SUPPLY CHAIN STRATEGIES, TECHNOLOGY AND PERFORMANCE OF LARGE-SCALE MANUFACTURING FIRMS IN KENYA

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1 SUPPLY CHAIN STRATEGIES, TECHNOLOGY AND PERFORMANCE OF LARGE-SCALE MANUFACTURING FIRMS IN KENYA By Peterson Obara Magutu A Research Thesis Submitted in Partial Fulfillment of the Requirement for the Award of the Degree of Doctor of Philosophy in Business Administration, School of Business, University of Nairobi October, 2013

2 DECLARATION DECLARATION BY CANDIDATE: I hereby declare that the work contained in this research thesis is my original work and has not previously, in part or in its entirety, been presented at any other university towards the award of any degree. Signed Peterson Obara Magutu D80/80027/2008 Date. DECLARATION BY SUPERVISORS: This PhD research thesis has been submitted with our approval as the university supervisors. Signed Date... Prof. Isaac Meroka Mbeche Department of Management Science School of Business, University of Nairobi Signed Date. Dr. James Muranga Njihia Department of Management Science School of Business, University of Nairobi Signed Date. Dr. Josiah Aduda Department of Finance & Accounting School of Business, University of Nairobi i

3 DEDICATION I would like to lovingly dedicate this Doctoral thesis to the friendship and memory of my late mum, Gatharina Kate Nyanchera who has been my constant source of inspiration. All kids who have been named after her, you are equally dedicated. There is no doubt in my mind that without her taking me to school the first day in 1983 and counsel to always do the right thing, I could not have completed this process which requires a lot of discipline and humility. Kate's strength and faith during the last year of her life gave me a new appreciation for the meaning and importance of friendship. Kate gave me the drive and discipline to tackle any task with enthusiasm and determination. She lived her life well, acting upon her spiritual beliefs conscientiously by assisting friends, relatives and strangers in need. She faced her 1992 too early death bravely. Her example kept me working when I wanted to give up. R.I.P Good Mum. ii

4 ACKNOWLEDGEMENTS At the completion of my thesis, it is a pleasant task to express my thanks to all those who contributed in many ways to the success of this study. I am sincerely grateful for the support and encouragement of numerous people including my supervisors, mentors, well wishers, my friends, colleagues and various institutions who either have directly or indirectly supported me along the way in completing my PhD thesis. This thesis being the final mark of PhD studies, I would like to thank all those people who made this thesis possible and an unforgettable experience for me. Foremost, I would like to express my sincere gratitude and acknowledge the inspirational instruction and guidance of my three supervisors Prof. Isaac Meroka Mbeche, Dr. James Njihia and Dr. Josiah Aduda throughout the time it took me to complete this research and write the thesis. I gratefully and sincerely thank the trio for their continuous support, patience, motivation, enthusiasm, immense knowledge and most importantly, their friendship during my graduate studies. The trio encouraged me to not only grow as a manager but also as an instructor and an independent thinker. I could not have imagined having better supervisors and mentors for my PhD study. These three gentlemen have given me a deep appreciation and love for the beauty and detail of this subject. They have been very generous in their support of my academic pursuits. Prof. Mbeche provided detailed guidance and encouragement throughout the course of preparing for and conducting the research. His belief that it was, indeed, possible to finish iii

5 kept me going. For everything you ve done for me, Prof. Mbeche, I thank you. I am grateful for the helpful comments provided on all my drafts by Dr. Njihia and Dr. Aduda by providing insightful comments on short notice. I would also like to thank Dr. Maalu and Dr. Machuki for their assistance and guidance in getting my initial impetus to study supply chain strategy and providing me with the foundation for writing this work. I am also indebted to the chairmen and members of my departmental to the doctoral committee for their input, valuable discussions and accessibility. In particular, I would like to thank Prof. Evans Aosa (Oral Defense), Prof. Francis Kibera (Doctoral Defense), Dr. Zack Awino (Open Forum), Dr. Owino Okwiri (Departmental), Prof. Peter K Obonyo, Prof. Martin Ogutu, Dr. Kate Litondo, Dr. XN Iraki, Dr. Munyoki and Dr. John Yabs for their advice and generously sharing their meticulous research insights that supported and expanded my own work. I must acknowledge as well the many friends, colleagues, students and teachers who assisted, advised, and supported my research and writing efforts over the years. Richard Ndubai and my Dean SNM Nzuve thanks for your wisdom which has consistently helped me keep perspective on what is important in life and shown me how to deal with reality. My thanks go to the University of Nairobi for their fee waiver towards my studies. Thanks for the full scholarship for my MBA that found the base for my PhD. My thanks must go also to supply chain and procurement managers of large-scale manufacturing firms in Kenya for their willingness to fill and return my research questionnaires. I thank my three research assistants Mary Likavo, Monica Njenga and iv

