Factors affecting the operational success of strategic airline alliances

With increased liberalisation in major air transport markets, the intensity of competition has increased amongst air carriers. Airlines have responded to the competitive pressures in many ways, one of which has been the formation of alliances. These alliances are linkages between the firms at various operational levels. They go beyond the common interlining agreement to encompass certain marketing and cost-reducing features. However, the question is how the success of these alliances can be ensured? While companies' culture compatibility is important and much has been written in that area, this paper focuses on factors that affect operational success of airline alliances. The operational success is measured by the change in the level of partners' inter-hub traffic due to formation of the alliance. This research has developed a methodology which could be used as a management tool to measure alliances' operational success before embarking on such agreements. The analysis of recent major alliances covering 52 inter-hub routes suggests that the main factors ensuring the alliances' operational success are: the partners' network size and their compatibility, the frequency of service between the hubs of the partners, the flight connection time at the hub and the level of competition on their network.

     

Airline competition and network structure

This paper studies airline networks and their welfare implications in an unregulated environment. Competing airlines may adopt either fully-connected (FC) or hub-and-spoke (HS) network structures; and passengers exhibiting low brand loyalty to their preferred carrier choose an outside option to travel so that markets are partially served by airlines. In this context, carriers adopt hubbing strategies when costs are sufficiently low, and asymmetric equilibria where one carrier chooses a FC strategy and the other chooses a HS strategy may arise. Quite interestingly, flight frequency can become excessive under HS network configurations.     

Assessment of carbon emission costs for air cargo transportation

This study presents a set of models that calculate carbon emissions in individual phases of flight during air cargo transportation, investigates resultant carbon footprints by aircraft type and flight route, and estimates increases in transportation costs for airlines due to carbon taxes imposed by the EU ETS. The estimated results provide useful references for airlines in aircraft assignment on different routes and in aircraft selection for new purchases. Validation of the model is conducted by simulating the potential impact of the implementation of the EU ETS on costs of air cargo transportation for six routes and six types of aircraft. Results show that the impact may be subject to various factors including unit carbon emissions per aircraft, aviation emission allowances per airline, and carbon trading prices; and that increases in costs of air cargo transportation range from 0% to 5.27% per aircraft per route. Therefore, the implementation of the EU ETS may encourage airlines to cut down their operating costs by reducing their carbon emissions, thereby ameliorating greenhouse gas pollution caused by air cargo transportation.     

Environmental charges in airline markets

Over the last two decades many airline markets have been deregulated, resulting in increased competition and use of different types of networks. At the same time there has been an intense discussion on environmental taxation of airline traffic. It is likely that an optimal environmental charge and the effects of a charge differ between different types of aviation markets. In this paper, we derive optimal flight (environmental) charges for different types of airline markets. The first type of market is a multiproduct monopoly airline operating either a point-to-point network or a hub-and-spoke network. The optimal charge is shown to be similar in construction to an optimal charge for a monopolist. We also compare the environmental impact of the two types of networks. Given no differences in marginal damages between airports we find that an airline will always choose the network with the highest environmental damages. The second type of market we investigate is a multiproduct duopoly, where two airlines compete in both passengers and flights. The formulation of the optimal charge is similar to the optimal charge of a single product oligopoly. However, we also show that it is, because of strategic effects, difficult to determine the effects of the charge on the number of flights.     

An aggregate demand model for air passenger traffic in the hub-and-spoke network

In this paper, we build an aggregate demand model for air passenger traffic in a hub-and-spoke network. This model considers the roles of airline service variables such as service frequency, aircraft size, ticket price, flight distance, and number of spokes in the network. It also takes into account the influence of local passengers and social-economic and demographic conditions in the spoke and hub metropolitan areas. The hub airport capacity, which has a significant impact on service quality in the hub airport and in the whole hub-and-spoke network, is also taken into consideration.Our demand model reveals that airlines can attract more connecting passengers in a hub-and-spoke network by increasing service frequency than by increasing aircraft size in the same percentage. Our research confirms the importance of local service to connecting passengers, and finds that, interestingly, airlines’ services in the first flight leg are more important to attract passengers than those in the second flight segment. Based on data in this study, we also find that a 1% reduction of ticket price will bring about 0.9% more connecting passengers, and a 1% increase of airport acceptance rate can bring about 0.35% more connecting passengers in the network, with all else equal. These findings are helpful for airlines to understand the effects of changing their services, and also useful for us to quantify the benefits of hub airport expansion projects.At the end of this paper, we give an example as an application to demonstrate how the developed demand model could be used to valuate passengers’ direct benefit from airport capacity expansion.     

An optimization model for a real-time flight scheduling problem

Although airlines plan aircraft routes and crew schedules in advance, perturbations occur everyday. As a result, flight schedules may become infeasible and would need to be updated. This Day of Operations Scheduling problem impacts the entire system of an airline as the decisions enforced are final. When perturbations are relatively small, the airline may be able to at least preserve the planned aircraft and crew itineraries. We propose a model that determines new flight schedules based on planned crew transfers, rest periods, passenger connections, and maintenance. Its dual is shown to be a network model, hence solvable in a real-time environment. In addition, it can be used in more sophisticated operational and planning systems.     

