. E. (2006). Privatization and its implications for human resources management. In N. M. Riccucci (Ed.), Public personnel management: Current concerns, future challenges (4th ed., pp. 204-224). New York: Longman. •
Finegold, D. & Frenkel, S. (2006). Managing people where people really matter: the management of human resources in biotech companies. International Journal of Human Resource Management, 17(1), 1-24.
Finkelstein, S. (1992). Power in top management teams: Dimensions, measurement, and validation. Academy of Management Journal, 35(3), 505-53 8.
Fisher, C. D. & Dowling, P. (1999). Support for an HR approach in Australia: the perspective of senior HR managers. Asia Pac c Journal of Human Resources, 37(1), 1-19.
Floyd, S. & WooIdridge, B. (1992). Middle management involvement in strategy and its association with strategic type: a research note. Strategic Management Journal, 13,153-167.
Floyd, S. & Wooldridge, B. (1994). Dinosaurs or dynamos? Recognising middle management's strategic role. Academy ofManagement Executive, 8(4), 47-57.
Floyd, S. & Wooldridge, B. (1997). Middle management's strategic influence and organisational performance. Journal ofManagement Studies, 34(3), 465-485.
Foa. E. B., & Foa, U. F. (1980). Resource theory: Interpersonal behavior as exchange. In K.J. Gergen, M. S. Greenberg & R. H. Willis (Eds.), Social exchange: Advances in theory and research (pp. 77-94). New York: Plenum Press.
Fombrun, C. J., Tichy, N. M. & Devanna, M. A. (1984). Strategic human resource management. New York: John Wiley.
Fornell, C. & Bookstein, F. L. (1982). Two structural equation models: LISREL and PLS applied to consumer exit-voice theory. Journal of Marketing Research, 19(4), 440-453.
Fornell, C. & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18, 39-50.
Fox, J. R., Crask, M. R. & Kim, J. (1988). Mail Survey Response Rate: A Meta-Analysis of Selected Techniques for Inducing Response. Public Opinion Quarterly, 52(4); 467-491.
Francis, H. & Keegan, A. (2006). The changing face of HRM: In search of balance, Human Resource Management Journal, 16(3), 231-249.
217
Frazier, P. A., Tix, A. P. & Barron, K. E. (2004). Testing moderator and mediator effects in counseling psychology. Journal of Counseling Psychology, 51(I), 115-134.
Fried, Y., Shirom, A., Gilboa, S. & Cooper, C. L. (2008). The Mediating Effects of Job Satisfaction and Propensity to Leave on Role Stress-Job Performance Relationships: Combining Meta-Analysis and Structural Equation Modeling. International Journal of Stress Management, 15(4), 305-328.
Gautam, D. K. & Davis, A. J. (2007). Integration and devolvement of human resource practices in Nepal. Employee Relation, 29 (6), 711-726.
Galanaki, E. & Papalexandris, N. (2005). Outsourcing of human resource management services in Greece. International Journal of Manpower, 26 (4), 382-396.
Galanaki, E. & Papalexandris, N. (2007). Internationalization as a determining factor of HRM outsourcing. International Journal of Human Resource Management, 18(8), 1557-1567.
Galanaki, E., Bourantas, D., & Papalexandris, N., (2008). A decision model for outsourcing training functions: distinguishing between generic and firm job-specific training content. The International Journal of Human Resource Management, 19(12), 2332-2351.
Gamey, T. W. & Klaas, B.S. (2002). Outsourcing the HRD function: results from the field. Human Resource Planning, 25 (1), 16-22.
Gainey, T. W., & Klaas, B. S. (2003). The Outsourcing of training and development: Factors impacting client satisfaction. Journal ofManagement, 29(2), 207-229.
'Gainey, T. W., Klaas, B. S. & Moore, D. (2002).Outsourciug the Training Function: Results from the field. Human Resource Planning, 25, 16-22.
Garver & Mentzer, J. T. (1999). Logistics Research Methods: Employing Structural Equation Modeling to test for Construct Validity. Journal of Business Logistics, 20(1), 33-57.
Gay, C. L., & Essinger, J. (2000). Inside outsourcing: An insider's guide to strategic sourcing. London: Nicholas Brealey Publishing.
Gennard, J. & Kelly, J. (1997). The unimportance of labels: The diffusion of the personnel/HRM'function. Industrial Relations Journal, 28 (1), 27-42.
Gerbing, D. W. & Anderson, J. C. (1988). An updated paradigm for scale development incorporating unidimensionality and its assessment. Journal of Marketing Research, 25(May), 186-192.
Gibb, S. (2003). Line manager involvement in learning and development Small beer or big deal? Employee Relations, 25(3), 281-293.
Gibbons, P. T., & O'Connor, T. (2005). Influences on strategic planning processes among Irish SMEs. Journal ofSmall Business Management. 43(2), 170-186.
Gilley, K. M., Greer, C. R. & Rasheed, A. A. (2004). Human resource outsourcing and organizational performance in manufacturing firms. Journal of Business Research, 57, 232-240.
Gilley K. M., & Rasheed, A. A. (2000). Making more by doing less: an analysis of outsourcing and its effects on firm performance. Journal of Management, 26(4), 763-790.
Golden, K.A. & Ramanujam, V. (1985). Between a dream and a nightmare: on the integration of the I-IRM and strategic business planning process. Human Resource Management, 24 (4), 429-452.
218
Gopalakrishnan, R. (2008).1 wonder.. .1 wonder..., Business World, 5 May, p.38.
Gratton, L., Hope-Halley, V., Stiles, P. & Truss, C. (1999). Strategic Human resource management: Corporate rhetoric and human reality. Oxford: Oxford University Press. ,
Gratton, L. & Truss, C. (2003). The three-dimensional people strategy: Putting human resource policies into action. Academy of Management Executive, 17 (3), 74-86.
Green, K. W., Cindy W. H, Whitten, D. & Medlin, B. (2006). The impact of strategic human resource management on firm performance and HR professionals' work attitude and work performance. International Journal of Human Resource Management, 17(4), 559-579.
Greenberg. M. S. (1980). A theory of indebtedness. In K. J. Gergen, M. S. Greenberg, & R. H. Willis (Eds.), Social exchange: Advances in theory and research (pp. 3-26). New York: Plenum Press.
Greer, C. R., Youngblood, S. A., & Gray, D. A. (1999). Human Resource Management Outsourcing: The Make or Buy Decision. The Academy of Management Executive, 13(3), .85-96.
Grossman, R.J. (2008). HR's rising star in India. Available at: http://www.shrm.orWJindia/ 07 risingstar.asp, 21 May 2008.
Guest, D. (1987). Human resource management and industrial relations. Journal of Management Studies, 24 (5), 503-521.
Guest, D. E. (1989). Human resource management: Its implications for industrial relations and trade unions, In Storey, J. (Ed.), New Perspectives on Human Resource Management (pp. 41-55). London: Routledge.
Guest, D. E. (1997). Human resource management and performance: A review and research agenda. International Journal of Human Resource Management, 8(3), 263-276.
Guest, D. & Conway, N. (2011). The impact of HR practices, HR effectiveness and a `strong HR system' on organisational outcomes: A stakeholder perspective. The International Journal of Human Resource Management, 22(08), 1686-1702.
Gunnigle, P. (1998). Human resource management and the personnel function. In Roche, W. K., Monks, K. and Walsh, J. (Eds), Human Resource Management Strategies: Policy and Practice in Ireland, Oak Tree Press, Dublin.
Hair, J. F., Black, W.C., Babin, B.J., Anderson, R.E. & Tatham, R. L. (2008). Multivariate Data Analysis. (Sixth Edition), India: Pearson Education.
Haire, M., Ghiselli, E. E. and Porter, L. W. (1966). Managerial Thinking. New York: Wiley.
Hall, L. & Torrington, D. (1998). Letting go or holding on? The devolution of operational personnel activities. Human Resource Management Journal, 8(1), 41-55.
Hales, C. (2005). Rooted in supervision, branching into management: Continuity and change in the role of first-Iine manager. Journal of Management Studies, 42(3), 471-506.
Hambrick, D. C. & Mason, P. (1984). The organization as a reflection of its top managers. Academy of Management Review, 9, 193-206.
