The technical efficiency of container ports: Comparing data envelopment analysis and stochastic frontier analysis |
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| Institution: | 1. School of Marine Science and Technology, Armstrong Building, University of Newcastle upon Tyne, Newcastle NE1 7RU, UK;2. Centre for International Shipping and Logistics, Plymouth Business School, University of Plymouth, Drake Circus, Plymouth PL4 8AA, UK;3. Centre of Urban Planning and Environmental Management, The University of Hong Kong, Pokfulam Road, Hong Kong;4. Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong;1. Faculty of Economics and Management of Sfax, University of Sfax, Tunisia;2. School of Engineering, University of Quebec at Trois-Rivieres, Canada;1. Division of Economics, Center for Research and Teaching of Economics (CIDE), Carretera Mexico Toluca 3655, Col. Lomas de Santa Fe, 01210 Mexico DF, Mexico;2. Infrastructure and Transport Research Group, Dept. Applied Economics, University Las Palmas de Gran Canaria (ULPGC), Campus de Tafira, Modulo D, Despacho 2.20, 35017 Las Palmas de Gran Canaria, Spain;1. Center for Studies in Logistics, Infrastructure and Management, COPPEAD Graduate Business School, Federal University of Rio de Janeiro, Brazil;2. Instituto Superior de Economia e Gestão, University of Lisbon, Rua Miguel Lupi, 20, 1249-078 Lisbon, Portugal;1. Tourism and Transport Research Unit, Institute of Tourism and Sustainable Economic Development, Las Palmas University, Campus Universitario de Tafira, Módulo D, Las Palmas de Gran Canaria 35017, Spain;2. Oviedo Efficiency Group, Department of Economics, University of Oviedo, Avenida del Cristo s/n, 33071, Spain;1. School of Chemistry, Physics and Mechanical Engineering, Science and Engineering Faculty, Queensland University of Technology, Brisbane, QLD 4001, Australia;2. Institute of Materials for Energy and Environment, School of Materials Science and Engineering, Qingdao University, Qingdao 266071, PR China;3. School of Chemical Engineering, The University of Queensland, St Lucia, QLD 4072, Australia |
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| Abstract: | The efficiency of the container port industry has been variously studied utilising either Data Envelopment Analysis (DEA) or Stochastic Frontier Analysis (SFA). Given the strengths and weaknesses associated with these two approaches, the efficiency estimates and scale properties derived from these analyses are not always convincing. This paper applies both approaches to the same set of container port data for the world’s largest container ports and compares the results obtained. A high degree of correlation is found between the efficiency estimates derived from all the models applied, suggesting that results are relatively robust to the DEA models applied or the distributional assumptions under SFA. High levels of technical efficiency are associated with scale, greater private-sector participation and with transhipment as opposed to gateway ports. In analysing the implications of the results for management and policy makers, a number of shortcomings of applying a cross-sectional approach to an industry characterised by significant, lumpy and risky investments are identified and the potential benefits of a dynamic analysis, based on panel data, are enumerated. |
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