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DETERMINANTS OF EFFECTIVE MANAGEMENT OF CONSTITUENCY
DEVELOPMENT FUNDED PROJECTS IN KASIPUL CONSTITUENCY, HOMA
BAY COUNTY, KENYA
BY
ANDHOGA WALTER OTIENO
(M.Div. Africa International University, B.A Global University)
A THESIS SUBMITTED TO THE SCHOOL OF POST-GRADUATE STUDIES IN
PARTIAL FULLFILLMENT OF THE REQUIREMENTS FOR THE AWARD OF
THE DEGREE OF DOCTOR OF PHILOSOPHY IN LEADERSHIP AND
GOVERNANCE OF THE SCHOOL OF ARTS AND SOCIAL SCIENCES,
DEPARTMENT OF POLITICAL SCIENCE AND PEACE STUDIES, KISII
UNIVERSITY
OCTOBER 2019
DECLARATION AND RECOMMENDATION
Declaration by the CandidateThis thesis is my original work and has not been presented for a degree in any other
university.
Andhoga Walter Otieno Signature……………… Date……………………DAS/60423/15
Recommendations by the Supervisors This thesis has been submitted for examination with our approval as the University
Supervisors.Dr. George Nyarigoti Mose Signature……………… Date……………………Lecturer and Chair of DepartmentSociology and Development StudiesSchool of Arts and Social SciencesKisii UniversityDr. Johnson Nzau Mavole Signature……………… Date……………………Lecturer and Head of DepartmentSocial Sciences and Development StudiesFaculty of Arts and Social SciencesCatholic University of Eastern Africa (CUEA)
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PLAGIARISM DECLARATION
DECLARATION BY STUDENTi. I declare I have read and understood Kisii University Postgraduate Examination
Rules and Regulations, and other documents concerning academic dishonesty. ii. I do understand that ignorance of these rules and regulations is not an excuse for a
violation of the said rules. iii. If I have any questions or doubts, I realize that it is my responsibility to keep seeking
an answer until I understand.iv. I understand I must do my own work. v. I also understand that if I commit any act of academic dishonesty like plagiarism, my
thesis/project can be assigned a fail grade (“F”)vi. I further understand I may be suspended or expelled from the university for academic
dishonesty.
Name Andhoga Walter Otieno Signature_____________________
DECLARATION BY SUPERVISOR (S)
i. I/we declare that this thesis/project has been submitted to plagiarism detection service.
ii. The thesis/project contains less than 20% of plagiarized work.iii. I/we hereby give consent for marking.
1. Name Dr. George Nyarigoti Mose Department of Sociology and Development Studies School of Arts and Social Sciences
Kisii University
Signature_____________________________ Date_________________________
2. Name Dr. Johnson Nzau MavoleDepartment of Social Sciences and Development StudiesFaculty of Arts and Social SciencesCatholic University of Eastern Africa (CUEA)
Signature______________________________Date_________________________
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DECLARATION OF NUMBER OF WORDS
I confirm that the word length of:
1) the thesis, including footnotes, is 56,690 2) the bibliography is 2,690
and, if applicable, 3) the appendices are 6,859
I also declare the electronic version is identical to the final, hard bound copy of the thesis andcorresponds with those on which the examiners based their recommendation for the award of thedegree.
Signed: …………………………………… Date……………………………
I confirm that the thesis submitted by the above-named candidate complies with the relevant wordlength specified in the School of Postgraduate and Commission of University Education regulationsfor the PhD Degrees.
Signed: ..................................... Email………….……………. Tel…………………………
Dr. George N. Mose Date……………………….
Signed: ............................ Email………………………. Tel………………….……… Dr. Johnson N. Mavole Date…………………………
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COPY RIGHT
All rights are reserved. No part of this thesis may be reproduced, stored in a retrieval system
or transmitted in any form or by any means electronic, mechanical, photocopying, recording
or otherwise, without the prior written permission of the author or Kisii University on that
behalf.
© 2019, Andhoga Walter Otieno
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DEDICATION
This thesis is dedicated to my dear wife Benta whose love, care, understanding and support
has made me the person I am today. My Son Henry and my daughters Edna and Joy who in
spite of being students themselves allowed me to undertake my studies and prayed with me.
You lifted my spirit when I was low and you were a source of encouragement to me. God
bless you all.
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ACKNOWLEDGEMENTS
I wish to acknowledge with a lot of gratitude the following people for their technical
support, care and love notwithstanding: Free Pentecostal Fellowship in Kenya for their
financial and moral support; Supervisors; Dr. George N. Mose and Dr. Johnson N. Mavole,
they went through my work most thoroughly and offered expert advice; my research
assistants who assisted me in the collection of data in Kasipul Constituency and colleagues
in the Leadership and Governance Class. I want to thank Mr. Bernard, Mr. Wangalwa, Mr.
Abuga and Mr. Ebenezer who helped me in different ways during the period of my research
writing. All the members of our faculty who taught and interacted with me in the various
classes, our Dean of School Dr. Margaret Barasa who in spite of her busy schedules did
proof reading for my work. God bless you all.
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ABSTRACT
The debate over the effectiveness of various governance models to deliver social servicesequitably and efficiently have been inconclusive. In Kenya where decentralization has beeneffected through the Constituency Development Fund (CDF), the responsive andaccountability outcomes have largely been elusive for projects funded by the CDF atconstituency level. Studies point that conflict of interests, political elite, and legal challengeshave often hampered effective implementation. The purpose of this study was to investigatethe determinants of effective management of Constituency Development Funded (CDF)projects in Kasipul Constituency, Homa Bay County, Kenya. Specific objectives includedestablishing the influence of project financing, stakeholder participation, political influenceand technical capacity on effective CDF projects management in Kasipul Constituency. Thestudy was guided by the project-completion, competency and stewardship theory. Mixedresearch design involved both quantitative and qualitative research approaches. The targetpopulation was 254 projects from which samples of 77 projects were stratified randomlyselected. Census sampling was used to sample CDFC members and National Governmentofficials. Beneficiaries were sampled through simple random sampling and project managersusing purposive sampling. A pilot study was conducted which revealed that the collectioninstrument was valid and reliable. Qualitative data was analyzed and presented as narrationsand verbatim. Quantitative data was analyzed using STATA version 14. Model estimationand hypotheses testing adopted Structural Equation Modeling using AMOS version 23.Project financing and stakeholder participation had significant effects on effectivemanagement of CDF funded projects while political intervention and technical capacity hadno significant influence. Introducing regulatory framework was found to have a moderatinginfluence on the relationship between the determinants and effective management ofprojects. It was recommended that the government should strengthen existing policies thatadvocate for appropriate project financing and embrace stakeholder participation to enhanceeffective management of CDF projects.
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TABLE OF CONTENTS
DECLARATION AND RECOMMENDATION.................................................................ii
PLAGIARISM DECLARATION........................................................................................iii
DECLARATION OF NUMBER OF WORDS....................................................................iv
COPY RIGHT.........................................................................................................................v
DEDICATION.......................................................................................................................vi
ACKNOWLEDGEMENTS.................................................................................................vii
ABSTRACT.........................................................................................................................viii
TABLE OF CONTENTS......................................................................................................ix
LIST OF TABLES...............................................................................................................xiv
LIST OF FIGURES............................................................................................................xvii
LIST OF APPENDICES...................................................................................................xviii
LIST OF ACRONYMS.......................................................................................................xix
LIST OF ABBREVIATIONS...............................................................................................xx
CHAPTER ONE.....................................................................................................................1
1.0 INTRODUCTION............................................................................................................1
1.1 Background of the Study.................................................................................................1
1.2 Statement of the Problem..............................................................................................11
1.3. Significance of the Study.............................................................................................12
1.3.1. Significance to Policy...........................................................................................12
1.3.2. Project Manager, CDF Committee and Other Stakeholders.................................13
1.3.3. Significance to Academics....................................................................................13
1.3.4 Significance to General Readership.......................................................................13
1.4 General Objective of the Study.....................................................................................14
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1.5 Specific Objectives of the Study...................................................................................14
1.6 Hypotheses of the Study................................................................................................15
1.7 Assumptions of the Study..............................................................................................15
1.8. Scope of the Study........................................................................................................16
1.9. Limitations of the Study...............................................................................................16
1.10. Conceptual Framework..............................................................................................17
1.11. Operational Definition of Terms................................................................................18
CHAPTER TWO..................................................................................................................20
2.0 LITERATURE REVIEW..............................................................................................20
2.1. Introduction..................................................................................................................20
2.2. Theories Informing the Study......................................................................................20
2.2.1. Project Completion Theory...................................................................................20
2.2.2 Competence Based Theory....................................................................................22
2.2.3 Stewardship Theory...............................................................................................25
2.3. Review of Empirical Studies........................................................................................26
2.3.1. Project Financing..................................................................................................26
2.3.2. Stakeholder Participation in the Management of Projects....................................31
2.3.3. Political Influence.................................................................................................36
2.3.4. Technical Competence and Skills.........................................................................45
2.3.5 Legal & Policy Framework Governing CDF Management...................................48
2.4. Gaps to be filled by Current Study...............................................................................50
CHAPTER THREE..............................................................................................................55
3.0 RESEARCH METHODOLOGY..................................................................................55
3.1. Introduction..................................................................................................................55
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3.2. Geographical Description of the Research Area..........................................................55
3.3. Research Design...........................................................................................................56
3.4. Study and Target Population of the Study....................................................................57
3.5 Sample Size and Sampling Procedure...........................................................................58
3.5.1 Sampling of Project Managers...............................................................................60
3.5.2 Sampling of CDF Committee................................................................................60
3.5.3 Sampling of National Government Departmental Heads......................................60
3.5.4 Sampling of the Beneficiaries................................................................................61
3.6. Data Collection Instruments.........................................................................................62
3.6.1 Questionnaires........................................................................................................63
3.6.2 Interview schedules................................................................................................63
3.6. 3 Focused Group Discussions..................................................................................64
3.7. Data Collection Procedure...........................................................................................64
3.8. Reliability and Validity of the Research Instruments...................................................65
3.8.1. Reliability..............................................................................................................65
3.8.2. Validity..................................................................................................................66
3.9. Methods of Data Analysis, Diagnostics and Presentation............................................67
3.9.1 Quantitative analysis..............................................................................................67
3.9.2 Path Analysis..........................................................................................................67
3.9.3 Qualitative data analysis........................................................................................71
3.10 Ethical Considerations.................................................................................................72
CHAPTER FOUR................................................................................................................73
4.0 RESULTS........................................................................................................................73
4.1 Introduction...................................................................................................................73
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4.2 Instruments Response Rate...........................................................................................73
4.3 Demographic Characteristics of Respondents...............................................................74
4.3.1 Beneficiaries Demographic Characteristics...........................................................74
4.3.2 Project Managers/Contractors Demographic Data................................................77
4.3.3 CDF Committee Members Demographic Data......................................................79
4.4 Descriptive Analysis......................................................................................................82
4.4.1 Project Financing........................................................................................................83
4.4.2 Stakeholder Participation...........................................................................................91
4.4.3 Political Influence....................................................................................................105
4.4.4 Technical Capacity...................................................................................................113
4.4.5 Regulatory Framework.............................................................................................120
4.4.6 CDF Project Management........................................................................................124
4.5 Validity of the study instruments.................................................................................130
4.6 Inferential analysis......................................................................................................131
4.6.1 Measurement model validity and reliability........................................................132
4.6.2 Correlation analysis.............................................................................................135
4.6.3 Confirmatory Structural Model............................................................................137
4.6.4 Moderated multiple regression............................................................................154
4.6.5 Comparison between Completed, ongoing and stagnant Projects.......................159
CHAPTER FIVE................................................................................................................164
5.0 DISCUSSIONS.............................................................................................................164
5.1 Introduction.................................................................................................................164
5.2 CDF Project Management in Kasipul Constituency...................................................166
5.3 The influence of projects financing on effective management of Constituency
Development Funded projects...........................................................................................168
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5.4 Contribution of stakeholder participation on effective management of Constituency
Development Funded projects...........................................................................................177
5.5 The role of political intervention on effective management of Constituency
Development Funded projects...........................................................................................187
5.6 The influence of Technical capacity on effective management of Constituency
Development Funded projects...........................................................................................193
5.7 Moderating influence of Regulatory framework on the relationship between the
determinants Effective management of CDF Projects......................................................198
5.7 Summary of Research Objectives, Hypotheses, Findings and Verdict.......................203
CHAPTER SIX...................................................................................................................206
6.0 CONCLUSION AND RECOMMENDATIONS........................................................206
6.1 Introduction.................................................................................................................206
6.2 Conclusions.................................................................................................................206
6.3 Recommendation.........................................................................................................210
6.3.1 Project Financing.................................................................................................210
6.3.2 Stakeholder Participation.....................................................................................211
6.3.3 Political Influence................................................................................................212
6.3.4 Technical Capacity...............................................................................................213
6.4 Implications.................................................................................................................213
6.4.1 Theoretical implication on theories that guided the study...................................213
6.4.2 Contribution to the Study Methodology..............................................................215
6.4.3 Implications to the Policies..................................................................................216
6.5 Recommendation for further areas of studies.............................................................216
REFERENCES...................................................................................................................218
APPENDICES.....................................................................................................................237
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LIST OF TABLES
Table 2. 1: Operationalization of Study Variables..................................................................54
Table 3. 1: Targeted Projects Per Ward..................................................................................58
Table 3. 2: Sample Projects Per Ward....................................................................................59
Table 3. 3: Sampling of Beneficiaries....................................................................................61
Table 3. 4: Sampling of the Respondents...............................................................................62
Table 3. 5: Item-to-total Correlations of Performance Measurement Variables obtained
through Pilot Survey...............................................................................................................66
Table 3. 6: Summary of Structural and Observed variables...................................................71
Table 4. 1: CDF Beneficiaries Demographic Data.................................................................75
Table 4. 2: Project Managers/Contractors Demographic Data...............................................77
Table 4. 3: CDF Committee Members Demographic Data....................................................80
Table 4. 4: Project Financing-Beneficiaries...........................................................................84
Table 4. 5: Project financing-Project Managers/ Contractors................................................85
Table 4. 6: Project Financing-CDF Committee......................................................................87
Table 4. 7: Comparison between Respondents Views on Project Financing.........................88
Table 4. 8: Stakeholder Participation- Stages of Participation for Beneficiaries...................92
Table 4. 9: Stakeholder Participation-Forms of Participation and identification of
beneficiaries............................................................................................................................93
Table 4. 10: General Stakeholder Participation for Beneficiaries..........................................94
Table 4. 11: Stakeholder Participation-Stages of Project Managers/contractors participation
.................................................................................................................................................96
Table 4. 12: Stakeholder Participation-Forms of Participation and identification for Project
Managers/Contractors.............................................................................................................97
Table 4. 13: General Stakeholder participation for Project Managers/Contractors...............97
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Table 4. 14: Stakeholder Participation in Accountability and Transparency of Finances by
CDF Committee Members......................................................................................................99
Table 4. 15: Stakeholder Participation - Stages of Participation by CDF Committee
Members...............................................................................................................................100
Table 4. 16: Stakeholder Participation-Forms of Participation and identification by CDF
Committee Members.............................................................................................................101
Table 4. 17: General Stakeholder Participation by CDF Committee Members...................102
Table 4. 18: Political Influence on effective management of CDF projects-Beneficiaries’
View......................................................................................................................................106
Table 4. 19: Political Influence on effective management of CDF projects -Project
Managers/Contractors...........................................................................................................108
Table 4. 20: Political Influence on effective management of CDF projects-CDF Committee
Members’ View.....................................................................................................................110
Table 4. 21: Project management skills by Beneficiaries to monitor and report project status
and progress..........................................................................................................................114
Table 4. 22: Project Management Skills by Project Managers/Contractors to Monitor and
Report Project Status and Progress.......................................................................................115
Table 4. 23: Project Management Skills by CDFC members to Monitor and Report Project
Status and Progress...............................................................................................................117
Table 4. 24: Comparison between Respondents Views on Technical Capacity...................118
Table 4. 25: Beneficiaries’ View on the Regulatory Framework..........................................120
Table 4. 26: Project Managers/Contractors View on the Regulatory Framework................122
Table 4. 27: CDF Committee View on the Regulatory Framework......................................123
Table 4. 28: Beneficiaries View on Effective CDF Project Management.............................125
Table 4. 29: Project Managers/Contractors View on Effective CDF Project Management..126
Table 4. 30: CDF Committee View on Effective CDF Project Management.......................127
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Table 4. 31: Comparison between Respondents Views on Effective CDF Project
Management..........................................................................................................................128
Table 4. 32: Status of Sampled Projects from 2013 to 2017.................................................129
Table 4. 33: Sampling Adequacy and Bartlett's test of sphericity.........................................130
Table 4. 34: KMO and Bartlett's Test....................................................................................133
Table 4. 35: Internal consistency..........................................................................................134
Table 4. 36: Correlation analysis..........................................................................................136
Table 4. 37: Normality Results.............................................................................................138
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Table 4. 38: Collinearity Statistics........................................................................................140
Table 4. 39: Heteroscedasticity Results................................................................................141
Table 4. 40: Durbin-Watson Results.....................................................................................141
Table 4. 41: Goodness of fit thresholds................................................................................145
Table 4. 42: Goodness of fit statistics for model 1...............................................................145
Table 4. 43: Path coefficient estimates for model 1..............................................................147
Table 4. 44: Goodness of fit test for model 2........................................................................148
Table 4. 45: Path coefficient estimates for model 2..............................................................150
Table 4. 46: Goodness of fit test for model 3........................................................................151
Table 4. 47: Path coefficient estimates for model 3..............................................................153
Table 4. 48: Model Summary statistics.................................................................................155
Table 4. 49: Coefficient estimates.........................................................................................156
Table 4. 50: Multiple Linear Regression: Comparison between Completed, ongoing and
stagnant Projects...................................................................................................................160
Table 4. 51: Legal Framework as a moderating Variable; Comparison between Completed,
ongoing and stagnant Projects..............................................................................................162
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LIST OF ABBREVIATIONS
CDF Constituency Development Fund
CDFC Constituency Development Fund Committees
CFA Confirmatory Factor Analysis
CFI Comparative Fit Index
DDO District Development Officer
DFRD District Focus for Rural Development
GFI Goodness of Fit Index
KHRC Kenya Human Right Commission
KMO Kaiser-Meyer-Olkin
LATF Local Authority Transfer Fund
LVPA Latent Variable Path Analysis
M & E Monitoring and Evaluation
MLGH Ministry of Local Government and Housing
MMR Moderated Multiple Regression
NACCSC National Anti-Corruption Steering Committee
NFI Normed Fit Index
CDF Government Constituency Development Fund
OLS Ordinary Least Squares
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PGFI Parsimony Goodness-of-Fit Index
PMC Project Management Committee
PNFI Parsimonious Normed Fit Index
SRMR Standardized Root Mean square Residual
SPSS Statistical Package for Social Science
SMEs Small and Medium Enterprises
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CHAPTER ONE
1.0 INTRODUCTION
This chapter briefly introduces the topic of study, giving the background to the study, problem
statement, and significance of the study. Further, it highlights the study objectives, research
hypothesis, assumptions, scope and limitations of the study, conceptual framework and
definitions of key terms.
1.1 Background of the Study
Governments globally have a moral responsibility of ensuring equitable and timely delivery of
social services to its citizens. Different governments use different governance models
conceptualized in their legal and policy frameworks to ensure this has been achieved. Proper
delivery of these services has a close relationship with economic growth expected by many
countries due to the fact that social service delivery and social functioning of citizens are
inseparable. Amongst different models that have been used by various governments to achieve
improved service delivery and citizen satisfaction is decentralization of government services.
Decentralization leads to the desired equitable distribution of resources, ensure improvement in
the delivery of services such as health and education, and empower local communities so as to
ultimately attain development (World Bank, 2015). Decentralization has been associated with a
number of beneficial outcomes that have direct or indirect bearing on local and national
governance (Amponsah, 2012).
Devolution as a form of decentralization provides citizens with a framework and mechanism to
participate in development projects. In both developed and developing countries, devolution is
considered as an essential theme within the circle of governance (Dasgupta & Beard, 2007).
Devolved bodies have the capability to be easily accessed, monitored as well as watched
therefore accountability and transparency in service delivery can be realized (Faguet & Fabio,
2006). Devolution enables government officials and public representatives to be held
accountable as it offers grassroots levels some decision-making powers and at the same time
enhance participation of local community in government. Therefore, devolution leads to good
governance since it is an avenue of promoting suitable local representation and enhancing
transparency in decision making.
Decentralization denotes dispersal of authority among a number of individuals or units.
Decentralization is a concept which can be defined as transfer or dispersal of decision making
powers, accompanied by delegation of authority to individuals or units at all levels of an
organization, even if any are located far away from the power center. In the context of power and
governance "decentralization' signifies the devolution of power and authority of governance of
central and state governance to the sub-state level organization (Boisot & Child, 2013).
However, it is very difficult to pin down the exact meaning of the term decentralization as the
concept is often confused with similar ideas like deconcentration, devolution, delegation, and
privatization. In deconcentration, a superior officer lessens his workload by delegating some of
his functions to his subordinate so that administration functions efficiently and effectively.
Devolution, which also implies dispersal of authority, is a process wherein power is transferred
from one organ of government to another by means of legislation or constitution (Moyo &
Ncube, 2014). Decentralization is also different from delegation. Delegation means entrusting
part of one's work to others. Decentralization, on the other hand, is much broader concept. It is
"transfer of planning, decision making or administrative authority from the central government to
its field organizations, local administrations units, semi-autonomous and parastatals
organizations, local” (Atienza, 2012).
Globally, decentralization has been adopted especially in Africa, Asia and Latin America in
countries where they have autocratic or military regimes as with aim of attaining democracy.
Through democratization, decentralization has promoted good governance strategy thus
achieving accountability, citizen participation, greater pluralism, transparency as well as
development. Smith and Revell (2016) observes that decentralization is designed to reflect local
unique circumstances in development policy-making and implementation accruing various
benefits; making policies more responsive to local needs, provides a mechanism that is
responsive to varying local circumstances thereby improving development allocations more
efficient and makes local politicians and bureaucrats more responsive and accountable to local
communities.
In Europe, there has been creation of regional governments in Italy in the 1970s and in France in
the 1980s, the strengthening of administrative federalism in Germany in the 1990s, and finally,
the Republican devolution revolution in the late 1990s in the United States (Miller, Martini &
Pezard, 2012). In the United Kingdom (UK), even though it is not totally federal system of
government, decentralization has been achieved by making significant changes through
formation of Scottish executive and parliament, Northern Ireland Assembly and Welsh Assembly.
Each of these units has distinct executive and legislative power as well as special relationship
with London.
In Latin America, Ecuador and Bolivia have associated decentralization with fundamental
institutional and political transformation. This has resulted in decreasing structural territorial
inequalities as well as empowering the local communities (Tulia, 2010). Cooperative Federalism
principle of India has achieved implementation of decentralization as it ensures there is amicable
understanding amongst their three tier system of governance that includes the local, the state and
the central. Even though Indonesia has implemented decentralization, the local government
suffers from limited administrative capacity especially on budgetary allocation which hampers
public service delivery. In Jamaica, the focus of decentralization has focused on four main
thematic areas; legal framework, funding and finance, function and structure and lastly
governance which is further divided into democracy and transparency (Bland, 2006).
In Africa, Okojie (2009) found that the Nigerian government has decentralization practices
through federalism. However, the federal government has over concentration of financial,
political power and human resource to the disadvantage of local government and the state.
Owusu et al. (2005) indicated that even though decentralization in Ghana has a positive impact
on local government service delivery and strengthening of their mandate, there was still some
shortcoming such as technical expertise capacity as well as good infrastructure. Decentralization
efforts in Uganda officially commenced in 1992 with creation of political organs at local level
known as council. The members of the local council are elected during regular election and they
are tasked with coordination, accounting and monitoring the implementation of sectoral
development plans (Onzima, 2013).
Decentralization in Kenya began with the introduction of District Focus for Rural Development
(DFRD) in 1993 by the Government as a strategy to further decentralized development interest
using districts as key development units (Chitere & Ireri, 2008). However, the performance of
DFRD was limited by factors like implementation, monitoring, evaluation and project
prioritization due to limited community members’ involvement. Local Authorities Service
Delivery Action Plan (LASDAP) was introduced in 2001 with aim of allowing local authority
jurisdiction residents to participate in decision making process, implementation, monitoring and
evaluation of various services delivered to them. Nevertheless, like its predecessor DFRD it had
various challenges such as institutional capacity, technical capacity and managerial skills,
resources sufficiency, participation, accounting as well as accountability (Devas, 2005).
The involvement of parliamentary in community development as well as grassroots project rising
has been evidenced in various set countries such India, Pakistan, Papua New Guinea, Jamaica,
Uganda, Kenya among others as a form of decentralization (Mwangi & Meagher, 2004). One of
such policy tool is the Constituency Development Funds (CDFs) whose main aim is to devolve
public funds for the purpose of benefiting a particular political sub division. The representative in
the national parliament influences the allocation and in some cases the spending decision of CDF
funds. The CDFs’ policy making entails size and goal of the funds, overseeing of CDF
management and operations, the structure and modality on the utilization of CDF as well as
relative influence of various groups and individuals who are involved in the policy making
process that govern the utilization of CDF for social and economic developments.
In Jamaica, the CDF is based on the principal of promoting infrastructural and human
development at both constituency and community levels (PMRC, 2014). The initiation, selection
and implementation of CDF projects entail various stakeholders including religious leaders. In
Philippines, the CDF money is channeled through implementing Bank account for various socio-
economic developments such as security and forest management. India has two CDF scheme
styles at national level and each of 28 states. At national level, there is Members of Parliament
Local Area Development Scheme while at state level there is Member of Legislative Assembly
Local Area Development Fund for the Legislative Assembly (Keefer & Khemani, 2009).
In Ghana, 5.0% of the National budget is allocated to District Assemblies Common Fund for
education and health care development. In Zimbabwe, CDF Act came into place in 2010 and the
funds are channeled to House of Assembly Members to disburse funds for school and clinic
repair, purchase of generators and boreholes construction. In Uganda, CDF is managed by
Member of Parliament (MP) who receives the fund through their account and then identify
project to fund. However, there are weak structure for monitoring and evaluation. Just like in
Uganda, CDF in Tanzania is controlled by MP who is allocated the funds and has exclusive
control on its usage (Baskin, 2010).
The Constituency Development Fund in Kenya was established through CDF Act 2003 and
Amended in 2007 with other supplementary amendments in 2013 and 2015 whose main aim has
been to adjust the administration of the fund with an aim of making it more project focus and
constituents driven. “The Fund is a National Government Fund managed by the National
Government CDF Board at the National level, the CDF committees at the constituency level and
the Project Management Committees (PMC) at the community level (GoK, 2015). The CDF
Board is a body corporate falling under the Ministry of Devolution and Planning. The Ministry
ensures budgetary provisions and offers policy direction to the Fund. The National Treasury
finances the CDF budgets and provides financial guidelines for effective and efficient
management of the Fund. The National Government CDF committees develops project proposals
in consultation with citizens through periodic ward level open forums, submits them to the CDF
Board for approval and facilitates the PMCs in the planning, implementation, and sustenance of
the projects once completed. The project Management committees and the CDF committees
collaborates for efficient project management through technical support of relevant government
department within the sub-county (Gathitu, 2016)”.
All these administrative changes over the years, have not been adequately empirically analyzed
by putting them to these specific perspectives; analysis of factors that informed changes in the
administration structure of the Fund, the level of fund awareness brought about by the these
administrative changes among the constituents, the level of community participation in the
selection and implementation of projects brought about by the administrative changes, the
administrative, transparency and accountability mechanisms brought about by the changes and
whether CDF projects had benefited the local citizens by comparing outputs against stated
objectives of the Fund (GoK, 2015).
Following the court ruling on 20th February 2015 the High Court declared the CDF Act 2013
unconstitutional hence invalid. The court stated in No. 139 of its ruling: First, the Act establishes
CDF as a mechanism that runs parallel to the constitutionally recognized governance structures.
By charging it with local projects under section 22 of the CDF Act, it threatens to upset the
division of functions between the national and county levels of governments and interfere with
the county government autonomy. By involving Members of Parliament in the planning,
approval and implementation of the CDF projects, the CDF Act violates the doctrine of
separation of powers between the executive and legislative functions. It also undermines some
key national values and principles of governance including devolution of power, accountability
and good governance (Gathitu, 2016).
The order of invalidity was however suspended for a period of twelve (12) months, during which
the court gave the National Government an option of addressing the anomalies in the Act by way
of either an Amendment or repeal of the entire CDF Act. Finally, the National Government
Constituencies Development Fund (CDF) Act 2015 replaced the Constituencies Development
Fund (CDF) Act 2013 with effect from 19th February 2016.
Key changes brought about by the CDF Act 2015 are Clear provision on objects of the Act
(section 3 of CDF Act): The objects of the Fund are now clearly provided for in the Act by
clearly defining the Fund as specific to the National Government in the furtherance of its
functions. Clear specification on the establishment of the fund (Section 4 of NG- CDF Act): The
Act specifies that the Fund is drawn from the National Government’s Share of revenue in
accordance with the Division of Revenue Act enacted pursuant to Article 218 of the Constitution.
This provision serves to correct the view that CDF Act introduces a third level of Revenue
Sharing contrary to the constitution, as highlighted in the High Court ruling. Nature of projects to
be funded (section 24 of the CDF Act): The eligible projects under the CDF Act are only those
entailing works or services falling under the functions of the National Government as provided
for in the constitution. This is an important provision in compliance with the ruling of the High
Court, which determined that the Act as earlier formulated violated the principle of separation of
functions between the National and County governments as provided for in the fourth schedule
of the constitution, by connoting that CDF can implement any project regardless of whether it
falls under the functions of the County or National government (GOK, 2015).
Tenure of office for the Constituency Development Fund Committee (section 43 sub sections 8
of the CDF Act): The term of office of the members of the Constituency Committee shall be two
years and shall be renewable, but shall expire upon the appointment of a new Constituency
Committee. Introduction of Constituency Oversight Committee (section 53 of CDF Act); The
Act introduces an additional committee at the Constituency level, the Constituency Oversight
Committee whose main function is to oversee the projects undertaken under the Act and to
sensitize and receive feedback from members of the public during forums convened for the said
purpose (GOK, 2015).
The purpose of CDF was to ensure there is equitable grass-root and constituency-level
developments. The purpose of this devolved fund is to ensure there is rapid social and economic
development by financing local prioritized projects at constituency level and improve public
participation at community level (Owuor et al., 2012). Besides, the introduction of CDF was
aimed at controlling and reducing regional development imbalances as a result of partisan
politics (Mapesa & Kibua, 2006). There have been doubts on whether CDF has achieved its
objective from various quarters giving an obvious signal that the degree to which CDF has
achieved set goals continues to be research imperative domain for scholars (Bagaka, 2008).
Kasipul Constituency, one of the constituencies in Homa Bay County comprises of five wards;
West Kamagak, West Kasipul, East Kamagak, South Kasipul and Central Kasipul. According to
Kenya National Bureau of Statistics 2013 for Homa Bay County, the population for Kasipul was
projected to be 183,073 in the year 2015 with a population density of 525 KM2. Poverty rate in
the constituency is 49.4% with majority of the population engaged in small scale agriculture and
Small and Medium Enterprises (SMEs). The Constituency poverty index is higher than the
National average of 47%. In 2013/2014 it received Ksh. 75,059,249.00, 2014/2015 it increased
to Ksh. 107,763,163 which represents a 30.3% increase and 2015/2016 it received Ksh.
114,199,520 which was 5.6% from the previous year allocation from the national budgets of
those financial years. Commonly, the CDF has been utilized in education, health, roads, water,
and security.
The National Taxpayers Association (NTA) Social Audit for the constituency on projects funded
found that out of the total sum awarded, 2.9% was wasted and 1.0% was unaccounted for. The
total amount badly used, wasted and unaccounted for would have paid for 22 teachers for a year
(NTA, 2016). According to project implementation status report as at May 2016, some of the
projects that started 2013/2014 had not been completed. Construction of Oyugis Community
Library has not been started due to delay in fund disbursement for FY 2014/2015. Majority of
completed projects have been found to cost more than what was budgeted, for example
construction of a greenhouse at Agoro Sare High School required extra Ksh. 50,000. The delay in
completion of these projects and need for extra cost for their completion is the basis of the study.
It is believed that the resources have not been used so as to achieve value for money principles of
economy, effectiveness and efficiency. The citizens were not adequately involved in CDF project
management at all stage according to data from baseline survey. Proper Monitoring and
evaluation was not conducted as required for the agencies responsible were incapacitated due
lack of sufficient support, facilitation and the authority to administer over questionable
expenditures. The health sector has been seriously affected as there is inadequate medical
equipment and acute understaffing. Schools in the constituency are unable to hire trained
teachers through PTA or BOG initiatives increasing student teacher ratio. Poor transport network
has hampered transportation of farm produce and there is prevalence of water shortage for both
livestock and consumption (GOK, 2013).
There are contextual gaps existing as evidenced in Gathoni & Ngugi’s (2016) work on drivers of
effective project performance in Kiambu County. There is need to focus on a single constituency
within the Country. Conceptual gaps also exist in that most studies have considered a narrow
view of the variables under use. The narrow approach is evident in the studies by among others
Mwangi (2008), Daib (2014) and Obare (2014). The need to embrace a broad concept of the
determinants remains not sufficiently addressed. Empirical gaps are also vivid in that most of the
studies reviewed embraced a narrow framework of variables and have sidelined some key
variables such as political influence, financial management, and technical competence despite
their obvious weight to the subject at hand. Therefore, going by the discussion, it was prudent to
undertake a study on determinants of effective management of Constituency Development
Funded projects in Kasipul Constituency, Homa Bay County, Kenya (2013/2014-2015/2016
F/Y).
1.2 Statement of the Problem
Kenya has been using devolved funds such as LATF and CDF for several years to enhance local
governance in service delivery improvement, better environmental stewardship, increase
responsiveness capacity of local elected representatives and reduce the gap between people and
government. Since 2013 to 2017, a total of Sh186 billion has been disbursed to 290
constituencies (GoK, 2018). CDF is guided by The National Government Constituencies
Development Fund Act, 2015 which has Acts related to politics, participation, technical capacity
and financial resources management. The main aim of CDF establishment was to iron out
imbalances brought about by patronage politics by providing funds to parliament jurisdictions
(constituencies) to fight poverty. The fund is designed to fight poverty through the
implementation of development projects at the local level and particularly those that provide
basic needs like education, health care, water, agriculture services, security, electricity and food
security.
However, the existence and management of these funds have been performing below
expectations and have prevented devolved funds from realizing the desired goals of
decentralization and good governance achieving 42.9% completion rate in Kasipul Constituency
according to Kenya Tax Payers Association (KTPA, 2016). Various studies have related CDF
project management with governance issues. Omeno and Sang (2018) warned that, the noble
objectives of the devolved funds would be hard to achieve if projects were being managed in
total disregard of the fundamental principles of good governance. Nekesa and Ndungu, (2009)
revealed lots of criticisms on the way the CDF is managed and implemented at constituency
level. Therefore, this study sought to investigate the determinants of effective management of
Constituency Development Funded projects in Kasipul Constituency, Homa Bay County, Kenya.
1.3. Significance of the Study
The main goal of CDF funded projects is to have immediate impact on socio-economic
development. Thus, the purpose of the CDF projects is to alleviate poverty, improve lives,
infrastructural development and other aspect of local development. These projects are for the
community as such their benefits are felt by all individuals in the community. To sum up, the
CDF kitty seek to address the regional development imbalances, targeting pro-poor as well as
expanding and improving development coverage in the republic. This can be achieved by
involving local people in decision making and prioritization.
1.3.1. Significance to Policy
The findings from the study may inform CDF policies at the National Assembly level, County
government level and the CDF Secretariat level on the administration of CDF at the constituency
level and how such administration accelerate or deter projects completion. Particularly, the
policies may be empirically informed about the following key aspects of CDF administration;
analysis of factors that informed changes in the administration structure of the Fund, the level of
fund awareness brought about by these administrative changes among the constituents, the level
of community participation in the selection and implementation of projects brought about by the
administrative changes, the administrative, transparency and accountability mechanisms brought
about by the changes and whether CDF projects had benefited the local citizens by comparing
outputs against stated objectives of the Fund.
1.3.2. Project Manager, CDF Committee and Other Stakeholders
Project management usually entails various stakeholders and resources such as budgetary,
technical and human variables. Furthermore, a lot of CDF projects are initiated in unpredictable,
dynamic, political and turbulent environment. This makes the process of project implementation
complex thus stakeholders such as project managers are faced with fragmentation, superficiality
and role overload. Therefore, this research expounds on various factors under which different
stakeholders such as project manager, citizens, CDF committee among others control so as to
have a successful project management.
1.3.3. Significance to Academics
The findings from this study may attract interests in different academic scholarship including;
governance, project management, strategic management, economics, sociology, political science,
leadership on factors that informed changes in the administration structure of the Fund, the level
of fund awareness brought about by the these administrative changes among the constituents, the
level of stakeholders participation in the selection and implementation of projects brought about
by the administrative changes, the administrative, transparency and accountability mechanisms
brought about by the changes and whether CDF projects had benefited the local citizens by
comparing outputs against stated objectives of the Fund.
1.3.4 Significance to General Readership
CDF is today a household name and cuts across many interests in the constituencies and the
wider society. The findings from this study therefore, will elicit readership interest across general
readers on how the administration of CDF accelerates or luck of it in project completion in the
Constituencies in the Kenya. The general readership will be interested in what informs changes
in the administration structure of the Fund, the level of fund awareness brought about by the
these administrative changes among the constituents, the level of community participation in the
selection and implementation of projects brought about by the administrative changes, the
administrative, transparency and accountability mechanisms brought about by the changes and
whether CDF projects had benefited the local citizens by comparing outputs against stated
objectives of the Fund.
1.4 General Objective of the Study
The general objective of this study was to investigate the determinants of effective management
of Constituency Development Funded projects in Kasipul constituency, Homa Bay County,
Kenya.
1.5 Specific Objectives of the Study
i. To assess the influence of projects financing on effective management of Constituency
Development Funded projects.
ii. To establish the contribution of stakeholder participation on effective management of
Constituency Development Funded projects.
iii. To determine the role of political influence on effective management of Constituency
Development Funded projects.
iv. To establish the influence of technical capacity on effective management of Constituency
Development Funded projects.
1.6 Hypotheses of the Study
H01: There is no significant relationship between projects financing and effective
management of CDF funded projects.
H02: There is no significant relationship between stakeholder participation and effective
management of CDF funded projects.
H03: There is no significant relationship between political influence and effective
management of CDF funded projects.
H04: There is no significant relationship between technical capacity and effective
management of CDF funded projects.
1.7 Assumptions of the Study
The following formed assumptions of the study;
i. That the concept of CDF is familiar amongst the respondents and they are able to provide
the required information that is needed for this study.ii. That the project completion in the Kasipul Constituency is linked to CDF management.
iii. That the respondents who are recruited from the study uniformly understand the CDF
projects and can distinguish them from other Government and Non-governmental
projects. iv. That the sampled respondents avail themselves during the period of carrying out this
research and their responses are honest.v. That the current data or information on selected CDF projects is available in the CDF
offices.
1.8. Scope of the Study
The study was limited to evaluating the effective management of Constituency Development
Funded projects in the financial year 2013/2014- 2015/2016 in Kasipul Constituency, Homa Bay
County, Kenya. The study covered; state of CDF project in the Constituency, examined projects
financing of the CDF Projects, level of stakeholder participation, political influence in CDF
projects implementation and technical capacity of those awarded tenders. The study sought to
collect data from Kasipul Constituency Homa Bay County, CDF committee members in the
Constituency, suppliers of CDF projects and key informants on management of CDF projects.
1.9. Limitations of the Study
The following were the limitation which could hamper the study from attaining its objective and
testing the research hypotheses.
i) The sampled size of selected CDF projects could be small so as to enable generalization
of the finding to all constituencies in Homa Bay County as well as whole country. To
address this limitation, the study selected a sample that was very representative coupled
with selection of respondents with extremely high variability.
ii) The study suffers from some non-response especially from CDF administration because
of the sensitive information of funds and vested political interests. In some cases, some
respondents could be apprehensive about the motive of the study which may affect
collection of data. The researcher guaranteed the respondents that this study was purely
academic and the information provided was treated with utmost confidentiality and their
identity kept anonymous.
1.10. Conceptual Framework
Below is a conceptual frame work on management of CDF and project completion in Kasipul
Constituency in Homa Bay County.
Independent Variables
Figure 1. 1: Conceptual Framework
Source: Researcher (2017)
The first independent variable was project financing which was determined by the availability,
allocation and disbursement of funds in effective management of projects, the second
independent variable was stakeholders’ participation characterized by; frequency of stakeholders’
participation in project management, level participation and tasks performed during citizen’s
participation. The third independent variable was political influence whose dimension included
political interest in identification and allocation CDF project, politician commitments and
political will to manage CDF projects. Lastly, technical capacity which was determined by
competence, skills and experience of PMC and CDFC in the management of projects. The
dependent variable was effectiveness of CDF project management characterized by; projects
Moderating Variable
Dependent Variables
Stakeholders ParticipationFrequency of participationLevel of ParticipationKey tasks performed
Effectiveness of CDFProject Management
Projects completed per time scheduleProject completed as per the budgetProjects on the planned scopeProjects achieving set Goal and objectivessatisfaction
Political InfluencePolitical interestPoliticians commitment levelPolitical will
Project FinancingAvailabilityDisbursementAllocation
Technical CapacityCompetenceSkillsExperience
Existing Legal framework
NG-CDF Acts
completed on time as at the budget, meeting the set objective/s and also projects covering the
planned scope. The intervening variable was the CDF legal framework. It was hypothesized that
when the state of the current CDF projects are positively influenced by availability of funds,
stakeholders’ participation, political influence and technical capacity then the effectiveness of the
CDF projects will increase in terms of projects completed on time, scope and budget leading to
impact on citizen lives and the wider society.
1.11. Operational Definition of Terms
CDF Projects: This was taken to mean Constituency Development Projects funded through
Constituency Development Fund kitty. These projects could be security, education, health or
infrastructure projects among others.
Constituency Development Fund Financial Management – this is developing financial
systems that will track CDF money from disbursement to when they financial activities are
audited.
Constituency Development Fund: This is a devolved fund from the National Budget allocated
to the constituencies in Kenya for purposes of funding socio-economic projects in the
constituencies.
Constituency: This is a group of voters within a specific region demarked by law who elect a
representative to a legislative body.
Effectiveness of CDF Project Management – These are functions needed to ensure that CDF
funds serve their intended purpose including timely execution of the projects within the allocated
budget and scope to achieve the initially specified objective/s in Kasipul Sub-County.
Constituency development Fund Management: This is the tasks needed to control the
operations and plans of the devolved fund at the Constituency level for the purposes of
implementing the projects selected by the locals
Project Implementation: Involves mobilization, utilization and control of resources in order to
facilitate project operation.
CHAPTER TWO
2.0 LITERATURE REVIEW
2.1. Introduction
This chapter presents the theoretical framework guiding this study, empirical review of related
literature according to the specific objectives, and gaps in both the theories and literature
presented.
2.2. Theories Informing the Study
This study was guided by project completion theory, stewardship and competence based theory.
