trust within teams: the relative importance of ability...

Trust within Teams:

the

relative importance

of

Ability, Benevolence and Integrity

Douglas A. Beatton

BBus (Finance and Management)

School of Management

Queensland University of Technology

A Dissertation

in fulfilment of the requirements

for the

Degree of Master of Business (Research)

2007

iii

Abstract

Trust between team members is important: Research has shown that teams with

higher levels of trust have a propensity to be higher performers. This study built on

contemporary trust theory by examining initial interpersonal trust development

between a new team member and a newly formed work-team using experimental

rather than correlation-based survey methods. Undergraduate students from a

metropolitan Australian university participated in a vignette experiment examining

the effect of teams with varying levels of Ability, Benevolence and Integrity on trust

development. It was hypothesised that these antecedents of trust do not have similar

effect on our Intention to Trust as is currently depicted in Mayer, Davis and

Schoorman’s (1995) integrative model of organisational trust. Their model is

developed by hypothesising that the type and magnitude of the information we

receive about a trustee moderates the relationship between our Intention to Trust and

its antecedents. Initial examination of the traditional scales identified overlaps that

needed clarification. This was completed by informing existing scales and the

vignette manipulations with the context specific information that emerged from the

thematic analysis of structured interviews. Subsequent analyses of the questionnaire

data used ANOVA and Structural Equation Modelling techniques. In testing the

hypotheses, Ability was found to be most salient in the development of Intention to

Trust. This research contributes methodologically by developing a vignette-based

experimental method that improves the reliability of existing trust scales. The study

contributes theoretically by further explaining the salience of the trust antecedents

and practically by identifying that the judgment and decision-making of new work-

team members can be distorted by halo bias wherein they ignore the Benevolence

traits of team members of a group that exhibits high levels of Ability.

KEYWORDS: Ability; ANOVA; Benevolence; Integrity; Intention to Trust ; Groups; Halo Bias; Teams; Trust; Vignette; Structural Equation Modelling.

v

Table of Contents

CHAPTER ONE..................................................................................................................................... 1

1.1 INTRODUCTION AND OVERVIEW ............................................................................................... 1

1.2 WHY TRUST IS IMPORTANT ......................................................................................................3

1.3 THE RATIONALE FOR THE RESEARCH....................................................................................... 4

1.4 THE RESEARCH GAP................................................................................................................. 6

1.5 THE RESEARCH QUESTIONS......................................................................................................9

1.6 OVERVIEW OF THE THESIS......................................................................................................10

CHAPTER TWO .................................................................................................................................. 15

2.1 DEFINING TRUST.................................................................................................................... 15

2.1.1 THE DIFFERENT TYPES AND THEMES OF TRUST............................................................ 16

2.1.2 RISK .............................................................................................................................. 18

2.1.3 CONTEXT ...................................................................................................................... 19

2.1.4 TRUST IS DYNAMIC ....................................................................................................... 20

2.1.5 ABILITY ........................................................................................................................ 24

2.1.6 INTEGRITY..................................................................................................................... 26

2.1.7 BENEVOLENCE.............................................................................................................. 28

2.2 CHAPTER TWO SUMMARY ......................................................................................................29

CHAPTER THREE............................................................................................................................... 31

3.1 REFINING THE STUDY MODEL ................................................................................................ 31

3.2 CHAPTER THREE SUMMARY ................................................................................................... 39

CHAPTER FOUR................................................................................................................................. 41

4.1 FURTHER DEVELOPING THE HYPOTHESES FOR THIS STUDY.................................................... 41

4.2 CHAPTER FOUR SUMMARY ..................................................................................................... 46

CHAPTER FIVE .................................................................................................................................. 47

5.1 THE RESEARCH DESIGN.......................................................................................................... 47

5.2 ISSUES IN SCALE DEVELOPMENT............................................................................................ 60

5.3 THE DATA COLLECTION PLAN ................................................................................................ 64

5.4 ANALYTIC STRATEGY............................................................................................................. 65

5.5 CHAPTER FIVE SUMMARY ......................................................................................................66

CHAPTER SIX .................................................................................................................................... 67

6.1 METHODOLOGICAL EMPLOYMENT OF THE RESEARCH DESIGN - THE THREE STUDY STAGES . 67

CHAPTER SEVEN ............................................................................................................................. 139

7.1 OVERALL SUMMARY OF STUDY FINDINGS ........................................................................... 139

CHAPTER EIGHT.............................................................................................................................. 143

8.1 DISCUSSION, LIMITATIONS AND FUTURE RESEARCH............................................................ 143

REFERENCE LIST............................................................................................................................. 153

vii

List of Tables

Table 1: Research results from a recent study by Serva et al. (2005) .................................... 43

Table 2: Effect and sample size estimates calculations from similar trust-related studies .... 57

Table 3: Examples of the low Cronbach Alpha results for the trust scales from recent studies............................................................................................................................................... 61

Table 4: Theoretical basis for the thematic analysis of the structured interview transcripts . 70

Table 5: Summary of results for the thematic analysis of the structured interview transcripts............................................................................................................................................... 71

Table 6: The five-point Likert-scaled Propensity to Trust items used in the Pilot Stage of the study....................................................................................................................................... 72

Table 7: The five-point Likert-scaled Intention to Trust items used in the Pilot and Final stages of this study................................................................................................................. 75

Table 8: Examples of the good Cronbach Alpha results for the Ability, Benevolence and Integrity scales used in recent studies.................................................................................... 76

Table 9: The five-point Likert-scaled Ability items used in the Pilot and Final stage of this study....................................................................................................................................... 76

Table 10: The five-point Likert-scaled Benevolence items used in the Pilot and Final stages of this study............................................................................................................................ 77

Table 11: The five-point Likert-scaled Integrity items used in the Pilot and Final stages of this study ................................................................................................................................ 77

Table 12: 2x2 Factorial design for the manipulation of the dimensions of Ability and Benevolence........................................................................................................................... 82

Table 13: 2x2 Factorial design for the manipulation of dimensions of Ability and Integrity 82

Table 14: Descriptive statistics and correlations from Study Stage 2, N = 187 .................... 87

Table 15: Comparison of ITT study results from this research and recent studies employing similar measurement scales based on the Mayer et al. (1995) theoretical foundation........... 87

Table 16: Ability information provided in the Pilot Study Low Ability vignette.................. 88

Table 17: Ability information provided in the Pilot Study High Ability vignette ................. 88

Table 18: Grading scale for the university population........................................................... 89

Table 19: Updated Low Ability vignette content reflecting failing grades............................ 89

Table 20: Univariate statistics from the missing variable analysis of the Stage 3 data ......... 93

Table 21: Descriptive statistics and correlations from Study Stage 3, N = 224..................... 95

Table 22: Comparison of ITT study results from this research and recent studies employing similar measurement scales based on the Mayer et al. (1995) theoretical foundation; N = 224............................................................................................................................................... 96

Table 23: A comparison with recent trust studied reveals the improved scale reliability for Intention to Trust.................................................................................................................... 99

Table 24: Measures and suggested thresholds applied to assess SEM model fit................. 102

Table 25: Y–Variable Squared Multiple Correlations - initial model; N = 224................... 105

Table 26: Squared Multiple Correlations for the Y–Variables in the initial model with the RCMF; N = 224 ................................................................................................................... 107

viii

Table 27: Y–Variable Squared Multiple Correlations - the respecified ITT model; N = 224..............................................................................................................................................110

Table 28: Model-based measures of scale reliability - the respecified ITT model, N = 224110

Table 29: Summary of model fit improvement between the initial ITT model and the respecified ITT model; N = 224 ...........................................................................................110

Table 30: Squared Multiple Correlations for the X–Variables; N = 224..............................111

Table 31: Table A3.1: Squared Multiple Correlations for the X – Variables for the respecified Ability Congeneric model; N = 224...................................................................113

Table 32: Table A3.2: Model-based measures of scale reliability for the respecified Ability Congeneric model; N = 224..................................................................................................113

Table 33: Summary of model fit improvement between the initial and respecified Ability models; N = 224 ...................................................................................................................113

Table 34: Squared Multiple Correlations for X – Variables; N = 224 .................................114

Table 35: Squared Multiple Correlations for the X–Variables in the respecified Benevolence model....................................................................................................................................116

Table 36: Model-based measures of scale reliability for the respecified Benevolence model..............................................................................................................................................116

Table 37: Summary of Model Fit Improvement between the initial and respecified Benevolence models; N = 224..............................................................................................116

Table 38: Squared Multiple Correlations for the X – Variables in the initial Integrity model..............................................................................................................................................117

Table 39: Squared Multiple Correlations for the X – Variables in the initial Integrity model..............................................................................................................................................119

Table 40: Model-based measures of scale reliability for the respecified Integrity model....119

Table 41: Summary of Model Fit Improvement between the initial and respecified Integrity models; N = 224 ...................................................................................................................119

Table 42: Squared Multiple Correlations for the X–Variables for the respecified three-factor CFA model; N = 224 ............................................................................................................121

Table 43: Model-based measures of scale reliability for the respecified three-factor CFA model; N = 224.....................................................................................................................121

Table 44: Summary of model fit difference between the respecified three-factor CFA model and the χ2 threshold for 24 degrees of freedom at p = 0.05..................................................121

Table 45: Variable loading combinations for the comparison of rival First Order CFA Models..................................................................................................................................122

Table 46: Fit indices for the competing First Order CFA models of Ability, Benevolence and Integrity identifying the superiority of the three-factor oblique CFA model; N = 224 .......123

Table 47: Squared Multiple Correlations for the X and Y–Variables in the respecified path analysis model; N = 224.......................................................................................................125

Table 48: Summary of Model Fit Improvement between the initial and respecified path analysis; N = 224. .................................................................................................................125

Table 49: Summary of Model Fit Improvement between the respecified path analysis model and the re-specified path analysis model excluding item Int4; N = 224...............................126

Table 50: Fit indices identifying the superiority of the hypothesised three-factor path analysis model; N = 224.....................................................................................................................127

ix

Table 51: 2x2 Factorial design for the manipulation of the High and Low Information Levels for Ability and Benevolence ................................................................................................ 129

Table 52: 2x2 Factorial design for the manipulation of High and Low Information Levels for Ability and Integrity............................................................................................................. 129

Table 53: Descriptive Statistics of the Dependent Variable: Intention to Trust for Groups with High and Low Information Levels of Ability (ability) and Integrity (integ) ............... 131

Table 54: Descriptive Statistics of the Dependent Variable: Intention to Trust for Groups with High and Low Information Levels of Ability (ability) and Benevolence (benev)....... 134

xi

Table of Figures

Figure 1: Stages of small group development; adapted from Robbins (2006, p. 489)........... 22

Figure 2: Antecedent of Trust – Ability................................................................................. 25

Figure 3: Antecedents of Trust – Ability and Integrity.......................................................... 27

Figure 4: A proposed model of the antecedents of trust – Ability, Benevolence and Integrity............................................................................................................................................... 29

Figure 5: McKnight et al's. (1998) model of initial trust formation....................................... 31

Figure 6: Integrative model of organizational trust (Mayer et al., 1995, p. 715).................. 33

Figure 7: Example dimensions of Situational Strength; adapted from (Gill et al., 2005)...... 36

Figure 8: The proposed Information Levels of the trust antecedents..................................... 37

Figure 9: The proposed theoretical model for the study of how the antecedents of trust affect our Intention to Trust in the context of newly forming work-teams...................................... 38

Figure 10: The Three study Stages ........................................................................................ 47

Figure 11: Initial 3x2 factorial design depicting Information Levels of Ability, Benevolence and Integrity........................................................................................................................... 59

Figure 12: The Study Stages .................................................................................................. 65

Figure 13: Study Stage 1........................................................................................................ 67



Figure 16: Box plot of Intention to Trust for Stage 2 ............................................................ 98

Figure 17: Box plot of Intention to Trust for Stage 3 ............................................................ 98

Figure 18: A priori conceptualisation of the study model to be tested using LISREL 8.3 .. 101

Figure 19: Standardised Solution for the respecified Congeneric CFA Model of the endogenous factor Intention to Trust; items Itt2, Itt3, Itt7 and Itt9 excluded ...................... 109

Figure 20: Standardised solution for the respecified congeneric CFA model of the trust antecedent Ability; items Ab1, Ab5 and Ab6 excluded....................................................... 112

Figure 21: Standardised Solution for the Re-specified Congeneric CFA Model of the trust Antecedent Benevolence; items Ben2 and Ben3 excluded..................................................115

Figure 22: Standardised Solution for the respecified Congeneric CFA model of the trust Antecedent Integrity; Items Int4, Int5 and Int6 excluded .................................................... 118

Figure 23: Standardised Solution for the respecified first order CFA model of the trust antecedents; Ability, Benevolence and Integrity; N = 224 .................................................. 120

Figure 24: Standardised solution for the respecified path analysis model of Intention to Trust and its antecedents Ability, Benevolence and Integrity; N = 224........................................ 124

xiii

Glossary of Terms and Abbreviations AB Ability

ANOVA Analysis of Variance

BEN Benevolence

CFA Confirmatory Factor Analysis

DV Dependent Variable

HAHB High Ability combined with High Benevolence Information Level

HALB High Ability combined with Low Benevolence Information Level

HAHI High Ability combined with High Integrity Information Level

HALI High Ability combined with Low Integrity Information Level

INT Integrity

ITT Intention to Trust

IV Independent Variable

LAHB Low Ability combined with High Benevolence Information Level

LAHI Low Ability combined with High Integrity Information Level

LALB Low Ability combined with Low Benevolence Information Level

LAHI Low Ability combined with Low Integrity Information Level

LISREL Linear Structural Relations

ML Maximum Likelihood

PTT Propensity to Trust

QUT Queensland University of Technology

SEM Structural Equation Modelling

SPSS Statistical Package for the Social Sciences

xv

Statement of Original Authorship

The work contained in this thesis has not been previously submitted for a Degree or

Diploma at any other higher education institution. To the best of my knowledge and

belief the thesis contains no material previously published or written by another

person except where due reference is made in the thesis itself.

Signed : ___________________________ Date: __________

Douglas A. Beatton

xvii

Acknowledgements

Many people contributed to the completion of this thesis. To all those involved I

offer my sincere gratitude and thanks. There are some people whose contribution was

exceptional; I would like to acknowledge their considerable assistance. First, thank

you to my wife, Debbie, and our two sons, for their understanding and patience. It

was your love and support that has been the greatest driving force. To my

supervisors, Dr. Kerrie Unsworth, Dr. Neal Knight-Turvey, thank you for your

guidance and advice, for believing in me, for helping me develop my research skills,

and especially to Kerrie for your continuous support, even as you readied for your

firstborn.

To Dr. Stephen Cox, thank you for your responsiveness and willingness to answer

my interminable questions regarding method and quantitative analysis. Stephen, your

proactive assistance helped me improve my analytical approach and enabled me to

realise additional benefits from my study effort. To Associate Professor Lisa Bradley

whose knowledge and experience in the development of vignettes was invaluable. To

Dr Chrys Gunasekara for his ongoing mentoring and support, thank you. To my

fellow research students for the helpful advice and debate that contributed to my

understanding. In particular, thank you to Francis Chan, Sukie Sawang, Tony Niven,

Mark Keogh, Laxman Samtani and the recently completed Dr Jack Keegan and Dr

Glen Murphy who were always available to share the load when things became

difficult.

My thanks go to the hundreds of anonymous Queensland University of Technology

(QUT) Business Faculty students who willingly, and without reward, offered

themselves as subjects for this study. Finally, the assistance of the School of

Management, the Faculty of Business, the Research Students Centre and the Library

staff at QUT is gratefully acknowledged.

1

Chapter One

1.1 Introduction and Overview

Trust touches nearly every facet of our lives. As a baby, we are initiated to trust

through a deep and abiding faith that emerges from the relationship with those who

care for us (Raths, 1972). In our daily lives, we extend interpersonal trust to a person

or group in expectation that they can be relied upon (Rotter, 1967). ‘Trust is essential

for stable social relations’ (Blau, 1964, p. 99). In business, we trust in the benefits

that are expected to result from our cooperative day-to-day interpersonal relations

with fellow workers (Whitener, Brodt, Korsgaard, & Werner, 1998). Trust promotes

mutual understanding and global collaboration (Child, 2001). From an organisational

perspective, trust between individuals and groups within our organizations is a very

important ingredient in the long-term stability of our organizations and the well-

being of their participants (Cook & Wall, 1980). Trust is a fundamental ingredient or

lubricant, an unavoidable dimension of social interaction (Mayer et al., 1995)

between employees and their managers.

Today’s managers are expected to be forward thinking, they are expected to apply

their limited time to long-term strategic decision-making (Hill & Jones, 2004;

Mankins & Steele, 2006). At the same time, managers are goaled to satiate the

shareholder mentality that holds them responsible for short-term budgets, revenues,

profits and dividends (Misztal, 2002). In an environment of escalating global market

demands (Prahalad, 1997) business seeks nimbleness and agility (Champy, 1997) in

pursuit of sustainable competitive advantage, efficiency and flexibility. To maximise

flexibility and efficiently reduce costs in our dynamic global marketplace many

companies have downsized, reduced management layers and employed more part-

time or contracted staff (Daft, 2004; Makridakis, 1992); and this has the potential to

erode trust in the organisation, management and fellow employees (Mishra &

Spreitzer, 1998). ‘The myth of a life-long career with an organization is shattered by

the stark realities of downsized and flattened corporations’ (Lawrence & Corwin,

2003, p. 937). In the period 1971 and 2001, the proportion of employed persons

working in full-time jobs in Australia declined from 89% to 69%’ (ABS, 2003). In

the August 2005 quarter, the 27,200 increase in part-time workers in Australia

2

exceeded the 14,500-fulltime workforce increase by 88 percent. In the growth labour

market of the past decade, where demand for skilled workers currently exceeds

supply, it would seem reasonable to expect that Australian employers would seek to

retain their workforce by offering them full-time employment. This has not been the

case, the trend towards part-time employment continues; part-time workers now

constitute 2,926,400 of Australia’s total workforce of 10,288,800 (ABS, 2006).

An impermanent workforce of part-time workers has reduced exposure to the culture

of our organisations (Misztal, 2002); organisations whose success is founded upon

the moral bonds of social trust (Fukuyama, 1995). In western countries like

Australia, reliance on a part-time workforce can undermine organisational trust and

the human resource development initiatives that seek to enhance employee

commitment and teamwork (Lawrence & Corwin, 2003). To complicate matters, the

complexity of today’s work tasks (Keen, 1990) finds managers responsible for an

increasing number of teams containing knowledge workers (Handy, 1996) whose

skills and experience can exceed that of the manager (Drucker, 1999). Work

complexity has resulted in an increased dependence on work teams (Drucker, 1997).

A resultant high-trust managerial culture demands that organisations of the future

create the conditions for the prompt development of trust among its teams of

employees (Drucker, 1997 in Misztal, 2002). In an environment where managers are

held more accountable and the workforce more mobile, managers are forced to trust

in work-teams to deliver expected outcomes on time and within budget.

3

1.2 Why Trust is Important

If managers are to deliver to expectations, they would do well to recognise that

societies of high trust do better economically (Fukuyama, 1995). The development of

trust between the employees of an organisation has been shown to offer positive

outcomes for the organisation and its employees. From the organisational

perspective, trust enhances alliance success (Parkhe, 1998) and encourages

communication and collaboration between organisations (Child, 2001) and their

leadership (Atwater, 1988). Trust is considered pivotal to encouraging intra and

inter-organisational communications across virtual collaborative environments like

the Internet (Coppola, Hiltz, & Rotter, 2004); (Paul & McDaniel, 2004).

Trust increases acceptance of an organisation’s culture and contributes to employee

satisfaction with their employer, their managers, and their direct supervisors

(Costigan, Ilter, & Berman, 1998; Mayer & Davis, 1999; Martin, 1999; Rousseau,

Sitkin, Burt, & Camerer, 1998; Simon, 1995). Trust reduces the intention for

employees to leave their current employer (Wong, Ngo, & Wong, 2002) thereby

reducing an organisations cost of employment and training. Trusting employees are

more innovative (Tan & Tan, 2000) thereby contributing to a firm’s competitive

advantage (Santoro & Saparito, 2003). Trusting employees are less likely to waste

valuable time monitoring others to protect their own positions (Costa, Roe, &

Taillieu, 2001). Trusting employees are more likely to exhibit increased commitment

(Whitener, 2001; Watson & Papamarcos, 2002) to value-adding activities and the

achievement of their organisation’s goals (Mayer & Gavin, 2005). Trusting

employees are more productive (Earley, 1986). Trust acts as a control, tempering the

potential downside of empowerment and reducing the risk that employees will not

perform work to expectations (Mills & Ungson, 2003). More importantly, the

development of trust between employees and an organisation’s customers enhances

customer loyalty and optimises the retention of valued clients (Casielles, Alvarez, &

Martin, 2005). The development of trust between management, employees and

customers offers positive outcomes and considerable benefits to an organisation.

4

From the perspective of the employee, increased levels of trust positively affect an

organisation’s commitment to the employee (Wong, Ngo et al., 2002). This

reciprocal social exchange which engenders feelings of personal obligation,

gratitude, and trust (Blau, 1964, p. 94) between the organisation and its employees

can enhance cost-reducing organisation citizenship behaviours such as helping fellow

workers or even lead to socially responsible behaviours such as volunteering to assist

in the wider community (Aryee, Budhwar, & Chen, 2002; Mayer & Gavin, 2005;

Watson & Papamarcos, 2002). An increase in interpersonal trust between employees,

their fellow team members, and their managers can help rebuild trusting

interpersonal relationships (Kim, Ferrin, Cooper, & Dirks, 2004; Tan & Tan, 2000),

reduce workplace stress (Costa et al., 2001) and assist in reducing conflict in the

workplace (Tidd, McIntyre, & Friedman, 2004). This can lead to increased

communication (Giffin, 1967), collaboration (Coletti, Sedatole, & Towry, 2005),

greater information sharing (Abrams, Cross, Lesser, & Levin, 2003) and transfer of

knowledge both within and between organisations (Levin, Cross, & Abrams, 2002).

Increased levels of trust can enhance job satisfaction and increase job performance

by individuals, work teams and organisations (Dirks, 1999); (Spreitzer, Noble,

Mishra, & Cooke, 1999). This research recognises the positive benefits of trust and

seeks to enhance those benefits by deepening our understanding of the development

of trust between the employees, work teams, and the management of an organisation.

Understanding how to better develop trust has the potential to help management

optimise the ensuing positive outcomes that can benefit the organisation, its

employees and the customers they serve.

1.3 The Rationale for the Research

The introduction identified that a plethora of recent research effort has been applied

to widening our understanding of trust. However, there are disparate views of trust.

Elangovan and Shapiro (1998) as well as Jones and George (1998) view trust as an

independent variable affecting outcomes. On the other hand, McKnight, Cummings,

& Chervany (1998) theorise trust as an outcome; they view trust as a variable

dependent upon our initial disposition to trust, the institutions involved in the

decision to trust and how we cognitively assess outcome certainty based on our

trusting beliefs in the competence, benevolence and honesty of those involved. In

5

some cultures like Japan, trust is distinguished as a dependent variable, an outcome

arising from individuals linked to one another through bonds and relationships. For

example, Ouchi (1981, p. 54 & p. 87) is of the opinion that Japanese cultural identity

is based upon clans of workers, teams, dedicated to their organisation on the basis of

trust. Das and Teng (2001b; 2004) perceive different types of trust that moderate or

mediate our behaviour. Similarly, Robinson & Rousseau (1994) assert that trust has a

moderating role in shaping causal relationships and interpersonal behaviour in

organizations and social settings. In seeking to develop theory, trust has been viewed

differently by many researchers.

Much theory development has focussed on the outcomes of trust (Bhattacharya &

Devinney, 1998). Considerable effort has been exerted to understand trust outcomes

in direct and virtual relationships between employees, management, organisations

and their customers (Abrams et al., 2003; Auh, 2005; Connell, Ferres, &

Travaglione, 2003; Coppola et al., 2004; Costigan et al., 1998; Das & Teng, 2001a;

Korsgaard, Brodt, & Whitener, 2002; Wong, Wong, & Ngo, 2002). In spite of these

laudable scholarly efforts, there has been a call for additional theory contribution;

research on the antecedents of trust has lagged behind theory (Ferrin & Dirks, 2003).

A recent study by Ferres, Connell, & Travaglione (2004, p. 617) reinforces the

importance of understanding trust development in the workplace because ‘co-worker

trust may contribute to factors aiding individual and organisational performance’.

They suggested future studies could focus on causal inferences by deepening our

understanding of the antecedents that lead to the development of trust in the

workplace.

6

1.4 The Research Gap

There appears to be a gap in our understanding of the antecedents that affect co-

worker trust development. Trust is an important factor in an employees preference to

work in a team, the development of the team, team behaviour, and the effective

functioning of work teams (Coppola et al., 2004; Costa, 2003; Kiffin-Petersen &

Cordery, 2003; Serva, Fuller, & Mayer, 2005; Williams, 2001). Trust is important

because we have previously identified that teams complete much work in our

organisations, and, trust positively affects team effectiveness and their contribution

to the business. In the September 2005 Journal of Organisational Behaviour the

research of Serva et al. (2005) focussed on trust and teams and concluded by calling

for deeper contextual consideration in trust theory development within work teams.

Thus, there appears to be two areas where research could potentially contribute to

our understanding of trust; 1) we could benefit from enhancing our understanding

how the antecedents affect trust development, in; 2) the context of the work-teams

that now populate our workplaces.

In seeking to refine a research gap, it may assist if we review recent contributions

from trust researchers. Much research has clarified our understanding of how we

extend trust to the organization, manager, individual or work group (Costa, 2003;

Costa et al., 2001; Earley, 1986; Gill, Boies, Finegan, & McNally, 2005; Mayer &

Davis, 1999; Schoorman, Mayer, & Davis, 1996b; Serva, Benmati, & Fuller, 2005;

Tan & Tan, 2000; Whitener et al., 1998). However, much of this research involved

field studies that, while more generalisable to the context under study, can suffer

from confounds that could reduce the internal validity of study results (Christensen,

2004). For example, the 1999 study by Mayer & Davis involved a field quasi-

experiment that sought to understand the effect of a newly introduced performance

appraisal system on employee’s trust in management. While the study deepened our

understanding of factors that can affect trust, the study was performed in the

everyday work environment where numerous confounding factors such as social

interaction between employees, workload, or even experiences from outside the work

environment could have contaminated study results. More recent field research by

Serva et al. (2005) enhanced our understanding of trust development by studying

trust development over the life of work-teams. The Serva et al. (2005) study gauged

7

the trust between work teams over a six-week software development project.

However, like the Mayer study, it too could have suffered from the contamination

that arises from uncontrollable factors. Thus, there appears to be an opportunity to

deepen our understanding of trust development in a research setting that seeks to

minimise confounding factors (Christensen, 1994); there appears to be opportunity

for experimentation in the area of trust.

The experiment of Gill et al. (2005) pursued such a goal and helped us understand

how different levels and types of antecedent information affect how we extend trust

to others. However, like previous studies (Costa, 2003; Costa et al., 2001; Mayer &

Davis, 1999; Schoorman et al., 1996b; Tan & Tan, 2000; Serva et al., 2005), the

work of Gill et al. (2005) concurrently examined the antecedents of trust. Perhaps

this is why Gill et al. (2005) concluded by calling for additional research that furthers

our understanding of the specific factors that are most salient in the development of

interpersonal trust. In seeking to exclude confounding factors, there appears to be an

opportunity to perform an experiment that seeks to enhance our understanding of the

salience of the antecedents in the development of trust.

While we have identified that there is an opportunity to perform an experiment that

seeks to enhance our understanding of the salience of the antecedents in the

development of trust, the earlier discussion reminds us of the paucity of trust

research in the context of work-teams. The aforementioned longitudinal study by

Serva et al., (2005) sought to enhance our understanding of trust development by

collecting and examining three waves of data. However, the data were collected after

the teams had formed and their team goals had been defined by management.

Contemporary views of the lifecycle of a team (Robbins, 2006) build on the work of

Tuckman & Jensen (1977) and remind us of a pre-stage in team development. The

pre-stage is when we know little about future team members. At this stage, we need

to apply our past teamwork experience and what little information we have about

team members to cognitively assess whether we could trust the newly forming work-

team. This researcher is not aware of studies that concatenate the three identified

trust research gaps: 1) which combination of antecedents are most salient in trust

development; 2) in the pre-stage context; 3) of a newly forming work-team?

8

In the context of newly forming work teams, there is a paucity of research examining

the extent to which the antecedent factors contribute to the initial development of

trust between the team members. Increasing our understanding of which antecedent

or combination of antecedents optimally impacts upon interpersonal trust has the

potential to help management develop new work-teams. In seeking to contribute to

this gap in the literature, this study will examine which antecedent or combination of

antecedents most affects trust development between members of a newly forming

work-team.

In summary, deepening our knowledge of how to better develop trust between

members of newly forming work-teams has positive implications for business. This

is particularly important because much of our work today is performed in teams.

Research effort that contributes to trust theory development in the area of newly

forming work-teams has the potential to accelerate the benefits that emerge from

more trusting work environments. In the hands of practitioners, the knowledge of

how to develop trust between members of newly forming work-teams has the

potential to form the basis of organisational development programs that positively

contribute to individual, team, management and organisational performance.

