The impact of strategic management and fleet planning on airline efficiency – A random effects Tobit model based on DEA efficiency scores

• Published in: Transportation research. Part A, Policy and practice Policy and practice, 2011-08, Vol.45 (7), p.686-695
• Main Authors: Merkert, Rico, Hensher, David A.
• Format: Article
• Language: English
• Subjects: Air transportation and traffic; Aircraft; Airlines; Applied sciences; Commercial aircraft; Commercial planes; Data Envelopment Analysis; Data Envelopment Analysis Airlines Efficiency Strategic management Fleet planning; Efficiency; Exact sciences and technology; Fleet planning; Fuels; Ground, air and sea transportation, marine construction; Marketing; Markets; Operations research; Passengers; Strategic management; Transportation planning, management and economics
• ISSN: 0965-8564; 1879-2375
• DOI: 10.1016/j.tra.2011.04.015

► Our results show that airlines with large aircraft and only a small number of aircraft families in their fleet have relatively high efficiency scores. ► Stage length and age of fleet are less relevant. ► Growth of airlines has a positive impact not only on technical efficiency but also on allocative and cost efficiency. ► However, from an airline size of 100bn ASK we find diseconomies of scale. ► Bootstrapping of first-stage airline efficiency scores improves second-stage random effects Tobit regression results only marginally. As a result of the liberalisation of airline markets; the strong growth of low cost carriers; the high volatility in fuel prices; and the recent global financial crisis, the cost pressure that airlines face is very substantial. In order to survive in these very competitive environments, information on what factors impact on costs and efficiency of airlines is crucial in guiding strategic change. To evaluate key determinants of 58 passenger airlines’ efficiency, this paper applies a two-stage Data Envelopment Analysis (DEA) approach, with partially bootstrapped random effects Tobit regressions in the second stage. Our results suggest that the effects of route optimisation, in the sense of average stage length of the fleet, are limited to airline technical efficiency. We show that airline size and key fleet mix characteristics, such as aircraft size and number of different aircraft families in the fleet, are more relevant to successful cost management of airlines since they have significant impacts on all three types of airline efficiency: technical, allocative and, ultimately, cost efficiency. Our results also show that despite the fuel saving benefits of younger aircraft, the age of an airline’s fleet has no significant impact on its technical efficiency, but does have a positive impact on its allocative and cost efficiency.