FORECASTING TECHNIQUES, OPERATING ENVIRONMENT AND ACCURACY OF PERFORMANCE FORECASTING FOR LARGE MANUFACTURING COMPANIES IN KENYA

Transcription

1 FORECASTING TECHNIQUES, OPERATING ENVIRONMENT AND ACCURACY OF PERFORMANCE FORECASTING FOR LARGE MANUFACTURING COMPANIES IN KENYA CHINDIA, Elijah Wakhungu A Thesis Submitted in Fulfillment of the Requirements for the Award of the Degree of Doctor of Philosophy in Business Administration School of Business, University of Nairobi

2 DECLARATION This doctoral thesis is my original work and has not previously, in its entirety or in part, been presented as a degree at any other university... CHINDIA, Elijah Wakhungu D80/P/8052/02.. Date This doctoral thesis has been submitted for examination with our approval as university supervisors.. Prof. Francis N. Kibera, PhD Date Prof. Ganesh P. Pokhariyal, PhD.. Date Prof. Gituro Wainaina, PhD Date 2

3 COPYRIGHT All rights reserved. No part of this thesis may be used or reproduced in any form by any means, or stored in database or retrieval system, without prior written permission of the author or University of Nairobi on that behalf except in the case of brief quotations embodied in reviews, articles and research papers. Making copies of any part of this thesis for any purpose other than for personal use is a violation of the Kenyan and international copyright laws. For any information, please contact Chindia Elijah Wakhungu using the following address: P.O. Box 4577, NAIROBI Kenya. Telephone: Mobile: ewc2811@gmail.com 3

4 DEDICATION To the Lord, for He is good; His love and His kindness go on forever. To my children, for the love and support; and to the memory of my dad and mum. 4

5 ACKNOWLEDGEMENTS The completion of this thesis is partly due to the encouragement and prompting of many individuals to whom I render due honour and thanks. I am pleased to acknowledge the guidance and assistance of my supervisors, Prof. Francis Kibera from the School of Business, Prof. Ganesh Pokhariyal from the School of Mathematics and Prof. Gituro Wainaina from the School of Business, University of Nairobi. My appreciation also goes to Dr. Murang a Njihia of the School of Business, who edited my initial work and provided additional reading material. I am very grateful for the many hours of dedication and tireless effort these resource persons spent in critiquing this work and providing useful comments and direction. I accept full responsibility for the general arrangement of the thesis and I am also prepared to forfeit many of the plaudits provoked by the textual material. I would like to recognize my parents, the late Jeremiah Lutatwa and the late Morina Makokha, my brothers and sisters Simiyu, Mark, Wanyama, Mwenje, Rhoda, Nanzala, Maria and Keta, who have always stood by me over the years. My late parents can be remembered for being a great source of inspiration in our lives. They encouraged all of us to continue with the struggle to learn, despite the many challenges. My wish to succeed was as much for them as it was for me. I will always remain grateful for the influence they brought in my life, even when everything else appeared dark and gloomy. Most importantly, I wish to express my profound appreciation to my loving children Jei Lutatwa, Tim Samadi and Morina Avoga for bringing a lot of excitement in my life and by challenging me to complete a study of this magnitude. For everyone who contributed emotionally, intellectually, spiritually and socially to translate this thesis into a readable whole, may God bless you abundantly in your pursuit to make this world a better place to live. Your efforts will go a long way to change and enrich this turbulent environment, especially in the field of business management where much more still needs to be done. 5

6 TABLE OF CONTENTS DECLARATION.. ii COPYRIGHT.. iii DEDICATION iv ACKNOWLEDGEMENTS. v LIST OF TABLES. x LIST OF FIGURES. xvi ABSTRACT.. xvii ABBREVIATIONS AND ACRONYMS... xviii CHAPTER ONE: INTRODUCTION Background of the Study Forecasting Techniques, Environment and Accuracy of Performance Forecasting Forecasting in Large Manufacturing Companies and the Manufacturing Sector in Kenya Research Problem Research Objectives Value of the Study Outline of the Thesis 13 CHAPTER TWO: LITERATURE REVIEW Introduction Forecasting Methods Judgmental Forecasting Method Objective Forecasting Method Combined Forecasting Method Environmental Factors and Forecasting External Operating Environment Internal Operating Environment 21 6

