共同邊界動態網路差額基礎衡量(MDN-SBM)模型之建立與應用─以航空公司之營運績效評估為例

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姓名

蔡孟佑(Mon-You Tsai) 查詢紙本館藏

畢業系所

土木工程學系

論文名稱

共同邊界動態網路差額基礎衡量(MDN-SBM)模型之建立與應用─以航空公司之營運績效評估為例
(The Meta Dynamic Network Slack-based Measure: Efficiency Evaluation of Global Airlines)

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摘要(中)

本研究以差額變數基礎衡量模型(slack-based measure, SBM)為基礎，整合網路SBM、動態SBM以及共同邊界模型，發展出共同邊界動態網路SBM(meta dynamic network slack-based measure, MDN-SBM)，並進一步納入變異模型(Tone, 2010)之概念，建構出一般化之績效評估模型稱之為MDN-SBM變異模型。最後以全球50家航空公司為例進行績效衡量，結果顯示廉價航空與一般航空公司之在於MDN-SBM模型衡量結果之平均營運效率值無明顯的差異，但於共同技術比率(metatechnology ratio, MTR)廉價航空明顯的較一般航空公司低，表示廉價航空之生產技術較一般航空公司差。

摘要(英)

In non-parametric boundary analysis, there are 2 methods for measuring performance, e.q. the data envelopment analysis (DEA) and the slack-based measure (SBM). In this paper, we focus on SBM methods, and we integrate their models in the SBM framework, called meta dynamic network slack-based measure (MDN-SBM). Furthermore, for improving the shortcoming of SBM model, we combine the MDN-SBM model and SBM variations methods. Last we apply MDN-SBM model to evaluate performance of the 50 airlines of worldwide. Our findings indicate that, in general, there is no different between full service carriers (FSC) and low cost carriers (LCC) in the result of MDN-SBM model. But it different at metatechnology ratio (MTR), which present that the MTR value of LCC is lower than FSC.

關鍵字(中)

★ 資料包絡分析
★ MDN-SBM
★ 變異模型
★ 廉價航空公司
★ 一般航空公司

關鍵字(英)

★ DEA
★ MDN-SBM
★ variations
★ low cost carrier
★ full service carrier

論文目次

摘要 I
ABSTRACT II
致謝 III
目錄 IV
圖目錄 VI
表目錄 VII
第一章緒論 1
1.1研究背景與動機 1
1.1.1 資料包絡分析擴張模型發展 1
1.1.2 航空產業特性 2
1.2研究目的 3
1.3研究對象與範圍 3
1.4研究流程 5
第二章文獻回顧 7
2.1 DEA模型發展 9
2.1.1 CCR以及BCC模型 9
2.1.2 麥氏生產力指數 10
2.1.3 網路DEA 11
2.1.4 共同邊界 12
2.1.4 運輸產業特性 13
2.2 SBM模型發展 14
2.2.1 SBM模型 14
2.2.2 SBM 麥氏生產力指數模型 14
2.2.3 網路SBM 15
2.2.3 SBM變異模型 15
2.2.4 動態SBM 16
2.3運用資料包絡分析於航空公司之文獻 16
2.4 小結 17
第三章現有文獻之SBM模型 20
3.1 SBM模型 22
3.2 網路SBM 24
3.3 動態SBM 27
3.3.1 投入導向 29
3.3.2 產出導向 30
3.3.3 考慮任意變動項 31
3.4 共同邊界 33
3.4.1 共同邊界與群體邊界生產技術集合 33
3.4.2 共同技術比率 34
3.5 運輸產業特性 34
3.6 小結 35
第四章群體邊界動態網路差額衡量基礎模型 36
4.1 生產技術集合與生產可能集合 39
4.2 目標式與效率值 42
4.2.1 投入導向 42
4.2.2 產出導向 45
4.2.3 無導向 48
4.3 任意變動項納入效率值評估 50
4.4 投射(projection) 52
4.5 群體邊界動態網路SBM變異模型 53
4.6 運出產業群體邊界動態網路SBM模型 55
4.6.1 運輸產業不可儲存性 55
4.6.2 運輸安全特性 56
4.6.3 無導向模型之計算 60
4.7 小結 64
第五章共同邊界動態網路差額衡量基礎模型 66
5.1 共同邊界動態網路SBM投入導向模型 69
5.2 共同邊界動態網路SBM變異模型 74
5.3 運輸產業共同邊界動態網路SBM模型 76
5.4 共同技術比率(MTR) 79
5.5 小結 80
第六章案例分析 81
6.1 獨立模型 82
6.2 MDN-SBM模型分析結果 82
6.3 共同技術比率分析 85
第七章結論與建議 89
參考文獻 92
附錄1 111
附錄2 112
附錄3 113
附錄4 115

