中國機場標竿管理之研究

Benchmark Management in Chinese Airports

楊琇如(Hsiu-Ju Yang)

指導教授 ： 王維康

元智大學/管理學院/商學碩士班(會計學程)/碩士(2011年)

摘要

本文旨在探討中國機場的經營效率及標竿學習地圖之運用。除了從機場位置，機場所有權，機場服務型，都市區和經濟特區等特徵探討外，並且結合傳統資料包絡分析法、階層資料包絡分析法、吸引力測度及進步測度來擴展傳統資料包絡分析法，以評估在中國43個主要機場的績效。本研究主要評估目的乃幫助管理人員經營管理機場以為其客戶提供更好的航空運輸效率。本研究發現，中國的機場在不同位置、所有權及服務類型有顯著的營運績效差異，此外，尚構建標竿學習地圖以逐步改善無效率之機場，使其能達到最佳狀態。這項研究體現了如何設置標竿並實際執行，藉由標竿學習地圖來改善無效率之機場。最後，敏感性分析的結果表明，大多數機場，其營運效率來源主要為客運量。本研究強調應用資料包絡分析法以評估中國機場之績效。

關鍵字

資料包絡分析法 ； 機場 ； 背景依賴資料包絡分析法 ； 吸引力測度 ； 進步測度 ； 階層資料包絡分析法

並列摘要

This paper aims to examine the operating efficiency and benchmark-learning roadmap for the airports in China. In addition to exploring the performance differences from the angles of airport location, airport ownership, airport service type, metropolitan area and special economic zone, this study presents an extension of the data envelopment analysis (DEA) method by incorporating the traditional DEA method, the stratification DEA method, attractiveness measure, and progress measure to assess the performance of 43 major airports in China. The purpose of this assessment is to help managers of airports improve their operational management and the airports in providing better transport efficiency to their customers. This study has discovered that the qualities of operating efficiency of Chinese airports differ significantly because of airport region, airport ownership, and airport service type, except for metropolitan area and special economic zone. Furthermore, a benchmark-learning roadmap is constructed for inefficient airports so as to gradually ameliorate their performance to an optimal state. This study exemplifies how to set benchmarking goals and implementation to improve an inefficient airport by using the benchmark-learning roadmap. Finally, the results of sensitivity analysis show that most airports mainly rely on the number of passengers for their efficiency. The potential applications and strengths of the DEA method in assessing the Chinese airports are highlighted.

並列關鍵字

Attractiveness measure ； Progress measure ； Stratification DEA ； Data envelopment analysis (DEA) ； Airports ； Context-dependent DEA

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