User Involvement in Implementation of Enterprise Resource

USER INVOLVEMENT IN IMPLEMENTATION OF ENTERPRISE RESOURCE

PLANNING SYSTEMS IN PUBLIC UNIVERSITIES: A CASE OF KISII UNIVERSITY,

KENYA.

BOGONKO BEN MARIGA

BSC.IT (JOMO KENYATTA UNIVERSITY OF AGRICULTURE AND TECHNOLOGY)

A THESIS SUBMITTED TO THE SCHOOL OF POSTGRADUATE STUDIES IN

PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE AWARD OF A

MASTER OF INFORMATION SYSTEMS DEGREE, DEPARTMENT OF COMPUTING

SCIENCES, SCHOOL OF INFORMATION SCIENCE AND TECHNOLOGY, KISII

UNIVERSITY.

JUNE, 2019 DECLARATION Declaration by the Candidate

This thesis is my original work and has not been presented for a degree in any other university.

Ben Mariga Bogonko ……………………. …………………

MIN11/20473/15

Recommendation by the Supervisors

This thesis has been submitted for examination with our approval as University supervisors.

1. Dr. James Ogalo, PhD ……………………. …………………..

Senior Lecturer,

Department of Computing Sciences,

School of Information Science and Technology,

Kisii University.

2. Dr. Charles Nyangara, PhD ……………………. ………………

Senior Lecturer,

Department of Computing Sciences,

School of Information Science and Technology,

Kisii University.

PLAGIARISM DECLARATION

Declaration by the Student

i. 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 can be assigned a fail grade (“F”) vi. I further understand I may be suspended or expelled from the University for Academic Dishonesty.

Name: Ben Mariga Bogonko Sign………………… Date…………………

Reg. No: MIN11 /20473 /15

Declaration by Supervisor (S)

i. We declare that this thesis has been submitted to plagiarism detection service.

ii. The thesis contains less than 20% of plagiarized work. iii. We hereby give consent for Library Binding

1. Dr. James Ogalo, PhD …………… …………….

Kisii University

2. Dr. Charles Nyangara, PhD …………… …………….

Kisii University

iii

DECLARATION OF NUMBER OF WORDS

Declaration by the Candidate

I confirm that the word length of the thesis, including footnotes is 25,663 and the bibliography is 4,115. I also declare that the electronic version is identical to the final, hard bound copy of the thesis and corresponds with those on which the examiners based their recommendation for the award of the degree.

Signed: …………………………………… Date: …………………………………

Declaration by Supervisors

I confirm that the thesis submitted by the above-named candidate complies with the relevant word length specified in the School of Postgraduate and Commission of University Education regulations for the Masters Degrees.

1. Dr. James Ogalo, PhD ……………… ………………….

Kisii University

2. Dr. Charles Nyangara, PhD ……………… ……………….

Kisii University

No part or section of this thesis may be reproduced, stored in a retrievable system or transmitted in any form without explicit authority of the researcher and/or Kisii University on behalf of the researcher.

All rights are reserved.

DEDICATION

I wish to most sincerely dedicate this thesis to my wife Sarah Matoke Mariga, my son Euclid

Bogonko Mariga and my mother Monicah Kemunto Bogonko.

ACKNOWLEDGEMENTS

I would like to appreciate my supervisors Dr. James Ogalo and Dr. Charles Nyangara for their positive criticism and thorough guidance in this research despite their busy schedules. I would also like to appreciate the effort that the school has given me towards the completion of this research. I also thank my dear wife Sarah Matoke Mariga, my mother Monicah Kemunto

Bogonko, my elder sister Rose Kwamboka Bogonko and my brother in-law Eric Oscar Mwebi for their material support, encouragement and due patience in my tight schedule. Special thanks go to my colleagues especially Mr. Dennis Nyamasege and Ms. Irene Nyamweya too for providing me with the enabling moral and material support during this study. All those who contributed either directly or indirectly to the completion of this study thanks a lot and be blessed in your daily endeavors. Above all, I thank the almighty God for all the amazing opportunities that He has given me to undertake this research.

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LIST OF ABBREVIATIONS & ACRONYMS

ADS: Advanced Planning Systems

BI: Business Intelligence

BPR: Business Process Reengineering

CRM: Customer Relationship Management

CSF: Critical Success Factors. CM: Change Management CVI: Content Validity Index DOI: Diffusion of Innovation. EIS: Executive information Systems

ERP: Enterprise Resource Planning. ICT: Information Communication Technology ISS: Information System Success IS: Information Systems PCC: Pearson Correlation Coefficient KSU: Kisii University MRP: Material Requirement Planning MRPII: Manufacturing Resource Planning TAM: Technology Acceptance Model TMS: Transportation Management Systems SPSS: Statistical Package for Social Science SRM: Supplier Relationship Management UI: User Involvement. UP: User Participation. WMS: Warehouse Management Systems

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ABSTRACT

Despite heavy investment in Enterprise Resource Planning system (ERP), it is not yet vivid how Kenyan Universities have involved users in implementation of the system for the realization of their operations to obtain the benefits from this investment. This research sought to evaluate user involvement in implementation of ERP systems in public universities. Objectives of this study were to: examine extent of user involvement in the implementation of ERP system employed, establish user factors in the implementation of the ERP system employed and finally to find out the challenges encountered in implementing the ERP system in public universities. The study used Information Systems Success Model and Diffusion of Innovation Theories. The researcher adopted a survey research design and the area of the study was Kisii University. Target population comprised of 1130 with a sample size of 92 respondents. Questionnaires were used for data collection. Results were presented in form of frequency, percentages and tables. Findings showed that majority of the ERP users were of the opinion that user involvement was imperative to a large extent (M=2.09; SD=0.802), there was a strong positive relationship between the extent of user involvement and ERP system implementation (r=.854). User factors had high influence in implementation of the ERP systems (M=2.22; SD=1.116). Results further indicated that there were various challenges facing the implementation of ERP systems in public universities (M=2.29; SD=.963). Therefore, the study concludes that despite the fact that users were involved in the implementation of ERP systems, there are still a number of executional challenges that need to be addressed by the management for a better for implementation success. The study recommended that, in as much as the university rolled out the implementation of the ERP system which is ongoing, it has not fully done so to realize its value. The university should address the user factors and ERP system implementation challenges for they are fundamental for the success of the ERP system implementation in public universities. This study is valuable to the existing domains of knowledge by acting as a blue print to future researchers on the application of the ERP systems. The results of this research enlighten the management of public universities in making sound decisions on the effectiveness of the ERP system in both administrative and academic functions of the university.

TABLE OF CONTENTS TITLE PAGE ...... Error! Bookmark not defined.

DECLARATION ...... ii

ACKNOWLEDGEMENTS ...... vii

LIST OF ABBREVIATIONS & ACRONYMS ...... viii

ABSTRACT ...... ix

TABLE OF CONTENTS ...... x

LIST OF TABLES ...... xv

LIST OF FIGURES ...... xvi

CHAPTER ONE ...... 1

1.0 INTRODUCTION ...... 1

1.1 BACKGROUND OF THE STUDY ...... 1

1.2 STATEMENT OF THE PROBLEM ...... 8

1.3 MAIN OBJECTIVE/PURPOSE OF THE STUDY ...... 9

1.3.1 SPECIFIC OBJECTIVES OF THE STUDY ...... 9

1.3.2 RESEARCH QUESTIONS ...... 9

1.4 JUSTIFICATION OF THE STUDY ...... 10

1.5 SIGNIFICANCE OF THE STUDY...... 10

1.6 SCOPE OF THE STUDY ...... 11

1.7 WEAKNESSES/LIMITATIONS OF THE STUDY ...... 11

1.9 SUMMARY ...... 12

CHAPTER TWO ...... 13

2.0 LITERATURE REVIEW ...... 13

2.1 INTRODUCTION ...... 13

2.2 THEORETICAL FRAMEWORK ...... 13

2.2.1 DIFFUSION OF INNOVATIONS THEORY ...... 13

2.2.2 INFORMATION SYSTEMS SUCCESS MODEL ...... 19

2.2.3 TECHNOLOGY ACCEPTANCE MODEL ...... 21

2.3 EMPIRICAL REVIEW ...... 21

2.4 USER INVOLVEMENT IN ERP SYSTEMS IMPLEMENTATION ...... 25

2.4.1 USER PARTICIPATION ...... 27

2.4.2 PURPOSE OF USER INVOLVEMENT...... 27

2.4.3 DEFINE ROLES IN INFORMATION SYSTEM PROJECTS ...... 28

2.5 USER FACTORS ...... 32

2.6 CHALLENGES OF THE ERP IMPLEMENTATION IN UNIVERSITY ...... 34

2.6.1 CONFLICTS BETWEEN USER DEPARTMENT ...... 34

2.6.2 ATTEMPTS TO BUILD BRIDGES TO LEGACY SYSTEMS ...... 35

2.6.3 INADEQUATE EFFECTIVE PROJECT MANAGEMENT METHODOLOGY...... 36

2.6.4 EFFECTIVE COMMUNICATION...... 37

2.6.5 MISUNDERSTANDING OF CHANGE REQUIREMENTS ...... 37

2.6.5 FAILURE TO REDESIGN BUSINESS PROCESS ...... 40

2.6.6 COMPOSITION OF PROJECT TEAM MEMBERS ...... 40

2.7 ERP SYSTEM IMPLEMENTATION FACTORS ...... 41

2.7.1 DETAILED KNOWLEDGE OF THE ORGANIZATION AND LEGACY SYSTEMS ... 42

2.7.2 HAVING A CLEAR AND CONCISE STRATEGY ...... 42

2.7.3 HAVING TOP MANAGEMENT SPONSORSHIP ...... 43

2.7.4 FOLLOWING TOP-NOTCH PROJECT MANAGEMENT PRACTICES AND PROCESS MANAGEMENT ...... 43

PRACTICES FOR BPR ...... 43

2.7.5 FOLLOWING TOP-NOTCH CHANGE MANAGEMENT PRACTICES ...... 44

2.7.6 CREATING CLEAR PROCEDURES FOR DATA ENTRY AND ACCURACY ...... 44

2.7.7 CONDUCTION TRAINING AND STREAMLINING THE COMMUNICATION ...... 45

2.7.8 CREATING PERFORMANCE MEASURES ...... 45

2.7.9 DECIDING ON THE IMPLEMENTATION APPROACH...... 46

2.8 COMPUTER SELF-EFFICACY ...... 46

2.8.1 PERFORMANCE ACCOMPLISHMENTS ...... 47

2.8.2 VICARIOUS EXPERIENCE ...... 47

2.8.3 VERBAL PERSUASION ...... 48

2.8.4 PSYCHOLOGICAL STATE ...... 48

2.9 CONCEPTUAL FRAMEWORK ...... 49

2.8 SUMMARY ...... 51

CHAPTER THREE ...... 52

3.0 RESEARCH METHODOLOGY...... 52

3.1 INTRODUCTION ...... 52

3.2 RESEARCH DESIGN ...... 52

3.3 GEOGRAPHICAL AREA OF THE STUDY ...... 52

3.4 TARGET POPULATION ...... 53

3.5 SAMPLING TECHNIQUE ...... 53

3.6 SAMPLE SIZE ...... 53

3.7 DATA COLLECTION ...... 54

3.8 DATA COLLECTION INSTRUMENT...... 55

3.9 VALIDITY AND RELIABILITY OF THE INSTRUMENT ...... 55

3.9.1 VALIDITY ...... 55

3.9.2 RELIABILITY ...... 56

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3.10 DATA ANALYSIS AND PRESENTATION ...... 57

3.11 ETHICAL ISSUES ...... 57

3.12 EXPECTED OUTCOME ...... 58

3.13 SUMMARY ...... 58

CHAPTER FOUR ...... 59

4.0 DATA ANALYSIS, PRESENTATION AND INTERPRETATION ...... 59

4.1 INTRODUCTION ...... 59

4.2 RESPONSE RATE ...... 59

4.3 EXTENT OF USER INVOLVEMENT...... 59

4.3.1 DISCUSSION OF THE EXTENT OF USER INVOLVEMENT ...... 64

4.4 USER FACTORS ...... 65

4.4.1 DISCUSSION OF USER FACTORS ...... 71

4.5 ENTERPRISE RESOURCE PLANNING SYSTEM IMPLEMENTATION CHALLENGES ...... 72

4.6.2 DISCUSSION OF THE ERP SYSTEM IMPLEMENTATION CHALLENGES ...... 76

4.7 SUMMARY ...... 78

CHAPTER FIVE ...... 79

5.0 SUMMARY OF THE FINDINGS, CONCLUSION AND RECOMMENDATIONS ...... 79

5.1 INTRODUCTION ...... 79

5.2 SUMMARY OF THE FINDINGS ...... 79

5.2.1 USER INVOLVEMENT ...... 79

5.2.2 USER FACTORS ...... 80

5.2.3 ENTERPRISE RESOURCE PLANNING SYSTEM IMPLEMENTATION CHALLENGES ...... 81

5.3 CONCLUSION ...... 82

5.4 RECOMMENDATIONS ...... 82 xiii

5.4.2 SUGGESTION FOR FURTHER RESEARCH...... 84

5.5 SUMMARY ...... 84

APPENDIX A: INTRODUCTORY LETTER ...... 96

APPENDIX B: RESEARCH QUESTIONNAIRE FOR THE STAFFS ...... 97

APPENDIX C: RESEARCH QUESTIONNAIRE FOR THE STUDENTS ...... 100

APPENDIX E: RESEARCH AUTHORIZATION BY NACOSTI...... 104

APPENDIX F: RESEARCH CLEARANCE PERMIT ...... 105

APPENDIX G: CORRELATION MATRIX TABLE ...... 106

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LIST OF TABLES Table 3. 1: Sample Size Determination ...... 54 Table4.1: Response Distribution Rate ...... 59 Table 4.2: Extent of User Involvement ...... 60 Table 4.3: Correlation Analysis between Extent of User Involvement and the ERP System Implementation ...... 61 Table 4.4: Regression Analysis of Extent of User Involvement and the ERP System Implementation ...... 63 Table 4.5: Computer Self-Efficacy ...... 66 Table 4.6: User Factors ...... 66 Table 4.7: Student view on the ERP Implementation ...... 67 Table 4.8: Correlation Analysis between User Factors and the ERP System Implementation .... 68 Table 4.9: Regression Analysis of User Factors and the ERP System Implementation ...... 69 Table 4.10: ERP System Implementation Challenges ...... 72 Table 4.11: Correlation Analysis between Challenges and the ERP System Implementation ..... 74 Table 4.12: Regression Analysis of Challenges and the ERP System Implementation ...... 75 Table 4.13: Moderator Analysis ...... 76

LIST OF FIGURES Figure 2.1: IS Success Model (DeLone& McLean, 1992) ...... 20 Figure 2.2: Conceptual Framework ...... 49

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CHAPTER ONE

1.0 INTRODUCTION

1.1 Background of the Study

Historically, ERP systems evolved from Materials Requirement Planning (MRP) earlier in the 1970s. Subsequently, in the 1980s, Manufacturing Resources Planning (MRPII) provided production, tactical and strategic decision-making capability, and was used as

Decision Support Systems (DSS) and Executive Information Systems (EIS). After that, in the 1990s, ERP systems introduced financial services, accounting services, human resource management, production management, and sales functionality in a combined business suite.