9

1.5 The Research Questions

There is a need to understand how to initiate trust in newly forming work-teams by

seeking an explanation to the questions:

R1: How do we develop interpersonal trust in the context of newly forming

work-teams?

And, more specifically

R2: Which trust antecedents are more important when initiating trust between

the team members?

10

1.6 Overview of the Thesis

Chapter 1 has identified the growing importance of trust in today’s complex

workplace with a propensity to organise workers into teams. A concurrent move

towards an impermanent workforce of contract, part-time and temporary staff raises

the spectre of declining levels of trust between organisations, management and

employees with ramifications for loss of productivity and declines in the level of

customer service. In the shadow of this potential threat, managers are expected to

deliver expected outcomes on time and within budget.

In the environment of managers delivering to expectations, the significance of high

levels of trust within our workforce has been identified. In our contemporary

environment of part-time employees working in teams, the advantages of high levels

of trust between the stakeholders of a business was applied to support an informed

opinion emerging from the literature that further research contribution is warranted in

the area of trust development within work-teams. Initial information gathering

revealed disparate research perspectives of trust as an independent, dependent, or

moderating variable. Clarity emerged by identifying the paucity of research

addressing the causes, the antecedents of trust. It is argued that a research gap exists

in our current theoretical understanding of trust development in the context of newly

forming work-teams. Two antecedent focussed research questions emerged:

R1: How do we develop interpersonal trust in the context of newly forming

work teams?

and

R2: Which trust antecedents are more important when initiating trust

development between team members?

11

In Chapter Two, the literature review reveals the many facets of trust that sparkle

from the disparate views of the scientific disciplines. In the work-team context of this

study, a non-exhaustive list of trust types is defined and exampled. Instead of

accepting the perspective of a particular scientific discipline, the differing

perspectives are distilled to produce six core themes that are considered the essence

of trust; they are risk, context, dynamics, expectation, principles, and, competence. A

synthesis of these trust themes reveals three antecedent factors of Ability,

Benevolence and Integrity that arguably contribute to our Intention to Trust members

of a newly forming work-team. These antecedents and the hypotheses that emerge

are the focus of this study.

Chapter Three develops the study model of initial trust formation between members

of a newly forming work-team by comparing and contrasting two competing models.

While the kernel of the McKnight et al. (1998) model is similar to the Mayer et al.

(1995) integrative model of organisational trust, the McKnight et al. (2002) model

fails to adequately consider the dynamics involved in trust formation. For this reason

the Mayer et al. (1995) model is selected as the foundation for this study. However,

the Mayer et al. (1995) model also has deficiencies; it does not consider the effect of

the good or bad information that feeds back to us after we extend trust. In

consideration of the varying levels of the good or bad feedback that we receive when

we extend trust to a trustee, an Information Level for the trust antecedents is added to

the study model.

Chapter Four applies the study model to the context of a member joining a newly

forming work-team. It is proposed, that at the pre-stage of trust development, the

feedback that informs us that the trustee did what we expected does not come into

play because we have not yet shared a trusting episode. It is identified that before we

make an informed decision to join a team, we need information about the Ability,

Benevolence and Integrity of the other team members. In seeking to understand these

factors, previous studies provided differing results; there is scholarly disagreement

over which antecedent of trust is most important in trust development between

members of a newly forming work-team. In the context of a member choosing to join

a newly forming work-team, hypotheses predict the salience of the trust antecedents.

12

Chapter Five justifies and explains the research design for this three stage

experimental study. The initial Vignette Development Stage will use structured

interviews to determine the content of the vignette manipulation applied in

subsequent stages. The Pilot Stage pre-tests the vignettes and questionnaires to

facilitate their refinement for the Final Data Collection Stage. The research design

choices for the study setting, the type of measures, the unit of analysis, the time

horizon, and, the research paradigm are defined and justified. In the study context of

newly forming work-teams, it is argued that a population of Business Faculty

Undergraduate Students from a metropolitan Australian university are appropriate for

this research. The sampling design is justified in terms of the randomised application

of eight different vignette manipulations and sample size recommendations are

supported by calculations that consider the effect size requirements of the

correlation, ANOVA, and Structural Equation Modelling (SEM) techniques to be

employed in the subsequent data analysis. Finally, the reasons for questionnaire item

customisation is justified in terms of random measurement error reduction and the

resultant vignette and questionnaire development strategy is offered as a contribution

to enhance the reliability of contemporary trust scales. To finalise the methodological

plan, the data collection process is explained.

Chapter Six details the methodological application of the research design in the three

study stages. In Stage 1, structured interviews are thematically analysed to

theoretically derive the questionnaire and vignette content. In seeking to improve

internal validity of the scales, the phrases of the interviewees are applied to reword

the questionnaire items to reflect the context of the study. In Stage 2, issues emerge

from the piloting of the vignettes; expectations concerning subject interpretation of

work-team information reveal an interesting perspective on how university students

adjudge the ability of fellow team members. The resultant refined vignettes are

applied to collect the Stage 3 data that is prepared for correlation, ANOVA and SEM

analysis. Congeneric Confirmatory Factor Analysis refines the measurement

variables and subsequent First Order Confirmatory Factor Analysis identifies the

antecedents of trust. A test of competing path analysis models converges on a multi-

factor model that identifies the antecedents of trust and ANOVA analysis is used to

identify the salience of the trust antecedents in the context of newly forming work-

teams.

13

Chapter Seven progressively applies empirical results to summarise study findings.

The relative importance of the trust antecedents of Ability, Benevolence, and

Integrity on the development of our Intention to Trust is revealed. Hypotheses

conclusions are supported with descriptive statistics and inferences from ANOVA

and the results of the fitted Structural Equation Models.

Chapter Eight discusses the finding in the context of the study setting. Explanations

are offered for why particular trust antecedents are more salient in trust development.

Practical implications for the findings are discussed and possible trust-building

actions are suggested. Finally, a non-exhaustive list of study limitations is offered

and opportunities for future trust-related research are revealed.

15

Chapter Two

2.1 Defining Trust

A review of literature identified that trust may be difficult to define; scientific

disciplines view trust differently (Korsgaard et al., 2002; Rotter, 1967 ; Rotter,

Chance, & Phares, 1972). McKnight et al. (1998) assert that the word "trust" is so

confusing (Shapiro, 1987a) and broad (Williamson, 1993) that it defies careful

definition (Gambetta, 2003). Viewed through the lenses of the scientific disciplines,

the disparate definitions of the phenomena referred to as trust can be confusing.

Anthropologists embark on an intellectual journey that views trust from the

perspective of a society’s cultural values and practices (Blum, 2005). Sociologists

have contributed to our scholarly understanding by considering trust from the

perspective of socially embedded processes between people and authority (Bijlsma-

Frankema & Costa, 2005). They consider the socially embedded properties of our

relationships and the involvement and exchange of power in our social relations with

others and the notion of social balance wherein we innately reciprocate to the good

intentions of others (Blau, 1964).

To an economist ‘trust is important and businessmen rely on it much more

extensively than is commonly realized’ (Williamson, 1975, p. 108). Economists

consider that trust flows from structured contracts, rewards or punishments that cause

individuals to behave in a certain manner. Economists are concerned with the cost

and benefits of specific behaviours (Bhattacharya & Devinney, 1998). The

econometric view takes a calculative (Williamson, 1975) and institutional (North,

1990) perspective wherein trust production involves a process of exchange (Zaheer,

McEvily, & Perrone, 1998) that is predicated upon expectations and outcomes that

are based upon the characteristics of the individuals and the nature of the institutions,

the firms, and the organisational structures involved in the transaction (Zucker, 1986,

p. 60). On the other hand, political scientists view trust through the lens of a political

process predicated upon civic morality and honesty (Letki, 2006; Craig, Martinez,

Gainous, & Kane, 2006). However, like a psychologist, this research views trust in

terms of the dyadic relationship between a trustor and the trustee (Rousseau et al.,

1998) by focusing on the thinking processes an individual, the trustor, goes through

to cognitively determine their Intention to Trust the trustee, another person, group or

16

organisation. With the scientific disciplines viewing trust from disparate

perspectives, it is easy to understand why there are so many different types of trust.

2.1.1 The Different Types and Themes of Trust

Perhaps the reason for the disparate perspectives of the scientific disciplines is the

multitude of facets to the phenomena called trust. Trust appears burdened with a

plethora of descriptive adjectives. Lewicki & Bunker (1996) suggest that trust may

be categorised based on the perspective from which it is viewed. For example, from

the organisational perspective, professional-trust exists among similar professionals

(Misztal, 2002) whose common interests lubricate intra- and inter-organizational

collaborations (Oliver, 1997) which Rus (2005) views as network-trust. Similarly,

institutional-trust results from institutional arrangements characterised in a

sociological perspective (Zucker, 1986); it is the security one feels in a supported

situation where we have ‘guarantees, safety nets, or other structures’ to support our

endeavours (McKnight et al., 1998, p. 475). For example, we trust in our ‘main

foundation’ institution, our government, to look after our best interests (John Child,

2001, p. 276); organisational-trust ‘is a type of institutional trust’ (Wong, Ngo, &

Wong, 2003, p. 487).

From the perspective of trust-based transactions, some use economic-trust to explain

human choice (Miller, 1992); while others use financial-trust to explain our

confidence to deposit money in a banking institution in expectation of it being

returned with interest. From an interpersonal perspective, knowledge-based-trust

(Abrams et al., 2003) assumes the parties have first-hand knowledge of one another

based on a history of information-sharing (McKnight et al., 1998). Similarly,

competence-based-trust is important for the transfer of tacit knowledge (Levin et al.,

2002). Mollering’s (2005) theoretical analysis of trust identifies three types of trust:

1) rational-trust involving choice based on perceived trustworthiness in a specific

context; 2) institutional-trust based on the trustor’s natural propensity to trust in

certain situations, and; 3) active-trust that involves the development of trust in fast

changing situations. When confronted with a new situation such as making a decision

whether to join a newly forming work-team, McKnight et al. (1998, p. 485) are of the

opinion that we engage in cognition-based trust that ‘relies on rapid, cognitive cues

17

or first impressions, as opposed to personal interactions’. This non-exhaustive list of

trust categories has the potential to cloud our understanding of trust. However, if we

probe for themes the mist of confusion begins to clear.

Probing these trust categories, the emerging themes provide direction along the path

to trust definition. Professional, knowledge, or competence-based trust invokes the

notion of capability and competence of the trustee. Organisational and institutional-

based trust could be viewed as emerging from familiar entities in whose standards

and principles of operation and behaviour we trust. Network, cognition and rational-

based trust invokes a vision of the interrelationships between trustors and trustees

wherein the trustee cognitively applies their thinking processes to rationally set

expectations of the benefits that should emerge from decisions to extend trust to a

trustee. Financial and economic-based trust positions the trust decision within a

context or situation wherein the benefits of the transaction are evaluated by the

trustor. Active-trust reminds us that states of trust change, trust is dynamic. As

trustors, we cognitively assess the feedback or new information that emerges from

the previous trusting episodes to decide whether to extend trust to that person or

organisation in the future.

In summary, five core trust themes have been identified: 1) the capabilities or

competence of the trustee; 2) the principles and standards under which they behave;

3) the trustor’s expectation of the benefits that arise from a decision to trust; 4) the

notion that trust occurs in situation or context, and; 5) the dynamic nature of trust.

Before we look at each of these themes in more detail, perhaps we should ask

ourselves, why do we need to trust in the first place? Close examination identifies

that trust occurs in situations where we have a probability that an outcome will differ

from what we expect. In a word, 'uncertainty regarding whether the other intends to

and will act appropriately is the source of risk' (Rousseau et al., 1998, p. 395). Trust

is not needed if our actions proceed with complete certainty and no risk is involved

(Lewis & Weigert, 1985). Therefore, risk is the sixth trust theme.

18

2.1.2 Risk

Das & Teng (2004, p 110) take a risk-based view of trust; defining trust as ‘a mirror

image of risk’. On the other hand, Coleman (1990) and Williamson (1993) identify

trust as subclass of risk because both deal with uncertainty and probability. One thing

we should be able to agree upon; trust is predicated upon uncertainty (Bhattacharya

& Devinney, 1998). If there were no risk involved in our day-to-day interactions with

others, the notion of trust would not emerge (Golembiewski & McConkie, 1975).

Everything would be certain, as we expect. Clearly, we do not live in a world of

certainty. The rate of change is faster now than any other previous time in human

history (Marshall, 2000). In times of change trust is important because it bridges

barriers, helps us form friendships, partnerships and alliances in most situations

(Buchan, Croson, & Dawes, 2002).

For risk to be involved in a situation there needs to be a probability of loss or gain

(Mayer et al., 1995). For example, as managers we provide scarce resources like

computer equipment and money to our staff in expectation that their efforts will lead

to positive outcomes such as the sale of our products and services. In doing so, there

is a probability that our investment may not return what we expect. If our resources

have been expended and the result is no sales, we have effectively lost our resources.

On the other hand, we have made a gain if resource expenditure results in sales with

above average profits. As managers, we evaluate the risk involved in a situation to

determine the probability of success or failure. As a trustor, the trustee is considered

trustworthy when we feel secure in the knowledge that the actions of the individual,

group or organisation will not harm or put us at risk (Jones & George, 1998).

Trusting relationships involve a confidence that no party to the exchange will exploit

the other's vulnerability (Jones & George, 1998). A willingness to take risks may be

one of the few attributes of all situations involving uncertainty (Davis, Schoorman,

Mayer, & Tan, 2000). Trust is a risk taking behaviour or a willingness to be

vulnerable (Costa, 2003). We extend trust in situations of uncertainty (Mayer &

Gavin, 2005) in expectation of positive outcomes (Das & Teng, 2004). In summary,

risk is a theme that affects how we trust; the other trust themes are dynamics,

expectation, principles, competence and context.

19

2.1.3 Context

The literature review identified that trust development in the context of a work-team

has the potential to enhance team, management and organisational performance.

Rousseau et al. (1998, p. 398) assert the importance of considering context in trust-

related research; ‘research on trust requires attention to the context in which trust is

studied; in particular, the researcher needs to be careful about, pulling together

disparate research on trust’; such action ‘requires attention to the context in which

trust is studied’ (Rousseau et al., 1998, p. 398). Jones & George (1998) identify that

trustors and trustees experience positive moods and emotions reflective of the

context in which the trust relationship is developed. Bigley & Pearce (1998) assert

that different trust components can be more important in some contexts. For

example, a different locus of explanation for trust emerges when dispositional,

behavioural-decision, or institutional contexts are involved. In the case of a team,

distal contextual elements like team structures are not only relevant in the

institutional context, they affect how people behave, how they make decisions, and

how they trust those around them (Bigley & Pearce, 1998). Therefore, because this

study considers a trustor’s disposition to trust members of a newly forming work-

team, the theoretical model for this study will focus on the context of teamwork.

In spite of almost universal theoretical acclamation that context has the potential to

affect trust research results, Serva et al. (2005) are of the opinion that our

understanding of trust is hampered by lack of contextual clarity in the literature. The

discussion emerging from the research of Currall & Inkpen (2002) recommends that

context and the level of theorizing, individual, group, or organisation, needs to be

carefully considered for proper trust measurement. The findings of Kiffin-Petersen &

Cordery (2003) add weight to this thinking by suggesting that future trust studies

should distinguish between generalised trust in entities like our institutions and

societal structures and trust in strangers or peers depending on the specific context in

which the relationship is embedded. This research responds to the concerns of these

researchers by focussing the definition of the study model, the subsequent research

design, and the measurement instrument enhancement on the specific context of the

development of trust between members of a newly forming work-team.

20

This research seeks to enhance our knowledge and understanding of how to develop

trust in the specific context of newly forming work-teams. One problem with doing

research on teams is that the label “team” can be associated with a variety of social

and organizational forms; ‘a delimitation of this domain is necessary in order to

understand what work teams mean and how to select them’ (Costa et al., 2001, p.

226). Looking at groups and teams, both have social bonds that integrate and unite

their members. However, the bonds of a team rest on social forces of identity and

attraction that go beyond the minimum requirement externally imposed by groups

who voluntarily form based on a loosely-shared common interest (McShane &

Travaglione, 2003, pp. 274-277). The integrative bonds of a team identify the

members as part of a distinct social group (Blau, 1964). A team is a tight

conglomeration of individuals who have cohesively melded into a single entity

(Chansler, Swamidass, & Cammann, 2003). From the perspective of trusting team

members, we have a proclivity to associate and are socially attracted to those who

share interests, ideas and goals similar to our own (Blau, 1964, p. 34). For the

purposes of this research, the distinct social entity called a work-team is defined as a

formal group of persons who come together for the purposes of work. The

hypothetical work-team in this study shares a social bond based on common values,

beliefs, and, common goals for which all team members are collectively and

equitably recognised and rewarded. The dynamic nature of trust is now discussed.

2.1.4 Trust is Dynamic

One of the most salient factors in the effectiveness of a complex social organizational

form like a work-team is the willingness of one or more individuals in the social unit

to trust others. ‘The efficiency, adjustment, and, even, survival of any social group

depends upon the presence or absence of such trust’ (Rotter, 1967, p. 651).

Researchers from diverse fields agree that trust develops through repeated social

interactions that generate the feedback that enables us to update the information we

use to assess the trustworthiness of the person, the team, the organisation (Gabarro &

Athos, 1976; Lewicki & Bunker, 1996; Mayer et al., 1995; McAllister, 1995;

Sheppard & Sherman, 1998; Williams, 2001; Zand, 1972). These repeated trusting

social interactions cycle through phases of conditional trust to unconditional trust

towards blind trust (Jones & George, 1998). While Rotter (1980) states that we are

21

predisposed to trust. Jones & George (1998) assert that, initially, we do not expect

the other person to be trustworthy; in cognitively assessing the probability that the

trustee will act in our best interests, we conditionally extend trust to them in a

particular situation. As the trustee continues to behave as we expect our confidence

(Deutsch, 1960) builds, we are positively affected and move towards a state of

unconditional trust (Jones & George, 1998) wherein we relax trusting conditions and

become more trusting. When we consider the trustee will always behave as we

expect we enter a state of blind trust wherein we may even defend trustee

transgressions (Jones & George, 1998). An example would be a spouse defending the

errant actions of their long-term partner. Alternatively, if we exhibit negative affect

by continually breaking trust, then the trustor may distrust us by not choosing to

interact with or trust us in the future. The positive affect in the cycle of our

interpersonal social interactions influences our cooperative, pro-social behaviours

and dynamically facilitates trust development (Williams, 2001).

Similarly, trust development is influenced by the trustworthiness beliefs and

behaviour of fellow team members (Williams, 2001). In the context of a team,

(Golembiewski & McConkie, 1975, p. 177) identifies trust as ‘a fundamental

building block upon which the most basic human interaction is built'. Trust between

team members does not just emerge from the ether; trust is a dynamic phenomena, it

builds, declines, and re-emerges over time. For example, beliefs about

trustworthiness may be influenced by how we feel about our social group (Williams,

2001, p. 378), our work-team. In addition, how we feel about our work-team is

subject to the feedback we receive from the previous trusting behaviours of our team

members. Sitkin & Roth (1993) state that trust has a bandwidth with variance in

scope as well as degree. If a trustor extends trust to a trustee and the trustee’s

behaviour is congruent with what the trustor expects, then the trustor will be

positively affected and more likely to reciprocate by extending trust to that person or

entity on another occasion (Blau, 1964). On the other hand, if the behaviour of the

trustee is not what the trustor expects then the probability that the trustor will trust

the trustee in the future will be much reduced. Like the Pavlovian response of a dog

negatively responding to punishment with a rolled up newspaper, the

communications and other feedback we receive from previous trusting episodes

affects our Intention to Trust team members in the future (Galford & Drapeau, 2003;

22

McClelland, 1987; Owen, 1996; Popa, 2005). Therefore, because our trusting state

dynamically changes over time, scholars should view trust as a continuum and focus

on specific stages when developing trust definitions and conceptual frameworks

(Rousseau et al., 1998). In response, this research focuses on the pre-stage (Tuckman

& Jensen, 1977) development of trust between members of a newly forming work-

team.

To clarify, in the life of a team Tuckman & Jensen's (1977) original five stages of

small group development have been extended to incorporate a pre-stage (Figure 1).

Figure 1: Stages of small group development; adapted from Robbins (2006, p. 489)

While a team may transit back and forth through these stages during its lifetime, the

context for this study is the initiation of trust in a dyadic relationship between a

member and their newly forming work-team. At this pre-stage, a new team member

would possess little, if any, knowledge about the other team members. Knowledge

and information about a trustee fuels our decision to extend trust in a given situation

(Lewicki & Bunker, 1996). This information helps us cognitively identify trustee

attributes (Popa, 2005) and affects both our expectations of the trustee (Frost,

Stimpson, & Maughan, 1978) and our Intention to Trust (Mayer et al., 1995). In the

context of this research, a new team member would rely on limited information,

hearsay, available written evidence, or draw on the trust related beliefs from previous

group trusting-experiences to assess whether the group could be trusted.

Pre-stage IPre-stage I Stage IForming

Stage IIStorming

Stage IIINorming

Stage IVPerforming

Stage VAdjourning

Pre-stage IPre-stage I Stage IForming

Stage IIStorming

Stage IIINorming

Stage IVPerforming

Stage VAdjourning

Stage IIINorming

Stage IVPerforming

Stage VAdjourning

23

Trust related beliefs arise from our previous group memberships (Kramer, 2001), our

trusting experiences affect how we associate with social groups (Golembiewski &

McConkie, 1975), like work-teams. Given previous work-team experience, a trustor

would have preconceived perceptions about what to expect from a work-team and

have categorised this form of social or organisational grouping as desirable or

undesirable (Kramer & Cook, 2004). A team member who enjoyed a work-team

experience, perhaps because their expectations were satisfied, would be more likely

to trust in future team-work situations; a dissatisfied team member who was

disappointed with their work-team experience would have a lower propensity to trust

team-work situations in the future (Rousseau et al., 1998).

In the context of this study, a new team member who is offered the opportunity to

join a newly forming work-team would need to decide whether the work-team has

attributes that they consider acceptable. For example, is the team’s work of high

quality, will the team members treat me with respect and will they do as they say. In

making a decision to extend trust to a work-team in a particular context or situation,

we project the attributes (Blau, 1964) of what we categorise as an ideal work-team

into our mental model then incorporate (Williams, 2001) observed recent behaviour

and new information about the work-team we could join. Based on how we

cognitively assess this information, our ensuing trustor behaviour reflects our

decision to extend, or not to extend, trust to the work-team. Our previous work-team

membership and the information we receive about the group affects our decisions to

extend trust. Of course, this raises a question, how does a trustor decide whether to

trust an individual, group or entity when we have no information about the trustee.

In a situation where we have no information about the trustee, we draw on our

previous trusting experiences. Initially, we rely on our innate or natural propensity to

trust or distrust (Raths, 1972). A new team member joining their first work-team

would lack the social or learned experience from pervious teamwork episodes (Rotter

et al., 1972). Based on limited or perhaps no information, they would need to

determine the probability of work-team success or failure based solely on their innate

or propensity to trust.

24

Researchers have different views on how to define Propensity to Trust. (McKnight et

al., 1998) propose those with high faith in humanity (high propensity to trust) would

attend selectively to information congruent with their level of trust in humanity, and

interpret new information according to their natural tendency. J. B. Rotter (1980)

argues that our social learning adjusts both our expectations of others and how we

trust them in the future. Gill et al. (2005) suggests our Propensity to Trust is an

individual’s disposition to trust when we have little or no information about the

trustworthiness of the trustee. In the absence of specific information, it seems natural

that our life experiences, personality type, cultural background, education, and

numerous other socio-economic factors would affect our Propensity to Trust (Mayer

et al., 1995). They propose that once a trustor has information about a trustee,

Propensity to Trust is subsumed by what they call our Intention to Trust, which they

term as our trusting intention when we have context specific information about the

trustee.

This study provides initial information about a trustee and therefore focuses on our

Intention to Trust others. Specifically, this study seeks to identify the salience of the

antecedent information in developing trust between members of a newly forming

work-team. The review of literature has identified a body of evidence that supports

the assertion that once a trustor has received information about a trustee their

Propensity to Trust wanes and our trusting behaviour is a function of our Intention to

Trust (Davis, 1999; Gill et al., 2005; Mayer et al., 1995; Schoorman, Mayer, &

Davis, 1996a). Therefore, the theoretical model for this study will focus on the

antecedents that lead to the development of our Intention to Trust. Based on the

themes that emerged from the review of literature, the first antecedent is our

competence, our ability.

2.1.5 Ability

Our decision to extend trust in a situation is based upon our assessment of the

information we have about the trustee, and that includes their competence (Das &

Teng, 2001b). The trust antecedent of competence is synonymously referred to as

capability (De Dreu, Giebels, & Van de Vliert, 1998), skills (Kirkman, Rosen,

Gibson, Tesluk, & McPherson, 2002), applied, shared or communicated knowledge

25

(Levin et al., 2002), aptitude, expertise, or the expertness that arises from education,

training and experience (Mayer et al., 1995). Williams (2001, p. 379) defines

‘competence as ability or set of skills or competencies that allow us to perform in

some area’. For example, if we provide resources to our employees, do they have

the knowledge, skills, and experience to use them to deliver the outcomes that we

expect? In the case of work teams performing to expectation, we need to trust in the

ability of our fellow team members to perform as expected (Serva et al., 2005); ‘to

trust another party, a trustor must perceive that the trustee has the ability or

competence’ (Davis et al., 2000, p. 566). Gill et al. (2005) found that Ability was

positively associated with our Intention to Trust. Cook & Wall (1980), Mayer et al.

(1995) and Tan & Tan (2000) also consider Ability an essential element, an

antecedent, of our Intention to Trust. Based on this weight of evidence, Competence

is considered, or as Davis et al. (1999) term it, Ability, an antecedent of our

Intention to Trust (Figure 2).

Figure 2: Antecedent of Trust – Ability

Antecedentsof Trust

Ability

Intentionto Trust

+

Antecedentsof Trust

Ability

Intentionto Trust

+

26

2.1.6 Integrity

The next theme affecting trust are the standards or principles underpinning trust. That

belief that another will adhere to a set of standards, principles or values that we deem

acceptable (Mayer et al., 1995). Integrity is another word for principles and both are

perceived as ‘a virtue of character’ (Audi & Murphy, 2006, p. 3); a foundation or

basis for our behaviour (Levin et al., 2002). High levels of integrity are perceived as

a positive trait in an individual (Audi & Murphy, 2006) and an asset to a business

(Koehn, 2005). Integrity is founded upon principles that involve the consistent

adherence to standards of behaviour that are acceptable to a trustor (Mayer et al.,

1995, p. 719-720). McFall (1987) considers adherence and acceptability of the

principles under which we operate as important; others judge our moral and ethical

standards and personal Integrity when they make a decision to extend trust (Bews &

Rossouw, 2002). Davis & Rothstein (2006) found that employees positively

identified with an individual, group or organisation they perceived as high in

Integrity.

Sitkin & Roth (1993, p. 368) go beyond principles to introduce the notion of value

congruence to Integrity. Value congruence emerges from the compatibility and

alignment of beliefs and values between individuals, groups and organisations that

define shared cultural values and norms of behaviour that underpin our Integrity.

Gabarro & Athos (1976) and Misztal (1996) identify that a person of Integrity openly

and reliably exhibits honesty and fairness. To a trustor, these attributes of Integrity

engender a belief that the trustee has a strong sense of justice; there is a low

probability that their words or deeds will harm us (Mayer et al., 1995). Deviant

behaviours such as lying or actions incongruent with our words do the opposite; they

undermine our Integrity (Wanek, 1996), and; they create distrust (Kramer, 1999). We

optimally perceive others to be possessive of Integrity when we share congruent

principles, values and beliefs (Gabarro & Athos, 1976). For example, based on

perceived behaviours, we judge the trustworthiness of a group of workers by

evaluating their principles and values to determine if the Integrity of the trustee is

acceptable and congruent to the standards of behaviour that we consider acceptable

(Sitkin & Roth, 1993, p. 834). Gill et al. (2005) found that Integrity was positively

27

correlated with our Intention to Trust. Together with Ability, Integrity is considered

an antecedent of our Intention to Trust (Figure 3).

Figure 3: Antecedents of Trust – Ability and Integrity

Antecedentsof Trust

Ability

IntegrityIntentionto Trust

+

+

Antecedentsof Trust

Ability

IntegrityIntentionto Trust

+

+

28

2.1.7 Benevolence

Jones & George (1998) propose that a trust experience is determined by the interplay

of not only people's principles and values but also their attitudes, moods and

emotions; how they feel about one another. These feelings are founded upon our

expectation (Rotter et al., 1972) of how the trustee, the other person, group or

organisation, will behave and whether the resultant behaviour is reflective of our

needs and desires (Jones & George, 1998). For some time, expectation has been

viewed as a fulcrum of trust. In 1978, Frost et al. (1978) defined trust as expectancy

held by an individual that the behaviour of another person or a group would be

altruistic and personally beneficial. Much trust literature defines this expectancy as

Benevolence; the extent to which the trustor perceives that the trustee intends to do

good to the trustor in a relationship (Hosmer, 1995; Levin et al., 2002; McKnight et

al., 2002; Mayer et al., 1995; Whitener et al., 1998; Williams, 2001). Benevolence

involves a duty or desire to care for or protect another. Persons of high Benevolence

exhibit loyalty (Butler Jr., 1991) by behaving with a willingness to protect, support,

and encourage others (Hosmer, 1995); Davis et al. (2000) state that Benevolence

represents a positive personal orientation of the trustor towards the trustee.