An optimization model for aircraft maintenance scheduling and re-assignment

The aircraft maintenance scheduling is one among the major decisions an airline has to make during its operation. Though maintenance scheduling comes as an end stage in an airline operation, it has potential for cost savings. Maintenance scheduling is an easily understood but difficult to solve problem. Given a flight schedule with aircraft assigned to it, the aircraft maintenance-scheduling problem is to determine which aircraft should fly which segment and when and where each aircraft should undergo different levels of maintenance check required by the Federal Aviation Administration. The objective is to minimize the maintenance cost and any costs incurred during the re-assignment of aircraft to the flight segments.This paper provides a complete formulation for maintenance scheduling and a heuristic approach to solve the problem. The heuristic procedure provides good solutions in reasonable computation time. This model can be used by mid-sized airline corporations to optimize their maintenance costs.     

Airline flight scheduling for oligopolistic competition with direct flights and a point to point network

In this research, we consider a flight scheduling problem for oligopolistic competition with direct flights and a point to point network. In this type of market situation, passengers are sensitive to the departure time of a flight rather than the transfer time. The airline needs to carefully consider the departure times of their competitors when determining their own. Therefore, unlike past approaches which have only considered one departure time for a competitor's flight, a flight scheduling framework is developed which takes into consideration possible competitor departure times. The framework includes two dependent stages which are repeatedly solved during the solution process. In addition, an upper bound model is also designed to evaluate the solution quality. Numerical tests are performed using data for Taiwan's outlying island route which is characterized by the above market situation. Satisfactory results are obtained, showing the good performance of the framework. Copyright © 2017 John Wiley & Sons, Ltd.     

Monitoring Aircraft Turnaround Operations – Framework Development,Application and Implications for Airline Operations

Abstract

A real-time operation monitoring system – Aircraft Turnaround Monitoring System – is developed based on a system framework to monitor aircraft turnaround operations at an airport. Mobile computing devices (PDAs) and wireless network technology General Packet Radio Service (GPRS) are used to implement the real-time monitoring system for an airline. System implementation and test results indicate that real-time operation monitoring can potentially reduce delays occurring from airline operations. Proactive measures can be taken immediately by ground handling staff to reduce delays, once the risk of delays and potential delay propagation is identified. The availability of detailed operating data can help airlines identify the root delay causes from complex connections among aircraft, flight/cabin crew and passengers. In addition, these operating data also shed some light on the future development of aircraft routing algorithms in order to consider explicitly stochastic disruptions and delay propagation in airline schedule planning.     

A decision support framework for handling schedule perturbation

Perturbations of flight schedules may occur everyday. Poor scheduling of flights may result in a substantial loss of profit and decreased levels of service for air carriers. This research aims at developing a framework to help carriers in handling schedule perturbations caused by the breakdown of aircraft. The framework is based on a basic schedule perturbation model constructed as a dynamic network from which several perturbed network models are developed for scheduling following incidents. These network models are formulated as pure network flow problems or network flow problems with side constraints. The former are solved using the network simplex method while the latter are solved using Lagrangian relaxation with subgradient methods. To show how to apply the framework in the real world, a case study focusing on the operations of a major Taiwan air carrier in East Asia is presented.     

Congestion spill effects of Heathrow and Frankfurt airports on connection traffic in European and Gulf hub airports

We develop two stage fixed-effects single-spill and double-spill models for congestion connection spills of London Heathrow and Frankfurt airports on 9 hub airports in Europe and the Gulf. Our panel data covers connection traffic from 1997 to 2013 for Heathrow and 1997 to 2011 for Frankfurt. The single-spill results support strongly that the connection spills from Heathrow’s capacity limitations do strengthen competing hub airports of major alliance groups and to a lesser degree one Gulf hub. The double-spill model for Heathrow and Frankfurt shows nearly asymmetric overall spill characteristics between the two airports. Our results underline the influence of airline network strategies on congestion spills as European airline networks are shaped by alliances and umbrella mergers. Thus, the airline network perspective in airport capacity expansion decisions needs to play a greater role, as indicated by our asymmetric results for overall spill effects between Heathrow and Frankfurt airports.     

The benefits of airline global alliances: an empirical assessment of the perceptions of business travelers

Many claims have been made concerning the benefits of airline global alliances, often from the viewpoint of airline operators. By contrast, the focus of this paper is an empirical study of the perceptions of consumers. Studied first are the perceptions that business travelers have of the benefits of global alliances. Results show that a sizeable minority are unsure of the benefits or hold at least some misconceptions. This varies depending on the nature of the benefit and the type of respondent. Results also suggest that no major differences are perceived in the benefits offered by competing global alliances. Second, the importance of global alliance benefits in determining airline choice by business travelers is considered. Relative to other benefits, alliance benefits are not seen as particularly important.     

