세계 주요 공항 운영 효율성 분석: DEA와 Malmquist 생산성 지수 분석을 중심으로
An analysis of the operational efficiency of the major airports worldwide using DEA and Malmquist productivity indices
0
조회
0
다운로드
11
인용
0
참고문헌
키워드
초록
Purpose - We live in a world of constant change and competition. Many airports have specific competitiveness goals and strategies for achieving and maintaining them. The global economic recession, financial crises, and rising oil prices have resulted in an increasingly important role for facility investment and renewal and the implementation of appropriate policies in ensuring the competitive advantage for airports. It is thus important to analyze the factors that enhance efficiency and productivity for an airport. This study aims to determine the efficiency levels of 20 major airports in East Asia, Europe, and North America. Further, this study also suggests suitable policies and strategies for their development. Research design, data, and methodology - This paper employs the DEA-CCR, DEA-BCC, and DEA-Malmquist production index analysis models to determine airport efficiency. The study uses data on the efficiency and productivity of the world’s leading airports between 2006 and 2010. The input variables include the airport size, the number of runways, the size of passenger terminals, and the size of cargo terminals. The output variables include the annual number of passengers and the annual cargo volume. The study uses basic data from the 2010 World Airport Traffic Report (ACI). The world’s top 20 airports (as rated by the ACI report) are investigated. The study uses the expanded DEA Model and the Super Efficiency Model to identify the most effective airports among the top 20. The Malmquist productivity index analysis is used to measure airport effectiveness. Results - This study analyzes longitudinal and cross-sectional data on the world’s top 20 airports covering 2006 to 2010. A CCR analysis shows that the most efficient airports in 2010 were Gatwick Airport (LGW), Zurich Airport (ZRH), Vienna Airport (VIE), Leonardo da Vinci Fiumicino Airport (FCO), Los Angeles International Airport (LAX), Seattle-Tacoma Airport (SEA), San Francisco Airport (SFO), HongKong Airport (HKG), Beijing Capital International Airport (PEK), and Shanghai Pudong Airport (PVG). We find that changes in airport productivity are affected more by technical factors than by airport efficiency. Conclusions - Based on the study results, we offer four airport development proposals. First, a benchmark airport needs to be identified. Second, inefficiency must be reduced and high-cost factors need to be managed. Third, airport operations should be enhanced through technical innovation. Finally, scientific demand forecasting and facility preparation must become the focus of attention. This paper has some limitations. Because the Malmquist productivity index is based on the hypothesis of the, the identified production change could be over- or under-estimated. Further, as DEA estimates the relative efficiency. It also cannot generalize to include all airport conditions because the variables are limited. To measure airport productivity more accurately, other input variables and environmental variables such as financial and policy factors should be included.
Abstract
Purpose - We live in a world of constant change and competition. Many airports have specific competitiveness goals and strategies for achieving and maintaining them. The global economic recession, financial crises, and rising oil prices have resulted in an increasingly important role for facility investment and renewal and the implementation of appropriate policies in ensuring the competitive advantage for airports. It is thus important to analyze the factors that enhance efficiency and productivity for an airport. This study aims to determine the efficiency levels of 20 major airports in East Asia, Europe, and North America. Further, this study also suggests suitable policies and strategies for their development. Research design, data, and methodology - This paper employs the DEA-CCR, DEA-BCC, and DEA-Malmquist production index analysis models to determine airport efficiency. The study uses data on the efficiency and productivity of the world’s leading airports between 2006 and 2010. The input variables include the airport size, the number of runways, the size of passenger terminals, and the size of cargo terminals. The output variables include the annual number of passengers and the annual cargo volume. The study uses basic data from the 2010 World Airport Traffic Report (ACI). The world’s top 20 airports (as rated by the ACI report) are investigated. The study uses the expanded DEA Model and the Super Efficiency Model to identify the most effective airports among the top 20. The Malmquist productivity index analysis is used to measure airport effectiveness. Results - This study analyzes longitudinal and cross-sectional data on the world’s top 20 airports covering 2006 to 2010. A CCR analysis shows that the most efficient airports in 2010 were Gatwick Airport (LGW), Zurich Airport (ZRH), Vienna Airport (VIE), Leonardo da Vinci Fiumicino Airport (FCO), Los Angeles International Airport (LAX), Seattle-Tacoma Airport (SEA), San Francisco Airport (SFO), HongKong Airport (HKG), Beijing Capital International Airport (PEK), and Shanghai Pudong Airport (PVG). We find that changes in airport productivity are affected more by technical factors than by airport efficiency. Conclusions - Based on the study results, we offer four airport development proposals. First, a benchmark airport needs to be identified. Second, inefficiency must be reduced and high-cost factors need to be managed. Third, airport operations should be enhanced through technical innovation. Finally, scientific demand forecasting and facility preparation must become the focus of attention. This paper has some limitations. Because the Malmquist productivity index is based on the hypothesis of the, the identified production change could be over- or under-estimated. Further, as DEA estimates the relative efficiency. It also cannot generalize to include all airport conditions because the variables are limited. To measure airport productivity more accurately, other input variables and environmental variables such as financial and policy factors should be included.
