隨著航空產業的蓬勃發展，航空業者競爭日漸劇烈。有鑑於此，深入評估全球航空公司的效率，對於航空產業的管理者及投資者皆相當重要。至今，鮮少學者針對全球航空公司進行兩階段的績效分析，因此，本研究選定探討全球航空公司的經營績效進行兩階段評估，以便更加深入了解航空公司營運流程上績效的來源。
本研究資料來源以國際航空運輸組織 ( international air transport association) 歷年統計報表內之全球航空公司為受評估的決策單位，並將航空公司營運流程分成服務生產與價值創造兩個階段來探討航空公司的績效。第一階段評估整體服務生產營運效率；第二階段評估全球航空公司的價值創造效率，並運用社會網路分析的α中心性排序，進一步篩選出標竿的航空公司。本研究將分析對象區分為航空公司加入聯盟與未加入聯盟進行比較，探討兩者績效是否存有差異；最後，更進一步探討航空公司優劣勢與其營運策略。
實證結果發現: (1) 標竿航空公司中，新加坡航空公司於服務生產階段效率與同儕比較相當傑出；荷蘭皇家航空於價值創造階段效率相對突出；(2) 航空聯盟中，星空聯盟與寰宇一家聯盟於服務生產效益佔比相當傑出；天合聯盟於價值創造效益佔比最佳；(3) 加入聯盟航空公司之效率於服務生產和價值創造階段皆優於未加入聯盟的航空公司；(4)透過階層式分群與策略雷達圖分析，第一群組航空公司包括國泰航空等，服務生產階段資源運用上顯著的效益；第二群組航空公司包括荷蘭皇家航空等，營運策略分別著重在銷售載客服務與載運貨物服務；第三群組航空公司包括廈門航空等，主要航線與航點著重於境內市場而非境外並透過代碼共享航班，使其提高營業收入為主要目的。

As the aviation industry continues to flourish nowadays, the competitions among global airline companies are getting fierce. It is therefore important to understand the performance of efficiency and productivity of the airline companies for managers as well as for investors. Until now, there are very few literature tried to evaluate the performance of airline companies via two-stage data envelopment analysis (DEA). As a result, this research intends to use this method to assess the performance of airline corporations.
The Decision Making Units (DMUs) in this research are chosen from the statistic annual report of International Air Transport Association (IATA). In addition, this study investigates the performance of global airline companies from the two-stage of service production and value creation in terms of input, operation and output. The first stage evaluates the performance of service production. The second stage assesses the performance of value creation. Thus, this paper also intends to analyze the efficiency of global airline companies with benchmark and alpha centrality from the concept of social network analysis. In the end, this study categorizes DMUs into four alliances to evaluate the performance of airline companies.
The result of this research shows that (1) Singapore Airline has better benchmark than others in service production process. KLM has better benchmark than others in value creation process. (2) Star Alliance and One World Alliance have better performance at service production process. Sky Team Alliance has better performance at value creation process. (3) Airline companies joining in alliance have better performance than non-alliance ones. In the future, performance evaluation results can be served as foundations for investment strategies definition. (4) According to hierarchical clustering and strategies radar analysis, the first group like Cathay Pacific Airways has better performance at service production process. The second group like KLM Royal Dutch Airlines focus on Revenue Passenger-Kilometer and Freight Tonne-Kilometres respectively. And the third group like Xiamen Airlines’ routes and waypoints focus on domestic market, they share code of flights to increase the revenue.

