determinants of effective management of …

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)

ii

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…………………………

iv

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

v

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.

vii

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

ix

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

x

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

xi

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


5.5 The role of political intervention on effective management of Constituency


5.6 The influence of Technical capacity on effective management of Constituency


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

xiii

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

xiv

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

xv

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

xvi

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. 46: Goodness of fit test for model 3........................................................................151


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

xvii

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

xix

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

xx

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


iv. To establish the influence of technical capacity on effective management of Constituency


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


H03: There is no significant relationship between political influence and effective


H04: There is no significant relationship between technical capacity and effective


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


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


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


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


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


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


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


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


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


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


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


SD

(%)

D

(%)

U

(%)

A

(%)

SA

(%)

Mean STD



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


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


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


SD

(%)

D

(%)

U

(%)

A

(%)

SA

(%)

Mean STD



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


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



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



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


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


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


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



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


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


SD

(%)

D

(%)

U

(%)

A

(%)

SA

(%)

Mean STD



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


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


SD

(%)

D

(%)

U

(%)

A

(%)

SA

(%)

Mean STD



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


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


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


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.


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


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



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


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


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


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


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


threshold

Status


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.


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


threshold

Status


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.


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


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


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


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.


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


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.


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)


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)


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?


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




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


2


3

Stakeholders are equipped with prerequisite training, skills andapproaches to adequately monitor and report the project’s statusand progress

4



CITIZEN PARTICIPATION1. At what levels do you consider citizen participation in the management of CDF projects? (Please, multiple selections are allowed)


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)


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



4



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?


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


2



4



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)




1There is accountability and transparency in the use of NG- CDFfund for the management of projects




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?


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




3


4


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



4 CDF projects are implemented according to the set technical

requirements


6 CDF projects are implemented to user satisfaction

Thanks

APPENDIX IV: QUESTIONNAIRE FOR THE PROJECT MANAGER/CONTRACTORS




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


2


3

Stakeholders are equipped with prerequisite training, skills andapproaches to adequately monitor and report the project’s statusand progress

4



CITIZEN PARTICIPATION1. At what level have citizens participated in the project awarded to your company by CDF? (Please, multiple selections are allowed)


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



4



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?


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


2



4



PROJECT FINANCING1. To what extent does the financial resource influence the effectiveness of CDF project management? (Please, tick one)




1There is accountability and transparency in the use of CDF fundfor the management of projects




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?


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




3


4


CDF MANAGEMENT1. To what extent have you been satisfied with the management of CDF?


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



4CDF projects are implemented according to the set technicalrequirements


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

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