Three factors of Ability, Benevolence and Integrity have been identified and are

considered reliable antecedents that lead to the development of trust between

members of a newly forming work-team. Previous studies have similarly identified

Ability Benevolence and Integrity as trust antecedents. Mayer & Davis (1999) found

that Ability, Benevolence and Integrity were positively correlated with trust in

management. Tan & Tan (2000) identified that Ability, Benevolence, and Integrity

were positively associated with an employee’s Intention to Trust their supervisor. In

addition, Serva et al. (2005) identified the positive relationship that the antecedents

of Ability, Benevolence and Integrity have in the development of our Intention to

Trust work teams. Similarly, Ability, Benevolence and Integrity are considered

antecedents of our Intention to Trust (Figure 4). Therefore, it is hypothesised that:

H1: Benevolence and Integrity and Ability will be positively associated

with our Intention to Trust members of a newly forming work-team.

29

Figure 4: A proposed model of the antecedents of trust – Ability, Benevolence and Integrity

2.2 Chapter Two Summary

This literature review has revealed the many facets of trust that sparkle from the

disparate views of the scientific disciplines. In the work-team context of this study,

the non-exhaustive list of trust types was explained and exampled. Instead of

accepting the perspective of a particular scientific discipline, distillation of the

differing views revealed six core themes that are considered the essence of trust.

These themes are risk, context, dynamics, expectation, principles, and, competence.

These themes and the study hypotheses are the focus for refining the study model.

Antecedentsof Trust

Ability

Integrity

Benevolence

Intentionto Trust

+

+

+

Antecedentsof Trust

Ability

Integrity

Benevolence

Intentionto Trust

+

+

+

31

Chapter Three

3.1 Refining the Study Model

A study model of the formation of trust between members of a newly forming work-

team needs to consider all six themes identified from the literature review in Chapter

Two. A researcher could take two approaches to defining the study model. One

approach is to develop a completely new model. This is not the preferred approach of

this researcher. Leveraging from previous research effort provides a solid foundation

for ongoing research and offers a more plausible foundation upon which to build our

knowledge of trust and develop our understanding of how to refine trust-related

research designs, test instruments and analysis methods. A number of existing trust-

models incorporate some or all of the trust antecedents and themes identified in

Chapter Two. Firstly, a literature review by McKnight et al. (1998) proposed a model

for examining how trust is formed in new organizational relationships (Figure 5).

Figure 5: McKnight et al's. (1998) model of initial trust formation

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32

Reflecting on the themes and antecedents identified earlier, the model incorporates

the factors of ‘principles’ (Benevolence), ‘competence’ (Ability) and the factor

‘honesty’ (honesty is commonly viewed as a reflection of our or an organization’s

Integrity (Becker, 1998; Sackett & Wanek, 1996; Wanek, 1996). The model also

recognizes our Propensity to Trust. McKnight et al. (1998) termed this factor

‘disposition to trust’. Their model also incorporates the cognitive processes involved

in trusting decisions and in consideration of context it incorporates the notion of

‘institution-based trust’ discussed earlier in this thesis. However, the McKnight et al.

(1998) model appears to view trust in stasis. It has been identified that we do not live

in a vacuum, trust is dynamic. The changing information that informs us about our

changing environment predicates that our trust state must alter. As we constantly

receive feedback, the new information that emerges from our numerous daily trust

experiences. The McKnight et al. (1998) model ill-considers the dynamic nature of

trust and the feedback that emerges from the numerous contextual situations in which

we find ourselves.

One could expect that this feedback is not restricted to the ‘institution-based trust’

context recognized in the McKnight et al. (1998) model; feedback emerges from all

the contexts, situations, where we extend trust. For example, if we were in a

professional-trust situation where we took advice from one of our peers and as a

result lost our job, it would be a natural reaction to be more cautious next time we

took advice, not just from a professional peer but in any situation, even a person one,

where we had similar stakes at risk. The McKnight et al. (1998) model restricts

consideration to institutions, those societal-based support systems such as

governments. As a theoretical foundation for this study, the McKnight et al. (1998)

model is deficient in that it inadequately considers context and the dynamic role that

feedback plays in our ongoing decisions to extend trust to others.

Alternatively, the earlier work of Mayer et al. (1995) includes all trust themes in the

McKnight et al. (1998) model as well as their missing feedback theme. There is ten

years of research based on the Mayer et al. (1995) integrative model of

organizational trust (Figure 6) (Bell, Oppenheimer, & Bastien, 2002; Cardona &

Elola, 2003; Costa et al., 2001; Davis, 1999; Davis et al., 2000; Franta, 2000; Gill et

al., 2005; Kiffin-Petersen & Cordery, 2003; Klein, Lim, Saltz, & Mayer, 2004;

33

Mayer, 1998; Mayer & Davis, 1999; Mayer & Gavin, 2005; Schoorman et al., 1996a,

1996b; Serva et al., 2005; Tan & Tan, 2000).

Figure 6: Integrative model of organizational trust (Mayer et al., 1995, p. 715)

In explaining the dynamic nature of our dyadic trusting inter-relationships, the Mayer

et al. (1995) model incorporates a feedback loop which emerges from the trustor’s

outcome evaluation, whether the behaviour of the trustee met the expectations of the

trustor. If a trustee’s behaviour was acceptable, we could risk extending trust on

another occasion. Alternatively, if the trustee’s behaviour did not meet our

expectations, it would be reasonable for us to expect that extending trust to the same

trustee again will have a high probability of a similarly unacceptable outcome. In

such situations, it would be normal for us to decide that it is too risky to extend trust

to that person, group or organisation, in the future. The Mayer et al. (1995) model

considers the dynamic nature of our trusting relationships by incorporating a

feedback factor.

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34

To review the competing models, the McKnight et al. (1998) model (Figure 5) and

the Mayer et al. (1995) model (Figure 6) have similarities. The factors of perceived

trustworthiness, the trust antecedents of Ability, Benevolence, and Integrity from the

Mayer et al. (1995) are consistent with the trust antecedents of Competence (Ability),

Benevolence, Honesty (Integrity) in the McKnight et al. (1998) model. Both models

consider our innate Propensity to Trust (Mayer et al., 1995); McKnight et al. (1998)

terms this our Disposition to Trust. Additionally, both models consider Risk,

McKnight et al. (1998) in terms of Predictability. Mayer et al. (1995) go further by

identifying the dynamic role that feedback plays when we make a decision to extend

trust in a particular relationship or situation. While both models incorporate five of

the six trust-themes that emerged from the review of literature, Context, Risk,

Ability, Benevolence and Integrity, only the Mayer et al. (1995) model adequately

considers the dynamic effect of the feedback we receive from our trusting inter-

relationships.

While the Mayer et al. (1995) model includes feedback from our trusting episodes, it

is argued that it inadequately considers the contextual difference in our trusting

episodes. Wekselberg (1996) criticises the Mayer et al. (1995) model because it fails

to adequately consider that the social context in which a trusting episodes occurs can

have an important impact on how we trust. In countering this criticism, Schoorman

et al. (1996b) assert that none of the variables in their dyadic model needs to change;

the model merely needs the addition of moderators or mediators to adjust for context.

In support of Schoorman’s (1996b) assertion, a plethora of supportive results, from

differing contextual situations, attest to the Schoorman et al. (1996b) affirmation that

the trust antecedents of Ability, Benevolence, and Integrity do provide a solid

foundation for the study of trust development (Bell et al., 2002; Cardona & Elola,

2003; Costa et al., 2001; Davis, 1999; Davis et al., 2000; Franta, 2000; Gill et al.,

2005; Jarvenpaa, Knoll, & Leidner, 1998; Kiffin-Petersen & Cordery, 2003; Martin,

1999; Mayer & Davis, 1999; Mayer & Gavin, 2005; Ridings, Gefen, & Arinze, 2002;

Schoorman et al., 1996a; Serva et al., 2005; Tan & Tan, 2000).

Given the significant level of scientific support for the Mayer et al. (1995) integrative

model of organizational trust, it has been selected to form the theoretical foundation

for this study. However, in consideration of the significant evidence (Bigley &

35

Pearce, 1998; Currall & Inkpen, 2002; Kiffin-Petersen & Cordery, 2003; McKnight

et al., 1998; Rousseau et al., 1998; Schoorman et al., 1996b; Serva et al., 2005) that

trust studies should be not undertaken without adequately considering the context in

which the trust takes place, an extra dimension has been added to the trust

antecedents in the Mayer et al. (1995) model.

The extra dimension added to the Mayer et al. (1995) model addresses the dynamics

associated with initial trust development in the context of this study, newly forming

work-teams. This addition addresses the concerns of Williams (2001, p.379) who

states that while ‘current models clarify many of the processes that are fundamental

to interpersonal trust development,(sic) they do not jointly address both the cognitive

and the affective influences of social group membership on trust’. In the context of

this study, a potential team member would cognitively assess what they know about

team members before making a decision to join the team. This is as far as this cross-

sectional study goes; it does not proceed into the dynamic life of the team wherein

ongoing feedback may bring about affective changes in the trust of fellow team

members. This is not to say that the affective factor of feedback should not be

included in the model for future studies; particularly those longitudinal studies that

expose trustors and trustees to multiple trusting episodes over time. Given the cross-

sectional nature of this study, and the single trusting context of a new member

making the decision to join a newly formed work-team, the affective factor of

feedback will not be included in the model for this particular study.

What has been included in this study is a context moderation factor that incorporates

the different types of information we could expect to receive about the members of a

new team we were considering to join. For example, if asked to join a team of

students working on an assignment, we would seek information about their

knowledge (Ability), whether they complied with university rules about plagiarism

(Integrity), and whether they looked after the best interests of fellow team members

(Benevolence). Some students do work to a high standard, others to a lower standard.

Thus, there are levels of information that could be communicated concerning a work-

team’s Ability, Benevolence, or Integrity. The question is how to operationalise

antecedent information levels.

36

In seeking to clarify the relationship between trust and its antecedents, Kramer &

Cook (2004) propose numerous contextual moderators of the trust antecedents,

Situational Strength among them. Gill et al. (2005) defined Situational Strength as

the quantity and type of information about the trustee available to the trustor prior to

the trustor extending trust to the trustee in a given situation. For example, a trustor

may be informed that a team is highly skilled and experienced. Perceiving a team

with high levels of Ability, the trustor may have Intention to Trust the team in the

expectation of an acceptable outcome. Alternatively, if the trustor is advised that the

team have low Ability, the trustor may choose not to trust the team. Gill et al. (2005)

incorporated a Situational Strength factor into their study by providing levels of

information about a trustee’s Ability, Benevolence, and Integrity; they termed the

levels Strong, Weak and Ambiguous (Figure 7).

Figure 7: Example dimensions of Situational Strength; adapted from (Gill et al., 2005)

In the (Gill et al., 2005) study, when all the antecedent information was bad (Low),

the situation was viewed as Weak and when there was a mix of good (High) and bad

(Low) information, the situation was seen as Ambiguous. When the trustor

considered all the information about the trustee was good (High), the situation was

termed Strong. The Gill et al. (2005) notion of Situational Strength is flawed because

a situation where all the trust antecedent information is bad could also be considered

as strong, strongly negative. It is argued that we would be ambivalent about

IntegrityBenevolenceAbility

Situational Strength(Moderator)

Weak

Ambiguous

Strong

LowHighLowHighLowHigh

IntegrityBenevolenceAbility

Situational Strength(Moderator)

Weak

Ambiguous

Strong

LowHighLowHighLowHigh

37

ambiguous information. We humans naturally focus on marginal differences when

we make decisions {Easterlin, 2005 #960}). In the context of this study, we would

focus on the margin of the trust information, the good or bad information we assess

when making a decision to join a work-team.

Therefore, unlike the Gill et al. (2005) study, it is asserted that under normal

circumstances a trustor would consider the marginal Information Level about a

trustee on two dimensions; good (High) and bad (Low) (Figure 8). For this study, the

terms of good and bad will be avoided because goodness or badness is in the eye of

the beholder, what some consider good, may be considered bad by others with

different values and beliefs. Instead, the notion of High and Low Information Level

is applied.

Figure 8: The proposed Information Levels of the trust antecedents

Let us view some examples of High and Low Information Levels. A person who

always looks after the best interests of their fellow team members could be seen to

exhibit High Benevolence. The same person could possess fewer skills and therefore

be considered to have Low Ability. While having fewer skills, if we viewed this

person as an honest person, they would attribute them with High Integrity. In this

way, the antecedents of trust have varying information levels that affect our personal

decision to trust. Therefore, it is offered that under a context where we can choose to

join a newly forming work-team, we would rationally consider {van Praag, 1999

#961} the marginal difference in the trust-related information communicated about

the teams. Based our cognitive assessment of the marginal difference, the level of

information, we would make our decision to extend trust and join the work-team, or

IntegrityBenevolenceAbilityInformation Level

Low

High


Low

High

38

vice versa. Therefore it is proposed to incorporate High and Low Information Levels

into the Mayer et al. (1995) Integrative Model of Organisational Trust (Figure 9).

Figure 9: The proposed theoretical model for the study of how the antecedents of trust affect our Intention to Trust in the context of newly forming work-teams

Figure 9 identifies the theoretical model for this study. In selecting formal definitions

for the factors in the study model, consideration of the competing definitions of trust

has identified that the Mayer et al.'s (1995) trust theory incorporates the six themes of

trust distilled from the review of the literature (Chapter 2). Therefore, this research

will build on the previous work of Mayer et al. (1995) and others who have

subsequently sought to advance the integrative model of organisational trust.

Consistent with their research, the definition of Intention to Trust applied to this

study is:

Ability

Benevolence Trustor’s Intention To Trust

Integrity

Antecedent Factors of the

Trustee

Contextual

Information Level

+

+

+

Ability

Benevolence Trustor’s Intention To Trust

Integrity


Trustee

Contextual

Information Level

+

+

+

39

‘the willingness of a party to be vulnerable to the actions of another

party based on the expectation that the other will perform a particular

action important to the trustor, irrespective of the Ability to monitor or

control that other party’ (Mayer et al., 1995, p. 712).

The trust antecedents are defined as:

Ability is ‘the skills competencies and characteristics that enable a party to have

influence over some specific domain’ (Mayer et al., 1995, p. 717)

Benevolence is ‘the extent to which a trustee is believed to want to do good to the

trustor’ (Mayer et al., 1995, p. 718).

Integrity is ‘the trustor’s perception that the trustee adheres to a set of principles

that the trustor finds acceptable’ (Mayer et al., 1995, p. 719).

In consideration of the proposition that the level of information about a trustee

affects our Intention to Trust, this study contributes Information Level which is

defined as the dimensional combinations (High to Low) of the good or bad

information communicated to a trustor about the Ability, Benevolence and

Integrity of a trustee prior to the trustor initially extending trust to that trustee.

3.2 Chapter Three Summary

Chapter 3 compared and contrasted two competing models to develop the study

model of initial trust formation between a potential team member and a newly

forming work-team. In doing so, it was shown that the kernel of the McKnight et al.

(1998) model was similar to the Mayer et al. (1995) integrative model of

organisational trust but that the McKnight et al. (1998) model failed to adequately

consider the role that the themes of Context and Dynamics play in the formation and

development of our Intention to Trust. It was identified that the Mayer et al. (1995)

model better addressed Dynamics by incorporating a Feedback loop which informs

the trustor about the probability of success or risk in future trusting episodes.

However, the Mayer et al. (1995) model inadequately considered the context in

40

which trusting episodes occur. In consideration of the varying levels of the good or

bad information that feeds back to a trustor after extending trust to a trustee, a High

and Low Information Level was incorporated into the study model and model

variables were subsequently defined in preparation for hypotheses development.

41

Chapter Four

4.1 Further Developing the Hypotheses for this Stud y

One thing becomes apparent from a review of the literature and the selection of a

study model; scholars operationalise trust differently depending upon the focus and

phase of the trust study. On the one hand, trust could be operationalised as a single

phase; a one-off transaction that is typically derived from a weighed calculus of how

much we think we will gain and lose (Williamson, 1975). On the other hand, we

have an ‘intra- or interpersonal trust continuum’ (Rousseau et al., 1998, p. 395) that

operationalises trust as an ongoing relationship where we question not "How much

do I trust?" but "In what areas and in what ways do I trust?" (Lewicki, McAllister,

& Bies, 1998, p. 443). While it is acknowledged that some ongoing relations are

transactional, with a focus on gains and losses, Rousseau et al. (1998, p. 398) remind

us that ‘both history and the nature of the interaction between the parties can shape

the form that trust takes’. This study operationalises the theoretical model identified

in Figure 9 of Chapter Three and focuses on the contextual situation where the new

team member (trustor) and the newly formed work-team (trustee) are unknown to

one another. In this context, the trustor needs to cognitively assess how the High and

Low Information Levels of information about the trustee affect their decision to

initially extend trust to the trustee.

Prior to the trustor having any information about the trustee, it has been argued that a

trustor’s Propensity to Trust should be most salient. Our Propensity to Trust is our

‘general willingness to trust others’ (Mayer et al., 1995, p. 715). Propensity to Trust

is that level of trust we extend before we have any information about the trustee, akin

to our innate or natural trust (Raths, 1972). The information or feedback that we

receive from our relationships and interactions with others readjusts our trust

perception. Considerable research effort has identified that, once we receive

information about a trustee, our Propensity to Trust wanes in favour of or Intention to

Trust (Costa, 2003; Costa et al., 2001; Gill et al., 2005; Huff & Kelley, 2003; Mayer

& Davis, 1999; Serva et al., 2005; Tan & Tan, 2000). Because considerable research

effort has previously been applied to understanding Propensity to Trust, this study

42

focuses on how we cognitively determine our Intention to Trust in the context of a

trustor receiving initial information about a trustee.

So what happens when we initially receive information about a trustee, which trust-

antecedents most affect our Intention to Trust? Table 1 identifies results from a

recent study by Serva et al. (2005). This longitudinal study was conducted in the

setting of two interacting teams developing software for a website. What is

interesting about this study is that the dynamic nature of trust that was revealed via

the changing correlation of Intention to Trust (ITT) with its antecedents. At Time T1,

the forming stage of team development when the management team communicated

functional requirements to the development team, the trust antecedents of Ability (r

= .70, p = .001), Benevolence (r = .51, p = .05) and Integrity (r = .62, p = .001)

correlated with Intention to Trust. At Time T2, the antecedent data from the previous

time, T1, no longer significantly correlated with ITT. Similarly, at Time T3, the

antecedent data from the previous time, T2, no longer significantly correlated with

ITT. The Intention to Trust of the teams had changed over time. Depending on the

stage of team development, the antecedents appeared to have varying effects on trust.

43

Table 1: Research results from a recent study by Serva et al. (2005)

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44

This is not surprising because there has been scholarly disagreement over the relative

strength of the relationship between trust and its antecedents. In 1999, Davis found

that Integrity (r = .818, p = .01) had the strongest relationship with Intention to Trust.

More recently, Gill et al. (2005, p. 99) proposed that ‘it is possible that Ability,

Benevolence, and Integrity contribute differently to the establishment of trust’. The

results of the Serva et al. (2005) study supports this proposition but, unlike this study,

their research did not measure trust and its antecedents in the pre-stage. This study

seeks to address the gap in the Serva et al. (2005) study by clarifying our

understanding of how the trust antecedents affect our Intention to Trust during the

pre-stage of the life of a work-team. Just as the effect of the trust antecedents differed

in the later stages of team development, it is hypothesised that:

H2: At the pre-stage of team development, the trust antecedents of

Ability Benevolence and Integrity will have differential effects on our

Intention to Trust members of a newly forming work-team.

Pursuing this hypothesis avails us of an opportunity to better understand trust by both

clarifying and the contributing to our current knowledge of trust development in the

context of newly forming work-teams. As a person with an opportunity to join a

newly forming work-team, we would seek information about the other group

members. How competent (Ability) are they? Will they lie (Integrity) and get me into

trouble with authority? In addition, will they do what is in my best interests

(Benevolence)? From the perspective of Ability, it would be easy for us to gauge the

knowledge of team-members; we could simply assess physical examples from their

previous work assignments; reports, products or perhaps customer feedback. A team

member devoid of the necessary skills and experience would not normally be able to

produce examples of previously completed quality work.

While manifestations of Ability would be physically obvious, it would be more

difficult to gauge the Integrity or Benevolence of other team members. Benevolent

behaviour would be less obvious than Integrity because issues of Integrity should

emerge during the employee hiring process. If we exhibit low Integrity behaviour by

lying and deceiving our peers we may get away with it on the first or perhaps the

second occasion, but it would be reasonable to assume that our peers would be less

45

likely to trust us after each additional episode of low Integrity behaviour.

Deceitfulness and dishonesty are memorable events (Arvey & Wanek, 2006); our

honesty image reflects our honest and dishonest behaviours and these are highly

visible to others (Van Iddekinge, Taylor, & Eidson Jr., 2005). We can all recall

episodes where someone has disappointed us when they do not do what they say they

will do. Because humans tend to have a behavioural trait towards trustworthiness

(Rotter, 1980), if we were contacted by an employer checking on the credentials of a

person previously in our employ, most of us would truthfully inform the new

employer if our past employee had exhibited low Integrity behaviour (Bulmash,

2006). Therefore, we would be more likely to find out about episodes of Low

Integrity.

Identifying Benevolent behaviour would be more difficult. For example, we first

need to extend trust to a person, group or organisation and wait for the feedback that

informs us that they have, or have not, behaved in our best interest (Benevolence).

This takes time. For example, when we first meet a new member of a work-team, we

have not previously trusted them; we have not received feedback from a previous

trusting episode. We could ask other people who had worked with them, but, with so

many of today’s teams comprising temporary, part-time or contract staff, we may not

have the opportunity to gather the information we need to adjudge other team

member’s Benevolence. They are strangers to us. Therefore, it is hypothesised that:

H3: Ability will have a more salient effect on our Intention to Trust

members of a newly forming work-team than Integrity and

Benevolence.

46

4.2 Chapter Four Summary

Chapter Four applied the study model to the context of a member making a decision

to extend trust by joining a newly forming work-team. At this stage of trust

development, the feedback that informs us that the trustee performed as we expected

has not come into play because we have not yet shared a trusting episode. Before we

make a decision to join a team we would request information about the Ability,

Benevolence and Integrity of the other team members. In seeking to understand

which of these factors is most salient in the development or our Intention to Trust,

previous studies have provided different results. There is scholarly disagreement over

which antecedent of trust is most important in trust development between members

of a team. In the context of this study, it was hypothesised that the salience of the

antecedents of our Intention to Trust is Ability, Integrity then Benevolence. The

research design is now justified.

47

Chapter Five

5.1 The Research Design

The research design is the plan that structures the investigation to obtain answers to

the research questions (Punch, 2000). Holistically, this research is to be conducted in

three stages (Figure 10).

Figure 10: The Three study Stages

To gain an understanding of the study setting and to collect data to assist with the

development of the scales and the vignette manipulation, the Vignette Development,

Stage 1, involved structured interviews. Additionally, descriptive statistics from

similar trust-related studies were applied to identify typical effect sizes that were

used to estimate sample size requirements for the subsequent study stages. The Pilot

Stage 2 pre-tested the vignettes, experimental manipulations, and measurement

scales on a sample frame from the population. The Final Data Collection stage

applied the refined scales and vignettes to collect data for final analysis. The

following pages seek to justify and define the research design choices for the study

setting, the type of measures, the unit of analysis, the time horizon, and, the research

paradigm (Cavana, Sekaran, & Delahaye, 2001, pp. 285-382).

Study Stage 1 Study Stage 2 Study Stage 3

Vignette Development• Qualitative• Structured Interview• Thematic analysis• n = 20• Vignette content• Effect size

Pilot• Quantitative• Questionnaire• Manipulation questionnaire• n = 187• Refine vignette & measures

Final Data Collection• Quantitative• Questionnaire• Manipulation questionnaire• n = 224• Data analysis





48

5.1.1 The Research Paradigm Past trust studies have applied qualitative methods of action research (Levin et al.,

2002) and the quantitative methods of field experiment (Costa et al., 2001;

Korsgaard et al., 2002; Mayer & Davis, 1999; Schoorman et al., 1996b; Serva et al.,

2005; Tan & Tan, 2000; Whitener, 2001 ; Wong, Wong et al., 2002). Fewer studies

used laboratory experiments (Buchan et al., 2002; Earley, 1986; Gill et al., 2005).

While practitioners can gain increased understanding and benefit from the more

generalisable field studies (Sekaran, 2003), to maintain rigour this study seeks to

exclude the numerous confounding factors that could possibly affect trust

development in a typical work environment. For example, in a field study, our trust

with other employees could emerge from our work interactions or that trust could

arise from the social contact we have with them as friends, outside of work hours.

Laboratory experiments generally have higher internal validity than field studies

because the researcher seeks tighter control by excluding these confounding influences

that can potentially contaminate study results (Christensen, 2004, pp. 5-26). This study

mandates high internal validity because it seeks theory development by clarifying our

understanding of trust by validly testing Intention to Trust behaviour with its

antecedents. Sekaran (2003) supports a decision to select a laboratory experiment

strategy for this type of study because it seeks to understand relationship and

possibly causal effects while maintaining high internal validity.

5.1.2 Time Horizon This experimental research design seeks constancy and control wherein a comparison

is produced between two or more levels of the independent variable (IV) while all

other aspects of the experimental situation are held constant (Kantowitz, Roediger, &

Elmes, 1994). Causality is often only accepted in a longitudinally designed study that

measures pre and post effects of an experimental IV manipulation on a dependent

variable (DV); the dimension of change over time must be invoked (Cavana et al.,

2001). This cross-sectional designed experiment, that collects data at a single point in

time, does not claim causation but does seek strong relationship evidence by

applying Structural Equation Modelling (SEM) and Analysis of Variance (ANOVA)

analysis techniques. Causation based on SEM analysis is not claimed, even though

Bollen (1989b, pp. 40-79) argues that analysis techniques such as Structural Equation

49

Modelling satisfy the causation requirements for isolation, association and direction

of causality. Even if all influences on the DV are excluded except the manipulation

of the IV variable, pragmatically, it is almost impossible to have absolute certainty

that a change in one variable is only caused by another; extraneous factors can

confound results.

Previous trust research may have not isolated the extraneous factors that can

confound results. For example, the field research by Serva et al. (2005) had similar

objectives to this study in a setting involving university students working in groups.

While the development of trust was clearly observed, why and how that trust

developed was opaquely explained. Did trust emerge from the day-to-day

interactions between the workgroup members? Perhaps the trust emerged, at some

other time, from social activities outside of the university context. Perhaps trust was

evident prior to the experiment. Isolation of extraneous effects is at question. While

this cross-sectional designed research does not claim causation, it seeks to clarify our

understanding of how to develop trust in newly forming work-teams by satisfying the

need for isolation, association and direction of causation. The research design path

leads towards Structured Equation Modelling and ANOVA of the final data to

strengthen claims for, but not necessarily prove, causation. The experimental

methodology, the Analysis of Variance and SEM analysis techniques designed into

this study seek to isolate and exclude extraneous variables to identify the association

between the antecedents of trust and directionally depict how these exogenous

factors relate to our Intention to Trust in a study setting of a newly forming work-

team.

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5.1.3 The Study Setting This research seeks to build on the effort and knowledge derived from similar trust

studies (Costa et al., 2001; Kiffin-Petersen & Cordery, 2003; Gill et al., 2005; Mayer

& Gavin, 2005; Serva et al., 2005) by more clearly identifying how trust develops

between members of a work-team in the pre-stage of development. In examining

trust development, a university is considered a suitable study setting because

university students need to regularly form new work-teams in order to complete their

group-based assessments. Like the increasing number of part-time and temporary

employees that are populating today’s business and government organisations, the

success of a university student often depends upon their decision to join, or not to

join, a particular work-team. Their individual success or failure is a function of the

combined efforts of their team members (Spreitzer et al., 1999). If the work-team

performs well, all team-members are rewarded as high performers. In the case of the

part-time employee, they could be rewarded with a pay rise, bonus or perhaps the

offer of additional work. On the other hand, if a hard-working team-member, with

high achievement expectations, chooses to join an underperforming work-team, there

is a risk of failure and under-achievement; loss of expected reward. When a student,

or part-time worker, needs to choose a work-team, they need to select a group that is

most likely to satisfy their expectations.

While this expectation of success is synonymous with that of permanent employees,

there is one important difference between a newly forming work-team drawn from

fulltime employees and those drawn from a temporary/part-time workforce or a

student population. The students and part-timers have not been previously socialised,

they do not know one another; they have no shared previous work experiences. Over

time, permanent employees develop shared values and beliefs, the basis for the

integrity antecedent of trust (Rotter, 1967). Similarly, permanent employees have

probably seen the quality of their colleagues’ work and are therefore in a better

position to judge whether the skills and abilities of those colleagues. At the same

time, permanent employees would have received feedback from their work

colleagues about which staff make good team members, can be relied upon to do the

right thing by the team and treat other team members decently. This is the basis for

Benevolence.