The project completion theory was the main theory as it focuses on the CDF/ CDF project
implementation which is an indicator of the dependent variable in this study. The competence
based theory was also used as it lays down the foundation of how management can use available
resources such as human resources, financial resources and other resources to achieve effective
management of CDF funded projects. Lastly, the study also included stewardship theory which
gives it a governance perspective as CDFC, project managers, political leaders and other leaders
are required to act as stewards in the management of CDF.
2.2.1. Project Completion Theory
Project completion theory according to Nutt (1996) is considered as various steps taken serially
by reliable agents of an organization to scheme change process so as to stimulate compliance
required for installation of changes. Project managers utilize project completion theory so as to
make organization achieve planned changes through creation of environments in which changes
can persist. Nonetheless, the pervasiveness of project implementation has made it difficult for
procedural steps to be implemented. Slevin and Pinto (1987) affirm that it is difficult and
complex to successful implemented project. The realization of successful implemented project
depends on the project manager’s capabilities in terms of energy and time on financial, technical
and human resources.
Further, there are a number of determinants which influence project implementation outcome and
they need to handle them with utmost care. They include: bureaucracy that is witnessed in
government offices leading to delay in paying contractors, contractors delivering project below
required standards and expectations, project cost escalation due to inflation, change in
Government which are frequent, scope of project increasing, pre-contact consultation changes
especially architects, inadequate working capital, project finance plans which are ineffective,
parastatals restructuring and reorganization, awarding contracts indiscriminately without
referencing to location, availability of funds, political consideration in determining contracts,
shifting of original design and political influence (Harries & Reyman, 2010).
Project completion theory underscores various critical success factors during project
management. They include top management support and project schedule plan. Top management
support for project or any kind of implementation determines success or failure of a project
(Schultz & Slevin, 1975). However, Beck (1993) revealed that the success of project
management does not wholly depend on top management support, direction and authority but
more importantly the manner in which top management set organization goals as well as
implementing plan. Schedule plan involves coming up with a comprehensive plan that is needed
for all implementation process stages. The process should include all stakeholders so that their
views are incorporated during implementation process (Pinto & Slevin, 1989). Most importantly
for this stakeholder involvement is client consultant for successful project implementation.
Anyanwu (2003) asserted that the extent to which clients participate during implementation
process will determine the degree of variation in supporting the project. The client’s participation
should be limited to the early stages of project management but should be considered throughout
project life cycle (Schultz, Pinto & Slevin, 1987). This theory was found to be more
comprehensive in explaining the relationship between all independent variables and effective
CDF management.
2.2.2 Competence Based Theory
Competence theory was established in the 80s by MCBer and McClelland. They expounded that
competency as the essential quality of a person that is causally identified with criterion-
referenced efficient as well as prevalent performance in a situation or job (Cicmil and Hodgson,
2006). Competencies of an organization can be trailed back to singular competencies, yet they do
not rise to the straightforward entirety of individual competencies, in light of the fact that
individual competencies, yet the manner in which they are associated influence them. This
implies the competencies of an organization is of social character and is typified in the structure
of an organization.
Competence is the main business input that has the previously mentioned attributes, this is the
reason it may be deemed as the most significant asset. As indicated by one of the proponents of
the theory, economic information is embodiment of competence on which the transferability of
the other rare assets relies, however which itself can't be moved or be estimated dependably
(Pelikan (1988). Carlsson-Eliasson includes (Kapás 2000) that competence is the capacity of the
company to utilize just as to recognize and grow its potentials in production. The competence of
the company relies particularly on the competencies of the leader and ultimately the owners will
follow. The shortage of competencies as an asset is a perspective on primary significance, since it
is the possible motivation behind why companies cannot optimize.
The theory of resource-based recommends that a company A is more fruitful than company B if
A controls increasingly viable and additionally proficient resources than B (Hunt and Davis,
2012). The competence based view, rather, goes above and beyond: Firm A must be more fruitful
than B if A is in a situation to utilize the accessible assets all the more adequately or potentially
proficiently than B. This obliges the accessibility and the use of competence which cannot
rapidly be copied individually substituted by competitors (Teece et al., 1997).
Though the resourced based view infers that prevalent assets will produce performance contrasts
among companies, the competence based view inclines toward a progressively inconspicuous
thinking. Heterogeneous and homogeneous assets are the beginning stage of the chain. Be that as
it may, the resource enrichment is not sufficient so as to clarify performance contrasts. The
company on its own must be in a situation to utilize these assets in market-oriented and objective
way. This is just conceivable if there should arise an occurrence of accessible activity related
competencies. They unfurl the capability of assets and afford the company to adjust to the
prerequisites in target market promptly in a non-irregular way.
Competencies fill the illustrative lacuna between performance and idiosyncratic resources by
deliberating both exercise and “resource streams" (Dierickx/Cool 1989). In regards to Freiling,
Gersch and Goeke (2008), there is additional motivation behind why the competence based point
of view goes past the resource based view by filling an explanatory hole of the last mentioned.
The causal augmentation of the resource based view exists in the clarification that it takes
capabilities so as to create resources by resource alteration forms. All things considered,
contrasted and the resource based view the competence point of view offers new conceptual
dimension which catch more parts of the mind boggling and dynamic interchange of
competence, resources and assets(Hong and Stahle, 2005).
Proficient competency in the management of project is accomplished by the mix of knowledge
gained in the course of training, and development of skills via experience and the utilization of
the gained knowledge. Present day practices of managing projects in this way, requests other
knowledge in regards to management and in general, coupled with skills that stretch out past the
technical facets of areas in traditional engineering. As projects obviously constitute part of
organization function, a great part of the extra knowledge will overlap with the general capacities
needed for overseeing ventures. This will incorporate areas such as ; stress management,
individual time management, conflict management, personal administration, organizational
behavior, operational planning, strategically planning, marketing and sales, accounting and
finance (Abdelnaser et al., 2012).
The theory of competency is of relevance to this study based on the fact that it expounds on the
importance of having stakeholders that have the required competence in the management of CDF
resources for effective management of CDF funded projects. Any project requires various
resources such as financial, human resources, technological and other tangible resources for
effective implementation. However, the competence of stakeholder such as leadership, technical,
risk management, cost control, effective communication among other would results to effective
management of the projects. Abilities gained via practice and learning is considered as technical
skills. Therefore is essential for managers managing NG-CDF projects in regard to supervising
other personnel. Interpersonal skills will empower the managers of projects to appropriately
interface with others individuals for instance committees of CDF and project management in the
project management funded by CDF. Theoretical aptitudes will help the managers of project in
the development of idea, comprehend project ideas and the implementation of projects funded by
CDF effectively.
2.2.3 Stewardship Theory
Theory of stewardship was related to regulatory frameworks in regard to management of CDF
funded projects. Decision making of project managers is dependent on the procedures and
policies as per the CDF Act. Davis and Donald proposed the theory of stewardship in 1993 and
1991 respectively. This theory expresses that there is no irreconcilable circumstance between
owners and managers. The most crucial thing is to discover harmonization between the managers
and owners (Tornyev and Wereko, (2012).
Development of stewardship theory has pursued two distinct yet shortened tracks. The primary
stream of stewardship inquires about focuses on the director as the unit of investigation and the
inborn inspiration and situational settings that explains behavior of stewards (Wesley, 2010).
Tencati and Zsolnai (2010) considers a positivist perspective on theory of stewardship by
expressing that proprietors who plan structures of governance that amplify the productivity of
steward CEO's quest for unrivaled organization performance will be remunerated. His
perspective takes a normative perspective; that the focal point of proprietors should change to
mirror the presumption of steward-principal when they accept to utilize a steward. Proprietors
that accept their companies requires solid oversight of the executives ought to give solid agency
recommended structures of governance; then, proprietors that consider or believe their
organizational management that require the scope to settle on decisions autonomously and
independently ought to guarantee governance structures take into account greatest adaptability in
decision making of the management.
Adoption of stewardship approaches within the government sectors will bring a number of
changes within the sector, because stewardship theory serves as accountability mechanisms for
ensuring good monitoring and evaluation of government projects (Cribb, 2006). This is because
stewardship nature of governance enables the compliance of certain policies within the
organizations (Albrecht et al., 2004). Therefore, using this kind of theory within the context of
government agencies will lead to the attainment of their respective objective because the
stewardship theory has concerns that might lead to project success.
Stewardship theory is concerned with the matters that organizations’ leaders have the obligation
of ensuring better achievement of such organization activities than any other selfishness
(Donaldson & Davis, 1991). The same is applicable to CDF projects context, if the National
Assembly does well in terms regulatory framework, the CDF committee will also do well toward
the objective achievement of the national government through CDF projects. The theory on
stewardship is of importance to the study by helping in explaining how the regulatory framework
affects the effectiveness of CDF projects. Financial regulations help in accountability and
management of CDF funds. Disputes/conflicts are resolved according to the regulations put in
place. The theory is relevant since the regulations for the project process helps in ensuring that
the CDF projects are implemented and that they perform.
2.3. Review of Empirical Studies
This section is structured according to the empirical studies on the determinants of effective
project management with special focus on the resource allocation and availability, monitoring
and evaluation, stakeholder participation and the political influence in the decentralized system
of governance project management.
2.3.1. Project Financing
Project management is critical as it allows monitoring of project progress which can be realized
through financial process of soliciting and maintaining sufficient finances for project activities
(Gasper, 1999). Adequacy of funds is crucial for effective implementation of projects to be
realized. Narh (2016) cited inadequacy of funds as the main resources for poor project outcomes
such as delay in completion and unexpected poor standards. Rosenau and Githens (2011)
commitment of financial resources as well as other resources to project management especially
from the benefiting communities are crucial for successful project completion.
Financial resources allocation is essential to all successful project management. Good financial
governance is imperative in any public project as it enhances accountability and transparency.
According to African Financial Governance Status Report (2011) prudent financial governance
ensures there is efficient and effective use of resources as well as sound fiscal management. It
can be concluded that to ensure an organization attains maximum level of accountability and
transparency in the utilization of organization financial resources and long-term success both
economically and socially, there is need to employ financial governance systems which are
efficient and effective in the use of resources. Jordaan (2013) asserted that various recent
literatures underlined the significance of prudent financial governance through adoption of firm
systems of financial management to poverty reduction and service delivery so as to attain
sustainable development goals.
The execution of budget is the stage in which resources of organization are utilized so as to
implement various activities within the organization. During budget execution, focus is usually
directed so as to comply with budgetary authorizations and this is subject to internal control
system governance. Muhunyo and Jagongo (2018) faulted vulnerable internal control systems as
recipe for financial misappropriation through side deals to influence contracts or making of
unapproved side payments. In effort to ensure that there are stringent internal control systems for
good governance, there must be provisions that explain the roles of the management, financial
accounting and payment which associate with budget execution.
Empirical evidence has supported the notion that financial resources management through the
process of budget execution has strong relationship with governance of projects. Using US
organizations, Elbannan (2009) revealed that quality internal controls have positive relationship
with good governance. Further, Ahmed Sheikh, Wang and Khan (2013) indicated that board
governance efficiency is positively related to the effectiveness of internal control. It can therefore
be deduced that good governance is dependent on internal control system strength in regard to
project execution. One of the most vital reasons for delay of construction sector in Malaysia as
indicated by Sambasivan and Soon (2007) is deficient customer's funds. Haseeb et al's. (2011)
study additionally expressed that, financial issues are significant delay factors of construction
industry in Pakistan. Khalied and Amr (2009) proposed that projects which are infrastructural
based require tremendous initial capital expense and are generally undertaken in order to be
operational for a long term purposes.
Examining the small project implementation is influenced by financial resources in India; Jamal
(2004) demonstrated that Indian's cottage ventures began with the producing of straightforward
family unit things however have improved after some time astounding the traditional countries of
the world which are industrial with prominent modern items. He saw that, this incredible
achievement accomplished in the development of cottage industry in India was encouraged by
the administration's enthusiasm for assigning assets to the business as it was resulting to various
job opportunities to its workforce. In Trinidad and Tobago in the West Indies Islands, Mijean
(2007), noticed that efficiency of an endeavor was an immediate result of accessibility of assets.
He further counted the asset types that impact business accomplishment as, skilled personnel,
operating cash and fixed assets.
Sullivan and Mayer (2010) indicated that the most consistent greatest hindrance to timely
delivery of project is budget limitations. According to them, it is difficult to compensate
inadequacies of funds unlike other limitations such as technical or human capacity which can the
compensated through outsourcing and training. Therefore, according to Gwadoya (2012),
financial resources should be realistically planned and estimated in advance before
commencement of projects especially building and construction projects. There is a need to plan
financial resources for various project functions separately so as to avoid run off during the
execution of projects. This can be achieved by having two distinct budget lines for actual project
implementation and another one of project management through monitoring and evaluation.
In Africa, project management approach is considered the most effective technique for turning
around the performance of all sectors of development. Based on factors influencing
implementation of community-based poultry projects in Guinea Bissau, Tounde (2012) noted
that effective project implementation is a field of practice that demands skilled personnel, yet
most project participants did not display substantial ability to effectively perform their individual
project activities. In Ghana, implementation of health projects was hampered due acute cash flow
problems in the district hospitals. It was noted, there was delay in cash disbursement which
disrupted the construction of health unit (Kumi, 2017). Kikwasi (2012) notes that in Tanzania
there are serious disruptions and delay facing government funded construction projects. Some of
the causes of these delays included funding problems, compensation issue, work valuation
disagreement and contractor’s payment delays.
Gwaya et al. (2014) noticed that, financing of project was among essential customer's
commitments. It is attested that, cost overrun and delays in non-private sector investments can
raise the capital-yield proportion in the sector and somewhere else consequently cutting down
the adequacy of the investment. Shamala (2006) pointed out in her study on factors influencing
viability of brick making projects in Busia County that bricks remained the most popular
building material in Kenya, yet lack of resources to transport those products to competitive
markets exposed them to exploitation by the brokers whose prices were poor.
In Bomet County, Chepkorir (2010) established that due to lack of financial resources to put up
green shades for selling agricultural products such as green maize, fruits, vegetables and Irish
potatoes, sellers resorted to lining directly along the road. Moenga, (2015) posits that the most
important factor influencing timely completion of construction projects in Kenya is; financed by
the contractor during the project and delays in contractor’s payment. Kalungu (2010) indicated
that to achieve the objectives and goals set by the government in allocation of CDF resources
proper budgeting practices for the resources should be put in place to aid in planning,
coordinating and control of the resources.
Kalungu (2010) sought to establish the budgetary practices among CDFs in Nairobi County. The
case study was carried out in the eight constituencies of the Nairobi County. The population of
interest was the CDF management committee and project managers as they are the ones
concerned with issues of budgeting in these constituencies. There are fifteen (15) CDF
committee members and a project manager in all the constituencies in Kenya according to the
CDF act 2003. From the study, the researcher found out that activity-based budgeting was
preferred by many constituencies, while a few practiced a combination of activity based and
zero-based budgeting. The respondents cited some challenges to the budgetary preparation as
lack of enough time for budgeting, lack of clear budgeting policies to budget the funds, lack of
enough trained personnel on financial management and lack of access of CDF information for all
and lack of budget committees. This could be addressed if these factors were put in place in
order to enable proper utilization of CDF resources in Kenya for the common benefit of the local
citizens.
A descriptive survey study carried out in Kimilili Constituency by Kibebe and Mwirigi (2014) on
the selected factor affecting CDF projects implementation. The study targeted 103 respondents
who have benefitted from CDF projects and they were selected using systematic sampling,
purposive sampling, and proportionate sampling and stratified sampling design. Data collected
from questionnaires revealed that there was significant relationship between CDF projects
implementation and managerial factors such as knowledge, skills and staff competence.
However, in a qualitative cross-sectional study to investigate financial performance of water
projects in Kenya funded by CDF, the findings from interview conducted on project managers
revealed that fund management practices such use of budgetary allocation has significant strong
positive influence on the financial performance (Kung’u, & Mwangi, 2014).
2.3.2. Stakeholder Participation in the Management of Projects
Citizen participation enhances good governance as such it is a concept that has attracted a lot of
attention in CDF projects. Practitioners in governance, leadership, project management among
other fields believe that success of a project depend on active role played by
citizens/communities in designing, planning, implementing as well as projects that have
influence on them. The increased interest in stakeholder participation emanates from growing
interest to identify and adjust participative tactics in relations to top-down policy making
approaches. Through participation, it is believed that public policies can efficiently maximize
and the people voices can inform public policies (Yetano et al., 2010). In project life cycle, the
nature and number of stakeholders will be at variant; therefore, it is important to perform
regularly identification review throughout the project (Moodley 2002). Participation in project
life cycle takes place at different stage; different levels of society as well as in distinct forms.
These can range along a continuum from contribution of inputs to predetermined projects and
programmes, to information sharing, consultation, decision making, partnership and
empowerment.
The CDF Act (2015) requires that projects undertaken by CDF are community based so that the
benefits derived from these projects are widespread and felt within a particular political
subdivision area (GOK, 2013). Pursuant to Article 10(2)(a) of the Constitution, the Act requires
that there is people participation in determining and implementing of identified project at the
constituency level. The role of participation in CDF funded project is to ensure that funds
released by National Government remains in the constituency. Therefore, participation is a
strategy to allow all citizens irrespective of their social, economic and political status to
participate in democratic processes as well as public decisions (Gikonyo, 2008).
According to Richard (2013), project implementation is found to be more challenging than any
other activity in the project work. He noted that, as the elite spend more resources suggesting the
potential projects to be implemented; the actual implementers are conspicuously ignored leading
to lack of project ownership which subsequently translates into poor project implementation.
Osief-Ofusu (2011) notes that, communities were assembled, projects identified for them and
implementation carried, without any participation in decision making when operationalizing the
project management processes. The Gulbenkian Foundation (1986) in the UK recommended that
there is a need for a center of community development of a national institute with capability to
support practice and at the same time advice local authorities and government on policy.
In conformity to the ideas of Richard (2013), both being professional project consultants based in
Malawi, indicated that the local initiatives that recognized the need for people involvement in all
phases of the project life cycle, delivered satisfactory project outcome in stark contrast to the
projects that ignored the people. Thwala (2001) contends that the participation of public in
developmental projects planning and management is critical for long term success. Nonetheless,
he found out in South Africa that there is little community participation in provision of water
services as they have no say and they are not adequately considered during decision making
processes. Cardwell (2008) in his case study of Philippines, based on sustainability of rural
development projects pointed out that such projects are demand- driven based on perceived
needs of participating communities with involvement and support from local government and
other key service providers. In these projects communities are to take charge of their
developments with improved access to knowledge, technologies and resources.
According to Varis, Rahaman and Stucki (2008), focusing on the implementation of agriculture
projects in Senegal; the highest project output was attainable through extensive stakeholders’
participation in project activities. Payne et al(2011), writing on his experience with community-
based projects implementation in Gambia, disclosed that mature project management practices
that respected the decisions of project members and involved them in critical aspects of the
project, promised efficient and effective project closure with attractive results. According to
Chowns (2014), focusing on his study based on factors influencing the implementation of NGO
funded projects in Malawi, observed that some projects were readily vandalized by the intended
project beneficiaries because such were initiated with minimum stakeholder participation. He
suggested that effective project implementation needed as its key participants, the contribution of
the beneficiaries, since without developing a feeling of ownership, the hitherto project
beneficiaries turn into project enemies.
In Kenya, there is a tradition of passive, active or interactive communal participation in the
implementation of projects (Wasilwa, 2017). In active participation, which is common during
Harambee School projects during former President Moi’s regime, the communities were allowed
to actively participate from beginning to completion of projects. In respect to CDF funded
projects, the people are tasked with decision making process as well as monitoring and
evaluation of projects implemented (Otundo, 2015). For passive participation, the community do
not directly involve themselves with the management of projects however; they are consistently
updated on the progress of the projects. This entails informing them on what are going on or
what has already been done therefore, the community do not intervene with the activities of the
projects and they maintain a distance. Lastly, interactive participation occurs when there is a joint
analysis and planning process amongst various stakeholders so as to enhance existing structure
and taking control of the development process.
Nyaguthii and Oyugi (2013), in Mwea Constituency, Kirinyaga, carried out a descriptive study to
find out the extent of community involvement in community-based projects and its effect on
CDF projects successful implementation. The involvement was determined by their
identification, monitoring, evaluation and implementation. The findings revealed that most of
residents rarely participated in the management of CDF projects resulting to project failures.
Ngondo (2014) investigated the influence of community participation in project management
processes, as one of the contributors to timely completion of CDF projects in Kanyekini ward-
Kirinyaga Central Constituency. This study used descriptive survey methodology. The target
population was 32,333 direct beneficiaries where a sample of 100 project beneficiaries were
selected using simple random selection method. The study found out that project beneficiaries
had not been approached directly to join any of the CDF projects activity teams during the CDF
projects’ planning and implementation, however, where participation occurred, their participation
was valued fairly well and that during implementation deadlines are met to help stay within
schedule, budget and credibility. The study recommended that project managers and their team
should introduce frequent meetings with project beneficiaries and allocate time for them in their
schedules.
Kemei (2014) investigated the influence of Community Participation on Sustainability of
Constituency Development Fund Projects in Tinderet Constituency, Nandi County, Kenya. The
study utilized a descriptive research design technique. The target population for the study
involved 11 CDFC members, 39,109 Tinderet constituents and 20 PMC members. The
community members were selected through cluster random sampling while the PMCs and CDFC
officials were selected through census method. The study also showed that there existed a
significant difference (p<0.05) between community participation in sustainability of CDF
projects although correlation results revealed that the relationship was weak. Some projects were
found to have stalled while others were found to be incomplete and this could be due to non-
involvement of communities in all the phases of the project cycle. The study recommends that
the level of participation in projects should be increased; and the communities should continue
with their methods of organization with more emphasis on regular awareness forums to
encourage citizens to participate in development projects so as to ensure that projects funded by
CDF become sustainable.
Gikonyo (2015) researched factors that results to varying degree of participation of citizens in
projects funded by CDF in Nakuru Town Constituency. The examination configuration utilized
was descriptive while questionnaires with key respondents, key source interviews with CDF
officials, work area audits for finding out information and observation methods. Purposive
examining was utilized to recognize respondents for the Key Informant Interviews. Arbitrary
inspecting was utilized to distinguish essential respondents. The investigation inferred that
participation of citizen has been low. The investigation prescribes all around considered
structures to energize participation of citizen just as elective support of the CDF so as to distance
local development from the present impression of the fund being a token for resident's who
function admirably with the Member of Parliament.
In Isiolo North Constituency, Adan (2012) sought to find out the role of stakeholder on the
performance of CDF projects. To achieve this objective, the study employed descriptive design
targeting 155 CDF projects. One hundred and forty project representatives were selected using
stratified proportionate sampling and CDF committee members as well as government officials
were sampled using census sampling. The findings revealed that all sampled stakeholder
participation had significance influence on project performance. Further, the results revealed that
the constituents (beneficiaries) had critical role on the performance of CDF projects.
From the above reviewed literatures, it is evident that citizen participation is key to successful
implementation of devolved projects as it promotes ownership and sustainability of projects
implemented. However, some reports indicate that about 60 per cent of Kenya’s communities are
excluded from participation in implementing community-based projects (Gituto, 2007). This
implies that despite the fact that the CDF Act provides for people’s participation, CDF projects
have low participation levels. The main concerns in many public development projects are how
to enhance participation effectiveness so as to influence project outcome instead of focusing on
increasing number of participants (Sanoff, 2000). Hence, this study tested the second hypothesis
that posits there is no significant influence of citizen participation on the management of CDF
projects in Kasipul Constituency.
2.3.3. Political Influence
Decentralized projects are inherently political product that ensures service delivery is close to the
citizen they serve as such; they have some direct political implications. Political leaders may
view it as an investment of their political careers with returns. According to Jowah (2012) project
management is heavily infiltrated by politics, as project manager’s work in an environment with
an authority gap which leaves project managers without much power. The presence of different
groups with different personal and organizational goals working in one project, this coupled by
the absence of clear leadership on pertinent issues resulting from the authority gap (Jowah,
2012). The levels of uncertainty in certain issues in the absence of powerful leadership, and
differences of opinion on what is the ‘correct way’, becomes breeding ground for divergent
political formations. The absence of both power and authority therefore results in a project
manager with no stable power base.
CDF is a creation of parliament by Members of Parliament who according to CDF Act 2013 are
the patrons of CDF and also constituency political representatives. In the CDF committee there
are also representatives from the wards who represent political interests. This setup predisposes
CDF to political influence which extends to CDF projects. CDF is additionally seen by Baskin
(2010) as politically-driven projects. He contends that apparently they are politically determined
development activities. Parliamentary contribution in grassroots projects and development of
community as per Baskin (2010) has been developing in numerous nations including Kenya,
Tanzania, Uganda, India, Pakistan, Jamaica, Bhutan and Papua New Guinea. It is additionally
stated that one of the approach apparatuses for this contribution is Constituency Development
Funds (CDF), which submits public fiance to profit explicit political sub-divisions through
allotments as well as spending choices affected by their delegates in the National Parliament.
The structure of the Constituency Development Fund has political influence as a central theme.
Though the Constituency Development Fund Act of 2015 spells out the role of the MP as purely
oversight, their influence of project undertakings has remained vivid as observed by (Nyaguthii
& Oyugi, 2013) in an exclusive study of Mwea Constituency Development Fund. According to
Kenya Human Rights Commission (2010) influence of politicians is evident during monitoring
and evaluation of projects. The politicians have veto power to determine what aspect of project
should be monitored and evaluated, which information should be disclosed for stakeholder
consumption and some areas will be locked out of CDF projects. Therefore, the ranking of CDF
projects will not focus on societal benefits but rather on political mileage. To the constituents,
they will view the CDF projects as political goodwill and therefore they will continue to suffer at
the mercy of their politicians. Projects with benefits that extend beyond host constituency will
not be considered and this is worsened by fragile institutional framework thus they will not be
able to support implementation of such projects.
Ashaye (2010) affirms that, political goodwill is the key to successful institutional projects
development and implementation; conditions and participatory frameworks alone cannot render
government bodies fully responsible. According to him, a country like South Africa had to do
with inequality and populism. The pressures for clientelist distribution are the strongest in
countries with very sharp class stratification, and where a large number of very poor people are
left out of economic growth. Okonta et al (2013) observed political factors have largely been
blamed for hampering community participation in decentralized projects. According to him
bureaucrats and politicians are considered as crucial agents in public project delivery. However,
it was noted that public projects frequently completed with poor quality or abandoned leading to
loss of billions of dollars every year globally.
Studies in countries that are implementing CDF also sight weaknesses in areas of project
implementation, where CDF projects sometimes do not target the neediest and they do not reach
all the community members. Instead project selection is driven by political factors. There are
also challenges in monitoring the implementation of CDF projects. Furthermore, CDF may
negatively impact on the relationship between MPs and their constituents. CDF may contribute
to shifting the relationship between MPs and their constituents from its democratic basis to a
financial basis (Centre for International Development, 2009). The performance of MP is hinged
on their effectiveness in the use of CDF. In Philippines, the performance of an MP is not pegged
on the contribution to legislative motions as well as debate and their ability to make laws but on
their capability in bringing developments that would benefit the constituents (Chua and Cruz,
2004).
The politicians can literally manipulate CDF as in most cases they determine which projects to
fund irrespective of the community priority and principle of checks and balances (Musamba et
al., 2013). The MPs, according by law are required to be part of management structure as well as
oversight of CDF therefore; the CDF is at the mercy of politicians. Therefore, as long as
politicians have major stake in constituency development fund projects, they will use it for
political survival through skewed choices (Kimenyi, 2005). Most of the local people will not be
aware of fund embezzlement and in cases where they are aware they cannot have the audacity to
question the politicians or right channel to lodge their complaint.
Murray (2011) asserted that elected politicians always have interest on the CDF funded projects
in their constituencies in a bid to support their re-election in the next general election. This
interest according to Murray (2011) is not genuine and legitimate as they are sometimes used for
seeking approval for re-election. This has resulted to conflict of interest between the constituents
and the politicians as they make decision on how and when to spend public funds without
consultations. CDF committee members are political appointee by the MP and in some cases, it
has been reported that MPs have overly influence on the CDF committee so as to use them in
rubberstamping CDF projects. This makes the CDF undisputed MP kitty irrespective of their
competence in planning, implementation and development as well as failure to offer adequate
checks to deter abuse. Furthermore, the governing structure of CDF is silent in providing
adequate checks and balances for example, the Board of CDF is unwilling to hold rogue MPs to
account.
Murray (2011) indicated the solution to this problem is to avoid MPs from the administration so
as to avoid accountability and conflict of interest problems. This would allow the CDF funds to
be sent directly to projects identified by constituents via recognized structures. Locations where
the MP does not enjoy much political support tend to be sidelined in project prioritization
(Wanjiru, 2008). Infrastructure projects abandonment is evident of political clientele influence
(Robinson & Torvik. 2004). It is common in countries where politicians make sound promises
for political interest that would benefit them but not their competitors. To get votes, the
incumbent is forced to leave projects unfinished so that when they are re-elected they can
complete them. However, the scenario becomes ugly when the competitor is elected and the
unfinished projects are abandoned in favor of new project for their own political
entrepreneurship.
Studies have indicated that political influence has mixed outcome on the performance of
decentralized projects. In Brazil, Ferraz and Finan (2011) revealed that re-election incentives
force mayors to cut down on misappropriation of funds set aside for development projects as
compared to those mayors who are not after re-election. In India, Iyer and Mani (2012) showed
that politicians use their influence to affect bureaucratic assignment in the public institutions. In
Nigeria, Rogger (2014) found that politicians who are facing high competition in politics prefer
to delegate public projects implementations in their political jurisdiction to more independent
institutions to increase their chances of political survival.
Various authors have indicated that CDF has been mostly utilized for political patronage instead
of local community development initiatives as envisaged in the CDF Act (Mwalulu & Irungu,
2007; Mapesa & Kibua, 2006; IEA, 2006; Gikonyo, 2008; Awiti, 2008). There have been
concerns that only selected persons close to MP are involved in the selection of projects to be
implemented under CDF. A research by Wambugu (2008), in Dagoretti Constituency reveals that
there is political intervention on the implementation of CDF projects which leads to
underperforming of CDF projects in the period of study.
Malala and Ndolo (2014) examined in detail factors that affect the performance of Constituency
Development Fund (CDF) projects in Kenya. The study adopted a quantitative and descriptive
survey research design. The study targeted Kikuyu Constituency constituents who are the
beneficiaries of CDF projects during the financial year 2009/2010. The researcher used
questionnaires for data collection and informal interactive sessions with the members of the
public. Both primary and secondary data was collected during the research. The results revealed
that political intervention directly affect CDF project performance which in turn has resulted into
CDF projects in Kikuyu Constituency being rated by the public (as the evaluators) as being
behind schedule (88 % percent of projects), with a paltry 12 % of projects being on schedule and
no project was rated as being ahead of schedule (0 %). Ntuala (2010) conducted a study on
factors affecting the implementation of CDF funded projects in Tigania East constituency and
recommended that a regulation be enforced to block the involvement of the politicians in the
activities of CDF implementation. He said that their role should be limited to legislative and
oversight.
A study by IPAR on the management and utilization of the CDF in Kenya, found out that, there
was an obvious tug-of-war between MPs and councilors to control grass-roots development
funds. Councilors argued that the local councils are endowed with the relevant structures,
systems and personnel to administer the funds while MPs are individuals lacking any supporting
mechanisms and systems to manage development funds (Mapesa & Kibua, 2006). This implies
that the two groups are competing over who should patronize at local level. Each of the group
seems to lay a claim that, they are better placed to respond to local felt needs and manage the
implementation of development projects. The study also found out that, the MPs opted to excuse
themselves out of being chairpersons and ended up being the patrons of the constituency
committees while the Act makes no provision for a patron (Mapesa & Kibua. 2006), a clear
indication that they act as de facto leaders within the structure.
Previous studies have shown prioritization of projects in constituency by politicians has resulted
to budgetary allocation and utilization of funds. Politicians have been found not to prioritize
projects that are much needed by locals for their political interest (Richard, 2013). Further, the
appointments in the CDF board of management are met with political influence resulting to
incompetent board (Baskin, 2010). Ongoya and Lumallas, (2005) asserted that CDF has the
possibility to be utilized politically for mobilization of political support and building politician’s
reputation. Gikonyo (2008) alluded that the CDF fund is purely a political tool with no particular
development agenda. According to Wamugo (2007) the character and the commitment of an MP
on the CDF utilization would determine the success of the fund.
Wabwire (2010) indicated that there is lack of political will to effectively disseminate
information about CDF to the local people, by for instance organizing meetings with members of
the public in the constituency. Lack of access to information by the public also breeds ground for
misappropriation of the funds by the officials. However, Mwangi (2015) revealed CDF project
monitoring and evaluation is not significantly influenced by political influence. Further,
Odhiambo (2007) explained that reduction in political intervention and enhancing community
participation is likely to have positive outcome on local development projects as the locals can
manage and control funds dedicated to these projects. Also, Baskin (2010) hinted that elected
politicians play critical role in sourcing funds from CDF in school development hence politics
affect the scope of fund local school will receive from CDF.
Tero (2014) sought to investigate the factors influencing performance of CDF funded dispensary
projects in Kenya using a case of Nandi County specifically to determine the effect of
commitment from political leaders on performance of CDF funded dispensary projects. This
study used descriptive research design. The target population of this study comprised of the CDF
dispensary projects committees in Nandi County, the staff working in the dispensaries, the local
leaders, the beneficiaries of the dispensaries. This study used questionnaires as the data
collection instruments. The study revealed that there is low level of transparency and
accountability in the CDF dispensary projects due to interference by political leaders. This study
recommended that implementation team needs to be trained, educated and supported to enhance
their competency and delivery.
Maalim and Kisimbii (2017) sought to establish the factors affecting (CDF) projects performance
with reference to political influence of CDF projects in Kenya. The study targeted CDFC
members and PMC through stratified random sampling. Valid data collected using questionnaire
revealed that political influence has significant influence on monitoring and evaluation of CDF
projects. Kamau and Muturi (2015) tried to evaluate the variables influencing the effective
execution of projects funded by CDF in Kenya. The examination was conducted in Nyandarua
County, Kenya. The study was based on descriptive design. The population of interest was 60
participants drawn from CDF committees. The study sampling method was census. The
collection of primary data was facilitated via structured interview. The discoveries showed that
there exists a frail and negative connection between CDF projects completion and interest of
politicians. It is suggested that mechanism of accountability and transparency ought to be set up
and executed in regard to projects funded by CDF.
A mixed methodology case study approach on the relationship between CDF and resource
allocation politics in Kenya was conducted by Kirk (2016). The study was carried out in six
constituencies of Rongo, Taveta, Njoro, Wundanyi, Webuye East and Tongaren. The respondents
who were interviewed included CDF Committee members, PMCs, civil servants and politicians.
The results revealed that where ethnicity is significant, politicians channeled CDF resources
towards their community and their ethnicity hail CDF as helpful. However, in the absence of
ethnicity supremacy, there is no ethnicity in resource allocation.
Regardless of the abundance of research that has examined political intervention and project
performance, there remain a number of gaps that form the basis for this study. The political
influence was mainly used in conjunction with monitoring and influence. Further, there has been
amendment in CDF Act the prefix National government has been added to avoid conflict of
interest with county government projects. The MPs roles have been considerably curtailed as
compared to when majority of the reviewed studies were carried out. It is imperative therefore,
that the understanding of political intervention as an antecedent of project implementation is
enriched through extending the frontiers of research.
2.3.4. Technical Competence and Skills
One of the main objectives of decentralized system of governance is equitable and transparent
allocation of resources to the benefitting community. The CDF Act (2013) provides that PMCs
will implement projects with support from the CDF and technical advice from relevant
government department.
The processes/activities of project management require high levels of skills and competencies
from both the project staff and the implementers. The focus on capacity building of the project
staff ensures a workforce with appropriate skills to promote participatory and sustainable
implementation of the projects. This implicitly engages the community to be increasingly
inquisitive about their circumstances, assets and create proper intercessions, to address their
difficulties (Wall, Hayes and Renton, 2009). Managers with competency in leadership ought to
be urged to control adjustments and accomplish supportable projects results. Donors upheld
projects and programs must be structured and oversaw so that there is some adaptability in
execution. Plans should now and again be staged and permitted to develop as lesson are
acquired, field level supervisors should in this manner have the option to react rapidly to
priorities and dynamic needs, and procedures related to financial and administrative management
ought not be made troublesome (OECD, 1999). Programs and projects can only set realistic
objectives in light of such practical constraints. Achievement of staff competencies through
training need to be encouraged in all the government sponsored projects like the CDF Projects.
In his study, Adan, (2012) indicated that technical officers have a positive impact on the
Constituency Development Funded projects performance through their roles in project
identification, planning, implementation and monitoring and evaluation of such projects.
Similarly, Kaliba (2013) revealed that there is a high influence of the role of technical expertise
on utilization of CDF funds at 0.683 per unit increase in utilization of the funds. Tero (2014)
concluded that the competence of the implementation team influenced the performance of the
CDF funded dispensaries. He recommended that implementation team needs to be trained,
educated and supported to enhance their competency and delivery. He also recommended that
human resource provision should utilize individuals to effectively achieve results.
According to Thomas and Thomas-Slayter (2019), self-help projects in Kwale district were
discovered to be doing poorly, due to lack of training. She believes that a trained business
person will be able to evaluate the course of a venture in view of both internal and external
forces and fix any deviation if identified. In the study based on influence of training on the
implementation of community-based projects in Nyeri District, Rugir and Njangiru (2018)
indicated that training in skills and knowledge of basic project management should be
emphasized in order to steer projects effectively. The study recommends that the government of
Kenya should strengthen project management curriculum at all levels in education ladder to
equip school leavers with project management knowledge, that would help them obtain
livelihood without having to rely on formal employment.
Chesiyna and Wanyoike (2016) sought to establish the determinants of effective implementation
of CDF funded projects in Baringo Central Constituency, Kenya. The study employed a
descriptive design using quantitative approaches. The target population was all 150 project
beneficiaries, management committees and constituency planning and development officers in all
CDF funded projects. The study used closed ended questionnaires to collect data. The study
found that training influenced effective implementation of CDF projects. The study recommends
enhanced planning and training in order to have effective implementation of CDF projects in the
country.
Mwangi et al (2015) sought to establish the factors affecting (CDF) projects performance with
reference to technical capability of CDF projects in Kenya. The study targeted CDFC members
and PMC through stratified random sampling. Valid data collected using questionnaires revealed
that technical capacity has significant influence on monitoring and evaluation of CDF projects.
In another descriptive study, Wanjiru (2013) sought to find out influence of technical capacity on
performance of CDF projects in Kenya. The sample size comprises 100 CDFC, PMC and CDF
committee members. Data collected using structured questionnaires revealed that technical
capacity was crucial for coordinating various activities as well as different stakeholders which
influenced performance of CDF projects.
Kipsaina (2010) sought to investigate the influence of attitude, skills and knowledge on CDF
project performance in relationship to monitoring and evaluation in Emgwcn constituency. The
study employed cross sectional research design. A census sampling design was used in which a
total of 30 respondents were involved in the study. It was concluded that project implemented’
knowledge, skill and attitude influenced performance CDF projects in Emgwcn constituency.
The study recommended that project implementers need to be empowered with the right skills,
attitude and knowledge in regard to monitoring and evaluation.
The literature review has exposed that availability of resources influence project implementation
and outcome. To achieve the objectives and goals set by the government in allocation of CDF
resources proper financial management practices for the resources should be put in place to aid
in planning, coordinating and control of the resources. Little research has been carried out on the
area of financial management practices specifically on the CDF, though there has been continual
attention on the misappropriation on the use of CDF fund. Similarly, the empirical studies have
revealed that, the stakeholder competence and technical skills influences project management.
Therefore, this project derived the first hypothesis of the study to test the relationship between
resources availability and effective management of CDF project in Kasipul Constituency in
Homa Bay County, Kenya.
2.3.5 Legal & Policy Framework Governing CDF Management
The Constitution of Kenya is the supreme law of the Country; all laws work within the precincts
of the constitution. Thus, both the CDF Act, 2003, and the Constituencies Development fund
(Amendment) Act, 2016, do not contradict the laws of the land in the aspects of utilization of
public resources or any other, and they do comply with Section 99(1-4) of the constitution on the
Consolidated Fund and other public funds. The Constituencies Development Fund Act, 2003 as
amended by the Constituencies Development Fund (Amendment) Act, 2016 are acts of
parliament that provide for the Constituency Development Fund and its subsequent guiding
principles, for instance, establishing various CDF institutions and organs with clearly defined
roles. These legislations guide the CDF project cycle from identification, implementation to
monitoring and reporting (GoK, 2016).
The CDF Implementation Guidelines were first development by the National Management
Committee and subsequently updated by the CDF National Management Board. Although they
don’t have statutory authority, they are mandatory guidelines designed to guide operational
aspects of CDF management such as the code of conduct of committees, procurement processes
and so forth.
The Ministry of Planning and Devolution which is the parent ministry of CDF also issues
periodic circulars and regulations to guide CDF operations. The Public Procurement and
Disposal Act, 2005 as read together with the subsidiary legislations, Public Procurement and
Disposal Regulations 2006, and 2009 respectively deal with procurement by public entities. The
2006 guidelines give specific reference to the CDF by establishing procurement thresholds which
spells out rules and levels to be adhered to when procuring. In addition, the legislations are vivid
on the need and importance of Tendering Committees at all levels which have an oversight role
in the procurement process (GoK, 2013).
The Public Officers and Ethics Act, 2003: Provides for a code of conduct and ethics for officers
and requires financial declarations from certain public officers. One major sticking issue is the
article on Conflict of interest. This directly applies to PMCs in the process of assessing and
evaluating tender applications for various projects. [If a public officer has interests in a particular
project, it’s prudent for him/her to declare his interests beforehand]. This in bid to stem conflict
of interests that most cases result to favoritism, bias, nepotism and other economic vices (GoK,
2012).
Closely related is the Anti-Corruption and Economic Crimes Act, 2003 which provides for the
prevention, investigation and punishment of corruption, economic crimes and related offences.
This Act established the Kenya Anti-Corruption Commission [KACC], authorized to investigate
allegations of corruption in Public entities in the country, CDF inclusive. In this regard, members
of the public have an obligation to report suspected criminal activities involving CDF to the
KACC. Other legislations include: The Public Audit Act, 2003: -Provides for the audit of
government, state corporations, public entities and local authorities, to provide for economic
efficiency and effectiveness; The Government Financial Management Act, 2003: -Provides for
the proper management of the government financial affairs and for persons to be responsible for
government resources (GoK, 2012).
Constituency Development Fund and political decentralization of asset to the devolved unit of
management is viewed as one of the positive move by the centralized authorities yet there is a
worry about the hierarchical and the executives’ structure of the CDF since government officials
control the disbursement of funds as well as formulation of projects. Government officials can
manage what is to be checked and assessed on a certain project, what the stakeholders ought to
or ought not know and certain places will not be considered during distribution of CDF projects
(Kenya Huma Rights Commission, 2010). Projects of CDF will at that point be put together and
positioned with respect to political advantages as opposed to the more extensive advantages to
society. The constituents will endure believing that those activities are a civility of the generosity
of the political leaders. Those projects stretching out advantages to other constituencies outside
the host voting demographic will be dismissed and this combined with the feeble institutional
structure makes them not to help evaluation and monitoring (Mwangi, 2005).
2.4. Gaps to be filled by Current Study
This chapter reviewed relevant literature relating to research general and specific objectives. The
study was guided by three theories which were anchored to the research objectives and therefore,
they form the basis of this project as indicated in CDF Act (2003, 2013). The aim of empirical
studies was to review what other researchers have done in decentralization and project
implementation with aim of critique, presentation of research argument and creation of research
gaps which the current study will contribute to new knowledge in theory and concept.
