Disentangling the European airlines efficiency puzzle: A network data envelopment analysis approach |
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| Institution: | 1. University of Hull, United Kingdom;2. Universitat Autònoma de Barcelona, Spain;3. University of Sheffield, United Kingdom;4. Emili Tortosa-Ausina, Department d?Economia, Universitat Jaume I, Campus del Riu Sec, 12071 Castell de la Plana, Spain;1. Associate Professor in Banking and Finance,UQ Business School,The University of Queensland,Australia;2. National Graduate Institute for Policy Studies,Tokyo,Japan;1. Faculty of Commerce, Fukuoka University, Fukuoka 814-0180, Japan;2. Department of Economics and Finance, Southeast Missouri State University, Cape Girardeau, MO 63701, USA;3. University of Missouri, Columbia, MO, USA;1. Instituto Superior de Economia e Gestão, University of Lisbon, Rua Miguel Lupi, 20, 1249-078 Lisbon, Portugal;2. COPPEAD Graduate Business School, Federal University of Rio de Janeiro, Rua Paschoal Lemme, 355, 21949-900 Rio de Janeiro, Brazil;1. Graduate School of Logistics, Inha University, Incheon, Republic of Korea;2. Asia Pacific School of Logistics, Inha University, Incheon, Republic of Korea;1. COPPEAD Graduate Business School, Federal University of Rio de Janeiro, Rua Paschoal Lemme, 355, 21949-900 Rio de Janeiro, Brazil;2. ISEG – Lisbon School of Economics and Management, ULisboa and CEsA - Research Centre on African, Asian and Latin American Studies, Rua Miguel Lupi, 20, 1249-078, Lisboa, Portugal |
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| Abstract: | In recent years the European airline industry has undergone critical restructuring. It has evolved from a highly regulated market predominantly operated by national airlines to a dynamic, liberalized industry where airline firms compete freely on prices, routes, and frequencies. Although several studies have analyzed performance issues for European airlines using a variety of efficiency measurement methods, virtually none of them has considered two-stage alternatives – not only in this particular European context but in the airline industry in general. We extend the aims of previous contributions by considering a network Data Envelopment Analysis (network DEA) approach which comprises two sub-technologies that can share part of the inputs. Results show that, in general, most of the inefficiencies are generated in the first stage of the analysis. However, when considering different types of carriers several differences emerge – most of the low-cost carriers’ inefficiencies are confined to the first stage. Results also show a dynamic component, since performance differed across types of airlines during the decade 2000–2010. |
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| Keywords: | Airlines Network DEA |
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