Race to the bottom or swimming upstream: Performance analysis of US airlines

Data envelopment analysis is used to examine inter-temporal and peer group airline efficiency. Results for the US for 1985–2006 indicate that airline performance is converging over time. In particular, airlines inter-temporal inefficiency peaked earlier and then converged. Furthermore, using Tobit specifications it is seen that while demand intensity matters less in determining airlines inter-temporal inefficiency, their influence is stronger in determining peer group inefficiency. Block time, a representative of operational factors, tends to negatively impact airlines efficiency by imposing burdens on airline operations. Among the structural cost and revenue factors, fuel cost tends to affect inter-temporal inefficiency more robustly than it does to peer group efficiency. Labor pay tends to reduce inefficiency in case of inter-temporal while increasing peer group inefficiency. The events of September 11th had little or no impact on inter-temporal inefficiency but tended to reduce peer group inefficiency in a significant way. Finally, airlines efficiency tends to be robustly affected by block hours; reducing them increases efficiency.     

The impact of environmental variables on the efficiency of Chinese and other non-Chinese airlines

This paper explores the impact of an international focus, the proportion of cargo traffic, and the level of salaries on the operational efficiency of Chinese airlines and other non-Chinese airlines. Data envelopment analysis (DEA) is employed to evaluate the operational efficiency and a bootstrapped truncated regression is applied to explore the impact of environmental variables on efficiency. The results show that an international focus has a negative impact, while the level of salaries has a positive impact. Also, we demonstrate that there is an inverted U-shaped relationship between efficiency and the proportion of cargo traffic.     

Route-based performance evaluation of Taiwanese domestic airlines using data envelopment analysis: A comment

This paper provides critical remarks and remedies to a recent article published in [Chiou, Y.-C., Chen, Y.-H., 2006. Route-based performance evaluation of Taiwanese domestic airlines using data envelopment analysis. Transportation Research Part E 42, (2) 116–127]. In their article, the authors adopted data envelopment analysis (DEA) to measure the route-based performance of Taiwanese domestic airlines. The present paper points out the faults or errors found in their article, in terms of variable selection, model selection, scale efficiency and scale economy, slack analysis, Tobit regression, and terminologies used. It is hoped to make more appropriate and much clearer the DEA applications to airline’s performance evaluation.     

A comparative performance analysis of airline strategic alliances using data envelopment analysis

As “open skies” agreements became more common among different countries and thus began to open up international routes to further competition, the global airline industry has undergone accelerated structural changes for the last two decades. These changes include the consolidation and expansion of airline strategic alliances throughout different regions of the world. Though airline strategic alliances are generally perceived to be a major driver for enhancing the operating efficiency and the subsequent competitiveness of participating member airlines, the concrete evidence supporting such a perception is still lacking in the literature. This paper is one of few attempts to evaluate the comparative efficiency of the strategic alliances among global airlines and then assess the managerial impact of airline alliances on the airline's comparative performances.     

The geographical efficiency of Spain's regional airports: A quantitative analysis

Previous studies of the role of regional airports in the Spanish economy have focused on calculating efficiency using air traffic as the output and airport infrastructure data as the input. We present an alternative quantitative analysis based upon the geographical structure within the airport's market basin. We formulate a ‘geographical efficiency’ model that considers territorial variables within the airport hinterland. Input data for our model include the socio-economic structure of the population, intermodal transport links, industrial and tourism potential and existing leisure-related services. The output is the annual number of passengers associated with such constraints. The result is a relative efficiency estimate that shows uneven patterns of geographical efficiency amongst Spain's regional airports and also provides insights into opportunities for expanding some of these critical items of infrastructure. They suggest that some of Spain's regional airports may be better placed than others to compete in a liberalized market that exhibits a clear tendency in favor of coastal, tourism-based airports.     

Measurement of airlines’ capacity utilization and cost gap: Evidence from low-cost carriers

The aim of this paper is to evaluate the capacity utilization and cost gap between actual and global long-run minimum costs. Based on the data for thirteen low-cost carriers around the world for the year 2010, an input-oriented data envelopment analysis model is used to estimate the physical capacity utilization and cost gap between actual and global long-run minimum costs. The empirical results show that more than half of low-cost carriers should improve their capacity utilization, and all low-cost carriers should enhance their market efficiency and reduce their excess costs. Of the thirteen low-cost carriers, three should improve their technical efficiency, four should re-distribute the mix of variable inputs, all thirteen should pay lower prices for all variable inputs, and ten should enhance the utilization rate of their fixed factors.     