6 Marubu Felister for their research assistance and for providing necessary infrastructure & resources to accomplish my research work. The offer to use your family resources especially your car KBQ ---to ease logistics was God sent. Basweti Nobert and Dr. Justine Magutu, thanks for your editorial services. I am grateful too for the support and advice from my faculty colleagues in the Schools of Business who offered unflagging support and wise advice. Special thanks to my family for their good-natured forbearance with the process and for their pride in this accomplishment. It was a team effort. To start with, my Dad Jonnie Rodgers, your inspiration in me to always lead the leaders kept the fire burning in me. In the list of my immediate family, I would like to thank my wife for her support and encouragement. I could not have completed this effort without her assistance, quiet patience, unwavering love, tolerance, and enthusiasm; and My Late Grandparents; theirs is an Everlasting Omwando. Finally and most importantly, ALMIGHTY GOD thanks for your emotional, intellectual, spiritual and social support to translate this thesis into a readable whole. Amen Peterson Obara Magutu v

7 Learning and Failure are the Most Powerful Symbols of Renewal, Rebirth and Growth. There is a Lot to Learn through Failure Anonymous vi

8 COPYRIGHT Copyright magutumop2013 By Obara Peterson Magutu All rights reserved. vii

9 TABLE OF CONTENTS Declaration... i Dedication... ii Acknowledgements... iii Copyright... vii Abbreviations and Acronyms... xiv Abstract... xvi CHAPTER ONE: INTRODUCTION Background to the Study Research Problem Research Objectives Value of the Study Organization of the Thesis CHAPTER TWO: LITERATURE REVIEW Introduction Supply Chain Management Theories of Supply Chain Management and Performance Supply Chain Strategies Technology in Supply Chain Management Firm and Supply Chain Performance Summary of Empirical Studies Conceptual Framework Hypotheses of the Study CHAPTER THREE: RESEARCH METHODOLOGY Introduction Research Philosophy Research Design Population of the Study Sampling Technique Data Collection Operationalisation of the Study Variables Validity and Reliability Tests Data Analysis Tools CHAPTER FOUR: DATA ANALYSIS AND RESULTS Introduction Pilot Study to Pre-Test the Research Tool Study Response Rate Firm Level Supply Chains Management SC Strategies Used by Large-Scale Manufacturing Firms in Kenya Factors Motivating Investment in Supply Chain Strategies SC Technologies Used by Large-Scale Manufacturing Firms viii

10 4.8 Benefits of Adopting Technologies in Supply Chain Management Performance Index for Large-Scale Manufacturing Firms in Kenya Correlation Analysis on SC Strategies, Technology and Firm Performance CHAPTER FIVE: TEST OF HYPOTHESES AND INTERPRETATIONS Introduction Supply Chain Strategies and Supply Chain Performance Outcome Supply Chain Strategies and Firm Performance Relationship between SC Strategies, Technology and SC Performance Relationship between SC Strategies, Technology and Firm Performance CHAPTER SIX: SUMMARY, DISCUSSION, CONCLUSIONS AND IMPLICATIONS Introduction Summary of the Findings Discussion of the Findings Conclusions Contributions of the Study Findings Recommendations Limitations of the Study Future Research Directions REFERENCES APPENDICES Appendix I: Letter Of Introduction Appendix Ii: Research Questionnaire Appendix Iii: KMO and Bartlett's Test (a) For Supply Chain Strategies used by Large- Scale Manufacturing Firms In Kenya Appendix Iv: Rotated Component Matrix (a) for Supply Chain Strategies used by Large- Scale Manufacturing Firms In Kenya Appendix V: KMO And Bartlett's Test (a) for Supply Chain Technologies used by Large- Scale Manufacturing Firms in Kenya Appendix Vi: Rotated Component Matrix (a) for Supply Chain Technologies used by Large-Scale Manufacturing Firms In Kenya Appendix Vii: Annual Performance Composite Scores, Supply Chain Performance Index (Y 1 ) and Firm Performance Index (Y 2 ) Appendix Viii: Cronbach Alpha Reliability Coefficients Appendix Ix: Spearman's RHO Correlation Coefficients for Supply Chain Strategies and Supply Chain Performance Appendix X: Spearman's RHO Correlation Coefficients for Supply Chain Strategies and Firm Performance Index Appendix Xi: Spearman's RHO Correlation Coefficients for Supply Chain Technologies And Supply Chain Performance Index Appendix Xi: Spearman's RHO Correlation Coefficients for Supply Chain Technologies And Firm Performance Index ix