It is evident that project financing has influence on project performance yet there are nascent
studies that have explicit relation between project financing and project management
performance. Moenga (2015) posits that the most important factor influencing timely
completion of construction projects in Kenya is financial resources. However, the study did not
indicate how projects finance influence effective project management which this study sought to
establish. Similar outcome were reported by Kalungu (2010) although the study took a narrow
scope by focusing on the budgetary practices of CDFs in Nairobi County. The study scope was
wide as it did factor all constituencies in Nairobi County and there was no comparison done
among various CDF offices. In the light of the above studies, it was necessary to examine what is
the influence of project financing on effective CDF funded projects in Kasipul constituency.
Previous studies have revealed inadequacies in the theories and theoretical framework that
underpinned and guided the study on the management of CDF funded projects (Chepkorir, 2010;
Moenga, 2015). In scholarly work, theories have been frequently used in relation to the
objectives of the study and they have strengthened arguments in relation with philosophical
approach of the study. However, these authors have been silent on the implication of theories to
the study findings thereby weakening the arguments hence, less theoretical contributions.
Theories have been casually used in the study therefore, necessitating this study to use project
completion theory, stewardship theory and competence based theory to guide the study.
The peak of theoretical framework is project completion theory as effective management of the
projects is determined by the mechanisms in which completed projects are delivered to the
beneficiaries by various stakeholders. In this regard, competent use of resources such as
financial, human and technological resources as provided by national government would enhance
effective CDF project management hence the inclusion of competence based theory. Various
studies have indicated that resource availability and allocation have significant influence on the
project management (Kibebe & Mwirigi, 2014; Haseeb et al., 2011). However, the approach
taken by this study favors the application of competence based theory unlike resource based
theory which this study used. This study, sought to find out effective management of CDF
projects and therefore, it is presumed that availability of resources may not result to effective
project management but how the resources are competently utilized. The study also found it fit to
include stewardship theory due to various regulations, Acts and policies that governance the
utilization of CDF kit. Various previous studies on CDF projects have failed to use governance
theories yet, the purpose of CDF is to enhance decentralization and therefore, the study sought to
fill this theoretical gap.
CDF fund are political initiative and politicians have vested interest in the management of
projects for their own political gain. Studies have indicated that CDF projects have mixed out in
relation to political intervention. Most of the study done in Kenya revealed that, political
interventions have negative effect in project implementation while studies in abroad have
indicated positive effect. Tero (2014) revealed that support and commitment from political
leaders and their supporters is necessary for any people-driven development process. Therefore,
there is need to upscale these findings on CDF funded projects in Kenya. The public has also
raised questions about governance and political intervention of the fund; some members of the
CDFC are ill informed about project management and therefore, put in doubt their ability to
manage and govern the CDF funded projects effectively.
Different roles in project management will require different competencies. Previous studies in
principality have failed to address how technical competence of human resources has contributed
to effective management of CDF projects as most of them have focused on its influence and
characteristics in relation to project performance. Adan, (2012) only indicated it has positive
impact but failed to indicate how it affects specific aspect of project management. This was also
indicated by Kaliba (2013) and Tero (2014) as effective aspect of project management was not
addressed. In Baringo Central Constituency, Kenya, Chesiyna and Wanyoike (2016) found that
training influenced effective implementation of CDF projects although the study failed to
indicate which aspect of training influenced effective project management.
In another study, Mwangi et al (2015) indicated that technical capability is significant during
project monitoring and evaluation and effective project management was not investigated.
Another significant knowledge gap was exposed by Wanjiru (2013) and Kipsaina (2010) on
technical capacity and performance of CDF projects. Their outcome was superfluous as they
indicated that knowledge, skills and attitude influenced CDF project performance. The study left
a significant knowledge gap on what aspects of project performance are affected through
effective project management.
Lastly, up-to-date, there are no researches that have been carried out to investigate determinants
of effective CDF project management in Kasipul Constituency or any other devolved units in
Kenya or abroad using regulatory framework as intervening variable. Therefore, this current
study sought to fill the identified gaps per the objectives and extend the findings by examining
the intervening influence of regulatory framework on the effectiveness of CDF project
management and identified determinants. The operationalization of variables is as shown in
Table 2.1.
Table 2. 1: Operationalization of Study Variables
Variable Parameters/Indicators Empirical Studies Technical
Capacity
Competence Jordan (2008), Rapa (2005)Skill Chesiyna and Wanyoike (2016)Experience Zwikael (2006), Al Mashari (2003)
Stakeholder
Participation
Level of participation Yetano et al. (2010) IDEA (2008), Caleb (2015)Frequency of participation Ngondo (2014), Liyong (2012),Key tasks performed Otundo (2015), Nyaguthii and Oyugi (2013)
Political
Intervention
Commitment level Tero (2014), Wamugo (2007)Political will Wabwire (2010)Political Interest Eyaa (2010), Ntuala (2010)
CDF Project
financing
Availability Gasper (1999), Natasha (2003), Disbursement Jack and Samuel (2006), Allocation Kikwasi (2012)
CHAPTER THREE
3.0 RESEARCH METHODOLOGY
3.1. Introduction
This chapter presents the following geographical description of the research area, research
design, target population of the study, sample size, sampling procedure, instruments of data
collection, data collection procedure, reliability and validity of the research instruments, data
analysis procedures and ethical considerations.
3.2. Geographical Description of the Research Area
Kasipul Sub County (Kasipul Constituency) comprises of five wards; West Kasipul, South
Kasipul, Central Kasipul, East Kamagak and West Kamagak. According to Kenya National
Bureau of Statistics 2013 for Homa Bay County, the population for Kasipul Constituency was
projected to be 183,073 in the year 2015 with a population density of 525 KM2. It is one of the
eight Sub-Counties of Homa Bay County. It is Constituency Number 41 and the map of the
Constituency is as indicated in Appendix VIII (Homa Bay County Government, 2013).
The Constituency population is as follows: - West Kasipul Ward (total population approximated
to 41,740); South Kasipul Ward (total population approximated to 41,558); Central Kasipul
Ward (total population approximated to 42,106); East Kamagak Ward (total population
approximated to 23,799); West Kamagak Ward (total population approximated to 34,783).
Poverty rate in the constituency is 49.4% with majority of the population engaged in small scale
agriculture and SMEs. The Constituency poverty index is higher than that of the national average
of 47%. Sixty-six percent of the population attended primary school and 83% of between 15-18-
year-old young people are currently attending school, which is ahead of the national average of
70%. Despite being ahead of the national average on these development indicators, Kasipul
constituency is far behind on other basic infrastructure, particularly electricity and improved
water supply. Only 3.3% of households have electricity, compared to the national average of 23%
(CRA Fact Sheets, 2011). Forty-eight percent use improved water sources and 32% use improved
sanitation, according to 2011 MICS estimates (Homa Bay County, 2013).
3.3. Research Design
A research design is often referred to as the framework guiding the methods chosen by the
researcher which defines the arrangement of conditions for collection and analysis of data in a
manner that aims to combine relevance to the research purpose with economy in the procedure
(Orodho, 2008). The study considered a mixed research design guided by a non-experimental
cross-sectional survey to inform the methods used with the aim of achieving the objective of the
study which was to investigate the determinants of effective management of Constituency
Development Funded projects in Kasipul constituency, Homa Bay County, Kenya. The design
also drew from quantitative, qualitative, descriptive and causal approaches.
The research design framework was guided by philosophical assumptions as suggested by
Creswell, (2003) which includes about what constitutes knowledge claims, general procedures or
strategies of inquiry and detailed procedures of data collection, analysis, and report writing
(methods). A cross-sectional survey has no time dimension but relies mainly on the existing
differences between or from among a variety of elements, or phenomena (Uzel, 2012). This
study considered differences across the projects as perceived by the various stakeholders without
considering the time variations over the period. In experimental designs, the researcher has
control by active intervention to produce and measure change or to create differences across the
elements in study (Bachman & Schutt 2006). This study however adopted a non-experimental
approach where no manipulations by the researcher were done to develop differences for
causative experiments.
The consideration of both qualitative and quantitative data was done concurrently thus allowing
the researcher to corroborate and to support the results relative to the same phenomenon with
different methods and to ameliorate internal and external validity. This process is referred to as
triangulation (Lincoln and Guba, 2000; Bentahar and Cameron, 2015). This consideration of both
quantitative and qualitative approaches provided techniques for adequate and holistic description
of the phenomena status of study variables basing on the descriptive design approaches
(Saunders & Thornhill, 2009). The aim of the descriptive approach is to fact find and examine
traits and characteristics of the phenomenal (effective management of constituency development
funded projects and its determinants). To determine the determinants and their influences on
effective management of CDF, a causal approach was also incorporated in the design. Causal
designs are essential in studies that seek to determine the causal relationships between variables.
Causal relationships are explorations of the cause-effect which involves the belief that a variation
in an independent variable causes variation in the dependent variable, when all other things are
held constant (ceteris paribus).
3.4. Study and Target Population of the Study
The study targeted 254 projects in the Kasipul Constituency between 2013/2014 and 2015/2016
in the five wards as indicated in Table 3.1. To get unit of inquiry in regard to the management of
these projects, beneficiaries, CDFC, project managers and national government representative
were considered. The projects were categorized as education, health, water, security, roads,
sports and environment. According to Kenya National Bureau of Statistics (2013) the population
for Kasipul Constituency was projected to be 183,073 in the year 2015. The study therefore
targeted 183,073 possible beneficiaries, 254 project managers, 10 NG-Constituency development
fund committee and 7 National government representatives (departmental Heads from the
respective represented sectors). Therefore, these four population units formed unit of inquiry. To
get information from these categories, questionnaires, focused group discussion schedules and
interview guides was used as tools for data collection.
Table 3. 1: Targeted Projects Per Ward
WardEducation
Health
Security
Environment Sports Roads Water Total
West Kasipul 33 7 6 0 1 6 4 59South Kasipul 30 5 3 0 0 4 2 40Central Kasipul 32 9 4 0 0 5 2 59East Kamagak 39 11 7 2 2 8 8 69West Kamagak 15 3 2 0 0 3 1 27Total 149 35 22 2 3 26 17 254
3.5 Sample Size and Sampling Procedure
A pre-field survey was conducted by the researcher to ascertain on some parameters during the
proposal writing process in Kasipul Constituency. These parameters included: - Projects
executed by the constituency administration within the study period, the type of projects done,
the budget allocated. Informed by this pre-field study, this study sampled 77 CDF projects from
254 projects. According to Mugenda & Mugenda (2008) a sample size of between 10% and 30 %
is a good representation of the target population while according to Dooley (2007), a sample size
of between 10% and 40% is considered adequate for detailed or in-depth studies hence the
30.31% of the CDF projects was adequate for analysis. The sample size of 77 CDF projects was
obtained using coefficient of variation. Nassiuma (2000) asserts that in most surveys or
experiments, a coefficient of variation in the range of 21% to 30% and a standard error in the
range of 2% to 5% is usually acceptable. The Nassiuma’s formula does not assume any
probability distribution and is a stable measure of variability. Therefore, a coefficient variation of
21% and a standard error of 2% were used in this study. The lower limit for coefficient of
variation and standard error were selected so as to ensure low variability in the sample and
minimize the degree of error.
22
2
)1()(
)(
eNCv
CvNS
Where S = the sample size
N = the population size
Cv = the Coefficient of Variation
e = standard error
Therefore, the sample size was:
S = 254(0.212) = 76.87989019 ≈ 77 CDF Projects
0.212 + (254-1) 0.022
Table 3. 2: Sample Projects Per Ward
WardEducation
Health
Security
Environment Sports Roads Water Total
West Kasipul 10 2 2 0 0 2 1 17South Kasipul 9 2 1 0 0 1 1 14Central Kasipul 9 3 1 0 0 2 1 16East Kamagak 12 3 2 1 1 2 2 23West Kamagak 4 1 1 0 0 1 0 7Total 44 11 7 1 1 8 5 77
From Table 3.2, proportionate sampling technique was used to sample project type per each ward
according to the target distribution as indicated in Table 3.1. Proportionate sampling is a
sampling strategy used when the population is composed of several subgroups that are vastly
different in number. The number of participants from each subgroup is determined by their
number relative to the entire population. With this technique, the study ensured that selection of
project type and project per ward is proportionate to the target projects. Therefore, most of the
sampled projects were from East Kamagak and overall, education projects comprised more than
a half (44/77). After achieving the sample size of the projects, the study sampled four units of
inquiry as follows.
3.5.1 Sampling of Project Managers
The project managers/contractors were sampled purposively according to the 77 selected
projects. In this regard, the study first identified the project there after it purposively sampled the
project manager or the contractor responsible for a given project. The purpose of using purposive
sampling was to ensure that relevant information about project management is obtained from
relevant sources. Therefore, 77 project managers/contractors were sampled in this study.
3.5.2 Sampling of CDF Committee
According to the Kenya National Government Constituencies Development Fund Act 2015, CDF
committee at the constituency level should have 10 members. These 10 members represent
general interests of the Constituency. The researcher used census sampling technique of all the
10 CDF committee members to form part of the sample of interest to the study.
3.5.3 Sampling of National Government Departmental Heads
The researcher also targeted the National Government heads of departments as they are included
in the supervision of National Government projects such as CDF. Since the study focused on
seven types of projects, census sampling was used to select seven national government officials
in this case, the departmental heads.
3.5.4 Sampling of the Beneficiaries
Further, the researcher adopted Yamane, (1967:886) formula that can be used to calculate a
suitable sample for the study which comprised of all CDF beneficiaries currently in the Wards.
21
Nn
Ne=
+
Where n = Minimum Sample Size; N = population size: - e = precision set at 95 % (5%=0.05)
183,073 (Study population) x0.5 =
n = 183,073
1+183,073(0.0025)
n = 399.11 ≈ 400 Beneficiaries.
Table 3. 3: Sampling of Beneficiaries
Proportion of
Projects
Population
Proportion
Targeted beneficiaries
sampleWest Kasipul 22.07% 18.07% 85South Kasipul 18.18% 14.02% 61Central Kasipul 20.77% 10.59% 68East Kamagak 29.87% 50.78% 164West Kamagak 7.7% 6.54% 22Total 100.00% 100.00% 400
The researcher applied multi-stage sampling technique to select the 400 beneficiaries of 77 CDF
projects which comprised of 3 stages. In the first stage, all the beneficiaries in the constituency
were grouped according to their wards to ensure all five wards are considered in the study. The
second stage of the sampling was to get the proportionate sample size in each word as derived
from the target population using proportionate sampling technique. The last stage (stage 3) was
to random select the respondents from each ward according to the location of the 77 projects.
Then the researcher formed focused group discussions to get important information that needs
clarification from the constituents.
The projected sample size for the beneficiaries were 400 respondents, all the 10 CDF committee
members of Kasipul Constituency, 77 Contractors/project managers awarded contracts between
2013/2014 and 2015/2016 and 7 National government representatives (departmental Heads).
Sample sizes for different categories are displayed in the Table 3.4
Table 3. 4: Sampling of the Respondents
Respondents Target Sample Sampling Strategy InstrumentBeneficiaries 183,073 400 Multi-stage Questionnaire and
FGDCDF Committee 10 10 Census Questionnaire &
Interview Contractors/projectmanagers
254 77 Purposive Questionnaire
Government Officials 7 7 Census Interview guides
Total 494
3.6. Data Collection Instruments
Quantitative and qualitative approaches (mixed methods) guided data collection procedures were
employed in this study. Tools including questionnaires, focused group discussions schedules and
interview guides were used to collect relevant data on the determinants of effective CDF projects
management in Kasipul Constituency. Primary data was collected by use of questionnaires and
interview guides and focused group discussions.
3.6.1 Questionnaires
A Questionnaire is an orderly listing of questions that one would like to put to the respondents to
solicit particular type of information (Gatara, 2010). It enables the researcher to collect the data
from a large population and within a short time. It also helps capture both qualitative and
quantitative data. In addition, they give a relatively objective data and thus are most effective
when it comes to their usage (Khan, 2008). This study used both the structured and unstructured
items in the questionnaires for the 400 sampled beneficiaries, the 10 CDF committee members,
and the 77 contracted project managers/staff. The unstructured questions allowed the participants
to explain further by providing their own opinions and feelings on the question under study while
the structured questions require respondents to select appropriate responses from a list of them.
Self-administration of questionnaires applied along the researcher’s face to face administration of
questionnaires depending on the education and understanding level of the respondent.
3.6.2 Interview schedules
McMillan (2008) defines interview guide as a form of data collection in which questions are
asked orally and subjects’ responses recorded either verbatim or summarized. He adds that
interviews may be in structured, semi-structured and unstructured form. This study employed
unstructured questions. The interviews were administered purposively to the chair of the CDF
committee and the managers/contractors purposively selected from key sectors funded with the
intention of gathering their insights, feelings and motivations on the determinants of CDF
management in Kasipul Constituency. These Interviews helped to probe for more meanings
about the respondents’ answers. Audio recorders also be used during the interviews
3.6. 3 Focused Group Discussions
This is a qualitative method of data collection which is done through in-depth discussion by a
small group led by a facilitator on a given subject of research and practical significance (Gatara,
2010). After data collection using questionnaire, the researcher organized ten focused groups
(two in each ward) of twelve people each in the different wards of the Constituency. Information
probed until data saturation levels are realized. The researcher first explained to the beneficiary
the essence of the research. Tape recording was done for future reference where information may
have not been properly recorded through writing.
3.7. Data Collection Procedure
Once the proposal was successfully presented, the researcher obtained an official letter from
Kisii University to allow him apply for research permit from The National Commission
for Science, Technology and Innovation (NACOSTI). After obtaining the permit, the researcher
requested NACOSTI to give him an introductory letter/s to the authorities of Kasipul
Constituency. The researcher trained and hired the services of 10 research assistants. Each two of
them collected data from the five wards from the beneficiaries, Government Officials, the CDF
Project managers as well as the CDF committee members. The researcher led the data collection
process by supervising the data collection activities carried out by the research assistants. At the
end of every day’s activities, the researcher had telephone conversation for purposes of
backstopping in order to increase the quality of the data collected.
3.8. Reliability and Validity of the Research Instruments
3.8.1. Reliability
Reliability of measurements concerns the degree to which a particular measuring procedure gives
similar results over a number of repeated trials. The researcher prepared questionnaires and
interview guides and administered them to the similar respondents’ in Kasipul Constituency for
pre-testing purposes. These respondents were not used in the main study. The pilot study
respondents were eliminated in the final study respondents. The study used 15 participants for
pilot study. This is according to Isaac and Michael (1995) who suggested 10 – 30 participants are
ideal in pilot study. A short questionnaire was attached at the end in which they are asked to
indicate the length of time it takes to complete the questionnaire, the questions that they find
ambiguous, those questions that they are uncomfortable with and they will make comments to
improve the questionnaire. To measure the reliability, the Alpha (Cronbach) technique was
employed. Alpha (Cronbach) is a model of internal consistency, based on the average inter-item
correlation. A large value of alpha (preferably greater than 0.7) indicates high level of
consistence of the instruments in measuring the variables. Kline (1999) noted that acceptable
value for Cronbach’s alpha is between 0.7 and 0.9 of which the study adopted.
A scale is said to be reliable, if Cronbach’s coefficient alpha of the scale is well above the
threshold value of 0.700 and the acceptable minimum of 0.600 (Hair et al., 2006). In this study,
the Cronbach’s coefficient alpha for the entire scale consisting of 20 measurement variables was
>0.700 with relatively high corrected item-to-total correlations indicating the presence of high
internal consistency in the measurement scale and therefore reliable and acceptable for further
analysis.
Table 3. 5: Item-to-total Correlations of Performance Measurement Variables obtained
through Pilot Survey
Variable No of items Cronbach Alpha
Project Financing 5 0.847
Stakeholder Participation 5 0.809
Political Influence 5 0.645
Technical Capacity 5 0.866
Regulatory Framework 4 0.834
CDF Management 6 0.827
3.8.2. Validity
Validity refers to the degree that an instrument actually measures what it is designed or intended
to measure (Burton and Mazerolle, 2011; Bolliger and Inam, 2012). Drost (2011) suggests that
there are four types of validity that researchers should consider. This includes statistical
conclusion validity, internal validity, construct validity, and external validity. Statistical
conclusion validity refers to inferences about whether it is reasonable to presume covariation
given a specified alpha level and the obtained variances. Internal validity communicates the
validity of the research itself. External validity of a study implies generalizing to other persons,
settings, and times and not necessarily to the target population. Construct validity exists when a
measure reliably measures and truthfully represents a unique concept. It refers to how well a
concept, idea, or behaviour that is a construct has been translated or transformed into a
functioning and operating reality (Aila & Ombok, 2015). This study assessed the validity of the
study instrument using construct validity.
For this study, construct validity which seeks to measure whether an instrument accurately
measures the study phenomena was tested using factor analysis then confirmatory factor analysis
to verify the construct validity, this is recommended for large sample techniques (n>50) (Aila &
Ombok, 2015). The study used 15 respondents in pilot study to ascertain validity. In addition,
since all the respondents are relatively homogenous in terms of socio-culture and socio-
economic, the results can be generalized to the entire population of the study.
3.9. Methods of Data Analysis, Diagnostics and Presentation
3.9.1 Quantitative analysis
Descriptive and inferential statistics techniques were used to analyze quantitative data after
appropriate data coding done. Descriptive statistics describe patterns and general trends in a data
set. Also, it was used to examine or explore one variable at a time. Descriptive statistics used
included; frequencies, percentages and mean.
3.9.2 Path Analysis
Inferential statistics was used to test the associations and relationships between the independent
variable (determinants of effective CDF project implementation) and the dependent variable
(effective implementation of CDF projects) in Kasipul Constituency. The relationship between
level of the independent and dependent variables was measured using Structural Equation
Modeling (SEM) which is best suited to analyze path for latent variables. This informs whether
the independent variables significantly matter in effective implementation of projects in Kasipul
Constituency and thereby test the research hypotheses.
Diagnostics tests were carried out to ensure that the model fitted meets the classical assumption
that SEM and maximum likelihood estimation linear models are based on. This included
normality test by use of Kolmogorov-Smirnov test which has power to detect departure from
normality due to either skewness or kurtosis or both. Its statistic ranges from zero to one and
figures higher than 0.05 indicate the data is normal (Razali and Wah, 2011) and Multicollinearity
test was performed through assessing the variance inflation factors of the independent variable.
This ensures that independent variables cannot be expressed as linear functions of each other. A
test for heteroscedasticity of model residuals and that of independence of model residuals were
also tested. The heteroscedasticity test was carried out to ensure that model residuals are
homoscedastic based on the assumption that they exhibit a constant variance. Independence test
of the residuals was carried out by testing for autocorrelation using Durbin-Watson test. This was
based on the assumption that the residuals do not exhibit autocorrelation. Considering the use
SEM, a test for common method bias was carried out to ensure the variations exhibited are not
attributed to common method variance from the measurement using the same respondent to
answer the entire questionnaire at once.
Two Structural Equation Models (SEMs) was used in these analyses; that is multiple SEM
without regulatory framework and another multiple SEM with regulatory framework which is a
latent intervening variable. To achieve the specific objectives aimed at determining the
influences of the independent variables on effective management of CDFs, the regression models
were fitted to determine the cause-effect relationships by estimating the mathematical equation.
The coefficient of each independent variable represents the causal influence on effective
management of CDFs. Equation 1 represents the general model used for examining the causal
relationships between the latent dependent and independent variables;
Y=β1 X1+ β2 X2+β3 X3+β4 X4+ε…… ..………………………………………………….eqn1
Where;
У = Effectiveness of CDF project management
β1……β4= Regression Coefficients
X1=Project financing X2= Citizen Participation X3= political influence X4= Technical capacity
ε = the error of term.
To assess the moderating effect of regulatory framework as detailed in the hypothesized
(theoretical) model, a hierarchical regression modeling technique was adopted. In this technique,
a step wise approach was taken where the moderating variable regulatory frameworks (Z) was
added to the first model represented in equation 1 followed by introduction of the interactions
between the regulatory frameworks and each of the independent variables. The influence of
regulatory framework as a moderating variable was determined by examining the effect of the
introduction of its interaction terms with the independent variables. The model to assess the
moderating effect of regulatory frameworks is shown by the equation below;
y=β1 X1+ β2 X2+ β3 X3+β4 X4+βM Z +βM 1 X1∗Z+βM 2 X2∗Z+ βM 3 X3∗Z+βM 4 X4∗Z+ε…
…. eqn 2
Where;
У = Effectiveness of CDF project management
β1 to β4= Regression Coefficients of independent variables
X1 to X4= Independent variables as mentioned aboveZ = Regulatory framework (the moderating variable)βM = Regression Coefficient of the moderating variableXi*Z = the interaction term between the ith independent variable and the moderating variableβM1 to βM4 = Regression Coefficients of independent interaction terms
ε = the error of term.
These analyses were done using STATA version 14 and the quantitative data was presented in
terms of tables and charts. The Structural equation modeling was done using the Analysis of
Moment Structures (AMOS) software version 23. The following is the table presenting the
summarized latent and observed variables together with their measurement scale. Note that both
the constructs were further measured in a five Likert scale and level of analysis included
descriptive, correlation analysis (Observed Index Matrix -OIM calculation) and structural
modeling.
Table 3. 6: Summary of Structural and Observed variables
Objective Indicators/Operationalization MeasureStakeholderParticipation
Level of participations Participation from projectioninitiation to completion
Frequency of participation No of time they are involved in CDFproject management
Key tasks performed Roles given to stakeholders inproject management (structures) andform of participation
Political Influence Political will Prioritization during identificationand allocation
Commitment Level Oversight role in the management ofprojects
Political interest Politically motivated projectsTechnical Capacity Competence Training in relevant areas
Skills Academic qualification, knowledgeExperience Expertise as per the job awarded
Project Financing Availability Presence of funds, transparency andaccountability of available funds
Allocation Auditing, adequacy of allocationDisbursement Frequency and amount disbursement
Effectiveness Projects completed per timeschedule
Stipulated time
Project completed as per thebudget
Within the cost (absence of costoverrun
Projects on the planned scope Initial scopeProjects achieving set objectives ObjectivesSatisfaction Meet expectation of the users
3.9.3 Qualitative data analysis
As indicated by Boyatzis (1998) and Merriam, (1998), analysis of data which is qualitative in
nature should be analysed in manner that the analyst seeks portray data in manners that catch the
context or individuals who created this content on their own terms instead of as far as predefined
hypotheses and measures. This was additionally stressed by Kawulich, (2004). Data which is
qualitative in nature were gathered through KIIs and FGDs were deciphered, and the yield sorted
out into different classifications that were topic based. A top to bottom investigation was
undertaken and discoveries exhibited in type of verbatim citations and narrations. So as to keep
up the setting where the information was gathered or delivered, the analyst treated subjective
information first by representing to a setting with the respondents' terms and from their very own
perspective; also, represented to a context with their terms and from respondents' perspective and
thirdly the researcher guaranteed dynamic center where the he associated with the information
and step by step refined his focus where deem fit. Qualitative data was generally applied in
triangulation of the quantitative information as introduced by the respondents in Kasipul
constituency to improve legitimacy and unwavering quality of all variables related with
successful management of projects funded by the CDF in the area of the study.
3.10 Ethical Considerations
Ethical considerations were observed during the course of this research. The identity and privacy
of the respondents was protected by the researcher. The respondents were assured that the
information provided was used solely for academic purposes. No pressure or inducements of any
kind was applied to encourage the respondents to become participants in the research study.
Participants were allowed to withdraw from the process if they so wish. The researcher followed
the laid down procedures for data collection by the University and other statutory organs.
CHAPTER FOUR
4.0 RESULTS
4.1 Introduction
The chapter presents the results of both quantitative and qualitative data analysis structured by
objective and hypothesis. The field research conducted between October and November 2017
and quantitative data collected from CDF beneficiaries, CDF committees, CDF
contractors/project managers and Government Officials who gave both qualitative and
quantitative information on specific areas of the study. The data was analyzed using the STATA
version 14, by use of both descriptive and Structural equation modelling (SEMs). Descriptive
statistics such as frequency, percentage, mean and standard deviation were used. The four
hypotheses of the study were tested using multiple SEMs. Correlations were also conducted
among various pairs of latent variables.
4.2 Instruments Response Rate
The study proportionately sampled respondents from the following categories; direct
beneficiaries, project managers/contractors and CDF committee members. The questionnaire was
distributed to each of the category where 400 were distributed to CDF beneficiaries, 77
distributed to CDF contractors and project managers and 10 for CDF committee members.
Interview schedule tool was equally used to collect data from 7 Government Officials. Lastly
Focus Group Discussion (FGD) was conducted on beneficiaries in their natural environment. The
instrument return rate was based on the 400 questionnaires to CDF beneficiaries and 77
distributed to CDF contractors and project managers. Out of the 400 of the questionnaires
distributed to CDF beneficiaries the researcher was able to collect 321 questionnaires
representing 80.25% and out of 77 distributed to CDF contractors and project managers, the
researcher was able to collect 71 back representing 92.2%. Out of the 10 questionnaires
distributed to CDF committee members all the questionnaires were returned giving a return rate
of 100%. Generally, the return rate was high and able to answer the set objectives of the study.
Mugenda and Mugenda (2008) assert that a response rate of more than 50% is adequate for
analysis. Babbie (2004) also asserts that a 60% response rate is good and a 70% response rate is
very good.
4.3 Demographic Characteristics of Respondents
The data set for respondents’ demographic characteristics for both the CDF beneficiaries and
project managers and contractors included; age bracket, gender, level of education, County
Assembly where the respondent came from, period of residency in the constituency and
contracted to carry out CDF activities and the type of projects they were involved in. Previous
studies have noted some relationship between these demographic factors on effective
implementation of projects (Muchiri, 2010).
4.3.1 Beneficiaries Demographic Characteristics
CDF demographic data was analyzed and presented in Table 4.1. Based on the presented data,
the study established that 183 (57%) of the respondents had age bracket of 30-39 years, 47
(14.6%) were less than 30 years, 53 (16.5%) were between 40-49 years and 38 (11.8%) were 50-
59 years. These findings indicated that slight majority of the direct beneficiaries of CDF projects
in Kasipul Constituency were young generations who have their children in primary and
secondary schools where CDF has been used to build classrooms, set tree nurseries-built school
toilets and buy school buses used the learners. Apart from schools, the beneficiaries also use
bridges, health centers built by the funds and also Chief Camps where they seek their civic
services among others. This finding further indicates that the fund serves a young generation who
by virtue of age are likely to benefit over many years.
Table 4. 1: CDF Beneficiaries Demographic Data
Variable Data Set Frequency PercentAge Bracket Less than 30 47 14.6
30-39 years 183 57.0
40-49 years 53 16.5
50-59 years 38 11.8
Total 321 100Gender Male 227 70.7
Female 94 29.3
Total 321 100Level of Education Primary School 13 4.0
Secondary 40 12.5
College/University 261 81.3
Masters 7 2.2
Total 321 100County Ward West Kasipul 58 18.1
South Kasipul 45 14.0
Central Kasipul 34 10.6
East Kamagak 163 50.8
West Kamagak 21 6.5
Total 321 100Period being resident
5 Years 39 12.1
5-15 years 167 52.0
16-25 years 38 11.8
Above 25 years 77 24.0
Total 321 100Source: Field Data (2017)
Concerning the beneficiaries’ gender and level of education, first, the study found out that
majority of the respondents 227(70.7%) were male compared to 94 (29.3%) who were female.
The study explored the location of the 254 CDF projects in the constituency and collected data
from the gender found at the project site where the majority was men. This finding indicated that
although the projects served the wider population as a whole, there is gender questions that this
finding raised although were not among the objective the study explored; do the CDF projects in
the constituency involve women? Do the projects address gender parity needs especially of
women? Are women totally left behind in the whole agenda of CDF projects in the constituency?
Second the study established that majority of the respondents 261 (81.3%) had some
college/university education, 13(4.0%) had primary school education, 40(12.5%) had college
(University) education and 7(2.2%) masters level of education. This finding showed that the
CDF beneficiaries in the constituency had upper limit of basic education indicating that they had
a fair understanding on CDF management and how they can benefit from them.
Small majority of the respondents 163 (50.8%) of the respondents came from East Kamagak
Ward, 58(18.1%) came from West Kamagak and 34 (10.6%) who came from central Kasipul 58
(18.1%) who came from West Kasipul and 45 (14.0%) came from South Kasipul. Concerning
period of residency in the Constituency, the study established that 171 (45%) had resided in the
constancy for more than 25 years, 97 (25%) had been residents for 5-15 years, 72 (19%) had
been residents for 5 years and 43 (11%) had been residents for 16-25 years. This finding on
period of residency indicated that the respondents had resided in the constituency long enough to
understand effectiveness of CDF project implementation in the constituency.
4.3.2 Project Managers/Contractors Demographic Data
The study sought to find out demographic characteristics of project manager/contractors. The
results are as shown in Table 4.2
Table 4. 2: Project Managers/Contractors Demographic Data
Variable Data Set Frequency Percent
Age Bracket Less than 30 5 7.030-39 years 11 15.5
40-49 years 23 32.4
50-59 years 25 35.2
60-69 years 7 9.9
Total 71 100Gender Male 48 67.6
Female 23 32.4
Total 71 100Level of Education Primary School 4 5.6
Secondary 12 16.9
College/University 47 66.2
Masters 8 11.3
Total 71 100County Ward West Kasipul 18 25.4
South Kasipul 12 16.9
Central Kasipul 18 25.4
East Kamagak 21 29.6
West Kamagak 2 2.8
Total 71 100Period being resident 5 Years 58 81
5-15 years 13 18Total 71 100
Type of project Education 56 79Health 6 8Transport (Bridges) 1 1Environment 6 8Security 2 3
Total 71 100Source: Field Data (2017)
CDF project managers and contractor’s demographic data was analyzed and presented in Table
4.2. Based on the presented data, the study established that less than majority of respondents 25
(35.2%) of the respondents had age bracket of 50-59 years, 23 (32.4%) had age bracket 40-49
years, between 30-39 years were 11(15.5%), 5 (7%) were less than 30 years and only 7 (10%)
were 60-69 years. This finding indicated that majority of the direct project managers/contractors
of CDF projects in Kasipul Constituency were old generation. This finding indicates that
although the fund serves a young generation who by virtue of age are likely to benefit over many
years, the project managers who the head of institutions were where the projects were
implemented and contractors were older generation questioning the application of Public
Procurement Act which recommended that 30% of public procurement is a reserve of the youths
whose age cut off is 35 years.
Project managers/contractors gender and level of education indicated that, first, majority of the
respondents 48(67.6%) were male compared to 23 (32.4%) who were female. This finding
indicated that although the CDF Act recommends gender representation, this finding raised the
following gender questions; does the CDF committee and Secretariat at the Constituency level
keen implementing the projects where women are in advantaged positions to be the project
managers of contractor? Do the projects address gender parity needs especially women? Are
women totally left behind in the whole agenda of CDF projects in the constituency?
Second the study established that majority of the respondents 47 (66%) had college/university
education, 12 (17%) had secondary school education, 4 (5.6%) had primary education and
8(11.3%) had masters level of education. This finding showed that the CDF project managers by
virtue of their positions in the public institutions where the projects are implemented were
somehow had college/university education and also to contractors. The level of education gave
them due advantage in understanding basic principle in project management which they could
easily transfer in CDF management to make such projects successful.
Small majority of the project managers and contractors 21 (29.6%) of the respondents came from
East Kamagak Ward, 18 (25.4%) came from West Kasipul and 2(2.8%) who came from West
Kamagak 18 (25.4%) who came from Central Kasipul and 12 (16.9%) came from South Kasipul.
Concerning period of residency in the Constituency, the study established that majority 57 (80%)
had resided in the constancy for 5 years, 13 (18%) had been residents for 5-15 years, 1 (1%) had
been residents for 16-25 years. This finding on period of residency indicated that the project
managers and contractors had resided in the constituency for shorter period by virtue of being
professionals who can be transferred from one location to the other or seek contract opportunities
from elsewhere.
CDF in Kasipul constituency has range of projects implemented to alleviate poverty. The study
established that majority of respondents 56 (79%) observed that CDF projects in the constituency
were being implemented in education sector, 6 (8%) were being implemented in health sector 2
(3%) were implemented in security sector and 1 (1%) in transport sector.
4.3.3 CDF Committee Members Demographic Data
The study also sought to find out demographic characteristics of CDF committee members. The
results are as shown in Table 4.3
Table 4. 3: CDF Committee Members Demographic DataVariable Data Set Frequency PercentAge Bracket Less than 30 1 10.0
30-39 years 4 40.0
50-59 years 5 50.0
Total 10 100Gender Male 7 70
Female 3 30Total 10 100
Level of EducationSecondary 3 30.0
College/University 6 60.0
Masters 1 10.0
Total 10 100County Ward West Kasipul 1 10
South Kasipul 1 10Central Kasipul 2 20East Kamagak 4 40West Kamagak 2 20Total 10 100
Period being resident5 Years 1 105-15 years 3 3016-25 years 6 60Total 10 100
Group representedYouth 2 20Men 1 10Women 1 10People with disability 1 10National Government 1 10Nominated member 2 20Co-opted 1 10NGO 1 10
Total 10 100Source: Field Data (2017)
CDF committee demographic data was analyzed and presented in Table 4.3. The study
established that slightly majority of respondents 5 (50%) of the respondents had age bracket of
50-59 years, 1 (10%) had age bracket less than 30 years and 4(40%) were 30-39 years. This
finding indicated that majority of CDF committee members in Kasipul Constituency was a
mixture younger generation and the old guards which aid in getting various insights about project
management. This finding is in the support of the data from the beneficiaries which indicated
that the fund serves a young generation who by virtue of age are likely to benefit over many
years and also likely to promote the youth participation in the procurement of services and
material which is likely to fulfill the requirements of Public Procurement Act which
recommended that 30% of public procurement is a reserve of the youths whose age cut off is 35
years.
In terms of gender and level of education the study established, first, majority of the respondents
7 (70%) were male compared to 3 (30%) who were female. This finding indicated that CDF
committee was still dominated by men compared to women. The study established that majority
of the respondents 6 (60%) had some college/university education, 3 (30%) had secondary
education, 1 (10%) had masters level of education. This finding showed that the CDF committee
members had secondary school education which may be a challenge in understanding basic
principle in project management being the directors of the CDF project approval and direction in
the constituency.
Small majority of the committee members 4 (40%) of the respondents came from East Kamagak
Ward, 2 (20%) came from West Kamagak and Central Kasipul Ward respectively and 1 (10%)
who came from West and South l Kasipul respectively. Concerning period of residency in the
Constituency, the study established that majority of the committee members 60 (60%) had
resided in the constancy for 16-25 years, 3 (30%) had been residents for 5-15 years, 1 (10%) had
been residents for 5 years. This finding on period of residency indicated that the CDF committee
members had resided in the constituency for longer period by which made them understand the
constituency in terms of the needed projects that can accelerate development in the constituency.
CDF committee members in Kasipul constituency had small majority of responding 2 (20%)
representing the youths and nominated members respectively whereas the rest 1 (10%)
represented, women, men, National Government and co-opted members. It can be deduced that
there is fair representation of groups in the management of CDF projects in Kasipul
Constituency. This is according to CDF Acts as well as other regulatory frameworks which insist
on affirmative action especially on youth, women and people with disabilities in the participation
of devolved funds.
From the findings, it’s evident that demographic characteristics of sampling units (CDF
committee, beneficiaries and project contractors/managers) showed varied outcome. Male were
dominant in all sampling units unlike age where majority were between 30 and 39 years while
project manager were between 40 and 59 years a pattern that was also observed amongst CDF
committee members. It was also noted that beneficiaries, CDF committee members and project
contractors/Managers were well educated with over 70% of them having post-secondary
education implying that they have necessary knowledge and awareness of CDF projects
management.
4.4 Descriptive Analysis
Descriptive analysis included an assessment of the technical capacity, stakeholder participation,
political influence, project financing, regulatory framework and CDF management. Descriptive
measures included mean, standard deviation, frequency and percentage. Mean is a measure of
central tendency used to describe the most typical value in a set of values. Standard deviation
shows how far the distribution is from the mean. The presentation in this section was based on
the objectives of the study for the three categories of the respondents; beneficiaries, project
manager/contractors and CDFC.
4.4.1 Project Financing
Project financing is essential to all successful project management. Good financial governance is
imperative in any public project as it enhances accountability and transparency therefore improve
public trust. Therefore, the first objective of the study was to assess the influence of projects
financing on effective management of Constituency Development Funded projects. Project
financing was measured using adequacy allocation to projects, timely disbursement of the funds,
auditing process, transparency and accountability.
Five statements were formulated to measure the technical capacity variable using a five point
Likert-type scale ranging from 1=strongly disagree to 5= strongly agree and respondents were
asked to indicate the extent to which they agreed to the statements. They included; accountability
and transparency in the use of CDF fund for the management of projects, satisfaction level with
the auditing process of CDF projects, timely disbursement of CDF finances to the identified
projects, sufficiency of the funds as per the various projects in the constituency, adequate
allocation of the funds to the various projects. The section analyzes the views of beneficiaries,
project managers/contractors and CDF constituency committee on the project financing of the of
CDF projects in Kasipul Constituency. Table 4.4 presents findings as obtained from beneficiaries
of CDF projects in Kasipul Constituency
Table 4. 4: Project Financing-Beneficiaries
Project Financing
SD
(%)
D
(%)
U
(%)
A
(%)
SA
(%)
Mean STD
Accountability and transparency 11.2 11.2 45.2 19.0 13.4 3.12 1.13Auditing process 11.2 44.9 12.1 15.6 16.2 2.81 1.29Timely disbursement 9.3 14.6 10.0 50.5 15.6 3.48 1.19Funds allocation 11.5 18.1 41.7 15.9 12.8 3.00 1.15Adequate allocation 10.0 16.2 11.5 50.2 12.1 3.38 1.19Overall Mean 3.16 1.19
Source: Field Data (2017)
From Table 4.4, 45.2% of the sampled beneficiaries were undecided on whether there is
accountability and transparency in the use of CDF fund for the management of projects as shown
by 45.2% with a mean of 3.12 and standard deviation of 1.13. Only 19.0% and 13.4% of the
sampled beneficiaries agreed and strongly respectively that accountability and transparency in
the use of CDF fund for the management of projects. This indicates that few sampled
beneficiaries were able to reveal that there is accountability and transparency in the management
of CDF funded projects. More than half of the respondents (56.1%) did not confirm that they are
satisfied with the auditing process of NG – CDF projects with 31.8% of the respondents
indicating varying level of satisfaction of CDF projects auditing process with a mean of 2.81 and
standard deviation of 1.29.
More than half of the sampled beneficiaries (50.5%) agreed that CDF funds are timely disbursed
to the identified projects which has enhanced project management and additional 15.6% strongly
agreed on the same with a mean of 3.48 and standard deviation of 1.19. However, 41.7% of the
sampled beneficiaries were undecided on whether there are sufficient funds allocated for various
aspect of CDF projects with a mean of 3.00 and standard deviation of 1.15. It was also noted that
28.7% confirmed that there is sufficient funds allocation to various aspect of CDF funded
projects management such as monitoring and evaluation and stakeholder participation.