Harrison, R. (2005). Learning and Development. (Fourth Edition), London: Chartered Institute of Personnel Development.
219
Harkins, P., Brown, S., & Sullivan, R. (1995). Shining new light on a growing trend. HR Magazine, 40(12), 75-79.
Harman, H. H. (1967). Modern factor analysis. Chicago, IL: University of Chicago Press. Harmon. H. A., Brown. G., Widing, R.E. Il & Hammond. K. L. (2002). Exploring the
sales manager's feedback to a failed sales effort. Journal of Business and Industrial Marketing, 17(1), 43-55.
Harper, S. J. (1993). The challenges facing CEOs: Past, present, and future. The Executive, 6(3),7-2.
Harris, L., Doughty, D. & Kirk, S. (2002). The devolution of HR responsibilities-perspectives from the UK's public sector. Journal of European Industrial Training 2615, 218-229.
Hart, O. (1988). Incomplete contracts and the theory of the firm. Journal of Latin, Economics and Organization, 4, 119-139.
Hart, P. M. (1994). Teacher Quality of Work Life: Integrating Work Experiences, Psychological Distress and Morale. Journal of Occupational and Organizational Psychology, 67, 109-132.
Harvey, L. (1987). Factors affecting response rates to mailed questionnaires: A comprehensive literature review. Journal of the Market Research Society, 29, 341-353.
Hayduk, L., Cummings, G.G., Boadu, K., Pazderka-Robinson, H., & Boulianne, S. (2007). Testing! Testing! One, Two Three-Testing the theory in structural equation models. Personality and Individual Differences, 42 (2), 841-850.
Heberlein, T. A., & Baumgartner, R. (1978). Factors affecting response rates to mailed questionnaires: A quantative analysis of the published literature. American Sociological Review, 43, 447-462.
Hendry, J. (1995). Culture, Community and Networks: The Hidden Cost of Outsourcing. European Management Journal, 13(2), 193-200.
Heneman, R. L., Tansky, J. W. & Camp, S. M. (2000). Human resource management practices in small and medium-sized enterprises: unanswered questions and future research perspectives. Entrepreneurship Theory and Practice, 25(1), 11-26.
Henson, R. K. & Roberts, J. K. (2006). Use of Exploratory Factor Analysis in Published Research: Common Errors and Some Comment on Improved Practice. Educational and Psychological Measurement. 66(3), 393-416.
Hennig-Thurau, T., Gwinner, K. P. & Gremler, D. D. (2002). Understanding relationship marketing outcomes: An integration of relational benefits and relationship quality. Journal of Service Research, 4(3), 2002.
Heraty, N. & Morley, M. (1995). Line managers and human resource development. Journal of European Industrial Training, 19 (10), 31-37.
Hirschman, C. (2000).For PEOs, business is still booming. HR Magazine, 45, 42-48
Hope Halley, V., Famdale, E. & Truss, C. (2005). The HR department's role in organisational performance. Human Resource Management Journal, 15(3), 49-66.
Hope-Hailey, V., Grafton, L., McGovern, P., Stiles, P. & Truss, C. (1997). A chameleon function? HRM in the 1990s. Human Resource Management Journal, 7(3), 5-18.
Hoogendoorn, J. & Brewster, C. (1992). Human resource aspects: Decentralization and devolution. Personnel Review, 21(1), 4-11.
220
Hooper, D., Coughlan, J. & Mullen, M. R. (2008). Structural Equation Modelling: Guidelines for Determining Model Fit. Electronic Journal of Business Research Methods, 6(1), 53-60.
Hu, L. & Bentler. P. M. (1999). Cut off criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1-55.
Huselid, M. A., & Becker, B. E. (2000). Comment on `Measurement error in research on human resource and firm performance: how much error is there and how does it influence effect size estimates?' by Gerhart, B., Wright, P.M., McMahan, G.C., and Snell, S.A. Personnel Psychology, 53 (4), 835-854.
HuseIid, M. A. (1995). The impact of human resource management practices on turnover, productivity and corporate financial performance. Academy of Management Journal, 38(3), 635-672.
Huselid, M. A., Jackson, S. E. & Schuler, R. S. (1997). Technical and Strategic Human Resource Management Effectiveness as Determinants of Firm Performance. Academy of Management Journal. 40(l), 171-188.
Hutchinson, S. (1995). Variations on the partnership model. People Management, 2
Hutchinson, S. & PurceIl, J. (2003). Bringing Policies to Life: The Vital Role of Front Line Management in People Management, London: CIPD.
Hutchinson, S. & Purcell, J. (2007). Front-line managers as agents in the HRM performance causal chain: theory, analysis and evidence. Human Resource Management Journal, 17 (1), 3-20.
Hutchinson, S. & Purcell, J. (2010). Managing ward managers for roles in HRM in the NHS: overworked and under-resourced. Human Resource Management Journal, 20 (4), 357-374.
Hutchinson, S. & Wood, S. (1995). The UK experience. Personnel and the line: Developing the new relationship. London: CIPD.
Hsu, Yu-Ru & Leat, M. (2000). A study of HRM and recruitment and selection policies and practices in Taiwan. The International Journal of Human Resource Management, 11(2), 413 -435.
Huy, Q. N. (2001). In praise of middle managers. Harvard Business Review, 80(8), 72-79.
Industrial Relations Services (1994). Centre cannot hold: devolving personnel duties. IRS Employment Trends, 566, 6-11.
IRS Employment Trends (1995). Changes in personnel. 598, December, 4-9.
Israel, G. D. (2009, April). Sampling Issues: Non-response. Working Paper PEOD9, University of Florida. Downloaded from http://edis.ifas.ufl.edu/pdOO8 on August 5, 2010.
Jack, S., Hyman, J., & Osborne, F. (2006). Small entrepreneurial ventures culture, change and the impact on HRM: A critical review. Human Resource Management Review, 16(4), 456-466.
Jackson, S. E. & Schuler, R. S. (1999). Understanding human resource management in the context of organizations and their environments, in Schuler, R.S. and Jackson, S.E. (Eds), Strategic Human Resource Management, Blackwell, Oxford.
Jackson, S. E. & Schuler, R. S. (2000). Managing human resources: A partnership perspective, Cincinnati, OH: South-Western College.
221
Jackson, D. L., Gillaspy, J. A., Jr., & Pure-Stephenson, R. (2009). Reporting practices in confirmatory factor analysis: An overview and some recommendations. Psychological Methods, 14, 6-23.
Jain, H.C. (1991). Is there a Coherent Human Resource Management System in India? International Journal of Manpower, 12, 10-17.
Jamrog, J., Groe, G. M., & Pyle, W. (1997). The HR revolution heats up. Paper presented at the 1997 meeting of the Human Resource Planning Society, Ithaca, NY.
Jennings, D. R. (1996). Outsourcing opportunities for financial services. Long Range Planning, 29(3), 393-404.
Jennings, D. (2002). Strategic sourcing: Benefits, problems and a contextual model. Management Decision, 40(1), 26-34.
Jobber, D. (1986). Improving response rates in industrial mail surveys. Industrial Marketing Management, 15, 183-195.
Jobber, D. & Sanderson, S.M. (1983). The effects of a prior letter and coloured questionnaires on mail survey response rates. Journal of the Market Research Society, 25(4), 339-349.
Jonas, H. S., 111, Fry, R. E. & Srivastva, S. (1990). The office of the CEO: Understanding the executive experience. The Executive, 4(3), 36-48.
Jones, O. (1996). Strategic HRM: The implications for pharmaceutical R&D. Technovation, 16(1), 21-32.
Joreskog, K. & Sorbom, D. (1993). LISREL 8: Structural equation modeling with the SIMPLIS command language. Chicago: Scientific Software International.
Joreskog, K. & Svrbom, D. (1996). LISREL 8: User's reference guide [Computer software manual]. Chicago: Scientific Software International.
Joreskog, K. & Sorbom, D. (2002). LISREL 8.53: User's Reference Guide. Chicago: Scientific Software International Inc (SSI).
Judge, T. A., & Hulin, C.L. (1993). Job satisfaction as a reflection of disposition: A multiple source causal analysis. Organizational Behavior and Human Decision Processes, 56, 388-421.
