ABSTRACT
In today’s complex and aggressive business environments, it is only an effective decision making that gives organizations an edge over their competitors. Since organizations continuously make decisions, managers should ensure that it is done scientifically so as to minimize the inherent risk of errors in the subjective approach to decision making. This work seeks to appraise the application of operations research techniques in the decision making processes of manufacturing companies. This study therefore sets to identify the various operations research tools applied in decision making, the benefits of using operations research and the various limitations to its application. The target population of this study is made up of the entire top, middle and lower management staff of the selected manufacturing companies; Innoson, Anammco and Juhel Nigeria Limited. Stratified sampling method was adopted so as to give a fair representation to the selected organizations in the ratio of 3:5:2 using the proportionality formular.(Q=A/N × n/1). The study obtained its data from both primary and secondary sources. The questionnaire was the major instrument of collecting data for the research. Interviews were also conducted to complement the information from the questionnaire. Data analysis was done through the use of tabular presentation, pie and bar charts. The five (5) formulated hypothesis were also tested for acceptance or rejection using the chi-square statistical technique. The findings indicates that linear programming, Network Analysis and decision trees are some of the operations research tools used in decision making and that the benefits enjoyed as a result of applying operations research to decision making justifies the expenditure incurred in that respect. The study also recommends that the use of operations research should be encouraged and sustained in view of the numerous benefits it offers to firms and that firms should embark on aggressive training of personnel to reduce resistance to its use.
TABLE OF CONTENTS
Title page – – – – – – – – i
Certification – – – – – – – ii
Dedication – – – – – – – iii
Acknowledgement – – – – – – iv
Abstract – – – – – – – – vii
Table of Contents – – – – – – viii
CHAPTER ONE: INTRODUCTION
- Background of Study – – – – 1
- Statement Of The Problems – – – 9
- Objectives of the Study – – – – 11
- Research Questions – – – – 11
- Research Hypotheses – – – – 12
- Significance of the Study – – 13
- Scope of the Study – – – – 14
- Limitation of Study – – – – 15
- Historical Background Of Firms Used –
- Definition of Terms – – – – 16
References – – – – – – 17
CHAPTER TWO: REVIEW OF RELATED LITERATURE
2.1 Operation Research Defined – – – 18
2.2 Evolution of Operations Research – – 19
2.3 Nature and Characteristics of operations
Research – – – – – – – 20
2.4 Procedures in Conducting Operations Research 22
2.5 Model Building in Operations Research – 26
2.6 Importance of Models in Operations Research 27
2.7 Classification Schemes of Models – – 28
2.8 Characteristics of a Good Models – – 31
2.9 Techniques of Operations Research – – 31
2.10 Decision Making in Organizations – – 40
2.11 Types and Characteristics of Managerial
Decisions – – – – – – – 45
2.12 Characteristics of the Decision Process – 46
2.13 Decision Techniques – – – – – 48
2.14 Blue Print for Decision Making – – – 50
2.15 Scope and Application of Operations Research
in Management Decision Making – – 52
2.16 Managing the Decision Making Process – 54
2.17 Human Side of Operations Research – 55
2.18 Limitations of Operations Research – – 56
References – – – – – – 58
CHAPTER THREE: RESEARCH METHODOLOGY
3.1 Introduction – – – – – – 60
3.2 Sources of Data – – – – – 60
3.3 Population of the Study – – – – 61
3.4 Method of Sampling – – – – – 62
3.5 Research Instruments – – – – 64
3.6 Data Analysis Techniques – – – – 65
3.7 Validation of Instruments for Data Collection 66
References – – – – – – 67
CHAPTER FOUR: PRESENTATION, ANALYSIS AND DATA INTERPRETATION
4.1 Data Presentation – – – – – 69
4.2 Data Analysis – – – – – – 69
4.3 Hypotheses Testing – – – – – 96
CHAPTER FIVE: SUMMARY OF FINDINGS, CONCLUSIONS AND RECOMMENDATIONS
5.1 Summary of Findings – – – – 118
5.2 Conclusions – – – – – – 120
5.3 Recommendations – – – – – 121
BIBLIOGRAPHY
APPENDIX
CHAPTER ONE
INTRODUCTION
1.1 BACKGROUND OF THE STUDY
Everyday, managers makes decisions that commit organizational resources. These decisions determine the survival, growth or even death of an organization. The decision making process is not always activated when a manager perceives a problem as most decisions are made to ensure the stability, continuity and expansion of good prospects and operating performance. (Akintoye and Oluwatosin, 2006; 387).The Process of decision making requires the analysis of alternative solutions and the identification and selection of the alternative that offers the best outcome.
Managers today especially in developing countries use exclusively experience, hunches and rule of thumb in their decision making process. This qualitative approach may be found useful and adequate in certain circumstances but inadequate in others. When the problem is repetitive and the data are quantifiable, we find greater scope for the application of the quantitative techniques to ensure rational and logical decisions.
Okeke (1996; 1) opines that in the qualitative approach to decision making, the manager relies on his personal intuition or past experience in solving similar problems. Such an Intuitive “feel” for the problem may be sufficient for making a decision. He however concluded that there are problems for which more quantitative approach is inevitable.
This quantitative approach that we mean here goes by so many names; Management science, operations research, Quantitative Management, Decision Sciences, Systems Analysis etc. Although attempts have been made by some writers to differentiate these terms, they are quite often used interchangeably, their unifying factor or common denominator being their utilization of the techniques of Mathematics, Engineering, Economics, Computer Science etc in finding solutions to organizational problems.
Operations Research is simply defined as the application of scientific methodology in making more explicit, more systematic and better decisions. (Litterer, 1978:171).Scientific methodology is defined as a process of or logical approach to developing models that explain and predict real-world behavior. (Dannenbring and starr, 1988:1).Thus operation research seeks to describe, understand and predict the behavior of complex systems of human beings and equipment (Stoner, 1982:186).
As the name implies, one can say that operations research means research on operations. Filley and House (1969:10) have noted that organizations and their component units carry on goal-oriented activities referred to as “operations” and that the systematic study leading to decisions as to which operations should be undertaken and how they should be tackled is termed “research”. What management scientists or operations researchers do is to observe decision making environment, try to identify, define and analyze problems, construct models which seek to solve these problems, choose those inputs of data required for a solution, find the optimal solution when it could be found and help in the implementation of the identified solution(Levin et al,1986:5).Operations research provides managers with quantitative basis for decision making and enhance their ability to make long range plans and develop broad strategy.
Operations research is approached in a spirit that demands that decision problems be properly defined, analyzed and solved in a conscious, rational, logical, systematic and scientific manner based on data, facts, information and logic (Loomba, 1978:25).The quantitative techniques inherent in management science are not to be regarded as an explicit formular to be uniformly applied to all types of situations. Rather, it is a style of management, which demands a conscious, systematic and scientific analysis and resolution of decision proba,1978:26-27).But the fact that the use of quantitative data constitutes the corner stone of operations research does not in any way preclude the use of qualitative analysis in arriving at optimal decisions. The quantitative approach, must build upon, be modified by and continually benefit from the experiences and creative insights of managers. The final stage in the decision making process, after all, is the exercise of judgment and in making this judgment, the decision taker has to take different factors-quantitative and qualitative into account. For example, there may be sudden change in government policy or of government itself, change of weather, technological advancement and so on. And this makes it very necessary for managers to involve qualitative approaches in decision making.
1.2. STATEMENT OF THE PROBLEMS