7 2.4 Forecasting, Bargaining Power and Customer Demand Theory Forecasting Performance and Measurement Conceptual Framework Hypotheses. 28 CHAPTER THREE: RESEARCH METHODOLOGY Introduction Research Philosophy Research Design Population of the Study Sample Design Data Collection Method Data Collection Instrument Types of Variables Operationalization of Variables Data Analysis Reliability and Validity Validity Tests for Instrument Used Analytical Techniques Applied. 45 CHAPTER FOUR: DATA ANALYSIS, RESULTS AND DISCUSSIONS Introduction Response Rate Characteristics of Large Manufacturing Firms in Kenya External Operating Environment Internal Operating Environment

8 CHAPTER FIVE: FORECASTING METHODS, OPERATING ENVIRONMENT AND ACCURACY OF PERFORMANCE FORECASTING Introduction Forecasting Methods and Business Performance in Large Manufacturing Firms, in Kenya Forecasting and Measures of Business Performance Forecasting Methods, Operating Environment and Accuracy of Performance Forecasting Results of the Study Discussion of Results Comparison of Forecasting Methods in Accuracy of Performance Forecasting Identification of Performance Measures Influenced by the Operating Environment Assessment of the Moderating Effect of the External Operating Environment on the Relationship Between a Forecasting Method and Accuracy of Performance Forecasting Examination of the relationships among forecasting techniques, operating environment and accuracy of performance forecasting Comparison with Previous Studies 143 CHAPTER SIX: SUMMARY, CONCLUSION AND RECOMMENDATIONS Introduction Summary Conclusions Recommendations Implications Limitations Suggestions for Future Research

9 REFERENCES APPENDICES Appendix I: Letter of Introduction Appendix II: Research Questionnaire Appendix III: Determination of Sample Size Appendix IV: Cronbach Reliability Tests Appendix V: Tests for Linearity, Collinearity and Homoscedasticity Appendix VI: Zero-order Correlation for the Forecasting Methods. 196 Appendix VII: Sampling Frame Kenya Association of Manufacturers Directory

10 LIST OF TABLES Table Page 1 Classification of Business Size by Number of Employees. 7 2 Summary of Knowledge Gaps Summary of Operational Definitions of the Variables Summary of Analytical Methods Employed 43 5 Distribution of Firm Ownership Year of Establishment of the Firms Sectors of the Large Manufacturing Firms Distribution of Employees in Firms by Category Target Markets International Standards Organization Certification Frequency Table Respondents Positions Respondents Education Level Respondents Years of Experience Variables of the External Operating Environment Descriptive Statistics Origin of Customers Descriptive Statistics Concentration of Customers Descriptive Statistics Market Share - Model Summary Growth in Market Share Coefficients Customer Market Share Model Summary Origin of Customers and Market Share Coefficients Customer Market Penetration Model Summary Customer Market Penetration Coefficients Origin of Competitors Descriptive Statistics Concentration of Competitors Descriptive Statistics Competitors Market Share and Market Penetration Descriptive Statistics Competitors Market Share Correlations Origin of Suppliers Descriptive Statistics Characteristics of Suppliers Descriptive Statistics 62 10

