Airline Efficiency: Volume 5

This chapter provides a survey of alternative methodologies for measuring and comparing productivity and efficiency of airlines, and reviews representative empirical studies. The survey shows the apparent shift from index procedures and traditional OLS estimation of production and cost functions to stochastic frontier methods and Data Envelopment Analysis (DEA) methods over the past three decades. Most of the airline productivity and efficiency studies over the last decade adopt some variant of DEA methods. Researchers in the 1980s and 1990s were mostly interested in the effects of deregulation and liberalization on airline productivity and efficiency as well as the effects of ownership and governance structure. Since the 2000s, however, studies tend to focus on how business models and management strategies affect the performance of airlines. Environmental efficiency now becomes an important area of airline productivity and efficiency studies, focusing on CO₂ emission as a negative or undesirable output. Despite the fact that quality of service is an important aspect of airline business, limited attempts have been made to incorporate quality of service in productivity and efficiency analysis.

Existing studies about airline productivity and cost competitiveness are focusing on combination carriers, transporting both passengers and cargo in the same aircraft and with the same inputs. Scientific research about the cost structure and productive performance of all-cargo carriers is very limited. However, the importance of air cargo and express transport in our globalized economy, the high volatility of all-cargo carriers (especially since the 2008 economic crisis), and the success of integrators show the need for more scientific attention to this industry. This chapter aims at benchmarking the productivity and cost competitiveness of US integrated and non-integrated cargo carriers, based on total factor productivity and unit cost competitiveness analyses. The results unveil a positive correlation between productivity on the one hand and the size of the carrier and its average stage length on the other hand, indicating economies of scale. Correcting the results for such factors beyond managerial control and input prices allows us to measure the impact of the crisis and the consequences for the management of the individual carriers.

This chapter analyses the efficiency of African airlines using a two-stage network DEA (Data Envelopment Analysis) model. Network DEA models usually take into account the production process with intermediate inputs derived from the first stage and a second stage that departs from it. This fundamental feature enables one to view the airline production process as a carry-over activity. The analysis covers the 2010–2013 period. The relative efficiency ranks are presented and policy implications are derived.

This paper aims to develop and test a new way of modeling airline operations and apply it to measure and compare the efficiency of international airlines, with a special focus on deregulation effects. The paper elaborates on the choice of variables, following the early work of Schefczyk (1993) and Scheraga (2004). The value chain of the airlines determines the variables included in three different models. Using data envelopment analysis, the efficiency scores show that North American airlines are more efficient in producing services offered to customers. Few differences are found between regions in allocating service output to match demand. One plausible explanation for this difference is that airlines operate within competitive environments. In a highly competitive market, management decisions focus on productive actions and cost reduction. In a less competitive environment, there is a higher degree of adjustments of the services produced. Using the Malmquist productivity index, measurements reveal that there is a catch-up effect for the European and Asian/South American airlines service production during the studied time period, which was from 1990 to 2003.

This chapter reviews the key results obtained in previous studies of airline mergers. It is found that the effect of mergers on airfares is dependent on the network configurations of merging airlines. Fare increases are frequently observed on overlapped routes. However, if the networks of two merging airlines are complementary, the expanded network after the merger leads to cost savings, increase in travel options, and improvement in service quality. Therefore, in a deregulated market, with few entry barriers, relaxing merger regulations is likely to improve welfare. However, most welfare evaluations do not incorporate quality changes or dynamic competition effects. Empirical investigations are primarily ex post analysis of mergers that have already passed antitrust reviews. The relationship between market concentration and welfare might be nonlinear and market specific. Therefore, airline mergers and alliances should be reviewed case by case. Methodological improvements are needed in future studies to control for the effects of complicating factors inherent in ex post evaluations.

This chapter examines the impact of recent airline consolidations in the United States on the technical efficiencies of the airlines involved. Data envelopment analysis (DEA) is used to assess the efficiencies, and the consolidations examined are those that occurred among major network carriers between 2005 and 2013. The airline production process is conceptualized as the transformation of labor, fuel, and fleet-wide seating capacity into available seat-miles, or, under an alternative model specification, into user value, as measured by the airline’s operating revenue. Efficiency is conceptualized in terms of minimizing the airline’s usage of the three inputs, given its output level. The analysis seeks to determine whether the airlines that consolidated were more efficient, post-consolidation, than they were prior to consolidation, compared to airlines that did not enter into consolidations. Although there are limitations owing to the small number of airlines in the dataset, the chapter finds no evidence that the consolidations enhanced the efficiencies of the airlines involved, relative to the efficiencies of the airlines that did not enter into consolidations.