一、 英文文獻

1. Alam, Ila M Semenick, Sickles, Robin C. (1998). The relationship between stock market returns and technical efficiency innovations: evidence from the US airline industry. Journal of Productivity Analysis, 9(1), 35-51.
2. Banker, Rajiv D, Charnes, Abraham and Cooper, William Wager. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management science, 30(9), 1078-1092.
3. Barbot, Cristina, Costa, Alvaro and Sochirca, Elena. (2008). Airlines performance in the new market context: a comparative productivity and efficiency analysis. Journal of Air Transport Management, 14(5), 270-274.
4. Bonacich, Phillip and Lloyd, Paulette. (2001). Eigenvector-like measures of centrality for asymmetric relations. Social Networks, 23(3), 191-201.
5. Charnes, Abraham, Cooper, William W and Rhodes, Edwardo. (1978). Measuring the efficiency of decision making units. European journal of operational research, 2(6), 429-444.
6. Charnes, Abraham, Gallegos, Armando and Li, Hongyu. (1996). Robustly efficient parametric frontiers via multiplicative DEA for domestic and international operations of the Latin American airline industry. European Journal of Operational Research, 88(3), 525-536.
7. Chen, Yao, Cook, Wade D, Li, Ning and Zhu, Joe. (2009). Additive efficiency decomposition in two-stage DEA. European Journal of Operational Research, 196(3), 1170-1176.
8. Cheng, Kuangnen. (2010). Evaluation of US legacy airline distribution strategies. Journal of Air Transport Management, 16(6), 337-339.
9. Cooper, William W, Li, Shanling, Seiford, Lawrence M, Tone, Kaoru, Thrall, Robert M and Zhu, Joe. (2001). Sensitivity and stability analysis in DEA: some recent developments. Journal of Productivity Analysis, 15(3), 217-246.
10. Fare, Rolf and Grosskopf, Shawna. (2000). Network dea. Socio-economic planning sciences, 34(1), 35-49.
11. Farrell, Michael J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society. Series A (General), 253-290.
12. Fielding, Gordon J, Babitsky, Timlynn T, Brenner and E, Mary. (1985). Performance evaluation for bus transit. Transportation Research Part A: General, 19(1), 73-82.
13. Fielding, Gordon J, Babitsky, Timlynn T and Brenner, Mary E. (1985). Performance evaluation for bus transit. Transportation Research Part A: General, 19(1), 73-82.
14. Ho, Mei Hsiu-Ching, Liu, John S, Lu, Wen-Min and Huang, Chien-Cheng. (2013). A new perspective to explore the technology transfer efficiencies in US universities. The Journal of Technology Transfer, 1-29.
15. Liu, John S, Lu, Louis YY, Lu, Wen-Min and Lin, Bruce JY. (2013a). Data envelopment analysis 1978–2010: A citation-based literature survey. Omega, 41(1), 3-15.
16. Liu, John S, Lu, Louis YY, Lu, Wen-Min and Lin, Bruce JY. (2013b). A survey of DEA applications. Omega, 41(5), 893-902.
17. Liu, John S and Lu, Wen-Min. (2010). DEA and ranking with the network-based approach: a case of R&D performance. Omega, 38(6), 453-464.
18. Liu, John S and Lu, Wen-Min. (2012). Network-based method for ranking of efficient units in two-stage DEA models. Journal of the Operational Research Society, 63(8), 1153-1164.
19. Liu, John S, Lu, Wen-Min, Yang, C and Chuang, M. (2009). A network-based approach for increasing discrimination in data envelopment analysis. Journal of the Operational Research Society, 60(11), 1502-1510.
20. Lu, Wen-Min, Wang, Wei-Kang, Hung, Shiu-Wan and Lu, En-Tzu. (2012). The effects of corporate governance on airline performance: Production and marketing efficiency perspectives. Transportation Research Part E: Logistics and Transportation Review, 48(2), 529-544.
21. Ray, Subhash C and Hu, Xiaowen. (1997). On the technically efficient organization of an industry: a study of US airlines. Journal of Productivity Analysis, 8(1), 5-18.
22. Schefczyk and Michael. (1993). Operational performance of airlines: an extension of traditional measurement paradigms. Strategic Management Journal, 14(4), 301-317.
23. Seiford, Lawrence M and Zhu, Joe. (1999). Profitability and marketability of the top 55 US commercial banks. management science, 45(9), 1270-1288.
24. Sengupta, Jati K. (1999). A dynamic efficiency model using data envelopment analysis. International Journal of Production Economics, 62(3), 209-218.
25. Tofallis, Chris. (1997). Input efficiency profiling: an application to airlines. Computers & operations research, 24(3), 253-258.

二、 中文文獻

1. 王昱鈞. (2003). 國內航空公司相對效率與生產力之研究. (碩士), 東海大學
2. 王振伊. (2012). 行動銀行服務對銀行經營效率之影響—網路資料包絡分析與Tobit迴歸之應用. (碩士), 國立臺灣科技大學
3. 林延儒. (1993). 臺灣地區航空公司生產效率之評估---DEA彈性函數方法之應用. (碩士), 國立清華大學
4. 林進榮. (2002). 國內航空公司經營效率之研究. (碩士), 國立台灣科技大學
5. 張有恆. (2003). 航空業經營與管理.
6. 莊哲維. (2011). 結合DEA與多目標規劃評估航空公司績效. (碩士), 開南大學
7. 郭恒志. (2004). 應用二階段資料包絡分析法評估國內航空公司營運效率之研究. (碩士), 崑山科技大學
8. 陳武宏. (2002). 世界主要國際航空公司營運績效之研究. (碩士), 國防管理學院
9. 陳俊男. (1999). 國籍航空公司營運績效之研究. (碩士), 國立交通大學
10. 陳慧紋. (2004). 國內航空公司財務與經營績效評估之研究. (碩士), 國立高雄第一科技大學
11. 彭志文. (2002). 航空公司營運績效之標竿分析. (碩士), 國立交通大學
12. 黃建誠. (2011). 大學院校技術移轉績效評估－以兩階段資料包絡分析結果排序. (碩士), 國立臺灣科技大學
13. 黃敏婷. (2010). 大學院校經營績效之評估－以資料包絡分析結果排序. (碩士), 國立臺灣科技大學
14. 楊絜如. (2005). 國內航空公司營運績效評估之研究. (碩士), 國立東華大學
15. 葉清江. (1994). 國內線航空公司營運效率之研究. (碩士), 國立交通大學
16. 廖逸君. (1993). 以 DEA 方法評估亞太地區航空公司的經營效率, 台灣大學商學研究所碩士論文.
17. 鄭章瑞. (2003). 亞太十五家國際航空公司績效之研究--以資料包絡分析法（DEA）分析. (碩士), 東吳大學
18. 羅印呈. (2008). 國籍航空公司經營績效分析－以資料包絡分析方法分析. (碩士), 國立中央大學