11 29 Importance of Substitute Products Descriptive Statistics Origin of Substitute Products Descriptive Statistics Pricing of Substitute Products Descriptive Statistics Importance of Demographic Characteristics Descriptive Statistics Forecast Horizons Descriptive Statistics Forecasting Focus Descriptive Statistics Leadership Kaiser-Mayer-Olkim and Bartlett s Test Leadership - Rotated Components Matrix Strategy Kaiser-Mayer-Olkim and Bartlett s Test Strategy - Rotated Components Matrix Organizational Structure Kaiser-Mayer-Olkim and Bartlett s Test Organizational Structure Factor Reduction Organizational Culture Kaiser-Mayer-Olkim and Bartlett s Test Organizational Culture Factor Reduction Forecasting Methods Descriptive Statistics Forecasting Methods Model Summary Forecasting Methods - Regression Analysis Coefficients Judgmental Forecasting Method Model Summary Judgmental Forecasting Method - Regression Analysis, Coefficients Objective Forecasting Method Model Summary Objective Forecasting Method - Regression Analysis, Coefficients Combined Forecasting Method Model Summary Combined Forecasting Method - Regression Analysis, Coefficients Measures of Business Performance Descriptive Statistics Profit Growth - Model Summary Profit Growth Regression Analysis, Coefficients Return on Assets - Model Summary Return on Assets Analysis of Variance Return on Sales - Model Summary Return on Sales Coefficients Growth in Sales - Model Summary

12 60 Growth in Sales Regression Analysis, Coefficients Growth in Market Share - Model Summary Growth in Market Share Regression Analysis, Coefficients Employee Growth - Descriptive Statistics Quarterly Employee Growths - Correlation Matrix New Products Development Descriptive Statistics New Products Correlations Correlation Matrix Objective Forecasting Method Analysis of Variance Objective Forecasting Method Coefficients Objective Forecasting Method Analysis of Variance Objective Forecasting Method Coefficients Objective Forecasting Method Analysis of Variance Objective Forecasting Method - Coefficients Objective Forecasting Method - Coefficients Judgmental Forecasting Method Analysis of Variance Judgmental Forecasting Method Coefficients Judgmental Forecasting Method Analysis of Variance Judgmental Forecasting Method Coefficients Judgmental Forecasting Method Analysis of Variance Judgmental Forecasting Method Analysis of Variance Combined Forecasting Method Analysis of Variance Combined Forecasting Method Coefficients Combined Forecasting Method Analysis of Variance Combined Forecasting Method Coefficients Combined Forecasting Method Analysis of Variance Combined Forecasting Method Analysis of Variance Internal Operating Environment Model Summary Internal Operating Environment Coefficients Internal Operating Environment Coefficients Internal Operating Environment Coefficients External Operating Environment Coefficients

13 91 External Operating Environment Coefficients External Operating Environment Coefficients External Operating Environment Coefficients External Operating Environment Model Summary External Operating Environment Coefficients External Operating Environment Model Summary External Operating Environment Coefficients External Operating Environment Model Summary External Operating Environment Coefficients External Operating Environment Model Summary External operating environment Coefficients External Operating Environment Model Summary External Operating Environment Coefficients External Operating Environment Model Summary External Operating Environment Coefficients External Operating Environment Model Summary External Operating Environment Coefficients External Operating Environment Model Summary External Operating Environment Coefficients External Operating Environment Model Summary External Operating Environment Coefficients External Operating Environment Model Summary External Operating Environment Coefficients External Operating Environment Model Summary External Operating Environment Coefficients External Operating Environment Model Summary External Operating Environment Coefficients Internal Operating Environment Model Summary Internal Operating Environment Coefficients Internal Operating Environment Model Summary Internal Operating Environment Coefficients

14 122 Internal Operating Environment Model Summary Internal Operating Environment Coefficients Internal Operating Environment Model Summary Internal Operating Environment Coefficients Internal Operating Environment Model Summary Internal Operating Environment Coefficients Internal Operating Environment Model Summary Internal Operating Environment Coefficients Internal Operating Environment Model Summary Internal Operating Environment Coefficients Internal Operating Environment Model Summary Internal Operating Environment Coefficients Internal Operating Environment Model Summary Internal Operating Environment Coefficients Internal Operating Environment Model Summary Internal Operating Environment Coefficients Internal Operating Environment Model Summary Internal Operating Environment Coefficients Internal Operating Environment Model Summary Internal Operating Environment Coefficients Internal and External Operating Environments Model Summary Internal and External Operating Environments Coefficients Internal and External Operating Environments Model Summary Internal and External Operating Environments Coefficients Internal and External Operating Environments Model Summary Internal and External Operating Environments Coefficients Internal and External Operating Environments Model Summary Internal and External Operating Environments Coefficients Internal and External Operating Environments Model Summary Internal and External Operating Environments Coefficients Internal and External Operating Environments Model Summary

