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研究生:王宗誠
研究生(外文):WANG, TSUNG-CHENG
論文名稱:經營績效評估之綜合管理架構研究-應用於國軍零售供應站
論文名稱(外文):A COMPREHENSIVE MANAGERIAL FRAMEWORK FOR OPERATING PERFORMANCE MEASUREMENT: Application in Taiwan’s Military Welfare Department
指導教授:楊千楊千引用關係
指導教授(外文):Chyan Yang
學位類別:博士
校院名稱:國立交通大學
系所名稱:管理科學系所
學門:商業及管理學門
學類:其他商業及管理學類
論文種類:學術論文
論文出版年:2006
畢業學年度:95
語文別:英文
論文頁數:66
中文關鍵詞:資料包絡分析法背景依賴資料包絡法吸引力測度進步測度零售店分層資料包絡分析法
外文關鍵詞:Data envelopment analysiscontext-dependent DEAattractiveness measureprogress measureretail storestratification DEA Method
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本研究主要以探索台灣國軍零售福利站之營運效率並擘劃運用標竿學習法指導營運效率不佳之零售店,學習經營效率極佳之福利站。 幾項實際之營運經驗法則分述如下: (1) 台灣國軍零售福利站之技術無效率,其主要由純技術無效率造成,而非規模無效率。 本研究同時也建議福利站之營運經理應先聚焦於純技術無效率之改革,而非先改進其規模無效率。 (2) 位於北部地區之零售福利站平均營運績效優於位於中部、南部、及東部之零售福利站。 由上述發現顯示零售福利站所處區域在影響營運績效上扮演一關鍵性腳色。 (3) 在不同層級對服務滿意度之零售福利站經營績效,確實有非常明顯之影響。 (4) 對顧客吸引力測度顯示,新營零售福利站為最具吸引力之福利站,如具全球化經營觀點之管理者。 同時,不論用何種評審標準與流程顯示台東零售福利站與其他福利站相比較,均不具競爭力。(5) 用資料包絡分析法(DEA) 相互關連性可顯示出零售福利站之標竿學習路徑,使吾等可得知如何改進無效率之零售福利站與確認何者是最具績效福利站。故本研究運用DEA評估國軍零售福利站之經營效率為重要實務之運用。
A comprehensive framework of performance measurement is developed and illustrated through application to in Taiwan’s Military Welfare Department. This dissertation aims to explore the operating efficiency and the benchmark-learning roadmap of retail stores for the General Welfare Service Ministry (GWSM) in Taiwan. Several empirical results are shown: (1) the overall technical inefficiencies of GWSM retail stores are primarily due to the pure technical inefficiencies rather than the scale inefficiencies. This also suggests that managers should focus on removing the pure technical inefficiency of retail stores, before improving their scale efficiencies; (2) the retail stores located on north on the average operate better than those on the other three regions. The findings show that the retail store’s region plays key role which affects its operating performance; (3) the service-satisfaction levels do have a very significant influence upon retail store’s performance; (4) the attractiveness measure shows that Hsinying retail store is the most attractive retail store, i.e. global leader, no matter which evaluation context is chosen, and the progress measure shows that Taitung retail store is the worst retail store; (5) the context-dependent DEA successfully draws the GWSM retail stores’ benchmark-learning roadmap to improve the inefficient retail stores progressively and can identify the best retail store. The potential applications and strengths of DEA in assessing the military retail stores are highlighted.
CONTENTS
中文摘要……………………………………………………………………….... i
Abstract………………………………………………………………………...... ii
Acknowledgement………………………………………………………………..iii
Table List………………………………………………………………................iv
Figure List……………………………………………………………………….. v
Acronyms and Abbreviations…………………………………………………….vi
Chapter 1. Introduction
1.1 History…………………………………………………………………... 1
1.2 Organization and Employee…………………………………………….. 1
1.3 Principles of Management……………………………………….............3
1.4 Research Motivation…………………………………………………..…3
1.5 Research Purposes...……………………………………………………..3
1.6 Organization of Dissertation……………………………………………..4
Chapter 2. Literature Review
2.1 Literature Survey…………………………………………………………6
2.2 Data Selection and Description…………………………………..............6
Chapter 3. Methodology
3.1 Technical Efficiency Measure…………………………………………...10
3.2 Context-Dependent DEA………………………………………..............13
3.2.1 Stratification DEA Method ...…………………………………….....13
3.2.2 Multiplier Model of the CCR/BCC Model……………………….....15
3.2.3 The Dual Program of the CCR/BCC Model………………………...18
3.2.4 The Slack-Adjusted CCR/BCC Model……………………………. .19
3.2.5 Returns to Scale……………………………………………………..21
3.2.6 Context-Dependent DEA…………………………………………..22
Chapter 4. Empirical Results and Analysis
4.1 Performance of GWSM Retail Stores…………………………………..25
4.2 Analysis of Managerial Decision-Making Matrix……………………...29
4.3 Constructing a Benchmark-Learning Roadmap………………………...31
4.4 Discussion………………………………………………………………38
Chapter 5. Conclusion Remarks
5.1 Conclusion……………………………………………………………....41
5.2 Suggestion………………………………………………………………42
Reference………………………………………………………………………..44
Appendix………………………………………………………………………..50
Resume………………………………………………………………………….64
[1] Andersen, P. and Petersen, N.C. (1993), A procedure for ranking efficient units in data envelopment analysis, Management Science 39 (10), 1261-1264.