Since the turn of the century, extended ERP or ERPII systems have provided functionality across the supply chain, including Warehouse Management Systems (WMS),

Transportation Management Systems (TMS), Advanced Planning Systems (ADS), analytics, Business Intelligence (BI), Supplier Relationship Management (SRM) systems,

Customer Relationship Management (CRM) systems, and e-business (Koh et al, 2011;

Tarhini et al, 2015).

An Enterprise Resource Planning (ERP) system refers to the application solution that integrates business functional units and data into a single system to be shared within an organization, though the initial implementation of Enterprise Resource Planning systems were observed in manufacturing industries, universities have taken up the systems to provide institutional-wide automation for their operations (Ferrell, 2003).In India, according to Gupta (2013), Enterprise Resource Planning systems have gained extensive demand in the 21st century owing to their holistic approach to organizational management.

According to Annamalai and Ramayah (2013), ERP systems have global popularity as the application that would lead to high profitability, enhance businesses‟ efficiency, 1 productivity and streamline their operations. ERP is not just an automation of the organization's business process; it enables the organization to make re-engineering of its business process to achieve its long term success. It provides several advantages such as enhanced process flow, reduced inventories, improved data analysis, superior customer service, better enterprise performance and greater efficiency. All of these invite organizations to adopt ERP systems to strongly enter the competitive market (ALdayel et al, 2011).

In central Europe, a study done by Hussain and Fadi (2014) confirms that technological and administrative challenges influencing the ERP system implementation in public universities in Europe have been described but they have not considered how users as a challenge too are incorporated in the implementation of the ERP system. It is in these contextual gaps that this research is geared towards filling.

Hence, the term ERP (Enterprise Resource Planning) systems as a complex and comprehensive software packages designed to integrate business processes and functions.

Despite the problems and threats of implementing such a system, the last decade has seen a remarkable global extension of such systems into other disciplines such as Higher

Education environments.

In spite of plentiful advantages of Enterprise Resource Planning systems, their thriving implementation has been better said than done (Venkatesh et al, 2003; Marchewka, Liu

&Kostiwa, 2007). With more users seeking to link application systems to departmental operations, public universities are seeking ways to integrate their processes in a bid to cut on operational costs, offer timely response to their clients and interact with their

2 stakeholders in „real-time‟. To keep up with the management apprehension in the 21st century as noted by Nyandiere et al. (2012), universities have turned to Enterprise Resource

Planning to substitute their legacy systems.

Upon accomplishment, these systems are anticipated to provide increased efficiency and effectiveness of operations, diminish overhead costs in ICT, get better decision making, improve resource management and building business innovation while supporting strategic change (Sullivan & Bozeman, 2010). In the course of the current seeking to establish the effect of some of these factors in the implementation of Enterprise Resource Planning systems in public universities in Kenya, prior studies in developed societies such as Shah et al. (2011) cited factors such as top management support, user involvement, vendor support, overlooking of change management aspects, turnover of vendors team member, transfer of top management in beneficiary institutions as crucial factors affecting successful implementation of ERP systems in institutions.

As eluded above, user involvement is of great significance in the ERP system implementation. Various studies have distinguished that user involvement and user participation are important factors affecting project outcomes (Kappelman et al, 2006;

Khang & Moe, 2008; Ngai et al, 2008; LePage, 2009). Inadequate user involvement has even been identified as contributing towards a distressed Enterprise Resource Planning system (Havelka & Rajkumar, 2006). Millerand and Baker (2010) asserted “that the user concept itself is underdeveloped in theory”. Locke et al. (1986) argued that “user involvement is a tool, not a panacea”.

The consequences of involving users in the ERP implementation is a better fit between the consequential system and the business operations (Panorama Consulting Group, 2013).

Any system implementation must track the best approach, for better outcomes. There are two strategies to implementing the Enterprise Resource Planning systems in an organization: reengineering business processes and the ERP customization (Shehab et al,

2004). Despite of these approaches, the implementation of the ERP systems in public universities has been described as a challenging undertaking (Rabaa et al, 2009). One study found that in 60% to 80% of higher education contexts, the ERP implementation failed to meet the projected outcomes and the results of implementation were found insufficient

(Mehlinger, 2006).

Public universities have made considerable investments in Enterprise Resource Planning

(ERP) system implementation to get better institutional business operations (Mehlinger,

2006). Separate legacy systems were “incongruent” and have led to “replica resources and services” (Allen & Kern, 2001). ERP enables public universities to merge disparate data and legacy systems and adopt best-of-breed processes and contemporary technology.

According to Abugabah and Sanzogni (2010), higher education institutions spent more than

$5 billion in ERP investment during the last few years. Enterprise Resource Planning

(ERP) system used in public universities integrates administrative functions that have been supported by separate legacy systems in the earlier period (Zornada & Velkavrh, 2011).

The literature reviewed asserts that most researchers have emphasized on other factors which they deem critical for the ERP system implementation success giving less attention

4 to the user involvement and user factors too as one of those factors (Shah et al., 2011). This creates gap in this study that needs to be investigated.

A research done at Cleveland State University in United States by Swanson (1974) identifies the “renowned wisdom” that “users ought to be „involved‟ in management information systems development and implementation, unfortunately, what is meant by involvement is rarely clear”. The author did suggest that the measurement of involvement should be based on their activities whether as a user or as a facilitator of its development.

User factors play a major role in the implementation of information systems in organizations. Researchers have given attention to some user factors whilst less consideration has been given to User self-efficacy that can be recognized as a self- motivator. People who are extremely confident of their abilities to share beneficial understanding are more inclined to impart that information to others with the certainty that the knowledge they share will lend a hand to resolve issues or improve performance (Liao

& Hsu, 2013).

Another user factor is trust which is a much-argued factor that always facilitates system implementation between two entities (Saba et al, 2012). Within the context of online social system based information sharing, trust is an initial condition required by communities to participate and share their ideas and opinions. The existence of trust plays an important role in cheering system adoption among members (Chai & Kim, 2010).

The user‟s attitude is to learn and use of the software only when the top management support and make available appropriate incentive for that. Enjoyment in helping others

5 refers to a motivation to help others without expectation of a return Papadopoulos et al,

2013). In a review of the literature on system implementation, enjoyment in helping others is described as self-sacrifice Svetlik et al, 2007). According to Arumugam (2001), he disputes that being short of celebration when success and extreme results have been achieved, tends to promote bad performance.

Diverse factors applicable to the ERP system implementation success or failure have been explained in the past studies; however, mostly the studies have been carried out in developed countries. (Moohebat et al, 2010). Presently developing countries like Australia are equally devoted to adopt the ERP systems in their universities, nevertheless, the factors that affected the ERP implementation in developed countries may also need to be researched in the context of developing countries like Kenya. The past research confirms that success of the ERP system implementation is problematic. Implementation of the ERP system is not an easy task as it is anchored on socio-technical factors relating to people, organization and technology. The failure pace of the ERP system implementation is disappointing (Moohebat et al., 2010; Leon, 2008).

Varied challenges that organizations commonly faced during the ERP implementation had been addressed in the past research (Spitze, 2001; Thavapragasam, 2003). A study done in

New Zealand by Leon (2008) mentioned that 69%, 28% and 13% failure rate of the ERP systems due to people, process and technological troubles respectively. It shows that people problems are more significant as opposed to the rest ones.

Numerous factors affect the ERP adoption in organizations (Shah et al., 2011). These factors include user involvement (Francoise et al., 2009; Rasmy et al., 2005). The involvement of the users during the phase of defining organizational information needs may decrease the resistance of users towards the ERP system implementation. The user involvement leads to better user requirements, achieving better quality system and system usage (Motwani et al., 2005).

The factors explored in developed countries have not been found different, this research on the evaluation of user involvement in the implementation of the ERP system in public universities in Kenya which is a developing country found a contextual gap to fill hence the motive of this study.

Implementation of the ERP system, just like any other information systems, encounters several issues and challenges Mahammadreza et al (2015). It is fascinating that only 63% of organizations consider their ERP projects were successful around the world in 2014, and this rate is much lower for Iranian organizations in Asia, which ERP is new to them and have failed in most of the cases. This was attributed to technological factors and individual factors like lack of user involvement. Further, a research done in Thailand converges with the findings of Helo et al (2008) who agrees that unlike other information systems, the major problems of ERP implementation are not technologically related issues, but mostly organizational and human related issues like resistance to change, organizational culture, incompatible business processes, project mismanagement, top management commitment and human related issues which have been given less attention.

Considering the momentous influence of information technology in universities wide operations, it is not surprising that many have adopted the ERP systems for development 7 and reengineering of administrative systems as a route to make their performance better

(King, 2009; Abugabah & Sanzogni, 2010). However, numerous factors affect the ERP adoption in organizations and these factors include user involvement (Francoise et al.,

2009; Rasmy et al., 2005).

It is fascinating that only 63% of organizations consider their ERP projects were successful around the world in 2014, and this rate is much lower for organizations in Asia, which ERP is new to them and have failed in most of the cases (Mahammadreza et al, 2015). This was attributed to technological factors and individual factors like lack of user involvement. In central Europe, a study done by Hussain and Fadi (2014) confirms that technological and administrative challenges influencing the ERP system implementation in public universities in Europe have been described but they have not considered how users as a challenge too are incorporated in the implementation of the ERP system.

A number of studies have been carried out worldwide in an effort to address the challenges facing ERP systems as well as identify its prospects. These studies include Jepng„eno et al.

(2016) who looked at the effects of ERP systems on organizational performance in Kitale technical training institute, Kenya. Mwove and Kwasira (2014) studied the effect of ERP system in enhancing service delivery in the procurement function in public universities in

Kenya.

1.2 Statement of the Problem

Based on the government policy and vision 2030 in running the government entities, there has been heavy investment in the ERP implementation across including universities. In

8 spite of this heavy investment in Kenyan universities, the implementation of the ERP systems has been noted as challenging as a result of inadequate user involvement in the implementation process. This study therefore sought to reduce this knowledge gap by evaluating user involvement in the implementation of the ERP system, hence the motive of carrying out this research.

1.3 Main Objective/Purpose of the Study

The main objective of this study was to evaluate user involvement in the implementation of the Enterprise Resource Planning systems in public universities, considering Kisii

University as a case study.

1.3.1 Specific Objectives of the Study

This research was guided by the following specific objectives:

i. To examine the extent of user involvement in the implementation of the Enterprise

Resource Planning system employed in Kisii University.

ii. To establish the user factors in the implementation of the Enterprise Resource

Planning system employed in Kisii University.

iii. To find out the challenges encountered in the implementation of the Enterprise

Resource Planning system in Kisii University.

1.3.2 Research Questions

This research was guided by the following specific objectives:

i. What is the extent of user involvement in the implementation of the Enterprise

Resource Planning system employed in Kisii University?

ii. What are the user factors in the implementation of the Enterprise Resource Planning

system employed in Kisii University?

iii. What are the challenges encountered in the implementation success of the

Enterprise Resource Planning system in Kisii University?

1.4 Justification of the Study

The purpose of this research was to evaluate the user involvement in the implementation of

Enterprise Resource Planning system in public universities. To achieve this the specific objectives were to examine the level of user involvement in the implementation of the

Enterprise Resource Planning system projects executed, establish the user factors in the

ERP implementation and to find out the challenges or problems encountered in implementing the ERP as a result of inadequate user involvement in the implementation of the Enterprise Resource Planning system in a university setup. Moreover, this research sought to explain the implementation effects and consequences which impact the institution and its processes; with a view to proposing guidelines for the way forward.

1.5 Significance of the Study

This research is valuable to the existing domains of knowledge by acting as a blue print to future researchers on the application of the ERP systems. The results of this thesis enlighten the management of public universities in making sound decisions on the effectiveness of the ERP system in both administrative and academic functions of the university. The findings of the study inform students who are important stakeholders on the efficiency of using the ERP system.

1.6 Scope of the Study

This research evaluated how user involvement influenced the implementation of an

Enterprise Resource Planning system in a University setup. The study was done at Kisii

University in Kisii County, Kenya. This location was chosen because it could provide the requisite information required according to the objectives of this research. Besides, the researcher was familiar with the institution. The target population was only confined to the students and other ERP system users like the University staff. This research belongs to education industry. It offers educational services to the citizens for building the nation.

According to Kisii University (KSU), it is a policy that a research ought to take one academic year. Therefore, this study focused on a period of one academic year between

August, 2016 and August, 2017.

1.7 Weaknesses/Limitations of the Study

One of the weaknesses of this research was that respondents could be skeptical about giving some confidential information as expected by the researcher. To counter this, they were encouraged to try as much as possible to give honest information as the research would be purely used for academic purposes only.

1.8 Operational Definition of Terms

Enterprise The Enterprise Resource Planning system in this perspective is the Resource University management information system that allows KSU to use a Planning system of integrated applications to manage their operations and automate many back office functions.

User In the context of this study it refers to a subjective psychological state of Involvement the individual and is defined as the importance and personal relevance that users attach either to a particular system or to information system in

general, depending on the user‟s focus and in this case these are University direct system users.

Project In this study, is a temporary and unique group of activities with the beginning and end in time clearly mapped out and designed to accomplish defined goals.

Project Within the context of this study, is the application of knowledge, skills, Management tools, and techniques to project activities to meet project requirements.

Change in the context of information systems project is understood as activities, Management processes, and methodologies that support employee understanding and organizational aspects during the information system projects.

Change In this study, it refers to a set of characteristics, conditions and variables Management which should be adequately sustained, maintained, or managed in order to Factors affect success factors of an organization competing in a specific industry.

1.9 Summary

This chapter describes the background of the study lucidly, the statement of the problem, the main and specific objectives of the study. Also the research questions are highlighted in this chapter. It explains the justification of the study, the significance of the study, the scope of the study and the weaknesses of the study.