參考文獻

[1] 吳濟華、何柏正，組織效率與生產力評估資料包絡分析法，前程文化事業有限公司，2008。
[2] 陳谷劦、楊浩彥，共同邊界Malmquist生產力指數的延伸：跨國總體資料的實證分析，經濟論文叢刊，第36卷，第四期，頁551-588，2008。
[3] 陳惠國，研究方法理論與實務，滄海書局，頁 179-209，2010。
[4] Banker R.D., Charnes A. and Cooper W.W., “Some models for estimating technical and scale inefficiencies in data envelopment analysis”, Management Science, Vol. 30, pp. 1078-1092, 1984.
[5] Barbot C., Costa A. and Sochirca E., “Airlines performance in the new market context: A comparative productivity and efficiency analysis”, Journal of Air Transport Management, Vol. 14(5), pp. 270-274, 2008.
[6] Barros C. P. and Peypoch N., “An evaluation of European airlines’ operational performance”, International Journal of Production Economics, Vol. 122(2), pp. 525-533, 2009.
[7] Battese G. E., Rao D. S. P. and O’Donnell C. J., “A metafrontier production function for estimation of technical efficiencies and technology gaps for firms operating under different technologies”, Journal of Productivity Analysis, Vol. 21(1), pp. 91-103, 2004.
[8] Caves D., Christensen L. and Diewert E., “The economic theory of index numbers and the measurement of input, output, and productivity”, Econometrica, Vol. 50, pp. 1393- 1414, 1982.
[9] Chang Y. C. and Yu M. M., “Measuring production and consumption efficiencies using the slack-based measure network data envelopment analysis approach: the case of low-cost carriers”, Journal of Advanced Transportation, 2012. DOI: 10.1002/atr.198
[10] Charnes A. Cooper W.W. and Rhodes E., “Measuring the efficiency of decision-marking units”, European Journal of Operational Research, Vol. 2, pp. 429-444, 1978.
[11] Chen K., “Evaluation of US legacy airline distribution strategies”, Journal of Air Transport Management, Vol. 16, pp. 337-339, 2010
[12] Chen K. H., Huang Y. J. and Yang C. H., “Analysis of regional productivity growth in China: A generalized metafrontier MPI approach”, China Economic Review, Vol. 20, pp. 777-792, 2009.
[13] Chen Y., “A non-radial Malmquist productivity index with an illustrative application to Chinese major industries”, International Journal of Production Economics, Vol. 83, pp. 27-35, 2003.
[14] Chen Y., Cook W. D., Kao C. and Zhu J., “Network DEA pitfalls: Divisional efficiency and frontier projection under general network structures”, European Journal of Operational Research, Vol. 226, pp. 507-515, 2013.
[15] Chiou Y. C. and Chen Y. H., “Route-based performance evaluation of Taiwanese domestic airlines using data envelopment analysis”, Transportation Research Part E: Logistics and Transportation Review, Vol. 42(2), pp. 116-127, 2006.
[16] Chiou T.Y., Lan L.W. and Yen T.H., “A joint measurement of efficiency and effectiveness for non-Storable commodities: integrated data envelopment analysis approaches”, European Journal of Operational Research, Vol. 201(2), pp. 477-489, 2010.
[17] Chow C. K. W., “Measuring the productivity changes of Chinese airlines: The impact of the entries of non-state-owned carriers”, Journal of Air Transport Management, Vol. 16(6), pp. 320-324, 2010.
[18] Cooper W. W., Seiford L. M., Tone K., Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-solver Software, Springer, 2007.
[19] Färe R. and Grosskopfb S., ”Network DEA”, Socio-Economic Planning Sciences, Vol. 34(1), pp. 35-49, 2000.
[20] Färe R., Grosskopf S., Norris M. and Zhang Z., “Productivity growth, technical progress, and efficiency change in industrialized countries”, American Economic Review, Vol. 84, 1994.
[21] Farrell M. J., “The measurement of productive efficiency”, Journal of the Royal Statistical Society Series A, General 120 (part 3), pp. 253-281, 1957.
[22] Fethi M. D., Jackson P. M. and Weyman-Jones T. G., “European airlines: a stochastic DEA study of efficiency with market liberalization”, Paper Presented at the Seventh European Workshop on Efficiency and Productivity Analysis, University of Oviedo, 2001.
[23] Fielding G. J., Brener M. E. and Faust K., “Typology for bus transit”, Transportation Research A, Vol. 19(3), pp. 269-278, 1985.