More than half of the sampled beneficiaries (50.2%) agreed that CDF funds are adequately
allocated to the identified projects and additional 12.1% of the sampled beneficiaries strongly
agreed that CDF funds are adequately allocated to the identified projects which have enhanced
effectiveness of CDF funded project management with a mean of 3.38 and standard deviation of
1.19. The overall mean response of 3.16 implied that the sampled respondents were undecided on
most of the statement regarding project financing while a standard deviation of 1.19 denoted that
there was some variation the response on the statement on project financing from beneficiaries’
point of view. This finding showed that there was evidence of disagreement in various constructs
that was used to determine project financing effectiveness and in some cases the respondents
were not sure on funds allocation, transparency and accountability.
Table 4. 5: Project financing-Project Managers/ Contractors
Project Financing
SD
(%)
D
(%)
U
(%)
A
(%)
SA
(%)
Mean STD
Accountability and transparency 5.6 4.2 2.8 46.5 40.8 4.13 1.05Auditing process 5.6 8.5 4.2 43.7 38.0 4.00 1.13Timely disbursement 8.5 31.0 7.0 26.8 26.8 3.32 1.38Funds allocation 2.8 42.3 7.0 28.2 19.7 3.20 1.26Adequate allocation 43.7 11.3 19.7 25.4 3.27 1.26Overall Mean 3.58 1.22
Source: Field Data (2017)
From Table 4.5, majority of the sampled project managers/contractors (87.3%) confirmed that
there is accountability and transparency in the use of CDF fund for various projects as shown by
a mean of 4.13 and standard deviation of 1.05. Similarly, there was agreement amongst the
sampled project managers/contractors that they are satisfied with the auditing process of NG –
CDF projects as indicated by a mean of 4.00 and standard deviation 1.13 which was further
supported by 43.7% of the respondents who agreed and 38.0% who strongly agreed.
The results further revealed that slight majority (53.6%) of the CDF project managers/contractors
confirmed that CDF funds are timely disbursed to the identified projects which have enhanced
project management with a mean of 3.32 and standard deviation of 1.38. However, 43.3% of the
sampled project manager/contractors disagreed that there are sufficient funds allocated for
various aspect of CDF projects which has resulted to effective management of CDF as compared
to 28.2% agreed and 19.7% strongly agree with a mean of 3.20 and standard deviation of 1.26. It
be deduced that fund allocation is still a challenge in the management of CDF funded projects as
only 19.7% of the sampled project managers/contractors strongly felt there was adequate
allocation that enabled effective management of CDF projects.
Lastly, 43.7% of the respondents disagreed that CDF funds are adequately allocated to the
identified projects which has enhanced project management with a mean of 3.27 and standard
deviation of 1.26 while 19.7% agreed and 25.4% of the respondents strongly agreed. Just as
sharp variation in the fund allocation for various aspects of project management, the same is
evident in the fund allocation for identified projects. This implies that project
managers/contractors are not satisfied with allocation of CDF projects both in term of actual
allocation for projects as well as other monies that are used in the management of identified
projects.
The overall mean response of 3.58 implied that the sampled respondents were in agreement on
most of the statement regarding project financing while a standard deviation of 1.19 denoted that
there was some variation the response on the statement on project financing from project
manager/contractors point of view. It was found that majority of the sampled respondents agreed
on the accountability and auditing process while disagreed on allocation and timely disbursement
which affected availability of fund to manage CDF projects. However, fund allocation seems to
be a problem which needs to address for effective management of CDF funded projects in
Kasipul Constituency.
Table 4. 6: Project Financing-CDF Committee
Project Financing
SD
(%)
D
(%)
U
(%)
A
(%)
SA
(%)
Mean ST
DAccountability and transparency 0.0 20.0 10.0 40.0 30.0 3.80 1.14Auditing process 0.0 10.0 10.0 40.0 40.0 4.10 0.99Timely disbursement 0.0 10.0 30.0 50.0 10.0 3.60 0.84Funds allocation 0.0 10.0 20.0 40.0 30.0 3.90 0.99Adequate allocation 0.0 0.0 0.0 70.0 30.0 4.30 0.48Overall Mean 3.94 0.89
Source: Field Data (2017)
From Table 4.6, CDF committee agreed that there is accountability and transparency in the use of
CDF fund for the management of projects as indicated by a mean of 3.80 and standard deviation
of 1.14 although two of the respondents did not confirm on accountability and transparency. The
results further revealed that there was satisfaction with the auditing process of NG – CDF
projects as shown by a mean of 4.10 and standard deviation of 0.99 although one of the
respondents disagreed on auditing process. Concerning timely disbursement of funds, the results
revealed that the CDF committee members agreed that CDF funds are timely disbursed to the
identified projects which have enhanced project management as indicated by a mean of 3.60 and
standard deviation of 0.84 with three of the respondents remaining undecided.
The results also revealed that sufficient funds allocated for various aspect of CDF projects which
has resulted to effective management of CDF as indicated by mean of 3.90 and standard
deviation of 0.99. Likewise, CDF committee agreed that CDF funds are adequately allocated to
the identified projects which have enhanced project management as indicated by a mean of 4.30
and standard deviation of 0.48. Close examination of the two means indicate that the CDF
committee members ranked allocation of funds to identified projects higher than funds allocated
to other aspects of CDF projects. It was revealed that the CDF Acts favour actual CDF project
allocations that other aspects such as monitoring and evaluation which are inadequately
allocated. It was therefore noted that the National Government should increase overall allocation
of CDF so as to ensure that there is effective management of CDF funded projects.
The overall mean response of 3.94 implied that CDF committee agreed on most of the statement
regarding project financing while a standard deviation of 0.89 denoted that there was small
variation the response on the statement on project financing from CDF-committee point of view.
Table 4. 7: Comparison between Respondents Views on Project Financing
Respondent N Min Max Mean Std. Dev
Beneficiaries 321 1 5 3.16 1.19
Project managers and contractors 71 1 5 3.58 1.22
CDF Committee Members 10 2 5 3.94 0.89
Grand Mean 3.56 1.1
Source: Field Data (2017)
Table 4.7 was used to analyze difference in view by beneficiaries, project managers/contractors
and CDF Constituency Committee on project financing in the management of CDF projects in
Kasipul Constituency. This comparison is important for the study because this category of
respondents view project financing differently as far as CDF projects management is concern.
The findings showed that CDF committee members had the best rating of project financing
among stakeholders compared to beneficiaries and project managers/contractors. However,
project managers/contractors rated project financing higher as compared to beneficiaries of CDF
funded projects.
The difference in rating can be attributed that CDF committee members are considered at the top
in the management of CDF projects and they implement project financing according to existing
regulatory frameworks such as CDF Acts and Procurement Acts among others. In some cases,
they delegate management of CDF projects to third parties and project managers/contractors to
avoid conflict of interest who can interfere with effectiveness of CDF projects. However, the
beneficiaries consider the overall management of CDF projects rest on CDF committee and are
therefore required to source project managers/contractors and other third parties with better
project financing capabilities to ensure effective management of CDF projects.
During collection of qualitative using interviews and FGDs, it was revealed that project
financing is one of the important determinants of successful CDF project management. The
Government Officials in the education department indicated that funds are need in various
aspects of projects not only for project itself but for monitoring and evaluation which ensure that
project is implemented according to set rules and regulations. However, the official hinted that
there is inadequate allocation of financial results to project contractors which leaves with no
options of facilitating M & E. The CDF Acts and other regulatory framework put a lot of
emphasize on the actual management of funds allocated to CDF funded projects but they are
silent on allocations that ensure the projects are effectively managed.
The FGDs results also revealed that the issue of timely disbursement of funds has delayed
completion of the projects in Kasipul Constituency. According to beneficiaries, some projects
take unnecessary long time. One of the beneficiaries of the CDF project who was also a casual
worker with CDF project contractor said that:
“There was a project which took three years to complete just because there was noconstant flow of money from the CDF office. In normal day, the project should takeat most one years but our foreman told us we are waiting for government to disbursethe money before we can resume. This delay affected some of us who work in thesesites” (FGD001, 2017)
This postulates that projects undertaken by Kasipul CDF drags for a long time that even
stakeholders who participate through offering labour find it difficult to cope without such
projects. On the other hand, delay in completion of projects have profound effect on the
beneficiaries who are forced to wait for long time before benefitting from a project which was
commissioned more than three years ago. This scenario affects mostly schools and health
projects as citizens are forced to look for alternative which in some cases is usually expensive
negating the objective of CDF in poverty alleviation. One of the beneficiaries in a secondary
school who happens to be head teacher revealed that the way the Kasipul CDF projects is
allocating money is wanting. She stated that:
“Instead of undertaking a lot of CDF projects at once with little allocation that isspread for over three years, the CDF office should concentrate on one project thenmove the next. The essence of CDF projects is to help mwananchi but delay indelivery make them feel cheated” (FGD003, 2017)
This implies that poor prioritization of funds is affecting effective management of CDF projects
in terms of delay in delivery and in some cases, contractors have been found to deliver poorly
finished projects as a result of cost overrun which is associated with inflation and other economic
shocks which increase cost of projects. The view was shared by the government official in charge
of roads and public works at district level. He indicated that doing public works in bits erode
public trust in the CDF projects due to insufficient allocation and delay in disbursement of funds
for project completion in one financial year. The public may have the opinion that the funds have
been misappropriated by the contractors and that is why they are unable to complete projects on
time. On the other hand, the beneficiaries may have the opinion that CDF Office has colluded
with the contractors to defraud the public through delay in completion.
However, some of the beneficiaries have faulted the project managers and contractors in the
misappropriation of the funds which have been allocated for CDF projects. This was common
among building and construction contractors who have undertaken shoddy job in pretext of small
allocation from the CDF office. It is therefore important for the CDF at National level to re-
examine laws and regulation on allocation of CDF funds to various project for effective
management.
4.4.2 Stakeholder Participation
Citizen participation in any project usually enhances good governance of the project activities
leading to project achievement assessable through parameters as; completion on schedule,
completion on budget, scalability of the project outcome through sustainability process and
citizens themselves being satisfied with the project outcome hence acceptability of project. The
essence of CDF projects is to spur local development through various stakeholder participations.
The second objective of the study was to establish the contribution of stakeholder participation
on effective management of Constituency development Funded projects. The aim of the
objective was to test the second research hypothesis which posits: There is no significant
relationship between stakeholder participation and effective management of CDF funded
projects. The objective was achieved through identifying the level of participation, how
participants are identified, form of participation and determination of stakeholder participation
which was measured using level of participation, structures and frequency of participation.
Five statements were formulated to measure the stakeholder participation construct using a five-
point Likert-type scale ranging from 1=strongly disagree to 5= strongly agree and respondents
were asked to indicate the extent to which they agreed to the statements. They included;
management of CDF projects is a collective responsibility that involves all stakeholders
including the citizens themselves. Stakeholders participation enhances better utilization of public
resources especially the citizen playing an over sight role. The participation structures enable
effective management of CDF projects. Frequent stakeholder investigation enhances the
assessment whether the planned benefits out of the project have been achieved. Stakeholder’s
frequent meeting enhances project progress assessment.
Further the respondents were also required to identify level of participation, identification of
participants and form of participation and their effectiveness. The presentation was for
beneficiaries, project manager/contractors and CDF committee members. Sampled beneficiaries
were required to identify various stage of participation in the management of CDF projects in
Kasipul Constituency. A mean close to 1 represents high while a mean close to zero shows that
there is low participation. The results are as shown in Table 4.8
Table 4. 8: Stakeholder Participation- Stages of Participation for Beneficiaries
Level Min Max
Percentage Mean Std. DeviationProject identification 0 1 75.4 .75 .43Project planning 0 1 31.8 .32 .47Project allocation 0 1 31.2 .31 .46Project implementation 0 1 29.6 .30 .46Project monitoring 0 1 29.0 .29 .45Project evaluation 0 1 24.6 .24 .43Project commissioning 0 1 51.7 .52 .50
From the Table 4.8, majority of the sampled beneficiaries indicated there was high level of
participation during project identification as shown by a mean of 0.7539 and it was supported by
75.4% of the respondents. After identification of projects, the level of participation of citizens
reduces during planning, allocation, implementation, monitoring and evaluation and increases
during project commissioning as indicated by a mean of 0.517 which was supported by 51.7% of
the respondents. This indicates that citizens are only involved during project identification and
commissioning of the projects in Kasipul constituency.
The study also sought to find out how citizen is identified for them to participate in the
management of the CDF projects. The results are as shown in Table 4.9
Table 4. 9: Stakeholder Participation-Forms of Participation and identification of
beneficiaries
Form of Participation Percentage Mean Std. DeviationRepresentation 75.7 0.78 0.43Laborers 21.2 0.21 0.41Others 2.2 0.022 0.15
Form of IdentificationNomination 33.0 0.33 0.47Election 10.9 0.11 0.11Appointment 57.0 0.57 0.50Source: Field Data (2017)
From Table 4.9, citizens are appointed to participate in the management of CDF projects as
shown by a mean of 0.57 which was supported by 57.0% of the respondents. In some cases, the
participants are also nominated (0.33) and election of the participants is rarely done as shown by
10.9% of the respondents. Similarly, the most common form of participation was through
representation by various groups as shown by a mean of 0.78 and supported by 75.7% of the
respondents. This representation was through various groups such as youth, people with
disability and women. Other form of participation was through laborers where local people were
employed to work in the CDF projects although it was only supported by 21.2% of sampled
beneficiaries.
Table 4. 10: General Stakeholder Participation for Beneficiaries
Stakeholder Participation
SD
(%)
D
(%)
U
(%)
A
(%)
SA
(%)
Mean STD
Collective Responsibility 5.9 9.3 6.9 59.8 18.1 3.75 1.05Utilization of resources 4.4 8.4 6.9 55.1 25.2 3.88 1.02Structures effective management 6.5 9.0 10.0 23.7 50.8 4.03 1.25Realized Objectives 2.8 10.0 6.2 59.5 21.5 3.87 0.96Progress of projects 5.3 10.3 8.7 29.0 46.7 4.02 1.20Overall Mean 3.91 1.10
Source: Field Data (2017)
From Table 4.10, majority of the respondents agreed that management of CDF projects is a
collective responsibility that involves all stakeholders as shown by 59.8% of the respondents and
18.1% who strongly agree with a mean of 3.75 and standard deviation of 1.05. Further,
stakeholder participation was found to enhance better utilization of public resources as the
people play an oversight role which was identified by 55.1% and 25.2% of the respondents who
agreed and strongly agree respectively with a mean of 3.88 and standard deviation of 1.02.
Concerning structures for citizen participation, it was confirmed that structures established for
stakeholder participation has enabled effective management of CDF projects as shown by 23.7%
who agreed and 50.8% who strongly agreed with a mean of 4.03 and standard deviation of 1.25.
The results also established that there was frequent stakeholder investigation and reviewing the
effects of the completed or ongoing projects to see whether the benefits which were planned to
flow from the project have indeed been realized as shown by a mean of 3.87 and standard
deviation of 0.96.
Lastly, it was confirmed that stakeholders hold frequent consultative meetings to deliberate on
the progress of the project management as shown by 29.0% of the respondents who agreed and
further 46.7% who strongly agreed. The overall mean response of 3.91 implied that the sampled
beneficiaries agreed on most of the statement regarding stakeholder participation while a
standard deviation of 1.10 denoted that there was some variation the response on the statement
on stakeholder participation from beneficiaries’ point of view.
The finding indicated that stakeholders participation had important contribution on effective
management of CDF projects in Kasipul Constituency by the contribution towards; stakeholder
participation contributed towards collective responsibility that involved all citizens in the
effective management of CDF projects in the constituency, enhancement of better utilization of
public resources by citizen participating playing oversight role of CDF projects in the
constituency, establishment of structures that enhanced effective management of CDF projects in
the constituency, frequent investigations and review of the effect of completed or ongoing
projects to verify whether the planned benefits were realized and holding of frequent consultative
meetings to deliberate on the progress of the projects.
Sampled project manager/contractors were required to identify various stage of participation in
the management of CDF projects in Kasipul Constituency. The results are as shown in Table
below.
Table 4. 11: Stakeholder Participation-Stages of Project Managers/contractors
participation
Level Min Max
Percentage Mean Std. DeviationProject identification 0 1 57.75 0.58 0.50project planning 0 1 45.07 0.45 0.50project allocation 0 1 30.99 0.31 0.47project implementation 0 1 64.79 0.65 0.48project monitoring 0 1 64.79 0.65 0.48project evaluation 0 1 43.66 0.44 0.50project commissioning 0 1 67.61 0.68 0.47
Source: Field Data (2017)
From the Table 4.11, majority of the sampled beneficiaries indicated there was moderate level of
participation during project identification (mean=0.58), project implementation (Mean=0.65),
project monitoring (Mean=0.65) and during commissioning (0.68). However, low involvement
was witnessed during project evaluation (Mean=0.44), project allocation (Mean=0.31) and
project planning (Mean= 0.45) This finding indicated that there was difference between
beneficiaries and project managers/contractor’s views on stakeholders’ participation with the
earlier having a view on participation on project identification while the latter had a view on
participation project implementation and monitoring.
The study also sought to find out how stakeholders are identified for them to participate in the
management of the CDF projects. From project managers/contractor’s views, stakeholders are
nominated to participate in the management of CDF projects in Kasipul Constituency as
indicated by a mean of 0.54 implying more than 50% are nominated. In some cases, there was
election of the stakeholders as indicated by 31.0% of the respondents with only 7.0% indicating
incidence of nomination. The results are as shown in Table 4.12.
Table 4. 12: Stakeholder Participation-Forms of Participation and identification for Project
Managers/Contractors
Form of Participation Percentage Mean Std. Deviation
Representation 70.42 0.70 0.46
Laborers 21.13 0.21 0.41
Others 2.82 0.03 0.17
Form of IdentificationNomination 53.5 0.54 0.50Election 31.0 0.31 0.47Appointment 7.0 0.07 0.26
Source: Field Data (2017)
From Table 4.12, the most common form of participation was through representation by various
groups as shown by a mean of 0.70 and supported by 70.42% of the respondents. This
representation was through various groups such as youth, people with disability and women.
Other form of participation was through laborers where local people were employed to work in
the CDF projects although it was only supported by 21.1% of sampled beneficiaries.
Table 4. 13: General Stakeholder participation for Project Managers/Contractors
Stakeholder Participation
SD
(%)
D
(%)
U
(%)
A
(%)
SA
(%)
Mean STD
Collective Responsibility 0.0 5.6 2.8 59.2 32.4 4.18 0.74Utilization of resources 0.0 0.0 4.2 29.6 66.2 4.58 0.71Structures effective management 2.8 14.1 4.2 43.7 35.2 3.94 1.11Realized Objectives 2.8 8.5 1.4 45.1 42.3 4.15 1.01Progress of projects 0.0 16.9 2.8 45.1 35.2 3.99 1.04Overall Mean 4.17 0.920
Source: Field Data (2017)
From Table 4.13, majority of the sampled project managers/contractors agreed that management
of CDF projects is a collective responsibility that involves all stakeholders as shown by 59.2% of
the respondents and 32.4% who strongly agree with a mean of 4.18 and standard deviation of
0.74. Further, stakeholder participation was found to enhance better utilization of public
resources as the people play an oversight role which was identified by 66.2% and 29.6% of the
respondents who strongly agreed and agree respectively with a mean of 4.58 and standard
deviation of 0.74.
Considering whether structures established for stakeholder participation has enabled project
identification to take shorter time, approximately 43.7% agreed and 35.2% strongly agreed with
a mean of 3.94 and standard deviation of 1.11. The results also established that there was
frequent stakeholder investigation and reviewing the effects of the completed or ongoing projects
to see whether the benefits which were planned to flow from the project have indeed been
realized as shown by a mean of 4.15 and standard deviation of 1.01. Lastly, it was confirmed that
stakeholders hold frequent consultative meetings to deliberate on the progress of the project
management as shown by 45.1% of the respondents who agreed and further 35.2% who strongly
agreed. The overall mean response of 4.17 implied that the sampled project managers/contractors
agreed on most of the statement regarding stakeholder participation while a standard deviation of
0.920 denoted that there was some variation the response on the statement on stakeholder
participation from project managers/contractors point of view. It is important to note that project
managers/contractors rated the contribution of stakeholder participation towards effective
management of CDF projects in the constituency higher than the beneficiaries.
Table 4. 14: Stakeholder Participation in Accountability and Transparency of Finances by
CDF Committee Members
Project Financing
SD
(%)
D
(%)
U
(%)
A
(%)
SA
(%)
Mean STD
Collective Responsibility 5.6 4.2 2.8 46.5 40.8 4.13 1.05
Utilization of resources 5.6 8.5 4.2 43.7 38.0 4.00 1.13Structures effective management 8.5 31.0 7.0 26.8 26.8 3.32 1.38Realized Objectives 2.8 42.3 7.0 28.2 19.7 3.20 1.26Progress of projects 0.0 43.7 11.3 19.7 25.4 3.27 1.26Overall Mean 3.58 1.22N=402
Source: Field Data (2017)
From Table 4.14, majority of the sampled project managers/contractors confirmed that there is
accountability and transparency in the use of CDF fund for the management of projects as shown
by a mean of 4.13 and standard deviation of 1.05. Similarly, there was agreement amongst the
sampled project managers/contractors that they are satisfied with the auditing process of NG –
CDF projects as indicated by a mean of 4.00 and standard deviation 1.13 which was further
supported by 43.7% of the respondents who agreed and 38.0% who strongly agreed.
The results further revealed that 26.8% of the CDF project managers/contractors agreed that
CDF funds are timely disbursed to the identified projects which have enhanced project
management and 26.8%% strongly agreed with a mean of 3.32 and standard deviation of 1.38.
However, 43.3% of the sampled project manager/contractors disagreed that there are sufficient
funds allocated for various aspect of CDF projects which has resulted to effective management
of CDF while 28.2% agreed and 19.7% strongly agree with a mean of 3.20 and standard
deviation of 1.26. Lastly, 43.7% of the respondents disagreed that CDF funds are adequately
allocated to the identified projects which has enhanced project management with a mean of 3.27
and standard deviation of 1.26 while 19.7% agreed and 25.4% of the respondents strongly
agreed.
The overall mean response of 3.58 implied that the sampled respondents were undecided on most
of the statement regarding project financing while a standard deviation of 1.19 denoted that there
was some variation the response on the statement on project financing from project
manager/contractors point of view. It was found that majority of the sampled respondents agreed
on the accountability and auditing process while disagreed on allocation and timely disbursement
which affected availability of fund to manage CDF projects. CDF committee members were
required to identify various stage of participation in the management of CDF projects in Kasipul
Constituency. The results are as shown in Table 4.15
Table 4. 15: Stakeholder Participation - Stages of Participation by CDF Committee
Members
Level Min Max Percentage Mean Std. DeviationProject identification 0 1 90.0 0.9000 0.32project planning 0 1 80.0 0.8 0.42project allocation 0 1 60.0 0.7000 0.32project implementation 0 1 70.0 0.7000 0.32project monitoring 0 1 70.0 0.7000 0.42project evaluation 0 1 60.0 .6000 0.48project commissioning 0 1 90.0 .9000 0.32
Source: Field Data (2017)
From the Table 4.15, majority of the CDF committee members indicated there was high level of
stakeholder participation in Project identification, project planning, project allocation, project
implementation, project monitoring, project evaluation and project commissioning. The level of
participation as indicated by committee is high as compared to other category of the respondents.
The study also sought to find out how stakeholders are identified for them to participate in the
management of the CDF projects. The results are as shown in Table 4.16
Table 4. 16: Stakeholder Participation-Forms of Participation and identification by CDF
Committee Members
Form of Participation Percentage Mean Std. Deviation
Representation 90.0 .9000 0.32
Laborers 40.0 .4000 0.52
Form of IdentificationNomination 60.00 0.60 0.52Election 50.00 0.50 0.53Appointment
40.00 0.40 0.52Source: Field Data (2017)
From CDF committee members’ views, stakeholders are nominated to participate in the
management of CDF projects in Kasipul Constituency as indicated by a mean of 0.60. It was also
noted that some position requires election of participants while other through appointment. It can
be established that various form of identification is adopted for participants’ identification.
From the Table 4.16, the most common form of participation was through representation by
various groups as shown by a mean of 0.90 and supported by 90.0% of the respondents. This
representation was through various groups such as youth, people with disability and women.
Other form of participation was through laborers where local people were employed to work in
the CDF projects.
Table 4. 17: General Stakeholder Participation by CDF Committee Members
Stakeholder Participation
SD
(%)
D
(%)
U
(%)
A
(%)
SA
(%)
Mean STD
Collective Responsibility 0.0 0.0 0.0 70.0 30.0 4.30 0.48Utilization of resources 0.0 0.0 0.0 40.0 60.0 4.60 0.52Structures effective management 0.0 0.0 0.0 50.0 50.0 4.50 0.53Realized Objectives 0.0 0.0 0.0 40.0 60.0 4.60 0.52Progress of projects 0.0 0.0 0.0 30.0 70.0 4.70 0.48Overall Mean 4.54 0.510
Source: Field Data (2017)
From Table 4.17, it was agreed that management of CDF projects is a collective responsibility
that involves all stakeholders as shown by a mean of 4.30 and standard deviation of 0.48.
Further, stakeholder participation was found to enhance better utilization of public resources as
the people play an oversight role as indicated by a mean of 4.60 and standard deviation of 0.52.
It was also confirmed that structures established for stakeholder participation has enabled
effective management of CDF projects as shown by a mean of 4.50 and standard deviation of
0.53. The results also established that there was frequent stakeholder investigation and reviewing
the effects of the completed or ongoing projects to see whether the benefits which were planned
to flow from the project have indeed been realized as shown by a mean of 4.60 and standard
deviation of 0.52. Lastly, it was confirmed that stakeholders hold frequent consultative meetings
to deliberate on the progress of the project management as shown by a mean of 4.70 and standard
deviation of 0.48
The overall mean response of 4.54 implied that the CDF committee members strongly agreed on
most of the statement regarding stakeholder participation while a standard deviation of 0.510
denoted that there was small variation the response on the statement on stakeholder participation
from CDF committee members’ point of view. It is important to note that CDF committee
members rated the contribution of stakeholder participation towards effective management of
CDF projects in the constituency higher than other respondents.
The results of interview and FGDs indicated that a lot need to done to ensure there is adequate
and meaningful stakeholder participation as it influence effective management of CDF funded
projects. All the respondents agreed that participation in Kasipul constituency which is the reason
why it has been performing better in comparison to other constituencies in the country. The
government officials in the department of public works affirmed that they have been consulted
on several occasions by the project contractors on the suitability of the projects in the
constituency. The Constitution of Kenya advocates for community participation in project
formulation and implementation for ownership and sustainability.
In this regards the CDF expects it implementing agencies to put community at the forefront in
the project cycle. The community is therefore expected to; Participate in open public meetings
convened by the Chairperson of the CDFC to deliberate on development matters in the ward and
the constituency, to facilitate in prioritization of projects to be submitted to the CDFC, to
participate in project implementation through provision of locally available resources (land,
materials, labour or skills) either voluntarily or for pay, Participate in nomination and formation
of PMCs and CDFC, to provide feedback to the Board and law enforcement Agencies on
matters concerning the Fund and witness the commissioning of projects and issuance of cheques
and other disbursements by the constituency committee
However, the government official faulted the manner in which his participation is viewed purely
as professional and not as residents. Therefore, his contribution is limited to technical support.
The Government official further revealed that training and seminars are rarely done to
stakeholders who participate in the management of CDF funded projects. According to him, the
benefit of participation can be realized if those who are involved in participation understand the
essence of participation in effective management of projects. The FGDs participants indicated
they have been involved heavily in the commissioning of projects One of the beneficiaries of the
CDF project who was also a teacher said that:
“We are normally called during opening of new classroom by the head teacher andlocal politicians. At the particular time is more of ceremonial than adding value tothe project. It would be good if we are involved from identification up to opening ofprojects” (FGD 002, 2017)
Another household head that has benefitted from a bridge that was constructed near his home
was not happy with the way the project was undertaken. It is clear that these projects were
shrouded in secrecy implying that there could be corrupt practices involved for in their
identification, planning and implementation. He said that:
“Even though am enjoying the bridge, the manner in which it was constructed doesnot go well with me. This (contractor) destroyed my crops in the name ofconstructing the bridge and I was not consulted or compensated for the damage. Iwas told the bridge is going to help the public. It would be proper if I was informedin advance about the construction so that I can remove my crops” (FGD001, 2017).
From the above to discussants, it is evident that residents are not properly represented or
participate in the CDF funded projects. It’s important to include the stakeholder in projects from
identification to completion and during opening. The success of project management depends on
the primary beneficiaries and not the monetary gains to the project contractors and those who are
involved as laborers. The respondents also fault the form of participation. Majority of the
discussants indicated that participation is associated with allowances.
Therefore, the CDF committee members have the tendency to appoint or nominate their friends
and relatives to participate at various stage of project life cycle. It was proposed that elections
should be conducted so that citizens can participate indirectly although some of discussants
indicated that election is not the way since some participants are required to carry evaluation
which requires a particular expertise. Therefore, the discussants and government officials
revealed there is need to find better ways of identifying participants since their contribution to
project management is vital.
4.4.3 Political Influence
The politicians have veto power to determine what aspect of project should be monitored and
evaluated, which information should be disclosed for stakeholder consumption and some areas
will be locked out of CDF projects. Therefore, the ranking of CDF projects may not focus on
societal benefits but rather on political mileage. To the constituents, they will view the CDF
projects as political goodwill and therefore they will continue to suffer on the mercy of their
politicians when the projects are directed towards fulfilling political interest leading to political
intervention. The third objective of the study was to determine the role of political influence on
effective management of Constituency Development Funded projects.
Political influence was operationalized along three dimensions such as political will,
commitment level and political interest. Five statements were formulated to measure the political
influence construct using a five-point Likert-type scale ranging from 1=strongly disagree to 5=
strongly agree and respondents were asked to indicate the extent to which they agreed to the
statements. They included projects, existence of political will in the identification and
implementation of CDF projects, political leadership ability to stick to oversight role leading to
effective management of CDF projects, CDF projects are successfully implemented due to
positive political influence, Political interest does not affect implementation of CDF projects in
the constituency and that involvement of local members of parliament add value to the projects.
The study established that majority of respondents 84.1% beneficiaries observed that local
politics interfered with CDF Constituency Project Management in Kasipul Constituency
compared to 15.9% who observed no influence. On the other hand, only 82.6% of respondents
observed that national politics influenced CDF Constituency Project Management in Kasipul
Constituency compared to 17.4% observed no political influence.
Table 4. 18: Political Influence on effective management of CDF projects-Beneficiaries’
View
Political Intervention
SD
(%)
D
(%)
U
(%)
A
(%)
SA
(%)
Mean STD
Political will 3.4 5.0 7.8 65.7 18.1 3.90 0.87Political leadership 5.3 12.1 6.9 58.6 17.1 3.70 1.06Political influence 5.0 13.7 45.2 20.2 15.9 3.28 1.05Conflict of interest 10.3 15.6 7.8 16.2 50.2 3.80 1.45MP involvement 5.0 7.8 5.9 53.6 27.7 3.91 1.05Overall Mean 3.72 1.10
Source: Field Data (2017)
From Table 4.18, majority of the sampled beneficiaries revealed that there is political will in the
identification and implementation of CDF projects as shown by 65.7% of the respondents who
agreed and 18.1% who strongly agree with a mean of 3.90 and standard deviation of 0.87.
Further, majority of the respondents confirmed that the Political leadership stick to oversight role
as indicated in the constitution which has resulted to effective management of CDF projects as
shown by a mean of 3.28 and standard deviation of 1.05. It was noted that small majority of the
respondents were undecided whether CDF projects are successfully implemented due to political
influence in their management as shown by 45.2% of the respondents while 20.2% agreed and
15.9% strongly agreed.
Regarding conflict of interest, half of the respondents strongly agreed that there is no conflict in
interest in the management of CDF project as results of political influence resulting to effective
management of CDF projects while 16.2% agreed with a mean of 3.80 and standard deviation of
1.45. Lastly, it was agreed that the involvement of the Member of Parliament adds value to the
project as shown by 53.6% of the respondents who agreed and further 27.7% who strongly
agreed and a mean of 3.91 and standard deviation of 1.05.
The overall mean response of 3.72 implied that the sampled beneficiaries agreed on most of the
statement regarding political influence while a standard deviation of 1.10 denoted that there was
some variation in the response on the statement on political influence from CDF beneficiaries’
point of view. This finding indicated that project beneficiaries agreed that; political leadership
stuck to the oversight role resulting into effective management of CDF projects in the
Constituency, there was no conflict of interest in the management of CDF Constituency projects
as a result of political and that Member of Parliament involvement in the management of CDF
projects in Kasipul Constituency added value to the projects.
The study established that majority of respondents 77.5% sampled project managers/contractors
observed that local politics interfered with CDF Constituency Project Management in Kasipul
Constituency compared to 22.5% who observed no interference. On the other hand, only 67.6%
of the sampled project managers/contractors observed that national politics interfered with CDF
Constituency Project Management in Kasipul Constituency compared to 32.4% observed no
political intervention.
Table 4. 19: Political Influence on effective management of CDF projects -Project
Managers/Contractors
Political Influence
SD
(%)
D
(%)
U
(%)
A
(%)
SA
(%)
Mean STD
Political will 2.8 9.9 2.8 38.0 46.5 4.15 1.06Political leadership 8.5 21.1 2.8 26.8 40.8 3.70 1.41Political influence 14.1 28.2 1.4 32.4 23.9 3.24 1.45Conflict of interest 14.1 33.8 5.6 14.1 32.4 3.17 1.53MP involvement 5.6 19.7 12.7 18.3 43.7 3.75 1.35Overall Mean 3.6 1.360
Source: Field Data (2017)
From Table 4.19, most of the sampled project managers/contractors revealed that there is
political will in the identification and implementation of CDF projects as shown by 38.0% of the
respondents who agreed and 46.5% who strongly agree with a mean of 4.15 and standard
deviation of 1.06. Similarly, majority of the respondents confirmed that the Political leadership
stick to oversight role as indicated in the constitution which has resulted to effective management
of CDF projects as shown by a mean of 3.70 and standard deviation of 1.41. However, most of
the respondents were undecided whether CDF projects are successfully implemented due to
political influence in their management as shown by a mean of 3.24 and standard deviation
although 28.2% of the respondents disagreed as compared to 32.4% who agreed.
In relation to conflict of interest, most of the sampled project manager/contractors were
undecided on whether there is no conflict in interest in the management of CDF project as results
of political influence resulting to effective management of CDF projects indicated by a mean of
3.817 and standard deviation of 1.53. Lastly, it was agreed that the involvement of the Member
of Parliament adds value to the project as shown by 43.7% of the respondents who strongly
agreed and further 18.3% who agreed with a mean of 3.75 and standard deviation of 1.35
The overall mean response of 3.60 implied that the sampled project managers/contractors agreed
on most of the statement regarding political influence while a standard deviation of 1.360
denoted that there was some variation in the response on the statement on political influence
from CDF project managers/contractors point of view. This finding indicated that the rating of
project managers/contractors on the role of political influence on effective management of
Constituency Development Funded projects was lower than the beneficiaries rating indicating
beneficiaries had opinion that CDF project management are political tools for politicians as
compared to project managers/contractors.
The study established that majority of respondents 60% CDF committee members observed that
local politics interfered with CDF Constituency Project Management in Kasipul Constituency
compared to 40% who observed no interference. On the other hand, only 70% of the CDF
committee members observed that national politics interfered with CDF Constituency Project
Management in Kasipul Constituency compared to 30% observed no political intervention.
Table 4. 20: Political Influence on effective management of CDF projects-CDF Committee
Members’ View
Political Influence
SD
(%)
D
(%)
U
(%)
A
(%)
SA
(%)
Mean STD
Political will 0.0 10.0 20.0 60.0 10.0 3.70 0.82Political leadership 0.0 20.0 10.0 70.0 0.0 3.50 0.85Political influence 0.0 30.0 40.0 20.0 10.0 3.10 0.99Conflict of interest 0.0 40.0 10.0 50.0 0.0 3.10 0.99MP involvement 0.0 40.0 40.0 20.0 0.0 2.80 0.79Overall Mean 3.24 0.89
Source: Field Data (2017)
From Table 4.20, it was established from the majority CDF committee members who agreed that
there was political will in the identification and implementation of CDF projects with a mean of
3.70 and standard deviation of 0.82. Similarly, majority of the respondents confirmed that the
political leadership stick to oversight role as indicated in the constitution which has resulted to
effective management of CDF projects as shown by a mean of 3.50 and standard deviation of
0.85.
However, small majority of the respondents were undecided whether CDF projects are
successfully implemented due to political influence in their management as shown by a mean of
3.10 and standard deviation of 0.99 and 40.0% of CDF committee members. In relation to
conflict of interest, slight of the sampled project manager/contractors were undecided on whether
there is no conflict in interest in the management of CDF project as results of political influence
resulting to effective management of CDF projects indicated by a mean of 3.10 and standard
deviation of 0.99. Lastly, only 20.0% of the CDF committee members confirmed that
involvement of the Member of Parliament adds value to the project as shown a mean of 2.80 and
standard deviation of 0.79
The overall mean response of 3.24 implied that the CDF committees were undecided on most of
the statement regarding political influence while a standard deviation of 1.89 denoted that there
was small variation in the response on the statement on political influence from CDF project
managers/contractors point of view. This finding indicated that the rating of CDF committee
members on the role of political influence on effective management of Constituency
Development Funded projects was lower than the other category of respondents.
The findings indicated that variant response on the influence of political leaders in the effective
management of CDF funded projects in Kasipul constituency. The beneficiaries view politics has
part in effective management of these projects while the project managers/contractors and CDF
committee members indicate the influence of politics was minimal. This was also revealed
during FGDs with the sampled beneficiaries where they indicated that distribution of CDF
projects takes a particular political line. The development to be realized through CDF projects
has favoured areas where there is political will from identification, implementation and
completion. One of the respondents from the area where the MP hails stated that:
“The current MP has brought a lot of development in our area. There is a roadwhich was in bad state for over ten years especially during rainy season but thatroad is now ok and impassable. The MP is good and am willing to vote him anytime” (FGD003, 2017).
This contradicts the sentiment of another discussant who was not pleased with the current MP on
the distribution of CDF projects. According to him, the MP has not developed the region as
expected and the projects of former MP have not been completed which has resulted to wastage
of tax payers’ money. It was also noted that most of the areas which border other constituencies
have not attracted CDF projects because of lack of clear demarcation. This was supported by
Government officials who have witnessed these areas been neglected at the expense of other
areas. One of the government officials in charge of education in the district indicated that:
“There is a school which is located at the border of Kasipul constituency andanother constituency. The areas have been neglected for years because of politicalas politicians think people in that area do not vote in the constituency of theirresidence. The other MP cannot come to upgrade the school because that area doesnot fall in his jurisdiction.” (INV004, 2017).
This is a clear indication that political influence makes it impossible to achieve growth and
development as the main objective of CDF. Such like areas are seen to suffer in term of
identification of project and representation as the current MP do not prioritize project in those
areas. It was also noted that over time, political influence may have two possible outcomes. One
of the discussants indicated some politicians have approved projects in their opposition
stronghold especially during two years to general election. The motive is the get political support
and adds some votes to his backyard. However, soon after re-election, these politicians have been
found to abandon these projects or in other scenario taking time to be completed.
Apart from identification of projects, participation in the management of CDF projects has also
been found to suffer from politicians. It was noted that majority of officials in the management of
CDF must have political will. The sitting MPs usually take advantage in the management of CDF
kitty to reward those who oiled their way to parliament and as such official they do not owe the
common mwananchi but the MP who gave them that position. This implies they are there to safe
guard the interest of the MP and also to ensure he is re-elected. In worst scenarios, such
appointees are used to accumulate wealth that would be used in campaign during the next
general election. In this regard, the effective management of CDF project cannot be achieved and
calls for the need to vet such individual before assuming office so as to serve public interest.
The situation is worse as one of the respondents indicated the current government employee who
was perfect in her work has been transferred to another constituency because the current MP is
not comfortable working with her. According to that respondent, that government official was
competent in allocation and accountability as far as CDF project management is concerned. He
credited the good CDF performance to her and she was sudden by the new she will no longer
work in that office again. She hinted that there is need for governance structure to ensure that
national government employees in charge of CDF at constituency should be transferred after
general election.
4.4.4 Technical Capacity
The study set out to establish the degree of technical capacity in the management of CDF
projects in Kasipul Constituency. Technical capacity was operationalized along five dimensions
namely expertise, training, skills and requisite knowledge. Five statements were formulated to
measure the technical capacity construct using a five-point Likert-type scale ranging from
1=strongly disagree to 5= strongly agree and respondents were asked to indicate the extent to
which they agreed to the statements. They included; stakeholders involved in the management of
CDF possession of the required expertise in their respective domains, stakeholders having gone
through the required training that equip them with project management skills, the stakeholders
trained and are able to monitor and report project status and progress of the implemented
projects, responsibilities of the management of CDF projects distribution according to academic
qualifications, availability of technical capacities among human resources to effectively manage
CDF projects.
Table 4. 21: Project management skills by Beneficiaries to monitor and report project
status and progress
Technical Capacity
SD
(%)
D
(%)
U
(%)
A
(%)
SA
(%)
Mean STD
Expertise 4.0 11.5 10.3 66.0 8.1 3.63 0.93Training 3.7 13.4 10.0 59.8 13.1 3.65 0.99Monitoring and Reporting 6.9 11.5 8.4 49.8 23.4 3.71 1.15
skillsAcademic qualifications 9.7 9.3 11.2 30.8 38.9 3.80 1.31Human Resource technical
capacity 5.9 12.8 10.3 47.4 23.7 3.70 1.14Overall Mean 3.7 1.1
Source: Field Data (2017)
From Table 4.21, findings on stakeholders’ expertise as from beneficiary’s point of view
indicated that majority of respondents 66% agreed that beneficiaries were involved in the
management of CDF possessed the required expertise in their respective domains that enhanced
the management of CDF projects and 8.1% strongly agreed with a mean of 3.63 and standard
deviation of 0.93. The findings also revealed that 59.8% and 13.1% of the respondents agreed
and strongly agree respectively that training encompasses all aspects of project management
process which has enhanced decision capabilities of stakeholders involved in the management of
CDF projects with a mean of 3.65 and standard deviation of 0.99.
It was revealed that 49.8% and 23.4% of the beneficiaries agreed and strongly agree respectively
that stakeholders are equipped with prerequisite training, skills and approaches to adequately
monitor and report the project’s status and progress with a mean of 3.71 and standard deviation
of 1.15. On academic qualification, 30.8% of the respondents agreed that responsibilities in the
management of CDF projects is distributed according academic qualification and knowledge in
specific area of specialization and further 38.9% strongly agreed. Lastly, 47.4% and 23.7% of the
beneficiaries agreed and strongly agreed that there is sufficient technical capacity amongst
human resources to effectively manage CDF Projects.
The overall mean response implied that the respondents agreed on most of the statement
regarding technical capacity while a standard deviation of 1.1 denoted that there was some
variation the response on the statement on technical capacity from beneficiaries’ point of view.
This finding showed that there was evidence of technical capacity among stakeholders in which
engendered their understanding on the management of CDF projects in Kasipul Constituency.