[2] Angulo-Meza, L. and Lins, M.P.E. (2002), Review of methods for increasing discrimination in data envelopment analysis, Annals of Operations Research 116 (1), 225-242.
[3] Baker, R.C. and Talluri, S. (1997), A closer look at the use of data envelopment analysis for technology selection, Computers Industry and Engineering 32 (10), 101-108.
[4] Banker, R.D., Charnes, A. and Cooper, W.W. (1984), Some models for estimating technical and scale inefficiencies in data envelopment analysis, Management Science 30 (9), 1078-1092.
[5] Banker, R.D. and Thrall, R.M. (1992), Estimation of returns to scale using data envelopment analysis, European Journal of Operational Research 62 (1), 74-84.
[6] Banker, R.D., Bardhan, I. and Cooper, W.W. (1995), A note on returns to scale in DEA, European Journal of Operational Research 88 (3), 583-585.
[7] Banker, R.D., Chang, H. and Cooper, W.W. (1996), Equivalence and implementation of alternative methods for determining returns to scale in data envelopment analysis, European Journal of Operational Research 89 (3), 473-481.
[8] Brockett, P.L. and Golany, B. (1996), Using rank statistics for determining programmatic efficiency differences in data envelopment analysis, Management Science 42 (3), 466-472.
[9] Barros, C P and Alves C (2003), Hypermarket retail store efficiency in Portugal, International Journal of Retail and Distribution Management 31(11), 549-560.
[10] Barros, C P and C Alves (2004), An empirical analysis of productivity growth in a Portuguese retail chain using Malmquist productivity index, Journal of Retailing and Consumer Services 11, 269-278.
[11] Barros, C P (2005), Efficiency in hypermarket retailing: a stochastic frontier model, The International Review of Retail, Distribution and Consumer Research 15(2), 171-189.
[12] Brockett, P L and B Golany (1996), Using rank statistics for determining programmatic efficiency differences in data envelopment analysis, Management Science 42, 466-472.
[13] Bush, R P , A J Bush, D J Ortinau, and J F Hair (1990), Developing a behavior-based scale to assess retail salesperson performance, Journal of Retailing 66, 119-136.
[14] Byrnes, P., Färe, R. and Grosskopf, S. (1984), Measuring productive efficiency: An application to Illinois strip mines, Management Science 30 (6), 671-681.
[15] Charnes, A., Cooper, W.W. and Rhodes, E. (1978), Measuring the efficiency of decision making units, European Journal of Operational Research 2 (6), 429-444.
[16] Charnes, A., Clark, C.T., Cooper, W.W. and Golany B. (1985), A development study of data envelopment analysis in measuring the efficiency of maintenance units in the U.S. Air Forces, Annals of Operations Research 2, 95-112.
[17] Charnes, A., Cooper, W.W. and Li, S. (1989), Using DEA to evaluate relative efficiencies in the economic performance of Chinese key cities, Socio-Economic Planning Sciences 23 (6), 325-344.
[18] Charnes, A., Lewin, A., Cooper, W.W. and Seiford, L.M. (1994), Data envelopment analysis: theory, methodology and application, Boston: Kluwer Academic Publishers.
[19] Chen, Y, H Morita, and J Zhu (2005), Context-dependent DEA with an application to Tokyo public libraries, International Journal of Information Technology and Decision Making 4(3), 385-394
[20] Cooper, W.W., Seiford, L.M. and Tone, K. (2000), Data envelopment analysis: a comprehensive text with models, applications, references and DEA-solver software, Boston: Kluwer Academic Publishers.