[24] Greer M. R., “Nothing focuses the mind on productivity quite like the fear of liquidation: changes in airline productivity in the United States, 2000-2004”, Transportation Research Part A, Vol. 42, pp. 414-426, 2008.
[25] Hayami Y. and Ruttan V. W., “Factor prices and technical change in agricultural development: The United States and Japan, 1880-1960”, Journal of Political Economy, Vol. 78, pp. 1115-1141, 1970.
[26] Hayami Y., “Sources of agricultural productivity gap among selected countries”, American Journal of Agricultural Economics, Vol. 51, pp. 564-575, 1969.
[27] Lin E. T. J. and Lan L. W., “Accounting for accidents in the measurement of transport inefficiency: A case of Taiwanese bus transit,” International Journal of Environment and Sustainable Development, Vol. 8, pp. 365-385, 2009.
[28] Lin E. T. J., “Route-based performance evaluation of Taiwanese domestic airlines using data envelopment analysis: A comment”, Transportation Research Part E: Logistics and Transportation Review, Vol. 44(5), pp. 894-899, 2008.
[29] Lu W. M., Wang W. K., Hung S. W. and Lu E. T., “The effects of corporate governance on airline performance: Production and marketing efficiency perspectives”, Transportation Research Part E, Vol. 48, pp. 529-544, 2012.
[30] O’Donnell C. J., Rao D. S. P., and Battese G. E., “Metafrontier frameworks for the study of firm-level efficiencies and technology ratios”, Empirical Economics, Vol. 34, pp.231-255, 2008.
[31] Pires H. M. and Fernandes E., “Malmquist financial efficiency analysis for airlines”, Transportation Research Part E, Vol. 48, pp. 1049-1055, 2012.
[32] Rambaldi A. N., Rao D.S. P., Dolan D., “Measuring productivity growth performance using meta-frontiers with applications to regional productivity growth analysis in a global context”, In: O’Donnell, C. J., Australian Meeting of the Econometric Society ESAM07, pp. 1-33, 2007.
[33] Scheraga C. A., “Operational efficiency versus financial mobility in the global airline industry: a data envelopment and Tobit analysis”, Transportation Research Part A, Vol. 38, pp. 383-404, 2004.
[34] Tone K., “A slacks-based measure of efficiency in data envelopment analysis” European Journal of Operational Research, Vol. 130, pp. 498-509, 2001.
[35] Tone K. and Tsutsui M., “Network DEA: A slacks-based measure approach”, European Journal of Operational Research, Vol. 197(1), pp. 243-252, 2009.
[36] Tone K. and Tsutsui M., “Dynamic DEA: A slacks-based measure approach”, Omega, Vol. 38(3-4), pp. 145-156, 2010.
[37] Tone K., “Malmquist production index: efficiency change over time”, Cooper W.W., Seiford L.M., Zhu J. (Eds.), Handbook on Data Envelopment Analysis (Chapter 8), Kluwer Academic Publishers, Dordrecht ,2004.
[38] Tone K., “Variations on the theme of slacks-based measure of efficiency in DEA”, European Journal of Operational Research, Vol. 200(3), pp. 901-907, 2010.
[39] Yu M. M., “Assessing the technical efficiency, service effectiveness, and technical effectiveness of the world’s railways through NDEA analysis”, Transportation Research Part A, Vol. 42, pp. 1283-1294, 2008.
[40] Yu M. M. and Lin E. T. J., “Efficiency and effectiveness in railway performance using a multi-activity network DEA model”, Omega, Vol. 36, pp. 1005-1017, 2008.
[41] Yu M. M. and Fan C. K., “Measuring the performance of multimode bus transit: A mixed structure network DEA model”, Transportation Research Part E, Vol. 45, pp. 501-515, 2009.
[42] Yu M. M. and Fan C. K., “Measuring the cost effectiveness of multimode bus transit in the presence of accident risks”, Transportation Planning and Technology, Vol. 29(5), pp. 383-407, 2006.
[43] Yu M. M., “Performance assessment of transport services with the ERM-NDEA model: evidence from a domestic airline in Taiwan”, Transportation Planning and Technology, Vol. 35(7), pp. 697-714, 2012.
[44] Yu M. M., “Assessment of airport performance using the SBM-NDEA model”, Omega, Vol. 38, pp. 440-452, 2010.
[45] Wang W. K., Lu W. M. and Tsai C. J., “The relationship between airline performance and corporate governance amongst US listed companies”, Journal of Air Transport Management, Vol. 17(2), pp. 148-152, 2011.

指導教授

陳惠國(Huey-Kuo Chen)

審核日期

2013-7-23

推文