Analysing airport efficiency in East China using a three-stage data envelopment analysis
Abstract
This paper evaluates the Technical Efficiencies (TEs) of a group of airports in East China by applying a three-stage Data Envelopment Analysis (DEA) method. The merit of this method allows us to consider the impact of the environmental factors on measuring airport efficiencies. Three variables, i.e. per capita Gross Domestic Product (GDP), the proportion of the tertiary industry, and the number of tourists, are used to represent the environmental factors. The results show that the environmental factors have airport-specific impacts on the value of the efficiencies. Additionally, airport TE are dominated by both Pure Technical Efficiency (PTE) and Scale Efficiency (SE). Based on empirical results, airport specific strategies can be provided to enhance airport efficiency, such as taking the effects of environmental variables and the statistical noise into consideration when analysing the airport efficiency, improving airport efficiencies according to their own conditions and improving the PTE or SE according to their categorizations.
Keyword : air transport, airport, technical efficiency, scale efficiency, three-stage DEA, East China
How to Cite
Zeng, Z., Yang, W., Zhang, S., & Witlox, F. (2020). Analysing airport efficiency in East China using a three-stage data envelopment analysis. Transport, 35(3), 255-272. https://doi.org/10.3846/transport.2020.12869
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Jaržemskienė, I. 2012. Applying the method of measuring airport productivity in the Baltic region, Transport 27(2): 178–186. https://doi.org/10.3846/16484142.2012.694079
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Lozano, S. 2015. A joint-inputs network DEA approach to production and pollution-generating technologies, Expert Systems with Applications 42(21): 7960–7968. https://doi.org/10.1016/j.eswa.2015.06.023
Lozano, S.; Gutiérrez, E.; Moreno, P. 2013. Network DEA approach to airports performance assessment considering undesirable outputs, Applied Mathematical Modelling 37(4): 1665–1676. https://doi.org/10.1016/j.apm.2012.04.041
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Merkert, R.; Mangia, L. 2014. Efficiency of Italian and Norwegian airports: A matter of management or of the level of competition in remote regions?, Transportation Research Part A: Policy and Practice 62: 30–38. https://doi.org/10.1016/j.tra.2014.02.007
OAG. 2018. OAG Database. Official Aviation Guide of the Airways, OAG, Luton, UK. Available from Internet: https://www.oag.com
Örkcü, H. H.; Balıkçı, C.; Doğan, M. I.; Genç, A. 2016. An evaluation of the operational efficiency of Turkish airports using data envelopment analysis and the Malmquist productivity index: 2009–2014 case, Transport Policy 48: 92–104. https://doi.org/10.1016/j.tranpol.2016.02.008
Radonjić, A.; Pjevčević, D.; Hrle, Z.; Čolić, V. 2011. Application of DEA method to intermodal container transport, Transport 26(3): 233–239. https://doi.org/10.3846/16484142.2011.622127
Wanke, P. F. 2012. Capacity shortfall and efficiency determinants in Brazilian airports: Evidence from bootstrapped DEA estimates, Socio-Economic Planning Sciences 46(3): 216–229. https://doi.org/10.1016/j.seps.2012.01.003
Wanke, P. F. 2013. Physical infrastructure and shipment consolidation efficiency drivers in Brazilian ports: A two-stage network-DEA approach, Transport Policy 29: 145–153. https://doi.org/10.1016/j.tranpol.2013.05.004
Wanke, P.; Barros, C. P. 2017. Efficiency thresholds and cost structure in Senegal airports, Journal of Air Transport Management 58: 100–112. https://doi.org/10.1016/j.jairtraman.2016.10.005
Wanke, P.; Barros, C. P. 2014. Two-stage DEA: an application to major Brazilian banks, Expert Systems with Applications 41(5): 2337–2344. https://doi.org/10.1016/j.eswa.2013.09.031
Yoshida, Y.; Fujimoto, H. 2004. Japanese-airport benchmarking with the DEA and endogenous-weight TFP methods: testing the criticism of overinvestment in Japanese regional airports, Transportation Research Part E: Logistics and Transportation Review 40(6): 533–546. https://doi.org/10.1016/j.tre.2004.08.003