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Thus, permanent employees are in a better position to make decisions on whether to

extend trust to work colleagues because they have priori information about the

ability, benevolence and integrity of potential team members. This is not the case

with temporary/part-time employees or students in a university. In a population of

containing thousands of students and hundreds of thousands of part-time workers, the

probability that a student or part-time worker has worked with potential team

members would be low; they would not have the benefit of the a priori information

that we applied when deciding whether to extend trust. Therefore, with the context of

a student population analogous to a temporary/part-time workforce, a university

setting containing students that have not shared work-team experience is considered

an appropriate study setting for this research.

The study setting of a student who needs to choose a work-team satisfies the

theoretical foundation (Mayer et al., 1995) for this study; notions of competence,

expectation, principles, risk and trust identified earlier as integral to trust formation

are involved in the dyadic relationship between the student and the work-team. The

student’s grade expectations are at risk if they choose a group with low competence

(Ability). As trustor, the student expects to benefit (Benevolence) from a work-team

relationship wherein principled members of the group meet their commitments by

truthfully (Integrity) delivering work when it is due and to the agreed standard.

Therefore, the study setting reflects the theoretical foundation for this study. The

antecedents of Ability, Benevolence and Integrity are present within the context of a

student’s cognitive assessment of their Intention to Trust members of a newly

forming work-team. In the group-assessment context of this study, a student needs to

think carefully about the team they will join because all team members will receive

the same grade for their work-team’s assignment submission. The choice of a

Business Faculty Undergraduate Student population of an Australian university fits

the theoretical foundation for this study and satisfies the need to engage in a simpler

experimental design. The selection of a student population also has the advantage of

reducing data collection effort. Sampling students in their scheduled lectures and

tutorials is convenient, less disruptive to teaching, and involves little additional cost

to the students or the researcher.

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Population It has been identified that the study setting of university students undertaking group-

based assessment is an appropriate study setting and it naturally follows that students

within that setting are the appropriate population. The sampling frame was selected

from the Business Faculty Undergraduate Student population of a metropolitan

Australian university. Similarly, university student populations from North America

were recently sampled to provide data for similar trust-related studies (Gill et al.,

2005; Serva et al., 2005; Williams, 2001). In particular, this research seeks to address

the gap in the research by focussing the pre-stage of group development, the stage

not addressed by Serva et al. (2005). Both this and the Serva et al. (2005) research

draw on samples from a population of university students.

5.1.4 Sampling Strategy The sampling strategy seeks a representative sample with parameters reflective of a

normally distributed university undergraduate student population. The students who

volunteer to participate in the study will do so without compensatory reward. The

sampling process (Tilley, 2004) will seek subjects who satisfy the parameters of

interest to the study; students without previous shared teamwork experience. Because

all students from the population of the Business Faculty satisfy this requirement, a

number of sampling frames will be drawn from first and second year subjects. While

it would be optimal to pursue a probability sampling method involving

randomisation wherein each person from the 15,000 member population had a

known and equal chance (Cavana et al., 2001, p. 257) of selection, this is logistically

impossible; instead, the subjects will self-select by voluntarily responding to a

request to complete a questionnaire. Randomisation will emerge from each subject

randomly receiving one of a number of questionnaires incorporating a manipulation

that communicates a different Information Level about the Ability, Benevolence or

Integrity of a work-team that they could choose to join.

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5.1.5 The Manipulation To explain and enhance our understanding of how combinations of the antecedents

of trust relate to our Intention to Trust, subjects will be exposed to combinations of

High and Low Information Levels of the Ability, Benevolence or Integrity describing

the group they could choose to join. This intervention is required to facilitate

examination and assessment of the treatment effects and relationships that are

expected to result from the manipulation of the independent variables (IV) on the

dependent variable (DV) (Cavana et al., 2001, pp. 269-269). Previous trust related

studies applied various manipulation techniques. These included the change of a

human resource system (Mayer & Davis, 1999), an in-basket task (Earley, 1986),

teams interaction during a software development project (Serva et al., 2005), and,

the use of vignettes (Gill et al., 2005).

Manipulation using vignettes is considered an unobtrusive measure. Kerlinger

defines vignettes as, ‘brief concrete descriptions of realistic situations so constructed

that responses to them will yield measures of variables’ (1986, p. 475). Vignettes are

considered appropriate for this study because they facilitate a low cost method

(Hughes & Huby, 2004) and ‘make it easier to manipulate variables’ (Gliner, Haber,

& Weise, 1999, p. 314). Information portrayed in a vignette is generally less

ambiguous than real-life situations; there are fewer interfering influences to

confound an experiment and the result is stronger signal strength. In the case of this

study, the IV effect of Ability, Benevolence and Integrity on Intention to Trust could

be perceived as a stronger relationship than would otherwise be the case. A study by

Murphy, Herr, Lockhart and Maguire (Murphy, Herr, Lockhart, & Maguire, 1986)

comparing vignette and behavioral observation identified that the signal strength was

indeed amplified when using vignettes; the mean was 30% higher and the standard

deviation was 60% higher. In this study, we propose to use this enhanced signal

strength to our advantage. With higher mean scores, we expect an amplified

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relationship between Intention to Trust and its antecedents. As a result, our analysis

of the data should detect smaller and more significant relationships between the

variables than would be the case with alternative manipulation methods.

A vignette also simplifies manipulation in low budget research like this study, the

sampling and manipulation costs are low for both the researcher and the subject(s).

There are no additional costs involved in organising the subjects; the data will be

collected in the student’s normal lecture or tutorial setting. After reading the vignette

manipulation, the anonymous subjects are expected to complete the questionnaire in

less than ten minutes.

In an experiment, the manipulation process must remain under the systematic control

of the researcher (Christensen, 2004). Instrumentation effects that arise from

changing the measuring instruments can introduce confounding variables and

threaten the internal validity of a study (Sekaran, 2003). A common error in studies

applying a vignette manipulation method is to present respondents with multiple

vignettes followed by comparisons across vignettes; this invokes vignette response

fatigue wherein respondents tire, lose interest, and, the quality of results suffers

(Hughes & Huby, 2004). Responding to multiple vignettes also risks a carry over

effect from one vignette to another (Sniderman & Grob, 1996). Even if the order of

the vignettes is randomised issues with order, additive or interaction effects cannot

be overcome because of the logical order of the vignette narratives (O'Connor &

Hirsch, 1999). The simultaneous manipulation with multiple cases inextricably

confounds study results (Zellman, 1990). This study takes advantage of this vignette-

related limitation. To minimise the confounds that can contaminate experimental

55

results; each subjects will only be exposed to a single vignette. Depending upon the

quality of the vignettes (Hughes & Huby, 2004), the subjects are expected to

cognitively respond to a vignette that succinctly projects a single combination of the

trust antecedents. By exposing each subject to information describing just one work-

team, the limitations of vignette manipulation are expected to advantage this study.

The reasoning behind manipulating each subject with a single vignette has been

justified. This means that each subjects needs to respond to the questionnaire

subsequent to reading a single vignette that depicts one of a number of dimensional

combinations of the High or Low Information Levels concerning the Ability,

Benevolence or Integrity of a work-team they could choose to join. Therefore, these

dimensional combinations lead to an a priori 3x2 factorial design; six groups that are

defined by three (3) trust antecedents each depicted with two (2) Information Level

combinations, High or Low. Consistent with the literature (Gill et al., 2005), a High

Information Level will identify a High Ability work-team that exhibits a high level of

knowledge and competence. A Low Information Level is the opposite. Similarly,

High Benevolence information depicts a work-team that exhibits concern for other

team members and High Integrity information conveys a work-team with high

principles and values that, for example, does not resort to lying. Thus, it is initially

planned to expose each subject to a single manipulation projecting a combination of

a High or Low Information Level of all three of the Intention to Trust antecedents;

Ability, Benevolence and Integrity.

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Identifying the number of manipulation options or work-teams in a factorial design

study provides useful group information to assist with determining sample size

requirements (Cohen, 1977). This is important for a number of reasons. Firstly, the

magnitude of the effort involved in this experimental study revolves around the time-

consuming logistical exercise of data collection. The magnitude of that effort is

predicated on sample size requirements. Sample size is also considered important

because it impacts on the precision, reliability, internal validity and ultimately affects

how confident we are that the sample results truly reflect population parameters

(Cavana et al., 2001, pp. 272-273). Secondly, too small a sample size interacts with

the power of the statistical tests to negatively impact upon the probability of

achieving statistically significant results (Cohen, 1988). On the positive side, the use

of vignettes for this behavioral observation should amplify the signal strength by

increasing the means and standard deviations of the variables under test (Murphy et

al., 1986). Vignette manipulation should help to assist in minimizing the sample size

requirements of the analysis methods proposed for this study.

Based on a strategy of employing ANOVA-based statistical analysis, first and second

moment information, from recent trust-related research employing similar samples,

measures and analysis methods to this study, was used to identify an average effect

size of .75; at a significance level of p < .05 (Table 2). G*Power software (Buchner,

Erdfelder, & Faul, 1997; Paul & Erdfelder, 1992) was used to estimate the minimum

number of subjects for each group. For the proposed between-subjects ANOVA

analysis, a minimum of seven subjects were required to achieve the small-medium

effect size of .75 (Cohen, 1988). For an eight-group factorial design using ANOVA

analysis, computations identified that a minimum total sample size of 56 subjects

was required for the Pilot stage of this study.

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Table 2: Effect and sample size estimates calculations from similar trust-related studies

Example Study Total n n per Group

Mayer & Gavin (1999) trust PM v TMT 3.21 2.72 0.77 0.64 ANOVA 108 4 Assumptions:

Mayer & Gavin (1999) ability PM v TMT 3.45 2.94 0.82 0.62 ANOVA 135 5 power = 0.95

Mayer & Gavin (1999) benevolence PM v TMT 3.14 2.59 0.93 0.59 ANOVA 135 5 p = 0.05

Mayer & Gavin (1999) integrity PM v TMT 3.23 2.79 0.85 0.52 ANOVA 162 6 Groups= 27

Gill et al., 2005 high trust v total trust 6.33 4.73 1.68 0.95 ANOVA 81 3

Gill et al., 2005 total trust v low trust 4.73 2.79 1.68 1.15 ANOVA 81 3 d = 1

Mayer & Gavin (1999) trust PM v TMT 3.21 2.72 0.77 0.64 ANOVA 64 8 Assumptions:

Mayer & Gavin (1999) ability PM v TMT 3.45 2.94 0.82 0.62 ANOVA 72 9 power = 0.95

Mayer & Gavin (1999) benevolence PM v TMT 3.14 2.59 0.93 0.59 ANOVA 72 9 p = 0.05

Mayer & Gavin (1999) integrity PM v TMT 3.23 2.79 0.85 0.52 ANOVA 96 12 Groups= 8

Gill et al., 2005 high trust v total trust 6.33 4.73 1.68 0.95 ANOVA 40 5

Gill et al., 2005 total trust v low trust 4.73 2.79 1.68 1.15 ANOVA 32 4

Levels of the Study Variable

Mean (m1)

Mean (m2)

Standard Deviation

(sd)Effect Size

(d=(m1-m2)/sd)

Sample Size Estimates ex G*Power

Assumptions: Power = .95 alpha = .05

Number of Groups = 27

Assumptions: Power = .95 alpha = .05

Number of Groups = 8

Analytical Test

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Subsequent to the Pilot Stage, the research design proposed to enhance the analysis

method in Stage 3 by adding Structural Equation Modelling (SEM) analysis. This

required a review of the sample size requirements. A sample size for SEM is not

determined using G*Power, the number of subjects required for SEM is a function of

the complexity of the model under test.

SEM is a large sample analysis technique (Kelloway, 1998, p.20) and the adequacy

of the sample size can affect the parameter estimate significance (Joresborg, 1997).

The success of a study could be jeopardised if subject data is collected and the

Critical N (CN) results from the SEM analysis results identifies that the sample size

is insufficient to yield an adequate model fit (Hoelter, 1983). With studies like this

that employ models of a moderate complexity, a sample size minimum of 200 is

recommended (Kelloway, 1998, p. 20). Additionally, sample size can also be

considered adequate if it satisfies recommended guidelines for the sample size to the

estimated parameters ratio of at least 5:1 to 10:1 (Bentler & Chou, 1987). Using this

guideline and dummy data, the preliminary test of a moderate complexity SEM

model of Intention to Trust with ten variables and 20 parameters computed a (Critical

N) sample size requirement of 98 subjects. However, the above ratios of 5:1 and 10:1

indicate a need for 100 to 200 subjects. Consistent with the sample size used in

similar trust-related studies (Mayer & Gavin, 2005), a conservative decision was

made to seek 200 subjects for Stage 3 of this study. The next section identifies why

both the subject and the group are the units of analysis for this study.

5.1.6 The Unit of Analysis The analysis techniques used in studies based on the (Mayer et al., 1995) trust theory

have evolved from the earlier research that applied ANOVA and similar relationship-

based analysis techniques that used the group as the unit of analysis (Mayer & Davis,

1999; Schoorman et al., 1996a; Tan & Tan, 2000). More recent studies (Costa et al.,

2001; Mayer & Gavin, 2005; Serva et al., 2005) sought stronger relationship

evidence by applying the analysis techniques facilitated by Structured Equation

Modelling (SEM) software such as LISREL (Joresborg & Sorbom, 1996). Both

ANOVA and SEM analysis are to be employed in this study; ‘SEM is a statistical

methodology that takes a confirmatory (hypothesis-testing) approach to the

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multivariate analysis of a structural theory bearing on some phenomena’ (Byrne,

1998, p. 3). For SEM, the unit of analysis is the subject because the raw data from

the individual subject generates the observed covariance matrix that forms the basis

for model comparison.

While the unit of analysis for SEM analysis techniques is the subject, the unit of

analysis for the ANOVA analysis will be the groups that emerge from the (3 x 2)

factorial design that dimensionally depicts groups with combinations of High or Low

Information Levels of the trust antecedents of Ability, Benevolence, and Integrity

(Figure 11). The four corners, dimensional, distribution of variable-responses from

the factorial design used in this study should also help to satisfy the multivariate

normality requirement of SEM (Byrne, 1998; Rigdon, 2006). This is important

because multivariate normality is essential to maximizing SEM’s power to detect

both main and interaction effects (Cohen, Cohen, West, & Aiken, 2003). The next

section discusses the measures and addresses issues with scale development.

Figure 11: Initial 3x2 factorial design depicting Information Levels of Ability, Benevolence and

Integrity


Low

High


Low

High

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5.2 Issues in Scale Development

Suitable measurement instruments are required to generate the variable data required

for SEM analysis (Byrne, 1998, pp. 135-137). In the context of this study,

measurement instruments need to facilitate accurate observation and recording of

how the antecedents of Ability, Benevolence and Integrity relate to the development

of our Intention to Trust a newly forming work-team. In order to minimise construct

validity errors, valid and reliable measures are needed to ensure a scientific approach

to the experiment. Researchers should use instruments that fit the theoretical

framework of the experiment to be conducted (Christensen, 2004). Previous studies

have utilized a range of different scales to measure trust. Julian Rotter (1967)

developed a much-used 25 item Likert-type scale (Cavana et al., 2001, p. 205)

measuring interpersonal trust, which he theoretically defined as a generalized

expectancy that the verbal statements of others can be relied upon. As discussed in

the review of literature, Mayer integrative model of organisational trust is an

evolution of Rotter’s (1967) trust theory. The following is an example from the

original Rotter (1967) interpersonal trust scale:

Q1: In dealing with strangers one is better off to be cautious until

they have provided evidence that they are trustworthy.

When researchers applied the Rotter (1967) interpersonal trust scales issues of

reliability began to emerge (Fitzgerald, Pasewark, & Noah, 1970; Pasewark,

Fitzgerald, Sawyer, & Fossey, 1973). There were calls for further research to develop

testing instruments that provided better predictions than Rotter's (1967)

interpersonal trust scale (Wright & Tedeschi, 1975, p. 476). Low Cronbach Alpha

values for the Rotter (1967) measures were considered reflective of inter-item

consistency issues (Cavana et al., 2001, p. 211); did all the questionnaire items in the

scale focus on measuring just trust or were they measuring something else?

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The Schoorman et al. (1996a) study simplified the 25-item Rotter (1967) scale to

develop Propensity to Trust and the Intention to Trust scales that have been applied

to much of the research based on the Mayer et al. (1995) theory of integrative trust.

A Cronbach Alpha of .8 or above strongly indicated that the instruments employed in

the earlier studies were consistent measures (Sekaran, 2003, p. 327). While the trust

scales customised for the Schoorman et al. (1996a) study setting resulted in

acceptable to good Cronbach Alpha results, more recent studies that employed the

scales are again exhibiting issues with internal consistency (Table 3).

Table 3: Examples of the low Cronbach Alpha results for the trust scales from recent studies

Study

Propensity to Trust

Intention to Trust

(Schoorman et al., 1996a) .71 .82

(Mayer & Davis, 1999) .55 .59 (Kiffin-Petersen & Cordery, 2003) - .63

(Gill et al., 2005) .64 .70 (Serva et al., 2005) - .56

Cronbach Alpha measure of inter-item consistency reliability: > .8 = good; > .7 = acceptable; < .7 = low.

There was concern that idiosyncratic items in the scales were inducing random

measurement error and thereby reducing the likelihood of detecting relationships

(Nunnally & Bernstein, 1994, pp. 211-230). In seeking to resolve this issue, Serva et

al. (2005) cited Nunnally (1978) in recommending the lowering of reliability

standards to .60 for exploratory measures. The Ability, Benevolence, Integrity and

Intention to Trust scales proposed for in this research could hardly be considered

exploratory; over the past ten years they have been designed into numerous studies

based on the Mayer et al. (1995) integrative theory of organisational trust. Other

studies like those of Gillespie (2003), that use scales customised to the study setting,

appear not to exhibit issues with trust measurement; ‘All scales had acceptable

reliability, ranging from .83 to .95 (Cronbach Alpha)’ (Gillespie, 2003, p. 15). The

issue would appear to be scale-related, not the accepted standards for alpha

measurement of reliability. As a contribution to method, this three-stage study

pursues a scale development process that has the potential to result in much

improved trust scale reliability.

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While the scales can affect internal reliability, measurement issues can also emerge

from the number of items used to tap each factor. Multi-item measures, like stimuli

emerging from the questions used in an experiment, can detrimentally affect the

reliability of the measurement instrument and can reduce detected effects leading to

measurement error that ‘can obscure or attenuate the lawfulness of nature’

(Nunnally & Bernstein, 1994, p.240). Additionally, a large number of questions in a

questionnaire can fatigue the respondents leading to inaccuracy and incompletion

(Cavana et al., 2001, pp. 225-246). While the Confirmatory Factor Analysis used as

part of the SEM analysis allows exclusion of variables that do not sufficiently

explain a factor, to minimise questionnaire-induced fatigue it was decided that the

number of questions in each measurement instrument would be capped at twelve

items. In support of this decision, item selection examples from (Nunnally &

Bernstein, 1994, pp. 306-308) identify that, on average, increasing the number of

items above ten to twenty has minimal effect on improving scale reliability.

Reliability is critical to the internal validity of an experimental study (Winer, 1999)

and context is important when measuring trust (Child & Mollering, 2003). Rotter

(1967, p.37) reminds us that the psychological situation is extremely important

determinant of behaviour and depends not only on personal characteristics but also

on situational considerations that emerge from the context of a study. This is

particularly the case in trust studies like this that are based on theory that involves

trustor expectations; expectations that change depending upon the context in which

the trustor finds herself (Rotter, 1967, pp. 38-41). With respect to the Mayer-based

studies noted in Table 3; they were conducted in different contextual situations. In

the context of trust and empowerment in a veterinary clinic, the initial Schoorman et

al. (1996a) study exhibited good trust scale reliability. Using the same scales, the

Mayer & Davis (1999) study involved a field quasi-experiment measuring employee

trust in management. Similarly, the Gill et al. (2005) study used the same scales and

involved university students. Both exhibited less than acceptable trust scale

reliability (Table 3).

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To enhance scale reliability Tan & Tan (2000) measured trust in supervisor with a

scale developed by Gabarro & Athos (1976) and modified the scale to fit the context

by replacing the word employer with supervisor; the resulting Cronbach Alpha was

good; .93. Gillespie (2003) conducted two pilot studies to develop a reliable scale

that successfully measured trust in the context of a research facility; the scales were

customised to suit the context of the study. A decision was made to follow the

example of Tan & Tan (2000) and Gillespie (2003) and customise the scales to suit

the context of this study.

To begin, the scale customisation process sought to optimise the face validity of the

trust scales by phrasing the questionnaire items so they were easier for the subjects to

understand (Cavana et al., 2001, p. 214). The methodology in Study Stage 1 calls for

structured interviews with convenience-sampled subjects drawn from the Business

Faculty Undergraduate Student population of a metropolitan Australian university.

The transcripts from those interviews will be used to customise the questionnaire

items so that the subjects better identify with their content. The subsequent Pilot

Stage will pre-test the customised questionnaire items on a representative sample

from the population. The Final Stage will apply the updated scales to measure the

independent (IV) and dependent (DV) variables in the theorised study model. The

data collection plan is next considered.

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5.3 The Data Collection Plan

In preparation for refining the scales, the data collection plan calls for three stages of

data collection. It is normal for student workgroup formation to be initiated in

university lectures or tutorials. Because this scenario exactly fits the context for this

study, the Stage 1 data will be collected at the beginning of scheduled lectures or

tutorials. The study plan calls for the structured interviews to be conducted as the

students waited for their lecture to begin. This approach offers a convenient data

collection method that is ideal for quick response by student subjects. Additionally,

the succinct, easy to answer, structured questionnaires are expected to help maximise

subject participation. In an experiment, a questionnaire provides a low cost, promptly

answerable, test instrument that can be used to easily assess subjects’ attitudes.

In an experiment, threats to construct validity can come from the conduct of the

experimenter whilst conducting the experiment; this is known as the ‘experimenter

attribute’. Experimenter attribute refers to the physical or psychological

characteristics of the experimenter that may affect the independent variables due to

an unexpected change in behaviour of the subjects (Christensen, 2004). To minimise

these effects, the researcher should remain isolated from the subjects. Because

disruption of the subject’s normal behaviour and activities needs to be avoided, the

subjects will be to free to take, or not take, a questionnaire as they enter their

scheduled lecture or tutorial. Subjects will be given sufficient time to compete the

questionnaire in normal lecture time, prior to the lecture commencement. Instructions

on how to complete the questionnaires will be communicated using a single

PowerPoint (Microsoft, 2006) slide projected onto the lecture theatre screen. To

maintain anonymity, the subjects will place the completed questionnaires under their

seats; the questionnaires will be collected after all subjects have exited the room. The

data collection plan calls for the researcher to maintain a remote, arms length

relationship, isolated from the subjects throughout the study.

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5.4 Analytic Strategy

To review, this study incorporates three stages (Figure 12).

Figure 12: The Study Stages

The analysis method varies in each study stage. To develop measurement scales and

the vignettes, Stage 1 will involve thematic analysis of the transcripts from structured

interviews. To test and refine the vignettes and scales, the Stage 2 data is to be

analysed using the correlation and ANOVA-based techniques employed in earlier

studies based on the (Mayer et al., 1995) integrative model of organisational trust.

The results of Stage 2 analysis will be used to update the vignettes and scales. In

seeking to explain the direct and indirect effects of the antecedents on the

development of trust, Stage 3 data will be analysed using descriptive statistics,

ANOVA and SEM analysis techniques.









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5.5 Chapter Five Summary

Chapter Five has explained and justified the research design for this three stage

experimental study. The Vignette Development, Stage 1, will thematically analyse

the transcripts from structured interviews to identify the vignette and questionnaire

wording to be applied in the subsequent study stages. The Pilot Stage 2 will pre-test

the vignettes and questionnaires and refine them for the Final Data Collection Stage

3. The research design choices for study setting, the type of measures, the unit of

analysis, the time horizon, and, the research paradigm were defined and justified. In

the study context of newly forming work-teams, the appropriateness of a population

of Business Faculty Undergraduate Students from a metropolitan Australian

university was justified. The sampling design was justified in terms of the

randomised application of eight different vignette manipulations and the sample size

requirements were supported by calculations that considered the effect size evident in

similar trust-related studies and the planned ANOVA and SEM analysis techniques.

Finally, the data collection process was explained. The application of this research

design is next detailed for each Study Stage.

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Chapter Six

6.1 Methodological employment of the Research Desig n - the Three Study Stages

6.1.1 Analysis and Results for Study Stage1: Vignette Development Stage 1 sought to develop the vignettes that would be used to manipulate the levels

of Ability, Benevolence and Integrity as well as to customize the questionnaire items

to the study context (Figure 13).

Figure 13: Study Stage 1

The vignette development process involved the thematic analysis of structured

interviews. The thematic analysis of each structured interview did not seek to extend

or inform the current theoretical foundations for trust. The progressive thematic

analysis of each interview sought to classify the subject’s statements in terms of the

antecedents of trust; Ability, Benevolence and Integrity. The structured interviews

continued until no new themes emerged from the thematic analysis; this resulted in

twenty interviews. The specific goal of the thematic analysis was to identify

interviewee statements that could be included in the vignette text; because ‘vignettes

written in familiar speech are easier to understand’ (Elsbach & Elofson, 2000, p.

81). The use of familiar language positively influences a reader's comprehension

(Carpenter, Miyake, & Just, 1995) of vignettes.









68

To maximise the external validity of the vignettes (Gliner et al., 1999), the thematic

analysis sought to identify and formulate vignette content that satisfied the

informational and rationale requirements (Shapiro, Buttner, & Barry, 1994) that a

potential team member would normally use to fairly decide (Bies, Shapiro, &

Cummings, 1988) if they would join a newly forming work-team. Therefore, to make

the vignettes more believable, the subject’s statements were incorporated into the

vignettes used to manipulate the dimensions of the antecedents of Intention to Trust.

To begin vignette development, Undergraduate Student subjects from the Business

Faculty population of a metropolitan Australian university were convenience

sampled as they entered the main entrance of the Business Faculty building. The

nature of the study was not revealed to the subjects, the structured interview

technique sought to avoid projecting the purpose of the study and the attitude of the

researcher onto the subject. Consistent with the goal for Stage 1 of the study,

capturing the subject's attitudes towards group work was the stated goal of the

interview. Without reward, the anonymous subjects voluntarily agreed to participate,

or not participate, in the individual structured interview that initially confirmed they

were undergraduate students from the Business Faculty. Those who satisfied the

undergraduate student criterion and confirmed their previous experience with

working in teams on group assignments were considered suitable for Stage 1 of this

study. Those persons who did not meet the criterion were thanked and advised that

they did not satisfy the parameters of the study population of Undergraduate Student

from the Business Faculty of a metropolitan Australian university.

Having confirmed they were part of the target population, the subjects were cued by

asking them to ‘caste your mind back to your group assignment experiences where

all members of the group received the same grade’. This statement sought to

cognitively position the subjects ready to respond to the following three questions:

1. Do you consider there are risks associated with working on group

assignments?

This closed question (Cavana et al., 2001, p. 142) sought to confirm that the subject

perceived there was, or was not, risk associated with group work. Risk is a

69

theoretical foundation for trust, without risk in an interrelationship there is no need to

trust (Golembiewski & McConkie, 1975). Subjects who did not confirm there were

risks associated with group work would not need to extend trust to another and

therefore were considered unsuitable for this trust-measuring study. Interestingly, all

those who agreed to participate in a structured interview perceived risks with group

work; all subjects stated there was more to lose than gain. It would appear that

students might not like group assignments; perhaps this is a future research

opportunity.

Those subjects who perceived risks with group work were then asked the open-ended

question:

2. What were they?

The subjects were neither prompted nor interrupted; a remote position was

maintained with respect to the subjects. In seeking to avoid invoking researcher bias,

the interviewee’s exact comments were recorded. The final question sought to

confirm a second theoretical foundation for Intention to Trust, expectation (Deutsch,

1960):

3. What do you expect from other team members when working on a

group assignment?

Responses were recorded in exactly the same manner as question two. The subjects

were asked if they had any other comments, these were recorded. Finally, the

subjects were thanked for their participation. On average, each structured interview

was completed in ten minutes.

With just three factors to consider, the interviewee statements were analysed and

sorted using a Microsoft Excel database (Microsoft, 2007). Excel’s database, sorting

and other data manipulation routines were more than adequate for this qualitative

analysis task. Thematic analysis of the interview transcripts synonymously identified

the words and phrases associated with each of the trust antecedents from the

70

theoretical foundation for this study; Mayer et al.'s (1995) integrative model of

organisational trust (Table 4).

