本研究運用資料包絡分析法的 CCR、BCC 模式以及 Mann-Whitney U 檢定評估全球低成本航空的營運效率，以2016年至2019年上市的全球低成本航空公司為研究對象，機隊規模、營業成本、可售座位公里當作投入變數，客運收益公里數和營業收入當作產出變數，建立實證模型。第一階段運用 CCR 模式評估技術效率、第二階段運用 BCC 模式評估純技術效率、第三階段將技術效率拆分為純技術效率與規模效率進行評估、第四階段運用 Mann-Whitney U 檢定找尋效率差異化之原因。實證結果中 CCR 模式顯示16 間公司中相對有效率為各地區的龍頭公司，BCC 模式顯示四年純技術效率呈現下降趨勢，原因為亞洲地區中相對規模較大的低成本航空公司所致，規模效率顯示整體上市低成本航空公司以規模報酬不變、規模報酬遞增為主，且愈早開始發展、營運時間愈久之公司愈能達成規模報酬不變。Mann-Whitney U 檢定顯示非亞洲地區的低成本航空公司效率顯著優於亞洲地區，然而成立時間愈久、規模愈大的公司效率並未顯著優於成立時間愈短、規模愈小的公司。

This study studies Data Envelopment Analysis (DEA) with CCR and BCC models, as well as the Mann-Whitney U test, to evaluate the operational efficiency of global low-cost airlines listed between 2016 and 2019. The empirical results show that, based on the CCR model, the most efficient companies among the 16 studied are the leading airlines in each region. The BCC model reveals a declining trend in pure technical efficiency over the four years, primarily due to relatively larger low-cost airlines in the Asian region. Scale efficiency results indicate that listed low-cost airlines generally exhibit constant and increasing returns to scale, with older and longer-operating companies more likely to achieve constant returns to scale. The Mann-Whitney U test demonstrates that non-Asian low-cost airlines are significantly more efficient than their Asian counterparts. However, longer-established and larger companies do not show significantly higher efficiency compared to newer and smaller ones.

中文文獻
1.高頻歡 (2014) 。 應用資料包絡分析法評估全球低成本航空公司營運績效之研究，國立臺灣海洋大學航運管理學系碩士論文。

2.陳世宗 (2006) 。資料包絡分析法在企業績效分析之運用與實證探討，以中國電視事業公司為例，國立空中大學管理與資訊學系管理與資訊學報。

3.張有恆、林靖容(2014) 。 兩岸航空公司營運績效評估。航空安全及管
理季刊，1(1) ，28-44。

4.盛浩恩 (2018) 。 傳統航空及廉價航空績效之比較：以台日航線為例，國立彰化師範大學企業管理學系碩士論文。

5.莊凱燕 (2023) 。 結合資料包絡分析法與麥氏生產力指數進行航空公司疫情前後之經營績效評估，臺北市立大學都會產業經營與行銷學系碩士班碩士學位論文。

6.楊昆妮 (2014) 。 亞洲低價航空業之營運效率分析，中原大學國際商學碩士學位 學程碩士學位論文。

7.裴何寶兒 (2021) 。 亞洲航空公司的營運效率:資料包絡分析法之應用，國立陽明交通大學管理學院企業管理碩士學位學程碩士論文。

英文文獻
1.Banker, R.D., Charnes, A. and Cooper, W.W. (1984), “Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis, ”Management Science, Vol. 30, No. 9, 1078-1092.

2.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.

3.Cui, Q. and Yu, L. T. (2021), A Review of Data Envelopment Analysis in Airline Efficiency: State of the Art and Prospects, Journal of Advanced Transportation, Vol. 2021, 1-10.

4.Cooper, W. W., Seiford, L. M., and Tone, K. (2007), Handbook on Data Envelopment, Springer.

5.Chang, Y. C. and Yu, M. M. (2012), “Measuring production and consumption efficiencies using the slackbased measure network data envelopment analysis approach: the case of low-cost carriers,” Journal of Advanced Transportation, Vol. 48, 15-31.

6.Farrell, M. J. (1957), The measurement of productive efficiency, Journal of the Royal Statistical Society, 120(3), 253-290.

7.Jain, R. K., and Natarajan, R. (2015), A DEA study of airlines in India, Asia Pacific Management Review, 1-8.

8.Mann, H. B., and Whitney, D. R. (1947), On a test of whether one of two random variables is stochastically larger than the other. Annals of Mathematical Statistics, 18, 50-60.

9.Min, H. and Joo, S. J. (2016), A comparative performance analysis of airline strategic alliances using data envelopment analysis, Journal of Air Transport Management, 2016, vol. 52, issue C, 99-110.

10.Poon, T. S. C., and Waring, P. (2010), The lowest of low-cost carriers: The case of AirAsia. The International Journal of Human Resource Management, 21(2), 197–213.

11.Rozenberg, R., and Szabo, S. (2014), Comparison of FSC and LCC and Their Market Share in Aviation, International Review of Aerospace Engineering, Vol. 7, N. 5, 49-151.

12.Smyth, M. (2006), Airline cost performance, IATA Economic Briefing N5, IATA, 13.

13.Sakthidharan, V. and Sivaraman, S. (2018), Impact of operating cost components on airline efficiency in India: A DEA approach, Asia Pacific Management Review, 23(4), 1-10.