Banker, R. D.; Charnes, A.; Cooper, W. W. 1984. Some models for estimating technical and scale inefficiencies in data envelopment analysis, Management Science 30: 1078–1092. https://doi.org/10.1287/mnsc.30.9.1078
Barros, C. P.; Weber, W. L. 2009. Productivity growth and biased technological change in UK airports, Transportation Research Part E: Logistics and Transportation Review 45(4): 642–653. https://doi.org/10.1016/j.tre.2009.01.004
Button, K.; Kramberger, T.; Grobin, K.; Rosi, B. 2018. A note on the effects of the number of low-cost airlines on small tourist airports’ efficiencies, Journal of Air Transport Management 72: 92–97. https://doi.org/10.1016/j.jairtraman.2017.12.003
CAAC. 2017a. Issues the Statistics Bulletin of Civil Airports in China 2017. Available from Internet: http://www.caac.gov.cn/en
CAAC. 2017b. CAAC Specifies Five Main Tasks in the 13th Five-year Plan for Civil Aviation Development. Civil Aviation Administration of China (CAAC). Available from Internet: http://www.caac.gov.cn/en
CAAC. 2018. Statistical Bulletin of Civil Aviation Industry Development in 2017. Civil Aviation Administration of China (CAAC). Available from Internet: http://www.caac.gov.cn/en
CAAC. 2014. Statistical Bulletin of Civil Aviation Industry Development in 2013. Civil Aviation Administration of China (CAAC). Available from Internet: http://www.caac.gov.cn/en
Charles, V.; Zegarra, L. F. 2014. Measuring regional competitiveness through data envelopment analysis: a Peruvian case, Expert Systems with Applications 41(11): 5371–5381. https://doi.org/10.1016/j.eswa.2014.03.003
Charnes, A.; Cooper, W. W.; Rhodes, E. 1978. Measuring the efficiency of decision making units, European Journal of Operational Research 2(6): 429–444. https://doi.org/10.1016/0377-2217(78)90138-8
Chen, Y.-H.; Lai, P.-L.; Piboonrungroj, P. 2017. The relationship between airport performance and privatisation policy: a nonparametric metafrontier approach, Journal of Transport Geography 62: 229–235. https://doi.org/10.1016/j.jtrangeo.2017.06.005
Cui, Q.; Li, Y. 2014. The evaluation of transportation energy efficiency: an application of three-stage virtual frontier DEA, Transportation Research Part D: Transport and Environment 29: 1–11. https://doi.org/10.1016/j.trd.2014.03.007
Cui, Y.; Huang, G.; Yin, Z. 2015. Estimating regional coal resource efficiency in China using three-stage DEA and bootstrap DEA models, International Journal of Mining Science and Technology 25(5): 861–864. https://doi.org/10.1016/j.ijmst.2015.07.024
Curi, C.; Gitto, S.; Mancuso, P. 2011. New evidence on the efficiency of Italian airports: a bootstrapped DEA analysis, Socio-Economic Planning Sciences 45(2): 84–93. https://doi.org/10.1016/j.seps.2010.11.002
D’Alfonso, T.; Daraio, C.; Nastasi, A. 2015. Competition and efficiency in the Italian airport system: new insights from a conditional nonparametric frontier analysis, Transportation Research Part E: Logistics and Transportation Review 80: 20–38. https://doi.org/10.1016/j.tre.2015.05.003
Fernandes, E.; Pacheco, R. R. 2018. Managerial performance of airports in Brazil before and after concessions, Transportation Research Part A: Policy and Practice 118: 245–257. https://doi.org/10.1016/j.tra.2018.09.003
Ferreira, D. C.; Marques, R. C.; Pedro, M. I. 2016. Comparing efficiency of holding business model and individual management model of airports, Journal of Air Transport Management 57: 168–183. https://doi.org/10.1016/j.jairtraman.2016.07.020
Fragoudaki, A.; Giokas, D.; Glyptou, K. 2016. Efficiency and productivity changes in Greek airports during the crisis years 2010–2014, Journal of Air Transport Management 57: 306–315. https://doi.org/10.1016/j.jairtraman.2016.09.003
Fried, H. O.; Lovell, C. A. K.; Schmidt, S. S.; Yaisawarng, S. 2002. Accounting for environmental effects and statistical noise in data envelopment analysis, Journal of Productivity Analysis 17(1–2): 157–174. https://doi.org/10.1023/a:1013548723393
Fuentes, R.; Fuster, B.; Lillo-Bañuls, A. 2016. A three-stage DEA model to evaluate learning-teaching technical efficiency: key performance indicators and contextual variables, Expert Systems with Applications 48: 89–99. https://doi.org/10.1016/j.eswa.2015.11.022