참고문헌 (46)
- Andersen, P., "A Procedure for Ranking Efficient Units in Data Envelopment Analysis", Management Science, 39(10), pp.1261~1264 (1993)
- Babot, A. C., "Airlines performance in the new market context : a comparative productivity and efficiency analysis", Journal of Air Transport Management, 14, pp.270~274 (2008)
- Banker, R. D., "Models for the Estimation of Technical and Scale Efficiencies in Data Envelopment Analysis", Management Science, 30, pp.1078~1092 (1984)
- Berger, A. N., "Measurement and Efficiency Issues in Commercial Banking, In Output Measurement in the Service Sectors" (1992), University of Chicago Press
- Caves, D. W., "An assessment of the efficiency effects of U.S. airline deregulation via an international comparison, In Bailey Public Regulation, New Perspective on Institutions and Policies", pp.285~320 (1987), MIT Press
- Charnes, A., "Measuring Efficiency of Decision Making Unit", European Journal of Operations Research, 2, pp.429~444 (1978)
- Choi, Deokjae, "To enhance the competitiveness of domestic banks bigger push direction: malmquist index using the empirical analysis of the effect the merger centered", 석사, pp.2006
- Cooper W. W., "Data Envelopment Analysis A Comprehensive Text with Models, Applications, References and DEA-Solver Software" (2000), Kluwer Academic Publishers
- Enrilich, I., "Productivity growth and firm ownership : An analytical and empirical investigation", Journal of Political Economy, 102(5), pp.1021~1031 (1994)
- 엄경아, "아태지역 항공사의 운영 성과평가 및 제고방안에 관한 연구", 한국항공경영학회지, 9(2), pp.23~49 (2011), 한국항공경영학회
- Farrell, M. J., "The Measurement of Productive Efficiency", Journal of the Royal Statistical Society, Series A, 120(3), pp.252~267 (1957)
- Good, D. H., "Efficiency and Productivity Growth Comparisons of European and U. S. Airlines : a First Look at the Data", The Journal of Productivity Analysis, 4, pp.115~125 (1995)
- Hong, Seok-Jin, "Research on the effectiveness of the air cargo sector, and airlines-DEA Model", Transportation Research, 22(3), pp.102~111 (2004)
- Im, Seng-Muk, "How to select elements in the input, output DEA", Industrial Engineering, 22(1), pp.44~55 (2009)
- Im, Ho-Sun, "Airlines point of research for the assessment of service productivity", Korean Society of production right, 14(2), pp.72~81 (2003)
- Study on strategic alliances in the airline industry, "Jeong, Tae-Rim", ~ (2001)
- 강호정, "국내 공항의 상대적 효율성 및 생산성 변화 연구", 한국항공경영학회지, 7(1), pp.119~128 (2009), 한국항공경영학회
- Ku, Bon-Bae, "Study on the airline strategic alliance outcomes and success factors. Institute of Tourism Management", Tourism Management Studies, 2, pp.21~43 (2003)
- Kim, Gi-Hong, "An Exploratory Study of Korean aviation industry and airline strategic alliances", Tourism Services Research, 3(1), pp.19~36 (2002)
- Kim, Do-Hyun, "Study on the relative efficiency of the domestic airport control tower", Korean Air luck paragraph Journal, 11(2), pp.59~77 (2003)
- Kim, Yang-Suk, "Airlines operating efficiency assessment using DEA model", Korean Air Management Society Proceedings, 3, pp.41~49 (2008)
- Kim, Jecheol, "Technical efficiency and determinants of the major airlines in Northeast Asia", Industrial research organization, 12(4), pp.1~32 (2004)
