A STUDY OF THE CROSS-STRAIT DIRECT FLIGHT AIRPORTS’OPERATING EFFICIENCY BETWEEN TAIWAN AND MAINLAND CHINA

• Main Authors: Li-jane Tsai, 蔡麗娟
• Other Authors: Mei-fang Chen
• Format: Others
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/70806068922598605511

碩士 === 大同大學 === 事業經營學系(所) === 98 === This study selects 30 major airports of the same operation in cross-strait direct flights between Taiwan and China from 2007 to 2008 as the samples for evaluation of airport operational efficiency. We use the SPSS statistical analysis software and DEA-Solver software for data envelopment analysis, slack variable analysis and sensitivity analysis for the data collected. The study result is used as reference for managers in airport operations. The study applies CCR-Output model proposed by Charnes et al. (1978) on the analysis of relative efficiency for airport operations with cross-strait direct charter flights. Five input variables affecting the operation of airports include terminal area, length of runway, number of aprons, number of taxiways, and distance from airport to the nearest urban area; and the three output variables include the number of passengers, number of aircraft movements, and ponds of cargo. The study used summarized data and obtained the following four results: 1. Data Envelopment Analysis: Nine airports with optimal relative efficiency (CCR value=1) include Urumqi, Taoyuan International, Shenzhen, Shanghai, Pudong, Kunming, Guangzhou, Chongqing, Beijing and Chengdu. Airports with worst relative efficiency (CCR value<1) and require further improvement include Taitung, Taichung, Hualien, and Kaohsiung in Taiwan and Jinan, Shenyang, Hefei, Tianjin, and Fuzhou in mainland China. 2. Slack Variable Analysis: The long-term input variables in the overall airport is analyzed, with the best utilization being “numbers of taxiways” and the worst utilization being the “distance from airport to the nearest urban areas.” With regards to long-term output utilization of airports, the “number of aircraft movements” needs less increase, while “ponds of cargo” or “number of passengers” generally perform poorly and need to be increased in number. 3. Sensitivity Analysis: “number of aprons” has highly sensitive impact on airport efficiency, while “runway length” and "distance from airport to the nearest urban area” have the least impact on airport operation. Output factor such as the “number of aircraft movements” is highly influential on airport efficiency, while “ponds of cargo” has the least impact. 4. With regards to management, airports with CCR value less than 1 may refer to benchmark airports with CCR value greater than 1 for adjustment in input and output productivity, which thereby enhances airport efficiency. Kunming Airport is the benchmark airport which has been referred to15 times. The study results show that airports with good operational efficiency should be maintained and improved on their overall service standards. The ultimate goal of performance assessment such as in the study is to maximize output with minimal inputs, in order to reduce input waste of airport resources. The results could be used as reference for the department in charge of airport management, such as the Ministry of Transportation, Transportation Research Institute and the Civil Aeronautics Administration. Furthermore, it also provides insights to the future consideration of constructing new airports. In the future, cross-strait airports are expected to steadily move towards their objectives, enhance airport efficiency and improve competitiveness in global management.