CHAPTER TWO

2.0 LITERATURE REVIEW

2.1 Introduction

This chapter elucidates the theoretical framework and the empirical review used in this study. It further explains the various aspects of the research which include user involvement in the ERP systems implementation, purpose of user involvement, user factors and challenges of the ERP systems implementation in the university setup.

2.2 Theoretical Framework

This thesis was developed on the theory of Diffusion of Innovation by Rogers, (1992). The theory was used to present a theoretical stamina to the study. Besides the employment of

Diffusion of

Innovations Theory, the study further advocated for the use of Information Systems

Success (ISS) model to further review the key variables in this study.

2.2.1 Diffusion of Innovations Theory

Diffusion of Innovations (DOI) theory was infused by Everett M. Rogers in 1962 and later improved in 2009. It is a comprehensively used theory in social science disciplines. The theory has its basis in communications and seeks to explain how an idea or product gains momentum and spreads through a specific population or social environment. The result of this diffusion is that users take up the new thoughts or innovation. Adoption as brought out in the theory assumes that users react differently to an innovation compared to previous products or innovations. This facilitates the diffusion process (Wang‟ombe & Kyalo, 2015).

Diffusion of Innovations Theory postulates that theoretically, 49%-87% of the discrepancy of an innovator‟s rate of adoption is explained by its perceived attributes, type of innovation decision, and nature of social systems which the innovation is diffusing and the extent of the agents‟ promotion hard work in diffusing the innovation (Nzuki, 2012). The theory is useful to both the developers and the users of ERP systems in evaluating how these systems are implemented in various projects.

As argued by Rogers (1995), an innovation such as the use of the enterprise systems in management of higher education institutions is regarded as a technological innovation. This is realized as a result of paradigm shift to integrated information systems from stand-alone information systems. As postulated by Sahin (2006), the process of implementing new innovations as explained at length by Rogers (2009) in the book, Diffusion of Innovations, the researches cited in the publication border on various disciplines including education and technology.

The theory as highly developed by Rogers (2009) has found prevalent usage in understanding technology diffusion and adoption. As affirmed by Medlin (2001), the theory is useful in investigating the implementation of technology in higher education environments. In carrying out the research, the theory is useful in evaluating the user involvement in the implementation of the Enterprise Resource Planning systems in public universities in Kenya.

Everett Rogers‟ diffusion of innovations theory is mainly appropriate for investigating the adoption of technology in higher education and educational environments (Medlin, 2001; 14

Parisot, 1995). In fact, much diffusion research involves technological innovations so

Everett Rogers (2003) more often than not used the word “innovation” and “technology” as synonyms. Essentially according to Rogers he defines the term technology as a design for instrumental accomplishment that minimizes the uncertainty in the cause-effect relationships involved in achieving a desired result. It consists of two parts: hardware and software. Whilst hardware refers to the tool that embodies the technology in the form of a material or physical object, software refers to the information base for the tool (Rogers,

2003). Since software (as a technological innovation) has a low level of observability, its rate of adoption is quite sluggish.

According to Rogers (2003), he argues that implementation is a decision of full use of an innovation as the best course of action available whereas rejection is a decision not to adopt an innovation. Rogers explains the term diffusion as the process in which an innovation is communicated through certain channels over time among the members of a social system.

As expressed in this definition, innovation, communication channels, time, and social system are the four key components of the diffusion of innovations.

The first element of the diffusion of innovations process according to Rogers, an innovation is a thought, practice, or project that is perceived as new by an individual or other unit of adoption (Rogers, 2003). An innovation may have been invented a long time ago, but if individuals perceive it as new, then it may still be an innovation for them. The newness characteristic of an adoption is more related to the three steps (knowledge, persuasion, and decision) of the innovation-decision progression that will be discussed afterward. Besides,

Rogers claimed that there is a lack of diffusion research on technology clusters. According 15 to Everett Rogers (2003) he asserts that technology cluster consists of one or more noticeable elements of technology that are perceived as being closely interrelated.

Uncertainty is an imperative impediment to the adoption of innovations. An innovation‟s consequences may create uncertainty, for Rogers (2003) he argues that consequences are the changes that crop up in an individual or a social system due to the adoption or rejection of an innovation. To shrink the uncertainty of adopting the innovation, individuals should be informed about its merits and demerits to make them aware of all its consequences.

Further, Rogers claimed that consequences can be classified as pleasing versus detrimental

(functional or dysfunctional), direct versus indirect (immediate result or result of the immediate result), and predictable versus unpredictable (recognized and intended or not).

The second element of the diffusion of innovations process is dissemination channels.

According to Rogers (2003), communication refers to a process in which participants create and share information with one another in order to reach a mutual understanding. This dissemination occurs through channels between sources. Rogers states that a source is an individual or an institution that originates a message. A channel is the means by which a message gets from the source to the receiver.

According to Rogers (2003) he described the innovation-decision process as an information-seeking and information-processing activity, where an individual is encouraged to minimize uncertainty about the merits and demerits of an innovation. For

Rogers (2003), the innovation-decision process consists of the five phases: (1) knowledge,

(2) persuasion, (3) decision, (4) implementation, and (5) confirmation. These phases normally follow each other in a time-ordered approach.

The innovation-decision process begins with the knowledge phase. In this stage, an individual learns about the existence of innovation and seeks information about the innovation such as “Why?” “How?” and “What?” are the most significant questions in the knowledge phase. During this step, the individual attempts to establish what the innovation is and how and why it works (Rogers, 2003). According to Rogers, the questions outline three types of knowledge: (1) awareness-knowledge, (2) how-to-knowledge, and (3) principles-knowledge.

The persuasion phase happens when the individual has a pessimistic or optimistic attitude toward the innovation, but the formation of a favorable or unfavorable attitude toward an innovation does not all the time lead directly or indirectly to an adoption or rejection”

(Rogers, 2003). The individual shapes his or her attitude after he or she knows about the innovation, so the persuasion stage follows the knowledge stage in the innovation-decision process.

Furthermore, Rogers states that while the knowledge phase is more cognitive- (or knowing-

) centered, the persuasion stage is more affective- (or feeling-) centered. Thus, the individual is involved more sensitively with the innovation at the persuasion stage. The degree of uncertainty about the innovation‟s functioning and the social strengthening from others including but not limited to colleagues, peers among others affect the individual‟s opinions and beliefs about the innovation. 17

At the decision phase in the innovation-decision progression, the individual decides to implement or reject the innovation. Whereas adoption refers to the full use of an innovation as the best course of action available, rejection means not to implement an innovation

(Rogers, 2003). If an innovation has a partial trial basis, it is usually adopted more quickly, since most individuals first want to try the innovation in their own situation and then come to an implementation decision. The explicit trial can speed up the innovation-decision process. However, rejection is possible in every phase of the innovation-decision process.

Rogers expressed two types of rejection: active rejection and passive rejection. In an active rejection circumstances, an individual tries an innovation and thinks about adopting it, but later he or she decides not to adopt it. In a passive rejection (or non-adoption) situation, the individual does not think about adopting the innovation at all.

An innovation is put into practice, which is at the implementation phase. On the other hand, an innovation brings the newness in which some degree of uncertainty is involved in diffusion. Indecision about the result of the innovation still can be a predicament at this step. As a consequence, the implementer may need technical assistance from change agents and others to diminish the degree of uncertainty about the consequences. Furthermore, the innovation-decision process will end, since the innovation loses its distinctive quality as the separate identity of the new idea disappears (Rogers, 2003).

This research borrows heavily from the third (decision) and fourth (implementation) steps in the Diffusion of Innovation theory. With the employment of the ERP systems in the management of public universities in Kenya interpreted as an innovative line of attack in 18 the study, diverse institutions are assumed to have undergone the first, second, and third processes in the diffusion of innovations theory as advanced by Rogers (2009). These include gathering knowledge about the ERP systems, persuading stakeholders to support the selected systems in automating their institutional operations and making the decision to implement the systems. While guided by the diffusion of innovations theory, the researcher sought to establish the user involvement experiences during the implementation phase of the ERP systems in public universities.

DOI theory explains the relation between the system users and the implementation of the information systems hence informing the study.Kisii university being one of the public universities in Kenya, it has not been left behind too in the implementation and with sufficient involvement of users in the implementation of the ERP system it can substantially improve its performance.

2.2.2 Information Systems Success Model

Further, this research besides employing Diffusion of Innovation Theory, it also engaged

Information Systems success Model. This research employed Information Systems Success model. The information systems success model as highly developed by DeLone and

McLean (2009) is based on earlier research in communications by Shannon and Weaver as well Mason‟s theory on Information Influence. As highlighted in the model, three key pillars of information systems success are advanced. These embrace System Quality,

Information Quality and Service Quality. The original D&M Information System Success

Model was subsequently sophisticated to include net benefits as a gauge of success (Delone

& Mclean, 2014). Figure 2.1 shows the information system success model.

Figure 2.1: IS Success Model (DeLone& McLean, 1992)

The theoretical model makes use of a causal relationship to scrutinize the success of the implementation of information systems in public universities. Information Systems Success

Model as revised by DeLone and McLean constitutes of six interrelated dimensions which influence success in implementation of an information system. These include information quality, system quality and service quality as independent factors. These influence the intention to use, user satisfaction and net benefits derived from implementation of an information system.

The information systems success model was useful in studying integrated institutional management information systems and their usage in public universities in Kenya. By using the model, the objectives of the research study were best addressed to ascertain not only challenges but also both user involvement and user factors in deployment of these systems in the management of public universities.

ISS has a strong connection between the system, information and service quality and the implementation success of the ERP systems. ISS evolved from TAM hence the researcher thought it wise to briefly mention of the technology acceptance model.

2.2.3 Technology Acceptance Model

In 1985 Fred Davis proposed the Technology Acceptance Model in his doctoral thesis

(Davis, 1985). He proposed that system use is a response that can be explained or predicted by user motivation, which in turn is directly influenced by an external stimulus consisting of the actual system‟s features and capabilities. Davis further refined his conceptual model and suggested that user motivation can be explained by three factors: Perceived Ease of

Use, Perceived Usefulness, and Attitude toward using the System. He hypothesized that the attitude of a user toward a system was a major determinant of whether the user will actually use or reject the system. The attitude of the user, in turn was considered to be influenced by two major beliefs: perceived usefulness and perceived ease of use, with perceived ease of use having a direct influence on perceived usefulness (Chuttur, 2009).

2.3 Empirical Review

Enterprise Resource Planning systems have found prevalent usage in large organizations across diverse continents. To continue with the management anxiety in the 21st century as noted by Nyandiere et al. (2012), universities have turned to ERPs to replace their stand- alone systems. The fact that initial implementation was noted in manufacturing industries; universities have implemented the systems to provide institutional-wide automation for their operations (Ferrell, 2009). This has helped them to automate their core business areas in student administration, finance, staffing, and client management among others. Upon implementation, these systems are expected to provide increased efficiency and effectiveness of operations, shrink overhead costs in ICT, make decision better, and improve resource management as well as building business innovation whilst supporting strategic change (Sullivan & Bozeman, 2010).

As affirmed by Davenport (2009), Enterprise Resource Planning systems provide flawless incorporation of all information flowing through a company‟s departments. With the faultless integration of information within institutions, managers are able to overcome the challenges emanating from incompatible systems and inconsistent operating activities.

Acquisition of these systems may be through commercial off-the-shelf systems or custom designed systems in line with a university‟s requirements.

Prior research in the implementation of ERP systems in educational institutions have focused more on the benefits that an institution can realize from adopting an Enterprise

Resource Planning system. In contrary, more literature on pitfalls facing these implementation experiences needs to be highlighted to inform current and future adoption of ERP systems in university administration (Yetton & Sharma, 2009).

According to Verville and Halingten (2009), Enterprise Resource Planning systems are used to bond back-office operations such financial and human resources into one system. In the recent decade, Enterprise Resource Planning has evolved to a suite of application modules that are used to link back-office operations to front-office operation as well as internal and external supply chains. They conjoin functional units and business operations in a flawless integrated environment. This provides a wider scope for applicability to organizations. ERP systems have gained pervasive usage in large corporations and institutions across the world. In modern trends witnessed in higher education as argued out by Zornada (2005), universities have turned to ERP systems as a means of substituting existing management and administration techniques by use of computer systems. 22

According to Pollock (2004), in a research whose objective was on the ERP systems use in a UK university points out that the uniqueness of a university set up makes most business

ERP systems irreconcilable with their operations. This necessitates a custom development of a system well-matched with the structure and functions of a specific university. The choice of either a custom development or adoption of a readily available system should be informed by informed by a thorough systems analysis and design evaluation while putting the institutional strategic objectives into deliberation (Basoglu &Kerimoglu, 2007). This can be achieved by drawing up a rigorous implementation framework to guide the processes.

Realization of Enterprise Resource Planning systems in institutions is a challenging process. A diversity of factors influences success rates in implementation of ERP systems from one organization to another. Through the current in quest to establishing the impact of some of these factors in implementation of Enterprise Resource Planning systems in public universities in Kenya, prior research in developed societies such as Shah et al. (2011) alluded that factors such as top management support, user involvement, vendor support, overlooking of change management aspects, turnover of vendors team member, transfer of top management in benefactor institutions as vital factors affecting successful implementation of the ERP systems in organizations. Other factors recognized include project cost overruns and delayed project schedules and their effect on user needs.

Implementation of ERP systems requires radical change to the existing work processes and such change requires to be managed for its success. Earlier researches have indicated that 23 successful implementation of Enterprise Resource Planning systems in institutions is anxious with the extent of mutual fit between an ERP system selected and business processes in an institution (Olson, 2004). Other research such as Nah et al. (2001) identifies a range of challenges that organizations face during ERP implementation. These if reviewed by universities provide valuable resources to inform their implementation processes and circumvent prospective pitfalls. These challenges engross people, processes and technology used in the implementation processes.

Implementation of the ERP systems in public universities is not a technology but a personnel project (Leon, 2008). In this view, consideration is given to the role of users in determining the implementation of an Enterprise Planning System. Zhang et al., (2002) further puts it that user involvement at initial stages of ERP system implementation is helpful in inferring a system so as to provide helpful response.

Hartwich and Barki (2001) elucidate user involvement as a psychological position of the individual and as the significance and personal consequence of an ERP system deployment to a user. In radiance of this, user participation in defining requirements and implementation of ERP systems in public universities is fundamental especially in improving service delivery. Matching user needs to choice of system used, service requirements and functional abilities of the chosen system are indispensable in determining the success in implementation of an Enterprise Resource Planning system (Motwani et al.,

2005).