[21] Cooper, W.W., Li, S., Seiford, L.M., Tone, K., Thrall, R.M. and Zhu, J. (2001), Sensitivity and stability analysis in DEA: some recent developments, Journal of Productivity Analysis 15 (3), 217-246.
[22] Cooper, W.W., Deng, H., Gu, B., Li, S. and Thrall, R.M. (2001), Using DEA to improve the management of congestion in Chinese industries (1981–1997), Socio-Economic Planning Science 35 (4), 227-242.
[23] Doyle, J. and Green, R. (1994), Efficiency and cross-efficiency in DEA: Derivation, meanings and uses, Journal of Operational Research Society 45 (5), 567-578.
[24] Enz, C. and Canina, L. (2002), Best of times, the worst of times: difference in hotel performance following 9/11, Cornell Hotel & Restaurant Administration Quarterly 43 (5), 22-32.
[25] Färe, R., Grosskopf, S. and Lovell, C.A.K. (1985), The Measurement of Efficiency of Production, Kluwer Nijhoff, Boston.
[26] Färe, R., Grosskopf, S., Lindgren, B. and Roos, P. (1992), Productivity Changes in Swedish Pharmacies 1980-1989: a non-parametric malmquist approach, Journal of Productivity Analysis 3 (1), 85-101.
[27] Färe, R. and Grosskopf, S. (1994), Estimation of returns to scale using data envelopment analysis: A comment, European Journal of Operational Research 79 (2), 379-382.
[28] Fay, C.T., Rhoads, R.C. and Rosenblatt, R.L. (1971), Managerial Accounting for Hospitality Service Industries, Bubuque, Iowa, William C. Brown Publishers.
[29] Gattoufi, S., Oral, M. and Reisman, A. (2004), Data envelopment analysis literature: bibliography update (1951-2001), Socio-Economic Planning Sciences 38 (2-3),159-229.
[30] General Welfare Service Ministry (2003), The operating annual report of retail stores in General Welfare Service Ministry, Ministry of National Defense, Taiwan, 2004. (In Chinese)
[31] Good, W S (1984), Productivity in the retail grocery trade, Journal of Retailing 60, 91-97.
[32] Ismail, J., Dalor, M. and Mills, J. (2002), Using RevPar to analyze lodging-segment variability, Cornell Hotel & Restaurant Administration Quarterly 43 (6), 73-80.
[33] Jaedicke, R.K. and Robichek, A.A. (1975), Cost-volume-profit analysis under conditions of uncertainty. In A. Rappaport (ed.), Information for Decision-Making-Quantative and Behavioural Dimensions (2nd Edition), Prentice-Hall, Englewood, Cliffs, NJ.
[34] Kimes, S.E. (1989), The basics of yield management, Cornell Hotel & Restaurant Administration Quarterly 30 (3), 14-19.
[35] Keh, H. T. and S. Chu (2003), Retail productivity and scale economies at the firm level: a DEA approach, Omega, International Journal of Management Science 31, 75-82.
[36] Lewin, A.Y., Morey, R.C. and Cook, T.J. (1982), Evaluating the administrative efficiency of courts, Omega, International Journal of Management Science 10 (4), 401-411.
[37] Li, X.B. and Reeves, G.R. (1999), A multiple criteria approach to data envelopment analysis, European Journal of Operational Research 115 (3), 507-517.
[38] Seiford, L.M. (1997), A bibliography for data envelopment analysis (1978-1996), Annals of Operations Research 73, 393-438.
[39] Seiford, L.M. and Zhu, J. (1999), Infeasibility of super-efficiency data envelopment analysis, INFOR 37 (2), 174-187.
[40] Sexton, T., Silkman, R. and Hogan, A. (1986), Data Envelopment Analysis: Critique and Extensions, Measuring Efficiency: An Assessment of Data Envelopment Analysis, New Directions for Program Evaluation, San Francisco: Jossey-Bass.
[41] Sherman, H.D. (1986), Managing productivity of health care organizations in R.H. Silkman (eds.), San Francisco, Jossey-Bass Inc., Publishers.
[42] Smith, P. and Mayston, D. (1987), Measuring efficiency in the public sector, Omega, International Journal of Management Science 20 (3), 181-189.
[43] Sueyoshi, T. (1999), Data envelopment analysis non-parametric ranking test and index measurement: Slack-adjust DEA and an application to Japanese agriculture cooperatives, Omega, International Journal of Management Science 27 (3), 315-326.