Table 4: Theoretical basis for the thematic analysis of the structured interview transcripts

Trust Antecedent:

High High HighHigh High LowHigh Low HighHigh Low Low

Low High HighLow High LowLow Low HighLow Low Low

competent incompetent do good not do good high principled low principled

skilled unskilled helpful not helpfulacceptable standards

non-acceptable standards

knowledgeable un-knowledgeable altruistic selfish high integrity low integrityexpert less expert good behaviour bad behaviour similar values dissimilar values

good judgement bad judgement good intentions bad intentions similar beliefs dissimilar beliefsdependent independent openness closedgroup goals self goals fair unfair

caring uncaring congruent non-congruentreliable unreliable moral immoral

doesn't lie liesconsistent inconsistent

Benevolence IntegrityAbility

Synonyms: Based on the

Integrative Model of Organisational Trust (Mayer et al., 1995)

High LowSynonym Dimensionality:

Low

High Low High Low

Information Level:

High Low HighHigh Low

The interviewee statements were categorised as pertaining to Ability, Benevolence or

Integrity based on the largest number of words in the statement that concurred with

the synonyms for each factor. For example, a statement such as ‘sometimes the other

students don’t tell the truth, they don’t do what they say they will do’ was themed as

an Integrity-related statement. Statements like ‘they don’t consider my opinion’ and

‘they don’t care about what is important to me’ were themed as a negative comment

relating to Benevolence. Other statements such as ’they may not have the necessary

knowledge’ and ‘the group may have lower grade expectations than me’ were

themed as Ability-related. The largest number of comments, 75, related to the

Integrity sub-themes (Table 5); many subjects appeared to be concerned that other

students did not share their values and standards. Benevolence sub-themes came

second, 51; many students had emerged dissatisfied from previous group assessment

encounters. Surprisingly, the trust antecedent that attracted the fewest number of

comments, 9, was Ability. If the volume of the comments is any guideline to the

salience of the trust antecedents, Integrity may be more important than Benevolence

and Ability could be viewed as least relevant.

71

Table 5: Summary of results for the thematic analysis of the structured interview transcripts

Antecedent of Trust

Ability Benevolence Integrity

Number of Comments (+ positive; - negative)

Ability Sub-themes

Benevolence Sub-themes

Integrity Sub-themes

+ - + - + -

Competency 5 4 Cooperative 3 4 Reliability 7 4

Group participation

3 1

Delivering work to the standard promised

3 5

Rapport between team members 3 4

Delivering work when it was promised

2 9

Sharing in decisions

3 5 Commitment

8 3

Communication 9 6

Share the workload

13 13

Recognition 1

Accepting responsibility for outcomes

2 3

Contribution involvement

3 Honesty

1 2

Treatment of fellow team members

6

Subtotals: 5 4 31 20 36 39 Totals: 9 51 75

At this stage of the study, this researcher’s interpretation of the interviewee

transcripts varies considerably from the study hypotheses and the results that

emerged from the Final Stage data analysis. However, this is understandable because

the interviewees had not been exposed to the experimental manipulation; one would

expect their responses to the structured interview questions to be reflective of their

past group assignment experiences. Interim research observations aside, selected

comments from the structured interviews were included in the wording of the

vignettes and the questionnaire items for the Intention to Trust, Ability, Benevolence,

Integrity and Propensity to Trust scales.

72

6.1.1.1 The Propensity to Trust Scale

The Propensity to Trust (PTP) scale, used in Stage 2 of this study, was founded upon

modified items from Gillespie (2003), Schoorman et al. (1996a), Mayer & Davis

(1999) and Rotter (1967). Based on the thematic analysis of the structured

interviews, it was determined that certain items from the original scale were not

applicable to the study setting. For example, ‘most salespeople are honest in

describing their products’ (Mayer & Davis, 1999, p. 136) is clearly out of context for

a university study setting. In replacement, more applicable items were incorporated.

For example, issues with reliance on the work of other students were consistently

raised during the structured interviews. Therefore, the following item was included

from the Gillespie (2003, p.32) scale; ‘ I would rely on task-related judgements made by

others’. Table 6 lists the twelve Propensity to Trust (PTP) items.

Table 6: The five-point Likert-scaled Propensity to Trust items used in the Pilot Stage of the study

The following questions ask about your general trus t in others:

Disagree Strongly

Disagree Neither Agree

nor Disagree

Agree Agree Strongly

1. In dealing with strangers, it is better to be cautious until they have provided evidence that they are trustworthy ..............................................................

2. Most people keep their promises ................................

3. Most people answer questions honestly................................

4. Most people say what they believe themselves and not what they think you want to hear ...............................

5. Most people tell the truth about the limits of their knowledge ................................................................

6. Most people cannot be counted on to do what they say they will do...............................................................

7. These days, you must be alert or someone is likely to take advantage of you................................

8. I normally rely on the task-related skills and abilities of others................................................................

9. I would not follow the advice of others on important issues................................................................

10. I confidently allow other people to make decisions for me during an absence................................

11. I would rely on task-related judgements made by others ....................................................................................

12. I usually monitor others when they have to do something for me ................................................................

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Reviewing Table 6, items 1 and 2 were derived directly from the Rotter (1967) scale.

Items 3 to 7 came from the original PTP scale of Schoorman et al. (1996a) and were

modified for study context. Items 8 to 11 are from the Gillespie (2003) study and

addressed trust-affecting issues raised by subjects during the structured interviews;

namely the risk of having to rely on the advice and judgement of others to make

decisions. Item 12 was added because the need to monitor the work of fellow group

members emerged as a strong theme during the structured interviews. Item 12 was

also included because the Mayer et al. (1995) definition of trust identifies monitoring

behaviours as a reflection of a lower Propensity to Trust. The notion of monitoring is

also included in Mayer et al. (1995) Intention to Trust scale.

74

6.1.1.2 The Intention to Trust Scale

The Intention to Trust (ITT) scale was constructed upon the foundation of items from

the initial Mayer et al. (1995) theory-based studies (Schoorman et al., 1996a; Mayer

& Davis, 1999). The ten ITT items were modified to reflect the study setting (Table

7). Currall & Inkpen (2002) recommend that context and the level of theorizing

needs to be considered for proper trust measurement. In line with that

recommendation, the questionnaire items used in this study were adjusted to reflect

the contextual issues that emerged from the thematic analysis of the structured

interviews with the student subjects during the Vignette Development Stage of this

study. For example, to mimic a theme that arose during the structured interviews,

item 38 was modified by removing the words ‘top management’ and replacing them

with ‘this group’.

‘If I had my way I wouldn’t let top management have any

influence over issues that were important to me’ (Mayer & Davis, 1999)

was modified to:

38. If I had my way I wouldn’t let this group have any

influence over issues that were important to me’

Interviewees in Stage 1 were not concerned about university management; they were

concerned that the behaviour of fellow group members would detrimentally affect

the grade they expected to receive for their group work. Other trust-related issues

raised by the subjects during the structured interviews were incorporated into the ITT

questionnaire items. These issues included: students proving they could do the work;

whether or not the other group members could be counted on to complete the work;

whether the students would be honest about their knowledge; whether social loafers

would leave the other group members to do all the work; whether the skills, abilities

and efforts of the other group members would result in work of an acceptable

standard, and; whether members would take notice of the opinions of fellow group

members or force decisions on them.

75

To make the questions understandable and more relevant to the student subjects, the

face validity of the questionnaire items 42 through 47 were improved (Cavana et al.,

2001, p214) by using the words and phrases spoken by the subjects when describing

issues raised during the structured interviews. Table 7 lists the ten Intention to Trust

questionnaire items employed in the Pilot and Final stages of the study.

Table 7: The five-point Likert-scaled Intention to Trust items used in the Pilot and Final stages of this study

Think about the information presented in the email and answer the following questions about how you perceive this group:

Disagree Strongly

Disagree

Neither Agree

nor Disagree


38. If I had my way I wouldn’t let this group have any influence over issues that were important to me ..............................................................................................

39. I would be willing to let this group have complete control over an assignment that was critical to me .................

40. If I joined this group, I feel I need to keep an eye on what other group members do ..............................................................................................

41. I would be comfortable giving this group a task or problem which was critical to me, even if I could not monitor the group’s actions ................................

42. In dealing with this group, it would better to be cautious until they have provided proof that they are trustworthy ................................................................

43. I feel this group could be counted on to do what they say they will do ..............................................................................................

44. This group should be honest about their knowledge ..............................................................................................

45. I will be cautious or this group could take advantage of me .............................................................................................

46. I feel I could rely on the skills and abilities of this group ..............................................................................................

47. I would allow this group to make decisions for me ..............................................................................................

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6.1.1.3 Ability, Benevolence and Integrity Scales

With the composition of the DV scales for Propensity to Trust and Intention to Trust

complete, a decision had to be made concerning the IV scales for the trust

antecedents of Ability, Benevolence and Integrity. Previous studies based on the

Mayer et al. (1995) trust theory have used the IV scales developed for the initial

Schoorman et al. (1996a) study; they have consistently exhibited good scale

reliability (Table 8).

Table 8: Examples of the good Cronbach Alpha results for the Ability, Benevolence and Integrity scales used in recent studies

Study Ability Benevolence Integrity

(Mayer & Davis, 1999) .85 .87 .82 (Serva et al., 2005) .96 .84 .85 (Gill et al., 2005) .96 .95 .94 (Mayer & Gavin, 2005) .91 .92 .89 Cronbach Alpha measure of inter-item consistency reliability: >

.8 = good; > .7 = acceptable; < .7 = low.

Because of their good reliability, the same scales were used in this study. Tables 9,

10, and 11 itemise the Ability, Benevolence, and Integrity questions employed in

both Stages 2 and Stage 3 of this study. Like the PTP and ITT scales, they were

modified to reflect the study setting. For example, the subject in items 48 to 53 was

changed from ‘manager’ to ‘group’.

Table 9: The five-point Likert-scaled Ability items used in the Pilot and Final stage of this study

Continue to think about the information presented in the email and answer the following questions about how you perceive this group:

Disagree Strongly

Disagree

Neither Agree

nor Disagree


48. The group is very capable of performing its job .............................................................................................

49. The group appears to be successful at the things it tries to do ................................................................

50. The group has much knowledge about the work that needs to be done ............................................................

51. I feel very confident about the group’s skills ..............................................................................................

52. The group has specialized capabilities that could increase my performance.......................................................

53. The group is well qualified ..............................................................................................

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Table 10: The five-point Likert-scaled Benevolence items used in the Pilot and Final stages of this study

Disagree Strongly

Disagree

Neither Agree

nor Disagree


54. The group will be very concerned about my welfare...................................................................................

55. My needs and desires will be very important to the group ................................................................

56. The group would not knowingly do anything to hurt me ..................................................................................

57. The group will really look out for what is important to me................................................................

58. The group will go out of its way to help me ..............................................................................................

Table 11: The five-point Likert-scaled Integrity items used in the Pilot and Final stages of this study

Disagree Strongly

Disagree

Neither Agree

nor Disagree


59. The group has a strong sense of justice ..............................................................................................

60. I will never have to wonder whether the group will stick to its word ................................................................

61. The group tries to be fair in dealings with others ..............................................................................................

62. The group's actions and behaviours are not very consistent ................................................................

63. I like the group’s values ..............................................................................................

64. Sound principles seem to guide the group’s behaviour................................................................

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6.1.1.4 Vignette Development

Like the scales, the vignettes were similarly developed from the thematic analysis of

the structured interviews. The research design called for all three antecedents of trust

to be concurrently manipulated within each vignette. With the goal of optimising a

subject’s comprehension, the vignettes were theoretically founded and composed to

reflect the specific words and phrases used by the subjects during the structured

interviews in Stage 1. For example, the theoretical foundation for this study (Mayer

et al., 1995) proposes that confidence in another’s Ability and their intent to act on

your behalf lies at the core of trusting another individual, group or organisation.

These issues emerged in the structured interviews conducted in Stage 1. There were

concerns that ‘group members would deliver inferior work’ or that they ‘lacked the

knowledge’ or would not ‘consider the welfare’ or ‘the needs and desires’ nor act in

the ‘best interests of other group members’. The customisation of vignette content

was expected to enhance subject understanding of vignette content; this tends to

maximise relevance to the subjects and engages their interest (Hughes & Huby,

2004, p. 40). The following is an example of how the subject’s words and phrases

were incorporated into a vignette depicting High Ability and High Benevolence:

• The group has good subject knowledge. • In the past, the members of this group have shown concern for the welfare of

other group members.

• Your needs and desire should be important to the group.

• The group members really look out for what is important to other group members.

The following vignette is an example of the concurrent manipulation of three trust

antecedents in a vignette depicting a work-team with High Ability, High

Benevolence and Low Integrity.

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6.1.1.5 Example Preliminary Vignette

Please read the following case and imagine that you are in the situation described. Then answer the questions in the following questionnaire. You are an undergraduate student enrolled in a compulsory unit for your Business Degree. The unit assessment includes a group assignment worth forty percent. You receive the following email from the unit coordinator: From: [email protected] Sent: Monday, 10 May 2006 9:02 AM To: BSB311_student@ student.uni.edu.au Subject: BSB311 Assessment item #2: The Group Assignment As unit coordinator, I reviewed the records for the unit and noticed that you are not currently assigned to a group for the written assignment. Receiving a pass grade for the assignment is a mandatory unit requirement. The Unit Outline states that ‘Students who do not receive a pass mark for their group assignment will fail the unit’. To receive your degree, you must pass this unit. Therefore, to pass the unit, you must immediately join an existing group. The assignment is due in three weeks; all members of a group receive the same mark for the assignment. A couple of the groups have room for another student. Group #6 members volunteered the following information about their group.

• The group has good subject knowledge. • The group exhibits good time management and decision-making skills. • The group’s written work is good. • Based on official University records, authenticated by me, the group

members volunteered the following information concerning their grades:

Student Grades from their last three Group Assignments

No. 1 No. 2 No. 3

Student Average for their Group Assignments

Student Grade Point

Average Student A 6 5 6 5.67 5.70 Student B 7 7 5 6.33 6.30 Student C 6 7 5 6.00 5.90

Overall Group Assignment Average: 6.00 Overall Student Grade Point Average for the Group: 5.97

• The group communicates well. For example, all group members promptly answer emails.

• Group members show concern for the welfare of others. For example, group

members always arrive on time for meetings and never make hurtful comments to other group members.

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• The members of this group are team-orientated and cooperative. For example,

they listen to the ideas of the other group members, are flexible, and openly discuss and resolve differences of opinion. They learn from one another and go out of their way to help fellow group members.

• With this group, things should get done the way you want them to be done.

• Some group members can have a questionable sense of justice. For example,

some group members may bend university rules and they may not value the extra effort put in by other group members.

• When it comes to doing the work, some group members can be unfair. For

example, when they finally agree on what has to be done, they won’t share the work equally.

• Sometimes, a group member may be untruthful; they sometimes don’t do

what they say.

• The weaker principles of this group will let you do anything you want. Now complete the following questionnaire. It will indicate to me if you should join the group or whether I need to arrange for you to join another group. Please begin the questionnaire now; it will be collected in about ten minutes. Thank You BSB311 Unit Coordinator Faculty of Business

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6.1.1.6 Reason for changing from a 3x2 to a dual 2x2 factorial design

Piloting the initial vignettes proved problematic, concurrent manipulation of the three

trust antecedents was a flawed design strategy; the vignettes suffered from face

validity issues. While the vignettes were written in familiar speech, that was easier to

understand and used oft-repeated familiar words and phrases from the structured

interviews, pre-test subjects had difficulty comprehending their meaning; they voiced

confusion. It became obvious that concurrent manipulation of all three antecedents

was illogical. The subjects doubted the validity of vignette content that depicted a

group with dimensionally opposite attributes of Integrity and Benevolence. The

following is an example of the vignette content for:

Low Integrity

• Some group members can have a questionable sense of justice. For example, some group members may bend university rules and they may not value the extra effort put in by other group members.

• When it comes to doing the work, some group members can be unfair . For

example, when they finally agree on what has to be done, they won’t share the work equally.

• Weaker principles guide the behaviour of this group. Sometimes, a group

member may be untruthful ; they sometimes don’t do what they say.

High Benevolence

• In the past, the members of this group have shown concern for the welfare of other group members.

• Your needs and desire should be important to the group.

• The group has not knowingly done anything to hurt anyone in the past.

• The group members really look out for what is important to other group

members.

Subjects voiced concern that the initial vignettes were not believable. This is not

unusual, because adults consistently detect lies and anomalies in vignettes (Bussey,

1992). A review of the above example revealed that; on the one hand it is easy to

imagine that group members of High or Low Ability could exhibit attributes of Low

Benevolence by, in the words of the vignettes, being ’untruthful’ and ‘showing little

concern for fellow group members’. On the other hand, it is hard to believe that a

Low Integrity group that are ‘untruthful’ and ‘unfair’ could exhibit High

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Benevolence at the same time by ‘looking out for what is important to other group

members’. To satisfy the basic prerequisite for a trustworthy vignette, the vignettes

must depict a believable situation familiar to the subjects (Bussey, 1992). In response

to pre-test subject feedback, the factorial design of the study was altered to facilitate

dimensional manipulation of the independent variables without compromising the

believability of the vignettes. The a priori 3x2 factorial design, where the three trust

antecedents were concurrently manipulated, was changed to a dual 2x2 factorial

design. In the (2x2) factorial design, four different vignettes manipulated High and

Low Information Levels of Ability and Benevolence (Table 12) and the other four

vignettes manipulated High and Low Information Levels of Ability and Integrity

(Table 13).

Table 12: 2x2 Factorial design for the manipulation of the dimensions of Ability and Benevolence

Trust Antecedent

Ability Benevolence High Low High Low

X X X X X X X X

Table 13: 2x2 Factorial design for the manipulation of dimensions of Ability and Integrity

Trust Antecedent

Ability Integrity High Low High Low

X X X X X X X X

83

The vignettes were rewritten to concurrently depict High or Low Ability with either a

dimension of Benevolence or a dimension of Integrity. The updated vignettes were

piloted on different pre-test subjects; none provided feedback that the new vignettes

were unbelievable or confusing. The dual 2x2 factorial design was applied in study

stages two and three.

With the design updated plus the vignettes and scales completed, the last page of the

questionnaire requested demographic information. The demographic questions

initially sought confirmation that the subject was a student from the target population

of Business Faculty undergraduate students. To ensure that the same subject did not

submit multiple questionnaires, personal information was requested; gender, age,

birth month and year, and mother’s maiden name. The students were advised they

would remain anonymous, no names or student numbers were collected. The subjects

were provided with sufficient questionnaire space to voluntarily provide feedback

and comment. The resulting Stage 2 questionnaire incorporated the Propensity to

Trust items prior to the vignette manipulation and the Intention to Trust, Ability,

Benevolence and Integrity items post the vignette. The demographic items were

included at the end of the questionnaire. To provide data for future research, items

addressing the following variables were included prior to the vignette manipulation:

• Preference for Teamwork (Kirkman & Shapiro, 2001)

• Individualism (Maznevski & DiStefano, 1995 in Kiffin-Petersen &

Cordery 2003)

• Self-assessed Ability (developed for this study and based upon

Schoorman et al. (1996a)

• Self-assessed Benevolence (developed for this study and based upon

Schoorman et al. (1996a)

• Self-assessed Integrity (developed for this study and based upon

(Schoorman et al., 1996a)

• Locus of Control from Carlopio, Andrewartha, Armstrong, & Whetten

(2001, p. 99) based on Rotter’s (1967) internal-external Locus of Control

Scale

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6.1.1.7 Summary of Stage 1 Results

The thematic analysis of the transcripts from the structured interviews identified

words and phrases synonymous with the theoretical foundation for this study.

Once categorised, interviewee comments were applied to develop the vignettes

that would manipulate the levels of the independent variables, Ability,

Benevolence and Integrity. Similarly, the questionnaire items for the IVs and the

DVs were refined to reflect the context of the study. In pre-testing the

questionnaires, the concurrent manipulation of all three IVs appeared

unbelievable to the respondents. In response, the planned 3 x 2 factorial study

design was re-engineered to a two 2x2 factorial design. Ability and Benevolence

were manipulated together and Ability and Integrity were concurrently

manipulated with separate vignettes. Finally, demographic items were added to

the questionnaire to be used for data collection in Stage 2.

85

6.1.2 Analysis and Results of Study Stage 2: Pilot of the Test Instruments The goal of Stage 2 was to strengthen internal validity and make the vignettes

realistic, by piloting and refining them (Hughes & Huby, 2004) prior to their final

application in stage three of this study. One hundred and eighty seven Undergraduate

Student subjects from the Business Faculty population of a metropolitan Australian

university were sampled to test the vignette manipulations and questionnaire items

developed in Stage 1 (Figure 14).


The 100 female and 87 male respondents, not involved in Study Stage 1, satisfied the

experimental requirement for previous experience with group-based assessment

where all team members received the same grade from their group work. The

respondents individually completed the questionnaire prior to their scheduled lecture

or tutorial. The subjects self-selected by choosing to accept or reject a questionnaire

as they entered their classroom. The subjects were offered neither recognition nor

reward for completing a questionnaire. Randomisation occurred via the random

nature of the subjects’ arrival at their class and their equal chance of receiving one of

the randomly sorted questionnaires that contained one of the eight different vignette

manipulations.









86

The subjects were directed to complete the questionnaire in a consistent manner; a

single overhead projection slide was used to convey completion instructions. This

process sought to normalise the process that all subjects would go through in

completing the questionnaire. The instructions directed the participants to respond

from the beginning of the questionnaire and proceed page by page to the

demographic items on the last page of the questionnaire. To maintain respondent

anonymity, the subjects placed the completed questionnaire under their lecture

theatre or tutorial room seat; the questionnaires were collected after the subjects had

exited the room.

6.1.2.1 The Data were Prepared for Analysis

Each questionnaire was assigned a sample identification code and the data were

entered into a Microsoft Excel spreadsheet in preparation for upload and analysis

using SPSS for Windows version 13 (SPSS, 2004). To ready the data for analysis,

the missing values were pre-processed using the maximum likelihood with EM

‘Missing Variable Analysis’ function in SPSS (Tabachnick & Fidell, 2007, pp. 62-

72). The rationale behind the choice of method for the replacement of missing

questionnaire data is discussed in more detail in the Final Stage results section of this

thesis. Subsequent to missing data replacement, the negatively worded items in the

Propensity to Trust, Integrity and Intention to Trust scales were recoded and data

analysed using SPSS for Windows version 13 to produce (Table 14) descriptive and

bivariate correlation statistics (Tabachnick & Fidell, 2007, pp. 56-58).

87

Table 14: Descriptive statistics and correlations from Study Stage 2, N = 187

Mean Standard Deviation

Propensity to

Trust

Intention to

Trust Ability Benevolence Integrity Propensity

to Trust 34.36 4.64 1

Intention to Trust 28.70 5.10 .272 ** 1

Ability 20.11 3.83 .168 ** .538 ** 1

Benevolence 14.56 3.19 .206 ** .465 ** .329 ** 1

Integrity 18.49 3.75 .136 ** .593 ** .459 ** .687 ** 1

Level of significance: * p < .05 ** p < .01 *** p < .001

In support of hypotheses H1, Ability ( r = .538, p = .01), Benevolence (r =.465, p =

.01) and Integrity (r = .593, p =.01) were found to have a positive relationship with

Intention to Trust (Table 14). Overall, these results were consistent with previous

studies (Table 15); there was a positive relationship between the trust antecedents,

Ability, Benevolence and Integrity, and Intention to Trust.

Table 15: Comparison of ITT study results from this research and recent studies employing similar measurement scales based on the Mayer et al. (1995) theoretical foundation

Correlation of

Intention to Trust with

Ability

Benevolence Integrity

Stage 2 Results from this Study .538 * .465 ** .593 **

Previous Studies (Davis et al., 2000) .561 *** .595 *** .655 *** (Davis, 1999) .796 ** .818 ** .759 ** (Gill et al., 2005) .60 ** .71 ** .68 ** (Mayer & Davis, 1999) .61 ** .60 ** .58 ** (Mayer & Gavin, 2005) .74 ** .72 ** .76 ** (Tan & Tan, 2000) .75 ** .83 ** .85 **


88

However, the significance of the Ability relationship with Intention to Trust was

lower than previous studies. A lower than expected level of significance prompted a

check of the effect of the vignette manipulation and a review of subject comments. A

review of questionnaire feedback comments identified that some subjects perceived

little or no significant difference between the High Ability and Low Ability

information in the vignettes (Tables 16 and 17).

Table 16: Ability information provided in the Pilot Study Low Ability vignette

Student Grades from their last three Group

Assignments

No. 1 No. 2 No. 3

Student Average for their Group

Assignments

Student Grade Point



Table 17: Ability information provided in the Pilot Study High Ability vignette


No. 1 No. 2 No. 3

Student Average for their Group

Assignments

Student Grade Point



In response to this qualitative information that appeared to identify that subjects

similarly perceived the Low and High Ability vignette information, the vignettes

were referred for expert review. The expert, who had extensive experience in

lecturing and teaching students from the target population, suggested that the

students would view the low grades depicted in the Low Ability vignettes as

acceptable grades. This may occur because the university allows students to graduate

with a small number of failing grades; a conceded pass of ‘3’ (Table 18); the

phenomenon that students may accept substandard marks as a passing grade is

worthy of further pedagogical research.

89

Table 18: Grading scale for the university population

Grade Example Grade

Percentages 1 Fail 0 to 14% 2 Fail 15 to 29% 3 Conceded Pass 30 to 49% 4 Pass 50 to 64% 5 Credit 65 to 74% 6 Distinction 75 to 84% 7 High Distinction 85 to 100%

In response to the advice of the vignette expert, the Information Level in the Low

Ability vignettes was changed to include more failing grades (Table 19).

Table 19: Updated Low Ability vignette content reflecting failing grades


No. 1 No. 2 No. 3

Student Average for their Group Assignments

Student Grade Point



In addition to the failing grade issue, some Pilot Stage subjects commented that the

one and a half page vignettes were too long. Some subjects mentioned that, by the

time they had progressed to the questionnaire items, they were experiencing

difficulty recalling the vignette information about the group. This is unacceptable

because subjects optimally respond to succinct vignettes (Murphy et al., 1986).

Additionally, the vignette expert considered that some of the vignette information

was verbose and inexplicit; as a result, the vignettes may not have had the desired

effect. In response, the length of each piece of vignette information was shortened,

large words that were more difficult to remember (Tehan & Tolan, 2007), and

information identified as confusing was omitted from the revised vignettes.

90

From the testing process perspective, there was a concern that the single Pilot Stage

questionnaire that consecutively measured PTT then ITT was potentially invoking

pre-testing effects that could compromise the internal validity of the study (Cavana et

al., 2001 , p. 295). In correction, the final data collection in Stage 3 was split into two

phases. Phase 1 collected Propensity to Trust and the data for future studies; Locus of

Control, Individualism, Preference for Teamwork, and, Self-assessed Ability,

Benevolence and Integrity. Phase 2 was a much shorter questionnaire incorporating

the vignette manipulation, the Intention to Trust items, then the items for Ability,

Benevolence and Integrity. The same demographics were collected in both phases.

6.1.2.2 Summary of Stage 2 Results

The goal of Stage 2 was to strengthen the internal validity of this vignette

experiment. The experimental process was piloted on 187 subjects. Results from

descriptive statistics were reflective of similar trust-related studies. However, lower

than expected mean differences between the High and Low levels of Ability, together

with comments from the subjects, flagged a possible issue with the vignette

manipulations. Subjects were experiencing difficulty perceiving difference between

the vignettes depicting High Ability from those depicting Low Ability. An expert

review identified that student subjects may have perceived the minimal passing grade

depicted in the Low Ability vignettes as High Ability. Additionally, subjects

commented that the vignettes and the questionnaire were verbose. In response, the

vignettes and questionnaire lengths were reduced and the grade projected in the Low

Ability vignettes was lowered to a failing grade. The refined questionnaires were

then applied in Study Stage 3.

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6.1.3 Analysis and Results of Study Stage 3: the Final Data Collection

The questionnaires developed from Stage 2 were used in Stage 3 (Figure 15). Two

hundred and twenty four Undergraduate Student subjects from the same Business

Faculty population of the metropolitan Australian university participated in Stage 3;

a comparison of the demographic information was used to ensure that no subjects

had participated in the previous two stages of the study.


The one hundred and twenty six female and ninety-eight male respondents satisfied

the experimental requirement for previous experience with group-based assessment

where all team members received the same grade from their group work. The method

for administering the questionnaires was identical to Stage 2. However, to avoid pre-

testing effects that can threaten the internal validity of a study the two Stage 3

questionnaires were administered one week apart. From the demographic section of

the questionnaire, the subject’s month of birth, the last two letters of their mother’s

maiden name and the last letter of the subject’s family name were used to

anonymously-match the two questionnaires. While this matching method was

considered an accepted method for matching data sources, it was not successful.

Sixty-five responses from the first phase and sixty responses from the second phase

could not be matched; 36% of the total Stage 3 responses. The identification and

testing of an optimal method for matching multistage data collections from

anonymous subjects offers an opportunity for future research.









92

Subsequent to data collection, the data were entered into an Excel spreadsheet in

preparation for analysis using SPSS for Windows version 13 (SPSS, 2004). To

satisfy the requirement for later Structural Equation Modelling (SEM) analysis, the

data were prepared according to Tabachnick & Fidell (2007, pp. 682-684). This

process involved: 1) computing the missing data values; 2) checking the data for

outliers; 3) testing the data for normality using SPSS, and finally; 3) normality was

further tested using the PRELIS 2.30 software (Joresborg, 1997).