11 Appendix xii: Regression Coefficients (a) for Mid-Range Supply Chain Strategies and Supply Chain Performance Appendix xiii: Regression Coefficients (a) for Long-Range Supply Chain Strategies and Supply Chain Performance Appendix xiv: Regression Coefficients (a) for Mid-Range Supply Chain Strategies and Firm Performance Appendix xv: Regression Coefficients (a) for Long-Range Supply Chain Strategies and Firm Performance Appendix xvi: Large-Scale Manafucturing Firms In Kenya Appendix xvii: Performance Criteria Weights Appendix xviii: Proposed Work Plan for PhD Proposal and Thesis x

12 LIST OF TABLES Table 2.1: Summary of Empirical Studies on supply chain strategies, technology and firm performance Table 3.1: Sampling Strata Table 3.2a: Operationalisation of the Study Independent Variable Table 3.2b: Operationalisation of the Study Moderating Variable Table 3.2c: Operationalisation of the Study Dependent Variable 1 (SC Performance) Table 3.2d: Operationalisation of the Study Dependent Variable 2 (Firm Performance) Table 3.3a: Summary of Statistical Tests of Hypotheses Table 3.3b: Summary of Analysis of Variance and Regression Analysis Statistical Tests of Hypotheses Table 4.1: Participants by Large-Scale Manufacturing subsectors Table 4.2: Success in Managing the Company's Supply Chain in General Table 4.3a: Mid-range SC Strategies Used by Large-Scale Manufacturing Firms in Kenya Table 4.3b: Long-Range SC Strategies Used by Large-Scale Manufacturing Firms in Kenya Table 4.4: Summary for Factor Analysis for Supply Chain Strategies Table 4.5: Factors Motivating Investment in Supply Chain Strategies Table 4.6a: Functional SCTs Used by Large-Scale Manufacturing Firms in Kenya Table 4.6b: Integrated SCTs Used by Large-Scale Manufacturing Firms in Kenya Table 4.7: Summary for Factor Analysis for Supply Chain Technologies Table 4.8: Benefits from the Adoption of Supply Chain Technologies Table 4.9 SC Performance Outcomes for Large-Scale Manufacturing Firms in Kenya Table 4.10: Firm Average Performance Table 4.11: Correlation between Supply Chain Strategies and Supply Chain Performance Table 4.12: Correlation between SC Strategies and Firm Performance Table 4.13: Correlation between SCT and SC Performance Table 4.14: Correlation between Supply Chain Technologies and Firm Performance Table 5.1a: Regression Results for SC Strategies and Supply Chain Performance Table 5.1b: Regression Coefficients (a) for SC Strategies and SC Performance Table 5.2a: Regression Model Summary Results for Mid-range SC Strategies and Supply Chain Performance xi

13 Table 5.2b: Regression Coefficient for Mid-range SC Strategies and SC Performance Table 5.3: Regression Model Summary Results for Long-Range SC Strategies and SC Performance Table 5.4a: Regression Results for SC Strategies and Firm Performance Table 5.4b: Regression Coefficients (a) for SC Strategies and Firm Performance Table 5.5a: Regression Model Summary Results for Mid-range SC Strategies and Firm Performance Table 5.5b: Regression Results for Mid-range SC Strategies and Firm Performance Table 5.6: Regression Model Summary Results for Long-Range SC Strategies and Firm Performance Table 5.7a: Summary Results for Supply Chain Strategies, Technology and SC Performance. 171 Table 5.7b: Regression Coefficients for Supply Chain Strategies, Technology and SC Performance Table 5.8: Summary Results for Integrative SCT on the relationship between Mid-range SC strategies and SC performance (outcome) Table 5.9: Summary Results for Integrative SCT on the relationship between Long-range SC strategies and supply chain performance (outcome) Table 5.10: Summary Results for Functional SCT on the relationship between Mid-range SC strategies and SC performance (outcome) Table 5.11 Summary Results for Functional SCT on the relationship between Long-range SC strategies and supply chain performance (outcome) Table 5.12a: Regression Summary Results for SC Strategies, Technology and Firm Performance Table 5.12b: Regression Coefficients for SC Strategies, Technology and Firm Performance Table 5.13: Summary Results for Integrative SCT on the relationship between Mid-range SC strategies and Firm performance Table 5.14: Summary Results for Integrative SCT on the relationship between Long-range SC strategies and Firm performance Table 5.15: Summary Results for Functional SCT on the relationship between Mid-range SC strategies and Firm performance Table 5.16: Summary Results for Functional SCT on the relationship between Long-range SC strategies and Firm performance xii