[44] Thomas, R. R., R. S. Barr, W. L. Cron, and J. W. Slocum Jr (1998), A process for evaluating retail store efficiency: a restricted DEA approach, International Journal of Research in Marketing 15, 487-503.
[45] Thrall, R.M. (1996), Duality, classification and slacks in DEA, Annals of Operations Research 66, 109-138.
[46] Tone, K. (2001), A slacks-based measure of efficiency in data envelopment analysis, European Journal of Operational Research 130 (3), 498-509.
[47] Tone, K. (2002), A slacks-based measure of super-efficiency in data envelopment analysis, European Journal of Operational Research 143 (1), 32-41.
[48] Torgersen, A.M., Førsund, F.R. and Kittelsen, S.A.C. (1996), Slack-adjusted efficiency measures and ranking of efficient units, Journal of Productivity Analysis 7 (4), 379-398.
[49] Van Doren, C.S. and Gustke, L.D. (1982), Spatial analysis of the U.S. lodging industry, Annals of Tourism Research 9 (4), 543-563.
[50] Wassenaar, K. and Stafford, E.R. (1991), The lodging index: an economic indicator for the hotel/motel industry, Journal of Travel Research 30(1), 81-21.
[51] Wijeysingle, B.S. (1993), Breakeven occupancy for a hotel operation, Management Accounting 71 (2), 32-33.
[52] Zhu, J. (1996a), DEA/AR analysis of the 1988-1989 performance of the Nanjing Textiles Corporation, Annals of Operations Research 66, 311-335.
[53] Zhu, J. (1996b), Robustness of the efficient DMUs in data envelopment analysis, European Journal of Operational Research 90 (3), 451-460.
[54] Zhu, J. (2000), Multi-factor performance measure model with an application to Fortune 500 companies, European Journal of Operational Research 123 (1), 105-124.
[55] Zhu, J. and Shen, Z. (1995), A discussion of testing DMUs' returns to scale, European Journal of Operational Research 81 (3), 590-596.
[56] Zhu, J. (2003), Quantitative Models for Performance Evaluation and Benchmarking: Data Envelopment Analysis with Spreadsheets, Kluwer Academic Publishers, Boston
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1. 沈志仁、張素凰(1991)。精神病患家屬的壓力源、應對策略與健康狀況—時間序列的探討。中華心理衛生學刊,5(2),103-12
2. 毛家舲(1984)。從家屬座談看照顧精神病病人的問題。護理雜誌,31(4),17-25。
3. 李選、盧瑛琪、顏文娟、林淑琴(2004)。中年期於人生轉折過程中所呈現之健康問題與因應。護理雜誌,51(1),14-19。
4. 李淑霞、吳淑瓊(1998)。家庭照護者負荷與憂鬱之影響因素。護理研究,6(1),57-67。
5. 李姿瑩、蔡芸芳、楊美賞(2000)。花蓮地區原住民與非原住民精神分裂病患主要照顧者需求極其相關因素探討。慈濟醫學,12(4),247-256。
6. 宋麗玉(1999)。精神病患照顧者之憂鬱程度與其相關因素探討。公共衛生,25(3),181-196
7. 呂寶靜(1998)。老人非正式和正式照顧體系關係之初探--從家人和日託中心工作員協助項目的比較分析出發。社會政策與社會工作學刊,2(1) ,3-38。
8. 吳瓊滿 (1999)。居家照顧者的負荷。美和專校學報,17,1-14。
9. 吳就君、楊延光、黃梅羹 (1996 )。檢式工具評估精神病患家屬表露情緒行為與家庭負荷、拒絕病患之關係。衛生教育論文集刊,9,37-53。
10. 吳就君(1995)。精神病患家庭照護者的負荷研究:跨國文化比較。中華心理衛生學刊,8(1),37-52。
11. 江漢光(1996)。罹患精神疾病青少年之個案輔導。教師天地,154,38-40。
12. 古永嘉、張威龍(2000)。社會期望反應偏差對付面消費者行為研究的影響:以物質主義為例的間接量表驗證。企業管理學報,46,49-76。
13. 王建楠、吳重達(2003)。兒童及青少年憂鬱症。基層醫學,18(7),154-165。
14. 毛家舲(1986)。家屬對精神疾病的反應-文獻查證。護理雜誌,33(4),13-2。
15. 沈詠萱、詹其峰、呂碧鴻(2003)。青少年憂鬱症。基層醫學,18(4),84-90