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Student Number 92322084
Author Ming-Yang Wu(吳明陽)
Author's Email Address No Public.
Statistics This thesis had been viewed 1969 times. Download 1179 times.
Department Civil Engineering
Year 2005
Semester 2
Degree Master
Type of Document Master's Thesis
Language English
Title Data Envelopment Analysis for Auto-Assembler Suppliers' Evaluation of Performance
Date of Defense 2006-01-17
Page Count 75
Keyword
  • Auto-Assembler Suppliers
  • Data Envelopment Analysis
  • Performance Evaluation
  • Abstract Abstract
    This thesis specially addresses performance evaluation of auto-assembler suppliers in after market (AM). In order to tackle these issues, this study adopts data envelopment analysis (DEA) to measure the relative efficiency of resource utilization of auto assemblers in Taiwan. The input variables of the proposed DEA model include the operational indices and the financial indices. They are “the number of employees”, “the annual asset”, “the average inventory time”, and “the average production time”. The output variable is “the annual revenue” Considering the data imprecision about these two variables, “the number of employees” and “the annual revenue”, this thesis adopts three approaches of imprecise DEA to evaluate auto-assembler suppliers’ relative efficiency and to deal with the data imprecision. All approaches are based on the DEA methodology, including α-cut DEA approach, possibility FDEA approach and IDEA approach.
    In order to follow the principle “homogeneous” of DMUs when applying DEA model to evaluate efficiency, this study categorizes auto-assembler suppliers into auto-component suppliers and auto-accessories suppliers, by means of the products. This study sends questionnaires to the 303 Taiwan auto assemblers of after market, and 75 questionnaires are received. 39 auto-assembler suppliers are selected out of 75 responses. All of our survey firms are Small Medium Enterprises (SEMs).
    This thesis has successfully applied α-cut DEA, PFDEA and IDEA approaches to evaluate auto assemblers’ performance. We also find advantage and disadvantage of each approach. Besides, the efficiency score of comparison analysis, OTE analysis and PTE analysis are provided to the auto assemblers for their reference. The main research finding indicates that Taiwan auto assemblers are already operating at respectable levels of pure technical efficiency. The thesis finds that the overall technical inefficiency of auto assemblers of Taiwan is caused from the scale inefficiency. The implication of results reflect the auto assemblers operate well in company management even if the most part of auto assemblers in Taiwan are SMEs in realistic situation.
    Table of Content Table of Contents
    長式摘要   I
    Abstract   IV
    AcknowledgementV
    Table of ContentsVI
    List of FiguresVIII
    List of TablesVIII
    Chapter 1 Introduction1
    1.1 Research Background and Motivation1
    1.2 Research Objectives2
    1.3 Research Methods and Framework3
    1.4 Organization of the Thesis5
    Chapter 2 Literature Review6
    2.1 Performance Criteria of Suppliers’ Efficiency Evaluation6
    2.2 Application of DEA Methodology on Performance Evaluation9
    2.3 Summary of This Chapter11
    Chapter 3 Data Envelopment Analysis12
    3.1 Literature Review of DEA12
    3.2 Some Approaches for the Fuzzy Data16
    3.2.1 Defuzzification Approach16
    3.2.2 α-Cut Approach17
    3.3 Literature Review of Fuzzy DEA18
    3.4 Possibility Approach to CCR Model21
    3.4.1 Possibility Approach- an Optimistic Viewpoint21
    3.4.2 Possibility Approach- a Pessimistic Viewpoint24
    3.5 IDEA Approach26
    3.6 Summary of This Chapter26
    Chapter 4 Taiwan Auto Assemblers’ Industry Environment28
    4.1 Literature Review of Taiwan Automotive Industry28
    4.2 Brief Discussions of the Taiwan Auto Assemblers’ Environment29
    4.3 Challenges of Taiwan Auto Assemblers31
    4.4 Survey Questionnaire Data of Auto Assemblers32
    Chapter 5 Case Study38
    5.1 The Sampling Procedure and Description38
    5.2 Input/Output Variables of DEA Model39
    5.3 Interval Data of the Two Variables39
    5.4 Influence Degree of Input Variables on the Efficiency Score44
    5.5 Comparison of the Three Approaches47
    5.6 Data Analysis and Results52
    5.6.1 Efficiency Score of CCR-I Model52
    5.6.2 Efficiency Score of BCC-I Model55
    5.6.3 Overall Efficiency Scores57
    5.6.4 Reference Comparison Analysis60
    5.6.5 Sensitivity Analysis62
    5.7 Results Implication of This Chapter64
    Chapter 6 Conclusions and Future Research65
    6.1 Conclusions65
    6.2 Suggestion of Future Research66
    Reference   68
    Appendix I   71
    Appendix II  75
    Reference Reference
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    Advisor
  • none(張美香)
  • Huey-Kuo Chen(陳惠國)
  • Files
  • 92322084.pdf
  • approve immediately
    Date of Submission 2006-07-03

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