15 153 Internal and External Operating Environments Coefficients Internal and External Operating Environments Model Summary Internal and External Operating Environments Coefficients Internal and External Operating Environments Model Summary Internal and External Operating Environments Coefficients Internal and External Operating Environments Model Summary Internal and External Operating Environments Coefficients Internal and External Operating Environments Model Summary Internal and External Operating Environments Coefficients Internal and External Operating Environments Model Summary Internal and External Operating Environments Coefficients Internal and External Operating Environments Model Summary Internal and External Operating Environments Coefficients Summary of Hypotheses Test Results

16 LIST OF FIGURES Figure Page 1 Porter s 5-Forces Diagram 20 2 Conceptual Framework 28 3 Leadership Scree Plot 66 4 Strategy Scree Plot 68 5 Organizational Structure Scree Plot Organizational Culture Scree Plot 70 16

17 ABSTRACT This study explored the relationship among forecasting techniques, operating environment and APF in LMFs. Study objectives were to compare forecasting techniques in APF, identify performance measures influenced by the operating environment, assess moderating effects of the operating environment on the relationship between a method and APF and to examine the relationships among forecasting methods, operating environment and APF. A model and framework were formed on the basis of previous research, an empirical testing of the model was done after collecting data using a structured questionnaire. From a sample frame of 487 LMFs proportionate stratified random sampling was used to select a sample of 217 firms. Response rate was 81 percent. Data analysis used descriptive statistics, factor analysis, ANOVA, correlation and linear regression. Hypotheses were tested by analyzing independent effects of selected variables on APF. Results indicated there was empirical evidence that the effect of objective and combined forecasting techniques, and external operating environment on APF was strong. Conversely, empirical evidence indicated the effect of variables of the internal operating environment on APF was not strong. Further, the effect of variables of the external operating environment accounted for more variation in APF compared to variables of the internal operating environment. There was statistical evidence that competitors and external customers influence APF. For objective one the hypothesis on the influence between a forecasting method and accuracy of performance forecasting was tested using objective, judgmental and combined forecasting methods. Measures of accuracy of performance forecasting used were EV, ROS, ROA and growth in market share. Results provided statistical evidence that the three forecasting methods yielded APF against expected value and ROS. It was concluded that the three forecasting methods could be used to accurately forecast expected value and ROS. Objective two was to identify performance measures that were influenced by the operating environment in LMFs. The above performance measures were tested against leadership, strategy, structure and culture as elements of the internal operating environment and customers, competitors, suppliers, substitute products and demographic characteristics as parameters of the external operating environment. There was statistically significant evidence that, except for EV and ROS, external operating environment had an influence on APF. Objective three assessed moderating effect of external and internal operating environments on the relationship between a forecasting method and APF. Using regression analysis, results indicated that external operating environment had a partial moderating effect on the relationship between each of the forecasting methods and APF, with respect to ROS and ROA for the objective method and ROA for both combined and judgmental methods. Conversely, the internal operating environment had a moderating effect on the relationship between objective forecasting method and APF with respect to ROS. Objective four examined relationships among forecasting techniques, operating environment and APF. Using regression analysis, results showed that the joint effect of the operating environments had a partial moderating effect on the relationship between objective and combined forecasting methods and APF, with respect to EV and ROS. Study findings indicated that objective and combined forecasting yielded APF in a competitive environment. For APF a forecasting method should not ignore the effects of the operating environment. The study contributes by developing an exploratory model to link LMFs APF with variables of the operating environment. 17