However, there was variation as for as responsibilities in the management of CDF projects is
distributed according academic qualification and knowledge in specific area of specialization
Table 4. 22: Project Management Skills by Project Managers/Contractors to Monitor and
Report Project Status and Progress
Technical Capacity
SD
(%)
D
(%)
U
(%)
A
(%)
SA
(%)
Mean STD
Expertise 5.6 16.9 7.0 43.7 26.8 3.69 1.20Training 0.0 12.7 9.9 38.0 39.4 4.04 1.01Monitoring & Reporting skills 0.0 4.2 5.6 59.2 28.2 4.06 0.88Academic qualifications 0.0 12.7 14.1 36.6 31.0 3.75 1.19Human Resource technical
capacity 0.0 2.8 4.2 46.5 40.8 4.14 1.03Grand Mean 3.94 1.06
Source: Field Data (2017)
From Table 4.22, project manager/contractors agreed that stakeholders involved in the
management of CDF projects have required expertise in their domain as indicated by 43.7% and
26.8% of the respondents who agreed and strongly agreed respectively (Mean=3.69, SD=1.20).
Further, 38.0% and 39.4% of the respondents agreed and strongly agreed respectively that
training encompasses all aspects of project management process which has enhanced decision
capabilities of stakeholders involved in the management of CDF projects with a mean of 4.04
and standard deviation of 1.20.
Sampled project manager/contractors also agreed that stakeholders are equipped with
prerequisite training, skills and approaches to adequately monitor and report the project’s status
and progress as indicated by a mean of 4.06 and standard deviation of 0.88. This was further
supported by 59.2% of the respondents who agreed and additional 28.2% who strongly agreed.
The results also revealed that 36.6% and 31.0% of the respondents agreed and strongly agree
respectively that responsibilities in the management of CDF projects is distributed according
academic qualification and knowledge in specific area of specialization with a mean of 3.75 and
standard deviation of 1.19. Lastly, project manager/contractors agreed that there is sufficient
technical capacity amongst human resources to effectively manage CDF Projects as indicated by
a mean of 4.14 and standard deviation of 1.03
The overall mean response of 3.94 implied that the project manager/contractors agreed on most
of the statement regarding technical capacity while a standard deviation of 1.06 denoted that
there was some variation the response on the statement on technical capacity from project
manager/contractors point of view. However, there was deviation from the meaning in term of
expertise and academic training. It can be deduced that some of the sampled project
managers/contractors had opinion that some of stakeholders involved in the management of CDF
projects lacked required expertise in their domain as well as responsibilities in the management
of CDF projects is distributed according academic qualification and knowledge in specific area
of specialization.
Table 4. 23: Project Management Skills by CDFC members to Monitor and Report Project
Status and Progress
Technical Capacity
SD
(%)
D
(%)
U
(%)
A
(%)
SA
(%)
Mean STD
Expertise 0.0 0.0 10.0 30.0 60.0 4.50 0.71Training 0.0 0.0 0.0 60.0 40.0 4.40 0.52Monitoring and Reporting skills 0.0 0.0 10.0 40.0 50.0 4.40 0.70Academic qualifications 0.0 0.0 10.0 70.0 20.0 4.10 0.57Human Resource technical capacity 0.0 0.0 10.0 50.0 40.0 4.30 0.67Mean 4.34 0.63
Source: Field Data (2017)
From Table 4.23, CDF committee strongly agreed that stakeholders involved in the management
of CDF projects have required expertise in their domain as indicated by a mean of 4.50 and
standard deviation of 0.71 although one of the respondents was not sure. The results further
revealed that their agreement that training encompasses all aspects of project management
process which has enhanced decision capabilities of stakeholders involved in the management of
CDF projects as shown by a mean of 4.40 and standard deviation of 0.52. Similarly, there was
agreement that stakeholders are equipped with prerequisite training, skills and approaches to
adequately monitor and report the project’s status and progress as indicated by a mean of 4.40
and standard deviation of 0.70.
The results also revealed that responsibilities in the management of CDF projects is distributed
according academic qualification and knowledge in specific area of specialization as indicated by
mean of 4.10 and standard deviation of 0.57. Lastly, CDF committee agreed that there is
sufficient technical capacity amongst human resources to effectively manage CDF Projects as
indicated by a mean of 4.30 and standard deviation of 0.63
The overall mean response of 4.34 implied that CDF committee agreed on most of the statement
regarding technical capacity while a standard deviation of 0.63 denoted that there was small
variation the response on the statement on technical capacity from CDF-committee point of view.
It was also established that all the committee members confirmed that there is mechanism used
in sourcing competent staff in the management of CDF projects in Kasipul Constituency.
Table 4. 24: Comparison between Respondents Views on Technical Capacity
Respondent N Min Max Mean Std. Dev
Beneficiaries 321 1 5 3.70 1.1
Project managers and contractors 71 1 5 3.94 1.06
CDF Committee Members 10 3 5 4.34 0.63
Grand Mean 3.99 0.93
Source: Field Data (2017)
Table 4.24 was used to analyze difference in view by beneficiaries, project managers/contractors
and CDF Constituency Committee on technical capacity in the management of CDF projects in
Kasipul Constituency. This comparison is important for the study because this category of
respondents view technical capacity differently as far as CDF projects management is concern.
The finding showed that CDF committee members had the best rating of technical capacity
among stakeholders compared to beneficiaries and project managers/contractors in which
engendered their understanding on the management of CDF projects in Kasipul Constituency.
This was difference possible because of CDF Committee members being the directors of CDF
projects in Kasipul Constituency looked at each issue of implementation closely, more so
technical capacity. They had a minimum of 3 as compared to other respondents. They were
followed by project managers/contractors having better education qualification which
predisposes them to better scope of understanding on technical capacity with a mean of 3.94
while beneficiaries had a mean of 3.70 with highest standard deviation denoting some variation
in regard to technical capacity.
Qualitative data collected from FGDs and interviews revealed that technical capacity is
significant in effective management of CDF funded projects. According to Government officials,
their purpose in CDF structure is to ensure all specification as met according to national
government requirements. However, one of the government officials in this study indicated it is
difficult to assess if technical capacity has been met because falsifications of various document
that are related with management of CDF funded projects. According to him, they cannot fast
track each aspect of CDF project management to ensure that they comply with government
requirement. He indicated that some of contractors are awarded tenders not based on their
technical capacity but in their relationship with CDF committee members. However, he further
revealed that if such contractors can hire expertise, then effective management of CDF projects
can be achieved
The same sentiments were shared by discussants in the FGDs where they praised and the same
time question the technical capacity of some of the stakeholders in the management of CDF
funded projects in Kasipul Constituency. One of the respondents indicated that the appointment
of some of stakeholders in the management of CDF projects do not take into consideration
academic qualification but nepotism and rewarding of cronies. In particular, some of the
appointees are allocated some position without considering their expertise and they may come
from same areas. This has been associated with favouritism in the identification, allocation and
implementation of CDF projects.
4.4.5 Regulatory Framework
The legal and regulatory framework under which the CDF operates has gone through changes
through the amendment of the CDF Act with the latest amendments leading to CDF Act 2016.
These amendments are expected to address gaps experienced during the actual implementation of
the fund meant to achieve enhanced and adequate guidelines on its implementation. This section
of the analysis presents the analysis of existing legal framework and later on attempt to analyze
the moderating effect of the framework on effective management of CDF projects in Kasipul
Constituency.
The key variables analyzed under this section include; there is clear policies and procedures on
financial practices resulting into effective management of CDF projects, the regulation on
technical capacity of the Act is implemented to the letter, regulation on community participation
has been fully embraced resulting into effective management of CDF projects, the relationship
between the CDF policies and actual implementation practice has been achieved resulting into
effective management of CDF projects. In achieving the intends of these variables, the study
analyzed the views of beneficiaries, project managers/contractors and CDF Constituency
Committee.
Table 4. 25: Beneficiaries’ View on the Regulatory Framework
Regulatory Framework
SD
(%)
D
(%)
U
(%)
A
(%)
SA
(%)
Mean STD
Clear policies and procedures 7.2 6.9 10.9 21.2 53.9 4.08 1.25Technical capacity 6.9 10.6 49.5 19.0 14.0 3.23 1.04Participation 9.3 13.7 13.1 49.2 14.6 3.46 1.17Policies and practice 7.8 9.7 14.6 21.5 46.4 3.89 1.30Overall Mean 3.67 1.19
Source: Field Data (2017)
From Table 4.25, most of the sampled beneficiaries revealed that there is clear policies and
procedures on financial practices that has resulted to effective management of CDF projects as
shown by 21.2% of the respondents who agreed and 53.9% who strongly agree with a mean of
4.08 and standard deviation of 1.25. However, majority of the respondents were undecided on
the CDF Acts on technical capacity implemented to the letter in the management of CDF projects
as shown by a mean of 3.23 and standard deviation of 1.04 with 49.5% of the respondents
remaining undecided.
It was also noted that most of the respondents agreed that the CDF Acts on community
participation has been fully embraced resulting to efficiency and effective management of CDF
projects as shown by 49.2% of the respondents who agreed and 14.6% of the respondents who
strongly agree. Finally, it was agreed that the CDF Acts on the relationship between politics and
CDF has been effectively implement results to noninterference in the management of CDF
projects as shown by 46.4% of the respondents who strongly agreed and further 21.5% who
agreed.
The overall mean response of 3.67 implied that the sampled beneficiaries agreed on most of the
statement regarding regulatory frameworks while a standard deviation of 1.19 denoted that there
was some variation in the response on the statement on regulatory framework from CDF
beneficiaries’ point of view.
Table 4. 26: Project Managers/Contractors View on the Regulatory Framework
Regulatory Framework
SD
(%)
D
(%)
U
(%)
A
(%)
SA
(%)
Mean STD
Clear policies and procedures 0.0 2.8 1.4 50.7 45.1 4.35 0.78Technical capacity 8.5 5.6 5.6 40.8 39.4 3.97 1.21Participation 0.0 5.6 12.7 40.8 40.8 4.17 0.86Policies and practice 2.8 18.3 5.6 38.0 35.2 3.85 1.18Overall Mean 4.09 1.01
Source: Field Data (2017)
From Table 4.26, majority of the sampled project manager/contractors indicated that there is
clear policies and procedures on financial practices that has results to effective management of
CDF projects as shown by 50.7% of the respondents who agreed and 45.1% who strongly agree
with a mean of 4.35 and standard deviation of 0.78. Similarly, majority of the respondents agreed
that CDF Acts on technical capacity has been implemented to the letter in the management of
CDF projects as shown by 40.8% of the respondents who agreed and 39.4% who strongly
agreed.
The results further revealed that most of the respondents agreed that the CDF Acts on community
participation has been fully embraced resulting to efficiency and effective management of CDF
projects as shown by 40.8% of the respondents who agreed and 40.8% of the respondents who
strongly agree. Finally, it was agreed that the CDF Acts on the relationship between politics and
CDF has been effectively implement results to noninterference in the management of CDF
projects as shown by 38.0% of the respondents who agreed and further 35.2%who strongly
agreed with a mean of 3.85 and standard deviation 1.18
The overall mean response of 4.09 implied that the sampled project managers/contractors agreed
on most of the statement regarding regulatory frameworks while a standard deviation of 1.01
denoted that there was some variation in the response on the statement on regulatory framework
from CDF project managers/contactors point of view. It can be noted this mean is higher than
that of beneficiaries.
Table 4. 27: CDF Committee View on the Regulatory Framework
Regulatory Framework
SD
(%)
D
(%)
U
(%)
A
(%)
SA
(%)
Mean STD
Clear policies and procedures 0.0 0.0 0.0 50.0 50.0 4.50 0.53Technical capacity 0.0 0.0 0.0 80.0 20.0 4.20 0.42Participation 0.0 0.0 0.0 50.0 50.0 4.50 0.53Policies and practice 0.0 0.0 0.0 50.0 50.0 4.50 0.53Overall Mean 4.43 0.5
Source: Field Data (2017)
From Table 4.27, majority of the CDF committee member indicated that there are clear policies
and procedures on financial practices that has results to effective management of CDF projects as
shown by a mean of 4.50 and standard deviation of 0.53. Similarly, majority of the respondents
agreed that CDF Acts on technical capacity has been implemented to the letter in the
management of CDF projects as shown by a mean of 4.20 and standard deviation of 0.42
The results further revealed that most of the respondents strongly agreed that the CDF Acts on
community participation has been fully embraced resulting to efficiency and effective
management of CDF projects as shown by mean of 4.50 and standard deviation of 0.53. Finally,
it was strongly agreed that the CDF Acts on the relationship between politics and CDF has been
effectively implement results to noninterference in the management of CDF projects as shown by
mean of 4.50 and standard deviation of 0.53.
The overall mean response of 4.43 implied that the CDF committee members agreed on most of
the statement regarding regulatory frameworks while a standard deviation of 0.5 denoted that
there was small variation in the response on the statement on regulatory framework from CDF
project managers/contactors point of view. It can be noted this mean is higher than that of
beneficiaries and CDF project managers/contractors.
4.4.6 CDF Project Management
Effective CDF project management was used in this study as a latent dependent variable which
depends on other latent variables including the effectiveness of stakeholder participation,
political influence, technical capacity and project financing. Effective CDF project management
was measured using set timeliness, set objectives, cost/budget provision, technical requirement,
quality standards and user satisfaction. The six-statement included CDF project management
included; CDF projects are implemented according to the set timeline, the projects were
implemented and evaluated according to set objectives, projects were implemented according to
cost/budget provision, projects implemented according to set technical requirements, projects are
implemented according to the intended quality standards and that projects implemented
according to users satisfaction.
Table 4. 28: Beneficiaries View on Effective CDF Project Management
CDF Management SD D U A SA Mean Std Dev
Timeline 7.8 41.4 6.2 24.6 19.9 3.07 1.33Set objective 5.0 18.7 24.6 31.8 19.9 3.43 1.15Cost/Budget 6.9 28.3 12.8 35.8 16.2 3.26 1.22Technical Requirements 6.9 26.2 15.0 31.8 20.2 3.32 1.25Intended quality standard 6.9 38.9 13.1 22.4 18.7 3.07 1.28User satisfaction 10.0 41.7 10.0 20.2 18.1 2.95 1.32Grand Mean 3.18 1.26
Source: Field Data (2017)
From Table 4.28, majority of the sampled beneficiaries did not confirm that CDF projects are
implemented according to the set timelines. Only 24.6% and 19.9% of the respondents agreed
and strongly agreed respectively that CDF projects are implemented according to the set
timelines with a mean of 3.07 and standard deviation 1.33. The results further revealed that
31.8% of the respondents agreed that CDF projects are implemented and evaluated according to
set objectives while 19.9% strongly agreed with a mean of 3.43 and standard deviation of 1.15.
On costing, 35.8% of the respondents agreed that CDF projects are implemented according to the
cost/budget provisions and 16.2% strongly agree with a mean of 3.26 and standard deviation of
1.22.
The results further revealed that 31.8 % and 20.2% agreed and strongly agreed respectively that
CDF projects are implemented according to the set technical requirements with a mean of 3.32
and standard deviation of 1.25. However, 38.9% of the respondents disagreed that CDF projects
are implemented according to the intended quality standards as compared to 22.4% who agreed
and 18.7% who strongly agree with a mean of 3.07 and standard deviation of 1.28. Similarly,
41.7% disagreed and 10.0% strongly disagreed that CDF projects are implemented to user
satisfaction as compared 20.2% who agreed and 18.1% who strongly agreed with a mean of 2.95
and standard deviation of 1.32
The overall mean response of 3.18 implied that the sampled beneficiaries were undecided on
most of the statement regarding CDF project management while a standard deviation of 1.26
denoted that there was some variation in the response on the statement on CDF project
management from CDF project beneficiaries’ point of view.
Table 4. 29: Project Managers/Contractors View on Effective CDF Project Management
CDF Management SD D U A SA Mean Std Dev
Timeline 2.8 18.3 2.8 25.4 50.7 4.03 1.24Set objective 5.6 8.5 5.6 42.3 38.0 3.99 1.14Cost/Budget 2.8 8.5 4.2 50.7 33.8 4.04 0.99Technical Requirements 2.8 11.3 11.3 25.4 49.3 4.07 1.15Intended quality standard 0.0 14.1 4.2 39.4 42.3 4.10 1.02User satisfaction 0.0 22.5 1.4 29.6 46.5 4.00 1.18Overall Mean 4.04 1.12
Source: Field Data (2017)
From Table 4.29, majority of the sampled project managers/contractors confirmed that CDF
projects are implemented according to the set timelines as shown by 25.4% and 50.7% who
agreed and strongly respectively with a mean of 4.03 and standard deviation 1.24. The results
also revealed that 42.3% of the respondents agreed that CDF projects are implemented and
evaluated according to set objectives and 38.0% strongly agreed with a mean of 3.99 and
standard deviation of 1.14. It was also noted that half of the respondents agreed that CDF
projects are implemented according to the cost/budget provisions and 33.8% strongly agree with
a mean of 4.04 and standard deviation of 0.99.
The results further revealed that 25.4% and 49.3% agreed and strongly agreed respectively that
CDF projects are implemented according to the set technical requirements with a mean of 4.07
and standard deviation of 1.15. Further, 39.4% of the respondents agreed that CDF projects are
implemented according to the intended quality standards and 42.3% who strongly agree with a
mean of 4.10 and standard deviation of 1.02. Lastly, 29.6% agreed and 46.5% strongly agreed
that CDF projects are implemented to user satisfaction with a mean of 4.00 and standard
deviation of 1.18.
The overall mean response of 4.04 implied that the sampled project managers/contractors agreed
on most of the statement regarding CDF project management while a standard deviation of 1.12
denoted that there was some variation in the response on the statement on CDF project
management from CDF project managers/contractors point of view. This rating of CDF project
management is greater as compared to sampled beneficiaries view
Table 4. 30: CDF Committee View on Effective CDF Project Management
CDF Management SD D U A SA Mean Std Dev
Timeline 0.0 0.0 10.0 50.0 40.0 4.30 0.67Set objective 0.0 0.0 0.0 20.0 80.0 4.80 0.42Cost/Budget 0.0 0.0 0.0 60.0 40.0 4.40 0.52Technical Requirements 0.0 0.0 0.0 60.0 40.0 4.40 0.52Intended quality standard 0.0 0.0 0.0 60.0 40.0 4.40 0.52User satisfaction 0.0 0.0 0.0 20.0 80.0 4.80 0.42Overall Mean 4.52 0.51
From Table 4.30, CDF committee members agreed that CDF projects are implemented according
to the set timelines as shown by a mean of 4.30 and standard deviation 0.67. The results also
revealed that the respondents strongly agreed that CDF projects are implemented and evaluated
according to set objectives as indicated by a mean of 4.80 and standard deviation of 0.42. It was
also noted that respondents agreed that CDF projects are implemented according to the
cost/budget provisions as indicated by a mean of 4.40 and standard deviation of 0.52.
The results further revealed that respondents agreed that CDF projects are implemented
according to the set technical requirements with a mean of 4.40 and standard deviation of 0.52.
Further, the respondents agreed that CDF projects are implemented according to the intended
quality standards as indicated that by a mean of 4.40 and standard deviation of 0.52. Lastly,
respondents strongly agreed that CDF projects are implemented to user satisfaction with a mean
of 4.80 and standard deviation of 0.42.
The overall mean response of 4.52 implied that the CDF committee members strongly agreed on
most of the statement regarding CDF project management while a standard deviation of 0.51
denoted that there was small variation in the response on the statement on CDF project
management from CDF committee members’ point of view. This rating of CDF project
management is greater as compared to sampled beneficiaries and CDF project
managers/contractors view.
Table 4. 31: Comparison between Respondents Views on Effective CDF Project
Management
Respondent N Min Max Mean Std. DevBeneficiaries 321 1 5 3.18 1.26Project managers and contractors 71 1 5 4.04 1.12CDF Committee Members 10 3 5 4.52 0.51Grand Mean 3.99 0.93
Source: Field Data (2017)
Table 4.31 was used to analyze difference in view by beneficiaries, project managers/contractors
and CDF Constituency Committee on the management of CDF projects in Kasipul Constituency.
The researcher visited the sampled projects, observed and determined the completion statuses of
the projects as summarized in table 4.31. This comparison is important for the study because this
category of respondents view CDF project management differently as far as CDF projects
management is concern. The finding showed that CDF committee members had the best rating of
CDF project management among stakeholders compared to beneficiaries and project
managers/contractors.
Table 4. 32: Status of Sampled Projects from 2013 to 2017
Project categoryProject Status
Completed On-going StagnantEducation 20.5%(9) 27.3%(12) 52.3%(23)Health 18.2%(2) 27.3%(3) 54.5%(6)Security 14.3%(1) 28.6%(2) 57.2%(3)Environment 0%(0) 100%(1) 0%(0)Sports 0%(0) 0%(0) 100%(1)Roads 25%(2) 25%(2) 50%(4)Water 20%(1) 40%(2) 40%(2)Total 14.0 37.5 48.5
From Table 4.32, 14.0% of projects were completed while 37.5% of projects were still on-going.
However, 48.5% of the projects were stagnant. The study noted it was most initiated projects
stalled after general election where new MP is reluctant to complete projected started by his/her
predecessor. Therefore, the 37.5% were also likely that some of them will be stalled during
project duration.
4.5 Validity of the study instruments
In order to establish the validity of study instruments, tests of sampling adequacy were used. This
enabled the study identify whether the items of the latent variables were appropriate for further
analysis. Table 4.33 shows Kaiser-Meyer-Olkin (KMO) test of sampling adequacy and Bartlett's
test of sphericity.
Table 4. 33: Sampling Adequacy and Bartlett's test of sphericity
Factors KMO Bartlett's Test of Sphericity Determinant
Test Approx.
Chi-Square
Df Sig.
Project Financing 0.743 1054.411 10 0.000 0.071Stakeholder
Participation
0.795 623.489 10 0.000 0.209
Political Influence 0.712 304.103 10 0.000 0.465Technical Capacity 0.795 623.489 10 0.000 0.209Regulatory Framework 0.797 631.815 6 0.000 0.205CDF Management 0.871 1006.631 15 0.000 0.080
The test results show that the scales had values above the threshold of 0.7 as established by
Williams et al, 2012): project financing (0.743), stakeholder participation (0.795), political
influence (0.712), technical capacity (0.795), regulatory frameworks (0.797) and CDF
management (0.871). Williams et al (2012) stated that KMO of 0.50 is acceptable degree for
sampling adequacy with values above 0.5 being better.
Bartlett's Test of sphericity which analyzes if the samples are from populations with equal
variances produced p-values less than 0.05 (p < .001) thus indicating an acceptable degree of
sampling adequacy. Project financing had a chi-square value of 1054.411 (p <.001), Stakeholder
Participation (623.489, p <0.001), Political Influence (304.103, p < 0.001), Technical Capacity
(623.489, P<0.001), Regulatory Framework (631.815, P<0.0001) and CDF Management
(1006.631, p < 0.001). Determinant values are more than 0: Project financing (p <.071),
Stakeholder Participation (0.209), Political Influence (0.465), Technical Capacity (0.209),
Regulatory Framework (0.205) and CDF Management (0.080). Thus, it was acceptable to
proceed with the analysis.
4.6 Inferential analysis
To draw conclusions on the objectives of the study, inferential analysis of the data collected was
carried out and used for hypothesis testing. The aim of the study was to investigate the
determinants of effective management of constituency development funded projects in Kasipul
constituency, Homa Bay County, Kenya. This was achieved by assessing the influence of the
determinants (projects financing, stakeholder participation, political influence and technical
capacity) on effective project management. Inferential analysis involved statistical model
estimation to explore the causal effects of these determinants on the dependent variable with
statistical significance. The statistical approach used for inferential analysis in this study was
structural equation modelling (SEM) which is a collection of techniques that combine both
confirmatory factor analysis and regression analysis to fit statistical models. Structural equation
modelling was carried out with the use of Analysis of moments structures (AMOS) software
version 23.
The strength of SEM is that it is flexible and allows examination of complex associations using
various types of data including categorical, dimensional, censored, count variables (MacCallum,
Widaman, Zhang, & Hong, 1999). Using both Factor analysis and regression analysis, SEM
explores the measurement and structural models during estimation of model coefficients.
4.6.1 Measurement model validity and reliability
SEM requires reliability and construct validity of the data to be used to be tested. The
measurement model relates the measured variables to the latent variables using factor analysis.
The measured variables are the observed items which are the indicators based on the data
collection instrument. The latent variables are the unobserved larger constructs to which the
observed indicators belong. Latent variables are unobserved and are uncovered by exploring the
underlying structure of a set of observed variables.
Factor analysis is a statistical dimension reduction technique used to explore the underlying
structure of a set of observed variables. There is a unidimensionality basic assumption of
measurement theory that a set of items forming an instrument measuring one thing in common.
To explore the relationships between a variable and another, the variable must be
unidimensional; the various items underlying the data must measure the same traits. Exploratory
factor analysis identifies underlying factors and categorizes items that are closely related without
considering any hypothesized priori model or theories. By this, a large number of variable items
are collapsed into a few interpretable and manageable underlying factors (Leech, Barrett and
Morgan, 2011). Appendix XII shows a summary of the proportion of variances explained by the
extracted components from EFA.
All the indicators in are subjected to EFA where possible components are extracted. There were 6
retained factors that had eigen values greater than 1 which is an implication of possible
extraction of 6 unidimensional latent variables from the items (Cattell, 1977; Leech, Barrett &
Morgan, 2011). The six retained factors explain up to 65.666% of the total variations from the
items. From the initial extraction, the first component explained up to 39.26% of the total
variance. Rotation was carried out which yielded results where all the 6 retained components
explain up to 65.666% of total variance with the first component only explaining 21.229%.
The exploratory factor loadings table from exploratory factor analysis is shown in Appendix
XIII. In EFA, factor loadings above 0.4 are acceptable and items are identified to belong to the
latent variable they load highest. Only one item PI1 was found not to have any loadings above
0.4 in any of the components. Table 4.34 Shows the Kaiser-Meyer-Olkin (KMO) test and
Bartlett’s test of sphericity which were also used under exploratory factor analysis (EFA). The
KMO is a measure that ranges from 0 to 1 and was used for the proportional variance in the
observed items that could have been caused by their underlying factors. A KMO value that is
very low is an indication of a likely inappropriateness of factor analysis as it shows likely
diffusions in the patterns of correlations as the sum of partial correlation is large relative to the
sum of correlations (Graham, 2006; Tavakol & Dennick, 2011).
Table 4. 34: KMO and Bartlett's Test
Test ValueKaiser-Meyer-Olkin Measure of Sampling Adequacy. 0.938Bartlett's Test of Sphericity Approx. Chi-Square 7196.994
df 435Sig. 0.000
Source: Field Data (2017)
The KMO value was found to be 0.938 which is a high figure that is close to 1 and acceptable.
The Bartlett's test of sphericity is to test for a significant relationship among the observed
indicators. A significant relationship is evident with the confirmation that the correlation matrix
of the indicators is not an identity matrix which would be an indication of unrelated indicators
(Pallant, 2010). For the Bartlett’s test in this study, the Chi-square statistic of the Bartlett’s test
was found to be 7196.994 with a p-value of 0.000. The p-value that is less than 0.05 is a
confirmation at 0.05 level of significance that the correlation matrix of the indicators is not an
identity matrix thus the indicators have an evident significance relationship as is expected for
appropriate factor analysis. Further analysis of reliability and validity of the measurement model
were carried out considering confirmatory factor analysis and measures of internal consistency.
Table 4.35 shows reliability test results of internal consistency.
Table 4. 35: Internal consistency
Constructs Cronbach alpha Number of items StatusProjects financing 0.866 5 ReliableStakeholder participation 0.809 5 Reliable
Political influence 0.844 5 ReliableTechnical capacity 0.847 5 ReliableLegal frameworks 0.834 4 ReliableProject management 0.866 6 ReliableSource: Field Data (2017)
Reliability analysis of the data collected was carried out using Cronbach alpha measurement of
internal consistency which found the data on all the constructs reliable with Cronbach alpha
statistics above 0.7. Cronbach alpha ranges from 0 to 1 where values higher than one imply high
reliability and values above 0.7 are considered acceptable.
Confirmatory factor analysis CFA is adopted as a coherent part of SEM considering it’s use in
verification of factor structure of a set of observed variables. It is a verification technique of
priori and hypothesised structures and relationships that are based on theoretical and empirical
information. Under CFA, the observed variables are subjected factor analysis to verify that they
belong to the latent variable that they are purported to belong to based on theoretical and
empirical research. Under CFA, the observed items are expected to load the latent variable above
0.4. As shown in appendix XIV, the factor loadings are all above 0.4 except PI1 which was found
to load Political influence by 0.32 which is less than 0.4. This indicator was thus expunged in
further analyses while all the other indicators were retained.
The results of CFA were also used to confirm construct validity of the data collected as is
required under SEM. Construct validity is confirmed by exploration of both convergent and
discriminant validity. Convergent validity is a measure that confirms that the items that are meant
to have relationships are actually related while discriminant validity gives a confirmation that
items that are not meant to be related are actually not related. Convergent validity was measured
by determining the average variances extracted (AVEs) from CFA. AVEs are measures of the
total amount of variance that can be ascribed to the latent construct (Fornell & Larcker, 1981;
Teo, 2011). The AVEs for all the constructs were found to be above 0.5 as regarded to be
adequate for convergent validity (Teo, 2011). The exploration of discriminant validity involves
the comparison of the AVEs and the squared multiple correlations. The data is said to exhibit
discriminant validity if all the squared multiple correlations are less than the relative constructs
AVE as was found in this study. These results thus showed a confirmation of both convergent
and discriminant validity thus a confirmation that the data collected and used had construct
validity.
4.6.2 Correlation analysis
In this study, correlation analysis of the latent variables was conducted and correlation
coefficients obtained. This analysis was carried out using the unobserved latent variables that
were generated for each construct from the measurement indicators by confirmatory factor
analysis. The correlation analysis aided in assessment of the influence of all study variables on
effective management of Constituency Development Funded projects. The analysis was based on
the objectives of the study. An analysis was thus carried out to assess the existence of a
significant relationship between each determinant and effective management of Constituency
Development Funded projects. Table 4.36 Presents the correlation analysis between each
determinant and effective project management.
Table 4. 36: Correlation analysis
Projects
financing
Stakeholder
participation
Political
influence
Technical
capacity
Legal
framework
Effective Project management
Pearson Correlation
0.738 .559 .490 .492 .599
Sig. (2-tailed) 0.000 0.000 0.000 0.000 0.000N 402 402 402 402 402
Source: Field Data (2017)
The results indicated that all independent variables had significant relationship with dependent
variable (Effective CDF project management). The relationship between project financing and
effective project management was found to be strong and positive (r=0. 738, p=0.000). The
relationship between stakeholder participation and effective project management was moderate
(r=0.4841, p=0.000). Both political influence and technical capacity were also found to have
moderate positive relationships with effective project management, (r=0.1346, p=000) and
(r=0.1346, p=000) respectively. The objectives of the study however sought to investigate the
causal relationships to determine the influence that the determinants have on effective CDF
project management.
4.6.3 Confirmatory Structural Model
The structural model under SEM is the part that uses regression analysis to explore the
relationship between the latent constructs. The study was based on hypothesised causal
heathenship between the determinants and project management. The general objective of this
study was to investigate the determinants of effective management of constituency development
funded projects in Kasipul constituency, Homa Bay County, Kenya. This was achieved by
exploring the influence of the determinants (projects financing, stakeholder participation,
political influence and technical capacity) on effective management.
Having explored and confirmed validity of the measurement model, the study further used SEM
to explore the causal influences of the unobserved latent constructs based on the objectives of the
study. SEM uses maximum likelihood estimation (MLE) to fit regression models (Leedy &
Ormrod, 2013). MLE is based on classical assumptions which under SEM were tested to confirm
that they were met for the model fitted (Pallant, 2010; Leedy & Ormrod, 2013).
4.6.3.1 Test of normality and outliers
This classical assumption in standard linear modelling using maximum likelihood estimation is
that the dependent variable and residuals follow a normal distribution. Structural equation
modelling that was adopted in this study also assumes that all the endogenous variables and the
residuals are normally distributed. This assumption in SEM implies that the joint distribution of
the endogenous variables should exhibit multivariate normality (Rex & Kline, 2015). Violation
of normality is attributed to existence of outliers thus the test for outliers was also carried out.
The Mahalanobis distance assessment was used to evaluate the existence of multivariate outliers.
Multivariate testing of outliers on the dependent variable using Mahalanobis D-Squared (D2)
was done and results presented in appendix XIX.
Table 4. 37: Normality Results
Kolmogorov-Smirnov a Shapiro-WilkStatistic df Sig. Statistic Df Sig.
PM1 .252 402 .000 .841 402 .000PM2 .222 402 .000 .886 402 .000PM3 .273 402 .000 .867 402 .000PM4 .229 402 .000 .873 402 .000PM5 .230 402 .000 .862 402 .000PM6 .257 402 .000 .851 402 .000Effective project management .103 402 .000 .957 402 .000
Multivariate NormalityKurtosis C.R.206.604 56.371
Source: Field Data (2017)
The Kolmogorov-Smirnov test was employed for normality testing of the endogenous variables.
This test establishes the extent of normality of the data by detecting existence of skewness or
kurtosis or both. The Kolmogorov-Smirnov statistic p-values range from zero to one with figures
higher than 0.05 indicating that the data is normal (Razali & Wah, 2011). The results showed
that all the endogenous indicators and the latent variable Effective Project management had p-
value of .000 which are less than 0.05 (p < 0.05) hence confirming deviation from normality. The
test for multivariate normality also showed that the C.R. of the multivariate Kurtosis is 56.371.
The C.R. is larger than 1.96 implying significant deviation from normality.
The evidence of violation of normality can also be shown in the test for multivariate outliers. The
outlier’s assessment table in appendix XIX shows the Mahalanobis distances furthest from the
centroid and significant tests whether they qualify as outliers. The distances (d-square) of these
furthest observations range 101.994 to 32.737. The probabilities of the Chi-square distribution of
the distances are computed and the outlier observations associated with probabilities less than
0.05 tested. The p-values (p1) of 72 observations are less than 0.05 confirming significant
outliers at 0.05 level of significance.
Due to violation of the normality assumption, bootstrapping was carried out during estimation to
deal with the violation. Performing a bootstrap is a technique for resampling to get multiple sub-
samples of the same size as the original sample are drawn randomly to provide data for empirical
investigation of the variability of parameter estimates & indices of fit where original data
violates normality assumption (Byrne, 2013). Bootstrapping would treat the non-normal data as
normal by drawing sub samples randomly out of the originally collected samples. Figure 4.1
shows the bootstrap distribution from the Structural equation model data which shows a bell-
shaped histogram indicating evidence of a normal distribution.
|--------------------607.372 |*641.349 |**675.326 |***
709.303 |*********743.280 |****************777.257 |****************811.234 |*******************
N = 1000 845.211 |***************Mean = 807.072 879.188 |***********S. e. = 2.437 913.165 |******
947.142 |****981.119 |**1015.09
6|*
1049.073
|*
1083.050
|*
|--------------------
Figure 4. 1: Bootstrap distribution ML discrepancy (implied vs sample) (Default model)
4.6.3.2 Test of Multicollinearity
Standard maximum likelihood estimation as well as SEM also assumes that the independent
(exogeneous) variables do not exhibit multicollinearity. Multicollinearity is said to exist if one or
more predictors can be expressed as a linear function of other predictor variables (Menard 2002).
Multicollinearity was tested by generating the Variance Inflation Factors (VIF) and its reciprocal
(the tolerance) for each independent variable. Multi-collinearity can be solved by omitting one of
the highly correlated variables and re-computing the regression equation (Belsley et al, 1980). A
variable with collinearity tolerance below 0.2 implies that 80% of its variance is shared with
some other independent variables which is a sign of multicollinearity. Multicollinearity is also
associated with VIFs above 5. In the current study tolerance ranged from 0.489 to 0.704 which
are all above 0.2 and therefore its reciprocal, the VIF was between 1.421 and 2.045, which are
below the threshold value of 5 as required. This indicated that the data set displayed no
multicollinearity. Table 4.38 presents the result of tests for Multicollinearity.
Table 4. 38: Collinearity Statistics
Tolerance VIFProjects financing .495 2.022Stakeholder participation .704 1.421Political influence .511 1.956Technical capacity .489 2.045Source: Field Data (2017)
4.6.3.3 Test of Heteroscedasticity
The test for heteroscedasticity was conducted to establish whether the model residuals exhibit
homoscedasticity. Linear Best linear unbiased estimate models (BLUE models) assume that the
residuals have a constant variance referred to as being homoscedastic (Belsley, Kuh and
Welsch’s, 1980). To test for heteroscedasticity, the Breusch-Pagan test. The BP Lagrange
multiplier (LM) statistic was computed for the residuals (Hassler & Breitung, 2006). The BP
tests the hypothesis that H0: residuals do not exhibit heteroscedasticity (residuals are
homoscedastic). The P-value of the BP-LM test was greater than 0.05 implying that the residuals
do not exhibit heteroscedasticity thus meeting the homoscedasticity assumption.
Table 4. 39: Heteroscedasticity Results
LM Sig Conclusions
BP 9.564 0.058 Fail to reject H0Source: Field Data (2017)
4.6.3.4 Test of Independence (non-autocorrelation)
Independence of error terms, which implies that observations are independent, was assessed
through the Durbin-Watson test. Durbin Watson (DW) test checked that the residuals of the
models were not auto-correlated since independence of the residuals is one of the basic
hypotheses of regression analysis (Montgomery et al, 2001). Its statistic ranges from zero to four.
The calculated Durbin-Watson statistic is compared to the tabulated Durbin-Watson statistics for
a model with 4 predictors excluding the intercept and sample size of 402. The calculated Durbin
Watson statistic is higher than the upper limit of the tabulated value that shows non-
autocorrelation implying independence.
Table 4. 40: Durbin-Watson Results
Durbin-Watson statistic Tabulated lower limit Tabulated Upper limit1.921 1.821 1.851
Source: Field Data (2017)
4.6.3.5 Common method Variance
Common method bias also referred to as common method variance is the bias which is due to an
inconsistency in observed measures causing variation that is not attributed to the construct
measurement (Podsakoff, MacKenzie & Podsakoff, 2003). The relationships among theoretical
constructs can get inflated or as a result of this bias leading to errors. Common method variance
normally occurs due to the use of the same survey participant (common source) to provide
responses to the questionnaires for both the independent and dependent constructs being studied
at the same time (Jakobsen & Jensen, 2015; Podsakoff, MacKenzie, Jeong-Yeon, & Podsakoff,
2003). The SEM diagram in Figure 4.2 Was shows the test results on common method bias test.
Figure 4. 2: Common method bias
To assess existence of common method bias in the structural equation modelling (SEM), the
paths from the items are subjected to a common factor and constrained to an equal variance
weight to the common factor. The common variance is shared and is expected to be less than 0.5
across the sub-dimensions. The results for the common method bias are shown in figure 4.1. The
items share a constrained common variance that was found to be 0.32 which is less than 0.5
which is an indication that the data collected does not exhibit common method bias.
4.6.3.6 Model Fit Indices thresholds
Model fit assessment is important in structural equation modelling to gauge how well the
estimated model best fits the data. It is therefore essential that studies test for model fitness since
the assessment of how a specified model fits the data is among of the most important steps in
SEM (Yuan, 2005). There is an abundance in available fit indices and a wide disparity in
agreement on which indices to report the cut-offs for the various indices. The choice of indices to
assess in this study was based on coverage by ensuring that the examination of model fitness
covered both absolute fitness, incremental fitness and parsimony of fitness. Table 4.40 Shows the
model fit indices adopted in the study with the proposed cut-off values.
Absolute fit indices are used to test how well the priori (hypothesised) model fits the sample data
(McDonald and Ho, 2002) and include the Chi-Squared test, RMSEA, GFI, AGFI, the RMR and
the SRMR. Absolute fit indices do not rely on comparison to any baseline model but are
measures of model fitness without comparison (Jöreskog and Sörbom, 1993). For absolute
fitness the considered the assessment of the Chi-Squared, RMSEA, GFI, and the SRMR. The
cut-offs used are based on empirical uses. Chi-Square test is the traditional measure goodness of
fit and is used to assess the discrepancy between the sample and fitted covariances (Hu &
Bentler, 1999) where a good fit would be reflected by a significant Chi-square at 0.05 level of
significance with a p-value less than 0.05. The Goodness of fit index (GFI) which is considered
an alternative to the Chi-square is a value of the proportion of variance that the estimated
population covariance accounts for (Tabachnick and Fidell, 2007). The recommended cut-off of
the GFI requires values above 0.9. The RMR is calculated as the square root of the difference
between the residuals and the hypothesised model’s covariance matrix. Interpretation of the
RMR is made difficult where the collection instrument considers varying number of items per
construct, a problem addressed by assessing the standardised RMR (SRMR) instead. According
to Hoyle, 2012, SRMR values ≤ .08 reflects an adequate fit.
To assess incremental fitness, the study considered the normed fit index (NFI) and the
comparative fit index (CFI) whose cut-offs also required values above 0.9. Incremental fit
indices are also referred to as comparative or relative fit indices and which compare the chi-
square to a baseline model (McDonald and Ho, 2002). The NFI is a measure of goodness of fit
that compares the model chi-square to that of the null model and has recommended values above
0.9 for adequacy Bentler and Bonnet (1980). The CFI also have recommendations of values
above 0.9 and is a measure which is a revision of the NFI to take the sample size into account
(Byrne, 1998).
Parsimony fit indices are goodness of fit indices that are adjusted to account for the average
ability for the model to fit diverse data patterns referred to as model fitting propensity (FP)
(Mulaik et al, 1989; Crowley and Fan, 1997). The study considered the Parsimony Goodness-of-
Fit Index (PGFI) and the Parsimonious Normed Fit Index (PNFI) which covered parsimony of
both absolute and comparative fitness. The cut-off for the parsimony fitness were set at 0.5 as it
is noted for possibility to obtain parsimony fit indices within the .50 with other goodness of fit
indices being over .90 (Mulaik et al 1989).
Table 4. 41: Goodness of fit thresholds
Index Desired (good fit) Cut-off/ ThresholdsChi-square p-value <0.05NFI ≥0.9CFI ≥0.9GFI ≥0.9SRMR ≤0.08RMSEA ≤0.08PGFI ≥0.5PNFI ≥0.5Source: Field Data (2017)
4.6.3.7 SEM on the determinants of effective management of projects
The analysis of the structural equation model is presented to show model fitness, path
coefficients and the structural equation diagram. The model was fitted to achieve the objective of
the study which was to investigate the causal relationships to determine the influence that the
determinants have on effective CDF project management. The fitted model was tested for
goodness against the set cut-offs as shown in table 4.42.
Table 4. 42: Goodness of fit statistics for model 1
Index Model Desired (good fit)
threshold
Status
Chi-squareStatistic 545.941
p-value <0.05 Good fitP-value 0.000NFI 0.905 ≥0.9 Good fitCFI 0.938 ≥0.9 Good fitGFI 0.905 ≥0.9 Good fitSRMR 0.056 ≤0.08 Good fitRMSEA 0.064 ≤0.08 Good fitPGFI 0.647 ≥0.5 Good fitPNFI 0.624 ≥0.5 Good fitSource: Field Data (2017)
The model was found to meet all the fitness tests. It was found to be of good fitness based on
both absolute and relative fitness tests. The traditional chi-square goodness of fit statistic was
545.941 with a p-value of 0.000 which is less than 0.05 implying significant fitness at 0.05 level
of significance. Both RMSEA and the SRMR were found to have values less than 0.08 as
required while the GFI an absolute fit index and the comparative fit indices CFI and NFI were
both found to have values greater than the required cut-off of 0.9. Figure 4.3 Shows the path
diagram for the structural equation model on the determinants of effective management of
projects without considering legal frameworks (the moderating variable) in the model.