Kahn, J. H. (2006). Factor analysis in counseling psychology research, training, and practice: Principles, advances, and applications. The Counseling Psychologist. 34(5), 684-718.
Kakabadse, A. & Kakabadse, N. (2002).Trends in Outsourcing. Contrasting USA and Europe. European Management Journal, 20(2), 189-198.
Kane, B., Crawford, J. & Grant, D. (1999). Barriers to effective HRM. International Journal of Manpower, 20 (8), 494-515.
Kanter, R. (1982). The middle manager as innovator. Harvard Business Review, July-August, 95-105.
Kanuk, L., & Berenson, C. (1975). Mail surveys and response rates: A literature review. Journal of Marketing Research. 12, 440-453.
Kaplan, R, M., & Sacuzzo, D. P. (1993). Psychological testing: Principles, applications and issues. Pacific Grove CA: Brooks Cole.
Katou, A. A. (2008). Measuring the impact of HRM on organisational performance. . Journal of Industrial Engineering and Management, 1(2), 119-142.
222
Keen, L. & Vickerstaff, S. A. (1997). We're all human resource managers now: Local government middle managers. Public Money and Management, 41-46.
Kelloway, E. K. (1998). Using LISREL for structural equation modeling: A researcher's guide. New York: Sage Publications.
Kellerman, S. E. & Herold, J. (2001). Physician response to surveys: A review of the literature. American Journal of Preventive Medicine, 20, 61-67.
Kelly, J. & Gennard, J. (1996). The role of personnel directors on the board of directors. Personnel Review, 25(1), 7-24.
Khatri, N. (2000) .Managing human resource for competitive advantage: A study of companies in Singapore. The International Journal of Human Resource Management, 11(2), 336-365.
Khatri, N. & Budhwar, P. S. (2002). A study of strategic HR issues in an Asian context. Personnel Review, 31(2), 166-188.
Khilji, S. E. (2002). Modes of convergence and divergence: An integrative view of multinationals in Pakistan. The International Journal of Human Resource Management, 13(2), 232-253.
Kinnie, N. (1990). The decentralisation of industrial relations? Recent research considered. Personnel Review, 19 (3), 28-34.
Kirkpatrick, S. A. & Locke, E. A. (1991). Leadership: Do traits matter? The Executive, 5(2), 48-60.
Kitay, J. & Wrght, C. (1999). An unexplored relationship: Australian management consulting and the management of human resources. Asia Pacc Journal of Human Resources, 37(3), 1-17.
Klaas, B.S. (2003). Professional employer organizations and their role in small and medium enterprises: The impact of HR outsourcing. Entrepreneurship Theory and Practice, 28 (1), 43-61.
Klaas, B. S., McClendon, J., & Gainey, T. W. (1999). HR Outsourcing and its impact: The role of tr nsaction costs. Personnel Psychology, 52 (1), 113-136.
Klaas, B. S., McClendon, J., & Gainey, T. W. (2000). Managing HR in the small and medium size enterprise: The impact of professional employer organisations. Entrepreneurship Theory & Practice, 25, 107-124.
Klaas, B. S., McClendon, J. A., & Gainey, T. W. (2001). Outsourcing HR: The impact of organizational characteristics. Human Resource Management, 40(2), 125-138.
Klassen, R. D. & Jacobs, J. (2001). Experimental comparision of web, electronic and mail survey technologies in operations management. Journal of Operations Management, 19(6), 7I3-728.
Klein, P. G., (2004-07). The make-or-buy decision: Lessons from empirical Studies. CORI Working Paper.
Kline, R.B. (2005). Principles and practice of structural equation modeling, (2°d, Edition), New York: The Guilford Press.
Klein, K. J., Buhl Conn, A., Smith, B. D., & Sorra, J. P. (2001). Is everyone in agreement? An exploration of within-group agreement in employee perceptions of the work environment. Journal ofApplied Psychology, 86(I), 3-17.
Knight, D., Pearce, C. L., Smith, K. G., Olian, J. D., Sims, H. P., Smith, K. A. & Flood, P. (1999). Top management team diversity, group process, and strategic consensus. Strategic Management Journal. 20, 445-465.
223
Koch, J., with Dell, D. J., & Johnson, L. K. (2004). HR outsourcing in government organizations: Emerging trends, early lessons (Research Report E-0007-04-RR). New York: The Conference Board.
Kodwani, A. D. (2007). Human resource outsourcing: Issues and challenges. The Journal of Nepalese Business Studies, IV (1), 3 8-46.
Kosnik, T., Wong-Ming, Ji, D. J., & Hoover, K. (2006). Outsourcing vs insourcing in the human resource supply chain: A comparision of five generic models. Personnel Review, 35 (6), 671-683.
Kramar, R. & Lake, N. (1998). The Price Waterhouse-Cranfield Project on International Strategic Human Resource Management, Macquarie University, Sydney.
Krishna, A. & Monappa, A. (1994). Economic restructuring and human resource management. Indian Journal of Industrial Relations. 29, 490-501.
Kulik, T.C. & Bainbridge, T. J.H. (2006). HR and the line: The distribution of HR activities in Australian organisations. Asia Pacific Journal of Human Resources 44(2), 240-256.
Kydd, C.T. & Oppenheim, L. (1990). Using human resource management to enhance competitiveness: Lessons from four excellent companies. Human Resource Management, 29 (2), 145-66.
Laabs, J. K. (1993). Why HR is turning to outsourcing. Personal Journal, 72(9), 99-101.
Laabs, J. J. (1998). The dark side of outsourcing. Workforce, 77, 42-48.
Lacity, M.C., & Hirschheim, R.A. (1993). Information systems outsourcing: Myths, metaphors and realities, New York: Wiley Series in Information Systems.
Lado, A.A., & Wilson, M.C. (1994). Human resource systems and sustained competitive advantage: A competency-based perspective. Academy of Management Review, 19(4), 699-727.
Lahaut, V. M. H. C. J.., Jansen; H. A. M., Mheen, D. V. D., Garretsen, H. F. L., Verdurmen, J.E. E. & Dijk, A. V. (2003). Estimating non-response bias in a survey on alcohol consumption: Comparison of response waves. Alcohol & Alcoholism, 38(2), 128-134.
Lambert, D. M. & Hanington, T. C. (1990). Measuring nonresponse bias in customer mail surveys. Journal of Business Logistics, 1(2), 5-25,
Larsen, H. H. & Brewster, C. (2003). Line management responsibility for HRM: What is happening in Europe? Employee Relations, 25(3), 228-244.
Lawler, J. J., Jain, H., Venkata Ratnam, C. S. & Atmiyanandana, V. (1995). Human resource management in developing economies; A Comparision of India and Thailand. International Journal of Human Resource Management, 6(2), 319-346.
Lawler, E. E. III & S. A. Mohrman. (2000). Beyond the visions: What makes HR Effective? Human Resource Planning, 23(4) 10-20.
Lawler, E.E. III & Mohrman, S.A. (2003), Creating a Strategic Human Resources Organization, Stanford University Press, Palo Alto, CA.
Lawler, E. E., III, Ulrich, D., Fitz-enz, J., & Madden, J. C. V. (2004). Human resources business process outsourcing: Transforming how HR gets its work done. San Francisco: Jossey-Bass.
224
Lawther, W. C. (2003). Privatizing personnel: Outsourcing public sector functions. In S. W. Hays & R. C. Kearney (Eds.), Public personnel administration: Problems and prospects (4th ed., pp.196-208). Upper Saddle River, NJ: Prentice Hall.
Legge, K. (1978). Power, innovation and problem-solving in personnel management. London: McGraw-Hill.
Legge, K. (1989). Human Resource Management: A Critical Analysis. In Storey, J. (Edition) New Perspectives on Human Resource Management. London: Routledge.
Legge, K. (1995). Human resource management: Rhetorics and realities, Chippenham: Macmillan Business.
Lemmergaard, J. (2009). From administrative expert to strategic partner. Employee Relations, 31(2), 182-196
Lengnick-Hall, C. A. & Lengnick-Hall, M. L. (1988). Strategic human resource management: A review of the literature and a proposed typology. Academy of Management Review, 13, 454-470.
Lever, S. (1997). An analysis of managerial motivations behind outsourcing practices in human resources. Human Resource Planning, 20, 37-47.
