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Mergers and acquisitions in aviation – Management and economic perspectives on the size of airlines
Rico Merkert a,⇑, Peter S. Morrell b a b
Institute of Transport and Logistics Studies, The University of Sydney, NSW 2006 Sydney, Australia
Department of Air Transport, Cranfield University, Cranfield, MK43 0AL Bedfordshire, UK
a r t i c l e
i n f o
Article history:
Received 31 July 2011
Received in revised form 14 December 2011
Accepted 7 February 2012
Keywords:
Mergers and acquisitions
Finance
Productivity
Size of firms
Data envelopment analysis
a b s t r a c t
This paper reviews literature and management perspectives on airline mergers and acquisitions. We find that M&A/consolidation is seen as a ‘‘game-changer’’ and mandatory to survive in aviation markets. We, therefore, apply DEA models to 66 airlines to evaluate whether big is indeed always beautiful. Our results suggest that the optimal airline size is between 34 and 52 bn available seat kilometre capacity and that airlines with more than
200 bn ASK are definitely too large to operate efficiently. This also applies when revenues are included in the DEA models, which is central as yield management and ancillary revenues are increasingly important.
Ó 2012 Elsevier Ltd. All rights reserved.
1. Introduction
A key outcome of the deregulation of the US and European aviation markets is that it has become possible for airline companies to grow much faster than just generically by merging acquiring each other, often even across borders. In general, consolidation in the form of mergers and acquisitions (M&A) is often seen as a very effective way of surviving in the competitive environments of many aviation markets. For example, Willie Walsh, CEO of the recently formed International Airlines Group
(IAG = BA/Iberia), sees M&A as a
References: Assaf, A.G., 2010. Bootstrapped scale efficiency measures of UK airports. Journal of Air Transport Management 16, 42–44. Assaf, A.G., 2011. Portuguese tour operators: a fight for survival. Journal of Air Transport Management 17, 155–157. 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. Barros, C.P., Peypoch, N., 2009. An evaluation of European airlines’ operational performance. International Journal of Production Economics 122, 525–533. Charnes, A., Cooper, W.W., Rhodes, E.L., 1978. Measuring the efficiency of decision making units. European Journal of Operational Research 2, 429–444. Coelli, T.J., Rao, P.D.S., O’Donnell, C.J., Battese, G.E., 2005. An Introduction to Efficiency and Productivity Analysis, second ed. Springer, New York. Färe, R., Grosskopf, S., Lovell, C.A.K., 1985. The Measurement of Efficiency of Production. Kluwer Nijhoff Publishing, Boston. Fisher, A.A., Lande, R.H., 1983. Efficiency considerations in merger enforcement. California Law Review 71, 1580–1692. Helvoigt, T.L., Adams, D.M., 2008. Data envelopment analysis of technical efficiency and productivity growth in the US Pacific Northwest sawmill industry. Canadian Journal of Forest Research 38, 2553–2565. Hong, S., Zhang, A., 2010. An efficiency study of airlines and air cargo/passenger divisions: a DEA approach. World Review of Intermodal Transportation Research 3, 137–149. Iatrou, K., Oretti, M., 2007. Airline Choices for the Future – from Alliances to Mergers. Ashgate, Burlington. Maruna, M., Morrell, P.S., 2010. After the Honeymoon. Airline Business, August. Merkert, R., Hensher, D.A., 2011. The impact of strategic management and fleet planning on airline efficiency – a random effects Tobit model based on DEA efficiency scores Merkert, R., Smith, A.S.J., Nash, C.A., 2010. Benchmarking of train operating firms – a transaction cost efficiency analysis. Journal of Transportation Planning and Technology 33, 35–53. Morrell, P.S., 2007. Airline Finance, third ed. Ashgate, Aldershot. Morrell, P.S., 2010. The Planned British Airways/Iberia Merger: A Viewpoint. AirNeth Column, November (assessed 28.12.10). Schefczyk, M., 1993. Operational performance of airlines: an extension of traditional measurement paradigms. Strategic Management Journal 14, 301–317. Simar, L., Wilson, P.W., 1998. Sensitivity analysis of efficiency scores: how to bootstrap in nonparametric frontier models. Management Science 44, 49–61. Simar, L., Wilson, P.W., 2000. A general methodology for bootstrapping in non-parametric frontier models. Journal of Applied Statistics 27, 779–802. Simar, L., Wilson, P.W., 2002. Non-parametric tests of returns to scale. European Journal of Operational Research 139, 115–132. Simar, L., Wilson, P.W., 2007. Estimation and inference in two-stage, semi-parametric models of production processes. Journal of Econometrics 136, 31–64. Simar, L., Wilson, P.W., 2008. Statistical inference in nonparametric frontier models: recent developments and perspectives. In: Fried, H.O., Lovell, C.A.K., Schmidt, S.S Thanassoulis, E., Portela, M.C.S., Despic´, O., 2008. Data envelopment analysis: the mathematical programming approach to efficiency analysis. In: Fried, H.O., Lovell, C.A.K., Schmidt, S.S Tofallis, C., 1997. Input efficiency profiling: an application to airlines. Computers and Operations Research 24, 253–258. Vasigh, B., Tacker, T., Fleming, K., 2008. Introduction to Air Transport Economics: from Theory to Applications. Ashgate, Aldershot. Wilson, P.W., 2010. Package ‘FEAR’ – Frontier Efficiency Analysis with R. Clemson, Department of Economics, Clemson University. Zou, L., Oum, T.H., Chunyan Yu, C., 2011. Assessing the price effects of airline alliances on complementary routes. Transportation Research Part E: Logistics and Transportation Review 47, 315–332.