Acquisition of established custom computer systems for institutional information convergence is a famous trend in universities across the world. As affirmed by Pollock,

(2004), many universities are adapting all-purpose solutions to their integrated management information system requirements. To this end, use of general software systems to meet the largest scope possible for their activities and processes is implemented. This is aimed at providing a host of management solutions which embrace cost savings, expediting processes and improving access through dependable platforms. However, accomplishment of these objectives is likely to vary from one institution to another and formed part of the research study in the Kenyan context.

2.4 User Involvement in ERP Systems Implementation

Another challenge institutions encounters refers to the decision on the extent of users‟ involvement during the implementation process. Lack of user involvement is noted as a leading cause of user confrontation (Aloini et al, 2007; Barker & Frolick, 2003; Shah et al,

2011). Aloini et al. (2007) classifies limited user involvement as a threat factor negatively impacting the implementation outcome.

Plentiful factors may affect the ERP adoption in organizations (Shah et al., 2011). These factors include user involvement (Francoise et al., 2009; Rasmy et al., 2005). The involvement of the users during the phase of defining organizational information needs may decrease the resistance of users towards the ERP system implementation (Motwani et al., 2005). The user involvement may lead to better user requirements, achieving better quality system and system usage (Motwani et al., 2005).

User Involvement (UI) and User Participation (UP) on information system projects have been studied for over 30 years. Melville et al (2004) confirms that the use of Enterprise

Resource Planning systems in higher education institutions is advantageous to their performance. There is a general assumption that UI of some sort is valuable to ERP system success (Nah & Delgado, 2006; Wagner & Piccoli, 2007) even to the point of calling it an

“institutionalized practice” (Howcroft & Wilson, 2003).

Research done at Turkey shows that user Involvement (UI) “can be defined as a subjective psychological state of the individual and is explained as the importance and personal relevance that users attach either to a particular system or to information system in general, depending on the user‟s spotlight” (Barki &Hartwick, 2008). Subsequent study has confirmed this definition and empirically supported this separate construct (Hartwick and

Barki, 2008; Kappelman& McLean, 2003).

Recent research by Hsu et al. (2013) is commencing to take into account information system development from a service provider perspective as consumers have become more involved with the design, development, and implementation of these systems. User involvement in information systems implementation efforts may begin by assuming that such participation will provide valuable input to various technical decisions to be made.

However, their participation may have a greater value because those decisions are more socio-technical than purely technological practice (Damodaran, 1996; Wang et al, 2006).

According to Harris and Weistroffer (2009) based on the meta-analysis of 28 papers finds substantive evidence for user involvement to positively impacting user satisfaction which 26 they argue is a proxy for system success. Chen et al. (2011) advocates that significant components of UP can provide further insights into the impact of user participation, such as user (decision-making capabilities) positively impacting information system operation quality.

This study is substantiated by Ives and Olson‟s (1984) statement that “the benefits of user involvement have not been strongly demonstrated”. Numerous researches of this topic have been performed in the last thirty years on this topic that generally support the benefits of user involvement, but there are still a number of studies that report insignificant or conflicting results.

2.4.1 User Participation

Involving those affected by the changes in planning and implementation (Salminen, 2000).

People on all levels and in all parts of the organization have an opportunity to actually affect the solutions implemented. Poorly managed participation may have negative motivational impacts. This author recognized the downside of change, and stated that whenever human communities are forced to adjust to shifting conditions, pain is ever- present and he goes on to say that managers and organizations also make mistakes in developing and implementing the change efforts.

2.4.2 Purpose of User Involvement

A study done at Cleveland State University in US, by Swanson (1974) identifies the

“famous wisdom” that “management should be „involved‟ in MIS development and implementation, unfortunately, what is meant by involvement is rarely vivid”. The author did advocate that the measurement of involvement should be based on their functions

27 whether as a user or as a facilitator of its development. Ten years later, Ives and Olson

(1984) affirmed the same in their critical study of user involvement. The authors separate the extent of participation from the type of participation but note the research needs to develop a standard gauge of user involvement.

The Standish Group (PM Hut, 2009) routinely surveys project success and always finds that more projects are deemed to be failures than successes. Verner et al. (2005) asserted that the Standish Group has often quoted the lack of user involvement as a contributor to the high number of failures in the implementation of the Enterprise Resource Planning systems.

2.4.3 Define Roles in Information System Projects

According to (Salminen, 2000) he argues that defining roles and organization during the change process is of great importance. Responsibilities and authorities in the change process are clearly defined, the change project organization facilitates participation and effective control, and everyone knows what his/her role is during the change. Barczak et al.

(2006) outlined that "clearly defined roles and responsibilities enable individual team members to know what their particular tasks are … and hold each responsible for those activities". The roles, responsibilities and authorities are clearly defined and communicated during the change process.

It has been asserted that implementing an information system is actually a change project.

Cameron and Green (2004) express it in this way: “Information Technology based change) involves people doing special things in different ways, with different inputs and different

28 outputs”. Cameron and Green (2004) accordingly believe that it would be important for information technology people to learn about managing change and to understand what organizational change actually is.

Research conducted in China demonstrates that user roles (the titles, positions, or responsibilities held on projects) are generally not well understood. Leonard (2004) notes that users are often regarded as “an inferior party” by information technology gurus. Iivari et al (2010) diminish the user role to that of a static entity, a source of individual task productivity, regardless of how the user is defined. This may be compelling for research because of its simplicity, but it ignores social, organizational and technical factors.

Hsu et al. (2010) argues that effective UI (as measured by “quality interactions” that allow users some extent of control over the development process) influences project outcomes.

Similarly, Chen et al., (2011) and Havelka and Rajkumar (2006) attests that ambiguous role definitions may negatively impact UP. As a result, research efforts have been made to improve the basic constructs of a user‟s role.

In America, Ives and Olson (1984) noted two roles: primary users (use the output) and secondary users (generate input or run the system). Damodaran (1996) identifies multiple user roles: resource pool of user expertise, “Top management”, “Middle management”, user representatives and end-users. Mahanti (2006) affirms a number of stakeholders including executives, middle management, customers, developers, testers, analysts, finance personnel, and HR representatives. Kearns (2007) exclusively studies the executive manager.

Keil and Robey (1999) studied how troubled software development projects became troubled projects. They identified six roles that helped trigger de-escalation of the project‟s priority: top management, internal information system auditor, external auditor / consultant, information system users, information system project team member and information system management. Howcroft and Wilson (2003) suggest three roles in participatory practices: manager, employee and developer. Tudhope et al. (2000) suggest various user roles within the rapid application development methodology; these include the executive sponsor, visionary (business analyst), ambassador (user representative) and advisor (end users).

A study of Enterprise Resource Planning system implementations promotes two types of external roles: consultant and vendor (Wang et al, 2008). Developers can state that they try to keep user requirements in mind while they work, but this has been deemed to be insufficient in practice (Iivari, 2009). Jiang et al. (2000) study of project risks used three types of constituents: management, users and IT staff.

Upton and Staats (2008) accentuate the importance of chief executive officer-level involvement in strategic information technology projects. Kamadjeu et al. (2005) document the significance of executive sponsorship and support on overall project success. However,

Biffl et al. (2006) suggest that extra effort may be necessary to mentor loosely engaged executives into becoming active participants. Wu &Wang (2006) outlines four user roles in their study of ERP project success: managers and stakeholders, customers, suppliers, and employees.

Millerand and Baker (2010) affirm that user and developer roles are not static and should not be defined as such no matter how convenient for the researcher. They draw on organizational theory which acknowledges that users can have multiple simultaneous roles which they identify as user representatives, co-developers, and co-users. This multiple role play is designated “enactment” in their theory development section which contributes to their Integrative Design Model. Further, these users can have multiple relationships that include objects, actions and settings.

Terry (2008) reports on a survey of an electronic commerce projects that highlight new characteristics of users given the advent of electronic business or internet technologies. The study of forty-four recently completed projects considers a new user type named “customer users” described as remote customers who may not be known to the organization. They are the ultimate end-users, but are beyond the accepted definition of users, they are not staff and do not fall under the control structures of the organization.

The most frequently studied roles are internal user roles such as users, customers, management, and representatives. The two roles that are noted in more than half of the papers surveyed are users and executive management. These separate roles are important to

IS practitioners because the communication provided to each group varies based on their information needs and their potential level of influence on the project. The second most studied roles are internal information system staff such as developers, testers, analysts, and project managers. Harris and Weistroffer (2009) suggest that ERP system complexity increases the need for increased user involvement to capture the right requirements.

The challenges of dealing with individual and group issues are impacted by role perceptions as a result to increasingly diverse workforce issues, and could well be noted by the abdication of performance management tasks, and hypersensitivity towards multiplicity issues – to the point of paralysis – in supervising performance (Arumugam, 2001).

He additionally alludes to the fact that there tends to be a gap between the formal and informal cultures, resulting in mixed perceptions of end-users to the system. This tends to create conflict and causes end-users to take the path of least resistance; this often tends to generate mediocre performance.

2.5 User Factors

Self-efficacy is described as a person‟s belief that they own the capacity to act in a specific manner (Dennis et al., 2009). User self-efficacy can be recognized as a self-motivator.

People who are extremely confident of their abilities to share beneficial understanding are more inclined to impart that information to others with the certainty that the knowledge they share will lend a hand to resolve issues or improve performance (Liao, & Hsu, 2013).

The user‟s attitude is to learn and use of software only when the top management support and make available appropriate incentive for that. By implementation of ERP, the organization work can be done easily and a better way. The employees can customize their work as per organizational requirements.

Trust is a much-debated factor that always facilitates system implementation between two entities (Saba et al, 2012). Within the context of online social media based information sharing, trust is an initial condition required by communities to participate and share their

32 ideas and opinions. The existence of trust plays an important role in cheering system adoption among members (Chai & Kim, 2010).

Enjoyment in helping others refers to a motivation to help others without expectation of a return (Papadopoulos et al, 2013). In a review of the literature on system implementation, enjoyment in helping others is described as self-sacrifice (Svetlik et al, 2007). Altruism is defined as deliberate helping actions where a person attempts to improve the wellbeing of others at some cost to oneself (Ma & Chan, 2014).

According to Chuttur (2009), experience is prior familiarity of an individual with a specific technology. According to Igbaria and Iivari (1995), experience is gauged by using items such as: I have experience in using the systems, I have experience in using SPSS, I have experience in using word circuit maker software, I take part in feasibility studies, I am involved in requirements analysis, I have experience in using Lisrel for students, I have experience in using java and python programming languages, and I contribute in design of computerized information systems.

Getting people encouraged and committed to changes through active motivational hard work (Salminen, 2000). Those in charge of the changes guarantee the commitment of people through making the goals pleasing and the process trustworthy and actively promoting the significance of the changes in all possible instances. Embracing of new practices and sustains the change (Grover &Kettinger, 2000).

According to Arumugam (2001), he disputes that being short of celebration when success and extreme results have been achieved, tends to promote bad performance. The symptoms and consequences include perceptions amongst employees that merit in performance is not valued, blaming and hiding becoming the principal defense mechanism originality, innovation and personal growth are thereby fruitless a culture of mediocre performance can result just to dwell out of trouble.

2.6 Challenges of the ERP Implementation in University

Shehab et al. (2004), note out that although organizations spend millions on ERP packages and implementation process, there is widespread evidence that they experience substantial problems, particularly during the concrete implementation. Diverse challenges that organizations commonly faced during the ERP implementation had been addressed in the past research (Spitze, 2001; Thavapragasam, 2003). A study done in New Zealand by Leon

(2008) mentioned that 69%, 28% and 13% failure rate of the ERP systems due to people, process and technological troubles in that order. It reveals that people problems are more critical as opposed to the rest ones.

2.6.1 Conflicts between User Department

Sufficient functional coordination is taken as one key challenges faced by organizations, as lack of synchronization amongst different business units and stakeholders is often enlisted as one of the factors leading to implementation delays and organizational conflicts, eventually leading to implementation failure (Kim et al., 2005). Conflict of interest between different functional units and a lack of resource commitment are highlighted as vital challenges associated to the ERP system implementation failure (Kim et al., 2005).

Institutional processes must be compactly integrated, jobs redesigned and new procedures created throughout the institution.

The complete process of change is demanding and employees are often unprepared for new procedures and roles (Rishi &Goyal, 2008; Laudon &Laudon, 2006, 2000). Also, there is an issue of information sharing, which may contradict existing practices and culture

(O'Brien, 1997). Coleman (n.d.) captures the key problems in his piece of writing “ERP incorporation options". The problem of integrating the ERP applications is as old as ERP itself. Not long after the ERP suites first debuted in the early 1990s touted panaceas for corporate integration woes companies have struggled to improve the level of integration between their ERP packages and other applications such as legacy systems and institutional sites.

2.6.2 Attempts to Build Bridges to Legacy Systems

Strategies aiming to surmount this perceived drawback either opt to maintain use of the legacy solution, system configuration to integrate add-on modules to the original ERP solution (Kumar et al., 2003). Berente et al. (2009) puts it that integration of existing stand- alone information systems with ERP systems is a major challenge for many organizations.

This is further complicated by the fact that ERP systems also seek to integrate business processes in organizations which were previously functional-based.

Thus, the process-orientation resulting from operational integration is against the functional differentiation which is common in traditional organizations. While client/server and open

35 systems solve some technical difficulties, there are still troubles of integrating different types of data and procedures used by functional areas.

2.6.3 Inadequate Effective Project Management Methodology

Laudon and Laudon (2006), asserts that most managers are skilled to manage a product line, a division, or an office. Their argument is substantiated by (Rishi & Goyal, 2008).

They are hardly trained to optimize the performance of the organization as holistic as possible. However, Bingi et al. (2002) argues that the Enterprise Resource Planning systems require managers to take a much larger view of their own actions, to include other products, divisions, departments and even outside business firms.

The literature study robustly suggests that transformation is an unavoidable consequence of implementing various projects (Hornstein, 2014; Serra &Kunc, 2014). A project is an impermanent and unique group of activities with the commencement and ending time clearly mapped out and designed to realize defined goals (PMI, 2013). Although project management (PM) and change management are derived from different terminologies and different methodologies (Hornstein, 2014), they are, nevertheless, tightly associated and co- dependent. They also emphasize different sets of skills and competencies (Crawford,

&Hassner-Nahmias, 2010).

According to the Project Management Institute (PMI), project management is the application of knowledge, skills, tools, and techniques to project activities to satiate project requirements. It is accomplished through the application and integration of project

36 management processes such as initiating, planning, executing, monitoring, controlling and closing (PMI, 2013).