Lepak, D. P., Bartol, K. M., & Erhardt, N. L. (2005). A contingency framework for the delivery of HR practices. Human Resource Management Review, 15, 139-159.
Lepak, D. P., & Snell, S. A. (1998). Virtual HR: Strategic human resource management in the 21S' century. Human Resource Management Review, 8(3), 215-34.
Lepak, D., & Snell, S. (1999a). The strategic management of human capital: Determinants and implications of different relationships. Academy of Management Review, 24(1), 1-18.
Lepak, D. P., & Snell, S. A. (1999b). The human resource architecture: Toward a theory of human Capital allocation and development. Academy of Management Review, 24(1), 31-49.
Lever, Scott. (1997). An analysis of managerial motivations behind outsourcing practices in human resources. Human Resource Planning, 20, 37-47.
Likert, R. (1961). New Patterns of Management. New York: McGraw-Hill.
Linsky, A. S. (1975). Stimulating responses to mailed questionnaires: A review. Public Opinion Quarterly, 39, 92-101.
Lin, I. F. & Schaeffer, N. C. (1995). Using survey participants to estimate the impact of nonparticipation. Public Opinion Quarterly 59, 236-258.
Lindquist, J. D., Vida, I., Plank, R. E. & Fairhurst, A. (2001). The modified CETSCALE: Validity Tests in the Czech Republic, Hungary, and Poland. International Business Reviewl0, 505-516.
Littler, C. (1982). The development of the labour process in capitalist societies. London: Heinemann.
Liu, C. J. & Treagust, D. F. (2005). An Instrument for Assessing Students' Mental State and the Learning Environment in Science Education. International Journal of Science and Mathematics Education, 3, 625-637.
LoehIin, J. C. (2004). Latent Variable Models: An Introduction to Factor, Path and Structural Equation Analysis. (Fourth Edition), Mahwah, New Jersey: Lawrence Erlbaum Associates Publishers.
225
Long, J. S. (1983). Confirmatory factor analysis. A sage university paper series on quantitative applications in the social science, 07-033. Beverly Hills, CA.
Lopez, S. P., Peon, J. M. M. & Ordas C. J. V. (2005). Human Resource Practices, Organizational Learning and Business Performance. Human Resource Development International, 8(2), 147-164.
Lowe, J. (1992). Locating the line: The front line supervisor and human resource management' in Reassessing Human Resource Management. P. Blyton and P. Turnbull (edition).London: Sage.
Luna-Arocas, R., & Camps, J. (2008). A model of high performance work practices and turnover intentions. Personnel Review, 37, 26-46.
Macky, K. & Boxall, P. (2007). The relationship between "High Performance Work Practices" and employee attitudes: An investigation of additive and interaction effects. International Journal of Human Resource Management, 18(4), 537-567.
Macneil, C. (2001). The supervisor as a facilitator of informal learning in work teams. Journal of Workplace Learning, 13(6), 246-253.
MacNeil, C.M. (2003). Line managers: Facilitators of knowledge sharing in teams. Employee Relations, 25(3), 294-307.
Mahoney, C. & Brewster, C. (2002). Outsourcing the HR function in Europe. Journal of Professional HRM, 27, 23-8.
Marchington, M. (1999). "Professional qualification scheme: core personnel and development exam papers and examiners' reports May 1999", paper given to the IPD Professional Standards Conference, University of Warwick, July, Institute of Personnel and Line manager Development, I-12.
Marchington, M. (2001). Employee involvement at work. in Storey, J. (Ed.), Human Resource Management: A Critical Text, Thomson, London, 232-52.
Mayne, L. & Brewster, C. (May, 1995). Human resource management: The role of the line manager. Proceedings of the Conference on European Competitiveness: The HRM Dimension, University of Limerick.
Mayne, L., Tregaskis, 0. & Brewster, C. (1996). A comparative analysis of the link between flexibility and I RM strategy. Employee Relations, 18 (3), 5-24.
Mayrhofer, W., Muller-Caman, M., Ledolter, J., Strunk, G., & Erten, C. (2004). Devolving responsibilities for human resources to line management? An empirical study about convergence in Europe. Journal for East European Management Studies, 9(2), 1-23-146.
Maxwell, G.A. & Watson, S. (2006). Perspectives on line managers in human resource management: Hilton International's UK hotels. The International Journal . of Human Resource Management, 17(6), 1152-1170
Maxwell, G.A., Watson, S. & Quail, S. (2004). Quality service in the international hotel sector: A catalyst for strategic human resource development? Journal of European Industrial Training, 28, 159-183.
Maurer, R., & Mobley, N. (1998). Outsourcing: Is it the HR department of the future? HR Focus, 9-10.
Marinaccio, L. (1994). Outsourcing: A strategic tool for managing human resources. Employee Benefits Journal, 19, 39-42.
MacCallum, R.C., Browne, M.W., Sugawara, H.M. (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological Methods. 1(2), I30-149.
226
Malhotra, N. K (2007). Marketing Research: An Applied Orientation. (Fifth Edition), New Delhi: Pearson Education.
Malhotra, N. K & Dash, S. (201 I). Marketing Research: An Applied Orientation. (Sixth Edition), New Delhi: Pearson Education.
Malhotra, N.K., Kim, S. S., & Patil, A. (2006). Common method variance in IS research: A comparison of alternative approaches and a reanalysis of past research. Management Science, 52, I865-1883.
Marginson, P., Edwards, P., Martin, R., Purcell, J. & Sisson, K. (1988). Beyond the workplace: Managing industrial relations in the multi-establishment enterprise. Oxford: BIackwell.
Marlow, S. (2006). Human resource management in smaller firms: A contradiction in terms? Human Resource Management Review, I6(4), 467-477.
Martell, K. & Carroll, S. J. (1995). How strategic is HRM? Human Resource Management, 34,253-267.
Matteson, M. T. (1974). Type of transmittal letter and questionnaire colour as two variables influencing response rates in a mail survey. Journal of Applied Psychology, 59 (4); 535-536.
Mayrhofer, W. & Brewster, C. (2005). European human resource management: Researching Developments over Time. Management Revue, 16(1), 36-62.
Mayrhofer, W., Muller-Caman, M., Ledolter, J., Strunk, G., & Erten, C. (2004). Devolving responsibilities for human resources to line management? An empirical study about convergence in Europe. Journal for East European Management Studies, 9(2), 123-146.
Mayson, S., & Barrett, R. (2006). The "Science" and "Practice" of FIRM in small firms. Human Resource Management Review, 16(4), 447-455.
McCarthy, A., Darcy, C., Grady, G. (2010). Work-life balance policy and practice: Understanding line manager attitudes and behaviors. Human Resource Management Review, 20, 158-167.
McConville, T. (2006). Devolved HRM responsibilities, middle-managers and role dissonance. Personnel Review, 35(6), 637-653.
McConville, T. & Holden, L. (1999). The filling in the sandwich: HRM and middle managers in the health sector. Personnel Review, 28 (516), 406-24.
McCracken, M. & Wallace, M. (2000). Exploring strategic maturity in HRD - rhetoric, aspiration or reality? Journal ofEuropean Industrial Training, 24(8), 425-67.
McClendon, J., Klaas, B. S., & Gainey, T. W. (2002). HR outsourcing and the virtual organization. In R. L. Heneman & D. B. Greenberger (Eds.), Human resource management in virtual organizations (pp. 57-79). Greenwich, CT: Information Age Publishing.
McDonald, R. P. & Ho, M. H. R. (2002). Principles and practice in reporting statistical equation analyses. Psychological Methods, 7 (1), 64-82.
McGovern, P., Gratton, L., Hope-Halley, V., Stiles, P. & Truss, C. (1997). Human Resource management on the Line? Human Resource Management Journal, 7(4), 12-29.
McGuire, D,, Stoner, L. & Mylona, S. (2008). The role of line managers as human resource agents in fostering organisational change in public services. Journal of Change Management, 8(1), 73-84.
227
Medsker, G.J., Williams, L.J. & Holahan, P.J. (1994). A review of current practices for evaluating causal models in organizational behavior and human resources management research. Journal of Management. 20 (2), 439-64.
Mehrotra, N. (2005). Business Process Outsourcing The Indian Experience. (First Edition), Hyderabad, India: The ICFAI University Press.