Figure 4. 3: Path diagram for model 1 on the determinants of effective management of
projects
The path coefficients of the estimated model were tested for significance to establish the
significance of the causal relationships between the determinants and effective management of
projects. Table 4.42 Presents the estimated path coefficients of the fitted model with the standard
errors (S.E.), the critical ratios (C.R.) and the p-values of the CRs. SEM was fitted based on
maximum likelihood estimation for a large sample therefore the critical ratios follow a standard
normal distribution (Z-distribution) thus the p-values are determined considering the Z-
distribution. The critical ratio following a standard normal distribution considers 1.96 as the
critical point at 5% level of significance. Only 2 of the 4 determinants studied were found to
have significant influence on effective management of funded projects.
Table 4. 43: Path coefficient estimates for model 1
Variable path Estimate S.E. C.R. PPM <--- CP 0.316 0.073 4.308 ***PM <--- PI 0.039 0.175 0.222 0.825PM <--- PF 0.996 0.131 7.603 ***PM <--- TC -0.239 0.122 -1.953 0.051Source: Field Data (2017)
From the results in the Table 4.43, it was found that 2 of the 4 hypothesised determinants;
technical capacity (TC) and political influence (PI) have no significant causal effect on
effectiveness of management of funded project (PM). The critical ratios for the 2 were found to
be -1.953 and 0.222 respectively that both have absolute values less than 1.96 implying
insignificance at 5%. Projects financing (PF) with coefficient estimates (β=0.996, C.R =7.603)
and stakeholder participation (CP) with coefficient estimates (β=0.316, C.R =4.308) were both
found to be significant. The critical ratios are greater than 1.96 implying significance at 5%. This
implies that project financing, stakeholder participation and political influence improved the
effective management of CDF funded projects. The model for the estimate of effective project
management generated from this model is given by the equation below;
Y=0.996 X1+0.316 X2
4.6.3.8 Model 2: SEM with legal frameworks as a predictor
The study also sought to determine the moderating effect of legal frameworks. A structural
equation model was fitted including legal frameworks as a predictor in the model. This model
would determine the direct effect that legal framework has on effective CDF project
management. The fitted model was also tested for goodness against the set cut-offs as shown in
table 4.44.
Table 4. 44: Goodness of fit test for model 2
Index Model Desired (good fit)
threshold
Status
Chi-squareStatistic 1022.605
p-value <0.05 Good fitP-value 0.000NFI 0.860 ≥0.9 Acceptable fitCFI 0.912 ≥0.9 Good fitGFI 0.852 ≥0.9 Good fitSRMR 0.066 ≤0.08 Good fitRMSEA 0.078 ≤0.08 Good fitPGFI 0.586 ≥0.5 Good fitPNFI 0.634 ≥0.5 Good fitSource: Field Data (2017)
This model was also found to at least meet absolute fitness and incremental fitness. It was found
to be of good fitness based on both absolute and relative fitness tests. The traditional chi-square
goodness of fit statistic was 1022.605 with a p-value of 0.000 which is less than 0.05 implying
significant fitness at 0.05 level of significance. Both RMSEA and the SRMR were found to have
values less than 0.08 as required as was the CFI a comparative fit index which was also found to
have values greater than the required threshold of 0.9. The NFI and GFI were however both
found to be 0.860 and 856 respectively which are below the desired 0.9. The values are however
relatively close to 1 and acceptable according to Hooper et al (2014) that the GFI has been
proffered to be acceptable as low as 0.8. Notwithstanding the relatively acceptable GFI and NFI
indices, the PGFI and PNFI which are parsimony tests for both fitness indices were above 0.5
implying good fit. Figure 4.4 Shows the path diagram for the structural equation model on the
determinants of effective management of projects including legal frameworks as a predictor in
the model.
Figure 4. 4: Path diagram for model 2 with legal frameworks as a predictor
Table 4.45 presents the estimated path coefficients of the fitted model with the standard errors
(S.E.), the critical ratios (C.R.) and the p-values of the CRs for this model. This fitted model also
based on maximum likelihood estimation considered significance test based on the standard
normal critical point of 1.96 at 5% level of significance. In this model, 3 predictors including
legal frameworks were found to have significant influence on effect project planning for CDF
funded projects.
Table 4. 45: Path coefficient estimates for model 2
Variable path Estimate S.E. C.R. PPM <--- CP .354 .082 4.291 ***PM <--- PI .054 .210 .256 .798
PM <--- TC -.166 .135 -1.235 .217PM <--- PF 1.290 .189 6.819 ***PM <--- LF -.385 .141 -2.725 .006Source: Field Data (2017)
Legal frameworks with coefficient estimates (β= -.385, C.R = -2.725) has a significant negative
effect on effective management of CDF funded projects. The critical ratio has an absolute value
of 2.725 which is greater than 1.96 implying a significant influence at 5% level of significance.
4.6.3.8 Model 3: SEM on the moderating effect of legal frameworks
To objectively test the moderating effect of legal frameworks, a third model was fitted to include
the interaction variables between legal frameworks and the independent variables. Confirmatory
factor analysis yielded latent variables which were generated for each construct. The interaction
variables were then generated as cross products intersections of the independent latent variables
and the generated latent variable for legal frameworks. The generated interaction variables were
then included in the structural model to explore the moderating effect of legal frameworks. The
fitted model was also tested for significance as shown in table 4.46
Table 4. 46: Goodness of fit test for model 3
Index Model Desired (good fit)
threshold
Status
Chi-squareStatistic 1760.158
p-value <0.05 Good fitP-value 0.000NFI 0.803 ≥0.9 AcceptableCFI 0.889 ≥0.9 AcceptableGFI 0.801 ≥0.9 AcceptableSRMR 0.089 ≤0.08 AcceptableRMSEA 0.090 ≤0.08 AcceptablePGFI 0.587 ≥0.5 Good fitPNFI 0.625 ≥0.5 Good fitSource: Field Data (2017)
The model was found to be of good absolute and baseline fitness. The traditional chi-square
goodness of fit statistic was 1760.158 with a p-value of 0.000 which is less than 0.05 implying
significant fitness at 0.05 level of significance. The RMSEA and SRMR were to be 0.090 and
0.089 respectively which were found to be relatively acceptable. A low value of the RMSEA as
possible is desired, a value below 0.08 shows a good fit, a value below 0.1 acceptable but would
not want to employ a model with a RMSEA greater than 0.1 (Browne and Cudeck, 1993). The
other absolute and incremental fit indices; the GFI NFI and CFI all did not meet the good fit
thresholds above 0.9 the values were 0.801, 0.803 and 0.889 which all lie with then the range
<0.8 GFI, NFI < 0.9 and 0.85 < CFI < 0.9 that show acceptable fitness (Bentler, 1990; Cole,
1987; Marsh, Balla & McDonald, 1988). The parsimony tests for both absolute and comparative
fitness were of good fit. The PGFI and PNFI were found to be 0.587 and 0.625 which are both
above the 0.5 threshold. Figure 4.5 Shows the path diagram for the structural equation model on
the determinants of effective management including legal frameworks and the interaction terms
between the determinants and legal frameworks to assess the moderating effect it has.
Figure 4. 5: Path diagram for model 3 on the moderating effect of legal frameworks
In this model three determinants were found to have significant influence on effective
management of funded CDF projects at 5% level of significance. Table 4.47 Presents the
estimated path coefficients of the fitted model with the standard errors (S.E.), the critical ratios
(C.R.) and the p-values of the CRs.
Table 4. 47: Path coefficient estimates for model 3
Variable path Estimate S.E. C.R. P
PM <--- CP .354 .079 4.487 ***PM <--- TC -.259 .129 -2.008 .045PM <--- PF 1.160 .169 6.878 ***PM <--- LF -.177 .124 -1.427 .154PM <--- X1Z .116 .025 4.598 ***PM <--- X4Z -.086 .025 -3.415 ***PM <--- X2Z .035 .023 1.531 .126PM <--- PI .071 .196 .360 .719
Stakeholder participation (CP) and project financing (PF) positively influence effective project
management while technical capacity negatively influences it. The estimates were tested using
the critical ratios that follow a standard normal distribution with 1.96. the estimates of
stakeholder participation, project financing and technical capacity all had C.R.s above 1.96
implying statistical significance at 5%. Legal frameworks (LF) was interacted with the
hypothesised determinants and the interaction terms included in the model.
The interaction terms of legal frameworks with stakeholder participation (X2Z) and that with
political influence (X3Z) were found to be insignificant with C.R.s of 1.531 and -0.640
respectively which are both less than 1.96. The interactions of legal frameworks with project
financing (X1Z) and that with technical capacity (X4Z) were however found to be significant
with absolute C.R.s of 4.598 and 3.415 which are both greater than 1.96. This was an implication
that legal frameworks have a significant positive moderating effect on the relationship between
project financing and effective project management but have a significant negative moderating
effect in the relationship between technical capacity and effective project management. The
model for the estimate of effective project management generated from this model is given by
the equation below;
Y=1.160 X1+.354 X 2−.259 X4+.116 X1∗Z−.086 X4∗Z
4.6.4 Moderated multiple regression
Further to the structural equation models a hierarchical moderated multiple regression (MMR)
was carried out to assess the moderating effect. The MMR was adopted for the hierarchical
stepwise analysis involved. The hierarchical MMR is a three-step analysis where a predictor or a
set of predictors is added to the model at each stage and the effect on the overall model assessed.
The MMR analysis used the constructs generated from confirmatory factor analysis as latent
variables and was based on ordinary least squares regression (OLS). In stage one of the analysis,
the 4 hypothesised determinants of effective management of CDF funded projects were included
in the model. In the second stage, the moderating variable (legal frameworks) was introduced to
the model and the effect of the addition assessed. In the third stage to assess the moderating
effect of legal frameworks, the interaction terms between legal frameworks and the determinants
were also introduced and the effect to the model assessed. Table 4.48 shows the summary
statistics for the models at each stage of analysis.
Table 4. 48: Model Summary statistics
Model R R
Square
Adjuste
d R
Square
Std. Error
of the
Estimate
Change StatisticsR Square
Change
F
Change
df1 df2 Sig. F
Change
1 .770a .593 .588 .64151296 .593 144.348 4 397 .0002 .772b .595 .590 .64016609 .003 2.672 1 396 .1033 .779c .607 .598 .63367285 .012 3.039 4 392 .017
a. Predictors: (Constant), Technical capacity, Stakeholder participation, Political influence, Projectsfinancingb. Predictors: (Constant), Technical capacity, Stakeholder participation, Political influence, Projectsfinancing, Legal frameworkc. Predictors: (Constant), Technical capacity, Stakeholder participation, Political influence, Projectsfinancing, Legal framework, SP interaction LF, PI interaction LF, PF interaction LF, TC interaction LFSource: Field Data (2017)
The summary statistics show the effect of each stage of the analysis. The study assessed the
change statistics including the change in R-square and the change on F-statistics as the effect at
each stage. In model 1, the R-square of 0.593shows that 59.3% of the variation in the dependent
variable (management of CDF funded projects) is explained by the variation of the predictors
(the determinants) in model 1. Model 2 shows an R-square of 0.590. The R-square change is
0.003 as the increase due to introduction of the moderating variable. The change is however
insignificant at 5% level of significant as portrayed by the p-value of the change in R-square of
0.103 which is greater than 0.05. This is an implication that the change in the model due to the
addition of the variable legal frameworks has no significant effect to the model.
In stage 3, the interaction terms between each determinant and the moderator were added to the
model and the effect assessed. The R-square of the third model is 0.607 implying that 60.7% of
the variation in effective project management is explained by the variation of the predictors in
model 3. The R-square change due to the introduction of the interaction terms is 0.012. The
change is significant at 5% level of significance as implied by the p-value of the F-statistics for
model 3 which is less than 0.05. The significant improvement to the model due to introduction of
the interaction terms is an indication that legal frameworks is moderates the relationship between
the determinants and effective management of CDF funded projects. Table 4.48 shows the
coefficient estimates of the 3 MMR models.
Table 4. 49: Coefficient estimates
Model UnstandardizedCoefficients
t Sig.
B Std. Error1 (Constant) .000 .032 .000 1.000
Projects financing .625 .046 13.607 .000Stakeholder participation .256 .039 6.645 .000Political influence .027 .044 .620 .536Technical capacity -.052 .046 -1.121 .263
2 (Constant) .000 .032 .000 1.000Projects financing .592 .050 11.811 .000Stakeholder participation .247 .039 6.322 .000Political influence .017 .045 .387 .699Technical capacity -.084 .050 -1.670 .096Legal framework .089 .055 1.635 .103
3 (Constant) -.030 .041 -.727 .468Projects financing .588 .053 11.028 .000Stakeholder participation .252 .044 5.697 .000Political influence .014 .048 .290 .772Technical capacity -.116 .054 -2.150 .032Legal framework .140 .062 2.279 .023PF interaction LF .112 .043 2.641 .009SP interaction LF .051 .033 1.540 .124PI interaction LF -.013 .041 -.313 .755TC interaction LF -.098 .046 -2.123 .034
Source: Field Data (2017)
The coefficients of model 1 show that according to model 1 project financing and stakeholder
participation have significant influences in effective management of CDF funded projects. This
is similar to the findings from the SEM analysis that also found technical capacity and political
influence to have insignificant direct effect on effective project management. Project financing
(β= .625, t=13.607, p =.000) and stakeholder participation (β= .256, t=6.645, p =.000 .05) both
have p-values less than 0.05 implying significance at 5% level of significance. The model for the
estimate of effective project management generated from the MMR model 1 is given by the
equation below;
Y=0.625 X1+0.256 X2
The addition of legal frameworks to the model had no significant improvements to the model.
The added variable legal frameworks (β= .089, t=1.635, p = .103) has a p-value greater than 0.05
implying that in model 2, legal frameworks have no significant direct influence on effective
project management. Model 3 that saw the addition of the interaction terms was however found
to be significant. 2 of the added interaction terms were found to be significant. project financing
interaction legal frameworks (β= .112, t=2.641, p = .009) and stakeholder participation
interaction legal frameworks (β= -.098, t=-2.123, p = .034) both have p-values less than 0.05
implying significant influence. The results of model 3 therefore shows that legal frameworks
have a significant moderating effect on the relationship between project financing and
management of CDF funded projects and that between stakeholder participation and
management of CDF funded projects. The model for the estimate of effective project
management generated from the MMR model 3 is given by the equation below;
Y=.588 X1+.252 X2−.116 X 4+.140Z+.112 X1∗Z−.098 X 4∗Z
Legal frameworks were therefore found to moderate the relationships between project
management and 2 determinants. Graphical presentation of the moderating influence was
therefore constructed for the 2 effects. Figure 4.4 shows a graphical presentation of the
moderating effect of legal frameworks on the relationship between effective project management
and project financing. As shown, low levels of legal frameworks show a gradual slope which is
due to the existence of a causal relationship between project financing and effective management
of the projects. Increasing the levels of legal frameworks shows an increase in the slope of the
curve between projects financing and effective project management. The slope keeps increasing
at higher levels of legal frameworks implying that increasing the levels of legal frameworks has
a positive moderating effect which increases the strength of the causal relationship between
projects financing and effective project management.
Low Projects financing High Projects financing-0.8-0.6-0.4-0.2
00.20.40.60.8
11.2
Low Legal frameworkMed. Legal frameworkHigh Legal framework
Eff
ectiv
e m
anag
emen
t of
proj
ects
Figure 4. 6: Moderating effect of legal frameworks on project financing and effective
project mgt.
The study found that legal frameworks have a negative moderating effect on the relationship
between technical capacity and effective project management. Figure 4.6 shows a graphical
presentation of the moderating effect of legal frameworks on the relationship between effective
project management and technical capacity. As shown, low levels of legal frameworks show a
gradual positive slope which is causal relationship between technical capacity and effective
management of the projects. Increasing the levels of legal frameworks causes a change in the
direction of the relationship as shown in the negative slope of the curve between technical
capacity and effective project management at medium levels of legal frameworks. The slope
keeps decreasing at higher levels of legal frameworks implying that increasing the levels of legal
frameworks has a negative moderating effect which decreases the strength of the causal
relationship between technical capacity and effective project management.
Low Technical capacity High Technical capacity-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
Low Legal framework
Med. Legal framework
Eff
ectiv
e m
anag
emen
t of
proj
ects
Figure 4. 7: Moderating effect of legal frameworks on technical capacity and effective
project mgt.
4.6.5 Comparison between Completed, ongoing and stagnant Projects
The study further conducted regression analyses comprising of multiple and hierarchical analysis
to establish effectiveness of determinants according to the status of the projects. The results are
presented in Table 4.50 and Table 4.51.
Table 4. 50: Multiple Linear Regression: Comparison between Completed, ongoing and
stagnant Projects
Completed On-Going StagnantR .901 .859 .617R Square .811 (81.1%) .738 (73.8%) .381 (38.1%)Adj. R2 .802 .729 .368F Change 88.114*** 82.466*** 30.465***Df 4, 82 4,117 4,198Technical Capacity (TC) -.166* .154 .237***
Stakeholder Participation (SP) .785*** .231** .165**Political Influence (PI) .380*** -.101 -.156*Project Financing (PF) .289*** .698*** .408***
Notes: Dependent Variable: Effective project Management. Significance: *p<0.05; **p<0.01;***p<0.001.
From Table 4.50 shows that there was strong relationship between effective management
completed CDF projects and determinants (technical capacity, stakeholder participation, political
influence and project financing) as indicated by R coefficient of 0.901. This implies that up to
90.1% (R2=0.901, P<0.001) effective management of completed CDF projects is accounted for
by the selected determinants. All the determinants had significant influence on the effectiveness
management of competed CDF projects; however, there was notable difference in significant
level and direction. A unit increase in technical capacity would results to significant decrease in
effective management of completed projects by 0.166 units (P<0.05). On the other a unit
increase in stakeholder participation would results to increased effective management of
completed projects by 0.785 (P<0.001), a unit increase in political influence would results to
increased effective management of completed projects by 0.380 (P<0.001). Lastly, a unit
increase in project financing would results to increased effective management of completed
projects by 0.389 (P<0.001).
There was strong relationship between effective management of on-going CDF projects and
determinants as indicated by R coefficient of 0.859. This implies that up to 85.9% (R2=0.859,
P<0.001) effective management of on-going CDF projects is accounted for by the selected
determinants. Two of the four determinants had significant influence on the effectiveness
management of competed CDF projects; however, technical capacity and political influence did
have significant influence (P>0.05). On the other a unit increase in stakeholder participation
would results to increased effective management of on-going CDF projects by 0.231(P<0.01)
and a unit increase in project financing would results to increased effective management of on-
going projects by 0.698 (P<0.001).
There was moderate relationship between effective management of stalled CDF projects and
determinants as indicated by R coefficient of 0.617. This implies that up to 38.1% (R2=0.381,
P<0.001) effective management of stalled CDF projects is accounted for by the selected
determinants. All the determinants had significant influence on the effectiveness management of
competed CDF projects; however, there was notable difference in significant level and direction.
A unit increase in technical capacity would results to significant increase in effective
management of completed projects by 0.237 units (P<0.001). A unit increase in stakeholder
participation would results to increased effective management of stalled projects by 0.165
(P<0.01). On the other hand, a unit increase in political influence would results to significant
decrease in effective management of stalled projects by 0.156 (P<0.05). Lastly, a unit increase in
project financing would results to significant increased effective management of stalled projects
by 0.408 (P<0.001).
The study also examined the influence of moderating variable (legal framework) according to the
status of projects in relation to effective project management and the determinants. The results
are as shown in Table 4.51.
Table 4. 51: Legal Framework as a moderating Variable; Comparison between Completed,
ongoing and stagnant Projects
Completed On-Going StagnantR Square .897 .773 .430F Change 15.118 2.565 4.059R Square Change .086*** .035* .049**Df 4,77 4,112 4,193
Legal Framework (LF) -6.261*** -2.605* -3.358**TC interaction LF -2.098* .495 2.462*SP interaction LF 4.062*** 1.118 1.661PI interaction LF 1.903 -.416 -.217PF interaction LF 4.153*** 2.013* 1.866
Notes: Dependent Variable: Effective project Management. Significance: *p<0.05; **p<0.01;***p<0.001.
From Table 4.51, there was significant increase in R square as shown by R square change of
8.6% (R2=0.086, P<0.001). This implies that legal framework governing management of CDF
interaction determinants accounts for additional 8.6% effectiveness in the management of CDF
completed projects. Interaction between technical capacity and legal framework results to
negative predictive power on effective management of completed CDF projects as indicated β=-
2.098, P<0.05. This implies that as effect of legal framework on technical capacity increases,
effective management of completed CDF projects decreases. On the other hand, as effect of legal
framework on stakeholder participation increases, effective management of completed CDF
projects increases by 4.062, P<0.001 and as effect of legal framework on project financing
increases, effective management of completed CDF projects increases by 4.153, P<0.001.
In regard to on-going projects, there was significant increase in R square as shown by R square
change of 3.5% (R2=0.035, P<0.05). This implies that legal framework governing management
of CDF interaction determinants accounts for additional 3.5% effectiveness in the management
of CDF on-going projects. Interaction between project financing and legal framework results to
positive predictive power on effective management of on-going CDF projects as indicated
β=1.866, P<0.05. This implies that as effect of legal framework on project financing increases,
effective management of on-going CDF projects increases by 2.013, P<0.05.
There was significant increase in R square as shown by R square change of 4.9% (R 2=0.049,
P<0.01). This postulates that legal framework governing management of CDF interaction
determinants accounts for additional 4.9% effectiveness in the management of CDF stalled
projects. Interaction between technical capacity and legal framework results to positive
predictive power on effective management of stalled CDF projects as indicated β=2.462, P<0.05.
This implies that as effect of legal framework on technical capacity increases, effective
management of stalled CDF projects increases by 2.462.
CHAPTER FIVE
5.0 DISCUSSIONS
5.1 Introduction
This chapter explains the results regarding the determinants of effective CDF project
management in Kasipul Constituency, Homa Bay County, Kenya. It also explains the moderating
role of regulatory framework on the relationship between the determinants and effective CDF
project management. The chapter discusses the results of the hypothesized relationship of all
predictor variables and individual effects of each variable on effective CDF project management.
Finally, the chapter presents discussions on how the findings relate to the existing theory and
findings from empirical studies.
The literature on decentralization as a form of governance points out that decentralization
involves the establishment of an arena of decision making that lies outside the influence of the
central government in which the central government delegates some of its power to local or
regional administrators, which carry out certain function on their own (Parrado, 2005). In his
view Smith (1985), sees decentralization as the delegation of power to lower levels in a territorial
hierarchy whether the hierarchy is of governments within state or offices within a large-scale
organization. Further. Smith notes that decentralization can occur in all geographical areas like
neighborhoods, field personnel in the area of central department or within a large organization.
This study reveals that the government of Kenya adopts the decentralization system where funds
are allocated to local communities through the CDF.
The implementation of devolved funds and devolved systems in the community may be dogged
by controversy and confusion resulting to ineffective management of projects funded by CDF.
This can be generated in part by weaknesses in the respective Acts that these funds operate with
(Gikonyo, 2008). Some of these Acts may give excessive powers to various stakeholders such as
CDF committee members, fund managers and politicians involved in their management. The
uptake of this is that there may be cases of corruption, misappropriation of funds and a lack of
community participation in their activities. Indeed, there may exist few mechanisms of oversight
to hold such leaders accountable (Nowrojce, 2008).
There is need to set appropriate institutional structures to manage the devolution process in any
society. Governments are encouraged, where appropriate, to decentralize their public institutions
and services. This should be done to a level that is compatible with their overall responsibilities,
priorities and objectives. It is through this that they will be able to respond properly to local
needs and facilitate local participation. Effective decentralized units managing these devolved
funds also need to have the technical know-how, capacity and financial resources. These will
enable them to sustain the delivery of local public services and development at levels satisfactory
to citizens.
In an effective decentralized system, members are no longer predominantly unqualified
appointees named to appease party loyalists. They are rather well educated public servants
committed to the progress of their community. Decentralization will then be effective and proper.
It will also encourage further introduction of programs and services to this decentralized unit, it
is then that local authorities and association networks will be strengthened. Therefore,
governments at the appropriate levels, should review and revise necessary legislation. Through
this local autonomy and programs sustainability will be ensured. It will encourage participation
in decision making, implementation, and resource mobilization
Poor management structures are the greatest threat to the successful existence and
implementation of devolved funds. These may be in the form of poorly designed devolution
structures based on transfers from the central government. They may also be in the form of
similar systems of management and where expenditure responsibilities are inadequately defined.
The effect of this is that they weaken the effect of these systems due to coordination problems.
For decentralization to work adequately, accountability between all the players should be ensured
(Obuya, 2008). Proper role specification for the fund managers should be spelt.
Therefore, the purpose of this study was to investigate the determinants of effective management
of Constituency Development Funded projects in Kenya: a case of Kasipul constituency, Homa
Bay County, Kenya. This was achieved through formulation of four objectives and four
hypotheses while the moderating effect of regulatory framework was also investigated so as to
find out what influence it have on the relationship between the determinants (project financing,
stakeholder participation, technical capacity and political influence) on effective management of
CDF funded projects.
5.2 CDF Project Management in Kasipul Constituency
The results revealed that beneficiaries had a moderate rating on the effectiveness of CDF project
management as compared to CDF committee and project managers/contractors. Of all the CDF
project management effectiveness, set objective (3.43) was rated highly while user satisfaction
was rated lowest (2.95). For project manager/contractors, intended quality standards was rated
highly (4.10) while set objective was rated lowly (3.99). Lastly, the CDF committee rated user
satisfaction highly (4.80) while timeline was rated lowly (4.30). From this comparison, it can be
deduced that different stakeholders have different view on the effectiveness of CDF projects
management with CDF committee members implying that CDF projects have been effectively
managed as opposed to beneficiaries.
During FGDs and interviews, it was revealed that some of the beneficiaries have not been fully
convinced with the CDF projects have been managed. The delay in the completion of projects
was identified by majority of the beneficiaries as some of simple projects have taken more than 3
years to be completed. It was also noted the continuity of projects is also another cause of user
satisfaction with some project facing complete abandonment after new Member of Parliament
has been elected. This has been confirmed by empirical findings raising concerns on the factors
influencing effective CDF project implementation. Kirui, Chemutai and Rotich (2015)
examining the determinants of completion time of projects funded through constituency
development fund at Ainamoi Constituency found that 70.26% of the projects had not been
completed several years after commencement. KIPPRA (2008) also found that majority of the
projects undertaken through CDF had stalled or took long to complete.
Further, it was revealed that some of the project have been done especially road in some party of
the Constituency. It was revealed that some contractors have the tendency to deliver below par
road projects which cannot last even for one financial year. This had the Kasipul Constituency to
be impassable during rainy season hindering the citizens from undertaking their chores. There is
tendency for such like projects to be poorly done so as the same job to be reassigned to other
contractors after two years. According to Kirui and Wanyoike (2015) examining the determinants
of implementation of constituency development fund projects in Baringo Central Constituency
found that CDF projects were not completed within set timelines, costs and as per technical
requirements and hence majority of the projects were not effective.
5.3 The influence of projects financing on effective management of Constituency
Development Funded projects
In Kenya, the current allocation of CDF is 2.5% of the national budget which is felt by many
people to be rather small and may need to be enhanced to at least 5%. At the constituency level,
the entire amount allocated to each constituency is to be spent based on functional criteria set in
the law. One criterion emphasizes that not less than 73% of the CDF allocation should be spent
on development projects. This calls for proper management of project funds so as to achieve
effective management of CDF funded projects.
Therefore, objective one of the study sought to assess the influence of projects financing on
effective management of Constituency Development Funded projects. Project financing
comprised of allocation, auditing, timely disbursement, transparency and accountability.
Respondents had been asked to indicate the extent to which they agreed on these dimensions.
Effective CDF project management measures comprised of timeliness, objectives,
budget/costing, technical requirement, quality standards and user satisfaction. To achieve
objective one, it was hypothesized that there is no significant relationship between projects
financing and effective management of CDF funded projects.
From beneficiaries’ points of view, there was moderate extent in project financing when they
were required to state the extent of their agreement on five statements relating to project
financing in a scale of 1 to 5. Accountability, transparency, auditing and adequate allocation of
funds for various aspects of CDF projects was still in an issue as far as beneficiaries of CDF
funded projects are concerned. It was found that the allocation was only for the CDF projects and
little funds were allocated to monitoring and evaluation. However, majority of beneficiaries
revealed that CDF funds are timely disbursed to the identified projects as well as CDF funds are
adequately allocated to the identified projects which has enhanced completion of projects is
some of the projects undertaken by Kasipul CDF office.
This view was also revealed by the project managers/contractors who indicated that fund
allocated to some projects are inadequate so as conduct other functions that are required by law
that ensures effective management of CDF funded projects. It was also revealed that allocation of
funds to identify project delayed their completion as the Kasipul CDF offices prefer to allocate
one project up to three times. This means that a project that was to be finished within one
financial year can take up to three financial years to be completed. The project
managers/contractors hinted that there is need to allocate a project once till completion instead of
piecemeal which results to delay in completion and increase in fixed cost which increases the
overall cost of projects. In the allocation of funds and disbursement of funds for CDF funded
project, it is vital that there are adequate rules and regulation that would govern these two
aspects.
The CDF committee members ranked project financing in Kasipul Constituency above average
as compared to beneficiaries and project managers/contractors. It was however, revealed that
disbursement is still an issue which is beyond the control of CDF office as disbursement is done
at national level. It was established that, there is no law or regulations that governs disbursement
of funds from the National Government to respective CDF Constituency accounts. Further, the
allocation of funds to CDF has been found to insufficient to cover the cost of managing CDF
funded projects. Focusing on CDF projects auxiliary functions such as monitoring and
evaluation, auditing and stakeholder participation reduces CDF budgets for actual development
projects.
Interview with Government officials and FGDs also indicated that there are some delays in the
completion of projects which are associated with delay in disbursement of funds. The
government officials also revealed that the funds allocated to the CDF projects limit the effective
management of the projects as the budgetary allocation do not cater for stakeholder participation
during monitoring and evaluation. In this case, only government officials are involved with few
representatives from the local community based on the budgetary allowance.
Some of the challenges that affected project financing that were identified by respondents from
qualitative data collection included cost escalation beyond the expected limits, failure by the top
management to support the budget, unplanned repairs or patches of a budget due to uncertainty,
lack of trained personnel to prepare the budgets and conflict among members of the CDF staff,
lack of proper bookkeeping, lack of clear policies and procedures on budgets. It is clear that
challenges in CDF project financing are inherent in CDF stakeholders including policies and
procedures which are part of governance on the usage of devolved funds.
Before testing the first hypothesis, a correlation analysis was conducted to determine the strength
and direction of the relationship between the dimensions of project financing and the effective of
CDF project management. The results of the correlation analysis indicated that relationship
between the different dimensions of project financing and effect management of project was
positive and statistically significant. The composite mean of the project financing dimension was
found to have a strong and significant positive relationship with effective management of
Constituency Development Funded projects. Implying that improvement in timely disbursement
of funds, auditing process, adequate allocation of funds would result to effective management of
CDF funded projects. This is because effectiveness is associated with availability of funds and
sufficient funds would ensure projects are completed within timelines, project is within user
satisfaction due to their involvement hence quality standards.
The study further carried out a SEM analysis to assess the influence of project financing on the
effective CDF project management. From the findings, the null hypothesis was rejected implying
that there is significant relationship between projects financing and effective management of
CDF funded projects. It was thus found that an increase in project financing on its own by one
unit would result to increase in effective management of Constituency Development Funded
projects by 0.996 units holding other factors constant. Further, the study also deduced that legal
frameworks positively moderates the causal relationship that project financing has on effective
management of Constituency Development Funded projects. Both the moderating effected tested
by the SEM model and the moderated multiple regression (MMR) model revealed this
moderating effect. Based on the MMR model, the moderating effect is revealed by the
interaction between legal frameworks and projects financing which has a 0.112 significant effect
on effective CDF project management.
From the findings it can be deduced that project financing influences the effective management
of Constituency Development Funded projects. The most important aspect of project financing is
the availability of funds, allocation and how it is utilized to achieve project objectives. CDF
projects which are funded by tax payers are required to be allocated sufficiently and at the same
time there is need for a mechanism in place to monitor how they are utilized to ensure
accountability and transparency.
From the three sampling units, it is evident that project financing influence effective
management of CDF funded projects. According to CDF funded project beneficiaries, there is
need for transparency and accountability in the management of CDF projects and this can only
be achieved through proper auditing of the projects undertaken by CDF office at Kasipul
Constituency. Majority of project beneficiaries in this study are not aware about allocation and
disbursement of CDF funds to identified projects and the only to ensure effective project
financing is through auditing. Through auditing, transparency and accountability would be
achieved as it would reveal how much was allocated and how much was disbursed by the CDF
projects.
On the other hand, project contractors/managers faulted disbursement of funds from CDF office
and allocation of funds to CDF funded projects. It was revealed that effective management of
CDF projects is affected by timely disbursement of funds and adequacy in allocation. There are
no laws and regulations that stipulate at what time funds should be disbursed and allocated to the
identified projects. This implies that each Constituency has their own timelines of fund
disbursement and how a project is to be allocated. In Kasipul constituency, the project allocation
is spread over several financial years and the project contractors/managers are forced to comply
with these regulations. According to them, the longer the projects takes to be completed, the
ineffective is to be completed according to user satisfactions. This was also supported by
government officials who indicated that accessibility of CDF project funds influence
effectiveness managed of CDF funded projects
However, CDF committee members were of the opinion that they cannot control disbursement of
funds to projects as that mandate is vested on CDF Board that ensure timely and efficient
disbursement of funds to every constituency. It was revealed that CDF funds allocated
Constituency is little as the allocation is a minimum of two and half per cent (2.5%) of all
National Governments’ share of annual revenue towards community projects identified at
constituency level by the communities. This means that there is need to increase the minimum
allocation so as to increase the funds that reach Constituency. The CDF committee members also
revealed that effective management of CDF projects can be achieved if National Government
through National Assembly Select Committee on National Government CDF can continually
review the frame set out for the efficient delivery of development programmes financed through
the Fund as they are tasked with implementation.
From various responses, project financing influences effective management of CDF funded
projects in Kasipul Constituency. However, various gaps exist in CDF Acts implementation and
policy framework. This calls for proper governance structure that would ensure audit processing
is done to citizen satisfaction and every penny that is spent is accounted for through proper
budgeting so that funds allocated according to priority. This would increase citizen satisfaction
with the way projects funded by taxpayer money is effectively managed. The delay in
disbursement of funds at the national level implies that lack of policy framework that can ensure
consistent in disbursement also affects disbursement of funds at constituency level. Inadequate
allocation of funds at national level also affects allocation at constituency level as such
government has the responsibility to strengthen CDF kit for effective management of CDF
funded projects.
This finding agrees with previous studies such as Gwadoya (2012) by indicating that financial
resources should be realistically planned and estimated in advance before commencement of
projects especially building and construction projects. Shortcoming in project financing has been
associated with delay in project completion and sometime abandonment of projects which negate
the spirit of devolution through CDF. This finding is also supported by Moenga, (2015) who
posits that the most important factor influencing timely completion of construction projects in
Kenya is; financed by the contractor during the project and delays in contractor’s payment. Most
of the contractors have complained about delay in fund disbursement making to incur extra cost
due inflation of building materials and other fixed cost associated with the projects.
Study carried out by Ochieng, Owuor and Tubey (2013) who found that CDFC don’t fund
projects in full, funding projects in halves is very costly and it really assist the intended
beneficiaries not achieve their objective in time. In this study, the CDF committee members
revealed that there are a lot of projects to be funded and allocated one project huge sum of
money would indicate other projects would not be attended and as such there would be public
outcry. Another reason of piecemeal allocation was that it is easy to monitor the contractors and
in case of bad work another contractor can be sought in the next allocation. The project manager
also indicated that there is delay in disbursement of funds a problem which they associated with
National government delay in disburses of CDF to the constituency. This was also supported by
CDF committee members who indicated that delay in disbursement is not associated with
Kasipul CDF office but the treasury delay in disbursement.
The results also revealed that there was need for all stakeholders to informed and be vigilant on
effective budgeting of the CDFs, to review and make recommendations on the CDF management
programs and to monitor compliance with budgeting policies put in place, Review the budget
performance quarterly, half yearly and end year financial, to enhance proper management
through budgeting controls of the CDF, consider the major findings of CDF budgeting
investigations and responses as well as Train the CDF members on financial management and
especially on budgeting (Mburu and Muturi, 2016). It can thus be concluded that budgeting has
great impact on project finance which influence project management effectiveness
It was also noted audits were fairly carried out in completed projects in the Kasipul Constituency
although the reports of audit were not implemented so as improve future effectiveness of CDF
project management. As suggested by Wanjiru (2008) and Manasseh (2007) public audits are an
ideal strategy of monitoring allocation, use and sustainability of funds allocated through the
devolved funds. Such audits should aim at ensuring compliance with the International Public-
Sector Accounting principles, safeguard public assets and provide assurance to the stakeholders
who include government agencies, public, policy makers, donors and scholars (Manasseh, 2007).
The results are consistent with extant literature and previous studies that suggested that project
financing influence effectiveness of CDF funded projects. This finding is supported by Kalungu
(2010) who found budgetary influenced management of the CDF projects and activity-based
budgeting was preferred by many constituencies, while a few practiced a combination of activity
based and zero-based budgeting. There was no satisfaction on how the CDF is managed and
therefore proper budgeting is necessary to enhance CDF management. Most of the constituencies
do not have budget committees and that the people involved in the budget preparation were
accountants, however all the constituencies said they do prepare budgets. This necessitates
improvement in its allocation which can be enhanced through proper budgetary practices. Thus,
there is a clear indication that almost all the constituencies experienced budgetary deficits.
Kung’u & Mwangi, (2014) revealed that fund management practices such use of budgetary
allocation has significant strong positive influence on the financial performance. The efficiency
levels on fund management practices were average thus indicating that CDF funded water
projects embraced and implemented efficient fund management practices in project operations
hence the survival of CDF funded water projects are eminent. This implies that efficient fund
management practices have a significant effect on the financial performance of CDF funded
water projects in Kenya. The practices included budget preparation, cash deficit occurrence and
cash surplus.
The finding is further supported by Sullivan and Mayer (2010) who observed that the most
consistent greatest hindrance to timely delivery of project is budget limitations. According to
them, it is difficult to compensate inadequacies of funds unlike other limitations such as technical
or human capacity which can the compensated through outsourcing and training. Nganga (2011)
found that delay in government disbursement of CDF funds to the constituency influence factors
influencing cost-effectiveness of Constituency Development Fund by 198% whereby if not
observed reduces factors influencing cost effectiveness by 198%, whereas if observed they
improve the factors influencing cost effectiveness by 198% in in Kaloleni Constituency.
Kamau and Muturi (2015) found that there exists a very strong and positive relationship between
funds allocation and successful completion of CDF projects. It was, moreover, concluded that
how funds are allocated impacts very significantly on successful completion of CDF projects in
Nyandarua County. This in line with findings of current study where results from descriptive
and Structural Equation Model indicated timely disbursement of funds and funds allocation
influenced project management in Kasipul constituency. The amount allocated to the CDF
projects is insufficient, which agreed with Ochanda’s (2010) observation that amount of funds
that go through the district treasuries are much higher than the overall CDF allocation.
The CDF management in Nyandarua County was slightly similar with that of Kasipul
Constituency as it was revealed that legislature approves the overall CDF budget and may set
parameters for its expenditure and the greatest proportion of the CDF allocation should be spent
on development projects. It was also revealed that CDF funds can only be allocated to a defined,
auditable phase, unit or element of a given project as well as Individual legislators or their
committees have a free hand from a constitutional perspective, to allocate CDF funds to projects.
Lastly, they found out that once funds are allocated to a given project, they cannot be reallocated
or diverted to another project in the same financial year. However, it was difficult of apply these
finding to Kasipul Constituency because of methodology limitations as it was conducted at
county level
Further Mburu and Muturi (2016) determined that Project Funding was the major constraint as
the majority of respondents indicated that it was the single major factor that caused timely
completion of constituency development fund financed projects - case of water supply projects in
Kinangop constituency. The findings show that most respondents indicated that the disbursement
of CDF funds was not timely. The findings also showed that only a small majority at agreed that
projects budgets were well utilized. Additionally, the research determined that only a slight
majority of respondents showed that Fund allocation process was not effective as opposed to
45% who indicated to the contrary. Therefore, results show a positive coefficient of project
financing on project completion. This indicated that improved project financing would also lead
to improvement in timely completion of projects.
5.4 Contribution of stakeholder participation on effective management of Constituency
Development Funded projects
Effective decentralization and democratic local governance are advanced in tandem through the
creation of knowledge for all to be aware of the systems in place through proper participation.
Poor performance and failure of these funds can be attributed to poor participation by community
members and fund managers of their roles and responsibilities in the governance of funds. On the
other hand, increased participation has its benefits in community empowerment while results
have also indicated over participation in project management lead to delay in project delivery
and cost overrun.
Therefore, the second objective of the study was to establish the contribution of stakeholder
participation on effective management of Constituency Development Funded projects.
Stakeholder participation was measured by level and magnitude of participation, structures of
participation, and forms of participation and frequency of participation. The effectiveness of the
stakeholder participation was also sought. Respondents had been asked to indicate the extent to
which they agreed on these dimensions. To achieve objective two, it was hypothesized that there
is no significant relationship between stakeholder participation and effective management of
CDF funded projects.
It was found that most of the beneficiaries participated during identification and commissioning
of CDF projects. Few of them participated in planning, allocation, implementation, monitoring
and evaluation. This fact was also supported by results obtained from FGDs and interview with
government officials that the participation of citizen is limited to identification and
commissioning of CDF funded projects. Identification and commissioning was done mainly for
public relation and also for certain politicians to be associated with development. Therefore, the
effectiveness of these levels of participation was not up to standard. The government officials
indicated that citizen needs to participate in all level of project management which has not been
achieved with CDF projects according to various CDF Acts.
Monitoring and evaluation which increasing citizen satisfaction and owning of the projects was
least participated. However, results from the project managers/contractors and CDF committee
members revealed that there was some participation of citizens in all stages of project
management using various forms which are either direct or indirect. On other hand, majority of
the beneficiaries were unaware of existence of a complaint system in case the CDF projects are
not managed effectively. Thus, further implies even though stakeholders participate in the
management, they are unable to influence effective management of CDF funded projects as they
cannot get the wrong to be done it a right manner through existing regulatory frameworks.
The results from project manager/contractors and CDF committee members revealed that
stakeholder participation was done according to law. It was revealed that different forms of
identification and forms of participation are used. Most of the project managers/contractors and
CDF committee members revealed that they identified participation through nomination although
the beneficiaries indicated that appointment was common method of identification of
participants. According to the beneficiaries, appointment is not effective as people appointed are
close associates of the CDF committee members and project managers/contractors. It was
revealed that compromising an appointee is easy than elected participants. It was also revealed
that majority of participation was indirect through representation in various groups such as youth
and women, people with disability and other interested groups.
Sampled beneficiaries rate participation level lower than project managers/contractors and CDF
committee members. Participation, which is a collective responsibility for all stakeholders,
enhances better utilization of resources as it plays an oversight role. The Government officials
revealed that it’s difficult for politicians and CDF committee members to play oversight role as
some of them have influence on the CDF projects. This leaves other stakeholder to ensure
projects are managed according to stated terms and conditions. The frequency of stakeholder
participation was found to be moderate amongst the beneficiaries and good amongst project
managers/contractors and CDF committee members. This was supported from FGDs and
interview results where some projects have been undertaken without citizen participation yet
they are required to benefit the locals.