2.6.4 Effective Communication

Without proper communication, the employees involved in the change management would not know what changes were made, what changes are being made, what changes should be made. Besides, the employees would not be aware of their tasks related to the implemented changes. Communicating the message frequently up, down, and across the organization is necessary to ensure that the momentum and enthusiasm for change does not reduce over a time period (Graetz, 2000). Communication by top management is seen as a powerful influence in gaining commitment and building agreement about the required change

(Kotter, 1995).

2.6.5 Misunderstanding of Change Requirements

As cited by Umble et al. (2009), ERP system implementation is not just a software project but an institutional change project. The projects call for co-operation, teamwork, and planning for organizational change are difficult to do when top management is too busy to give the project satisfactory attention.

Wagner et al. (2006) further alludes that installing ERP systems successfully is not an easy task because of the key changes to an institution's business processes required by ERP software. The projects bring about enormous organizational changes as they consist of many functional modules that can span the entire organization and yet share a common database. Because departments are part of a larger organization, they are obligatory to share

37 systems and act not as independent units but as a larger organization, requiring a whole new understanding of their work (O'Brien, 1997).

Change management is required in separately functional areas, where the systems are to be applied, such as human resources, training department and the programme management office (Journal of Information Technology, 2009). Changes must be efficiently planned, scheduled, carried out, and documented, in order to minimize the cost and disruption during the implementation process (Van Tonder, 2004).

Identifying and communicating the reasons for the change (Salminen, 2000). Problems or opportunities requiring the changes are demonstrated clearly through analysis and practical examples and a shared feeling of necessity of changes is created (Salminen, 2000). A well- communicated shared understanding of the need for change was found to be one of the topmost success factors in the ERP implementation context in Australian practitioners‟ understanding (Hawking et al, 2005).

In Kenya, the prior studies on change management did not concentrate on the specific contextual characteristics of public organizations (Kuipers et al., 2014). However, an interesting change management in public organizations has been noted (Fernandez & Pitts,

2007; Fernandez &Rainey, 2006).

Recent studies have questioned the fact that change management techniques for the private sector are applicable in the public organization context and have suggested that the

38 differences between the public and private sector could play a significant role in this respect

(Boyne, 2006; Karp &Helgo, 2008; Kickert, 2013; Klarner et al, 2008; Rusaw, 2007).

A recent literature review of research on change management in the public universities sector by Kuipers et al. (2014) found that most studies emphasize the content and context of change, instead of the implementation process. Ubiquitous information systems and implementation of various kinds of changes related with information systems adoption have become a challenge for public organizations (Jääskeläinen &Sillanpää, 2013). However, the processes through which the change in public organizations comes about are not described in detail in the literature (Kickert, 2010; Kuipers et al., 2014).

The behavior and actions of the person or persons leading the change (Salminen, 2000).

“An active and enthusiastic leader, who believes in the significance of the change, shows the way and motivates others through his/her own behavior” (Salminen, 2000). A project promoter, as a responsibility, is particularly handy in the early phases and during implementation phase (Aloini et al., 2007).

In some cases, the project champion role is vital for marketing the project throughout the organization (Al-Mudimigh, 2007). The leader/leaders of change are committed to the change, active, enthusiastic, inspires others to believe in and act on the change through their behavior. Leadership can be extended to the functional organization by recruiting and training change coaches across the organization.

2.6.5 Failure to Redesign Business Process

Implementing an ERP system entails business process reengineering to ensure standardization and optimization of an organization‟s business processes in an attempt to obtain maximum benefits through the use of the embedded best practices of the ERP solution (Bingi et al., 1999; Davenport et al., 2004). Nonetheless, a lack of business process reengineering is also considered as a CFF (Amid et al, 2012; Hawari & Heeks,

2010; Umble et al., 2003; Wong et al., 2005).

Whereas an organization may even prefer to reengineer its processes completely to adapt to the new best practice standard as embedded by the ERP system (Kumar et al., 2003), the underlying complexity is that the proposed solution will not match the whole organizational needs (Davenport, 1998). The reality is that an ERP solution may lack key functionalities which are needed to connect all the required business processes of an enterprise (Kim et al.,

2005; Kumar et al., 2003).

As such organizations face different problems with ERP that customized system development owing to the need to change their organizational practices in order to fit the software `unsurpassed practices' (Davenport, 1998; Pollock & Conford, 2004; Wagner &

Newell, 2004; Light, 2005b; Chiasson & Green, 2007). ERP systems thus incorporate values and practices that may not essentially match all environments.

2.6.6 Composition of Project Team Members

Consolidating a balanced, dedicated team comprising of the most experienced, most knowledgeable people from various functional units is paramount for a successful ERP

40 implementation (Gargeya & Brady, 2005). An organization‟s inability to build the right team as a result of the shortage of required ERP knowledge that the assigned implementation team should possess is a noted significant human resource impediment.

Employees in a reasonable team should possess both technical expertise and business

(Barker & Frolick, 2003; Chen et al., 2009; Gargeya & Brady, 2005; Kamhawi, 2008; Kim et al., 2005). In effect, organizations make an effort to recognize the different qualities and skills that are required and to successfully acquire and integrate the different skills set and knowledge of people throughout the ERP phases (Chan, 1999). As a result of management‟s failure to source critical IT skills due to the perceived lack of in-house skills, organizations have to increasingly rely on external consultants to fill in the experienced gap

(Chen et al., 2009).

Well, project team competence is ranked as one of the topmost CSFs by Somers and

Nelson, (2004). Soja (2011) argues that a lack of personnel skills and knowledge is more repeatedly categorized as a critical challenge but seldom classified as a CSF. This is attributed to an organization‟s tendency to assume, de facto, that enough qualified resources will be allocated to the implementation project (Soja, 2011). The lack of accessibility and commitment of qualified resources during the different stages of an ERP implementation poses another major hitch to the organization (Somers & Nelson, 2001).

2.7 ERP System Implementation Factors

This subheading explains the various critical success factors in the implementation of the

ERP systems.

2.7.1 Detailed Knowledge of the Organization and Legacy Systems

Umble et al (2003), doesn‟t seem to give a lot of importance to this factor. But Nah et al. believe that the knowledge of the organization is required for change planning and knowledge of legacy systems is needed to create an appropriate business and IT system

(Nah et al., 2001). Hong et al. also give importance by analyzing this under the organizational fit factors (Hong& Kim, 2002), whereas Holland et al, says that without a proper understanding of the legacy systems there cannot be a successful implementation of an ERP project. It is of an immense importance that organizations understand that they need to recognize their business processes for the purpose of fitness between the ERP package and the overall business strategy of the organization.

Legacy systems also have to be carefully evaluated and defined to determine the nature and scale of the problems that the organization may come across during the implementation.

Some authors (like Bradley) also link a complete management function that will choose the right system according to the legacy systems in place. According to Finney, the consideration of legacy systems is a tactical factor during the implementation of ERP systems. (Al-Mashari, Al-Mudimigh, & Zairi, 2003; Bradley, 2008; Ehie & Madsen, 2005;

Finney & Corbe, 2007; Han, Liu, Swanner, & Yang, 2010; Hawking, 2007; Ngai, Law, &

Wat, 2008; Shaul &Tauber, 2013; Wong &Tein, 2003).

2.7.2 Having a Clear and Concise Strategy

It is obvious that all the four authors analyzed when this factor was derived agree that a company will not be successful during ERP implementation if it does not have a clear list of strategic goals. Clear goals, clear objectives, the business vision and mission, strategic

42 plans, focus and scope are factor in most authors that deal with critical success factors

(Akkermans & van Helden, 2002; Al-Fawaz, Al-Salti, & Eldabi, 2008; Al-Mashari et al.,2003; Bradley, 2008; Finney & Corbett, 2007; Hanafizadeh & Ravasan, 2011).

2.7.3 Having Top Management Sponsorship

This factor is of immense importance for every large scale project, and especially IT project for one organization (Laudon & Laudon, 2012). According to Akkerman, if the top management is not actively backing up the ERP project there is little hope that the project will be successful. Bradley adds it in the leading management function where he states that top management is not just involved, but engaged, and the support can come in form of bonuses tied with success or in any other form. Appropriate involvement of the top management is also described by

Somers, who proposes that a steering committee if formed consisting of senior management from across different functions, project management representatives, and end users who will have daily contact with the ERP. One thing is in common, without top management sponsorship, ERP project have little chance of success. (Akkermans & van Helden, 2002;

Bradley, 2008; Ehie& Madsen, 2005; Finney & Corbett, 2007).

2.7.4 Following Top-Notch Project Management Practices and Process Management

Practices for BPR

It sounds very obvious that a project will not succeed if it does not follow practices of the project management, as well as that a major project such as an ERP requires business process reengineering to improve the functionality of the software in accordance with the needs of the organization. According to Somers (2001), “minimal customization Fortune

1000 companies regarding ERP customization policies indicates that 41% of the companies re-engineer their business to fit the application, 37%of the companies choose applications that fit their business and customize a bit, and only5% customize the application to fit their business” which shows the importance of customization of the business processes in the organization (Somers & Nelson,2001). Ngai states that organizations should reengineer business processes to fit the software instead of trying to modify the software to fit the organizations current business processes.

2.7.5 Following Top-Notch Change Management Practices

According to Umble (2003), practice for change management is required since ERP implementation enforces BPR of key processes within organizations. Hong does give a slight importance mentioned under the ERP adaptation process as well as process adaptation, whereas Holland implies that change management is important especially for client acceptance of the project. Change management involves the effective balancing of forces in favor of a change over forces of resistance (Ngai et al., 2008). Thus training and education become imperative in the change management process. According to Mashari

(2003), “it is estimated that about half of enterprise system projects fail to achieve hoped- for benefits, because managers significantly underestimate the efforts required to manage effectively the wide range of changes involved” (Al-Mashari et al., 2003).

2.7.6 Creating Clear Procedures for Data Entry and Accuracy

Data management seems to be one of the new factors which are not included in Nah et al, study. It looks like more and more there is a need for validating the data and converts the data into single and consistent format before the system is used. Umble (2003) states that data quality has to be established for accuracy, and Hong mentions it not very significantly

44 under the factor organizational fit. However, Somers seems to give an importance to data quality and conversion. Similarly, Shaul, under data management states that there is a need for the organization to create a data analysis plan, quality control, migration and data cleansing as well as data accuracy. Finney considers this factor as tactical under the data conversion and integrity (Finney & Corbett, 2007; Ngai et al., 2008; Shaul&Tauber, 2013;

Somers & Nelson, 2001).

2.7.7 Conduction Training and Streamlining the Communication

According to Umble (2003), one of the most recognized CSF for enabling people to work with the system is the training in all levels of the organization. Hong doesn‟t seem to give importance to this factor, whereas Nah and Holland point to effective communication as a success factor. Communication includes formal promotion of ERP project teams and announcement (Ngai et al., 2008). Moreover, communication has to cover the scope, objectives and tasks of an ERP implementation project (Al-Mashari et al., 2003). They place communication under his style factors, whereas Wong et al, place three CSF for training and communication. Bradley from the management perspective in the leading function gives and importance to management education, communication and expectations, as well as the communication between the team and the rest of the organization as a success factor for ERP implementation.

2.7.8 Creating Performance Measures

Measures of performance for the new system that will be established take a critical role in

ERP implementation success. Successful management of user experiences is found to be related with successful system implementation (Somers & Nelson, 2001). Through monitoring and feedback from the users, the performance of the ERP system can be

45 reviewed and evaluated to see whether it is realizing the goals and objectives of the business (Nah et al., 2001, Ngai et al., 2008; Umble et al., 2003). According to Mashari

(2003), “measuring and evaluating performance is a very critical factor for ensuring the success of any business organization and indeed for making IT systems such as ERP pay back” and “it is advisable that regular auditing and benchmarking are considered for optimization of the potential” (Al-Mashari et al., 2003). Shaul points out to several acceptance control mechanisms like performance metrics, progress against a milestone and feedback management.

2.7.9 Deciding on the Implementation Approach

Implementation approach might lead to issues of multi-sites, so system integration becomes important due to the cross-module integration nature of the system (Al-Mashari et al.,

2003; Umble et al., 2003). Software development, configuration, testing and troubleshooting are commonly mentioned. Some authors for the implementation approach consider the vendor selection process as important factor, as a good vendorcan provide support ranging from technical assistance to training (Akkermans & vanHelden, 2002; Ngai et al., 2008; Somers & Nelson, 2001).

2.8 Computer Self-Efficacy

With the advent of Social Cognitive Theory came a transformation in the way investigators approached behavioral research. Prior to the Social Cognitive Theory, behavior was presumed to be influenced primarily by environmental factors, such as expected outcomes.

In his “Unifying Theory of Behavioral Change,” Bandura (1977) introduced a cognitive factor, self-efficacy, into behavioral theory. He suggested that humans were not driven

46 exclusively by environmental factors, but rather that a “triadic reciprocal causation” existed between environmental events, cognitive factors, and behavior (Wood and Bandura, 1989).

He identified four sources of information that interact to develop self-efficacy expectations, which, in turn, affect outcome expectations and behavior: performance accomplishments, vicarious experience, verbal persuasion, and emotional arousal.

2.8.1 Performance Accomplishments

Performance accomplishments represent the reciprocity of the Social Cognitive Model.

That is, prior behaviors, or “accomplishments,” influence future behaviors via their effects on outcome expectations and self-efficacy. Through examination of this single relationship, behavioral change is an endless cycle of performance and feedback. Unfortunately, this recursive process is analytically untestable. That is, in one instance, self-efficacy and outcome expectations are the presumed causes of behavior. In the same model, behavior is the presumed cause of self-efficacy and outcome expectations. Assuming that self-efficacy and outcome expectations are exogenous constructs and that behavior is an endogenous construct, or even vice versa, this relationship is not statistically viable. Even the most sophisticated statistical modeling techniques cannot reconcile non-recursive path models between latent endogenous variables and latent exogenous variables (Pedhazur & Smelkin,

1991).

2.8.2 Vicarious Experience

Inherent in vicarious experience is the assumption that individuals identify with the model.

Much in the same way that a person watches an actor on television and emotionally

“becomes” that character for the duration of the show, a person increases or decreases his

47 own self efficacy by observing a model and sharing the model‟s feelings of success or failure when executing a task. The usefulness of vicarious experience, however, lies in the similarity of the model and the observer (Brown & Inouye, 1978).

2.8.3 Verbal Persuasion

Verbal persuasion, the next factor in Bandura‟s model, is used to enhance performance and build self-efficacy through guided encouragement. Verbal persuasion is an extremely powerful technique for changing behavior and is prevalent in much of psychotherapy today.