In computing the missing data values, the goal was to maximise the sample size and

thereby optimise the power of the statistical tests, (Cohen, 1977). Maximising the

sample size also aids in satisfying the large sample requirements of the SEM analysis

techniques (Byrne, 1998; Cortina, Chen, & Dunlap, 2001, p. 326). In replacing the

missing data values, traditional missing data approaches like list-wise deletion

(Cohen et al., 2003, p. 433), which removes variables or subjects, were discounted in

favour of a maximum likelihood imputation (ML) estimation technique using the EM

algorithm. ML-EM alternatively estimates and maximises missing values (Cohen et

al., 2003, pp. 433-451; Cortina et al., 2001 ;Enders, 2006; Tabachnick & Fidell,

2007, p. 680). In confirming selection of the ML technique, a number of criteria

were considered; the missing nature of the absent values; whether values were

missing in both independent and dependent variables, and, the sample size. The

Stage 3 sample size satisfied the initial ML-EM requirement for a ‘large sample size

(n > 200)’ (Cohen et al., 2003, p. 440). Using the SPSS 13.0 for Windows software

(SPSS, 2004), the missing values were pre-processed using Missing Variable

Analysis with ML-EM. Post hoc analysis identified no patterns in the missing data

(Table 20).

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Table 20: Univariate statistics from the missing variable analysis of the Stage 3 data

Item N Mean Std.

Deviation Missing No. of

Extremes(a, b)

Count Percent Low High Itt1 224 2.84 1.007 0 .0 0 0 Itt2 224 2.19 .943 0 .0 0 4 Itt3 224 2.46 .979 0 .0 0 7 Itt4 223 2.66 1.031 1 .4 0 0 Itt5 223 2.42 .876 1 .4 0 3 Itt6 222 3.18 .989 2 .9 0 0 Itt7 223 4.01 .626 1 .4 . . Itt8 223 2.85 .959 1 .4 0 0 Itt9 223 3.22 .999 1 .4 0 0 Itt10 224 2.67 .978 0 .0 0 5 Ab1 224 3.35 .940 0 .0 8 0 Ab2 224 3.39 .927 0 .0 2 0 Ab3 224 3.15 .928 0 .0 0 0 Ab4 224 3.04 .972 0 .0 0 0 Ab5 224 3.08 .978 0 .0 0 0 Ab6 223 3.13 .947 1 .4 0 0 Ben1 222 2.76 .962 2 .9 0 8 Ben2 224 2.74 .969 0 .0 0 6 Ben3 224 3.29 .920 0 .0 8 0 Ben4 224 2.75 .872 0 .0 0 4 Ben5 224 2.84 .877 0 .0 0 2 Int1 224 3.08 .887 0 .0 8 0 Int2 224 2.89 .933 0 .0 0 0 Int3 224 3.28 .850 0 .0 2 0 Int4 224 3.08 .836 0 .0 0 0 Int5 223 3.12 1.033 1 .4 0 0 Int6 224 3.19 .935 0 .0 0 0 JnGrp 224 3.11 1.119 0 .0 0 0 Enrol 224 .86 .346 0 .0 . . Faculty 224 1.38 1.599 0 .0 . . Gender 224 .56 .497 0 .0 0 0 AgeGrp 223 1.68 .674 1 .4 0 3 Birth 224 6.83 9.104 0 .0 0 47 Nation 224 5.14 7.647 0 .0 . . InAus 224 2.10 1.782 0 .0 0 22 WorkExp 224 .50 .798 0 .0 0 9 GrpExp 224 .95 .217 0 .0 . . Age 224 21.25 4.837 0 .0 0 18

a Number of cases outside range (Q1 - 1.5*IQR, Q3 + 1.5*IQR).

b indicates the inter-quartile range (IQR) is zero.

94

Subjects did not consistently fail to answer a particular question or sequence of

questions. From 224 responses, no item had more than two missing values; the

missing data appeared to be missing at random. Therefore, particular items were not

considered to be problematic (Cohen, 1988, 432-433). This was expected because

published and previously well-tested scales have been used (Robinson, Shaver, &

Wrightsman, 1991). The first two criteria for ML selection had been satisfied.

In addressing the last criteria for the appropriate use of ML, it was noted that values

were missing on not just independent variables, but also on the dependent variables.

For example, in the collected data there were seven values missing across six of the

ten ITT variables. When data are missing on more than one variable there is a

concern that study conclusions may be limited, particularly when the data are

missing on dependent variables. This raises the concern that a sample with missing

values may not be representative of the population (Cohen, 1988). However, in

support of the use of the ML procedure, ML ‘doesn’t care’ whether data are missing

on the independent or dependent variables; ‘one is not limited in generalization of

one’s findings’; the ML model estimating procedure provides the best possible,

unbiased, estimates for each missing value by considering all the data values in a

model (Cohen et al., 2003, p. 442). The final criteria for ML was satisfied, data

values were missing across both the independent and dependent variables. Therefore,

with the sample meeting the ‘large size requirement of n >200’ (Cohen et al., 2003,

p. 440), the missing at random nature of the absent values, and because those absent

values occurred in both the independent and dependent variables, the decision was

made to retain the estimated missing values from the application of the maximum

likelihood imputation (ML) estimation technique using the EM algorithm (Cohen et

al., 2003).

However, while the missing data had been replaced, its use for SEM analysis is

founded upon a key assumption; the variables in an SEM model must be distributed

multivariate normal. This is particularly important because Maximum Likelihood

estimation technique, ML, was the chosen analytic strategy for assessment of the

structural equation models. Prior to using the PRELIS 2.30 software (Joresborg &

Sorbom, 1996) to satisfy the SEM requirement for multivariate normality, the

outliers in the variables were assessed using the SPSS ‘Frequencies’ command. A

95

preliminary screen of the data (Tabachnick & Fidell, 2007 pp. 72-74) identified the z

scores were all less than 3.29, p = .01, two tailed; there appeared to be no potential

outliers. Histograms of the data for each variable appeared normal and no univariate

outliers stood out in the box plots. Initial SPSS examination of the data for

univariate and multivariate normality applied conservative alpha levels of .01 or .001

(Tabachnick & Fidell, 2007, pp. 80-810); the kurtosis and skewness statistics were

close to zero. In final preparation for SEM analysis, subsequent data screening used

the PRELIS 2.30 software (Joresborg & Sorbom, 1996). While the skewness and

kurtosis values are optimally zero, the demonstrated skewness of the IV and DV

variables fell within a PRELIS-accepted range of 2.00 to 3.00, and the kurtosis

values fell within the acceptable range of 7.00 to 21.00 (Curran, West, & Finch,

1996, p. 28). Repeating this analyses with and without missing data was considered

unnecessary because of the small number of missing values (Tabachnick & Fidell,

2007, p. 72). Therefore, the data are generally approximating a normal distribution

(Byrne, 1998). To get a feel for the results to come, the descriptive statistics of the

normalised Stage 3 data were next analysed.

In gaining a feel for the normalised Stage 3 data, initial analysis using SPSS 13.0 for

Windows (SPSS, 2004) identified descriptive statistics similar to Stage 2 (Table 21)

Table 21: Descriptive statistics and correlations from Study Stage 3, N = 224

Mean Standard Deviation

Intention to

Trust Ability Benevolence Integrity Intention to

Trust 28.49 5.93

Ability 19.15 4.93 .653 ** 1

Benevolence 14.39 3.80 .357 ** .203 ** 1

Integrity 18.63 4.04 .639 ** .488 ** .678 ** 1


Similar to Stage 2, hypotheses H1 was supported in Stage 3. In comparing Stage 2

and Stage 3 results (Table 22):

• the positive relationship between Intention to Trust and Integrity

strengthened slightly from r = .593, p = .01, in Stage 2 to r = .639, p = .01 in

Stage 3;

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• Ability had similarly strengthened and the significance level improved from r

= .538, p = .05, to r = .653, p = .01, but;

• the ITT relationship with Benevolence had weakened slightly from r = .465,

p = .01, to r = .357, p = .01.

These differences could have arisen from sample differences. Alternatively, the

differences could have arisen from the Stage 2 refinement of the vignettes and

questionnaire items which sought to contribute to the reliability of the trust scales.

Table 22: Comparison of ITT study results from this research and recent studies employing similar measurement scales based on the Mayer et al. (1995) theoretical foundation; N = 224

Correlation of Intention to Trust

with

Ability Benevolence Integrity

Stage 3 results from this Study .653 ** .357 ** .639 ** Stage 2 results from this Study .538 * .465 ** .593 **

Previous Studies (Davis et al., 2000) .561 *** .595 *** .655 *** (Davis, 1999) .796 ** .818 ** .759 ** (Gill et al., 2005) .60 ** .71 ** .68 ** (Mayer & Davis, 1999) .61 ** .60 ** .58 ** (Mayer & Gavin, 2005) .74 ** .72 ** .76 ** (Tan & Tan, 2000) .75 ** .83 ** .85 **


The refinement of the vignettes and questionnaire had improved the issues associated

with Stage 2 subjects differentiating between High and Low levels of Ability, A one-

way analysis of variance (Tabachnick & Fidell, 2007, pp. 20-27) was conducted on

the Stage 3 data to add weight to the evidence that the vignette refinement in Stage 2

had assisted subjects to better differentiate the levels of the trust antecedent

information communicated via the vignette manipulation. The ANOVA was

significant, F (7, 216) = 11.124, p = 0.00. The strength of the relationship between

the DV, Intention to Trust, and the varying levels of the IVs, Ability, Benevolence,

and Integrity, as assessed by ή2 was strong, with the independent variables

accounting for 26% of the variance of the dependent variable.

97

Follow up ANOVA tests were conducted at the 95% confidence interval, to evaluate

pairwise differences among the means. Variances among the eight groups ranged

from 13.76 to 40.58 and were considered not to be homogeneous. Therefore, post

hoc comparisons were conducted using Dunnett’s C. Figures 16 and 17 illustrate an

improvement between the means of the groups for Stages 2 and 3.

98

Figure 16: Box plot of Intention to Trust for Stage 2

Figure 17: Box plot of Intention to Trust for Stage 3

99

The refined Ability information in the Stage 3 vignettes contributed to an increase in

the mean difference between the High and Low Ability groups. For example, The

mean difference between a group manipulated with High Ability together with High

Integrity compared to a group manipulated with Low Ability together with High

Integrity has risen from mean difference = 3.83, n = 187 in Stage 2 to mean

difference = 5.02, n = 224 in Stage 3. While sample difference may have affected

these results, it seems reasonable to infer that the refined vignettes have contributed

to subjects better differentiating the levels of Ability communicated via the vignettes.

In addition to the improvements from the updated vignettes, the Cronbach Alpha

statistic for Intention to Trust had improved from acceptable in Stage 2 (ά = .77) to a

good result ( ά = .83) in Stage 3. When compared with previous studies (Table 23), it

would seem reasonable to infer that the study goal of contributing to vignette

development methods and improving the published trust scales had been achieved.

The thematic analysis-based development of the questionnaire items and scales in

Stage 1 of this study and their piloting and refinement in Stage 2 has contributed to

improving the inter-item consistency and reliability of the Intention to Trust scale.

Table 23: A comparison with recent trust studied reveals the improved scale reliability for Intention to Trust Study AB BEN INT Intention to

Trust Stage 2 Results from this Study .85 .87 .82 .77 Stage 3 Results from this Study .92 .88 .83 .83 (Mayer & Davis, 1999) .85 .87 .82 .59 (Gill et al., 2005) .93 .93 .93 .70 (Mayer & Gavin, 2005) .91 .92 .89 .70

Cronbach Alpha measure of inter-item consistency reliability:

.8 = good; > .7 = acceptable; < .7 = low

In summary, the descriptive statistics were similar in Stages 2 and 3. In support of

Hypothesis H1, the antecedents of trust were positively associated with Intention to

Trust. Increased mean-difference indicates that the rewording of the vignettes

appears to have contributed to subjects better differentiating between the High and

Low Ability manipulations. A method contribution arose from the improvement in

the inter-item consistency and reliability of the Intention to Trust scale. The Stage 3

raw data is now analysed using Structural Equation Modelling techniques.

100

6.1.3.1 SEM Analyses

Structural Equation Modelling (SEM) was applied in pursuit of two goals. Firstly, to

confirm that the data collected are reflective of the underlying trust theory of Mayer

et al. (1995) Secondly, to apply Confirmatory Factor Analysis techniques illustrate

the extent to which Study Stages one and two resulted in measurement scales that

reflected the underlying theory in the study setting. SEM was applied using the

maximum likelihood (ML) method of parameter estimation (Bollen, 1989b) in the

LISREL 8.3 software (Joresborg & Sorbom, 1996). In support of the use of SEM

with ML, Cortina et al. (2001, p. 326) identify that ML is robust with respect to

many types of violation of multivariate normality assumptions (Bollen, 1989) and the

ML technique results in a Goodness of Fit in an SEM model similar to those

provided by the ‘robust’ Satorra and Bentler technique (Satorra & Bentler, 1988 in

Byrne, 1998). The SEM statistical methodology pursued in this study is a

confirmatory, hypothesis testing, approach to the multivariate analysis of the

structural theory underlying the ‘integrative model of organisational trust’ (Mayer et

al., 1995, pp. 709-734). Unlike correlation-based statistical procedures that infer

relationship (Tabachnick & Fidell, 2007, pp. 56-57), SEM’s confirmatory approach

has the advantage of seeking to simultaneously test all hypothesized relationships in

an entire system of variables by determining the extent to which the hypothesised

model is consistent with the observed data (Byrne, 1998). SEM offers the

opportunity to overcome the descriptive nature of traditional multivariate procedures,

like the exploratory factor analysis or other correlation or means-based analyses used

in many recent trust-related studies (Gill et al., 2005; Kiffin-Petersen & Cordery,

2003; Serva et al., 2005). SEM does this by assessing and correcting for

measurement error in the observed variables and thereby providing explicit

parameter estimates of the unobserved latent factors (Byrne, 1998, pp. 4-5). In the

case of the ‘integrative model of trust’ theory (Mayer et al., 1995), the exogenous

latent factors of Ability, Benevolence and Integrity, and their effect on the

endogenous latent factor, Intention to Trust were examined (Figure 18).

101

Figure 18: A priori conceptualisation of the study model to be tested using LISREL 8.3

To test that the postulated a priori model holds in the population of Business Faculty

Undergraduate Students, a three-step approach, based on Anderson & Gerbing

(1988), was applied to structural equation model fitting and assessment:

Step 1. The one-factor congeneric measurement models sought parsimony by

assessing the impact of the latent factors, Ability, Benevolence, Integrity and

Intention to Trust, on their set of observed variables.

Step 2. A first-order confirmatory factor analysis (CFA) (Byrne, 1998, pp.

91-161) pursued measurement model reliability and validity, and sought to

operationalise the measurement model, by testing the multidimensionality of

the theoretical construct that Ability, Benevolence and Integrity are the

hypothesised antecedents of Intention to Trust .

Step 3. Finally, the full generalised structural equation model (Byrne, 1998,

pp. 231-255) applied path analysis to investigate the strength of the

relationship of the exogenous factors, Ability, Benevolence and Integrity, on

the exogenous latent factor, Intention to Trust.

Ability

BenevolenceTrustor’s

Intention To Trust

Integrity


Trustee

Contextual (Moderators)

Information Level

+

+

+

Ability

BenevolenceTrustor’s

Intention To Trust

Integrity


Trustee

Contextual (Moderators)

Information Level

+

+

+

102

The structural equation models were fitted and assessed using covariance matrices

generated from the questionnaire data by the PRELIS 2.30 software (Joresborg &

Sorbom, 1996). The results of the structural equations are expressed in standardized

scores. The measures of fit listed in Table 24 were applied to test the adequacy of the

models.

Table 24: Measures and suggested thresholds applied to assess SEM model fit

Measure

Class of

Measure Chi-squared (X2) Absolute Degrees of Freedom (df ) Absolute Significance Absolute

RMSEA Absolute

RMR Absolute GFI Absolute AGFI Absolute CFI Incremental IFI Incremental NNFI Incremental Normed chi-squared Parsimony AIC Parsimony

Smaller values indicate better fit; < 0.10 indicates good fit; <0.05 very good fit;

<.001 indicate and outstanding fit to the data.

<0.05 - 0.08

(overfit) 1.0 < X2 / df < 3.0 (underfit)No defined level, smaller is better.

Data Fit to the Model (Suggested Thresholds)

Non-significant; (at p < 0.05)

> 0.95

> 0.90 > 0.90 > 0.95 > 0.95

> 0p > 0.05

The parsimony, incremental, and absolute measures of fit were employed in a theory-

driven approach that was applied to scientifically infer the adequacy of the

comparative fit of a model over its competing alternatives (Bollen, 1989b). The

absolute measures, that compare the hypothesised model with no model at all (Hu &

Bentler, 1995), were assessed at the five percent level of significance; p = .05. The

Chi-square statistic, χ2, was used to determine how well the hypothesised model

fitted the population. χ2 tested the null hypothesis, H0: Σ= Σ(Θ), that there was a

significant difference between the covariance matrix of the hypothesised model,

Σ(Θ), and the population covariance matrix, Σ. This effectively tested the extent to

which the residuals in the structural equations were zero; Σ- Σ(Θ) = 0 (Byrne, 1998),

p.110). In seeking no difference between the models, that is non-significance at the p

= 0.05 level or greater, model saturation was avoided by maintaining the degrees of

103

freedom, 1/2(q)(q+1)-k, a function of the number of variables in the model, q, and

the number of parameters to be estimated, k, at one or above.

In addition to the χ2 statistic, the Root Mean Square Error of Approximation

(RMSEA), Root Mean Residual (RMR), Goodness-of-Fit Index (GFI) and the

Adjusted Goodness-of-Fit Index (AGFI) measures were also used to assess absolute

model fit. RMSEA was used to determine ‘how well the model, with unknown but

optimally chosen parameter values, fit the population covariance matrix were it

available’ (Steiger & Lind, 1980 in Byrne, 1998, p. 112). RMSEA values below .05

were considered indicative of very good model fit to the data. To enable

interpretation of the average error or discrepancy between the sample observed and

the hypothesised correlation matrix (Hu & Bentler, 1995), standardised RMR values

of .05 or less were sought. Additionally, Goodness of Fit (GFI), at the 0.9 or above

level, was used to assess the relative amount of variance and covariance in the

observed data that was jointly explained by that data. Finally, the AGFI measure, at

the 0.9 or above level, was used to take into account the inclusion or exclusion of

additional parameters in the respecified models. To adjudge degrees between lack of

fit (0) and perfect fit (1), to maintain independence from the effect of sample size on

χ2, and to assist with progressive improvement in model fit, incremental and

parsimony measures were considered (Kelloway, 1998, p. 26).

Incremental measures of the Comparative Fit Index (CFI), Incremental Fit Index

(IFI), and the Non-Normed-Fit Index (NNFI) were used as the basis for post hoc

analysis that sought to consider the alternative models and respecify those models

such that they fitted the data better than the baseline, the a priori model. The CFI

was used to assess whether the model under investigation was better than a

competing model(s) (Kelloway, 1998) and the NNFI was applied to assess the

progressive percentage improvement of the respecified model alternatives over the

baseline model. The IFI, instead of the Normed-Fit-Index, was used to progressively

assess incremental fit (Kelloway, 1998, p. 31) and parsimony in the model

alternatives, IFI accounts for sample size by taking into account the possibility that a

smaller sample size could possibly lead to an underestimation in model fit (Bollen,

1989a, p. 117). However, the sample size in this study satisfied the adequacy

104

requirements of being between five and ten times the size of the number of estimated

parameters (Kelloway, 1998, p. 20).

Other measures of parsimony applied in consideration of the model alternatives

better fitting the data included the Normed Chi-squared and the Akaike Information

Criteria (AIC) (Akaike, 1987 in Byrne, 1998). While the AIC has no predefined

value, it was used to assess progressive improvement in the parsimony by taking into

account the number of estimated parameters and the statistical goodness-of-fit of the

model alternatives (Kelloway, 1998, p.33). Finally, while some (Kelloway, 1998)

consider that the Normed Chi-squared, the ratio of the χ2 statistic relative to its

degrees of freedom, χ2/df, to be highly dependent on modeller’s experience, this ratio

was only used as a general indicator that a model was in need of further modification

(Joresborg & Sorbom, 1996).

While the above-discussed measures of model fit provided empirical-based guidance

towards optimal model fit to the data, such data-driven analysis can lead to the

undesirable over-fitting of the models that can dilute their theoretical foundation

(Cliff, 1983). Therefore, a theory-driven approach, based on scientific inference, was

adopted to compare plausible models by using an elimination process to determine

the ‘fittest’ to survive (Bollen, 1989b, p. 71). The next section initiates Step 1 of the

three-step approach (Anderson & Gerbing, 1988) to the structural equation model

fitting and assessment process by testing the one-factor congeneric CFA

measurement models of trust and its antecedents.

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6.1.3.2 The One-factor Congeneric Measurement Models of Intention to Trust and its Antecedents

This Confirmatory Factor Analysis (CFA) seeks parsimony by assessing the impact

of the exogenous latent factors, Ability, Benevolence, Integrity and the endogenous

latent factor, Intention to Trust, on their set of observed variables (Mayer et al.,

1995). CFA is the method of choice (Kenny & Kashy, 1992; Marsh & Grayson,

1995) and is based upon the taxonomy of nested models comparison (Widaman,

1985) and reflects the application by Byrne & Bazana (1996).

6.1.3.3.1 Intention to Trust Congeneric Model

6.1.3.3.2 The Initial Intention to Trust Model, All Y-Variables Included

The initial model included all questionnaire items from the published measure for the

Intention to Trust endogenous factor (Mayer & Davis, 1999). The items did not load

adequately onto the latent factor (Table 25). The individual standardised parameter

estimates varied between - .15 and .72 and questionnaire item Itt7 (λ7,1) parameter

was not statistically significant (Bollen, 1989a; Joresborg & Sorbom, 1996). Ranging

between .00 and .52, the Squared Multiple Correlations (R2) were problematic (Table

25). These preliminary results indicated that the variables were not reliably serving

as adequate measures to the underlying construct (Bollen, 1989a).

Table 25: Y–Variable Squared Multiple Correlations - initial model; N = 224

Item Itt1 Itt2 Itt3 Itt4 Itt5 Itt6 Itt7 Itt8 Itt9 I tt10 Standardised Parameter Estimates

.53 .45 .57 .68 .62 .72 -.01 .63 .65 .65

R2 .226 .240 .323 .466 .380 .512 .000 .400 .517 .425

Model fit to the data could only be achieved after the removal of six Y-Variables

and, subsequently, less than half of the variance extracted was explained by Intention

to Trust. Examination of the Y-Variables excluded from the models identified that

four of the six items were the negative-worded questions.

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Negative-worded questionnaire items complicate the interpretation of CFA results

(Williams, Ford, & Nhung, 2002, p. 376). Studies have identified that wording

effects impact on the factor structure (Harvey, Billings, & Nilan, 1985) and this can

detrimentally affect construct variance. Negative-worded items have also been found

to complicate the interpretation of alternative analysis methods like Exploratory

Factor Analysis (EFA) (Williams et al., 2002, pp. 377-379). Negatively worded

questions introduce an affective factor that has the potential to reduce trait variance

by up to 20% (Rogelberg, 2002). The cognitive response from subjects differs when

questions are positive or negatively worded. For example, a subject tends to look for

how much is in the glass when we use a positive-worded question like; ‘Is the glass

half full?’. Alternatively, a negative-worded question like ‘Is the glass half empty?’

affects a subject differently and results in an altered cognitive response (Williams et

al., 2002).

To bypass the issue one could singularly ‘use positively worded questionnaire items

to avoid the irrelevant construct factor’ (Rogelberg, 2002, pp. 377-379). However,

negatively worded questions contribute to the internal validity of a study by

minimising common method variance and consistency bias (Cavana et al., 2001, p.

229). Negatively worded questions make the subject think and provide direct

feedback to the researcher on whether the subjects understood the questions. An

alternative method provides for the benefits of negatively worded questions as well

as the inclusion of an item-wording factor that has been found to improve CFA

model fit and subsequent interpretation. The inclusion of an orthogonal Reverse-

Coded Method Factor (RCMF) has been has been shown to account for the affective

factor that can confound models incorporating negative-worded questionnaire items

(Williams et al., 2002, p.375). In consideration of a subject’s altered cognitive

response to negative-worded questionnaire items and a resultant detrimental effect on

variance, an RCMF factor was included in the initial and respecified Intention to

Trust CFA models.

In support of retaining negatively-worded questionnaire items, the initial Intention to

Trust CFA model included all the questionnaire items and the RCMF factor that

sought to explain the negatively worded questionnaire items; Itt1, Itt3, Itt5 and Itt8.

Based on their standardised parameter estimates, these items loaded more adequately

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onto the latent factor, Intention to Trust (Table 26). Other than item Itt7 which

remained non-significant, the individual standardised parameter estimates all

exceeded .41 and were statistically significant (Bollen, 1989a; Joresborg & Sorbom,

1996). The Squared Multiple Correlation (R2) for item Itt7 continued to be

problematic; the R2 values for the other items ranged between .23 and .51. These

preliminary results indicated that the variables were more adequately serving as

measures to the underlying construct (Bollen, 1989a).

Table 26: Squared Multiple Correlations for the Y–Variables in the initial model with the RCMF; N = 224

Item Itt1 Itt2 Itt3 Itt4 Itt5 Itt6 Itt7 Itt8 Itt9 I tt10 Standardised Parameter Estimates with ITT

.43 .51 .47 .68 .45 .73 .02 .80 .67 .67

Standardised Parameter Estimates with ITT and RCMF

.41 .44 .60 .41 .

R2 with ITT

.226 .240 .323 .466 .380 .512 .000 .400 .517 .425

R2 with RCMF and ITT

.358 .259 .409 .460 .596 .54 .000 .460 .64 .452

However, the overall measures of fit suggested problems with the model (χ2 (31)

117.70 at p = .00; RMSEA = .112; AGFI = .831; CFI = .877; IFI = .877; NNFI =

.821). The covariance matrix of the hypothesised model was significantly different to

the covariance matrix of the sample data (Bollen, 1989a) and suggests that re-

specification is needed to improve the model fit to the sample data. Examination of

the modification indices identified that four items were problematic; Itt2, Itt3, Itt7

and Itt9. Item Itt2, I would be willing to let this group have complete control over an

assignment that was critical to me; item Itt3, If I joined this group, I feel I need to

keep an eye on what other group members do; item 7, This group should be honest

about their knowledge, and; item Itt9, I feel I could rely on the skills and abilities of

this group. Even though these items were theory-based, they were found to have

correlated errors and high fitted residuals. Therefore I conclude that, in the context

108

projected by the vignettes, this sample from the population of Business Faculty

Undergraduate Students are associating or confusing the meaning of these items.

The items could be classically dealt with by including within-variable correlated

errors to improve model fit (Joresborg & Sorbom, 1996). However, the correlation of

measurement errors and the additional parameters arising from their use generates

additional error terms, which can result in a corresponding loss of the meaning and

dilute the substantive conclusions that can be drawn from a model (Gerbing &

Anderson, 1984). A more parsimonious first order CFA structure with fewer

parameters to satisfactorily account for the observed covariance matrix is preferred

(Gerbing & Anderson, 1984, p. 579). Additionally, the use of fewer parameters

avoids degrees-of-freedom penalties that can detrimentally affect the GFI and AGFI

absolute indices (Byrne, 1998, p. 116; Kelloway, 1998, pp. 32-33). Therefore, it was

decided not to correlate the measurement errors in the models but instead to test a

series of plausible theory-based models (Bollen, 1989a, p. 71) that progressively

excluded Intention to Trust items Itt2, Itt3, Itt7 and Itt9 to identify a respecified

congeneric CFA model that optimally fitted to the observed covariance matrix.

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6.1.3.3.3 The Re-specified Intention to Trust Congeneric Mode that excludes Items Itt2, Itt3, Itt7 and Itt9

The respecified congeneric model excluded items Itt2, Itt3, Itt7 and Itt9 from the

published scale (Mayer & Davis, 1999) for the Intention to Trust endogenous factor

(Figure 19). The individual standardised parameter estimates for ITT (Figure 19) all

exceeded .46 and were statistically significant (Bollen, 1989a).

Figure 19: Standardised Solution for the respecified Congeneric CFA Model of the endogenous factor Intention to Trust; items Itt2, Itt3, Itt7 a nd Itt9 excluded

The items appeared to load adequately onto the latent factor (Table 27). The Squared

Multiple Correlations (R2) for each variable ranged between .33 and .63 indicating

that the variables were reasonably serving as adequate measures to the underlying

construct (Bollen, 1989a). Additionally, the model-based measures of scale

reliability, construct reliability and variance extracted (Table 28) were within

suggested thresholds (Coote, 2006).

110

Table 27: Y–Variable Squared Multiple Correlations - the respecified ITT model; N = 224

Item Itt1 Itt4 Itt5 Itt6 Itt8 Itt10 R2 .326 .449 .626 .540 .480 .393

Table 28: Model-based measures of scale reliability - the respecified ITT model, N = 224

Variance Extracted (λ2)/Σ(λ2)+Σ(δ) =

>0.5 0.530

Construct Reliability Σ(λ)2/Σ(λ)2+Σ(δ) =

>0.7 0.916

Suggested Thresholds Measure of Scale Reliability

The overall measures of fit suggest that re-specification had improved model fit;

(χ2 (6) 9.36 at p = .154; RMSEA = .05; AGFI = .952; CFI = .990; IFI = .991; NNFI =

.976). The Chi-square difference, χ2diff = (25) 108.34, between the initial and

respecified models (Table 29) was significantly larger than the χ2 CRIT (25) p = .05:

37.6525; therefore re-specification had improved model fit to the data.