Mello, J. A. (2011). Strategic Human Resource Management. Cengage Learning: India.
Mentzer, J. T., Flint, D. J. & Kent, J. L. (1999). Developing a logistics service quality scale. Journal of Business Logistics, 20(1), 9-32.
Miles, J. & ShevIin, M. (2007). A time and a place for incremental fit indices. Personality and Individual Differences. 42 (5), 869-74.
Miller, D. & Tolouse J. (1986). Chief executive personality and corporate strategy and structure in small firms. Manage Sc!, 32(11), 1389-409.
Millward, N., Stevens, M., Stuart, D. & Hawes, W.R. (1992). Workplace industrial relations in transition: The ED/ESRC/PSI/ACAS Surveys, Dartmouth Publishing, Aldershot.
Mitsuhashi, H., Park, H. J., Wright, P. M. & Chua, R. S. (2000). Line and HR executives' perceptions of HR effectiveness in firms in the People's Republic of China'. The International Journal of Human Resource Management, 11(2), 197-216.
Mobley, N. (2000). What you need to know now about outsourcing HR functions. HR Focus, 7-I0.
Mohrman, S. A. & Lawler, E. E. 111 (1999). The new human resources management: creating the strategic business partnership, in Schuler, R.S. and Jackson, S.E. (Eds), Strategic Human Resource Management, Blackwell: Oxford.
Morley, M. J., Gunnigle, P., O'Sullivan, M. & Collings, D. G. (2006). Guest Editorial New directions in the roles and responsibilities of the HRM function. Personnel Review, 35(6), 609-617.
Mulaik, S.A., James, L.R., Van AIstine, J., Bennet, N., Lind, S., & StilweIl, C.D. (1989). Evaluation of goodness-of-fit indices for structural equation models. Psychological Bulletin. 105 (3), 430-445.
Murry, G. R. K. (2007). HRM in Knowledge Economy. (First Edition), Hyderabad, India: The ICFAI University Press.
Mustapha, .N., Ahnnad, A., Uli, J. & Idris, K. (2010). Mediating effects of work-family factors in the relationship between organizational characteristics and intention to stay. European Journal of Social Sciences, 16 (1), 117-137.
Nachmias, C. F. & Nachmias, D. (2008). Research methods in the social sciences. (7 h Edition), New York: Worth.
Nehles, A.C., van Riemsdijk, M.J., Kok, 1. & Looise, J.C. (2006). Implementing human resource management successfully: The role of first-line managers. Management Review, 17(3), 256-273.
Nininger, J.R. (1980). Human resources and strategic planning: A vital link. Optimum, 11(4), 33-46.
Nixon, J. & Carroll, M. (1994).. Can a line manager also be a Counsellor? Employee Counselling Today, 6(l), 10-15.
Nonaka, I. (1988). Towards middle up/down management: Accelerating information creation. Sloan Management Review, 29, 9-18.
228
Novicevic, M. M. & Harvey, M. (2001). The changing role of the corporate HR function in global organizations of the twenty-first century. The International Journal of Human Resource Management, 12(8), 1251-1268.
Nowack. K. •M. (1990). Getting them out and getting them back. Training and Development Journal, April, 82-85.
Nunnally, J. C. & Bernstein, I. H. (1994). Psychometric theory (3rd edition.). New York: McGraw-Hill.
Nunnally, J. C. (1978). Psychometric theory (2 ed.). New York: McGraw-Hill.
Nwachukwv, S. L. S., Vitell, Jr. S. J., Gilbert F. W. & Barnes, J. H. (1997). Ethics and social responsibility in marketing: An examination of the ethics evaluation of advertising strategies. Journal of Business Research, 39(2), 107-118.
O'Brien, P. (2005, October 1). The rise of human resources outsourcing. Computer Business Review Online.. Retrieved March 4, 2006, from http:Ilwww.cbronline.comlarticle—cbr.asp?guid3ED008C4-E811-4ABA-8333-C2 34E774D20F.
Ohtaki, R. (2005). HRM questions for the CEO, In Ohtaki, R. and Bucknall, H. (Eds.) Mastering Business in Asia Human Resource Management. Mercer Human Resource Consulting: JohnWiley & Sons (Asia) Pte. Ltd.
Oshima, M., Kao, T., & Tower, J. (2005). Achieving post-outsourcing success. Human Resources Planning, 28(2), 7-12.
Othman, R. B. & Ismail, Z. (1996). Strategic 1-IRM: A comparision between selected manufacturing and service firms. Research and Practice in Human Resource Management, 4(1), 43-65
Palo, K., Coetzer, A. & Guenole, N. (2010). Formal development opportunities and withdrawal behaviors by employees in small and medium-sized enterprises. Journal of Small Business Management, 48(3), 281-301.
Papalexandris, N., Chalikias, J. & Panayotopoulou, L. (2001). Comparative Research in Human Resource Management Practice in Greece and the European Union, Editions Benos, Athens.
Papalexandris, N. & Panayotopoulou, L. (2003). Creating synergies in HRM: The role of line managers. EBS Review, 18-24.
Papalexandris, N. & Panayotopoulou, L. (2005). Exploring the partnership between line managers and HRM in Greece. Journal of European Industrial Training, 29(4), 281-291.
Patton, 3. R. (2003). Intuition in decisions, Management Decision, 41(10), 989-96.
Paul, S. A. (2003). Making the outsourcing decision. Sloan Management Review, 45(1), 53-60.
Pfeffer, J. & Davis-Blake, A. (1987). Understanding organizational wage structure: A resource dependence approach. Academy of Management Journal, 30, 437-455.
Perry, E. L. & Kulik, C. T. (2008).The devolution of HR to the line: Implications for perceptions of people management effectiveness. The International Journal of Human Resource Management, 19(2), 262-273. .
Penrose, E. T. (.1959). The theory of the growth of the firm. New York: Wiley.
Pedhazur, E.J., & Pedhazur-Schmelkin, L. (1991). Measurement, Design, and Analysis: An Integrated Approach. Hillsdale, NJ: Lawrence Erlbaum.
229
Peterson, K. D., Wahlquist, C. & Bone, K. (2000). Student surveys for school teacher evaluation. Journal of Personnel Evaluation in Education, 14(2), 135-153.
Phipps, P. A, Robertson, K. W., & Keel, K. G. (1991. Does questionnaire color affect survey response rates? Bureau of Labor Statistics, 441 G St. N.W., Washington, D.C. 202I2.
Ping, R. A. Jr., (2004). On assuring valid measures for theoretical models using survey data. Journal of Business Research.57, 125-141.
Poole, M. J. F. & Jenkins, G. (1997). Responsibilities for human resource management practices in the modem enterprise: Evidence from Britain. Personnel Review, 26(5), 333-356.
Porter, M. E. (1991). Competitive Advantage to Corporate Strategy. In C. A. Montgomeri and M. E. Porter (Eds.), Strategy. Boston, MA: Harvard Business School Press.
Podsakoff. P. M. & Organ, D.W. (1986). Self-Reports in organizational research: Problems and prospects. Journal of Management, 12(4), 531-44.
Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal ofApplied Psychology, 88(5): 879-903.
Pricewaterhouse Coopers. (2002).GIobal human capital survey 2002. Executive Briefing Purcell, J. (1999). Best practice and best fit: Chimera or Cul-De-Sac. Human Resource
Management Journal, 3(9), 26-41.
Purcell, J. & Hutchinson, S. (2007). Front-line managers as agents in the HRM performance causal chain: Theory, analysis and evidence. Human Resource Management Journal, 17(1), 3-20.
Qadeer, F., Shafique, M. & Rehman, R. (2011). An overview of HR-line relationship and its future directions. African Journal of Business Management, 5 (7), 2512-2523.
Quinn, J. B. (1999). Strategic outsourcing: Leveraging knowledge capabilities. Sloan Management Review, 40(4), 9-21.
Quinn, J. B., Doorley, T. L., & Paquette, P. C. (1990). Technology in services: Rethinking strategic focus. Sloan Management Review, 79-87.
Quinn, J. B. & Hilmer, F. (1994). Strategic outsourcing. Sloan Management Review, 35(4), 43-55.