In fact, Wood and Bandura (1989) caution against persuading individuals to undertake behaviors that they are not physically or emotionally ready to perform. Verbal persuasion is effective in increasing self-efficacy and changing behavior only when the individual is truly capable of performing the behavior.

2.8.4 Psychological State

Typically associated with emotions such as anxiety and fear, emotional arousal is one of the major obstacles in behavioral change as it produces a condition known as avoidance behavior.

Avoidance behavior is the active or passive resistance of activities deemed as fearful, stressful, or otherwise ineffective and is especially sensitive to manipulation of the three factors discussed above (e.g. prior performance, vicarious experience, and verbal persuasion). Also termed “learned helplessness,” avoidance behavior occurs when people cease trying because they doubt their own abilities or because they deem their efforts to be futile in an “unresponsive environment” (Bandura, 1977).

2.9 Conceptual Framework

This refers to when a researcher conceptualizes the relationship between variables involved in the study and shows the relationship graphically or diagrammatically. The rationale of a conceptual model is to facilitate the reader to quickly see the proposed relationships

(Ashutosh Varshney, 2010).

The conceptual framework was formulated from the researcher‟s title. The relationship of the three variables involved in the study which includes the independent, dependent and the moderating variables is depicted in figure 2.2.

Independent Variable Dependent Variable

User Involvement in ERP Implementation

-Extent of User Level of ERP System Implementation Involvement Success -User Factors

Implementation Challenges

Moderating Variable

Figure 2.2: Conceptual Framework

As McGaghie et al. (2001) puts it that a conceptual framework “sets the theater “for the presentation of the particular research question that drives the investigation being reported based on the problem statement. The statement of the problem of a thesis presents the 49 context and the issues that caused the researcher to conduct the study. For academics, this may lead to fear that the use of a new system that results in increased transparency of their transactions would result in a loss of control. On the other hand, administrative staff may fear for their job security when redundant processes are eliminated work functions are automated across a university (Allen et al., 2002).

Employees „involvement is the degree to which employees participate in the improvement activities. By engaging employees in the implementation processes, they identify more with the success. Employees‟ participation is a degree to which employees believe they can make decisions about how they perform their tasks and work (Weber & Weber, 2001).

Implementation of an ERP system is a complex IT-related social phenomenon with a large body of information (Sarkera & Leeb, 2003).

A research done in Kenya, according to Amoako-Gyampah (2007) asserts that this implementation involves large expenditures, lengthy periods, and organizational commitment. An organization that decides to implement an ERP system is subjected to technological, information, business processes and people challenges. This implementation affects users at various levels of the organization since it cuts across all functional units.

These users range from top management to low level users who use the system on their day-to-day operations.

Academic research has shown that it is not the technology that provides an organization with a success, but the integration of technology into an organizational change management process (Hornstein, 2008). This approach takes into account the importance of people in an organization. Without proper communication, the employees involved in the 50 implementation process would not know what changes were made, what changes are being made, what changes should be made. Moreover, the employees would not be aware of their tasks related to the implemented changes.

2.8 Summary

This chapter explained the theoretical framework and the empirical review used in this study. It further discussed the various sub-headings of the research which include user involvement in the ERP system implementation, purpose of user involvement, user factors and the challenges of the ERP system implementation in the university setup.

CHAPTER THREE

3.0 RESEARCH METHODOLOGY

3.1 Introduction

This chapter presents the geographical area, target and the accessible population, by describing the research design, the sample size and sampling procedure, instrumentation, validity and reliability of the research instrument, data analysis, presentation and the expected outcome.

3.2 Research Design

A research design is the blueprint which specifies the methods or procedures for gathering, measuring and analyzing of the collected information (Cooper & Schindler, 2006). The researcher adopted a survey research design because it is used to obtain information concerning the current status of the phenomena to describe what exists with respect to the variables or conditions in a situation without changing the environment.

It is used to find out how people feel about a particular issue by enabling them to describe their experiences. Survey research design lays a greater emphasis on sample selection because major concern is to obtain a broad picture of the social challenges prevailing in the defined universe and the recommendations to bring about the desired change.

3.3 Geographical Area of the Study

The study was done at Kisii University in Kisii County. This location was chosen because it could provide the requisite information required according to the objectives of the study.

3.4 Target Population

According to Best et al. (2007) have explained a population as any group of individuals who have one or more characteristics in common that are of interest to the researcher. The population may be all the individuals of a particular type or a more restricted part of that group”. The researcher targeted the ERP system users such as students and employees of

Kisii University. Target population is the collection of individuals or regions that are to be investigated in a statistical study. This being a public university, it has 1130 active ERP users. The target population comprised of students, ICT personnel, academic, registry for students and finance personnel in Kisii universities. A sample population was derived from the respective above mentioned departments. The preference of the mentioned departments in this institution was due to its familiarity with the subject of the proposed study.

3.5 Sampling Technique

The researcher employed stratified random sampling technique because of the big size of the target population. Sampling is a procedure which uses represent parts of a given population as a basis for drawing conclusions about the entire inhabitants (Zikmund, 2003).

Sampling helps the researcher to save the time and resources and cut the cost of data collection because it would be impossible to cover all elements of a population to measure the desired characteristics. The two major objectives to be considered in a sample design are, first a sample should be the representative of the population, and the second is the size of the sample to be ample to get the preferred accuracy (Krishnaswami et al., 2006).

3.6 Sample Size

The target population of this study comprised of students, staffs. Regarding sample size,

Bryman and Bell (2007) recommend that the larger the sample size, the more the accuracy

53 of the results. There are several methods to determining sample size given the total population number was known, Yamane‟s (1967) formula was used to calculate a sample size as show below. A 90 per cent confidence level and p = .10 are assumed for this equation.

( )

(where „n‟ is the sample size, „N‟ is the population size, and „e‟ is the level of precision)

( )

=91.87

Therefore, the sample size is equal to 92 respondents.

Table 3.1: Sample Size Determination

Respondent Group Target Population Sample Size Response Rate

Staffs 930 76 84.2%

Students 200 16 100%

Total 1130 92

3.7 Data Collection

Data collection in this research comprised of gathering responses from the target population for further analysis. Data collection consisted of data sources, research instruments and data collection procedures. The research study relied on both primary and secondary data

54 sources. Primary data was gathered using structured questionnaires. In addition to the primary data, secondary data from journals and e-books were also used to provide more information to this study. The research study utilized questionnaires as the primary data collection research tool.

3.8 Data Collection Instrument

The researcher used structured questionnaires which were designed carefully according to specific objectives of the study. Questionnaires are suitable for extensive research, detailed, objective and respondents could have adequate time to answer the questions. A better quality questionnaire demands for both artistic and scientific skills and to be devised to obtain precise and comprehensive information on the research problem. The data collection of the present research exclusively depends upon the responses gathered through the questionnaire. Consequently, the questionnaire development followed the questionnaire design heuristics such as concise questions, use of helpful questions, and evading of leading questions (Cooper & Schindler, 2006; Zikmund, 2000).

3.9 Validity and Reliability of the Instrument

This study briefly explains the validity and reliability of the data collection instrument employed by the researcher.

3.9.1 Validity

Validity is the ability of a measurement degree to measure what it is projected to measure

(Zikmund, 2003). Reliability is a necessary condition for validity, but a reliable instrument may not be valid. Following the findings of this study using correlation matrix table, it was revealed in the Score-Total that 16 out of 20 items were flagged using Pearson correlation coefficient (PCC), demonstrating an appropriate level of significance value of .000<.05

55 with the sig. (2-tailed) test, view the correlation matrix table appendix H. Based on these results, the content validity index (CVI) value for staff was computed as 0.800 and for students was 0 .720 thus were considered as appropriate. This finding is supported by

Waltz et al., (2005). According to Waltz et al., (2005), a content validity index value of

>.70 is considered acceptable and as such the items of the research instrument could be used for further analysis.

3.9.2 Reliability

Reliability is the extent to which a variable or a set of variables is consistent in what it is anticipated to measure (Hair et al, 2006). If a test or assessment procedure is reliable, it produces similar scores or responses on every occasion. In this study, reliability was measured using Cronbach‟s Alpha Coefficient which is a reliability test used to rate the internal consistency or correlation of the items in a test. The alpha value range from 0 to 1 and a value above 0.70 is the frequently accepted reliability measure (Hair et al., 2006).

The Margin of error used in this study was 5%.

The actual data collected from the field was used to test for the reliability of the data collection instrument. The responses were then compared to measure the consistency of the instrument. The finding was shown in table 3.1

Table 3.1: Reliability Statistics Test Using Cronbach’s Alpha Coefficient

Category Cronbach's Alpha No of Items

Staff Questionnaire 0.809 19

Student Questionnaire 0.880 19

Table 3.1 indicated that staffs and students questionnaires had a reliability index of 0.809 and 0.880 respectively. This implied that the research questionnaires were considered reliable since the reliability index was greater than 0.70.

3.10 Data Analysis and Presentation

The collected data was analyzed by the use of quantitative analysis method, descriptive statistics methods of percentages and standard deviation and inferential statistics methods of correlation and regression analysis. Then the results were presented in the form of APA tables using SPSS software.

3.11 Ethical Issues

The objective of ethics in research is to guarantee that no one is harmed or suffers unfavorable consequences from the research activities (Cooper & Schindler, 2006). Ethical aspects regarding the confidentiality of responses, privacy, and consent of the data were seriously considered during the research process.

The ethical practices that were also put into consideration during this research include honesty in reporting findings from the proposed study and integrity in handling data and information collected from the research study. Presentation of the findings was done without disclosure of respondents‟ identities. A research letter was obtained from the office of the registrar, Kisii University. Besides a research authorization letter, a research clearance permit was also obtained from the national commission for science, technology and innovation upon application, see in appendix D.

3.12 Expected Outcome

The researcher expects to be awarded a Master of Science Degree in Information Systems from Kisii University after completing this research successfully. The researcher also expects to come up with a publishable research paper extracted from this study.

3.13 Summary

This chapter had presented the geographical area, target and the accessible population by describing the research design, the sample size and sampling procedure, instrumentation, validity and reliability of the research instrument, data analysis presentation and the expected outcome.

CHAPTER FOUR

4.0 DATA ANALYSIS, PRESENTATION AND INTERPRETATION

4.1 Introduction

This chapter presents the findings of the specific objectives of this research using descriptive analysis methods of percentages, means and standard deviation then the results presented in form of tables. Inferential statistics was also used to establish whether a relationship existed between the various variables. Discussion of the results was also done in this chapter in line with the literature review.

4.2 Response Rate

The researcher prepared 92 structured questionnaires and issued them to the ERP system users in the university (76 staffs and 16 students). The response rate is shown in table 4.1.

Table4.1: Response Distribution Rate

No of No of Rate of Return

Questionnaires Questionnaires

Issued Returned

Staffs 76 64 84.2%

Students 16 16 100.0%

4.3 Extent of User Involvement

The first objective of the study was to examine the extent of user involvement in the implementation of the Enterprise Resource Planning system employed in public universities. The respondents were issued with questions concerning the user involvement

59 such as Interaction Quality (Quality of inputs provided to the system organization is an indication of user Involvement.), Interaction Nature (Whether the user role and their assigned responsibility with respect to the system tasks are instrumental behind user involvement in the project.), Commitment level (Level of commitment of the users is an indication of increasing user involvement.) and Psychological Stance (Increase in importance and relevance of the project to the users is an indication of increasing user involvement. ) for the success of the ERP implementation in public University. The respondents were required to provide their opinion based on the likert scale of: 1 = Very

Large Extent (VLE), 2 = Large Extent (LE), 3 = Moderate Extent (ME), 4 = Small Extent

(SE) and 5 = No Extent (NE).

The finding of the study was summarized in table 4.2.

Table 4.2: Extent of User Involvement

Statement N M SD

Interaction Quality 64 1.95 .785

Interaction Nature 64 2.16 .718

Commitment Level 64 2.00 .777

Psychological Stance 64 2.25 .926

Overall Result 64 2.09 0 .802

Scale: 1.0-1.4 = very large extent; 1.5-2.4 = large extent; 2.5-3.4 = moderate extent; 3.5-4.4

= small extent; 4.5-5.0 =no extent.

Table 4.2 showed the preliminary descriptive results of the research. The finding indicated that the respondents agreed that to a large extent interaction quality was achieved (M=1.95;

SD=.785); interaction nature (M=2.16; SD=.718); commitment level (M=2.00; SD=.777) and psychological stance (M=2.25; SD=.926). The overall result showed that the level of user involvement was to a large extent achieved (M=2.09; SD=.802) in the implementation of the ERP systems in public universities in Kenya. The study also carried out correlation analysis to test whether there was a relationship between the extent of user involvement and the ERP system implementation. The results were summarized in Table 4.3.

Table 4.3: Correlation Analysis between Extent of User Involvement and the ERP

System Implementation

Extent of User ERP System

Involvement Implementation Success

Pearson 1 .854** Extent of User Correlation

Involvement Sig. (2-tailed) .000

N 64 64

Pearson .854** 1 ERP System Correlation

Implementation Sig. (2-tailed) .000

N 64 64

**. Correlation is significant at the 0.01 level (2-tailed).

The results of correlation analysis revealed a strong positive (r =.854; p-value <.05) relationship between the extent of user involvement and the ERP system implementation as indicated in the SPSS output in Table 4.3.

We do therefore reject the null hypothesis because p-value<.05 and conclude that there was a significant relationship between the extent of user involvement and the ERP system implementation in public universities in Kenya. From this result, it therefore implied that if the extent of user involvement was practiced it would result to effective ERP system implementation. The coefficient of determination was calculated, R2 = .7293, indicating that the two variables share about 72.93% of their variance. This means that there was evidence of overlap between the two variables.

The research also carried out regression analysis to establish the extent of significance of the level of user involvement and the ERP system implementation. The finding is shown in table 4.4.

Table 4.4: Regression Analysis of Extent of User Involvement and the ERP System

Implementation

Unstandardized Standardized t Sig.