Table 29: Summary of model fit improvement between the initial ITT model and the respecified ITT model; N = 224

Model χχχχ2 df p = .05 Non-significant? RMSEA RMSEA

Improved? Initial Model 117.7 31 .0000 no .182 Respecified Model 9.36 6 .154 yes .05 yes

Chi-square Difference: 108.34 25 .05

There was no significant difference between the covariance matrix of the

hypothesised model and the covariance matrix of the sample data (Bollen, 1989a)

and suggested that further re-specification was not needed to improve the model fit to

the sample data. A congeneric CFA analysis follows for the Integrity, Benevolence

and Ability exogenous factors.

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6.1.3.3.4 Ability Congeneric CFA Model

6.1.3.3.5 Initial Ability Model; All Questionnaire Items Included

The initial model included all questionnaire items from the published measure for the

Ability exogenous factor (Mayer & Davis, 1999). The items loaded adequately onto

the latent factor (Table 30). The individual standardised parameter estimates all


1996); and the Squared Multiple Correlations (R2) for each variable ranged between

.62 and .79 indicating that the variables were reliably serving as adequate measures

to the underlying construct (Bollen, 1989a).

Table 30: Squared Multiple Correlations for the X–Variables; N = 224

Item Ab1 Ab2 Ab3 Ab4 Ab5 Ab6 Standardised Parameter Estimates

.84 .86 .82 .89 .79 .83

R2 .71 .73 .68 .79 .62 .70

However, the overall measures of fit suggested some problems with the model

(χ2 (9) = 37 at p < .01; RMSEA = .118; AGFI = .878). The covariance matrix of the

hypothesised model was significantly different to the covariance matrix of the

sample data and suggested that re-specification was needed to improve the model fit

to the sample data (Bollen, 1989a). Examination of the modification indices

identified that three items were problematic: Item Ab1, The group is very capable of

performing its job; Item Ab5, The group has specialized capabilities that could

increase my performance; Item Ab6, The group is well qualified. These items had

correlated errors and high fitted residuals. Therefore it was concluded that, in the

context projected by the vignettes, this sample from the population of Business

Faculty Undergraduate Students are associating or confusing the meaning of these

items. The items could be classically dealt with by including within-variable

correlated errors to improve model fit (Joresborg & Sorbom, 1996). However,

consistent with the model trimming process applied to ITT, it was decided not to

correlate the measurement errors in the models but instead to test a series of plausible

theory-based models (Bollen, 1989a, p. 71) that progressively excluded Ability items

112

Ab1, Ab5 and Ab6 to identify a respecified congeneric CFA model that optimally

fitted the observed covariance matrix.

6.1.3.3.6 The Re-specified Ability Congeneric CFA Model that excludes Items Ab1, Ab5 and Ab6.

The respecified congeneric model excluded items Ab1, Ab5 and Ab6 from the

published scale for the Ability exogenous factor (Mayer & Davis, 1999). The

individual standardised parameter estimates (Figure 20) all exceeded .84 and were

statistically significant (Bollen, 1989a).

Figure 20: Standardised solution for the respecified congeneric CFA model of the trust antecedent Ability; items Ab1, Ab5 and Ab6 excluded

All the items appeared to load adequately onto the latent factor (Table 31). The

Squared Multiple Correlations (R2) for each variable ranged between .71 and .77

indicating that the variables were reliably serving as adequate measures to the

underlying construct (Bollen, 1989a). Additionally, the model-based measures of

scale reliability, construct reliability and variance extracted (Table 32) were within


113

Table 31: Table A3.1: Squared Multiple Correlations for the X – Variables for the respecified Ability Congeneric model; N = 224

Item Ab2 Ab3 Ab4 R2 .71 .71 .77

Table 32: Table A3.2: Model-based measures of scale reliability for the respecified Ability Congeneric model; N = 224

Suggested Thresholds

>0.7

>0.5


Variance Extracted Σ(λ2)/Σ(λ2)+Σ(δ) =

0.9

0.7

Measure of Scale Reliability

The overall measures of fit suggested that re-specification had improved model fit;

χ2 (1) = .00 at p > .05; RMSEA = .000; AGFI = .989). The Chi-square difference,

χ2 diff = (8) 37, between the initial and respecified models (Table 33) was significantly

larger than the χ2 CRIT (8) p = .05: 15.5073; therefore re-specification had improved

model fit to the data.

Table 33: Summary of model fit improvement between the initial and respecified Ability models; N = 224


Improved? Initial Model 37 9 .00003 no .118 Respecified Model 0.00 1 .622 yes .0001 yes

Chi-squared Difference: 37 8 .05

There was no significant difference between the covariance matrix of the

hypothesised model and the covariance matrix of the sample data (Bollen, 1989a)

and suggested that further re-specification was not needed to improve the model fit to

the sample data. A congeneric CFA analysis follows for the Integrity and

Benevolence exogenous factors.

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6.1.3.3.7 Benevolence Congeneric CFA Model

6.1.3.3.8 Initial Benevolence Model; All X-Variables Included

The initial model included all the items from the published measure for the Ability

exogenous factor (Mayer & Davis, 1999). The items appeared to load adequately

onto the latent factor (Table 34). The individual standardised parameter estimates all


1996). However, the Squared Multiple Correlations (R2) for each variable ranged

between .32 and .77 indicating that variable Ben 3 (R2 = .32) was marginally serving

as adequate measure to the underlying construct (Bollen, 1989a).

Table 34: Squared Multiple Correlations for X – Variables; N = 224

Item Ben1 Ben2 Ben3 Ben4 Ben5 Standardised Parameter Estimates

.88 .88 .57 .81 .72

R2 .77 .77 .32 .66 .52

Additionally, the overall measures of fit suggested some problems with the model

(χ2 (5) 41.75 at p < .01; RMSEA = .182; AGFI = .791; NNFI = .889). The covariance

matrix of the hypothesised model was significantly different to the covariance matrix

of the sample data (Bollen, 1989a) and suggested that re-specification was needed to

improve the model fit to the sample data. Examination of the modification indices

identified that two items were problematic: Item Ben2, ‘My needs and desires will be

very important to the group’ and item Ben3, ‘The group would not knowingly do

anything to hurt me’. These items were found to have correlated errors and high

fitted residuals. In addition, Benevolence did not explain the majority, 68%, of the

variance associated with Item Ben3 (Table 34). Therefore it was concluded that, in

the context projected by the vignettes, this sample from the population of Business

Faculty Undergraduate Students are associating or confusing the meaning of these

items. The items could be classically dealt with by including within-variable

correlated errors to improve model fit (Joresborg & Sorbom, 1996). However,

consistent with the re-specification process for the Ability congeneric CFA model, it

was decided not to correlate the measurement errors but instead test a series of

plausible theory-based models (Bollen, 1989a, p. 71) that progressively excluded

115

Benevolence items Ben2 and Ben3 to identify a respecified congeneric CFA model

that optimally fitted to the observed covariance matrix.

6.1.3.3.9 The Re-specified Benevolence Congeneric CFA Model that excludes items Ben2 and Ben3.

The respecified model excluded items Ben2 and Ben3 from the published scale

(Mayer & Davis, 1999) for the Benevolence exogenous factor. The individual

standardised parameter estimates (Figure 21) all exceeded .78 and were statistically

significant (Bollen, 1989a).

Figure 21: Standardised Solution for the Re-specified Congeneric CFA Model of the trust

Antecedent Benevolence; items Ben2 and Ben3 excluded

Items appeared to load adequately onto the latent factor (Table 35). The Squared


that the variables were reliably serving as adequate measures to the underlying




116

Table 35: Squared Multiple Correlations for the X–Variables in the respecified Benevolence model

Item Ben1 Ben4 Ben5 R2 .62 .73 .60

Table 36: Model-based measures of scale reliability for the respecified Benevolence model


Variance Extracted Σ(λ2)/Σ(λ2)+Σ(δ) =

Suggested Thresholds Measure of Scale Reliability

>0.7

>0.5

0.8

0.6


(χ2 (1) .08 at p > .05; RMSEA = .000; AGFI = .989). The Chi-square difference, χ2

diff = (3) 41.67, between the initial and re-specified models (Table 37) was

significantly larger than the χ2 CRIT (3) p = .05: 7.8173.

Table 37: Summary of Model Fit Improvement between the initial and respecified Benevolence models; N = 224


Improved? Initial Model 41.75 5 .0000 no .182 Re-specified Model

0.08 2 .7716 yes .000 yes

Chi-squared Difference 41.67 3 0.05

The respecified model had significantly improved model fit to the data. There was

no significant difference between the covariance matrix of the hypothesised model

and the covariance matrix of the sample data (Bollen, 1989a) and suggests that

further re-specification was not needed to improve the model fit to the sample data.

The congeneric CFA measurement model for Integrity is now analysed.

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6.1.3.3.10 Integrity Congeneric CFA Model

6.1.3.3.11 Initial Integrity Model; All X-Variables Included

The initial model included all six items from the published measure for the Integrity

exogenous factor (Mayer & Davis, 1999). All items loaded adequately onto the latent

factor except Int4 (Table 38). Other than Int4 (λx41 = .27), the individual standardised

parameter estimates all exceeded .60 and were statistically significant (Bollen,

1989a; Joresborg & Sorbom, 1996). Additionally the Squared Multiple Correlations

(R2) for each variable, except Int4 (R2 = .075), ranged between .36 and .79 indicating

that all variables except Int4 were reliably serving as adequate measures to the

underlying construct (Bollen, 1989a).

Table 38: Squared Multiple Correlations for the X – Variables in the initial Integrity model

Item Int1 Int2 Int3 Int4 Int5 Int6 Standardised Parameter Estimates

.76 .60 .64 .27 .89 .80

R2 Value 0.578 0.364 0.475 0.075 0.789 0.643 However, the overall measures of fit suggest some problems with the model

(χ2 (9) = 31.63 at p < .01; RMSEA = .106; AGFI = .895). The covariance matrix of

the hypothesised model was significantly different to the covariance matrix of the

sample data (Bollen, 1989a) and suggested that re-specification was needed to

improve the model fit to the sample data. Examination of the modification indices

identified that three items were problematic: Int4, Int5 and Int6. In particular, the

estimate of a structural relationship capturing the impact of a latent variable,

Integrity, on the observed variable, item Int4, was low at 0.27. In addition, perhaps

because Int4 it was the only negatively worded item and not clearly understood by

this sample from the Business School Undergraduate Student population, 92% of the

variance associated with Int4 was unexplained by Integrity. Item Int6, ‘Sound

principles seem to guide the group’s behaviour’ and item Int5, ‘I like the group’s

values’ were also problematic; these items were found to have correlated errors and

high fitted residuals. Therefore it was concluded that, in the context projected by the

vignettes, this sample from the population of Business Faculty Undergraduate

Students are associating or confusing the meaning of these items. The items could be

classically dealt with by including within-variable correlated errors to improve model

118

fit (Joresborg & Sorbom, 1996). However, consistent with the re-specification

process for the Ability congeneric CFA model, it was decided not to correlate the

measurement errors but instead to test a series of plausible theory-based models

(Bollen, 1989a, p. 71) that progressively excluded Integrity items Int4, Int5 and Int6

to identify a respecified congeneric CFA model that optimally fitted to the observed

covariance matrix.

6.1.3.3.12 The Re-specified Integrity Congeneric Model that excludes items Int4, Int5 and Int6

The respecified model excluded items Int4, Int5 and Int6 from the published scale

(Mayer & Davis, 1999) for the Integrity exogenous factor. The individual

standardised parameter estimates (Figure 22) all exceeded .69 and were statistically

significant (Bollen, 1989a).

Figure 22: Standardised Solution for the respecified Congeneric CFA model of the trust Antecedent Integrity; Items Int4, Int5 and Int6 excluded

The items appeared to load adequately onto the latent factor (Table 39). The Squared


that the variables were reliably serving as adequate measures to the underlying


119



Table 39: Squared Multiple Correlations for the X – Variables in the initial Integrity model

Item Int1 Int2 Int3 R2 Value 0.51 0.48 0.54

Table 40: Model-based measures of scale reliability for the respecified Integrity model

0.515

0.761


Construct Reliability Σ(λ)2/Σ(λ)2+Σ(δ) = >0.7

Variance Extracted Σ(λ2)/Σ(λ2)+Σ(δ) = >0.5



χ2 (2) = .65 at p = 0.214; RMSEA = .000; AGFI = .994). The Chi-square difference,

χ2 (7) = 30.98 at p = 0.5, between the initial and re-specified models (Table 41) was

significantly larger than the χ2 CRIT (7), p = .05: 14.0671.

Table 41: Summary of Model Fit Improvement between the initial and respecified Integrity models; N = 224

Model χχχχ2 df p = 0.05 Non-significant? RMSEA RMSEA

Improved? Initial Model 31.63 9 0.00003 no 0.106 Respecified Model 0.65 2 0.72168 yes 0.000 yes

Chi-squared Difference 30.98 7 0.05

The respecified had significantly improved model fit to the data. There was no

significant difference between the covariance matrix of the hypothesised model and

the covariance matrix of the sample data (Bollen, 1989a) and suggested that re-

specification was not needed to improve the model fit to the sample data. The first

order CFA model of Ability, Benevolence and Integrity is now analysed.

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6.1.3.3.13 First Order CFA Model of the Trust Antecedents

The First Order CFA model incorporated the resultant measurement models from the

preceding congeneric confirmatory factor analysis of the Intention to Trust

antecedents; Ability, Benevolence and Integrity. In seeking to operationalise the

measurement models, combinations of Ability, Benevolence and Integrity were

tested to support the hypothesis that a three (oblique) factor model optimally explains

Intention to Trust and its antecedents.

6.1.3.3.14 The Oblique Three-factor Model

A test of an initial model, that included all the X-variables for the trust antecedents of

Ability, Benevolence and Integrity, did not fit the covariance matrix of the observed

data (GFI = .846, AGFI = .797; NNFI = .892). This result supported the preceding

congeneric measurement modelling process that resulted in trimmed models that

excluded X-Variables to fit the covariance matrix of the observed data. It was

hypothesised that a respecified first order CFA model incorporating the resultant

item exclusions from the congeneric CFA modelling process of the trust antecedents

Ability, Benevolence and Integrity would better fit the covariance matrix of the

observed data (Figure 23).

Figure 23: Standardised Solution for the respecified first order CFA model of the trust

antecedents; Ability, Benevolence and Integrity; N = 224

121

The items in the respecified model loaded adequately onto the latent factors (Table

42). The individual standardised parameter estimates all exceeded .63 and were

statistically significant (Bollen, 1989a); (Joresborg & Sorbom, 1996); and the

Squared Multiple Correlations (R2) for each variable ranged between .39 and .77

indicating that the variables were reliably serving as adequate measures to the

underlying construct (Bollen, 1989a). Additionally, the model-based measures of

scale reliability, construct reliability and variance extracted (Table 43) were within


Table 42: Squared Multiple Correlations for the X–Variables for the respecified three-factor CFA model; N = 224

Item Ab2 Ab3 Ab4 Ben1 Ben4 Ben5 Int1 Int2 Int3 Standardised Parameter Estimates

.84 .84 .88 .76 .87 .83 .79 .63 .70

R2 0.704 0.709 0.775 0.584 0.670 .685 0.626 0.391 .497

Table 43: Model-based measures of scale reliability for the respecified three-factor CFA model; N = 224

Variance Extracted (λ2)/Σ(λ2)+Σ(δ) = >0.5 0.605


Construct Reliability Σ(λ)2/Σ(λ)2+Σ(δ) = >0.7 0.937


For the respecified model, all measures of absolute, incremental fit improvement,

and parsimony were within acceptable thresholds (Kelloway, 1998) (RMSEA = .053;

GFI = .963; AGFI = .930; NNFI = .976). However, the respecified model reflecting

the congeneric CFA models of Ability, Benevolence, and Integrity failed to achieve

non-significance (χ2 = (24) = 38.82, p = 0.029) at the p = 0.05 or higher level (Table

44).

Table 44: Summary of model fit difference between the respecified three-factor CFA model and the χχχχ2 threshold for 24 degrees of freedom at p = 0.05

Model χχχχ2 df p = 0.05

Respecified three-factor CFA model 38.82 24 0.029 χ2

THRESHHOLD (24) p = 0.05 36.42 24 0.05 Chi-square Difference at p = .05 2.40 0 0.05

There was a difference between the covariance matrix of the hypothesised model and

that of the observed data (Bollen, 1989b). However, the Chi-square difference

122

(χ2 (1)

= 2.4, p = 0 .05) was considered insufficient to warrant model refitting. Model

differences in the order of 2 are considered insufficient justification for the re-

specification of a model (Kelloway, 1998). Given the minimal Chi-squared

difference, the model was assessed as supporting the hypothesis that the respecified

three-factor CFA model fits the covariance matrix of the observed data. The

following section seeks to operationalise the model by comparing rival models.

6.1.3.3.15 Operationalising of the CFA Model

To clarify relationships between the observed variables and the exogenous factors,

rival models comparison tested the multidimensionality of the hypothesised three-

factor (oblique) CFA model. The comparison of the rival CFA models with the

hypothesised three-factor (oblique) CFA model sought to support the foundation

theory for this study, that the antecedents of Ability, Benevolence and Integrity

explain our Intention to Trust. However, the high positive correlation (.86) between

Benevolence and Integrity (Figure 23) indicate that, when a member joins a newly

formed work-team, Benevolence and Integrity could collapse into a single exogenous

factor. This was tested using a Two-factor oblique model (Table 45).

Table 45: Variable loading combinations for the comparison of rival First Order CFA Models

Model

Ability variables Ab2, Ab3 and Ab4

loaded on

Benevolence variables Ben1, Ben4 and Ben 5

loaded on

Integrity variables Int1, Int2 and Int3

loaded on Hypothesised Model:

Three-factor (oblique)

Ability BEN INT

Two-factor (oblique)

Ability BENINT

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The Fit indices from the rival models converged, suggesting that the hypothesised

(three oblique factor) model reflecting the theoretical foundation for this study was

superior (Table 46).

Table 46: Fit indices for the competing First Order CFA models of Ability, Benevolence and Integrity identifying the superiority of the three-factor oblique CFA model; N = 224

Model: χ2 df RMSEA RMR GFI AGFI CFI IFI NNFI

Hypothesised

Model:

Three-factor

38.82 24 .053 .036 .963 .930 .984 .984 .976

Two-factor

Ability-

BENINT

73.41 26 .09 .051 .932 .882 .960 .961 .943

In particular, comparison with the rival nested model identifies that the hypothesised

three-factor oblique model provides a superior fit to the data than the competing two-

factor model; the RMSEA measure of absolute measure of fit error has increased to

.09 in the two-factor model (Table 46). The three-factor oblique model better fits the

population covariance matrix from the sample data; all its fit indices are within

acceptable limits.

In conclusion, subsequent to fitting the measurement models of the exogenous

factors and consideration of rival first order CFA models, consistent with the

underlying theory for this study (Mayer et al., 1995), the hypothesised three-factor

(oblique) model better fitted the covariance matrix of the observed data from the

population of Business Faculty Undergraduate Students. The next section pursues a

path analysis of the complete model hypothesising that Ability Benevolence and

Integrity are antecedents of Intention to Trust.

124

6.1.3.3.16 Path Analysis of the Intention to Trust Model

The goal of the path analysis model was a test of Hypothesis H1 that Ability,

Benevolence and Integrity are antecedents of Intention to Trust. The initial path

analysis model that included all the X and Y-Variables did not adequately fit the

covariance matrix of the data: (χ2 (318) = 898.1, p = .000; RMSEA = .09; GFI = .77;

AGFI = .73; CFI = .85; IFI = .85; NNFI = .84). Subsequently, it was hypothesised

that a respecified model concatenating the results of the congeneric models and the

first order CFA models would better fit the covariance matrix of the observed data

(Figure 24).

Figure 24: Standardised solution for the respecified path analysis model of Intention to Trust

and its antecedents Ability, Benevolence and Integrity; N = 224

The items in the respecified model loaded adequately onto the latent factors (Table

47). The standardised parameter estimates of the X and Y-Variables in the

measurement model were statistically significant (Bollen, 1989a); (Joresborg &

Sorbom, 1996); and the Squared Multiple Correlations (R2) for each variable ranged

between .32 and .83 indicating that the variables were reasonably serving as adequate

measures to the underlying construct (Bollen, 1989a).

125

Table 47: Squared Multiple Correlations for the X and Y–Variables in the respecified path analysis model; N = 224

X-Variable Ab1 Ab2 Ab3 R2 0.683 0.668 0.827 X-Variable Ben1 Ben4 Ben5 R2 0.585 0.670 0.684 X-Variable Int1 Int2 Int3 R2 0.605 0.425 0.493 Y-Variable Itt1 Itt4 Itt5 Itt6 Itt8 Itt10 R2 0.318 0.389 0.668 0.669 0.483 0.358

The LISREL output results identified that the fit of the respecified model to the

observed data had significantly improved (χ2 (81) 142, p = .000; GFI = .92; CFI = .96;

IFI = .96; NNFI = .95; RMSEA = .058). Additionally, the Chi-square difference,

χ2diff = (237) = 755.93, p = 0.05, between the initial and respecified models (Table 48)

was significantly larger than the χ2 CRIT (237) p = 0 .05: 236.33, the respecified path

analysis model has improved fit to the covariance matrix of the observed data.

Table 48: Summary of Model Fit Improvement between the initial and respecified path analysis; N = 224.

Model χ2 df p = .05 RMSEA RMSEA Improved?

Initial Model 898.01 318 .00 .106

Respecified Model 142.08 81 .00 .058 yes

Chi-squared Difference 755.93 237 .05

However, the AGFI (.88) measure of absolute fit was marginally outside the

acceptable limit of .9 (Kelloway, 1998, p. 26). In addition, above limit modification

indices (18.65) were associated with item Int2. A model re-specification that

excluded Int2 from the model did not improve the model fit (Table 49).

126

Table 49: Summary of Model Fit Improvement between the respecified path analysis model and the re-specified path analysis model excluding item Int4; N = 224

Model χ2 df p = .05 RMSEA RMSEA Improved?

Respecified Model 142.08 81 .00 .058

Respecified Model excluding item Int2

116.76 68 .000 .057 NO

Chi-squared Difference 25.32 13 .05

The Chi-square difference, χ2diff = (13) 25.32, between the models (Table 53) is

smaller than the χ2CRIT (13) p = 0 .05: 38.8852. Therefore, the respecified model that

tentatively excluded item Int2 did not significantly improve model fit. Additionally,

in consideration of model re-specification, (Kelloway, 1998, p. 37) argues that

‘model differences of one measure probably do not provide sufficient information to

warrant such action’. Therefore, the hypothesised path analysis model in Figure 25

was considered to better fit the covariance matrix of the observed data.

While the measures of fit could be considered acceptable, the test statistic ratio of the

parameter estimate and its standard error, Est/SE, using maximum likelihood

estimation (Bollen, 1989a; Joresborg & Sorbom, 1996), indicated that all parameter

estimates in the structural model were not statistically significant. Benevolence

appeared not to adequately explain Intention to Trust. The parameter (γ12 = - .40, t

value (81) = - 1.88) estimate marginally failed to achieve statistical significance at t (1,

.05) = +/- 1.96 (Kelloway, 1998, p.29). A non-significant parameter could indicate that

Benevolence was unimportant to the model (Byrne, 1998). A competing ‘Two Factor

Model 1’, that excluded the Benevolence exogenous factor, was tested (Table 50).

The absolute measures of model fit indicated the models similarly fitted the

covariance matrix of the observed data; the RMSEA and RMR values of the

competing models were within .002. From a theoretical perspective there is

considerable support for Benevolence as an antecedent of Intention to Trust (Davis,

1999; Serva et al., 2005; Schoorman et al., 1996a); exclusion of Benevolence from

the model would contradict the theoretical foundation for this study (Mayer et al.,

1995) and previous correlation-based support that Benevolence is an antecedent of

Intention to Trust.

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Table 50: Fit indices identifying the superiority of the hypothesised three-factor path analysis model; N = 224

Trust Antecedents

Model: Ability BEN INT χ2 df RMSEA RMR GFI AGFI CFI IFI NNFI

Hypothesised

Model Three-

factor

FR FR FR 142.08 81 .058 .047 .922 .884 .959 .959 .946

Two-factor

Model 1 FR 0 FR 150.48 82 .060 .049 .917 .879 .956 .956 .943

128

Reviewing the hypothesised Three-factor model (Figure 25), the non-significant

negative parameter (γ12 = -.40) between Benevolence and Intention to Trust together

with the high Integrity to Intention to Trust parameter (γ13 = .92) appeared to be

evidence of suppression effect. Suppression effect is present when a parameter is much

larger than the sum of its contributing factors or when positive contributory factors result

in a negative parameter (Cohen, 1988, pp. 76-79; MacKinnon, Krull, & Lockwood,

2000). In the case of the hypothesised Three-factor model (Figure 24), the variables

explained by Benevolence had positive parameters but resulted in a negative parameter

between Benevolence and Intention to Trust. Additionally, in relation to the correlation

of Intention to Trust with its antecedents of Ability (r = .653), Benevolence (r = .357)

and Integrity (r = .639), the Integrity to Intention to Trust parameter was

disproportionately large (γ13 = .92). This evidence, together with the high correlation (r

= .86) between the exogenous factors of Benevolence and Integrity in the first order

CFA model of the trust antecedents, support the presence of suppression effect.

One way to deal with suppression effect is to follow the method of Yuan et al. (2005)

and combine the two highly correlated measures; in this case Benevolence and Integrity.

This method was tested earlier and was unsuccessful; a Two-factor CFA model was an

inferior fit to the covariance matrix of the observed data (Table 45). The hypothesised

Three-factor model better fitted the covariance matrix of the observed data. Consistent

with the theory, Ability, Benevolence and Integrity are considered antecedents of

Intention to Trust. While, the preceding tests supported the hypothesis that Benevolence

does have an effect on Intention to Trust and discounted the (Yuan et al. (2005) method

of dealing with suppression effect, these analyses do not provide evidence concerning

Hypothesis H3, which of the Intention to Trust antecedents is most salient. The following

Analysis of Variance (ANOVA) seeks evidence by examining the simple main and

indirect effects of the trust antecedents of Ability, Benevolence and Integrity on

Intention to Trust.

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6.1.4 ANOVA of Intention to Trust and its Antecedents of Ability, Benevolence and Integrity

To review the reasons for the dual 2x2 ANOVA; Stage 1 of the study identified that

vignettes depicting dimensionally opposite Information Levels of Benevolence and

Integrity were perceived by the subjects as being unrealistic. This resulted in a dual 2x2

factorial design where a subject was exposed to a single vignette depicting High or Low

Information Levels of Ability and Benevolence or a vignette depicting High or Low

Information Levels of Ability and Integrity (Tables 51 and 52).

Table 51: 2x2 Factorial design for the manipulation of the High and Low Information Levels for Ability and Benevolence

Trust Antecedent

Ability Benevolence High Low High Low

X X X X X X X X

Table 52: 2x2 Factorial design for the manipulation of High and Low Information Levels for Ability and Integrity

Trust Antecedent

Ability Integrity High Low High Low

X X X X X X X X

130

6.1.4.1 Manipulation Checks To add weight to the SEM analysis that identified that the experimental manipulations

embedded in the vignettes had been effective, a series of manipulation checks were

conducted using SPSS for Windows version 13 (SPSS, 2004). Each experimental

condition was assessed using a series of t-tests that supported a claim that the

participants rated the groups differently and congruent with the direction of

manipulation. For each test, the IV value was the summated scale for the variable as

completed after the participant read the vignette. The results indicate that:

• The High Ability Information Level group exhibited a significantly different

mean than the Low Ability Information Level group; (t(178.62) = -15.061, p =

.000).

• The High Benevolence Information Level group exhibited a significantly

different mean than the Low Benevolence Information Level group; (t(119) =

-9.237, p = .000).

• The High Integrity Information Level group exhibited a significantly different

mean than the Low Integrity Information Level group; (t(89.687) = -5.73, p = .000).

These results support the previous claim that all three experimental manipulations had

been successful. The effects of Ability and Integrity on Intention to Trust is next

analysed.

131

6.1.4.2 ANOVA of the effects of Ability and Integrity on Intention to Trust A 2x2 ANOVA evaluated the effects of combinations of High and Low Information

Levels of Ability and Integrity on Intention to Trust. The means and standard deviations

for Intention to Trust as a function of the two variables are presented in Table 53.