Rainey, G. W., Jr. (2005). Human resource consultants and outsourcing: Focusing on local government. In S. E. Condrey (Ed.), Handbook of human resource management in government (2nd ed., pp. 701-734). San Francisco: Jossey-Bass.
Rao, T.V., Silveria. D. M., Shrivastava. C. M. and Vidyasagar. R. (1994). HRD in the New Economic Environment. (Eds.) New Delhi: Tata McGraw-Hill.
Raykov, T. & Marcoulides, G. A. (2006). A First Course in Structural Equation Modeling. (Second Edition), Mahwah, New Jersey: Lawrence Erlbaum Associates.
Redman, T. (2001). Performance appraisal in Redman, T. and Wilkinson, A. (Eds), Contemporary Human Resource Management, Pearson Education, Harlow, 57-95.
Redman, • T. & Allen, P. (1993). The use of HRM consultants: Evidence from manufacturing companies in the north-east of England. Personnel Review, 22(2), 39-55.
230
Renwick, D. (2000). HR-line work relations. A review pilot case and research agenda. Employee Relations, 22 (2), 179-205.
Renwick, D. (2003). Line Manager Involvement in HRM in Britain: An inside view. Employee Relations, 25(3), 262-280
Renwick, D. & MacNeil, C. M. (2002). Line manager involvement in careers. Career Development International, 7(7), 407-414.
Ritter, J. M., Boone, W. J. & Rubba, P. A. (2001). Development of an instrument to assess prospective elementary teacher self-efficacy beliefs about equitable science teaching and learning • (SEBEST). Journal of Science Teacher Education. 12(3), 175-198.
Rockart, John F. (1988).The line takes the leadership-IS management in a wired society. Sloan Management Review, 29(4), 57-64.
Roszkowksi, M. J., & Bean, A. G. (1990). Believe it or not! Longer questionnaires have lower response rates. Journal ofBusiness and Psychology, 4, 495-508.
Roberts, V. (2001). Managing strategic outsourcing in the healthcare industry. Journal of Healthcare Management, 46(4), 239-249.
Roberts, M.L., & Wortzel, L.H. (1979). New life determinants of women's food shopping behaviour. Journal ofMarketing, 43, 28-39.
Roth, P. L. & Be Vier, C. A. (1998). Response rates in HRM/OB survey research: Norms and correlates, 1990-1994. Journal of Management, 24(1), 97-117.
Rust, R. T., Lee, C. & Valente, Jr. E. (1995). Comparing covariance structural models: A general methodology. International Journal of Research in Marketing, I2(November), 279-291.
Saha, M. (2005). Human resource outsourcing: A strategy for gaining competitive advantage. The Chartered Accountant, 866-874.
Salancik. G. R., & Pfeffer, J. (1977). An examination of need-satisfaction models of job attitudes. Admininistrative Science Quarterly. 22, 427-456
Sekaran, U. (2006). Research methods for -business: A skill building approach. (4 E' Edition). New York: John Wiley & Sons.
Seth, M. & Sethi, D. (2011). Human Resource Outsourcing: Analysis based on Iiterature review. International Journal of Innovation, Management and Technology, 2(2), 127-135.
Schuler, R. S. (1990). Repositioning the human resource function: Transformation or demise? Academy of Management Executive, (4)3, 49-60.
Schuler, R. S. (1992). Strategic human resources management: Linking people with the strategic needs of the business. Organizational Dynamics. 21(1), 18-32.
Schuler, R. S., Dowling, P. 3. & DeCieri, H. (1993). An integrative framework of strategic international human resource management. Journal of Management, 4, 419-459.
Schuler, R. S. & Huselid, M. (1997). HR strategy in the United States - examples of key issues identification and execution. In Tyson, S. (Eds), The practice of human resource strategy (174-203). London: Pitman.
Schuler, R. S. & Jackson, S. E. (1999). Strategic human resource management. Blackwell Publishers.
Schumacker, R. E., & Lomax R. G., (2004). A Beginner's Guide to Structural Equation Modeling. (Second Edition), Mahwah, New Jersey: Lawrence Erlbaum Associates.
231
Sharma, A. & Khandekar, A. (2006). Strategic Human Resource Management.- An Indian Perspective. New Delhi, India: Response Books.
Shaw, S. & Fairhurst, D. (1997). Outsourcing the HR function - personal threat or valuable opportunity? Strategic Change, 6, 459-68.
L. Shaw, J. B., Tang, S. Y. B., Fisher, C. D. & Kirkbridge, P. S. (1993). Organisational and environmental factors related to HRM practices in Hong Kong: A cross-cultural expanded replication. International Journal of Human Resource Management, 4(4), 785-815.
Shen, J. (2005). Human resources outsourcing: 1990-2004. Journal of Organisational Transformation and Social Change, 2(3), 275-296.
Sheehan, C. (2005). A model for HRM strategic integration. Personnel Review, 34(2), 192-209.
Shin, H., Collier, D. A. & Wilson. D. D. (2000). Supply management orientation and supplier/buyer performance. Journal of Operations Management, 18(3), 317-33.
Shook, C. L., Ketchen, D. J., Jr., Hult, G. T. M. & Kacmar, K. M. (2004). An assessment of the use of structural equation modeling in strategic management research. Strategic Management Journal, 25, 397-404.
Simmonds, D. & Gibson, R. (2008). A model for outsourcing HRD. Journal of European Industrial Training, 32(1), 4-18.
Singh, A. (2009). Human resource outsourcing: A bird's eye view. Punjab National Bank Institute ofInformation Technology, V (4), 10-14.
Sisson, K. (1993). In search of human resource management. British Journal of Industrial Relations, 31(2), 201-210.
Sisson, K. & Storey, J. (2000). The realities of human resource management, Buckingham: Open University Press.
Siugzdiniene, J. (2008). Line manager involvement in human resource development. VIESOJI POLITIKA IR ADMINISTRAVIMAS, 25.
Smith, V. (1997). Managing in the Corporate Interest: Control and Resistance in an American Bank. Berkeley CA: University of California Press.
Smith, P. C., Vozikis, G. S. & Varaksina, L. (2006). Outsourcing human. resource management: A comparision of Russian and U.S. practices. Journal of Labor Research, XXVII (3), 305-321.
Snell, S. A. (1992). Control theory in strategic human resource management: The mediating effect of administrative information. The Academy of Management Journal, 35(2), 292-327.
Sodhi, J. S. (1994). Emerging trends in industrial relations and human resource management in Indian industry. Journal of Industrial Relations, 30, 19-37.
Spanos, Y. E., & Lioukas, S. (2001). An examination into the causal logic of rent generation: Contrasting Porter's competitive strategy framework and the resource-based perspective. Strategic Management Journal. 22, 907-934.
Sparrow, P. R. & Hiltrop, J. (1994). European Human Resource Management in Transition. London: Prentice Hall.
Sparrow, P. R. & Marchington, M. (1998). Human Resource Management. The New Agenda. London: Pitman Publishing.
232
Sparrow, P., Schuler, R. S. & Jackson, S. E. (1994). Convergence or divergence: Human resource practices and policies for competitive advantage worldwide. The International Journal of Human Resource Management, 5(2), 267-299.
Spector, P. E. (2006). Method variance in organisational research: Truth or urban legend. Organisational Research Methods 9, 221-231.
Srimannarayana, R. (2010). Line management responsibility in HRM: An empirical study. The Indian Journal of Industrial Relations, 45(3), 470-480.
Stanton, P., Young, S., Bartram, T. & Leggat, S. G. (2010). Singing the same song: Translating HRM messages across management hierarchies in Australian hospitals. International Journal ofHuman Resource Management, 21(4), 567-581.
Steenkamp, J. & Trijp (1991). The use of LISREL in validating marketing constructs. International Journal of Research Marketing. (8), 283-299.
Stening, B. W. (1994). Expatriate management: Lessons from the British in India. International Journal of Human Resource Management, 5, 38S-404.
Stewart, T. (1996). Taking on the last bureaucracy. Fortune, 105-108. Storey, J. (1992). Developments in the Management of Human Resources. Oxford:
Blackwell.
Storey, J. (1995). Is HRM catching on? International Journal of Manpower, 16(4), 3-10. Storey. J. & Sisson, K. (1994). Managing Human Resources and Industrial Relations.
Buckingham: Open University Press.