14 LIST OF FIGURES Figure 2.1: Basic RBV Framework Figure 2.3: The Supply Chain Operations Reference (SCOR) Model Figure 2.2: Results Chain Figure 2.4: Conceptual Model Figure 4.1: Supply Chain Indicators Performance Outcome Figure 4.2: Supply Chain Performance Outcome Figure 4.3: Four Perspectives of Average Firm Performance Figure 4.4: Average Firm Performance xiii

15 ABBREVIATIONS AND ACRONYMS APS - Advanced Planning System AQCS - Automated Quality Control System BSC - Balanced scorecard CAD - Computer-Aided Design Systems CRM - Customer Relationship Management DFM - Demand Forecasting Management EDI - Electronic Data Interchange ERP - Enterprise Resource Planning FSCT - Functional Supply Chain Technologies GCTS - Geo-Coded Tracking Systems GDP - Gross Domestic Product GoK - Government of Kenya I/O - Input / Output IRR - Internal Rate of Return ISCM - Internal Supply Chain Management ISCT - Integrated Supply Chain Technologies IT - Information Technology JIT - Just-In-Time KAM - Kenya Association of Manufacturers MES - Manufacturing Execution Systems MRP - Material Requirements Planning MRPII - Manufacturing Resources Planning xiv

16 NPV - Net Present Value PDM - Product Data Management PwCIL - PriceWaters Consultancy International Limited RBV - Resource-Based View RFID - Radio Frequency Identification ROI - Return on Investment SC - Supply Chain SCE - Supply Chain Event Management SCM - Supply Chain Management SCOR - Supply Chain Operations Reference Model SCP - Supply Chain Planning Systems SCT - Supply Chain Technology SRM - Supplier Relationships Management TMS - Transportation Management Systems VMI - Vendor Managed Inventory WMS - Warehouse Management Systems YMS - Yard Management Systems xv

17 ABSTRACT This thesis set out to establish the role of technology in the relationship between supply chain strategies and overall firm performance by addressing four primary gaps in the literature: the study of the four variables (supply chain strategies, supply chain technology, supply chain performance and firm performance) in isolation; the research findings and results have been contradicting and no attempt to clear the contradictions; biased and unbalanced analysis of the different measures of firm performance, as well as the failure to use weighted scores to measure firm performance; the limited and still evolving literature on supply chain strategies; and the narrow literature on supply chain technology was largely focused on the adoptions, but not on the moderating effect on the relationship between supply chain strategies and firm performance. With a firm level focus, the study employed Resource Based View framework. To accomplish the four objectives of this study, four major and twelve sub hypotheses were developed and tested. A sample of one hundred and thirty eight (138) firms was drawn using proportionate sampling from a total population of six hundred and twenty seven (627) large scale manufacturing firms in Kenya. The descriptive statistics, reliability and validity tests of the constructs: correlation, factor and regression analysis models were used to test the hypotheses. The preliminary tests employed the use of Kaiser Mayer-Olkim (KMO) and Barlett s test. The findings indicate that there is a significant relationship between supply chain strategy and the firm s SC performance, where SC strategies alone are able to explain 51.3% of the variance in the firm s supply chain performance. Equally, there is a very strong relationship between supply chain strategies, SC technology and firm supply chain performance outcome with the supply chain strategies and technology explaining 92.9% of the changes in the firm s SC performance outcome. This implies that when SC strategies are combined with the supply chain technologies they explain 92.9% of the variations in the firm s supply chain performance. From the results, SC technologies have a greater impact of 42.6% ( ) on the relationship between SC strategies and SC performance than that of 11.5% ( ) on the relationship between SC strategies and firm performance; since these are basically SC technologies in support of the supply chain and not the firm s wider functional areas. At the end, the coefficient of the product variable show a very strong moderating effect of SC technologies on the relationship between supply chain strategies and supply chain performance (SC Strategy*Technology beta = 0.925) compared to that on the relationship between supply chain strategies and firm performance (SC Strategy*Technology beta = 0.532). In theory, policy and practice, the study cleared contradictions thus supporting the position that firms ought to invest in supply chain configurations that lead to improved service delivery and enhanced performance. Managers should recognize the need of long range supply chain strategies aligned with overall business strategy to improve overall firm performance than running the supply chain operations as Mid-range activities. A qualitative research design with more variables could be considered for further research. xvi