Is it the labor unions’ fault? Dissecting the causes of the impaired technical efficiencies of the legacy carriers in the United States

Data envelopment analysis is used to evaluate the technical efficiencies of a number of major passenger airlines in the United States at transforming their inputs (labor, fuel and fleet-wide seating capacity) into available seat-miles. A tobit regression model is then used to identify the underlying drivers of airline efficiency, as measured by the data envelopment analysis efficiency score. The impact of unionization on airline efficiency is found to be statistically insignificant, controlling for the influences of other hypothesized determinants of airline efficiency: the average age of an airline’s fleet, the average size of its aircraft, its average stage length, the extent to which the airline relies of hubbing within its route structure, the percent of its passenger enplanements that are international, and whether the airline is a legacy carrier. The statistically significant drivers of airline efficiency, at a ten percent level of significance, are average aircraft size, average stage length and the extent to which the airline relies on hubbing and connecting flights within its route structure. The stage length variable is not significant at a five percent level of significance, however. An increase in average aircraft size or in average stage length enhances an airline’s efficiency whereas an increase in hubbing reduces it.     

An optimal aircraft fleet management decision model under uncertainty

Decision planning for an efficient fleet management is crucial for airlines to ensure a profit while maintaining a good level of service. Fleet management involves acquisition and leasing of aircraft to meet travelers' demand. Accordingly, the methods used in modeling travelers' demand are crucial as they could affect the robustness and accuracy of the solutions. Compared with most of the existing studies that consider deterministic demand, this study proposes a new methodology to find optimal solutions for a fleet management decision model by considering stochastic demand. The proposed methodology comes in threefold. First, a five‐step modeling framework, which is incorporated with a stochastic demand index (SDI), is proposed to capture the occurrence of uncertain events that could affect the travelers' demand. Second, a probabilistic dynamic programming model is developed to optimize the fleet management model. Third, a probable phenomenon indicator is defined to capture the targeted level of service that could be achieved satisfactorily by the airlines under uncertainty. An illustrative case study is presented to evaluate the applicability of the proposed methodology. The results show that it is viable to provide optimal solutions for the aircraft fleet management model. Copyright © 2013 John Wiley & Sons, Ltd.     

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

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.     

Measuring the environmental efficiency of the global aviation fleet

This research analyses the environmental footprint of the airline industry in an attempt to highlight potential paths for improvement. We develop a directional economic-environmental distance function (DEED) which accounts for the production of both desirable and undesirable output and the potential for constrained increases in input utilization. This research applies the modeling framework to analyze the potential to reduce noise and airborne pollutants emitted by aircraft–engine combinations given the current state of aeronautical technology. The global aircraft–engine market is viewed from the regulatory perspective in order to compare the single environmental and operational efficient frontier to that of the airline carriers, and environmental objectives. The results of DEED are then applied in order to substitute the fleets serving Schipol, Amsterdam and Arlanda, Stockholm airports in June 2010 with the benchmark aircraft. The results highlight the inefficiencies of the current airline fleets and that the IPCC values of externalities are a magnitude of TEN too low to encourage changes in the global fleet hence the need for government intervention.     

A hybrid optimization-simulation approach for robust weekly aircraft routing and retiming

We address the robust weekly aircraft routing and retiming problem, which requires determining weekly schedules for a heterogeneous fleet that maximizes the aircraft on-time performance, minimizes the total delay, and minimizes the number of delayed passengers. The fleet is required to serve a set of flights having known departure time windows while satisfying maintenance constraints. All flights are subject to random delays that may propagate through the network. We propose to solve this problem using a hybrid optimization-simulation approach based on a novel mixed-integer nonlinear programming model for the robust weekly aircraft maintenance routing problem. For this model, we provide an equivalent mixed-integer linear programming formulation that can be solved using a commercial solver. Furthermore, we describe a Monte-Carlo-based procedure for sequentially adjusting the flight departure times. We perform an extensive computational study using instances obtained from a major international airline, having up to 3387 flights and 164 aircraft, which demonstrates the efficacy of the proposed approach. Using the simulation software SimAir to assess the robustness of the solutions produced by our approach in comparison with that for the original solutions implemented by the airline, we found that on-time performance was improved by 9.8–16.0%, cumulative delay was reduced by 25.4–33.1%, and the number of delayed passengers was reduced by 8.2–51.6%.     