Stratman, J. K. & Roth, A. V. (2002). Enterprise resource planning (ERP) competence constructs: Ibo-stage multi-item scale development and validation. Decision Science, 33(4), 601-628.
Stroh, L. K. & Treehuboff, D. (2003). Outsourcing HR functions: When and when not to go outside. Journal of Leadership and Organizational Studies, 10(1), 19-28.
Switser, J. (1997). Trends in human resource outsourcing. Management Accounting, 79, 22-24.
Tabachnick, B. G. & Fidell, L. S., (2007). Using Multivariate Statistics.. (Fifth Edition), United States of America: Pearson Education.
Takeuchi, N., Wakabayashi, M. & Chen, Z. (2003). The strategic HRM configuration for competitive advantage: Evidence from Japanese firms in China and Taiwan. Asia Pacific Journal of Management, 20,447-480.
Tang, W., Yu, Q., Crits-Christoph, P., & Tu, X. M. (2009). A new analytic framework for moderation analysis-moving beyond analytic interactions. Journal of Data Science. 7, 313-329.
Teo, S. T. T. (2000). Evidence of strategic FIRM linkages in eleven Australian corporatized public sector organizations. Public Personnel Management, 29(4), 557-574.
Teo, S. T. T. & Crawford, J. (2005). Indicators of strategic HRM effectiveness: A case study of an Australian public sector agency during commercialisation. Public Personnel, Management, 34(1), I-16
Teo, S. T.T., & Rodwell, J. J. (2007). To be strategic in the new public sector, HR must remember its operational activities. Human Resource Management, 46(2), 265-284.
Torrington, D. & Mackay, L. (1986). Will consultants take over the personnel function? Personnel Management, February, 34-7.
233
Thornhill, A. & Saunders, M. N. K. (1998). What if line managers don't realize they're responsible for HR? Lessons from an organization experiencing rapid change. Personnel Review, 27(6), 460-476.
Torrington, D. & Hall, H. (1996). Chasing the rainbow: How seeking status through strategy misses the point for the personnel function. Employee Relations, 18(6), 81-97.
Tracey, J. B. & Nathan, A. E. (2002).The strategic and operational - roles of human resources: An emerging model. Cornell Hotel and Restaurant Administration Quarterly, 43, 17-26.
Tremblay, M., Patty, M. & Lanoie, P. (2008). Human resources outsourcing in Canadian organizations: An empirical analysis of the role of organizational characteristics, transaction costs and risks. The International Journal of Human Resource Management, 19(4), 683-715.
Trochim, W. M. K. (2009). Research Methods. (Second Edition), New Delhi: Biztantra.
Truss, C. (2003). Strategic HRM: Enablers and constraints in the NHS. The International Journal of Public Sector Management, 16(1), 48-60.
Truss, C. & Gratton, L. (1994). Strategic human resource management: A conceptual approach. The International Journal of Human Resource Management, 5(3), 663-686.
Truss, C., Gratton, L., Hope-Hailey, V., Stiles, P. & Zaleska, J. (2002). Paying the piper: Choice and constraint in changing HR functional roles. Human Resource Management Journal, 12 (2), 39-63.
Tsui, A. (1984). A multiple constituency framework of managerial reputational effectiveness. In J. Hunt, D. Hosking, C. Schriesheim, & R. Stewart (Eds.), Leaders and managers: International Perspectives on managerial behavior and leadership (28-44), New York: Pergamon.
Tsui, A. & Milkovich, G. (1987). Personnel department activities: Constituency perspectives and preferences. Personnel Psychology, 40, 519-37.
Tulgan, B. (2001).Winning The Talent Wars, W.W. Norton and Company, New York, NY.
Turnbull, J. (2002). Inside outsourcing. People Management: Connected HR, 10-11.
Tayeb, M.H. (1994). Organisations and National Culture: Methodology Considered. Organisational Studies, 15, 429-446.
UIrich, D. (1996). Human Resource Champions. Boston, MA: Harvard University Press,
Ulrich, D. (1997). Human resource Champions: The next agenda for adding value and delivering results. Boston, MA: Harvard Business School Press.
Ulrich, D. & Brockbank, W. (2005). The HR Value Proposition. Boston, MA: Harvard Business School Press.
U.S. General Accounting Office (U.S. GAO). (2004). Human capital: Selected agencies' use of alternative service delivery options for human capital activities (GAO-04-679). Washington, DC.
Valverde, M. (2001). Mapping the HRM function: An exploratory study of responsibilities and agents in the managing of people. Universitat Rovira i Virgili, Reus.
Valverde, M., Ryan, G. & Soler, C. (2006). Distributing HRM responsibilities: A classification of organizations. Personnel Review, 35(6), 618-636.
234
Van Hoek, R. I. (1999). Postponement and the reconfiguration challenge for food supply chains. Supply Chain Management, 4 (1), 18-34.
Varma, A., Pichler, S., & Srinivas, E. S. (2005). The role of interpersonal affect in performance appraisal: Evidence from two samples-U.S. and India. International Journal of Human Resource Management, 16(11), 2029-2044.
Varma, A., Pichler, S., Srinivas, E. S., & Albarillo, M. (2007). Leader member exchange revisited: An investigation of the moderating and mediating effects of LMX in two samples-USA and India. Management & Labor Studies, 32(2), 203-220.
Vernon, P., Philips, J., Brewster, C. & van Ommeren, J. (2000). European trends in HR outsourcing. London: William M. Mercer and the Cranfield School of Management.
Venkata Ratnam. C. S. (1995). Economic liberalization and the transformation of industrial relations policies in India. In Verma, A., Kochan, T. A. and Lansbmy, R. D. (Eds.) Employment Relations in the Growing Asian Economies. London: Routledge.
Vieira, A. L. (2011). Interactive LISREL in Practice, Springer Briefs in Statistics,-Getting Started with a SIMPLIS Approach. Springer.
Wall, T. D., & Wood, S. J. (2005). The romance of human resource management and business performance, and the case for big science. Human Relations, 58, 429-462.
Wan, D., Kok, V. & Ong, C. H. (2002). Strategic human resource management and organizational performance in Singapore. Compensation and Benefits Review, 34(4), 33-42.
Watson, S. & MaxwelI, G. A. (2007). HRD from a functionalist perspective: The views of line managers. Advances in Developing Human Resources, 9 (1), 31-41.
Watson, S., Maxwell, G. A., & Farquharson, L. (2007). Line managers views on adopting human resource roles: The case of Hilton (UK) hotels. Employee Relations, 29(1), 30-49
Welbourne, T. M., & Cyr, L. A. (1999). The human resource executive effect in initial public offering firms. The Academy of Management Journal, 42(6), 616-629.
Werts, C. E., Rock, D. R., Linn, R. L. & Joreskog, K. G. (1974). Educational and psychological measurement, 1, 34(1), 25-33.
Whittaker, B. (1990). All managers are HR managers. HR Magazine, 67-70.
Whittaker, S., & Marchington, M. (2003). Devolving HR responsibility to the line threat, opportunity or partnership? Employee Relations, 25 (3), 245-261.
Wheaton, B., Muthen, B., Alwin, D., F., & Summers, G. (1977). Assessing reliability and stability in panel models. Sociological Methodology, 8 (1), 84-136.
Widaman, K. F., & Thompson, J. S. (2003). On specifying the null model for incremental fit indices in structural equation modeling. Psychological Methods. 8(1), 16-37.
Wilson, A. (2006). Marketing research: An integrated approach. 2nd ed. Gosport: Prentice Hall.
Wilson, C. (2003, September 5). There's more to outsourcing HT than trimming costs. IPMA-HR News. Retrieved December 22, 2004, from http://www.careerjournal. corn Ihrcenter/ipma/20030905-ipma.html.
235
Williams, L. & Buckley, M. R. (1989). Lack of method variance in self-reported affect and perceptions at work: Reality or artefact? Journal of Applied Psychology, 74(3), 462-468.
Williams, L. J., & Holahan, J. (1994). Parsimony-based fit indices for multiple-indicator models: Do they work? Structural Equation Modeling: A Multidisciplinary Journal. 1(2), 161-189.
Williams, B., Onsman, A. & Brown, T. (2010). Exploratory factor analysis: A five-step guide for novices. Journal of Emergency Primary Health Care (JEPHC), 8(3), Article 990399, 1-13.