- Kim, Sung-Ho, "Using simulation Monte kageul, parametric nonparametric comparison of the efficiency of a particular method", pp.1998
- 권영훈, "DEA모형을 이용한 대학운영효율성 분석 연구; 수도권 소재대학과 지방소재대학의 비교분석을 중심으로", 서비스경영학회지, 11(1), pp.179~208 (2010), 한국서비스경영학회
- Kwon, Young-Hun, "Take advantage of low-cost airlines and airlines in the DEA efficiency comparative analysis", Korea Business Review, 4(2), pp.59~79 (2011)
- The Effect of Mergers on Prices, Costs, and Capacity Utilization in the U.S. Air Transportation Industry, 1970-1984, "Lichtenberg, F. R.", The Jerome Levy Economics Institute Bard College, ~, pp.Working Paper No. 32 (1989)
- 이기상, "동북아 항공운송 환경변화와 우리나라 항공운송산업의 발전방향", 한국항공경영학회지, 5(1), pp.3~28 (2007), 한국항공경영학회
- Lee, Jaegyeong, "DEA model utilizing evaluation research on the effectiveness of Internet companies", 박사, pp.2006
- Lee, Jeongdong, "Efficiency Analysis Theory and Application" (2007), Seoul Economic Management Press
- Lee, Yeong-Soo, "TFP estimates and determinants of domestic air transport industry", Transportation Policy Studies, 12(1), pp.23~44 (2005)
- 이재구, "아시아 주요공항의 효율성 분석 －DEA와 초효ds율성 분석을 중심으로－", 한국항공경영학회지, 7(3), pp.3~12 (2009), 한국항공경영학회
- Lee, Hwan-Ho, "Daeung measures of changes in the environment and the world's air transport industry in Korea", Air and Industrial Research, 60, pp.102~120 (2002)
- Lee, Heung-Gyu, "Study on the efficiency of the airline reservation stub", Cultural tourism Korea Culture and Tourism Institute of Research, 7(3), pp.121~132 (2005)
- South Korea's major national industrial complexes operating efficiency analysis using DEA and Malmquist productivity index, "Lee, Yun", Korean Society of Regional Development, ~ (2011)
- 이형룡, "리조트직원의 경력몰입 결정요인과 이직의도에 관한 연구", 관광레저연구, 21(4), pp.173~195 (2009), (사)한국관광레저학회
- Oum, T. H., "Cost Competitiveness of Major Airlines : an International Comparison", Transport Research Part A : Policy and Practice, 32(6), pp.407~422 (1998)
- Operational efficiency of domestic travel agencies using the DEA model, "Park, Gwang-Sik", Korea Aerospace University, Institute of Management, Industrial and Management, 23~34 (2007)
- Park, Man-Hui, "Efficiency and productivity analysis", Korea Research, 14 (2008)
- Park, Jing-Yeong, "Korea and Japan, the rail industry's cost structure and productivity analysis: In connection with the restructuring plans and privatization measures in the railway industry", 박사, pp.2007
- Park, Chu-Hwan, "Mitch Impact Analysis Korea, the aviation industry to the local economy", A Study of Land, 68, pp.231~251 (2011)
- 박추환, "산업연관분석을 통한 우리나라 항공물류산업의 경제적 파급효과", 산업경제연구, 24(3), pp.1885~1908 (2011), 한국산업경제학회
- Park, Hye-Young, "Comparative analysis of airline strategic jehyo using DEA efficiency", Korean Air Management Association, 9(3), pp.72~82 (2011)
- Scheraga, C. A., "Operational Efficiency versus Financial Mobility in the Global Airline Industry: a Data Envelopment and Tobit Analysis", Transport Research Part A, 38, pp.383~404 (2004)
- AMOS Statistical analysis methods, "SPSS", pp.2008, Song Ji-Jun
- Windle, R. J., "The World's Airlines : A Cost and Productivity Comparison", Journal of Transport Economics and Policy, 25(1), pp.31~49 (1991)
- Yeo, Gyu-Heon, "For strategic alliances in the airline industry and productivity", Journal of the Korea Flight Schedule, 15(4), pp.131~141 (2007)