Title: 歐洲地區航空公司生產力評估
Productivity Comparison of European Airlines: Bootstrapping Malmquist Indices
Authors: 王東寶
楊千
Wang, Tung-Pao
Yang, Chyan
經營管理研究所
Keywords: 效率;生產力;拔靴法;資料包絡分析法;麥氏生產力指數;航空公司;Efficiency;Productivity;Bootstrap;DEA;Malmquist Indices;Airlines
Issue Date: 2016
Abstract: 運輸是因應經濟活動需要而產生,運輸活動之成長與衰退會受國家或地區經濟景氣的影響,航空運輸也不例外。依據國際航空運輸協會(IATA)公布的Annual Review 2014,過去10年間,全球航空客運量、貨運量與GDP增減曲線相似,顯示全球航空客運量、貨運量與經濟成長息息相關。因此,全球GDP 成長率的發展與未來趨勢是瞭解全球航空市場與預測未來的最主要觀察重點。近年,隨著隨著歐債危機發生、美國景氣疲軟及中國大陸經濟成長下滑,2013及2014年全球主要經濟體多呈現疲弱現象。由於航空產業對於整體貿易的關係密切,而航空公司的經營效率也直接影響國家的競爭力。為了充分了解的歐洲地區航空公司經營效能及其生產力變動情形,本研究運用資料包絡分析法、麥氏生產力指數及拔靴法,以2001至2006年25家歐洲航空公司為研究對象,並將歐洲航空公司區分為中歐、西歐、南歐及北歐等4個區域進行效率分析。 本研究探討歐洲地區航空公司長期的營運效率變動情形,並提供資源配置改善建議,以增加競爭優勢。實證結果發現,歐洲地區規模較大的航空公司,較能具有經濟規模,進而創造更佳的競爭優勢,而規模較小的航空公司平均效率相對較差,航空公司的經營管理者應該參考市場趨勢及效率較佳的航空公司,改善組織內的資源配置情形;在研究期間的歐洲地區航空公司,其經營效率有逐年改善與進步;就區域而言,西歐地區的航空公司,其經營效率較其他地區為佳。此外,西歐地區的航空公司受到政府較多的支持,且在營運上採用了開放的策略,使得航空公司相對較具效率及競爭優勢;在運用資料包絡分析法的多入多產出績效評估研究中,拔靴法可以提供資料包絡分析法的效率值信賴區間,有效改善及縮減效率前緣,提供更明確的效率改善建議。
Transportation activities occur because of the needs of a country’s economic activities. The growth and decline of transportation activities are influenced by a country/region’s economic situation, and air transport is no exception. According to the Annual Review 2014 published by the International Air Transport Association (IATA), the global revenue passenger kilometers (RPK), revenue tonne kilometers (RTK), and gross domestic product (GDP) curves over the past 10 years displayed similar trends. Such a result shows that the global RPK and RTK are closely related to economic growth. Therefore, global GDP growth rate changes and its future trends are keys to understanding the global aviation market and predicting its future development. Along with the European debt crisis, weak American economy, and China’s stagnant economic growth over recent years, most major economies in the world showed poor economic performance in 2013 and 2014. The airline industry plays an influential role in trading at the national level. Therefore, airlines’ operational efficiency can directly affect a country’s competitiveness. This study explored the operating efficiency and variability of productivity estimates of European airlines. This paper applies the data envelopment analysis (DEA) method to measure the technical efficiency of 25 European airlines during 2001-2006. We applied Malmquist productivity indices (MPI) with a bootstrap method to assess the productivities of European airlines in four regions in Europe (Central Europe, Western Europe, Southern Europe, and Northern Europe). Our study explored the operating efficiency of the airline industry in Europe for obtaining insights, from a long-term perspective, into the resource allocation and competitive advantage in an intensely competitive environment. The findings can be summarized in five points. First, large airlines have the opportunity to exploit economies of scale for creating a competitive advantage. According to the market requirements of airlines for assisting airlines in improving their scale efficiencies and our study suggests that airline managers should focus on improving their management practices. Second, the overall performance of European airlines inclined toward the optimal practice over the study period, although considerable room for improvement existed. Third, Western European airlines were the most efficient in Europe, implying that these airlines were the most competitive. Furthermore, Western European airlines, receiving government support, adopted an expanding-only development policy for their airline operation. These European airlines were operating at the higher efficiency and were the most competitive. Fourth, small airlines endeavoured to overtake the leading group in raising efficiency but failed to integrate their resources to compete with large airlines. Although large airlines exhibited growth and competitiveness, small airlines pursued them. Finally, the bootstrap method is useful for measuring sample changes in any productivity studies; however, in a multiple-input and multiple-output study, MPI should be employed for computing the confidence interval.
URI: http://etd.lib.nctu.edu.tw/cdrfb3/record/nctu/#GT079937802
http://hdl.handle.net/11536/138422
Appears in Collections:Thesis