Williamson, O. E. (1975). Markets and hierarchies: Analysis and antitrust implications. New York: Free Press.
Williamson, O. E. (1985). The economic institutions of capitalism. New York: Free Press.
Williamson, O. E., Wachter, M. L., & Harris, J. E. (1975). Understanding the employment relation: Analysis of idiosyncratic exchange. Bell Journal of Economics, 6(1), 250-280.
Wood, S. J. (1995). The four pillars of HRM: Are they connected? Human Resource Management Journal, 5 (5), 49-59.
Wooldridge, B. & Floyd, S. (1990). The strategy process, middle management involvement and organisational performance. Strategic Management Journal, 11, 231-241
Woodall, J., Gourlay, S. & Short, D. (2002). Trends in outsourcing HRD in the U.K: The implications for strategic HRD. International Journal of Human Resource Development and Management, 2(1/2), 50-66.
Woodall, J., Scott-Jackson, W., Newham, T. & Gurney, M. (2009). Making the decision to outsource human resources. Personnel review, 38(3), 236-252.
Wright, P. M., & McMahan, G. C. (1992). Theoretical perspectives for strategic human resource management. Journal of Management, 18 (2), 295-320.
Wright, P., McMahan, G., & McWilliams, A. (1994). Human resources as a source of sustained competitive advantage. International Journal of Human Resource Management, 5(3), 299-324.
Wu, S. (2005). Employability and Effective Learning Systems in Higher Education. Paper presented at Ninth Quality in Higher Education International Seminar in collaboration with ESECT and The Independent, Birmingham 27 h -28 h January 2005. Retrieved on 5, 2007 from www.qualityresearchinternational.co./ese/papers /wufv.doc.
Wu, W. & Sukoco, B. M. (2010). Why should I share? Examining consumers' motives and trust on knowledge sharing. Journal of Computer Information Systems. 11-19.
Yammarino, F. J., Skinner, S. J., & Childers, T. L. (1991), Understanding mail survey response behavior. Public Opinion Quarterly, 55, 613-629.
Yin, R. (1994). Case Study Research: Design and Methods. Thousand Oaks, CA: Sage Publications.
Young, S. (2000). Outsourcing: Lessons from the literature. Labour and Industry, 10(3), 97-117.
Yusoff, Y. M., Abdullah, H. S. & Ramayah, T. (2009). HR roles effectiveness and HR contributions effectiveness: Comparing evidence from HR and line Managers. International Journal of Business and Management, 4(2), 158-163.
236
Zhu, C. J., Cooper, B., IDe Cieri, H., Thomson, S. B., & Zhao, S. (2008). Devolvement of HR practices in transitional economies: Evidence from China. The International Journal of Human Resource Management, 19(5), 840-855.
Websites: • www.citehr.com/information-about-hrbpo-vt7351.html
• www.google.com
• www.mca.gov.in
237
4 Take part in decision-making vis-a-vis employee pay management 1 : L:LL
IL
S Take part in decision-making vis-a-vis employee performance a sisal ~~ if
s "~l[ i[i1 ,
6] Take part in decision-making vis-a-vis industrial relations i 2 s j I[J J
J Participate in HR planning processlactivities ❑ °, ' N ' 3 P i J[
j _J
Participate in employee. recruitment & selection processIactivit _j I ❑ .
~<< ❑ e,~ ~~ [ I
[' Participate in employee training & development process/activities ❑ ~; ;; ~x , ;' ;;~ ~ a , P LJjJjLJ 10 Participate In employee reward management processlactivities ❑ ❑ ~ ' T o o , r s a F
11 Participate in employee performance appraisal process!activities i, .0 ❑ ; i .,
12 Participate in maintaining industrial relations ❑ ~ N: ❑ . J j
13 Are involved in budgeting visavis HR planning ❑ ? ra x [:[.L[] . I4 Are
sele ction involved in budgeting vis-a-vis employee recruitment & r
,,:Grain j ::,~..: ,,.. ~.,:~ :`,•....
15 Are involved in budgeting vis-a,vis employee training & development
~a , r
N f 5~
16 -
Are involved in budgeting vis-a-vis employee pay management [_J a"~ tiE 1
11 Are involved in budgeting vis-a-vis employee performance appraisal x
i8 Are involved in budgeting vis-a-vis industrial relations 1 ,; I _____
II: Please write (Y) in the appropriate box depending on the extent of your agreement and disagreement with the following statements.
P S0. Strongly Disagree (1) =====r-=r> SA-Strongly Agree (5)
S,N Statements SD Z 3 4 SA
1 FIRM is viewed as a strategically important function in the organization T] ] 2 Top-level strategic decision-making teams include HR head/executive 9 ~Ll
[DStatusofHRdepartmentsisatparwithotherdeparftnents FIR function is represented at the board level 3 k i
HR executives are provided training in general managerial skills 5 i
66 There is frequent information sharing between FIR managers and senior managers i a :1 ] 1~ The HR department has sigriflcant influence on the strategic decision making process m
D[The HR department has positive relationships with stakeholders of the organization
Overall the HR department can be considered as very effective TJZ =
10. The overall performance of the organization is satisfactory ,~JLJ
1, Sector to which the organization belongs; Service (Write S) 2. Primary ownership of the Company viz, Public Sector (V/rite Pu) 3. Your designation 5. Total experience (Yrs) 7. Total No. of employees in the organization "
Manufacturing ('rite M) Private Sector (Write Pr) 4. Experience in the present position (Yrs) 6. Name of the Organization S. Country of Origin of the Company
Thank You
I: Please indicate whether the above agents perform HR roles in your organization using the key give. below Please mark /(tick) in the appropriate box depending on the extent o f involvementa grog f rom
I1Jo— III
HI
1. j Take part in decision-making vis~a•vis HR planning 1 2 3. 4 -5-.
Z', Takepart indecision -mkingvis•a•viscmployccrecruitment&salactior JJ o; 3. Takepartindecision•makingvis-a•visemp1oyeetraining&development
epartindecision makingvis-a•visemployeepaymanagement ? ?~ 51 Take part indecision makingvis-a•visemployce performance appraisal_ 6. Takepartindecision•makingvis-a•visindusirialrelations 7,; ParticipateinHRplanningprocesslactivities EE ; GI 8. Participate in employee recruitment && selectionprocesslactivitiea 9. Patticip teinem to eetrainin &dcve'l pmeatprace„ ssla. civitie s 10' Participatememployeerewardmagage~ncntprocesslactivities `' 11 Participateinemployeeparformauceappraisalprocess/activities ~2 fidicipateinmaintammgindustnalrclati ,IEEE] K, 13 Are mvolveinbudgetmgvis•a•visHRplamrmg 1 06 14; Areinvolvedinbudgetingyis•a•visamploycerecruitment&solcbtion 15T Areinvolvedinbudgefingvis a-visemployeetraining&'development
ry ~ ' 16: kictm g g vis-a -visemplo~eepaymauageinent. 11 Areanvolv
vedanb u
udget pae r. formanceapprai s gvls~ a vise e mpt Ye e_
Im ~a #
18 Aeinvolediubdgingvis•a•visindus_lrelations
II: P.lease marks (dek h the appropriate box depending on the extent of your agrQC►nent and d agr ement :I
I,~~ HRM is viewed as a siratcgieally important function in the organization 2. '.Top-level strategic decision•making team's include HR head/executive ~ '? 3. Status of HR depthracnts is at, par with other departments 4,! HR function is represented at the board level 5,: HR executives are provided training in general managenaI skills b There is frequent information sharing between HR managers and senior managers 0d
The HR department has significant inquence on the strategic decision•making process, ~y ""~'l, 8, The HR deparht ant has positive relationships with stakeholders of the organization 9.: Overall the HR department can be considered as very effective l The overall performance:of the organization is satisfactory
Conked
i a n t 4i w
1
r
Shahid Mushtaq~ a R,G.scHEy^
Or, Fens TabassumAzmi R niG~~
Fcu6tY Studies RGsrc Aligrh, 22 UU2!
h9obile~ ~9'~~97607~9 2 fail,sha~~an, 2 ~~ aiC,com,s ~~hlaq.Es~amu~a~~i~
Ir