Gillen, D.; Lall, A. 1997. Developing measures of airport productivity and performance: an application of data envelopment analysis, Transportation Research Part E: Logistics and Transportation Review 33(4): 261–273. https://doi.org/10.1016/S1366-5545(97)00028-8
Gitto, S.; Mancuso, P. 2012. Two faces of airport business: a non-parametric analysis of the Italian airport industry, Journal of Air Transport Management 20: 39–42. https://doi.org/10.1016/j.jairtraman.2011.11.003
Graham, A. 2005. Airport benchmarking: a review of the current situation, Benchmarking: an International Journal 12(2): 99–111. https://doi.org/10.1108/14635770510593059
Jaržemskienė, I. 2012. Applying the method of measuring airport productivity in the Baltic region, Transport 27(2): 178–186. https://doi.org/10.3846/16484142.2012.694079
Lai, P.-L.; Potter, A.; Beynon, M.; Beresford, A. 2015. Evaluating the efficiency performance of airports using an integrated AHP/DEA-AR technique, Transport Policy 42: 75–85. https://doi.org/10.1016/j.tranpol.2015.04.008
Li, K.; Lin, B. 2016. Impact of energy conservation policies on the green productivity in China’s manufacturing sector: evidence from a three-stage DEA model, Applied Energy 168: 351–363. https://doi.org/10.1016/j.apenergy.2016.01.104
Liu, D. 2017. Evaluating the multi-period efficiency of East Asia airport companies, Journal of Air Transport Management 59: 71–82. https://doi.org/10.1016/j.jairtraman.2016.11.009
Lozano, S. 2015. A joint-inputs network DEA approach to production and pollution-generating technologies, Expert Systems with Applications 42(21): 7960–7968. https://doi.org/10.1016/j.eswa.2015.06.023
Lozano, S.; Gutiérrez, E.; Moreno, P. 2013. Network DEA approach to airports performance assessment considering undesirable outputs, Applied Mathematical Modelling 37(4): 1665–1676. https://doi.org/10.1016/j.apm.2012.04.041
Luo, D. 2012. A note on estimating managerial inefficiency of three-stage DEA model, Statistical Research 29(4): 104–107. https://doi.org/10.3969/j.issn.1002-4565.2012.04.017 (in Chinese).
Merkert, R.; Mangia, L. 2014. Efficiency of Italian and Norwegian airports: A matter of management or of the level of competition in remote regions?, Transportation Research Part A: Policy and Practice 62: 30–38. https://doi.org/10.1016/j.tra.2014.02.007
OAG. 2018. OAG Database. Official Aviation Guide of the Airways, OAG, Luton, UK. Available from Internet: https://www.oag.com
Örkcü, H. H.; Balıkçı, C.; Doğan, M. I.; Genç, A. 2016. An evaluation of the operational efficiency of Turkish airports using data envelopment analysis and the Malmquist productivity index: 2009–2014 case, Transport Policy 48: 92–104. https://doi.org/10.1016/j.tranpol.2016.02.008
Radonjić, A.; Pjevčević, D.; Hrle, Z.; Čolić, V. 2011. Application of DEA method to intermodal container transport, Transport 26(3): 233–239. https://doi.org/10.3846/16484142.2011.622127
Wanke, P. F. 2012. Capacity shortfall and efficiency determinants in Brazilian airports: Evidence from bootstrapped DEA estimates, Socio-Economic Planning Sciences 46(3): 216–229. https://doi.org/10.1016/j.seps.2012.01.003
Wanke, P. F. 2013. Physical infrastructure and shipment consolidation efficiency drivers in Brazilian ports: A two-stage network-DEA approach, Transport Policy 29: 145–153. https://doi.org/10.1016/j.tranpol.2013.05.004
Wanke, P.; Barros, C. P. 2017. Efficiency thresholds and cost structure in Senegal airports, Journal of Air Transport Management 58: 100–112. https://doi.org/10.1016/j.jairtraman.2016.10.005
Wanke, P.; Barros, C. P. 2014. Two-stage DEA: an application to major Brazilian banks, Expert Systems with Applications 41(5): 2337–2344. https://doi.org/10.1016/j.eswa.2013.09.031
Yoshida, Y.; Fujimoto, H. 2004. Japanese-airport benchmarking with the DEA and endogenous-weight TFP methods: testing the criticism of overinvestment in Japanese regional airports, Transportation Research Part E: Logistics and Transportation Review 40(6): 533–546. https://doi.org/10.1016/j.tre.2004.08.003