Dynamic yield management when aircraft assignments are subject to swap

As a practical form of demand driven dispatch at some major airlines in North America, cockpit compatible aircraft of different capacities are paired in the fleet assignment for a possible future swap on the two involved flights. They are paired in such a way that the swap does not affect their aircraft routings on other legs. The swap decision depends on demand realization on the two flights and is made at a predetermined time prior to departure. Yield management on the two flights is studied in this paper. We begin by studying a base problem in which at a certain time before departure, the assignment on a flight is subject to change with a fixed probability. The base problem extends the threshold policy into the case where future capacity is uncertain. Secondly, we propose a heuristic for yield management over two flights with swappable aircraft by repeatedly updating the swap probability as demand unfolds. Our numerical result shows that this policy significantly enhances the airline’s capability to increase revenue under demand driven dispatch. In addition, the base problem may shed lights on derivation of optimal yield management policy in irregular operational settings where final capacity assignment is independent of yield management policy.     

Evaluating optimal multi-hub networks in a deregulated aviation market with an application to Western Europe

This paper develops, evaluates and ultimately aids in the choosing of an optimal, single allocation, hub-and-spoke network for an airline working in a deregulated market. An integer linear program evaluates potential hub network combinations, whose profits are then determined using a non-linear mathematical program. International gateway airports and regional hubs, profit, frequency and aircraft size are the decision variables. An adapted, conjugate-gradient projection algorithm is developed and the models are subsequently applied to Western Europe.     

Eco-efficiency management program (EEMP)—a model for road fleet operation

Fuel consumption has always been a matter of economic concern in road fleet management, giving rise to many initiatives aimed at fostering more efficient energy use. The increasingly awareness of environmental problems now requires these programs to include environmental aspects. A structured Eco-efficiency Management Program (EEMP) is proposed for road fleet operation, taking into account the traditional approach that strives to minimise fuel consumption as well as wider economic and environmental aspects. The EEMP has its potential evaluated in a case study undertaken for INFRAERO, Brazilian’s airport authority, on the operation of its road fleet supporting aircraft ground operations at Rio de Janeiro International Airport. The paper looks at EEMP’s implementation by identifying the program’s phases, its participants and their competencies, eco-efficiency indicators, and performance targets.     

A decomposition approach to determining fleet size and structure with network flow effects and demand uncertainty

This paper presents a new methodology to determine fleet size and structure for those airlines operating on hub‐and‐spoke networks. The methodology highlights the impact of stochastic traffic network flow effects on fleet planning process and is employed to construct an enhanced revenue model by incorporating the expected revenue optimization model into fleet planning process. The objective of the model is to find a feasible allocation of aircraft fleet types to route legs using minimum fleet purchasing cost, thus ensuring that the expected fleet profit is maximized subject to several critical resource constraints. By using a linear approximation to the total network revenue function, the fleet planning model with enhanced revenue modeling is decomposed into the nonlinear aspects of expected revenue optimization and the linear aspects of determining fleet size and structure by optimal allocation of aircraft fleet types to route legs. To illustrate this methodology and its economic benefits, an example consisting of 6 chosen aircraft fleet types, 12 route legs, and 57 path‐specific origin‐destination markets is presented and compared with the results found using revenue prorated fleet planning formulation. The results show that the fleet size and structure of the methodology proposed in this paper gain 211.4% improvement in fleet profit over the use of the revenue prorated fleet planning approach. In addition, comparison with the deterministic model reveals that the fleet size and structure of this proposed methodology are more adaptable to the fluctuations of passenger demands. Copyright © 2016 John Wiley & Sons, Ltd.     

Airline ambidextrous competition under an emissions trading scheme – A reference-dependent behavioral perspective

This study presents a reference-dependent Hotelling model for analyzing airline competition in pricing and green transportation investment, as well as the resulting financial performance under the European Union emission trading scheme. One feature of the proposed methodology is that it embeds psychological benefits/costs of consumers to characterize consumer attitudes to the increases in airline fare adjustments and improvements in green transportation. This study then investigates the equilibrium solutions for airfare adjustment and green transportation investment margins in different scenarios. The analytical results reveal specific operational conditions under which a cost-efficient airline can gain supreme competitive advantage by increasing both airfare and green transportation investment margins beyond the increases made by competitors under the emission trading scheme, whereas certain specific conditions may favor a cost leadership strategy. Conversely, a cost-inefficient airline can compete with a cost-efficient airline in both market share and profitability using the green transportation investment-differentiation strategy, particularly when consumers perceive the airfare difference as equaling the increased psychological benefit induced by the airline’s green effort.     