Table 53: Descriptive Statistics of the Dependent Variable: Intention to Trust for Groups with High and Low Information Levels of Ability (ability) and Integrity (integ)

ability integ Mean Std. Deviation N 1.00 low 26.0000 6.25833 25 2.00 high 27.7452 5.12036 26

1.00 low

Total 26.8897 5.71711 51 1.00 low 30.0400 6.37293 26 2.00 high 32.7597 3.88109 26

2.00 high

Total 31.3998 5.40168 52 1.00 low 28.0596 6.57781 51 2.00 high 30.2524 5.16191 52

Total

Total 29.1667 5.97880 103

A Levene’s Test of Equality of Error Variances indicated that the error variance of the

dependent variable was homogenous across the four groups and suggests this stated

assumption of ANOVA was not broken; (F(3,99) = 1.623, p = .189). The ANOVA

indicated a significant between-subjects main effect for Ability (F(3,99) = 17.485, p =

.000, η2 = .19); 19% of Intention to Trust was explained by Ability. Integrity also had a

significant main effect (F(3,99) = 4.252, p = .042) but the effect size (η2 = .04) was small

(Tabachnick & Fidell, 2007, p. 55). The interaction between Ability and Integrity was

trivial (η2 = .002) and not significant (F(3,99) = .203, p = .65). Plots (Figures 25 and 26)

of the interaction between the independent variables on the dependent variable identified

that High and Low Information Levels of Ability and Integrity made a significant

difference in the estimated marginal means of the DV, Intention to Trust.

132

Figure 25: Estimated Marginal Means of Intention to Trust with Low or High Integrity

highlow

Ability

33.00

32.00

31.00

30.00

29.00

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27.00

26.00

Est

imat

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argi

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eans

high

lowIntegrity

highlow

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133

Figure 26: Estimated Marginal Means of Intention to Trust for groups with Low or High Ability

highlow

Integrity

33.00

32.00

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30.00

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28.00

27.00

26.00

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134

6.1.4.3 ANOVA of the effects of Ability and Benevolence on Intention to Trust

The 2x2 ANOVA evaluated the effects of combinations of High and Low Information

Levels of Ability and Benevolence on Intention to Trust. The means and standard

deviations for Intention to Trust as a function of the two variables are presented in Table

54.

Table 54: Descriptive Statistics of the Dependent Variable: Intention to Trust for Groups with High and Low Information Levels of Ability (ability) and Benevolence (benev)

A Levene’s Test of Equality of Error Variances indicated that the error variance of the

dependent variable was homogenous across the four groups and suggests this stated

assumption of ANOVA was not broken; (F(3,117) = 1.202, p = .312). The ANOVA

indicated a significant between-subjects main effect for Ability (F(3,121) = 47.293, p =

.000, η2 = .29); 29% of Intention to Trust was explained by Ability. Benevolence also

had a significant main effect (F(3,121) = 4.533, p = .035) but the effect size (η2 = .04) was

small (Tabachnick & Fidell, 2007, p. 55). The interaction between Ability and

Benevolence was small (η2 = .04) but significant (F(3,121) = 4.722, p = .032). Based on

these results, the Intention to Trust of the sample appears to be affected to a greater

extent by Ability than Benevolence, which appears to have a weak effect on Intention to

Trust.

22.8433 5.46458 29

26.6552 5.12191 29

24.7493 5.59035 58

30.8622 5.08779 3130.8233 3.70887 32

30.8425 4.40494 63

26.9864 6.60786 60

28.8418 4.87389 61

27.9218 5.84919 121

benev1.00 low

2.00 high

Total

1.00 low

2.00 high

Total

1.00 low

2.00 high

Total

ability1.00 low

2.00 high

Total

Mean Std. Deviation N22.8433 5.46458 29

26.6552 5.12191 29

24.7493 5.59035 58

30.8622 5.08779 3130.8233 3.70887 32

30.8425 4.40494 63

26.9864 6.60786 60

28.8418 4.87389 61

27.9218 5.84919 121

benev1.00 low

2.00 high

Total

1.00 low

2.00 high

Total

1.00 low

2.00 high

Total

ability1.00 low

2.00 high

Total

Mean Std. Deviation N

135

A plot (Figure 27) of the interaction between the independent variables on the dependent

variable identified that High and Low Information Levels of Ability has a significant

difference on Intention to Trust for groups with High (F(1,117) = 40.641, p = .000) and

Low (F(1,117) = 11.149, p = .001) Information Levels of Benevolence. However, the

effect of a High Information Level of Ability was so high (Observed Power = 1.0) that

High or Low Information Levels of Benevolence had little or no effect on Intention to

Trust

Figure 27: Estimated Marginal Means of Intention to Trust with Low or High Benevolence

highlow

Ability

32.00

30.00

28.00

26.00

24.00

22.00

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imat

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eans

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136

However, High and Low Information Levels of Benevolence resulted in a significant

difference in the estimated marginal means of Intention to Trust for groups with Low

(F(1,117) = 8.887, p = .003) but not High (F(1,117) = .001, p = .975) Information Levels of

Ability (Figure 28); the Benevolence of a work-team appeared not to affect Intention to

Trust. On the one hand, for participants in the High Ability condition, the level of

Benevolence had no effect on their Intention to Trust. On the other hand, for those in the

Low Ability condition, High Levels of Benevolence resulted in higher Intention to Trust.

The perception is that work-teams with High Ability appears to buffer against any effect

their Benevolence has on Intention to Trust.

highlow

Benevolence

32.00

30.00

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Figure 28: Estimated Marginal Means of Intention to Trust with Low or High Ability

137

6.2 Summary of the Stage 3 Results Two hundred and twenty four subjects were matched to both phases of the data

collection. From the perspective of the secondary goal of this study, contribution to

method, the application of the SEM provided strong evidence that this three-stage study

had developed vignettes, questionnaires and scales that were firmly based on the theory

under test. Subsequent omnibus ANOVA results supported the inference that the refined

vignettes had contributed to subjects better differentiating the High and Low levels of

Ability communicated via the vignettes. In seeking to overcome limitations in similar

trust-related studies, the refinement of the Intention to Trust questionnaire items had

significantly contributed to improving the inter-item consistency and reliability of the

Intention to Trust scale.

Subsequent SEM analysis continued method contribution by exampling a process to

refine the trust scales to optimally reflect a study context. This process involved

Congeneric CFA models that identified the variables explained by the exogenous

factors, Ability, Benevolence, and Integrity as well as the endogenous factor, Intention

to Trust. The application of a Reverse Coded Method Factor contributed to overcoming

the affective factor that arose from the negatively worded Intention to Trust

questionnaire items. The subsequent test of rival First Order CFA models supported the

hypothesis that the earlier defined Congeneric CFA models of Ability, Benevolence and

Integrity reliably explained the trust antecedents. Subsequently, the First Order CFA

Model was applied to a full LISREL model to analyse the path analysis of the Intention

to Trust model. Rival single and two-factor models converged towards a fitted model

that provided support for the hypothesis that the three trust antecedents, Ability,

Benevolence and Integrity, explain Intention to Trust. However, a marginal non-

significant negative Benevolence-Intention to Trust parameter and an Integrity- Intention

to Trust parameter that appeared larger than the sum of its contributory factors heralded

the possibility of suppression effect in the model. A subsequent ANOVA sought to

explain hypothesis H3 by examining the simple main and indirect effects of the trust

antecedents of Ability, Benevolence and Integrity on Intention to Trust.

138

In pursuit of the primary study goal of answering the research questions, the between-

groups ANOVA supported the inference that our Intention to Trust increases when a

Low Integrity work-team has High Ability. Similarly, our Intention to Trust further

increases when a team has High Integrity together with High Ability. Ability had a

similar effect on groups with High and Low Levels of Benevolence. However,

Benevolence had little effect on Intention to Trust when a work-team had a High

Information Level of Ability. To the participants in this study, the competence,

knowledge and skills of a High Ability work-team appears to buffer against the work-

team’s Benevolent traits. Therefore, one could conclude that the study sample from the

population of undergraduate students from the Business Faculty of an Australian

university appear to consider Ability most important when cognitively assessing their

Intention to Trust a work-team that they could choose to join.

139

Chapter Seven

7.1 Overall Summary of Study Findings

In the dyadic relationship of a subject choosing to join a work-team, this research sought

to address a gap in our current understanding of the antecedents that affect co-worker

trust development. In doing so, this study pursued two goals. The first goal of the study

was to enhance our understanding of trust development in newly forming groups by

focussing on the research questions and the hypotheses. From the perspective of the

secondary goal, the three-stage methodology employed in this study improved the

reliability of the published trust scales by customising them to reflect the context of the

study. The Cronbach Alpha statistic for Intention to Trust improved from the low levels

of previous studies (ά = .56) to an acceptable level in Stage 2 (ά = .77) and further

improved to a good result (ά = .83) in Stage 3. The resultant trust scale for Intention to

Trust improved the internal validity of this study and strongly supported the claim that

instruments, particularly vignette manipulations, employed in a study need to

realistically reflect the study context. This supports the argument that context is

inexorably linked to our Intention to Trust.

While the research design of this vignette experiment offers method and scale

improvement alternatives that could be useful for future research, the primary study goal

was to address the research gap that identified a need to enhance our understanding and

seek explanation to the research questions:

R1: How do we develop interpersonal trust in the context of newly forming work-

teams?

Or more specifically

R2: Which trust antecedents are more important when initiating trust development

between the team members?

140

Three hypotheses provided the primary focus for the study effort:

H1: Benevolence and Integrity and Ability will be positively associated

with our Intention to Trust members of a newly forming work-team.

Hypotheses H1 was supported: in Stage 2, Ability (r = .538, p = .01) and Benevolence (r

=.465, p = .01) and Integrity (r = .593, p =.01), and; in Stage 3 Ability (r = .653, p =

.01), Benevolence (r =.357, p = .01) and Integrity (r = .639, p = .01). In the context of

newly forming work teams, Benevolence and Integrity and Ability are positively

associated with Intention to Trust.

H2: At the pre-stage of team development, the trust antecedents of

Ability, Benevolence and Integrity have differential effects on our

Intention to Trust members of a newly forming work-team.

Study Stages 2 and 3 supported Hypothesis H2. Stage 2 results identified differential

correlation relationships between the trust antecedents and Intention to Trust; Ability (r

= .538, p = .05), Benevolence (r =.465, p = .01) and Integrity (r = .593, p = .01).

Similarly, different IV correlations were witnessed in Study Stage 3; Ability (r = .653, p

= .01), Benevolence (r =.357, p = .01) and Integrity (r = .639, p = .01). More

importantly, the results from ANOVA and pairwise comparisons of the main and

interactive effects of the trust antecedents identified that the sample from a population of

undergraduate students from the Business Faculty of an Australian university appear to

consider Ability more important than Benevolence or Integrity when cognitively

assessing their Intention to Trust a work-team that they could choose to join. These

results support the hypothesis that the trust antecedents of Ability, Benevolence and

Integrity have differential effects on our Intention to Trust.

141

H3: Ability will have a more salient effect on our Intention to Trust

members of a newly forming work-team than Integrity or Benevolence.

Based on correlation results, support for Hypothesis H3 was initially inconclusive. The

pilot of the test instruments in Study Stage 2 resulted in a marginally stronger Intention

to Trust relationship with Integrity (r = .593, p = .01) than Ability (r = .538, p = .05) or

Benevolence (r =.465, p = .01). This correlation relationship was reversed in Stage 3; the

Intention to Trust relationship with Ability (r = .653, p = .01) was marginally stronger

than Integrity (r = .639, p = .01) and Benevolence (r =.357, p = .01). However, focusing

on Ability and Integrity, the results from ANOVA and pairwise comparisons of their

main and interactive effects provided stronger support for a claim that Ability is more

salient than Integrity in the development of Intention to Trust. The ANOVA indicated a

significant between-subjects main effect for Ability (F(3,99) = 17.485, p = .000, η2 = .19);

19% of Intention to Trust was explained by Ability. Integrity also had a significant main

effect (F(3,99) = 4.252, p = .042, η2 = .04) but it explained less (4%) of the variance

associated with Intention to Trust. The interaction between Ability and Integrity was

trivial (η2 = .002) and not significant (F(3,99) = .203, p = .65). Therefore, in the context

of members of newly forming work-teams, Ability is considered to have a more salient

effect on Intention to Trust than Integrity.

Similarly, Ability has a more salient effect on the development of Intention to Trust than

Benevolence. The ANOVA indicated a significant between-subjects main effect for

Ability ( F(3,121) = 47.293, p = .000, η2 = .29); 29% of Intention to Trust was explained

by Ability. Benevolence also had a significant main effect (F(3,121) = 4.533, p = .035) but

the small effect size (η2 = .04) indicated that Benevolence only explained 4% of the

variance associated with Intention to Trust. The interaction between the independent

variables and the dependent variable identified that High and Low Information Levels

of Ability has a significant difference on Intention to Trust for groups with High (F(1,117)

= 40.641, p = .000) and Low (F(1,117) = 11.149, p = .001) Information Levels of

Benevolence. However, the effect of a High Information Level of Ability was so high

(Observed Power = 1.0) that High or Low Information Levels of Benevolence had little

142

or no effect on Intention to Trust. Based on these results, the Intention to Trust of the

sample appears to be affected largely by Ability than Benevolence, which appears to

have a weak effect on Intention to Trust.

In summary, for study participants in a sample from the population of undergraduate

students from the Business Faculty of an Australian university, the Benevolence of a

work-team has no effect on their Intention to Trust a work-team with High levels of

Ability but does have a minimal effect on their Intention to Trust a Low Ability work-

team. Additionally, Integrity has a lesser effect on Intention to Trust than Ability. The

ANOVA results support Hypothesis H3; in the context of a member joining a newly

forming work-team, Ability has a more salient effect on Intention to Trust than

Benevolence or Integrity.

143

Chapter Eight

8.1 Discussion, Limitations and Future Research

It has been argued that understanding how to better develop trust has the potential to

assist management to realise the positive outcomes that can benefit an organisation, its

employees and the customers they serve. This research sought to contribute to the

success of our organisations by deepening our understanding of trust development, the

foundation for high performing individuals, teams, and their organisations.. The

contributive-effort focused on two gaols. Firstly, an experimental method has been

tested and is offered for consideration by researchers who seek to satisfy the requirement

for vignette-based manipulations that must appear realistic to the study participants and

optimally reflect a study setting (Murphy et al., 1986). This method contribution also

sought and improved published trust-related scales because it is important that our scales

consistently and accurately measure the variable they purport to measure (Christensen,

2004, pp. 185-198). By improving the quality of the measurement scales, this study

contributed by providing a three-stage methodology that could prove helpful to others

who seek to refine questionnaire item wording and vignette development. In particular,

the method led to improvements in the internal consistency of the previously

problematic Intention to Trust measure by increasing its Cronbach Alpha reliability

coefficient to a magnitude not evidenced in recent trust-related studies. The method is

offered for consideration by other researchers.

While the method contribution may be useful to other researchers, the primary goal of

this study was to contribute to our knowledge of how to develop the trust that leads to

higher performing employees, the teams they work in, and the organisations that engage

them (Ana Cristina Costa, 2003; Kiffin-Petersen & Cordery, 2003). This is particularly

important in today’s work environment because of the predominance of part-time and

contract employees (ABS, 2005) who do not benefit from the trusting work environment

that emerges from the culture of organisations with permanent employees (Misztal,

2002). Today, the number of part-time and temporary employees in Australian

workplaces is increasing (ABS, 2006). In the shadow of contemporary work

144

environments that exhibit disparate views of trust (Elangovan & Shapiro, 1998; Jones &

George, 1998), this study effort addressed a gap in the literature. Previous studies have

not addressed the pre-stage of team development. This is understandable because as

permanent employees we would transition this pre-stage once, when we first join a new

organisation.

As a permanent employee, we would go through a pre-stage induction or training

process designed to socialise us into our new work-team environment. From the training,

we would gain an understanding of what the organisation expected of us, the principles

and standards that underpin the integrity of the organisation. As we interacted with our

fellow team members, we would gain an understanding of their strengths and

weaknesses, those areas where they had particular abilities or skills. The feedback we

received from our multiple interactions with fellow employees would inform us of how

they treated fellow team members, how benevolent they were to others. Having

progressed through this initial pre-stage of team development, we would join our work-

team. Even if we moved throughout the organisation, we would be joining teams who

shared similar principles and values to ourselves. In environments where permanent

employees are pre-socialised, the pre-stage of team development would be almost non-

existent. This is not the case with part-time or temporary employees. They would need

to go through the pre-stage of team development every time they accepted a temporary

position with people whom they had not previously worked. These temporary employees

would have no information upon which to found expectations about what team members

had what skills, who was reliable, and, how they would be treated by other team

members. If we accept that increased levels of trust leads higher performing work-teams,

then it is important to understand the pre-stage of team development and how to

optimally develop trust between work-teams of temporary or part-time employees.

This and a plethora of previous studies have provided considerable evidence that our

consideration of the abilities, benevolence and integrity of others contributes to our

decision to extend trust to others. Like this study, much previous research was based

upon the integrative model of organisational trust (Mayer et al., 1995) which equitably

145

viewed the trust antecedents of ability, benevolence and integrity (Costa et al., 2001;

Davis et al., 2000; Gill et al., 2005; Mayer & Gavin, 2005; Schoorman et al., 1996a;

Serva et al., 2005). However, these studies did not address the pre-stage of team

development. This raises the question addressed by this research; which trust antecedent

is most salient in the pre-stage of team development? In pursuing this question, this

study built upon the existing integrative model of organisational trust by incorporating

the contextual moderation factor of Information Level that accounts for the type and

volume of information a trustor applies when cognitively making a decision to extend

trust to a trustee. Experimental manipulation of high and low Information Levels about

potential team members provided insight into what trust related attributes we expect in

our fellow team members. In the context of a member joining a newly forming work

team, this study found that Ability had a greater effect on our Intention to Trust than

Benevolence or Integrity.

More specifically, while our Intention to Trust a Low Ability team increased when the

team exhibited either a High level of Benevolence or a High level of Integrity, this was

not the case when the team exhibited High Ability. When the team exhibited a High

level of Ability, Integrity had a lesser effect on our Intention to Trust but more

importantly High or Low Information Levels of Benevolence had little or no effect on

our Intention to Trust a High Ability team. This result was unexpected and is counter to

the current literature. We would reasonably expect that the way we are treated, our level

of Benevolence to fellow team members, would in some way affect how we extend trust.

These results would have us believe that fellow team members do not care about how

they are treated by fellow team members. Clearly, this is not the case. As we work with

people we seek the acceptance and recognition through our everyday interactions (Blau,

1964). Working with people who we like and who reciprocate by liking and treating us

fairly is a much more desirable work environment. So how did this unexpected result

emerge?

146

This discussion has identified that it is not normal for us to ignore how we are treated by

others. Previous studies identified that Ability Benevolence and Integrity are all

important in the development of trust (Costa, 2003; Costa et al., 2001; Earley, 1986;

Gill, Boies, Finegan, & McNally, 2005; Mayer & Davis, 1999; Schoorman, Mayer, &

Davis, 1996b; Serva, Benmati, & Fuller, 2005; Tan & Tan, 2000; Whitener et al., 1998).

Perhaps the lack of effect from Benevolence is a reflection of the research design for this

study. After all, in Study Stage 1, the thematic analysis of structured interviews

identified eight times more participant statements relating to the Integrity, and five times

more statements relating to the Benevolence, than the Ability of a work-team. Based on

this qualitative evidence, one could conclude that Ability is the least important of the

trust antecedents. However, in Study Stages 2 and 3, quantitative results identified that

Ability was perceived to be more salient than Benevolence or Integrity. In seeking

explanation, Murphy et al. (1986) remind us that vignettes, like those applied in Stages 2

and 3, project information that is less subject to the confounds that can contaminate

experimental studies. The design of this study specifically sought to exclude confounds

from Study Stages 2 and 3. Having excluded these confounds, it would be reasonable to

expect that the salience of the trust antecedents could be different from the qualitative

Stage 1.

While vignettes help to minimise confounds, they can amplify the signal strength of a

manipulation above that of real-life situations (Murphy et al. 1986). This can affect the

power of a statistical test and could have caused one or more of the trust antecedents to

have a greater effect on Intention to Trust than the other antecedents. This may have

occurred with Ability. The observed power for Ability was nearly twice the result of

Benevolence and Integrity. This was unexpected because a priori calculation of effect

size and power predicted similar levels for Ability, Benevolence and Integrity. However,

the studies used as a basis for the priori power calculations did not address the pre-stage

context of team development; this study focussed on the pre-stage. Rousseau et al.

(1998, p. 398) assert the importance of considering context in trust-related research, the

importance of certain factors change depending upon the situation in which we find

ourselves. Therefore, the unexpected result could be reflective of the pre-stage context

147

of this study. Seeking another explanation, perhaps the subjects perceived stronger

Ability information in the vignettes than Benevolence and Integrity information.

Great care was taken to ensure a balanced projection of Ability, Benevolence and

Integrity information in the vignette content. However, the Ability information did use

more physical page-space in the vignettes. Perhaps the tabular depiction of the grade

history of the other work-team members may have caused the subjects to retain the

Ability information more prominently in their short-term memory and prompted them

make an Ability-related decision to join the work-team (Lurie & Mason, 2007). Thus,

the subjects could have more readily recalled Ability information when responding to

the questionnaire. However, statistical tests supported the inference that Benevolence

and Integrity manipulations were successful. Benevolence and Integrity information did

affect a subject’s Intention to Trust when the work-team had Low Ability. Of course,

this was not the case when the work-team had High Ability. Perhaps the information in

the High Ability vignettes was considerably stronger than the Low Ability information

in the vignettes. While this is a plausible explanation, it is considered unlikely because

the manipulation checks supported the effectiveness of the High and Low Ability

Information Levels depicted in the vignettes. Therefore, the strength of the High and

Low Ability information is considered balanced and equitable. While the strength of the

vignette information could have affected the salience of the trust antecedents, this is not

supported by the statistical tests. Another explanation is that subjects from a population

of undergraduate students from the Business Faculty of an Australian university do

consider Ability more important when considering their Intention to Trust a newly

forming work-team.

It somehow appears logical that students would consider Ability more important. After

all, they are at university to gain a professional qualification and the Australian

university constantly reminds them that, post graduation, their grade point average is

positively correlated with the starting salary they could expect from their initial

employer (Sandvig, Tyran, & Ross, 2005). Given that High Ability students have

superior skills and greater knowledge and is rewarded with higher grades, it would be

148

reasonable to assume that if we joined a work-team with High Ability we could expect

to increase the probability that we too would be rewarded with a higher grade; thus

increasing our overall grade point average and the chances of getting a higher paid job.

In responding to whether or not they would agree to join the group depicted in the

vignette, all subjects offered a group with high Ability agreed to join the group. This was

not the case with those offered a low Ability group. Just 15% of those subjects agreed to

join the group and they were subjects offered a group with Low Ability and a High level

of Integrity. Clearly students appear to focus on the Ability of fellow team members and

generally ignore the team’s Benevolence and to a lesser extent their Integrity.

In general, we could conclude that students are more positively affected by a High

Ability work-team, will trust them more because of the higher probability of success and

reward, and, be more likely to join a High Ability work-team. In explanation, the

students could view the scenario depicted in the vignettes as an example of transactional

trust wherein they need to extend trust to the other members of their work-team for the

twelve-week duration of a semester after which they may never come into contact with

those students again. They do not care how they are treated, they just want a high grade.

This could be a manifestation of halo error (McShane & Travaglione, 2003) wherein a

student’s need, or what Enos (2002) terms their positive emotional attachment, to

achieve a high grade point average causes them to singularly focus on the Ability trait of

the work-team while ignoring the work-team’s Benevolence and Integrity traits.

Of course, this beggars the question: does a similar situation arise in our workplaces that

are employing more and more part-time or contract employees. Given that context is

important in how we develop trust (Rousseau et al. 1998) perhaps a comparison between

a student environment and that of a part-time worker will help us understand the

applicability of this research to the general workplace. Firstly, the dynamics of the

trusting relationship is similar in both contexts; both the student and the part-time

workers come together for a finite period of time after which they may not meet again.

From the perspective of motivation and reward, both the part-time worker and the

student would view the trusting episode as a transaction. As a student, we would focus

149

on optimising our grade that on average should improve if we work with students of

higher ability. Given that our workplace tends to pay higher wages for higher

performance, a part-time worker would expect personal rewards to be maximised when

they joined a high ability work-team that would normally result in higher level of

performance. Therefore, the students and part-time workers could both view Ability as

most important; ability leads to a higher grade and higher monetary rewards. The repeat

of this study in a workplace context offers opportunity for ongoing research.

If Ability is more salient in the development of trust between members of a newly

forming work-teams, and higher levels of trust leads to higher performance teams, then

how should managers develop trust between team members? Should a manager just

ignore Benevolence and Integrity and focus on having everyone in the team exhort the

excellence of their Abilities? Clearly not, because the study of Gill et al. (2005) and

many other researchers has identified that the salience of the trust antecedents varies

over the life of a work-team. In the performing stage of a team Gill et al. (2005) found

that the importance of Ability waned in favour of Benevolence. Once the team members

had a clear understanding of the skills, expertise and Abilities of fellow team members,

they were more concerned about the other team members delivering the work to the

expected standard at a time when it was due. This is understandable because, in the short

life of a team project there would be little time to retrain team members. We would need

to identify who had the ability to do what, allocate tasks based on skills and expertise,

then trust in the benevolent nature of all team members to deliver as expected. The

willingness of students to join the High Ability groups would tend to indicate that this

was probably the thinking of the subjects in this study.

Of course, this is a very short-term view by the subjects in this study; they would very

quickly find out that not everyone does what they say they will do. After all, this is why

we have project managers within teams, to keep the work on time and to budget.

Therefore, as managers we should not ignore Benevolence and Integrity. It is our

Integrity, our values and principles, which underpin our expectations of, and compliance

with, group norms of behaviour (McShane & Travaglione, 2003, p. 270). Ability

150

Benevolence and Integrity are all important in trust development. What this study has

identified is that in the pre-stage of team development we have a propensity to be

blinded by the skills and expertise of others. As managers, we need to help our work-

teams over the halo effects of Ability. Managers could encourage unfamiliar team

members to not only share their knowledge and skills but more importantly, their past

group experiences. In sharing past group work experiences, team members could better

adjudge how a fellow team member is likely to perform later on in the project. Perhaps

the provision of references to past team members could help confirm the claims of our

fellow team members. Such manager-initiated actions could go some way to mitigating

the risk and help lower the risk of our work-teams underperforming. Some managers

could consider such get-to-know-you sessions a waste of time, particularly with teams

that are only together for a short time. However, this study has provide considerable

evidence to support a claim that a manager cannot just rely on the judgement of part-

time employees to develop the trust that leads to higher performing work teams, as

managers, we need to help them overcome their limitations.

Like our part-time workers, this study also has limitation. The most obvious limitation

emerges from the generalisability of the results; Business Faculty undergraduate

students from a metropolitan Australian university may not accurately reflect the

parameters of our part-time workforce. It has already been identified that future research

should consider trust development over the complete life of a work-team; the pre-stage,

the forming stage, the storming stage, the norming stage, the performing stage, and the

adjourning stage. Such research could help managers better understand how to fine-tune

their skills to continually develop greater levels of trust over the life of their work-teams.

Another limitation of this study is the use of vignette manipulation. Perhaps this vignette

experiment reveals a deeper method-related question; do we take more notice of written

information about how we will be treated by others or do we prefer personal contact?

Perhaps such a research question should focus on the psychometric limitation in this

study by questioning whether written vignette manipulations, paper people, are a valid

proxy for the interpersonal communication of information about fellow team members.

151

The use of vignette manipulation may not be single limitation in this experimental study.

A second limitation could be the thematic analysis of the structured interview transcripts

in Study Stage 1. They are the qualitative interpretations; analysis by another researcher

could reveal alternative meanings. A third limitation; because the study setting related

directly to a group assessment context the questionnaire responses of some student

subjects could have been positive or negatively affected by their previous assessment

experiences. In particular, a negative affective bias may have emerged because there

were more negative comments about group assessment in the feedback section of the

questionnaires than positive assessment-related comments. A fourth limitation arises

from a possible pre-testing bias in the Stage 2 questionnaire that concurrently collected

Intention to Trust and Propensity to Trust responses. However, future studies could

address this limitation by following the example of Study Stage 3 and collecting the data

at different times. The final limitation arises from Structural Equation Model fitting

interpretations and the decisions of this researcher to include or exclude certain

variables. Although the model fitting adjustments were theoretical and empirically

founded, it would be reasonable to expect that another researcher could make different

model trimming decisions. Such methodological refinements could lead to future

research opportunities.

This research has already revealed a plethora of future research opportunities. The first

is to strengthen the generalisability of the results by repeating this study across a

population that is more reflective of today’s work environment. Secondly, the

phenomenon glimpsed in Study Stage 2 may worthy of future research; do universities

that allow students to graduate with a small number of failing grades result in students

and universities that are accepting of lower academic standards? The problems that

emerged in Stage 3, with respect of matching multistage data collections from

anonymous subjects, offers an opportunity for future research. Additionally, the

collection of additional data on personal attribute factors offers the opportunity to

identify the personality types that lead to certain trusting behaviours; such knowledge

could help management select the most suitable employees for work-team assignments.

The most obvious research opportunity emerges from the unexpected results that

152

identified the minimal effect of Benevolence and Integrity on Intention to Trust when a

work-team exhibits High Ability. This question in particular motivates a desire to pursue

evidence of causation, perhaps a longitudinal study in a more generalisable setting that

offers the opportunity to strengthen the notion and explain why the dynamic nature of

trust leads to transient and varying antecedent effects on our Intention to Trust.

153

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