The findings also revealed that there is low awareness on stakeholder participation something
which has been blamed on CDF committee which is responsible for implementation of citizen
participation according to the CDF Acts and regulatory framework. The CDF funded project
beneficiaries indicated that some of them are unaware if they are to participate in the
identification, implementation, monitoring and evaluation of the projects. However, the CDF
Committee members revealed that in some cases, there are inadequate platforms to pass
information on when participation is to take place.
Further, both Project Managers/Contractors and CDF committee members indicated some
projects would require special time of stakeholder participation and therefore, they prefer to
nominate stakeholders who may add value to the projects. The FGD results also revealed that
PMC said that that they do value community participation but for things to move on it is not
always the case that local community should take part since it is not feasible. These sentiments
are just but a mere reflection of the extent to which it is a vivid and valid to allege that CDFC
and PMCs s are hypocritical in their undertakings in that, on paper they claim to establish
mechanisms that support positive and effective community engagement yet on the ground the
playbook changes.
Before testing the hypothesis, a correlation analysis was conducted to determine the strength and
direction of the relationship between the dimensions of stakeholder participation and the
effective of CDF project management. The results of the correlation analysis indicated that
relationship between the different dimensions of stakeholder participation and effective
management of project was positive and statistically significant. The composite mean of the
stakeholder participation dimensions was found to have a moderate and significant positive
relationship with effective management of Constituency Development Funded projects.
From the SEM analysis, it was found that stakeholder participation had a statistically significant
relationship on effective management of Constituency Development Funded projects. It was also
found that an increase in stakeholder participation on its own by one unit would result to
significant increase in effective management of Constituency Development Funded projects by
0.316 units holding other factors constant. Hence, the second null hypothesis was rejected as
there was sufficient evidence to suggest that there is significant relationship between stakeholder
participation and effective management of CDF funded projects.
The study also revealed that the application of regulatory frameworks such as CDF Acts would
have no moderating effect on the contribution of stakeholder participation on effective
management of CDF funded projects. The interaction between stakeholder participation showed
no significant effect on effective management of CDF funded projects.
From the findings, it can be deduced that level of stakeholder participation in the management of
CDF funded projects differs. Overall the moderate level of participation by stakeholders can be
attributed to effective management of CDF funded projects in Kasipul Constituency as compared
to other Constituencies in Kenya. It is paramount to state that CDF funded projects are people
driven and therefore participation of stakeholders at local level has significant effect in their
outcome. This implies that level of participation in the project life cycle, forms of participation
and identification of stakeholder to participate in project management has an influence on
effective management of CDF funded projects. As such, the effectiveness of CDF funded
projects depends on the structure in place to enhance participation and proper identification of
stakeholder to participate in project management
The findings of this study agree and disagree with various past studies in stakeholder
participation. This study indicated CDF committee member viewed the level of participation was
high to have positive influence on effective management of CDF funded projects. This is
contrary to Nyaguthii and Oyugi (2013) found that most of Mwea residents do not participate in
management of Community Development Fund projects, leading to failure in implementation.
These results imply that the community members were not involved in evaluation of CDF
projects because if they were involved most of them would have been satisfied with the outcome.
Gikonyo (2015) also found out that citizen participation has been low in CDF projects in Nakuru
Town Constituency but not as low as compared to results obtained in this study. Kemei (2015)
found out that only 43.5% of community members participated in CDF projects identification,
12.5% participated in project design and planning, 47.7% were involved in CDF project
implementation, while only 6.5% were involved in monitoring and evaluation processes in
Tinderet Constituency, Nandi County, Kenya.
From the findings of this study, it can be noted that participation is not an issue but the forms,
level and structure of participation influence project management outcome. This has been
supported by various past studies on stakeholder participation and effective management of CDF
funded projects. Adan (2012) found that CDFC, PMC and government officials’ role in project
implementation contributed most to project performance followed by CDFC, PMC and
government officials’ role in monitoring and evaluation, then CDFC, PMC and government
officials’ role in project planning while CDFC, PMC and government officials’ role in projects
identification had the least influence on project performance in Isiolo North Constituency.
Scholars in various studies have associated participation with positive project outcomes. This
implies that increase in stakeholder participation would result to increase in effective
management of CDF funded projects. Miano (2016) found that increase in stakeholder
participation as explained by level of awareness, political factors, level of education and
demographic characteristics would result to effective management of CDF projects in Mathira
Constituency in Nyeri County.
Ngondo (2014) also found that in Kanyekini Ward –Kirinyaga County community participation
in project management process had significant influence on timely completion of CDF projects.
The only weakness of the study is that it focused on timely completion of CDF projects and
methodological weakness as the study was carried in ward instead at constituency level.
However, the study finally concluded that participatory project implementation has the highest
effect on timely completion of CDF projects, followed by participatory projects identification,
while participatory project monitoring and evaluation has the lowest effect on the timely
completion of CDF projects in Kanyekini Ward, Kirinyaga County.
This study has found out that the level of participation especially during identification,
monitoring and evaluation are vital for citizen satisfaction. CDF projects ought to serve the local
community and therefore, fully participation is required to achieve this objective. Proper
governance is required to ensure that structures of participation in place are able to accord
citizens with project outcome satisfaction. This is echoed by Abdi (2010) who found out that the
constituents have no clarity on the roles of stakeholders on management of CDF and selection of
the CDF committee members resulting to poor performance and in some cases a complete failure
of the projects due to prioritization on of projects and exclusion in Dujis constituency.
There is need to balance between direct and indirect participation and where indirect
participation is utilized citizens should be consulted and given a chance to select who are
comfortable to represent them in the management of CDF projects. Therefore, the governance
issues cannot be overlooked as far as stakeholder participation is concerned in the management
of CDF funded projects since the structure of participation ensures there is proper governance of
public resources.
In Senegal, Varis, Rahaman and Stucki (2008) found out that the highest project output was
attainable through extensive stakeholders’ participation in project activities. This implies that
comprehensive stakeholder participation enhances CDF project management. Stakeholder
participation has also been associated with project sustainability and user satisfaction. In
Uganda, Chowns (2014) observed that some projects were readily vandalized by the intended
project beneficiaries, because such were initiated with minimum stakeholder participation.
Therefore, stakeholder participation creates ownership attitude since without developing a
feeling of ownership, the hitherto project beneficiaries turn into project enemies.
On form of participations, the findings agree with Otundo (2015) who indicated that the form of
community participation has significant on the project implementation. He indicated that for
passive/indirect participation, the community do not directly involve with the management of
project however, they are consistently updated on the progress of the projects. This entails
informing them what they are going or what has already been done therefore, the community do
not intervene with the activities of the projects and they maintain a distance. Interactive/direct
participation occurs when there is a joint analysis and planning process amongst various
stakeholders so as to enhance existing structure and taking control of the development process.
Kibebe and Mwirigi (2014) in in Kimilili Constituency, Bungoma County indicated that the
implementation of CDF project depends on level of stakeholder participation. In their study they
found that there was poor prioritization of community needs by the management committees,
poor decision making as community members are sidelined, insufficient support from the
community members and illiteracy and low level of awareness among community members.
Ouma and Mburu (2017) concluded that stakeholders’ participation in project identification had
significant influence on project sustainability with strongest influence on sustainability element
of beneficiary ownership followed by outcome results and lastly on maintenance cost. This
engagement defined full participation. Secondly, stakeholders’ participation in project planning
significantly influenced project sustainability. This this was by actively participating in work
planning, risk management and communication planning activities. Project planning had a strong
influence on sustainability elements of beneficiary ownership followed by outcome results and
lastly on maintenance cost respectively. This was due to high participation in all the three
sustainability elements scoring fair influence. Thirdly, stakeholders’ participation in project
monitoring and control had the highest influence amongst all the predictor variables. This was by
actively participating in project monitoring and control elements of Time management; cost
management and quality management roles respectively. There was prompted by community
demand for accountability and transparency in the CDF initiatives.
It was revealed that there is collective responsibility in the management of CDF projects in
Kasipul Constituency and the structure in place are at moderate in enhancing participation.
Fisher et al. (2017) observed that beneficiary communities were not sufficiently involved in the
management of CDF projects funds creating room for lope holes in management that affected the
performance of CDF projects financially and eventual project results. Lack of stakeholder
involvement was seen to have led to several cases of incomplete, substandard quality, irrelevant
projects in various constituencies in the country (Davidson, 2009).
Although the CDF Act of 2007 revised in 2013 mandates that meetings and forums be held for
project selection and identified projects then submitted to the CDFC prior to transmission for
funding (Kerote 2007), the CDF principles of Kasipul Constituency seem to have not created a
friendly platform for the participation of all stakeholders to share in the vision in the
development of Constituency. It was revealed that participation in project team meetings helps in
selecting the most appropriate project to fit the needs of the constituency, allows all stakeholders
an opportunity to share their views on CDF projects and Facilitate better prioritizing of projects.
Stake holder involvement was seen in previous studies to be critical for assessment of needs as
achieved from informed group discussions and helps stakeholders clarify the magnitude of the
problems lay down and deliberations made in line with the resources available (Kerote 2007).
The members of each constituency are hence accorded the right to be active through the
implementation processes of these projects. The constituents are also expected to monitor the
projects and see to it that objectives of each project are met and resources allocated are rightly
distributed and used appropriately whilst the aspect of time is adhered to (CDF National
Management Committee, 2004). Few beneficiaries had knowledge on CDF implementation
process which should be communicated by the principles as their limitation was limited to
commissioning of completed projects.
Passia, (2004) and Gyorkos, (2003) note that project planners ought to incorporate a well-defined
monitoring and evaluation strategy within the overall project plan. The monitoring and
evaluation plan should include activities to be carried out to get feedback, people to be involved
in carrying out these activities, frequency of carrying out the activities, budget expectations for
activities and specific insights expected to be achieved from the monitoring and evaluation
feedback. Evaluation is resourceful in building knowledge and enhancing favorable
implementation
5.5 The role of political intervention on effective management of Constituency Development
Funded projects
Devolution of resource to the decentralized unit of management is seen as one of the positive
move by the central authorities but there is a concern about the organizational and management
structure of the CDF since politicians (MPs) control the project formulation and disbursement of
the finance. CDFs are viewed as politically-initiated projects. It is argued that it appears that they
are politically driven development initiatives. It has been observed that political influence has
considerable effect on projects evaluation and monitoring, projects identification and
implementation as well as stakeholder participation. These three premises are key to effective
management of CDF funded projects.
Therefore, the third objective of the study was to determine the role of political
intervention/influence on effective management of Constituency development Funded projects.
Political influence was measured by political will, political leadership and political commitment.
Respondents had been asked to indicate the extent to which they agreed on these dimensions. To
achieve objective three, it was hypothesized that there is no significant relationship between
political influence and effective management of CDF funded projects.
The results revealed that both local and national politics have a positive but insignificant
influence on CDF project management although majority of the respondents associated local
politics with CDF project management as compared to national politics. The beneficiaries
indicated that there was skewed distribution of CDF projects not only at the ward level but also
at the village level. The same sentiments were shared by the government officials who also
indicated identifications of projects and their implementation was interfered with local political.
Also, CDF fund managers are at the discretion of current members of parliament (MPs) and the
MPs are comfortable working with a particular people who helped them during the campaign.
It was also revealed that some areas have benefitted a lot from CDF projects due to political
influence. This notion was not supported adequately by the CDF committee members who
indicated that although local politics have influence the national politics has also affected the
release of funds on time which greatly affects the management of CDF projects. The
Government officials also indicated that politicians have influenced on the award of tenders to
project contractors whereby certain contractors have undertaken more contracts as compared to
other yet they are pre-qualified.
The results indicated that political influence has two sides of the coin as some areas have
benefitted a lot from political interference while other has suffered. In this regard, the response of
beneficiaries tended to skewed depending on the relationship between the politicians and the
community of the beneficiaries. In nutshell, the influence of political has great impact on the
project management effectiveness. The sampled beneficiaries rated highly the influence of
political influence on CDF projects management. The general observation of the beneficiaries is
that politics plays great role in the CDF project management and it was found to influence
identification, allocation, participation and technical capacity.
It was found that for a project to be successfully completed according to set objectives, political
will is required otherwise, the project may take long to complete or abandoned especially when
new MP is elected. This continuation of project poses serious governance issue although there
are regulations that govern influence of politicians in the management of projects. Further,
conflict of interest was also identified in the management of the CDF projects as politicians
would want to prioritize projects that benefit them instead of benefiting the community. This can
be loosely associated with influence of politician in stakeholder participation something which
CDF Acts have clearly stated the role of MP.
The public has also raised questions about governance and political interference of the fund;
some members of the CDFC are ill informed about project management and therefore put in
doubt their ability to manage and govern the CDF funded projects effectively. The results from
FGD and interview revealed that politicians prefer to move projects in areas where they can
maximum gain both in terms of votes and financial support. The beneficiaries have been used as
voting machines while the contractors as source of funds to finance their campaign. In this case,
the CDF has been used as give and take basis whereby if you cannot give votes do not expect
projects.
Another governance concern that has been related with political influence in the management of
CDF funded projects is the commitment of politicians towards the kids. The CDF is managed by
the National Government and up to date there is no MP who has been held accountable on the
mismanagement of the fund or why the constituency is performing badly. This has resulted to
ineffective management of CDF funded projects due to existing loop holes in CDF Acts. A good
example in this study is where an MP can ignore projects of previous parliament or where an MP
has power to transfer government officials who are dealing with management of CDF projects at
constituency level.
Before testing the hypothesis, a correlation analysis was conducted to determine the strength and
direction of the relationship between the dimensions of political influence and the effective of
CDF project management. The results of the correlation analysis indicated that relationship
between the political influence and effective management of project was positive and statistically
significant. On the other hand, the composite mean of the political influence dimensions was
found to have a moderate and significant positive relationship with effective management of
Constituency development Funded projects.
However, from the SEM analysis, it was also found that political influence has no significant
effective management of Constituency development Funded projects. This implies that the
positive relationship between political influence and effective management of CDF projects is
not a direct linear causal relationship. From the descriptive results, some of the respondents who
have benefitted from CDF funded projects were quick to point that their politicians do not
influence management of CDF projects while those who were disadvantage thought otherwise.
On introduction of the moderating variable legal frameworks and the interaction between
political influence and legal frameworks, the causal relationship of political influence on
effective project management remains insignificant. The interaction term was also insignificant
confirming that legal frameworks have no moderating effect on the relationship between political
influence on effective project management. Hence the application of regulatory frameworks such
as CDF Acts has no significant moderation on the effect of political influence on effective
management of CDF funded projects. It can be postulated that political influence can have some
positive role in the effective management of CDF project if they operate under more stringent
regulations and laws.
According to the law, politicians are required to play an oversight role in the management of
CDF projects. This implies that they are required to make sure that project stages are done in
accordance to the law and ensure equity distribution of projects within the constituency.
However, this has not been achieved raising serious governance concern on the role of politicians
in the management of CDF projects. It was found that even though the politician can influence
distribution of projects, their role in selection of contractors can compromise the quality of the
projects results to low quality projects.
The politicians have also been found to thwart their oversight role by avoiding monitoring and
evaluation role to those contractors who financed them during campaign period. This has
affected project sustainability leading to misuse of tax payers as low-quality project has been
undertaken. Even though it’s difficult to disassociate politicians from CDF funded projects since
it’s awarded at the constituency, serious governance structure concerns need to be addressed on
the role of the politicians in the management of the projects so that politicians are been seen as
symbol of equity.
These findings support and contradict various findings of other studies. Ntuala (2010) conducted
a study on factors affecting the implementation of CDF funded projects in Tigania East
constituency and recommended that a regulation to be enforced to block the involvement of the
politicians in the activities of CDF implementation. The study concluded that their role should be
limited to legislative and oversight. Therefore, linking the reviewed literature with the study
findings on the issue of the influence of politics on the CDF funded projects showed that politics
had negatively influenced effective implementation of the CDF funded projects. Somehow
through the presence of CDF members in the CDF PMC members there was some
communication on how politics influenced the nomination of most of the CDF PMC members
into the committees.
This finding is supported by Ashaye (2010) who affirms that, political goodwill is the key to
successful institutional projects development and implementation; conditions and participatory
frameworks alone cannot render government bodies fully responsible. Although the findings
support political will in CDF managed projects, Kenyan authors have established doubts in the
political will for example Wabwire (2010) indicated that there is lack of political will, to
effectively disseminate information about CDF to the local people, by for instance organizing
meetings with members of the public in the constituency.
On the other hand, Musamba et al. (2013) affirmed by the fact that the politicians can literally
manipulate CDF as in most cases they determine which projects to fund in irrespective of the
community priority and principle of checks and balances. Kimenyi (2015) further affirmed by
the fact that as long as politicians have major stake in constituency development fund projects,
they will use it for political survival through skewed choices. Most the local people will not be
aware of fund embezzlement and in cases where they are aware they cannot have the audacity to
question the politicians or right channel to lodge their complaint.
Murray (2011) asserted that elected politicians always have interest on the CDF funded project in
their constituencies in bid to support their re-election in the next general election. This interest is
not genuine and legitimate as they after seeking approval for re-election. This has resulted to
conflict of interest between the constituents and the politicians as they make decision on how and
when to spend public funds without consultations. CDF committee members are political
appointee by the MP and in some cases, it has been reported that MPs have overly influence on
the CDF committee so as to use them in rubberstamping CDF projects. There have been
concerns that only selected persons close to MP have involved in the selection of projects to be
implemented under CDF.
A research by Wambugu (2008), in Dagoretti Constituency reveals that there is political
intervention on the implementation of CDF projects which leads to underperforming of CDF
projects in the period of study. Other authors have cited negative interventions for example
Malala and Ndolo (2014) who examined in detail factors that affect the performance of
Constituency Development Fund (CDF) projects in Kenya. The results revealed that political
interventions directly affect CDF project performance which in turn has resulted into CDF
projects in Kikuyu Constituency being rated by the public (as the evaluators) as being behind
schedule (88 % percent of projects), with a paltry 12 % of projects being on schedule and no
project was rated as being ahead of schedule (0 %).
Kamau and Muturi (2015) concluded that legislators are not free to employ CDF funds to woo
their political cronies in Nyandarua County unlike in Kasipul Constituency where some of the
respondents indicated that some regions have benefitted more due to affiliation with political
leaders especially member of parliament. In addition, the study concluded that, interference of
CDF projects by the members of the National Assembly is likely to negate the intended benefits
of these projects. Members of the National Assembly are not accorded too many powers in the
CDF governance structure in Nyandarua County. It was deduced that though political interest is
significant in CDF projects, their impact on successful completion of those projects is quite
marginal. However, it was difficult of apply these finding to Kasipul as it was carried out at
county level.
5.6 The influence of Technical capacity on effective management of Constituency
Development Funded projects
Understanding of project life cycle plays a major role on how to handle CDF funded projects.
This inadequacy in understanding limits the ability to extract and disseminate accurate and
useful. The first step in project management is to determine the available staff experience within
the team, partner organizations, target communities and any other potential participants in the
management with a view to identifying any gaps between the project needs and available
personnel, which will inform the need for capacity building so as to enhance their technical
capacity to undertake the exercise.
Therefore, the fourth objective of the study was to establish the influence of technical capacity
on effective management of Constituency Development Funded projects. Technical Capacity was
measured by knowledge, skills, competence and experience. Respondents had been asked to
indicate the extent to which they agreed on these technical capacity dimensions. To achieve
objective four, it was hypothesized that there is no significant relationship between technical
capacity and effective management of CDF funded projects.
In effective project management, technical capacity is important not only in the projects but also
on the budgetary allocation, monitoring and evaluation and decision-making capabilities bearing
in mind that CDF projects are public projects and there are various stakeholders with different
interests. The sampled beneficiaries indicated that there somehow good technical capacity in the
management of CDF projects; the same view was shared by project managers/contractors while
CDF committee members indicated it was good.
The beneficiaries revealed that the quality of work done by the CDF was good as a results
sourcing expertise especially in the construction of classroom. This was also linked to sufficient
technical capacity among human resources available in the management of CDF projects. As
expected, the project managers/contractors and CDF committee members revealed that they have
technical capacity in terms of expertise, skills, knowledge and experience acquired through
effective training programs and sourcing of highly qualified employees.
The results from the FGDs and Interviews also supported the findings although the government
officials noted that few projects have been awarded to contractors who have no experience due to
political influence. The beneficiaries also indicated that some of the staff deployments have not
been done according to academic qualification which cast doubt on their ability to monitor and
evaluate projects. The government officials hinted that some projects such as schools and
hospitals have been undertaken with the required technical capacity since their collapse can
results to injury or/and deaths. However, he noted that there is technical committee which is
supposed evaluate the technical capacity of contractors which leaves leeway to be abused by the
politicians in the award of contracts.
Before testing the hypothesis, a correlation analysis was conducted to determine the strength and
direction of the relationship between technical Capacity and the effective management of CDF
funded project. The results of the correlation analysis indicated that relationship between
technical capacity and effective management of project was positive and statistically significant.
The composite mean of the technical capacity dimensions was found to have a strong and
significant positive relationship with effective management of Constituency development Funded
projects. Finally, from SEM analysis, technical Capacity was found to have no significant direct
effect on effective management of CDF projects.
The estimation showed that the negative causal effect (-0.239) of technical capacity technical
capacity has on effective project management had no statistical significance. However, on
introduction of regulatory framework and the interaction terms between technical capacity and
regulatory frameworks, the model showed a significant change on the causal effect of capacity
technical capacity on effective project management. This was deduced based on moth the
structural equation model and the moderated multiple regression model (MMR). The MMR
showed that the interaction term has a significant negative effect of -.098 on the relationship
between technical capacity and effective management of CDF projects.
From the findings it can be deduced that technical capacity has a negative influence on effective
management of Constituency development Funded projects. Technical capacity in the literature
has been identified to have an influence on project outcome. However, some of these studies
have investigated technical capacity from the project management point of view leaving a
significant gap within the governance domain. This study has found that regardless of the fact
that it has a negative effect, the presence or the absence of technical capacity does not in itself
influence CDF project management outcome, rather other factors play significant role.
Some of these factors have been the ability of the management to use its competent and skilled
staff in appropriate manner so as to get maximum benefit from the pool. CDF projects been a
political brainchild is bound to suffer from reward in the award of tenders and opportunities
especially during monitoring and evaluation. The project management outcome is measured by
user satisfaction which is within the domain of meeting set objectives. This study concurs with
the findings obtained by Oyalo (2015) technical capacity is the genesis of user satisfaction and
this requires that all governance issue relating to technical capacity is adhered to. As it was noted
few projects have not been done according to user satisfaction and their sustainability has cast
doubt on the technical capacity of the contractors. This indicates that there are governance gaps
in the management of the CDF projects which need to be addressed.
Findings on technical capacity are supported by Wanjiru (2013) study which sought to find out
influence of technical capacity on performance of CDF projects in Kenya. The study on technical
capacity was shown to be crucial for coordinating various activities as well as different
stakeholders which influenced performance of CDF projects. This finding is in tandem with
Young (2007) who found out that training in skills and knowledge of basic project management
should be emphasized in order to steer projects effectively. On the other hand, Kipsaina (2010)
concluded that project implemented’ knowledge, skill and attitude influenced performance CDF
projects in Emgwcn constituency and that project implementers need to be empowered with the
right skills, altitude and knowledge in regard to monitoring and evaluation.
However, our findings differed with the study finding of Kaliba (2013) who found out that there
is a high influence of the role of technical expertise on utilization of CDF funds at 0.683 per unit
increase in utilization of the funds. Also, Tero (2014) recommended that implementation team
needs to be trained, educated and supported to enhance their competency and delivery. He also
recommended that human resource provision should utilize individuals to effectively achieve
results.
Nganga (2011) found out that technical incapacities of the Constituency Development Fund
committees and the Project Management Committees influence factors influencing cost-
effectiveness of Constituency Development Fund in Kaloleni Constituency whereas Mwangi et
al. (2015) found that increase in one unit of technical competency of the monitoring and
evaluation team accounted for 28% increase in effectiveness of CDF projects in Laikipia West
constituency.
Kibebe and Mwirigi (2014) in in Kimilili Constituency, Bungoma County indicated that the
implementation of CDF project depends on managerial factors such as knowledge, skills and
staff competence. They found that there was inadequate monitoring and evaluation of the
projects initiated at community level, decision making concerning the project is inefficient and
lack of commitment of the CDF management committees. However, there was skills and
experience of the project management committee and the Knowledge-ability of the management
committee.
The findings also established that CDF trainings help improve problem solving skills, CDF
trainings provide insight on a better future for CDF, CDF trainings open up members to being
more adoptive to change, trainings provide clarity on each team players role, trainings enhance
team skills, trainings help in enhancing creativity and innovation in handling CDF projects,
trainings aid in coming to conclusions on better policies for the CDF kitty, trainings enhance
more productivity, trainings educate members on better use of available resources and trainings
make us better managers.
Sugal (2017) found that management training positively affects the implementation of projects,
i.e. increase in technical capacity increases the implementation of projects in Balambala
Constituency. It was found that CDF trainings help provide clarity on each team players role
which builds on the quality of the team interactions, a factor which was well appreciated by the
CDF officers. This was also reveal in Kasipul constituency where human resource on the CDF
project should be given clear job allocation and designation befitting their expertise, if they are
inadequate then training for the requisite skills should arranged.
5.7 Moderating influence of Regulatory framework on the relationship between the
determinants Effective management of CDF Projects
The results revealed that regulatory framework had a significant moderating influence on the
relationship between the studied determinants and effective management of CDF projects in
Kasipul Constituency. The results indicated that beneficiaries are less conversant with rules and
regulation that govern CDF management as compared to project managers/contractors and CDF
Committee. This implies that, if beneficiaries are not aware of the regulations that ensure prudent
management of CDF funds, then they may not make significant contributions in questioning
improper management. Similarly, they may not be aware of the channels to follow to ensure
accountability of fund utilization as well as the process of implementation.
The descriptive results revealed that there are laws and regulations in the project financing,
technical capacity, stakeholder participation and political influence. For example, the CDF Act
(2015) spells out the role of political leaders in the management of the fund and CDF projects.
However, majority of the respondents indicated that while there were clear policies and
procedures on financial guidelines, they were not always followed to the letter.
The moderating effect of regulatory frameworks was assessed using SEM and moderated
multiple regression (MMR). The MMR revealed that addition of the interaction terms between
the determinants and regulatory frameworks to the model significantly improves the model as
shown by the significant change in R-square. The significance of the R-square change was
portrayed by the p-value of the change in F-statistic due to the introduction of the interaction
terms. The results showed that there was a 0.012 change in the R-square after adding the
interactions. This showed that adding the interaction terms yielded a 1.2% increase in the
variation of effective project management explained by the model which implied a significant
moderating effect. Both SEM and the MMR further showed that regulatory frameworks
particularly had significant moderating effect on the causal relationship that effective project
management has with project financing and that it has with technological capacity. It was
however revealed that regulatory framework had no significant effect on the relationship that
effective project management has with stakeholder participation and that it has with political
influence.
CDF lacks its own structure for disclosure and accountability, since these are handled by central
government officials. The Kenyan Public Service and especially procurement and supplies
departments have often been accused of inefficiency and ineffectiveness. This was also identified
during FGDs where some of the respondents were unable to connect the cost of the CDF projects
especially classrooms with the quality of completed works in Kasipul Constituency. This is
worsened by the near complete absence of civic participation in the use of the fund. This
notwithstanding, the introduction of CDF was not accompanied by additional human resources
hence it can be expected that the capability of accounting officers is far much stretched to be
effective. Without such effectiveness, unethical practices are likely to pass unnoticed in as far as
the utilization of the fund is concerned thereby hindering the objective of CDF as form of
spurring local development in most part of the country.
The CDF Act does not make provision for independent auditors and their rotation which is useful
transparency and accountability. It was established by project managers that no audit has been
carried on fund utilizations. However, audit can only be political motivated which negate the
essence of audit which is required to be carried out regularly. Further, it was also noted that
building and construction projects have not been audit upon completion. Even though there have
been cases of collapse, it was vital to audit such project for safety of the occupants. Best practice
suggests organizations should be audited externally by professionals who should also be
regularly rotated to ensure independence of audit reports. The fact that the same County
Development Office, which is involved in implementation of projects audits CDF utilization
implies the risk for familiarity, complacency and consequently corruption and ineffectiveness of
the programme, noble as it may be. In addition, passive participation of the grassroots
communities whose role is partly defined by the CDF Act means poor monitoring of the fund
utilization, throwing to irrelevance the idea behind the fund-decentralization and devolution of
power.
Even the regulations and laws governing CDF project management are clear on citizen
participation, it was not by the study that the regulation are silent on holding some of the
stakeholders accountable. CDF structure does not allow for effective citizens participation in
holding project leaders to account. Although CDF is a form of decentralization, this is only in
part since expenditure is not linked to local revenue sources or fiscal effort. Partial
decentralization, on the other hand, is likely to minimize citizens’ interest in monitoring the use
of funds since they might consider the funds as free (Kimenyi, 2005). Since the Kenyan
citizenship is not known for critically holding their leaders to account on the manner of use of
taxes, it is unlikely they can do the same in the use of CDF funds. Consequently, power is yet to
devolve from the center to the margin, the object of the CDF idea.
On technical competence, The CDF Act is silent on professional skills and competences for
Constituency Development Committee (CDC) members and the project manager, which implies
a significant lack of structure for sound management including planning, implementation,
monitoring and evaluation of development projects. It is assumed that other laws and regulation
are in place to guide human resource management in the management of CDF. It can be expected
that CDF members who lack relevant skills and competences are more likely to be manipulated
to participate or turn a blind eye to malpractices. Mapesa and Kibua (2006) note, that CDF
members are “used as rubber stamps” for predetermined decisions whether they understand them
or not. As such, politicians and central government officials at the district headquarters are left as
principal decision-makers to the disadvantage of the beneficiaries.
The regulations and rules on political influence were also found to be inadequate for effective
management of CDF projects. CDF is simultaneously an organizational and a political structure,
which effectively means conflict between organizational and political goals. With clear
regulations and laws, the political interference is inevitable as identified by some of the project
managers who indicated that monitoring and evaluation is grossly violated by members of
parliament. The organizational goal concerns uplifting social welfare but there is the likelihood
that the area Member of Parliament (MP) would often support, and influence the support of,
projects that ensure maximum political returns. In this respect, the CDF has the potential for
perpetuating unilateral leadership and similarly presents a forum where political competition can
be played out. The sole role of the MP availed by the CDF Act, gives sweeping powers to the
incumbent to appoint the management committee.
According to Mwenzwa (2015) CDF members by virtue of being in-charge of public revenue in
form of Constituencies Development Fund become public servants. Therefore, they are
accountable to the public regarding the way the fund is utilized in meeting public needs.
Consequently, like other mainstream public servants they need to be inducted into government
financial regulations, sign performance contracts and set time-bound targets so that the public
can have basis on which to hold them accountable. On the other hand, civil society need to be
empowered through training as well as advocacy so as to keep monitoring utilization of public
funds as well as holding public servants accountable.
According to Nafula (2015) revealed that most of the projects in the Kiminini constituency were
initiated by the area MP. Though they seemed to be urgent, they were not a priority for the school
community. Effective monitoring and evaluation mechanism greatly contributed to stalling of the
established projects. She further indicated that there are no defined structures to hold those in
charge of the projects accountable. Since this is not provided for clearly in the CDF act. Some of
the constituents felt that some locations had good rapport with the area MP and that is why most
of the projects were initiated in their locations. Therefore, the government should establish a
legal and regulatory framework to govern the operations of CDF projects at constituency level,
thus promoting accountability and transparency in the management of the said projects.
According, Gathoni and Ngugi (2016) insufficient regulatory environment greatly affects the
ability to spur performance of CDF funded projects. In their study carried out in Kiambu County,
the inadequacy of regulations has impacted negatively on the performance of CDF projects
which mirror the findings of this study. Some of the CDF project regulations are not clear. The
CDF Act has been revised so many times and as a result it a challenge to track some of the
changes. The policies and procedures should be updated as frequent as possible. The only
shortcoming of their study was the measure of regulatory environment was not clear.
5.7 Summary of Research Objectives, Hypotheses, Findings and Verdict
The summary of research objectives, hypothesis, findings and conclusions is presented in table
5.1.
Table 5.1 Summary of Research Objectives, Hypotheses, Findings and VerdictObjective Hypothesis Findings Verdict
To assess the influence of projects financing on effective management of CDF funded projects
Projects financing has nosignificant influence on effective management of CDF funded projects.
The findings established that projects financing significantly influencedeffective management of CDF funded projectspositively
H01 was Rejected
To establish the contribution of stakeholder participation on effective management of CDF funded projects
Stakeholder participationhas no significant influence on effective management of CDF funded projects.
The findings established that stakeholders have a significant and positive contribution to effective management of CDF funded projects
H02 was Rejected
To determine the role of political influence on effective management of CDF funded projects
Political influence has nosignificant influence effective management of CDF funded projects.
The findings established that political influence no significant role in the effective management of CDF funded projects
H03 was Accepted
To establish the influence of technical capacity on effective management of CDF funded projects
Technical capacity has no significant influence effective management of CDF funded projects.
The findings established that technical capacity no significant influence oneffective management of CDF funded projects
H04 was Accepted
The results in Table 5.1 show that the findings indicated a statistically significant positive
relationship between projects financing and effective management of CDF funded projects. This
finding led to rejection of the null hypothesis of objective one of the study. The results on the
other hand show a statistically significant relationship between stakeholder participation and
effective management of CDF funded projects. This led also to rejection of the null hypothesis of
objective two.
The study also established that political intervention has an insignificant influence on the
effective management of CDF funded projects. This implied that we failed to reject the null
hypothesis of objective three of the study. Finally, test on hypothesis four established that
technical capacity has non-significant relationship with effective management of CDF funded
projects. This led to failure of rejecting the null hypothesis.
CHAPTER SIX
6.0 CONCLUSION AND RECOMMENDATIONS
6.1 Introduction
This chapter provides conclusions based on the findings and discussions in the previous chapters.
The conclusions are derived by relating the findings to the achievement of the four objectives of
the study as well as the hypotheses that had been formulated for the study. The chapter also
highlights the contributions of the study to theory, methodology, policy and practice in both
governance and project management. Finally, the chapter outlines proposed areas of future
research.
6.2 Conclusions
The main objective of the study was to investigate the determinants of effective management of
CDF funded projects in Kasipul Constituency, Homa Bay County, Kenya. Four specific
objectives were derived from the main study objective. To achieve the specific objectives, four
hypotheses were formulated based on a review of literature and empirical studies. The
hypotheses were subjected to observed index matrix analysis and path analysis. Based on the
findings of the determinants of effective CDF project management, the study came up with the
following conclusions;
Basing on the first objective of the study, the hypothesis was tested in which the null hypothesis
H01 rejected and a conclusion drawn that project financing significantly influence the effective
management of Constituency Development Funded projects in Kasipul constituency, Homa Bay
County, Kenya. Adequacy of fund allocation to projects, timely disbursement of the funds,
auditing process, transparency and accountability positively and significantly influenced quality
standards and improved user satisfaction levels. It has been noted that delay in disbursement has
resulted to cost overrun due to inflation, foreign exchange rate, fixed cost which are not catered
during project valuation. Kasipul Constituency has been found to allocate fund spreading for
over more than one financial years. Even though the motive is explained, the effectiveness is
compromised as funded projects take long time complete which is against citizen satisfaction.
Further to the conclusion, the study notes that the significant influence that project financing has
on effective management of CDF project is moderated by regulatory frameworks.
Following the second objective of the study, which was to determine the contribution of
stakeholder’s participation on effective management of Constituency Development Funded
projects? The null hypothesis linked to this objective was also rejected and a conclusion drawn
that stakeholder’s participation has positive and significant contribution to effective management
of Constituency Development Funded projects. The study concludes that citizens who are viewed
as principals and their elected representatives as agents, at the local level provides for a better
means (in the form of information) for responsiveness. Apart from enhancing accountability,
stakeholders also increase effectiveness of fund management through transparency on the use of
public resources.
In particular, management of CDF project is a collective of responsibility of all participants
which ensures that public resources are utilized to the benefit of the citizens. Therefore,
appropriate structures of stakeholders’ participation which include level, form of identification
and form of participation have effective contribution to the management of CDF funded projects.
It was found that most of the constituents are only involved during project identification and
project commissioning. There is inadequate participation especially for monitoring and
evaluation of projects undertaken at the constituency which are the main stages of project
management that determine its effectiveness. However, it was revealed that funds allocated to
suggest projects do not take care of extensive citizen participation. As such, stakeholders are only
summoned during ground opening ceremony mostly for the purpose of public relation and
political gains.
As per the third objective, the findings revealed that political influence have a positive role but
do not have significant effect on the effective management of Constituency development Funded
projects. In practice, CDF is awarded at constituency level for devolved development;
nevertheless, it is not free from political manipulations as descriptively demonstrated. From the
findings, it is evident that there is wide problem of political accountability in terms of allocation
of control rights in the context of incomplete contracts, where breaches of contract are
observable, though not verifiable in administrative or judicial review. Despite the fact that
political will to identify and implement projects; MPs oversight role and varying political
interests that exists, all these do not significantly affect the outcome of CDF projects. The study
concludes that political accountability in the constituency is poor as it is particularly affected by
the likelihood of corruption or capture by interest groups. While decentralized units may have
better local information and accountability pressure, they may be more vulnerable to capture by
local elites, who will then receive a disproportionate share of spending on public goods. For
example, there is a revelation from governance point of view that the CDFC is composed of
political cronies to the politicians, although they are qualified to be in the CDFC. For this reason,
the CDFC as well as PMCs don’t propagate projects the locals would wish to be funded but
rather propagate those projects politicians need for their own political reasons; funding for
projects is also lightly done leading majority of projects being in perpetual state of ‘ongoing’.
The study found out that political influence has a relationship with effective project financing
however, the null hypothesis on political influence was accepted and a conclusion drawn that
political influence only have non-causal relationship with effective project management but has
no significant direct influence on management of CDF projects in Kasipul constituency, Homa
Bay County, Kenya. Regulatory frameworks were noted not to have any moderating effect on
this relationship.
For the last objective of the study, it was revealed that technical capacity has no significant
influence on effective management of Constituency Development Funded projects. The study
accepted the null hypothesis and drew a conclusion that there is no direct causal effect of
technical capacity on the effective management of CDF project. The study however noted that
introduction of legal frameworks significantly moderates this relationship causing a significant
negative causal relationship between technical capacity and effective project management. In
general, the study concludes that project implementation process at the constituency level is
extremely deficient, not always by design, but by the sheer dearth in technical capacity for
feasibility, design and costing knowledge. CDF projects vary in size and complexity as a result
technical capacity which include expertise, skills, experience and knowledge in certain project is
critical for it success. The findings imply that despite the transparency on awarding of the
contracts, the actual implementers may not be the same one that was actually awarded. This is
because, a project that is undertaken according to the required technical capacity would results to
user satisfaction, quality standards and set objectives.
From the joint contribution of the identified determinants on the management of CDF projects,
the study concluded that in presence of all determinants, project financing has highest significant
positive influence on the effective project management while stakeholder participation has the
least positive significant effect implying the contribution of stakeholders in project management
is minimal. Technical capacity and political influence however have no significant direct
influence on project management effectiveness as the other determinants.
Regulatory framework which was used as a moderating variable was also found to have a
significant moderating influence on the contribution of the determinants on effective
management of CDF projects. Considering specific determinants, regulatory frameworks was
found to moderate the influence of project financing and technical capacity on effective project
management. It was suggested that a project that is managed according to the existing
regulations on financial practices, stakeholder participation, technical requirements and political
influences would enhance its effective management. From the findings therefore, regulatory
framework never had any influence in terms of the direction or significance of the effects of the
key determinants under study.
6.3 Recommendation
The study provides suggestions or recommendations having in mind that for decentralization of
CDF to be really effective, there is a great need for serious attempts to change the existing
structures of power within communities and to improve the opportunities for participation and
voice and engaging the hitherto disadvantaged or disenfranchised in the political process as well
as those with technical incapacities to enable participation or implementation, The following
recommendations are drawn from the conclusion according to study objectives.
6.3.1 Project Financing
The study concluded that project financing influence effective management of the CDF funded
projects. The study recommends that there should be a clear financing framework that is focused
to allocation and disbursement of funds for approved projects with clear implementation plans to
achieve success in CDF project management. At the moment, the CDF Acts stipulate a minimum
of 2.5% of National budget to be allocated to CDF which is inadequate. The act can be amended
so that the amount allocated to each constituency is increased to 7.5% of the national budget to
cover all aspects of identified projects at the constituency. Further, there has been delay in
disbursement of fund from national government which spill over to constituency. This delay can
be overcome by enacting a law that would make it mandatory for national government to
disburse at particular dates in a given financial years thereby making the constituency make
proper arrangement on project financing with their contractors. Lastly, the CDF committee
should adopt a project financing model which would allow full allocation of project instead of
funding several projects at once. They would reduce overhead cost both of CDF committee and
for the contractors while at the same time delivering completed project within shortest time
possible
6.3.2 Stakeholder Participation
The study concluded that stakeholder participation influence effective project management and
therefore, increases in quality and quantity of stakeholder participation would results to effective
project management. Therefore, the study recommends a holistic involvement of all stakeholders
in all project cycles. Decentralization of decision-making to the lowest appropriate level is
crucial for all CDF projects management. This demand responsive approach includes key
principles such as the recognition of constituents in every location or sub location as principal
users and their inclusion by CDFC at the forefront of decision-making and management rather
than concentrating these functions at CDFC or constituency level. The involvement of all should
trickle down to the grassroots.
The recommendations made out of this study is that stakeholders whether influential or not be
involved in management of the CDF funded projects either directly or indirectly in all stages of
project management. In case where indirect participation is involved, the stakeholders should be
informed why and the form of selecting their representation should be open and justifiable.
Lastly, a system to curb mismanagement of CDF projects should also be put in place where
ordinary community members can go to raise their dissatisfaction and to report malpractices in
every phase of the projects life.
6.3.3 Political Influence
Political influence had mixed outcome on the effective management of CDF funded projects. We
found evidence to suggest that, projects that had the support of the political class for example
projects located in the support base had been completed in time compared to those that were not.
Implying that even though the influence was not explicit it was implicit indicative of lapses in
policy guidelines that needs further review. To ensure equity in successful project
implementation across the constituency, the study therefore recommends that the total mandate
of managing CDF projects to be shifted from Members of Parliament to a vetted board in order
to avoid failure of completion of politically initiated projects that ends up not being accepted by
the local communities. This action is not meant to undermine or downplay the capacity or the
weakening the politician but it is fundamentally about making governance of CDF at the
constituency level more responsive to the felt needs of the large majority of the population.
Further, the National government should enact laws that would ensure projected started in
previous parliament is completed within stipulated time so as to avoid abandonment after general
election as a result of newly elected Member of Parliament.
6.3.4 Technical Capacity
The study indicated that technical capacity plays a key role although negatively related to the
effective management of CDF funded projects. In this regard, the study recommends that the
national government should have adequate structures to ensure technical requirement are adhered
to at constituency level. There is need for trainings/workshops meant to increase managers’
expertise, skills and knowledge of implementing CDF project efficiently. On the other hand,
personnel can be increased at the county/constituency level to monitor human resource involved
in the management of CDF funded projects, coming up with legislation on the appointment of
various stakeholders involved in the management of CDF funded projects who will check on the
quality of the projects implemented. Lastly, the CDFC should ensure that their human resource
or those contracted met the minimum requirement in terms of experience, skills, academic
qualification and expertise in the area of specialization.