A heuristic model for frequency planning and aircraft routing in small size airlines

The flight schedule of an airline is the primary factor in finding the most effective and efficient deployment of the airline's resources. The flight schedule process aims at finding a set of routes with associated aircraft type, frequency of service and times of departures and arrivals in order to satisfy a specific objective such as profit maximization. In this paper, we develop a two‐phase heuristic model for airline frequency planning and aircraft routing for small size airlines. The first phase develops a frequency plan using an economic equilibrium model between passenger demand for flying a particular route and aircraft operating characteristics. The second phase uses a time‐of‐day model to develop an assignment algorithm for aircraft routing.     

The flight perturbation problem

Airlines spend considerable time, effort and financial resources on planning. It is essential to create a competitive timetable and construct a fleet and a crew schedule that utilizes these resources to the maximum. Unfortunately, it is all too common that an airline is faced with the necessity of reconstructing their schedules due to some unforeseen event, for example an aircraft breakdown or a crew member that is indisposed. In this paper, an application that can help airlines solve the complex problem of reconstructing aircraft schedules is presented. A mixed integer multicommodity flow model with side constraints is developed and further reformulated into a set packing model using the Dantzig—Wolfe decomposition. Cancellations, delays and aircraft swaps are used to resolve the perturbation, and the model ensures that the schedule returns to normal within a certain time. Two column generation schemes for heuristically solving the model are tested on real problem data obtained from a Swedish domestic airline. The computational tests show that the application is capable of presenting high quality solutions in a few seconds and therefore can be used as a dynamic decision support tool by the airlines.     

The punctuality performance of aircraft rotations in a network of airports

The aim of this paper is to investigate the influence of aircraft turnaround performance at airports on the schedule punctuality of aircraft rotations in a network of airports. A mathematical model is applied, composed of two sub-models, namely the aircraft turnaround model (turnaround simulations) and the enroute model (enroute flight time simulations). A Markovian type model is featured in the aircraft turnaround model to simulate the operation of aircraft turnarounds at an airport by considering operational uncertainties and schedule punctuality variance. In addition, stochastic Monte Carlo simulations are employed to carry out stochastic sampling and simulations in both the aircraft turnaround model and the enroute model. Results of simulations show the robustness of the aircraft rotation model in capturing uncertainties from aircraft rotations. The propagation of knock-on delays in aircraft rotations is found to be significant when the short-connection-time policy is used by an airline at its hub airport. It is also found that the proper inclusion of schedule buffer time in the aircraft rotation schedule helps control the propagation of knock-on delays and, therefore, stabilize the punctuality performance of aircraft rotations.     

Inter-city bus routing and timetable setting under stochastic demands

Vehicle fleet routing and timetable setting are essential to the enhancement of an inter-city bus carrier’s operating cost, profit, level of service and competitiveness in the market. In past research the average passenger demand has usually served as input in the production of the final fleet routes and timetables, meaning that stochastic disturbances arising from variations in daily passenger demand in actual operations are neglected. To incorporate the stochastic disturbances of daily passenger demands that occur in actual operations, in this research, we established a stochastic-demand scheduling model. We applied a simulation technique, coupled with link-based and path-based routing strategies, to develop two heuristic algorithms to solve the model. To evaluate the performance of the proposed model and the two solution algorithms, we developed an evaluation method. The test results, regarding a major Taiwan inter-city bus operation, were good, showing that the model and the solution algorithms could be useful in practice.     

Airline scheduling: a heurisitic approach

In this paper a practical technique for finding improved airline routings and schedules is developed. A dynamic programming algorithm is combined with a heuristic method for assigning routes to the aircraft such that the expected total contribution to profit is maximum. Expected passenger demands and priorities are taken to be an input to the model. The model may be used to check the effect on the total system of adding or removing aircraft or of varying aircraft capacity. Although the test runs were made on data for a six city‐ten aircraft array a smaller, more simple numerical example is given to demonstrate the model logic.     

