Disentangling the European Airlines efficiency puzzle:A network data envelopment analysis approach

Meryem Duygun (), Diego Prior, Mohamed Shaban () and Emili Tortosa-Ausina
Additional contact information
Meryem Duygun: Department of Accounting and Finance, University of Hull, UK
Mohamed Shaban: School of Management, University of Leicester, UK

No 2015/04, Working Papers from Economics Department, Universitat Jaume I, Castellón (Spain)

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.

Keywords: airlines; network DEA (search for similar items in EconPapers)
JEL-codes: C61 D61 L93 (search for similar items in EconPapers)
Pages: 46 pages
Date: 2015
New Economics Papers: this item is included in nep-com, nep-eff and nep-tre
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Journal Article: Disentangling the European airlines efficiency puzzle: A network data envelopment analysis approach (2016)
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