How efficient airways act as role models and in what dimensions? A superefficiency DEA model enhanced by social network analysis

In this empirical study, a five-stage methodology is used to examine the efficiency of 45 worldwide known airline companies from the financial, operation and marketing perspectives. Initially, the superefficient data envelopment model is run with inputs and outputs that are selected based on the literature review. However, because 21 out of 45 airline companies are found to be efficient based on this analysis, a stepwise regression-based mechanism is applied to four reduced models – one for each output variable – for better discrimination. The outputs are, namely, net profit margin (financial output), passengers carried, on-time departure performance (operational outputs), and customer satisfaction (marketing output). In this way, the significant input variables are found for each reduced model. In the third stage, in order to provide even more discrimination, social network-based eigenvector centrality values are used as the weights of the superefficiency scores, and the strengths and weaknesses of efficient airlines for each output are specified in terms of their related significant inputs. The results show that, when net profit margin is taken as an output, Vietnam Airlines has the top weighted superefficiency value and excels in terms of available seat kilometers and liquidity, but it should improve its debt level. Although Norwegian Airlines has the highest efficiency with respect to debt level, it is not the best role model because its eigenvector centrality value is relatively low. However, Norwegian airlines also has the highest weighted superefficiency and acts as a role model in terms of on-time departures with respect to this output. Its main strength is liquidity, and it has no significant weaknesses. On the other hand, in terms of overall satisfaction and passengers carried, Vietnam Airlines and Thai Airways are the leaders, respectively. Vietnam Airlines is the only superefficient company with respect to overall satisfaction, while the basic strengths of Thai Airways in terms of passengers carried are its employee and fleet, and it has no significant weakness. A final aggregation of the results is made by making pairwise comparisons of the relative importance of four outputs for 7 experts selected from different departments of airline companies. According to the results, Net Profit Margin has the highest priority, followed by On-time Departure and Overall Customer Satisfaction, while passengers carried has the lowest importance. Based on these relative priorities, it can be said that Vietnam Airlines can be accepted as the top performing airline company, followed by Norwegian Airlines.     

Efficiencies and scope economies of Chinese airports in moving passengers and cargo

The paper looks at the technical efficiency of Chinese airports using multi-output stochastic input distance function analysis. This method provides a statistical test of scope economies to investigate the contribution of air cargo transport to airport efficiency. Our findings confirm the presence of scope economies in air passenger and air cargo transport among airports in China. We compare and contrast these results with results obtained from single-output stochastic production frontier analysis in which the effect of scope economies is not included. Our results indicate that the presence of scope economies significantly affects the estimation of technical efficiency, thus implying different efficiency rankings among airports in China.     

Are outsourcing and non-aeronautical revenues important drivers in the efficiency of Spanish airports?

This paper evaluates the influence of contracting out, or outsourcing, certain airport services and of commercial diversification strategy. Although most of the effort is being put towards applying non-parametric techniques in airport efficiency studies, we have chosen parametric methodology. We use a distance function, as it has known advantages. The findings show the positive contribution of outsourcing and non-aeronautical revenues on the efficiency of the Spanish airports' network.     

Performance assessment of airlines using range-adjusted measure,strong complementary slackness condition,and discriminant analysis

This study integrates RAM (range-adjusted measure), SCSC (strong complementary slackness condition), and DEA–DA (data envelopment analysis–discriminant analysis) to rank airlines. As conventional DEA models do not fully use all inputs and outputs, they result zero in many multipliers. These sorts of DEA models may yield many efficient decision-making units (DMUs). This decreases the discrimination power of DEA. To overcome this limitation, this study proposes a novel application of RAM–DEA/SCSC along with DA. A case study demonstrates the applicability of our proposed approach.     

Operational efficiency of Asia–Pacific airports

Airports are important drivers of economic development and thus under tremendous pressure from emerging competitors. However, few studies have analysed the operational efficiency of Asia–Pacific airports. This study therefore evaluated the operational efficiency of 21 Asia–Pacific airports between 2002 and 2011. A two-stage method was used: Data Envelopment Analysis (DEA) to assess airport efficiency, followed by the second-stage regression analysis to identify the key determinants of airport efficiency. The first-stage DEA results indicated that Adelaide, Beijing, Brisbane, Hong Kong, Melbourne, and Shenzhen are the efficient airports. The second-stage regression analysis suggested that percentage of international passengers handled by an airport, airport hinterland population size, dominant airline(s) of an airport when entering global airline strategic alliance, and an increase in GDP per capita are significant in explaining variations in airport efficiency.     

Comparing efficiency of holding business model and individual management model of airports

This research compares the efficiency of holding business model to individual management model of airports, employing some robust non-parametric partial frontier-based methods to compare the statistical distributions of efficiency, under different scenarios, to find out which group of airports yields better global performance. The comparison between groups will follow a Malmquist index decomposition, which seems to be the most appropriate tool for within- and inter-group performance comparison. For this purpose, a sample of 145 airports from three continents is utilized. The results provide evidence that European airports are the most productive ones, and within this cluster, the individual management model presented a significant frontier shift with respect the holding cluster frontier, meaning that the former is much more productive than the latter.