6.4 Implications
6.4.1 Theoretical implication on theories that guided the study
The study investigated the determinants of effective CDF project management in Kasipul
Constituency, Homa Bay County, Kenya. The study bridged some of the conceptual,
methodological and contextual gaps that had been identified in the literature review. The findings
from this research present a number of issues that have implications for the theory, policy and the
practice of governance and devolved project management. The study advances theoretical
arguments on steward theory in regards governance and resource utilization for effective project
management. The study also advances the use of competence based and project completion in
governance research to examine the role of independent, dependent and moderating roles of
regulatory framework. This study has widened the scope of these theories to leadership and
governance studies.
In regard to project completion theory, the study recognizes the importance of various life cycles
of a project key actors, input, output, constraints and outcome. Project managers utilize project
completion theory so as to make organization achieve planned changes through creation of
environments in which changes can persist. However, the multiplicity of stakeholders as
indicated in this study indicated that it may results to delay in project completion if the
management is unable to come up with effective model of stakeholder participation. On the other
hand, project input which in this study is project financing and technical competence have
revealed to have significant influence on various aspects of project management key among them
project completion indicators such as schedule. Proper utilization of these resources in competent
manner results to effective management of CDF funded projects.
According to competence-based theory organizations have resources and capabilities which
enabled them to meet their objectives. The theory recognizes human resource, financial resources
and past experiences as organization critical success. In relation to this theory, it has a significant
role in linking project financing, technical capacity, stakeholder participation, political influence
and effective project management. Resources from National Government to constituency are less
adequate due to competing need at national government level. Therefore, effective management
of CDF projects, as shown in this study will be determined using available resources
competently in such a manner that value of money is achieved. This implies that the management
have stewardship role to ensure legal and regulatory framework are observed in stakeholder
participation, financial management, procurement of human resources and role of political class
in project management
In regard to steward ship theory, key stakeholders such as CDFC members, project managers and
national government officials among other group should ensure CDF projects are implement
according to various CDF Acts and laws on the utilization of public funds. The role of the CDF
was to ensure that individual at grassroots participate in local development either directly or
indirectly and therefore, enable sustainability and quality of projects. Therefore, the design of
governance structure in the management and administration of resources at grassroots would
enhance superior performance of CDF funded projects.
6.4.2 Contribution to the Study Methodology
The study developed not only an empirical but a structural model depicting the relationship
among the study variables. The model presents a useful framework for governance and project
management as most studies conducted in devolved project management have not considered
econometrically modeling the leadership and governance building blocks to effective CDF
funded project management. Firstly, the study highlights that governance has significant
influence on the CDF funded projects. Presence of project financing without proper governing
concerns such as accountability and transparency would affect allocation of the funds. Similarly,
the structure of stakeholder participation would ensure that collective responsibility involve
participation of all stakeholder. Further, political influence on the management of CDF project
can only be addressed adopting proper governance practices that would ensure prioritization of
projects based on the community need. Lastly, technical capacity which ensures their technical
requirement compliance can only be achieved by focusing on project outcome. Available studies
have dwelled so much on descriptive analysis with linear modeling of quantitative variables.
This study has gone further to model the latent variables of the key building blocks each with
more than four constructs as required. Structural equation modeling is a recent concept that leads
to generation of path coefficient used to determine the extent of effects of the structural variables
on effective management of CDF funded projects in the study area.
6.4.3 Implications to the Policies
At policy level, Kenya’s Vision 2030 aspires to boost development through creating an enabling
environment through economic, political and social pillar. In this regard, Vision 2030 aspires to
develop infrastructure, agriculture, health, National cohesion, youth and sports. These pillars can
be achieved through devolved projects such as CDF. The findings of this study indicated that
project financing and stakeholder participation significantly influence effective CDF project
management. In addition, the study reported on the moderating role of regulatory framework
increase the influence of this determinant on the effective CDF project management albeit
insignificantly. The Government should therefore focus on coming up with various policies that
would aid in the realization of vision 2030 through devolved funds. These policies should be
focused on strengthening project financing and stakeholder participation.
6.5 Recommendation for further areas of studies
This study focused on exploring the determinants of effective management of Constituency
Development Funded projects in Kasipul Constituency, Homa Bay County, Kenya. Four specific
objectives were considered that is the role of project financing, stakeholder participation,
political influence and technical capacity. To begin with, the scope of the study was only limited
to Kasipul Constituency, Homa Bay County and therefore the findings may not necessarily
reflect other constituencies due to different dynamics, thus there is a need for similar study
considering all constituencies in Kenya. Secondly, there is need for similar but a comparative
study to examine the determinants of effective CDF project among the county government
governments in Kenya. Thirdly, a panel data methodology can be adopted to examine the
efficiency of these building blocks on their impact to effectiveness of CDF project management
across east African community region. Studies of this nature may enhance regions, nations and
even on how each of the devolved entities can be effectively managed to benefit the citizens. The
recommendations from these studies may also help each of the entities/units learn from each
other.
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APPENDICES
APPENDIX 1: UNIVERSITY INTRODUCTION LETTER
APPENDIX II: QUESTIONNAIRE FOR THE BENEFICIARIES
1. What is your age bracket? a. Less than 30b. 30-39c. 40-49d. 50 – 59e. 60 – 69f. 69 and above
2. Gendera. Maleb. Female
3. Level of educationa. Primary schoolb. Secondary school educationc. Some college/University educationd. Master degreee. PhD level
4. Which County ward assembly do you come from?a. West Kasipulb. South Kasipulc. Central Kasipul d. East Kamagak ore. West Kamagak
5. For how long resident of Kasipul constituency have beena. 5 yearsb. 5-15 yearsc. 16-25 yearsd. Above 25 years
Technical Capacity1. To what extent does technical capacity influence the effectiveness of CDF project management? (Please, tick one)
i) To a very great extent [] ii) To a great extent [] iii) Moderate extent [] iv) Low extent [] v) Very low extent []
2. To what extent do you agree with the following statements regarding technical capacity in themanagement of CDF projects? Use a scale of 1 to 5 where 5 is to strongly agree, 4-agee, 3-undecided, 2-disagree and 1 is to strongly disagree
Technical Capacity 1 2 3 4 5
1Stakeholders involved in the management of CDF projects haverequired expertise in their domain
2
Training encompasses all aspects of project managementprocess which has enhanced decision capabilities ofstakeholders involved in the management of CDF projects
3 Stakeholders are equipped with prerequisite training, skills and
approaches to adequately monitor and report the project’s statusand progress
4
Responsibilities in the management of CDF projects isdistributed according academic qualification and knowledge inspecific area of specialization
5There is sufficient technical capacity amongst human resourcesto effectively manage CDF Projects
STAKEHOLDER PARTICIPATION1. What level of citizen participation are residents considered in the management of CDF projects? (Please, multiple selections are allowed)
i) Identification []ii) Planning []iii) Allocation []iv) Implementation []v) Monitoring []vi) Evaluation []vii)Commissioning []
Is the participation level (s) effective in the management of CDF projects?___________________________________________________________________________2. How are residents identified in citizen participation in your constituency in the management ofCDF project? (Please, multiple selections are permitted)
i) Nominationii) Electioniii) Appointment
Is the participant identified(s) adequate and sufficient in effective in the management of CDF projects? ___________________________________________________________________________3. What are the forms of citizen participation in your constituency in the management of CDF project? (Please, tick one)i) Representation []ii) Laborers []iii) Others specified_________ []Is the participant identification (s) effective in the management of CDF projects?___________________________________________________________________________4. To what extent does the citizen participation influence the effectiveness of CDF project management? (Please, tick one)
i) To a very great extent [] ii) To a great extent [] iii) Moderate extent [] iv) Low extent [] v) Very low extent []
5. To what extent do you agree with the following statements regarding citizen participation inthe management of CDF projects? Use a scale of 1 to 5 where 5 is to strongly agree, 4-agee, 3-undecided, 2-disagree and 1 is to strongly disagree
Citizen participation 1 2 3 4 51 Management of CDF projects is a collective responsibility that
involves all stakeholders
2Stakeholder participation enhances better utilization of publicresources as the people play an oversight role
3The structures established for stakeholder participation enableseffective management of CDF projects
4
Frequent stakeholder investigation and reviewing the effects ofthe completed or ongoing projects to see whether the benefitswhich were planned to flow from the project have indeed beenrealized
5Stakeholders hold frequent consultative meetings to deliberateon the progress of the project management
POLITICAL INFLUENCE1. Do you think the National politics interfered with CDF projects identification andimplementation process for the FY 2015/16?
i) Yes []ii) No []
If yes to the above, in what way/s do you think the above happened?……………………………………………………………………………………………….………………………………………………………………………………………………..2. Do you think the local politics interfered with the CDF projects identification andimplementation process for the FY 2015/16?
i) Yes []ii) No []
If yes to the above, in what way/s do you think the above happened?………………………………………………………………………………………………..………………………………………………………………………………………………..3. To what extent does a political factor influence the effectiveness of CDF project management?
i) To a very great extent [] ii) To a great extent [] iii) Neither great nor low extent [] iv) Low extent [] v) Very low extent []
4. To what extent do you agree with the following statements regarding political influence in themanagement of CDF projects? Use a scale of 1 to 5 where 5 is to strongly agree, 4-agee, 3-undecided, 2-disagree and 1 is to strongly disagree
Political Influence 1 2 3 4 5
1There is political will in the identification and implementationof CDF projects
2
The Political leadership stick to oversight role as indicated inthe constitution which has resulted to effective management ofCDF projects
3CDF projects are successfully implemented due to politicalinfluence in their management
4
There is no conflict in interest in the management of CDFproject as results of political influence resulting to effectivemanagement of CDF projects
5The involvement of the Member of Parliament adds value to theproject.
PROJECT FINANCING1. To what extent does the financial resource influence the effectiveness of CDF project management? (Please, tick one)
i) To a very great extent [] ii) To a great extent [] iii) Moderate extent [] iv) Low extent [] v) Very low extent []
2. To what extent do you agree with the following statements regarding the resource availabilityand allocation in the management of CDF projects? Use a scale of 1 to 5 where 5 is to stronglyagree and 1 is to strongly disagree
PROJECT FINANCING 1 2 3 4 5
1There is accountability and transparency in the use of CDF fundfor the management of projects
2 I am satisfied with the auditing process of NG – CDF projects
3CDF funds are timely disbursed to the identified projects whichhas enhanced project management
4There are sufficient funds allocated for various aspect of CDFprojects which has resulted to effective management of CDF
5CDF funds are adequately allocated to the identified projectswhich has enhanced project management
REGULATORY FRAMEWORK
1. Are you aware of any regulatory framework in the management of CDF projects? (Please, tick one)
i) Yes []ii) No []
If yes, what are they?i) ______________________________ii) ______________________________
2. To what extent does regulatory framework influence the determinants of effective CDF projectmanagement?
i) To a very great extent [] ii) To a great extent [] iii) Moderate extent [] iv) Low extent [] v) Very low extent []
3. To what extent do you agree with the following statements regarding regulatory framework inthe management of CDF projects? Use a scale of 1 to 5 where 5 is to strongly agree, 4-agee, 3-undecided, 2-disagree and 1 is to strongly disagree
Regulatory Framework 1 2 3 4 5
1There is clear policies and procedures on financial practicesthat has results to effective management of CDF projects
2The CDF Acts on technical capacity is implemented to the letterin the management of CDF projects
3
The CDF Acts on community participation has been fullyembraced resulting to efficiency and effective management ofCDF projects
4
The CDF Acts on the relationship between politics and CDFhas been effectively implement results to noninterference in themanagement of CDF projects
CDF MANAGEMENT1. To what extent have you been satisfied with the management of CDF?
To a very great extent [] To a great extent [] Moderate extent [] Low extent [] Very low extent []
2. To what extent do you agree with the following statements regarding management of CDFprojects? Use a scale of 1 to 5 where 5 is to strongly agree, 4-agee, 3-undecided, 2-disagree and1 is to strongly disagree
CDF project management 1 2 3 4 51 CDF projects are implemented according to the set timelines
2CDF projects are implemented and evaluated according to setobjectives
3CDF projects are implemented according to the cost/budgetprovisions
4CDF projects are implemented according to the set technicalrequirements
5CDF projects are implemented according to the intendedquality standards
6 CDF projects are implemented to user satisfactionTHANKS
APPENDIX III: QUESTIONNAIRE FOR THE CDFC
1. What is your age bracket? a. Less than 30b. 30-39c. 40-49d. 50 – 59e. 60 – 69f. 69 and above
2. Gendera. Maleb. Female
3. Level of educationa. Primary schoolb. Secondary school educationc. Some college/University educationd. Master degreee. PhD level
4. Which is county ward assembly?a. West Kasipulb. South Kasipulc. Central Kasipul d. East Kamagak ore. West Kamagak
5. For how long have been members of CDFC? a. 5 yearsb. 5-15 yearsc. 16-25 yearsd. Above 25 years
6. Which group do you represent in the CDFC? YouthWomenPeople with disabilityNational GovernmentNGOOthers specified______________________________
TECHNICAL CAPACITY1. Is there a mechanism used in sourcing competent staff in the management of CDF projects? (Please, tick one)
i) Yes [] ii) No []
If yes, what is the formula and what is it effectiveness in the management of CDF projects____________________________________________________________________2. To what extent does the resource availability and allocation influence the effectiveness of CDFproject management? (Please, tick one)
i) To a very great extent []
ii) To a great extent [] iii) Neither great nor low extent [] iv) Low extent [] v) Very low extent []
3. To what extent do you agree with the following Use a scale of 1 to 5 where 5 is to stronglyagree, 4-agee, 3-undecided, 2-disagree and 1 is to strongly disagree
Technical Capacity 1 2 3 4 5
1Stakeholders involved in the management of CDF projects haverequired expertise in their domain
2
Training encompasses all aspects of project managementprocess which has enhanced decision capabilities ofstakeholders involved in the management of CDF projects
3
Stakeholders are equipped with prerequisite training, skills andapproaches to adequately monitor and report the project’s statusand progress
4
Responsibilities in the management of CDF projects isdistributed according academic qualification and knowledge inspecific area of specialization
5There is sufficient technical capacity amongst human resourcesto effectively manage CDF Projects
CITIZEN PARTICIPATION1. At what levels do you consider citizen participation in the management of CDF projects? (Please, multiple selections are allowed)
i) Identification []ii) Planning []iii) Allocation []iv) Implementation []v) Monitoring []vi) Evaluation []vii)Commissioning []
Is the participation level(s) effective in the management of CDF projects?___________________________________________________________________________2. How do you identify participants in citizen participation in your constituency in the management of CDF project? (Please, multiple selections are allowed)
i) Votingii) Nominationiii) Appointing
Is the participant identified adequate and sufficient in effective in the management of CDF projects? ___________________________________________________________________________3. Which forms do you use in stakeholder’s participation in your constituency in the managementof CDF project? (Please, tick one)
i) Representation []ii) Laborer []iii) Others Specified_______ []
Is the form (s) of participation effective in the management of CDF projects?
___________________________________________________________________________4. To what extent does the citizen participation influence the effectiveness of CDF project management? (Please, tick one)
i) To a very great extent [] ii) To a great extent [] iii) Moderate extent [] iv) Low extent [] v) Very low extent []
5. To what extent do you agree with the following statements regarding citizen participation inthe management of CDF projects? Use a scale of 1 to 5 where 5 is to strongly agree, 4-agee, 3-undecided, 2-disagree and 1 is to strongly disagree
Citizen Participation 1 2 3 4 5
1Management of CDF projects is a collective responsibility thatinvolves all stakeholders including citizens
2Stakeholder participation enhances better utilization of publicresources as the people play an oversight role
3The structures established for stakeholder participation enableseffective management of CDF projects
4
Frequent stakeholder investigation and reviewing the effects ofthe completed or ongoing projects to see whether the benefitswhich were planned to flow from the project have indeed beenrealized
5Stakeholders hold frequent consultative meetings to deliberateon the progress of the project management
POLITICAL INFLUENCE1. Do you think the National politics interfered with CDF management?
i) Yes []ii) No []
If yes to the above, in what way/s do you think the above happened?……………………………………………………………………………………………….………………………………………………………………………………………………..2. Do you think the local politics interfered with the CDF projects management?
i) Yes []ii) No []
If yes to the above, in what ways do you think the above happened?………………………………………………………………………………………………..………………………………………………………………………………………………..3. To what extent does a political factor influence the effectiveness of NG- CDF project management?
i) To a very great extent [] ii) To a great extent [] iii) Moderate extent [] iv) Low extent [] v) Very low extent []
4. To what extent do you agree with the following statements regarding political influence in themanagement of CDF projects? Use a scale of 1 to 5 where 5 is to strongly agree, 4-agee, 3-undecided, 2-disagree and 1 is to strongly disagree
Political Influence 1 2 3 4 5
1There is political will in the identification and implementationof CDF projects
2
The Political leadership stick to oversight role as indicated inthe constitution which has resulted to effective management ofCDF projects
3CDF projects are successfully implemented due to politicalinfluence in their management
4
There is no conflict in interest in the management of CDFproject as results of political influence resulting to effectivemanagement of CDF projects
5The involvement of the Member of Parliament adds value to theproject.
PROJECT FINANCING1. In a scale of 1 to 5, rate the effectiveness of the following financial resource management in relation CDF projects where 1-very less effective, 2-less effective, 3-somehow effective, 4-most effective and 5-vey most effective
i) Budgetary Utilization [] ii) Fund allocation process [] iii) Fund Utilization []
2. To what extent does the financial resource influence the effectiveness of CDF project management? (Please, tick one)
i) To a very great extent [] ii) To a great extent [] iii) Moderate extent [] iv) Low extent [] v) Very low extent []
3. To what extent do you agree with the following statements regarding the resource availabilityand allocation in the management of CDF projects? Use a scale of 1 to 5 where 5 is to stronglyagree and 1 is to strongly disagree
PROJECT FINANCING 1 2 3 4 5
1There is accountability and transparency in the use of NG- CDFfund for the management of projects
2 I am satisfied with the auditing process of NG – CDF projects
3CDF funds are timely disbursed to the identified projects whichhas enhanced project management
4There are sufficient funds allocated for various aspect of CDFprojects which has resulted to effective management of CDF
5 CDF funds are adequately allocated to the identified projects
which has enhanced project managementREGULATORY FRAMEWORK1. Are you aware of any regulatory framework in the management of CDF projects? (Please, tick one)
i) Yes[]ii) No []
If yes, what are they?i) ______________________________ii) ______________________________
2. To what extent does regulatory framework influence the determinants of effective CDF projectmanagement?
i) To a very great extent [] ii) To a great extent [] iii) Neither great nor low extent [] iv) Low extent [] v) Very low extent []
3. To what extent do you agree with the following statements regarding regulatory framework in the management of CDF projects? Use a scale of 1 to 5 where 5 is to strongly agree, 4-agee, 3-undecided, 2-disagree and 1 is to strongly disagree
Regulatory Framework 1 2 3 4 5
1There is clear policies and procedures on financial practicesthat has results to effective management of CDF projects
2The CDF Acts on technical capacity is implemented to the letterin the management of CDF projects
3
The CDF Acts on community participation has been fullyembraced resulting to efficiency and effective management ofCDF projects
4
The CDF Acts on the relationship between politics and CDFhas been effectively implement results to noninterference in themanagement of CDF projects
CDF PROJECT MANAGEMENT1. Are you satisfied with the management of CDF projects? (Please, tick one)
i) Yes []ii) No []
2. To what extent do you agree with the following statements regarding management of CDFprojects? Use a scale of 1 to 5 where 5 is to strongly agree, 4-agee, 3-undecided, 2-disagree and1 is to strongly disagree
CDF project management 1 2 3 4 51 CDF projects are implemented according to the set timelines
2CDF projects are implemented and evaluated according to setobjectives
3CDF projects are implemented according to the cost/budgetprovisions
4 CDF projects are implemented according to the set technical
requirements
5CDF projects are implemented according to the intendedquality standards
6 CDF projects are implemented to user satisfaction
Thanks
APPENDIX IV: QUESTIONNAIRE FOR THE PROJECT MANAGER/CONTRACTORS
1. What is your age bracket? a. Less than 30b. 30-39c. 40-49d. 50 – 59e. 60 – 69f. 69 and above
2. Gendera. Maleb. Female
3. Level of educationa. Primary schoolb. Secondary school educationc. Some college/University educationd. Master degreee. PhD level
4. Which County ward assembly (is) have been contracted for CDF projects?a. West Kasipulb. South Kasipulc. Central Kasipul d. East Kamagak ore. West Kamagak
5. For how long have been contracted for CDF projects? a. 5 yearsb. 5-15 yearsc. 16-25 yearsd. Above 25 years
6. Which CDF projects are you undertaking or you have underken? a. Educationb. Healthc. Transportd. Environment e. Security f. Others, Specified__________________
TECHNICAL CAPACITY1. To what extent does technical capacity influence the effectiveness of CDF project management? (Please, tick one)
i) To a very great extent [] ii) To a great extent []
iii) Neither great nor low extent [] iv) Low extent [] v) Very low extent []
2. To what extent do you agree with the following statements regarding the resource availabilityand allocation in the management of CDF projects? Use a scale of 1 to 5 where 5 is to stronglyagree, 4-agee, 3-undecided, 2-disagree and 1 is to strongly disagree
Technical capacity 1 2 3 4 5
1Stakeholders involved in the management of CDF projects haverequired expertise in their domain
2
Training encompasses all aspects of project managementprocess which has enhanced decision capabilities ofstakeholders involved in the management of CDF projects
3
Stakeholders are equipped with prerequisite training, skills andapproaches to adequately monitor and report the project’s statusand progress
4
Responsibilities in the management of CDF projects isdistributed according academic qualification and knowledge inspecific area of specialization
5There is sufficient technical capacity amongst human resourcesto effectively manage CDF Projects
CITIZEN PARTICIPATION1. At what level have citizens participated in the project awarded to your company by CDF? (Please, multiple selections are allowed)
i) Identification []ii) Planning []iii) Allocation []iv) Implementation []v) Monitoring []vi) Evaluation []vii)Commissioning []
Is the participation level effective in the management of CDF projects?___________________________________________________________________________
2. How are residents identified in citizen participation in the project awarded to your company? (Please, multiple selections are permitted)
i) Electionii) Nominationiii) Approved
Is the participant identification(s) adequate and sufficient in effective in the management of CDFprojects? ___________________________________________________________________________3. What forms of citizen participation are participants involved in the project awarded to your company? (Please, tick one)
i) Representation []ii) Laborers []iii) Others Specified_______ []
Is the form (s) effective in the management of CDF projects?___________________________________________________________________________4. To what extent does the citizen participation influence the effectiveness of CDF project management? (Please, tick one)
i) To a very great extent [] ii) To a great extent [] iii) Moderate extent [] iv) Low extent [] v) Very low extent [] 6. To what extent do you agree with the following statements regarding citizen participation
in the management of CDF projects? Use a scale of 1 to 5 where 5 is to strongly agree, 4-agee, 3-undecided, 2-disagree and 1 is to strongly disagree
Citizen participation 1 2 3 4 5
1Management of CDF projects is a collective responsibility thatinvolves all stakeholders including citizens
2Stakeholder participation enhances better utilization of publicresources as the people play an oversight role
3The structures established for stakeholder participation enableseffective management of CDF projects
4
Frequent stakeholder investigation and reviewing the effects ofthe completed or ongoing projects to see whether the benefitswhich were planned to flow from the project have indeed beenrealized
5Stakeholders hold frequent consultative meetings to deliberateon the progress of the project management
POLITICAL INFLUENCE1. Do you think the National politics interfered with CDF projects management?
i) Yes []ii) No []
If yes to the above, in what way/s do you think the above happened?……………………………………………………………………………………………….………………………………………………………………………………………………..2. Do you think the local politics interfered with the CDF projects management?
i) Yes []ii) No []
If yes to the above, in what ways do you think the above happened?………………………………………………………………………………………………..………………………………………………………………………………………………..3. To what extent does a political factor influence the effectiveness of CDF project management?
i) To a very great extent [] ii) To a great extent [] iii) Moderate extent [] iv) Low extent [] v) Very low extent []
4. To what extent do you agree with the following statements regarding Political Intervention inthe management of CDF projects? Use a scale of 1 to 5 where 5 is to strongly agree, 4-agee, 3-undecided, 2-disagree and 1 is to strongly disagree
Political Intervention 1 2 3 4 5
1There is political will in the identification and implementationof CDF projects
2
The Political leadership stick to oversight role as indicated inthe constitution which has resulted to effective management ofCDF projects
3CDF projects are successfully implemented due to politicalinfluence in their management
4
There is no conflict in interest in the management of CDFproject as results of political influence resulting to effectivemanagement of CDF projects
5The involvement of the Member of Parliament adds value to theproject.
PROJECT FINANCING1. To what extent does the financial resource influence the effectiveness of CDF project management? (Please, tick one)
i) To a very great extent [] ii) To a great extent [] iii) Neither great nor low extent [] iv) Low extent [] v) Very low extent []
2. To what extent do you agree with the following statements regarding the resource availabilityand allocation in the management of CDF projects? Use a scale of 1 to 5 where 5 is to stronglyagree and 1 is to strongly disagree
PROJECT FINANCING 1 2 3 4 5
1There is accountability and transparency in the use of CDF fundfor the management of projects
2 I am satisfied with the auditing process of NG – CDF projects
3CDF funds are timely disbursed to the identified projects whichhas enhanced project management
4There are sufficient funds allocated for various aspect of CDFprojects which has resulted to effective management of CDF
5CDF funds are adequately allocated to the identified projectswhich has enhanced project management
REGULATORY FRAMEWORK1. Are you aware of any regulatory framework in the management of CDF projects? (Please, tick one)i) Yes []ii) No []If yes, what are they?
i) ______________________________
ii) ______________________________2. To what extent does regulatory framework influence the determinants of effective CDF projectmanagement?
i) To a very great extent [] ii) To a great extent [] iii) Moderate extent [] iv) Low extent [] v) Very low extent []
3. To what extent do you agree with the following statements regarding regulatory framework inthe management of CDF projects? Use a scale of 1 to 5 where 5 is to strongly agree, 4-agee, 3-undecided, 2-disagree and 1 is to strongly disagree
Regulatory Framework 1 2 3 4 5
1There is clear policies and procedures on financial practicesthat has results to effective management of CDF projects
2The CDF Acts on technical capacity is implemented to the letterin the management of CDF projects
3
The CDF Acts on community participation has been fullyembraced resulting to efficiency and effective management ofCDF projects
4
The CDF Acts on the relationship between politics and CDFhas been effectively implement results to noninterference in themanagement of CDF projects
CDF MANAGEMENT1. To what extent have you been satisfied with the management of CDF?
i) To a very great extent [] ii) To a great extent [] iii) Moderate extent [] iv) Low extent [] v) Very low extent []
2. To what extent do you agree with the following statements regarding management of CDF projects? Use a scale of 1 to 5 where 5 is to strongly agree, 4-agee, 3-undecided, 2-disagree and 1 is to strongly disagree
CDF management 1 2 3 4 51 CDF projects are implemented according to the set timelines
2CDF projects are implemented and evaluated according to setobjectives
3CDF projects are implemented according to the cost/budgetprovisions
4CDF projects are implemented according to the set technicalrequirements
5CDF projects are implemented according to the intendedquality standards
6 CDF projects are implemented to user satisfaction
Thanks
APPENDIX V: INTERVIEW GUIDE FOR CDFC CHAIRPERSON
1. Are you aware of any existing CDF Projects in your locality? Please explain2. Which types of projects are funded by the CDF in your locality?3. Do you think there is political intervention (National and local) in successful projects
management in your Constituency? If so, to what extend?4. What is the extent of community involvement in the affairs of CDF?5. To what extend are the administrative, transparency and accountability mechanisms of
CDF efficient?6. To what extent is the CDF outputs pegged with the Constituency development strategic
plan? 7. What do you think about the objectives of the strategic plan in line with the National
government of local needs?8. According to your observation, which areas need improvement for successful project
management in Kasipul Constituency?9. What do you think is the technical competency level of those awarded tenders in the
Constituency? 10. To what extent is the financial allocation for the CDF kitty sufficient for your
constituency development projects? 11. . How do the following affect effectiveness of the management of CDF projects?
i. Some people bribe to win CDF tendersii. The political class has the final say with regard to project allocations
iii. The political leadership has the final word for the projects selectediv. Political leaders affect transparency and accountability in allocation of the
CDFv. Political leaders influence the project committee in procurement processes
vi. The choice of the projects is solely within the discretion of the political
leadershipvii. The MP of this constituency play an influential role in the selection of CDF
projects
APPENDIX VI: FOCUSED GROUP DISCUSSION GUIDE
Technical Capacity (Role of governance in sourcing, application etc.)
Sufficiency of expertise in management of CDF Projects
Appropriate academic qualifications
Adequate skills and knowledge
Citizen Participation (Role of governance in participation structure)
i. Levels where citizens are allowed to participated in the management of CDF
Projects
o Is this level of participation adequate for effective management of CDF
projects?
ii. How are citizens identified to participate in CDF projects?
o Are you satisfied with the mode of participation?
Political Influence (Role of governance in planning, approval and implementation)
i) What is the level of political influence in the management of CDF projects
(Explain your views)?
ii) At what stage of project does political influence have greater role in the
management of CDF projects (both negative and Positive)
Project Financing (Role of governance in financial resource management)
In relation to availability of funds, discuss the following
i) Timely delivery of projects (Time delivery of funds results to timely delivery of
projects)
ii) Quality of projects (proper utilization of funds results to good quality projects and
vice versa)
iii) Auditing mechanism of CDF project (Transparency, verifiability and
accountability)
APPENDIX VII: LETTER FOR DATA COLLECTION
APPENDIX VIII: RESEARCH AUTHORIZATION
APPENDIX IX: RESEARCH PERMIT
APPENDIX X: SUB COUNTY RESEARCH AUTHORIZATION
APPENDIX XI: MAP OF HOMABAY COUNTY
Map of Homa Bay County Showing the County Assembly wards (Pointed by arrows) of
Kasipul Constituency (Source: KNBS & SID 2013)
APPENDIX XII: FACTOR EXTRACTION UNDER EXPLORATORY FACTOR
ANALYSIS
Comp-onent
Initial Eigenvalues Extraction Sums of SquaredLoadings
Rotation Sums of SquaredLoadings
Total% of
VarianceCumu-lative% Total
% ofVariance
Cumu-lative
% Total% of
Variance
Cumu-lative
%1 11.77
8
39.26 39.26 11.778 39.26 39.26 6.36
9
21.229 21.229
2 2.834 9.446 48.706 2.834 9.446 48.706 5.87
4
19.58 40.809
3 1.723 5.742 54.448 1.723 5.742 54.448 3.00
5
10.015 50.825
4 1.219 4.062 58.511 1.219 4.062 58.511 1.96
7
6.555 57.38
5 1.1 3.667 62.178 1.1 3.667 62.178 1.37
9
4.597 61.977
6 1.047 3.489 65.666 1.047 3.489 65.666 1.10
7
3.69 65.666
7 0.949 3.164 68.838 0.748 2.494 71.3249 0.725 2.415 73.74
10 0.678 2.261 7611 0.608 2.026 78.02612 0.577 1.922 79.94813 0.528 1.761 81.70914 0.512 1.705 83.41415 0.489 1.63 85.04416 0.422 1.407 86.4517 0.418 1.394 87.84418 0.397 1.324 89.16819 0.371 1.235 90.40320 0.36 1.201 91.60421 0.339 1.131 92.73622 0.322 1.074 93.80923 0.304 1.013 94.82224 0.272 0.906 95.72825 0.253 0.844 96.572
26 0.245 0.816 97.38827 0.225 0.75 98.13828 0.211 0.704 98.84329 0.184 0.612 99.45530 0.164 0.545 100
APPENDIX XIII: EFA FACTOR LOADINGS TABLE
ComponentIndicato
r
1 2 3 4 5 6
TC1 0.565 0.161 0.16 0.431 -0.096 -0.241TC2 0.55 0.274 0.269 0.363 0.026 -0.285TC3 0.614 0.151 0.262 0.252 0.066 -0.131TC4 0.75 0.076 0.108 0.267 -0.03 0.023TC5 0.655 0.294 0.195 0.294 -0.17 -0.054CP1 0.153 0.218 0.697 0.004 0.101 0.212CP2 0.048 0.334 0.755 0.051 0.063 0.067CP3 0.319 0.155 0.729 0.042 0.133 -0.127CP4 0.033 0.338 0.529 0.363 -0.231 0.079CP5 0.271 0.191 0.591 0.298 -0.138 0.08PI1 0.119 0.056 0.167 0.092 0.014 0.221PI2 0.394 0.174 0.037 0.615 0.288 0.204PI3 0.079 0.292 0.059 0.322 0.7 0.024PI4 0.773 0.016 0.051 0.168 0.068 0.089PI5 0.255 0.22 0.187 0.656 0.174 0.056PF1 0.3 0.724 0.131 0.177 -0.178 0.184PF2 0.051 0.826 0.118 0.271 0.04 0.076PF3 0.71 0.361 0.01 0.112 0.165 0.039PF4 0.499 0.535 0.065 -0.102 0.403 -0.005PF5 0.724 0.269 0.139 -0.065 0.379 0RF1 0.703 0.185 0.267 -0.078 -0.02 0.213RF2 0.296 0.684 0.183 0.242 -0.124 0.126RF3 0.697 0.401 0.264 -0.037 0.063 0.101RF4 0.818 0.159 0.032 0.088 0.021 0.115
PM1 0.177 0.686 0.25 0.055 0.101 -0.04PM2 0.302 0.673 0.136 0.178 -0.193 -0.064PM3 0.135 0.643 0.272 -0.031 0.151 -0.033PM4 0.223 0.594 0.283 0.048 0.25 -0.045PM5 0.182 0.71 0.135 0.056 0.214 -0.057PM6 0.091 0.762 0.14 0.079 0.239 0.056
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.a Rotation converged in 24 iterations.
APPENDIX XIV: CONFIRMATORY FACTOR ANALYSIS; CONSTRUCT VALIDITY
Item AVE
Squared
Multiple
Correlation
Factor loadings
Project
Financing
Stakeholders
Participation
Political
Influence
Technical
Capacity
Legal
framework
Project
Mgt.PF1 0.790 0.382 0.763PF2 0.288 0.720PF3 0.686 0.815PF4 0.602 0.846PF5 0.697 0.806CP1 0.755 0.438 0.745CP2 0.499 0.788CP3 0.516 0.762CP4 0.383 0.722CP5 0.477 0.757PI1 0.709 0.049 0.32PI2 0.455 0.834PI3 0.160 0.575PI4 0.490 0.668PI5 0.356 0.758TC1 0.810 0.518 0.804TC2 0.590 0.827TC3 0.563 0.818TC4 0.556 0.785TC5 0.624 0.818RF1 0.816 0.535 0.831RF2 0.410 0.721RF3 0.723 0.874RF4 0.605 0.839PM6 0.768 0.570 0.791PM5 0.567 0.731PM4 0.521 0.75PM3 0.464 0.778PM2 0.436 0.792PM1 0.557 0.799
APPENDIX XV: PATH COEFFICIENT ESTIMATES FOR MODEL 1
Variable path Estimate S.E. C.R. PPM <--- CP 0.316 0.073 4.308 ***PM <--- PI 0.039 0.175 0.222 0.825PM <--- PF 0.996 0.131 7.603 ***PM <--- TC -0.239 0.122 -1.953 0.051PF5 <--- PF 1PF4 <--- PF 1.037 0.065 15.981 ***PF3 <--- PF 1.122 0.066 17.105 ***PF2 <--- PF 1.21 0.105 11.576 ***PF1 <--- PF 1.076 0.089 12.05 ***CP5 <--- CP 1CP4 <--- CP 0.705 0.063 11.17 ***CP3 <--- CP 1.075 0.092 11.691 ***CP2 <--- CP 0.918 0.083 11.097 ***CP1 <--- CP 0.761 0.076 10.061 ***PI2 <--- PI 1.048 0.097 10.791 ***TC5 <--- TC 1TC4 <--- TC 1.042 0.07 14.915 ***TC3 <--- TC 0.966 0.062 15.563 ***TC2 <--- TC 0.909 0.056 16.304 ***TC1 <--- TC 0.837 0.056 14.942 ***PM1 <--- PM 1PM2 <--- PM 0.825 0.06 13.664 ***PM3 <--- PM 0.821 0.066 12.413 ***PM4 <--- PM 0.894 0.068 13.233 ***PM5 <--- PM 0.94 0.06 15.698 ***PM6 <--- PM 1.002 0.07 14.284 ***PI3 <--- PI 0.808 0.108 7.477 ***PI4 <--- PI 1.303 0.135 9.654 ***PI5 <--- PI 1
APPENDIX XVI: PATH COEFFICIENT ESTIMATES FOR MODEL 2
Variable path Estimate S.E. C.R. PPM <--
-
CP .354 .082 4.291 ***
PM <--
-
PI .054 .210 .256 .798
PM <--
-
TC -.166 .135 -1.235 .217
PM <--
-
PF 1.290 .189 6.819 ***
PM <--
-
LF -.385 .141 -2.725 .006
PF5 <--
-
PF 1.000
PF4 <--
-
PF 1.036 .060 17.246 ***
PF3 <--
-
PF 1.075 .060 17.937 ***
PF2 <--
-
PF 1.127 .096 11.799 ***
PF1 <--
-
PF 1.036 .082 12.655 ***
CP5 <--
-
CP 1.000
CP4 <--
-
CP .704 .063 11.085 ***
CP3 <--
-
CP 1.096 .094 11.689 ***
CP2 <--
-
CP .933 .084 11.153 ***
CP1 <--
-
CP .780 .077 10.159 ***
PI2 <--
-
PI 1.067 .099 10.740 ***
TC5 <--
-
TC 1.000
TC4 <--
-
TC 1.027 .068 15.189 ***
TC3 <--
-
TC .953 .060 15.891 ***
TC2 <--
-
TC .889 .054 16.499 ***
TC1 <--
-
TC .822 .054 15.118 ***
PM1 <--
-
PM 1.000
PM2 <--
-
PM .836 .062 13.567 ***
PM3 <--
-
PM .822 .067 12.280 ***
PM4 <--
-
PM .899 .069 13.121 ***
PM5 <--
-
PM .946 .061 15.591 ***
PM6 <--
-
PM 1.017 .072 14.191 ***
PI3 <--
-
PI .801 .109 7.330 ***
PI4 <--
-
PI 1.385 .142 9.760 ***
PI5 <--
-
PI 1.000
RF3 <--
-
LF 1.069 .066 16.310 ***
RF4 <--
-
LF 1.000
RF2 <--
-
LF .935 .073 12.781 ***
RF1 <--
-
LF .856 .059 14.396 ***
APPENDIX XVIII: PATH COEFFICIENT ESTIMATES FOR MODEL 3
Variable path Estimate S.E. C.R. P
PM <--- CP .354 .079 4.487 ***PM <--- TC -.259 .129 -2.008 .045PM <--- PF 1.160 .169 6.878 ***PM <--- LF -.177 .124 -1.427 .154PM <--- X1
Z
.116 .025 4.598 ***
PM <--- X4
Z
-.086 .025 -3.415 ***
PM <--- X2
Z
.035 .023 1.531 .126
PM <--- PI .071 .196 .360 .719PM <--- X3
Z
-.016 .026 -.640 .522
PF5 <--- PF 1.000PF4 <--- PF 1.030 .060 17.208 ***PF3 <--- PF 1.078 .060 18.007 ***PF2 <--- PF 1.133 .096 11.851 ***PF1 <--- PF 1.045 .082 12.711 ***CP5 <--- CP 1.000CP4 <--- CP .705 .064 11.073 ***CP3 <--- CP 1.099 .094 11.678 ***CP2 <--- CP .938 .084 11.158 ***CP1 <--- CP .784 .077 10.160 ***PI2 <--- PI 1.066 .099 10.742 ***
TC5 <--- TC 1.000TC4 <--- TC 1.028 .068 15.216 ***TC3 <--- TC .953 .060 15.890 ***TC2 <--- TC .888 .054 16.477 ***TC1 <--- TC .823 .054 15.133 ***PM1 <--- PM 1.000PM2 <--- PM .828 .059 14.144 ***PM3 <--- PM .814 .064 12.739 ***PM4 <--- PM .890 .065 13.606 ***PM5 <--- PM .936 .058 16.189 ***PM6 <--- PM 1.013 .068 14.858 ***
PI3 <--- PI .800 .109 7.321 ***PI4 <--- PI 1.384 .142 9.766 ***PI5 <--- PI 1.000
RF3 <--- LF 1.085 .067 16.182 ***RF4 <--- LF 1.000
RF2 <--- LF .946 .075 12.533 ***RF1 <--- LF .870 .061 14.252 ***
APPENDIX XIX: MAHALANOBIS DISTANCE (Observations farthest from the centroid)
Observation
number
Mahalanobis d-squared p1 p2
7 102.796 .000 .00051 86.681 .000 .00031 85.589 .000 .000221 81.316 .000 .000314 78.052 .000 .00053 77.049 .000 .000286 71.139 .000 .000236 67.918 .000 .00048 67.681 .000 .000218 67.461 .000 .000195 66.785 .000 .000187 63.078 .000 .00084 59.367 .000 .000288 59.367 .000 .000232 58.320 .000 .000325 57.802 .000 .000308 57.093 .000 .000238 54.976 .000 .000292 54.899 .001 .00025 54.705 .001 .000326 54.574 .001 .0005 54.497 .001 .000
237 54.315 .001 .00026 54.082 .001 .00011 53.731 .001 .000
313 53.025 .001 .00064 52.446 .001 .00036 51.662 .001 .000309 51.438 .001 .000297 50.456 .002 .00010 50.167 .002 .00047 49.664 .002 .00086 48.978 .003 .000328 48.973 .003 .000240 48.811 .003 .00062 48.749 .003 .000207 48.100 .004 .000329 47.977 .004 .000339 47.960 .004 .000147 47.871 .004 .000234 47.500 .004 .000
322 47.451 .004 .00055 47.323 .004 .00038 47.121 .005 .00012 46.161 .006 .00079 45.793 .007 .000285 45.608 .007 .00078 45.000 .008 .00052 44.649 .009 .00043 44.401 .010 .000210 44.312 .010 .00035 42.345 .016 .00063 42.005 .018 .000219 41.885 .018 .0009 41.853 .019 .000
307 41.511 .020 .000324 41.478 .020 .000217 40.314 .027 .00044 40.165 .028 .000204 39.623 .032 .000303 39.218 .035 .000298 38.860 .038 .00013 38.767 .039 .00018 38.512 .041 .000233 38.178 .044 .000196 37.988 .046 .00058 37.670 .050 .00049 37.553 .051 .00019 36.823 .060 .00056 36.469 .065 .000284 36.269 .068 .000327 36.168 .069 .000193 36.034 .071 .00083 35.686 .076 .000215 35.520 .079 .000278 35.268 .083 .000294 34.860 .091 .00060 34.743 .093 .000302 34.726 .093 .000199 34.530 .097 .000295 34.185 .104 .000242 34.065 .107 .000320 33.915 .110 .000208 33.406 .121 .00080 32.936 .133 .000156 32.854 .135 .000197 32.656 .140 .00085 31.772 .165 .000
54 31.689 .167 .00032 31.463 .174 .000203 31.384 .177 .000305 31.044 .188 .00096 30.746 .198 .00142 30.690 .199 .0008 30.494 .206 .001
174 30.206 .217 .003222 29.853 .230 .012318 29.664 .237 .020148 29.430 .246 .03973 29.224 .255 .063