This chapter examines the airline performance effect arising from collaboration between airlines and high speed railway (HSR). The analysis presents scenario simulations using a bi-level model, which takes into account the effect of competition among airlines and HSR. Using real data, we examine the Japanese domestic market and the Japan-based international market: the markets consist of Tokyo Metropolitan Area, Osaka Metropolitan Area, Seoul/Korea, Frankfurt/Germany, Paris/France, London/United Kingdom, and Los Angeles/United States. Analysis of the domestic market assumes airlines and HSR compete against each other, and analysis of the international market assumes airlines only compete with each other. Initially, we conduct performance analysis using a simulation that mimics the current relationship between airlines and HSR. Then we present three scenarios for different combinations of collaboration between airline and HSR based on airline alliances. The results from this exercise are then used to examine the impact of the collaboration on the profits of airlines and HSR, passenger’s utility, and the network design of airlines. Last, we show the potential benefit to airlines – profitability, market share, and demand growth – from the airline-HSR collaboration. Our model shows that in Japan: (1) Airlines can improve their profitability in international operations by the collaboration with HSR when airlines set their hubs so they can connect to HSR; (2) The airline which has a lower unit operating cost than rivals and sets its hubs to connect to HSR can improve its joint profit with HSR through collaboration; (3) Airlines that don’t operate domestic flights and don’t set their hubs to connect to HSR encourage increased fare competition by coordinating with HSR, but their profit decreases. Whether these results are generalizable to other regions should be the subject of future study.

Based on our experience related to the passenger terminal re-design at Sydney airport and its impact on belly-hold freight chains at the airport, this chapter takes a more general view on managing freight chains at large international airports. We aim to review literature and documents related to this area and also to undertake a fleet/traffic analysis of the 100 largest multi-function airports (when measured in terms of scheduled cargo traffic) to get a better understanding of current practice, particularly in the light of potential conflicts or benefits of the joint production of passenger and freight services. While most literature has focused on hub-and-spoke aspects of international hubs, relatively little has been done on economies of scale and scope of passenger and freight airline operations (including timing) at such hubs. This chapter explores to what extent terminal organisation of international airports impacts on the use of dedicated freighter of combination airlines and hence airline efficiency. A key finding in terms of airline efficiency is that economies of scale of air cargo operation appear to exist at the aircraft level as dedicated freighters are used more often if a sufficient threshold of air freight demand is observed at the airport level.

This research estimates a multi-product flexible cost function of airport variable costs. Data for the analysis are a panel of 50 airports from 1996 to 2008. Output includes domestic and international departures, non-aeronautical operating revenues, and the number of transport workload units, where a workload unit is a passenger or the equivalent of a 220 pound packet of cargo. The quasi-fixed factor is the equivalent number of 10,000′ × 150′ runways at an airport. After correcting for first-order serial correlation, the analysis finds that airports operate under constant returns to runway utilization and multi-product decreasing returns to scale, production technology is consistent with product specific returns to capacity utilization and anti-complementarity across outputs, and general airport operations have input substitution possibilities with personnel and contractual repair/maintenance inputs. The study also finds 1.05% technology progress over the sample period, due to strong growth prior to 2001, with similar productivity growth rates for large and medium hubs.

This chapter studies the technical efficiencies of Chinese airports by using a meta-frontier production function model which accounts for airports in different regions accessing different technologies. Our empirical results show that the technical efficiency scores of airports and provincial output in the coastal region are higher than their counterparts in the inland region. However, the technical efficiency scores of airports and provincial output in inland region are steadily increasing while the counterparts of airports and provincial output in coastal region are slowly declining. In addition, our analysis of provincial efficiency changes shows that airport productivity has a positive and statistically significant effect on the technical changes of provincial output. Our results partially confirm the success of the government policy of promoting airport construction and development in the western inland region.

Air carriers and aircraft manufacturers are investing in technologies and strategies to reduce fuel consumption and associated emissions. This chapter reviews related issues to assess airline fuel efficiency and offers various empirical evidences from our recent work that focuses on the U.S. domestic passenger air transportation system. We begin with a general presentation of four methods (ratio-based, deterministic frontier, stochastic frontier, and data envelopment analysis) and three perspectives for assessing airline fuel efficiencies, the latter covering consideration of only mainline carrier operations, mainline–subsidiary relations, and airline routing circuity. Airline fuel efficiency results in the short run, in particular the correlations of the results from using different methods and considering different perspectives, are discussed. For the long-term efficiency, we present the development of a stochastic frontier model to investigate individual airline fuel efficiency and system overall evolution between 1990 and 2012. Insight about the association of fuel efficiency with market entry, exit, and airline mergers is also obtained.

Following deregulation, the airline industry has dramatically changed. In addition to numerous mergers and bankruptcies, the industry has also seen an influx of small, “low-cost” carriers who offer differentiated competition to the traditional legacy carriers. These low-cost carriers traditionally avoided the hub-and-spoke networks of legacy carriers, offering point-to-point service often on adjacent routes. However, events of the past 10–15 years, including the terrorist attacks of 9/11, rising fuel prices, and economic recessions, have led to a shift in the operations of these airlines. The legacy carriers have unbundled many of their services, most notably through baggage fees, seeking to improve efficiency. Low-cost carriers have expanded services into major airports and have shifted to more direct route level competition with the legacy carriers as they use their cost efficiency advantages to their advantage. In this chapter, we examine airport and route choice decision to serve by legacy and low-cost carriers over time. Our descriptive and econometric models point to convergence of operations in terms of the airports and routes that low-cost and legacy carriers serve, with the implication that the current competitive atmosphere improves efficiency as the distinctions between legacy and low-cost carriers have become less obvious.