Coordinated scheduling models for allied airlines

Recently, as a means of forming global networks and improving operation efficiency, major air carriers have increasingly entered into alliances with other carriers. Fleet routing and flight scheduling are not only important in individual airline operations, but also affect the alliances. The setting of a good flight schedule can not only enhance allied airline operating performance, but can also be a useful reference for alliance decision-making. In this research, we develop several coordinated scheduling models, which will help the allied airlines solve for the most satisfactory fleet routes and timetables under the alliance. We employ network flow techniques to construct the models. The models are formulated as multiple commodity network flow problems which can be solved using a mathematical programming solver. Finally, to evaluate the models, we perform a case study based on real operating data from two Taiwan airlines. The preliminary results are good, showing that the models could be useful for airline alliances.     

Heuristic approach to the airline schedule disturbances problem

Abstract

When disturbances make it impossible to realise the planned flight schedule, the dispatcher at the airline operational centre defines a new flight schedule based on airline policy, in order to reduce the negative effects of these perturbations. Depending on airline policy, when designing the new flight schedule, the dispatcher delays or cancels some flights and reassigns some flights to available aircraft. In this paper, a decision support system (DSS) for solving the airline schedule disturbances problem is developed aiming to assist decision makers in handling disturbances in real-time. The system is based on a heuristic algorithm, which generates a list of different feasible schedules ordered according to the value of an objective function. The dispatcher can thus select and implement one of them. In this paper, the possibilities of DSS are illustrated by real numerical examples that concern JAT Airways' flight schedule disturbances.     

Impact of biometric and anthropometric characteristics of passengers on aircraft safety and performance

Demand for commercial air travel has been increasing over the years and recent forecasts indicate similar future trends. New aircraft with enhanced design features are being built and entering the airline service globally. These enhancements aim to ensure continued safety, efficiency, performance and prolonged life serviceability. However, these new enhancements often neglect the impact of the changing anthropometric characteristics of the passenger. Past studies have identified increasing trends in the average weight, height and other anthropometrical and biometrical measures of people at a global scale. However, many are limited to only exploring the ramifications primarily from the perspective of passenger experience. This paper highlights the importance of considering passengers’ anthropometric characteristics from a holistic perspective and identifies gaps for future research.     

Predicting market potential and environmental benefits of deploying electric taxis in Nanjing,China

This paper investigates the market potential and environmental benefits of replacing internal combustion engine (ICE) vehicles with battery electric vehicles (BEVs) in the taxi fleet in Nanjing, China. Vehicle trajectory data collected by onboard global positioning system (GPS) units are used to study the travel patterns of taxis. The impacts of charger power, charging infrastructure coverage, and taxi apps on the feasibility of electric taxis are quantified, considering taxi drivers’ recharging behavior and operating activities. It is found that (1) depending on the charger power and coverage, 19% (with AC Level 2 chargers and 20% charger network coverage) to 56% (with DC chargers and 100% charger network coverage) of the ICE vehicles can be replaced by electric taxis without driving pattern changes; (2) by using taxi apps to find nearby passengers and charging stations, drivers could utilize the empty cruising time to charge the battery, which may increase the acceptance of BEVs by up to 82.6% compared to the scenario without taxi apps; and (3) tailpipe emissions in urban areas could be significantly reduced with taxi electrification: a mixed taxi fleet with 46% compressed-natural-gas-powered (CNG) and 54% electricity-powered vehicles can reduce the tailpipe emissions by 48% in comparison with the fleet of 100% CNG taxis.     

Future electricity demand from battery‐powered vehicles

An important decision faced by airline schedulers is how to adapt the flight schedule and aircraft assignment to unforeseen perturbations in an established schedule. In the face of unforeseen aircraft delays, schedulers have to decide which flights to delay, and when delays become excessive, which to cancel. Current scheduling models deal with simple decision problems of delay or cancellation, but not with both simultaneously. But in practice the optimal decision may involve results from the integration of both flight cancellations and delays. In Part I of this paper, a quadratic programming model for the integration decision problem is given. The model can formulate the integration of flight cancellations and delays as well as some special cases, such as the ferrying of surplus aircraft and the possibility of swapping different types of aircraft. In this paper, based on the special structure of the model, an effective algorithm is presented, sufficient computational experiments are conducted and some results are reported. These show that we can expect to obtain a sufficiently good solution in terms of reasonable CPU time.