Model Coefficients Coefficients

B Std. Error Beta

(Constant) 9.863 1 9.863 167.651 .000b

1 Extent of User 3.648 62 .059 Involvement

Goodness of fit:

R=.854; R2=.730

Adjusted R2=.726;

F=167.651; p<.05

a. Dependent Variable: ERP system implementation

b. Predictors: (Constant), User Involvement

In table 4.4, R is the correlation coefficient. It provides a very strong degree of positive correlation (r=.854) between the extent of user involvement and the ERP system implementation. R-square of .730 measures part of the ERP system implementation which was explained by the extent of user involvement. It showed that approximately 73.0% of the variation in the ERP system implementation was attributed to variation in extent of user involvement. The adjusted R-square provides an idea of how the model may be generalized. It should be as close to R square as much as possible if not the same. In this case, the difference for the final model is small; i.e. .004 or 0.4%. This means if the model

63 was derived from the population rather than a sample, then it would have accounted for approximately 0.4% less variance in the ERP system implementation. The overall model was statistically significant (F-ratio =167.651; p-value<.05). The null hypothesis was rejected. The extent of user involvement therefore had a positive influence on the ERP system implementation in public universities in Kenya.

Un-standardized coefficient values were used to construct the regression equation. The Beta coefficient for the extent of user involvement was 3.648(p-value<.05) and was statistically significant. It made a unique contribution in explaining the ERP system implementation.

Table 4.5 and model 4.1 shows that optimum regression equation showing the relationship between the extent of user involvement and the ERP system implementation was

Y  9.863  3.648x1 (4.1)

Regression model 4.1 has a strong degree of positive correlation (r=.854) between the extent of user involvement and the ERP system implementation. The model is 73.0% explained by the variation in the extent of user involvement and is statistically significant.

4.3.1 Discussion of the Extent of User Involvement

The finding above is in agreement with Hsu et al (2013) who highlighted that user involvement in information systems implementation efforts provide valuable input to various technical decisions to be made. Further the results of the study concurred with

Harris and Weistroffer (2009) who argued that support for user involvement positively impacting user satisfaction which they argue is a proxy for system success.

Moreover, the finding of the study was in line with Chen et al (2011) who suggested that significant components of user participation can provide further insights into the impact of

64 user participation, such as user (decision-making capabilities) positively impacting information system process quality.

Based on the related literatures that concurred with the results of the study, the study advises the management of the public universities in Kenya to ensure that users are ever involved in the implementation of the ERP systems during the planning stages and the execution phases. The user involvement was significant to the quality of the information systems adopted in the universities. However, lack of user involvement normally results into user resistance to the implementation of the new information systems. Therefore, there is need for the user involvement in the implementation of the ERP systems in public universities in Kenya.

4.4 User Factors

The second objective of the study was to establish the user factors in the implementation of the Enterprise Resource Planning system employed in public universities. The respondents were provided with questions concerning the user factors namely attitude towards the use technology, enjoyment of using technology, trust, computer self-efficacy, user expectation, technology experience and organizational role. The respondents were required to provide their opinion based on the likert scale of: 1 = Very High (VH), 2 = High (H), 3 = Moderate

(M), 4 = Low (L) and 5 = Not at All (NAA). The finding of the study was summarized in table 4.5 and 4.6.

Table 4.5: Computer Self-Efficacy

Statement N M SD

Performance Accomplishment 16 1.94 1.063

Vicarious Experience 16 2.31 1.195

Verbal Persuasion 16 2.19 1.167

Psychological State 16 2.19 1.047

Overall Score 16 2.16 1.118

Table 4.5 revealed that the respondents cited that they had high performance accomplishment (M=1.94; SD=1.063). They also agreed that they had high vicarious experience (M=2.31; SD=1.195). Verbal persuasion (M=2.19; SD=1.167), and psychological state (M=2.19; SD=1.047). The overall score showed that the respondents had high computer self-efficacy (M=2.16; SD=1.118).

Table 4.6: User Factors

Statement N M SD Attitude towards the Use of Technology 16 1.94 1.063 Enjoyment of Using Technology 16 2.06 .998 Trust 16 2.44 1.315 User Expectations 16 2.44 1.209 Technology Experience 16 2.19 1.047 Organizational Role 16 2.25 1.065 Overall Results 16 2.22 1.116

The finding in table 4.6 showed that the influence of attitude towards the use of technology on implementation of the ERP system was high (M=1.94; SD=1.063); enjoyment of using technology (M=2.06; SD=.998); Trust (M=2.44; SD=1.315); user expectation (M=2.44;

SD=2.09); technology experience (M=2.19; SD=1.047); and organizational role (M=2.25;

SD=1.065). The overall results also showed that user factors had high influence in the implementation of the ERP systems (M=2.22; SD=1.116).

The study also looked at the students view on the ERP implementation by the university.

The finding is recorded in table 4.7

Table 4.7: Student view on the ERP Implementation

Statement N M SD

Detailed Knowledge 16 1.94 .929

Clear & Concise Strategy 16 2.06 .998

Sponsorship 16 2.06 .772

Business Reengineering 16 2.06 .574

Change Management 16 2.13 .619

Team Composition 16 2.25 .683

Data Entry & Accuracy 16 2.25 .683

Training & Communication 16 1.81 .403

Implementation Approaches 16 2.25 .683

Overall Result 16 2.09 0.705

The finding in table 4.7 indicated that students agreed that the ERP system implementation by the university was high (M=2.09; SD=0.705). This finding simply implied that the university was taking ERP system implementation seriously and therefore was to improve their service delivery.

The study also carried out correlation analysis to test whether there was a relationship between the user factors and the ERP system implementation. The results were summarized in Table 4.8.

Table 4.8: Correlation Analysis between User Factors and the ERP System

Implementation

User Factors ERP System

Implementation

Pearson 1 .509* Correlation User Factors Sig. (2-tailed) .044

N 16 16

Pearson .509* 1 ERP System Correlation

Implementation Sig. (2-tailed) .044

N 16 16

**. Correlation is significant at the 0.05 level (2-tailed).

The results of correlation analysis revealed a positive moderate (r =.509; p-value <.05) relationship between user factors and the ERP system implementation as indicated in the

SPSS output in Table 4.9. We do therefore reject the null hypothesis because p-value<.05 and conclude that there was a significant relationship between the user factors and the ERP system implementation in public universities in Kenya. From these results, it then implied that user factors influenced the ERP system implementation. The coefficient of determination was calculated, R2 = .259, indicating that the two variables share about

25.9% of their variance. This means that there was evidence of overlap between the two variables.

Further the research carried out regression analysis to establish the level of significance of the user factors and the ERP system implementation. The finding is shown in table 4.9.

Table 4.9: Regression Analysis of User Factors and the ERP System Implementation

Unstandardized Standardized t Sig.

Model Coefficients Coefficients

B Std. Error Beta

(Constant) 1.411 .321 4.396 .001 1 User Factors .306 .138 .509 2.212 .044

Goodness of fit:

R=.509; R2=.259

Adjusted R2=.206;

F=4.891; p<.05

a. Dependent Variable: ERP systems implementation

In table 4.9, R is the correlation coefficient. It provides a moderate degree of positive correlation (r=.509) between user factors and the ERP system implementation. R-square of

.259 measures part of the ERP system implementation which was explained by user factors.

It showed that approximately 25.9% of the variation in the ERP system implementation was attributed to variation in user factors. The adjusted R-square provides an idea of how the model may be generalized. It should be as close to R square as much as possible if not the same. In this case, the difference for the final model is small; i.e. .053 or 5.3%.

This means if the model was derived from the population rather than a sample, then it would have accounted for approximately 5.3% less variance in the ERP system implementation. The overall model was statistically significant (F-ratio =4.891; p- value<.05). The null hypothesis was rejected. The user factors therefore had a positive influence on the ERP system implementation in public universities in Kenya.

Un-standardized coefficient values were used to construct the regression equation. The Beta coefficient for the user factors was .509(p-value<.05) and was statistically significant. It made a unique contribution in explaining the ERP system implementation. Table 4.9 and model 4.2 shows that optimum regression equation showing the relationship between user factors and the ERP system implementation was

Y 1.411 0.509x2 (4.2)

Regression model 4.2 has a moderate degree of positive correlation (r=.509) between user factors and the ERP system implementation. The model is 25.9% explained by the variation in user factors and is statistically significant. 70

4.4.1 Discussion of User Factors

The finding of the study concurred with Liao and Hsu (2013) who highlighted that employee‟s attitude is able to learn and use of software only when the top management support and provide appropriate incentive for that. By implementation of the ERP system, the organization work can be done easily and in a better way. The employees can customize their work as per organizational needs.

Moreover, the results agreed with Seba et al, (2012) who argued that trust consistently facilitates system implementation between two parties. Within the context of online social media based knowledge sharing, trust is an initial condition required by communities to participate and share their ideas and opinions. The existence of trust plays an important role in encouraging system adoption among members (Chai &Kim, 2010). Further, the results were in line with Svetlik, Stavrou-Costea and Lin (2007) who said that enjoyment on using technology can improve the welfare of others at some cost to oneself.

From the results above, the study concluded that user factors played a significant role in building and implementation of the ERP systems in public universities in Kenya. The users should ensure that they develop trust on the universities‟ management so that it can facilitate the implementation of the ERP systems.

The users who readily and freely provide support on the use of technology normally result into an effective implementation of the ERP systems. In addition, the know-how on technology use can also encourage the implementation of the information systems in an

71 organization. Therefore, the study encourages most users voluntarily to offer support to the implementation of information systems in their respective institutions.

4.5 Enterprise Resource Planning System Implementation Challenges

The third objective was to find out the challenges encountered in implementing the

Enterprise Resource Planning system in public universities. The respondents were provided with questions revolving around the Enterprise Resource Planning systems implementation challenges namely lack of effective project management methodology, attempts to build bridges to legacy applications, conflicts between user departments, composition of project team members, failure to redesign business processes and misunderstanding of change requirements.

The respondents were required to provide their opinion based on the likert scale of: 1=

Strongly Agree (SA), 2 = Agree (A), 3 = Not Sure (NS), 4 = Disagree (D) and 5 = Strongly

Disagree (SD). The finding of the study was summarized in table 4.10.

Table 4.10: ERP System Implementation Challenges

Statement N M SD

Lack of effective project management methodology 64 2.06 .990

Attempt to build bridges to legacy applications 64 2.45 .795

Conflict between user departments 64 2.38 1.000

Composition of project team members 64 2.36 .982

Failure to redesign business process 64 2.27 .947

Misunderstanding of change requirements 64 2.22 1.061

Overall Results 64 2.29 0.963

The finding in table 4.10 showed that respondents agreed that lack of effective project management methodology was a challenge in the implementation of the ERP systems

The overall results revealed that respondents agreed (M=2.29; SD=0.963) that there were challenges facing the implementation of the ERP system in public universities in Kenya.

Further, the study carried out correlation analysis to test whether there was a relationship between the challenges and ERP system implementation. The finding of the study was shown in table 4.11

Table 4.11: Correlation Analysis between Challenges and the ERP System

Implementation

Implementation System Implementation

Challenges

Pearson 1 .152 Implementation Correlation

Challenges Sig. (2-tailed) .232

N 64 64

Pearson .152 1 Correlation System Implementation Sig. (2-tailed) .232

N 64 64

**. Correlation is significant at the 0.05 level (2-tailed).

Table 4.11 showed there was a weak relationship between the challenges and the ERP implementation. The p value was >0.05 so the study accepted the null hypothesis. This implied that there was no statistical relationship between the two variables.

The research also carried regression analysis to ascertain on the degree of effect of challenges on ERP implementation. The finding was put in table 4.12.

Table 4.12: Regression Analysis of Challenges and the ERP System Implementation

Unstandardized Standardized t Sig.

Model Coefficients Coefficients

B Std. Error Beta

(Constant) 1.838 .216 8.518 .000 1 User Factors .110 .091 .152 1.207 .232

Goodness of fit:

R=.152; R2=.023

Adjusted R2=.007;

F=1.457; p>.05

a. Dependent Variable: ERP systems implementation

Table 4.12 revealed that there was no statistical contribution of the challenges on ERP implementation in the university (P>0.05).

4.6.1 Moderator Analysis

The study carried out the moderator analysis to evaluate the contribution of challenges on the effect of user involvement in the ERP system implementation. The finding is shown in table 4.13.

Table 4.13: Moderator Analysis

Model Unstandardized Standardized t Sig.

Coefficients Coefficients

B Std. Error Beta

(Constant) .658 .115 5.742 .000 1 User Involvement .685 .053 .854 12.948 .000

(Constant) .641 .148 4.316 .000

User Involvement .683 .054 .852 12.645 .000 2 Implementation .009 .049 .013 .186 .853 Challenges

a. Dependent Variable: System Implementation

Table 4.13 showed that user involvement (p<0.05) had significant effect on the ERP system implementation while the challenges showed insignificant effect (p>0.05). In the absence of the challenges user involvement had a standard coefficient of .854 while with challenges it reduced to .852. This implied that the challenges contributed to .002(0.2%) in the ERP system implementation in the university.

4.6.2 Discussion of the ERP System Implementation Challenges

The results of the study agreed with Kim et al., (2005) who established that lack of coordination amongst different business units and stakeholders is often cited as one of the factors leading to implementation delays and organizational conflicts, eventually leading to system implementation failure.

Further Kim et al., (2005) stated that conflict of interest between different functional units and a lack of resource commitment are highlighted as critical challenges linked to system implementation failure. Further, the study finding concurred with Rishi and Goyal (2008) who asserted that the process of change was challenging and employees are often unprepared for new procedures and roles.

In addition, the findings agreed with Berente et al. (2009) who argued that integration of existing stand-alone information systems with the ERP systems was a major problem for many organizations. This is further complicated by the fact that the ERP systems also seek to integrate business processes in organizations which were previously function-based.

Thus, the process-orientation resulting from the process integration is against the functional differentiation which is common in traditional organizations. While client/server and open systems solve some technical difficulties, there are still problems of integrating different types of data and procedures used by functional areas.

Moreover, the finding agreed with Hornstein (2014) who said that project management

(PM) and CM are derived from different terminologies and different methodologies they are, nevertheless, tightly linked and co-dependent and also emphasizes different sets of skills and competencies.

These findings implied that challenges are ever there and as such any organization might not avoid. The differences between the user departments need to be resolved before the information systems are implemented because it will slow and hinder the successful 77 implementation of the ERP systems. There are also needs for the project team members to work harmoniously and with common focus towards the success of the ERP implementation. Since change is inevitable, the management should ensure that they communicate promptly on the need of changing the technology in an organization. The redesigning of business process might also be a challenge; however, there was a necessity of carrying out feasibility study before adopting the new information systems.

4.7 Summary

This chapter had discussed the findings of the specific objectives of the study using descriptive analysis methods of percentages, means and standard deviation. The results had been presented in form of APA tables. Inferential statistics had also been used to establish whether a relationship existed between the various variables.

CHAPTER FIVE

5.0 SUMMARY OF THE FINDINGS, CONCLUSION AND RECOMMENDATIONS

5.1 Introduction

This chapter highlights the summary of the findings in the previous chapter in relation to the specific objectives of the study, findings, conclusion and recommendations of the study.

5.2 Summary of the Findings

The study sought to evaluate user involvement in the implementation of the ERP system in public Universities in Kenya.

5.2.1 User Involvement

The first objective was to examine the extent of user involvement namely interaction quality, interaction nature, commitment level and psychological stance in the implementation of Enterprise Resource Planning system employed in public universities in

Kenya. The finding indicated that the respondents agreed that to a large extent interaction quality was achieved (M=1.95; SD=.785); interaction nature (M=2.16; SD=.718); commitment level (M=2.00; SD=.777) and psychological stance (M=2.25; SD=.926). The overall result showed that the extent of user involvement was to a large extent achieved

(M=2.09; SD=.802) in the implementation of the ERP systems in public universities in

Kenya.

The results of correlation analysis revealed a strong positive (r =.854; p-value <.05) relationship between the extent of user involvement and the ERP system implementation.

The coefficient of determination was calculated, R2 = .7293, indicating that the two variables share about 72.93% of their variance.

Regression results also revealed a strong degree of positive correlation (r=.854) between the extent of user involvement and the ERP system implementation. The model is 73.0% explained by the variation in the extent of user involvement and is statistically significant.

5.2.2 User Factors

Second objective was to establish the user factors such as such as attitude towards the use of technology, enjoyment of using technology, trust, computer self-efficacy, user expectations technology experience and organizational role in the implementation of the

Enterprise Resource Planning system employed in public universities in Kenya.

The study revealed that the respondents cited that they had high performance accomplishment (M=1.94; SD=1.063). They also agreed that they had high vicarious experience (M=2.31; SD=1.195). Verbal persuasion (M=2.19; SD=1.167), and psychological state (M=2.19; SD=1.047). The overall score showed that the respondents had high computer self-efficacy (M=2.16; SD=1.118). In addition, the study results showed that the influence of attitude towards the use of technology on implementation of the ERP system was high (M=1.94; SD=1.063); enjoyment of using technology (M=2.06; SD=.998);

Trust (M=2.44; SD=1.315); user expectation (M=2.44; SD=2.09); technology experience

(M=2.19; SD=1.047); and organizational role (M=2.25; SD=1.065). The overall results also showed that user factors had high influence in the implementation of the ERP systems

(M=2.22; SD=1.116).

The results of correlation analysis revealed a positive moderate (r =.509; p-value <.05) relationship between user factors and the ERP system implementation. The study rejected the null hypothesis because p-value<.05 and concluded that there was a significant

80 relationship between the user factors and the ERP system implementation in public universities in Kenya. From these results, it then implied that user factors influenced the

ERP system implementation. The coefficient of determination was calculated, R2 = .259, indicating that the two variables share about 25.9% of their variance. This means that there was evidence of overlap between the two variables.

Regression result revealed a moderate degree of positive correlation (r=.509) between user factors and the ERP system implementation. The model is 25.9% explained by the variation in user factors and is statistically significant.

5.2.3 Enterprise Resource Planning System Implementation Challenges

Finally, the third objective of the study was to find out the challenges namely (lack of effective project management methodology, an attempt to build bridges to legacy applications, conflicts between user departments, composition of the project team members, failure to redesign core business processes and misunderstanding of change requirements) encountered in implementing the Enterprise Resource Planning system in public universities. The study showed that respondents agreed that lack of effective project management methodology was a challenge in the implementation of the ERP systems

(M=2.09; SD=1.011); attempt to build bridges to legacy applications (M=2.06; SD=.990); conflict between user departments (M=2.45; SD=0.795); composition of project teams members (M=2.38; SD=1.000; failure to redesign business process (M=2.27; SD=.947); and misunderstanding of change requirements (M=2.22; SD=1.061). The overall results revealed that respondents agreed (M=2.29; SD=0.963) that there were challenges facing the implementation of the ERP system in public universities in Kenya.

The correlation analysis revealed a weak relationship between the challenges and the ERP implementation. The p value was >.05 so the study accepted the null hypothesis. This implied that there was no statistical relationship between the two variables.

Regression results revealed that there was no statistical contribution of the challenges on

ERP implementation in the university (P>.05).

5.3 Conclusion

Based on the results above, the study concluded that the extent of user involvement had a statistically significant influence on the ERP system implementations in public universities in Kenya.

Secondly, the study concluded that there was a positive moderate relationship between user factors and the ERP system implementation in public universities in Kenya.

The study also concluded that the ERP system implementations are faced by varied challenges which should be overcome to ensure smooth information systems implementation.

Finally, the study deduced that there was a positive moderate relationship between user involvement and the ERP systems implementation in public universities in Kenya.

5.4 Recommendations

The following are the recommendations based on the area for further research and practice.

5.4.1 Recommendations for Practice

Given the conclusion, the study recommended the following:

i. There was need for improved user involvement and commitment level on the ERP

system implementations because they lead to quality information systems.

ii. The users‟ attitude, technology experience, expectations and computer self-efficacy

plays key role in the ERP system implementation and therefore should be

encouraged among the users.

iii. There was need for preparedness by the universities on any implementation

challenges that might be encountered and develop appropriate strategies of

managing them.

The recommendations above were represented diagrammatically as shown in figure 4.1.

Improves Information and

System Quality User Involvement  Interaction Quality  Interaction Nature  Commitment level  Psychological Stance Level of ERP System Implementation Success

User Factors  Attitude  Experience in IT  Computer self- Implementation Challenges Efficacy  Conflict between User  Trust Departments  Technology  Composition of Team Enjoyment members

 Business Processes  Change Requirements  Organizational Role

83 Improves Service Quality

Figure 4.1: Conceptual Framework of the Study

5.4.2 Suggestion for Further Research

The study suggests that another research should be done on the moderating influence of the

ERP system implementation challenges on the relationship between user involvement and the ERP system implementation in public universities in Kenya. Further research ought to be conducted in a larger scale to determine other factors that may be influential to the ERP system implementation success in public universities.

5.5 Summary

This chapter highlighted the summary of the findings in the previous chapter in relation to the specific objectives of the study, findings, conclusion and recommendations of the study.

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Appendix A: Introductory Letter

Ben MarigaBogonko,

P.O. Box 56,

Kebirigo, Nyamira.

4th April, 2017.

Kisii University,

P.O. Box 408,

Kisii.

Dear Sir/Madam,

RE: REQUEST TO CARRY OUT RESEARCH IN THE UNIVERSITY

I am student at Kisii University pursuing a Master of Science Degree in Information Systems. I am conducting a research on, “User Involvement in the Implementation of the Enterprise Resource Planning Systems in Public Universities, Kenya.”. I am kindly requesting you to allow me to undertake this research in your organization. Any information to be given will be treated with utmost confidentiality for the purpose of this research. Your assistance and cooperation will be highly appreciated.

I will be very glad if you consider my application.

Yours faithfully, Mariga Ben MarigaBogonko

Appendix B: Research Questionnaire for the Staffs I am a student at Kisii University pursuing a Master of Science Degree in Information Systems and currently undertaking a research on the title quoted in bold below. Therefore, this is a questionnaire for ICT and other ERP system users in the university. You are kindly requested to respond to all items in the questionnaire as honestly as possible. The information you will provide on, “User Involvement in the Implementation of the Enterprise Resource Planning Systems in Public Universities, Kenya” will be treated with utmost confidentiality. Therefore, do not indicate your name. Your honest response will be very useful for this study. Kindly answer all questions in all the sections by filling in the blank spaces at the end of the question or statement or simply put a tick (√) where appropriate.

Section A: Extent of User Involvement

1. To what extent do you think your involvement in the ERP operations and decisions can lead to the success of the ERP implementation in the university? Please tick the response which matches your opinion. Key: VLE=Very Large Extent, LE= Large Extent, ME=Moderate Extent, SE=Small Extent, NE=No Extent Note: The user in the table below refers to you as the ERP system user.

Statement VLE(1) LE(2) ME(3) SE(4) NE(5)

1. Interaction Quality (Quality of inputs provided to the system organization is an indication of user Involvement.) 2. Interaction Nature (Whether the user role and their assigned responsibility with respect to the system tasks are instrumental behind user involvement in the project.) 3. Commitment Level (Level of commitment of the users is an indication of increasing user involvement.) 4. Psychological Stance (Increase in importance and relevance of the project to the users is an indication of increasing user involvement.)

Section B: ERP System Implementation

2. As a user, how do you assess the ERP system functionality and the environment of its operations based on the following factors? Please tick the response which matches your opinion. Key: SA=Strongly Agree, A=Agree, NS=Not Sure, D=Disagree, SD=Strongly Disagree

Statement SA(1) A(2) NS(3) D(4) SD(5)

1. Detailed knowledge of the organization and legacy systems

2. Having a clear and concise strategy

3. Having top management sponsorship

4. Following management practices for Business Process Reengineering

5. Following top notch change management practices

6. Having a knowledgeable and skillful team composition

7. Creating clear procedures for data entry and accuracy

8. Training and streamlining the communication process

9. Deciding on the implementation approaches

Section C: ERP System Implementation Challenges

3. To what extent do you agree with the following ERP implementation challenges encountered as impediments to success of the ERP System implementation? Please tick the response which matches your opinion. Key: SA=Strongly Agree, A=Agree, NS=Not Sure, D=Disagree, SD=Strongly Disagree

Statement SA(1) A(2) NS(3) D(4) SD(5)

1. Lack of effective project management methodology

2. Attempts to build bridges to legacy applications

3. Conflicts between user departments

4. Composition of project team members

5. Failure to redesign business process

6. Misunderstanding of change requirements

Thank You

Appendix C: Research Questionnaire for the Students This is a questionnaire for students on the use of the ERP system in the university. You are kindly requested to respond to all items in the questionnaire as honestly as possible. The information you will provide on, “An Evaluation of User Involvement in the Implementation Success of the Enterprise Resource Planning Systems in Public Universities: A Case of Kisii University” will be treated with utmost confidentiality. Therefore, do not indicate your name. Your honest response will be very useful for this study. Kindly answer all questions in all the sections by filling in the blank spaces at the end of the question or statement or simply put a tick (√) where appropriate.

Section A: Computer Self Efficacy

1. To what extent do you rate the following computer factors on the belief that one‟s capability to organize and execute the courses of action required (Computer Self Efficacy) is influential to the successful implementation of the ERP system. Please tick the response that matches your opinion. Key: VH=Very High, H=High, M=Moderate, L=Low, NAA=Not At All

Statement VH(1) H(2) M(3) L(4) NAA(5)

1. Performance Accomplishment (Experience of mastery influences your perspective on your abilities of using computers.) 2. Vicarious Experience (Observing someone perform a task or handle a situation using computers can help you to perform the same task.) 3. Verbal Persuasion (when other people encourage and convince you to perform a task) 4. Psychological State (Mood, Emotions, physical reactions may influence how you feel about personal abilities of using computers.)

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Section B: User Factors 2. To what extent do you rate the following user factors in the successful implementation of the ERP? Please tick the response which matches your opinion. Key: VH=Very High, H=High, M=Moderate, L=Low, NAA=Not At All Statement VH(1) H(2) M(3) L(4) NAA(5)

1. Attitude towards the Use Technology

2. Enjoyment of Using Technology

3. Trust in using Technology

4. User Expectations in system Friendliness

5. Technology Experience

6. Organizational Role in supporting Employees in Technology Use

1. Section C: As a user, how do you assess the ERP system functionality and the environment of its operations based on the following factors? Please tick the response which matches your opinion. Key: SA=Strongly Agree, A=Agree, NS=Not Sure, D=Disagree, SD=Strongly Disagree

Statement SA(1) A(2) NS(3) D(4) SD(5)

1. Detailed knowledge of the organization and legacy systems

2. Having a clear and concise strategy

3. Having top management sponsorship

4. Following management practices for Business process Reengineering

5. Following top notch change management practices

6. Having a knowledgeable and skillful team composition

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7. Creating clear procedures for data entry and accuracy

8. Training and streamlining the communication process

9. Deciding on the implementation approaches

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Appendix D: Letter of Authority from the University

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Appendix E: Research Authorization by NACOSTI

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Appendix F: Research Clearance Permit

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Appendix G: Correlation Matrix Table Level of Correlation From Item N=64 Score_Total(N=64),

Interaction Quality Pearson Correlation .564**

Sig. (2-Tailed Test) .000

Interaction Nature Pearson Correlation .655**

Sig. (2-Tailed Test) .000

Commitment Level Pearson Correlation .405**

Sig. (2-Tailed Test) .001

Psychological Stance Pearson Correlation .636**

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Sig. (2-Tailed Test) .000

User Involvement Pearson Correlation .753**

Sig. (2-Tailed Test) .000

Attitude towards the Use Pearson Correlation .579** Technology Sig. (2-Tailed Test) .000

Enjoyment of Using Pearson Correlation .642** Technology Sig. (2-Tailed Test) .000

Trust Pearson Correlation .577**

Sig. (2-Tailed Test) .000

Computer Self-Efficacy Pearson Correlation .685**

Sig. (2-Tailed Test) .000

User Expectations Pearson Correlation .453**

Sig. (2-Tailed Test) .000

Technology Experience Pearson Correlation .617**

Sig. (2-Tailed Test) .000

Organizational Role Pearson Correlation .580**

Sig. (2-Tailed Test) .000

User Factors Pearson Correlation .850**

Sig. (2-Tailed Test) .000

Lack of effective Project Pearson Correlation .285* Management Methodology

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Sig. (2-Tailed Test) .021

Attempts to Build Bridges to Pearson Correlation .370** Legacy Applications Sig. (2-Tailed Test) .002

Conflicts between User Pearson Correlation .176 Departments Sig. (2-Tailed Test) .161

Composition of Project Team Pearson Correlation .344** Members Sig. (2-Tailed Test) .005

Failure to Redesign Business Pearson Correlation .559** Process Sig. (2-Tailed Test) .000

Misunderstanding of Change Pearson Correlation .446** Requirements Sig. (2-Tailed Test) .000

Implementation Challenges Pearson Correlation .544**

Sig. (2-Tailed Test) .000

Level of User Involvement Pearson Correlation .753**

Sig. (2-Tailed Test) .000

User Factors Pearson Correlation .850**

Sig. (2-Tailed Test) .000

ERP System Implementation Pearson Correlation .576**

Sig. (2-Tailed Test) .000

User Involvement Pearson Correlation .911**

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Sig. (2-Tailed Test) .000

Content Validity Index Value .800

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