Open skies and open gates

Airline alliances are a global transportation issue which is the subject of increasing attention in the literature. A simple simulation model of air carrier competition in a network is constructed to examine the economic welfare effects of different levels of alliance between the carriers serving the network. The simulations confirm that consumers derive benefits from improved access to passenger markets. However, in many cases, carriers tend to gain from a limited alliance such as code-sharing. This suggests that closer alliances may be driven by other considerations such as raising barriers to entry or the cross-subsidisation of international routes through greater control of the domestic market.     

Airline-driven ground delay programs: A benefits assessment

Three decades of research studies in ground delay program (GDP) decision-making, and air traffic flow management in general, have produced several analytical models and decision support tools to design GDPs with minimum delay costs. Most of these models are centralized, i.e., the central authority almost completely decides the GDP design by optimizing certain centralized objectives. In this paper, we assess the benefits of an airline-driven decentralized approach for designing GDPs. The motivation for an airline-driven approach is the ability to incorporate the inherent differences between airlines when prioritizing, and responding to, different GDP designs. Such differences arise from the airlines’ diverse business objectives and operational characteristics. We develop an integrated platform for simulating flight operations during GDPs, an airline recovery module for mimicking the recovery actions of each individual airline under a GDP, and an algorithm for fast solution of the recovery problems to optimality. While some of the individual analytical components of our framework, model and algorithm share certain similarities with those used by previous researchers, to the best of our knowledge, this paper presents the first comprehensive platform for simulating and optimizing airline operations under a GDP and is the most important technological contribution of this paper. Using this framework, we conduct detailed computational experiments based on actual schedule data at three of the busiest airports in the United States. We choose the recently developed Majority Judgment voting and grading method as our airline-driven decentralized approach for GDP design because of the superior theoretical and practical benefits afforded by this approach as shown by multiple recent studies. The results of our evaluation suggest that adopting this airline-driven approach in designing the GDPs consistently and significantly reduces airport-wide delay costs compared to the state-of-the-research centralized approaches. Moreover, the cost reduction benefits of the resultant airline-driven GDP designs are equitably distributed across different airlines.     

On the relationship between airport pricing models

Airport pricing papers can be divided into two approaches. In the traditional approach the demand for airport services depends on airport charges and on congestion costs of both passengers and airlines; the airline market is not formally modeled. In the vertical-structure approach instead, airports provide an input for an airline oligopoly and it is the equilibrium of this downstream market which determines the airports’ demand. We prove, analytically, that the traditional approach to airport pricing is valid if air carriers have no market power, i.e. airlines are atomistic or they behave as price takers (perfect competition) and have constant marginal operational costs. When carriers have market power, this approach may result in a surplus measure that falls short of giving a true measure of social surplus. Furthermore, its use prescribes a traffic level that is, for given capacity, smaller than the socially optimal level. When carriers have market power and consequently both airports and airlines behave strategically, a vertical-structure approach appears a more reasonable approach to airport pricing issues.     

Measuring the energy efficiency for airlines under the pressure of being included into the EU ETS

In 2008, European Union (EU) announced that from 2012, each international flight taking off and landing in EU would be given an emission permit. Therefore, the period of 2008–2012 can be regarded as a buffer period for global airlines. Although EU formally decides to exclude non‐EU airlines from the EU Emission Trading System on March 4, 2014, it is necessary to investigate the impacts of the policy on airline energy efficiency in this period. Airline energy efficiency is divided into three stages—operations stage, service stage, and sales stage—and Greenhouse gas emission is treated as an undesirable output of service stage. Two models, network range‐adjusted measure model with weak disposability and network range‐adjusted measure model with strong disposability, are established to evaluate the efficiencies of 22 international airlines from 2008 to 2012. The results show that (i) most airlines' efficiencies have decreased in the period, and the EU Emission Trading System is not effective for the efficiency improvement; (ii) the average efficiency of European airlines is almost the same as that of non‐European airlines; and (iii) the model with weak disposability is more reasonable in distinguishing efficiency differences, while strong disposability is a more reasonable way in treating undesirable outputs. Copyright © 2016 John Wiley & Sons, Ltd.     

Serving vs. settling: What drives the establishment of low-cost carriers’ foreign bases?

This paper uses a probit model on a cross-sectional dataset of 202 airports and 29 airlines to assess the drivers for the establishment of foreign bases by European low-cost carriers (LCCs). We find that managerial, organizational, and environmental factors impact on foreign base establishment. In particular, there is evidence that the presence of a growth-oriented firm leader and the strategic importance of an airport for an airline significantly increase the probability of the presence of bases, while national unit labor costs, the volatility of flight operations and the membership of an LCC in an airline group significantly decrease this probability.     

Price effects of airlines frequent flyer programs: The case of the dominant firm in Chile

Frequent flyer programs create a switching cost for the consumer and allow firms to obtain rents, for example, by exploiting the principal agent problem existing between the employee who travel and purchases the ticket and the employer paying for that ticket. In Chile LAN is the dominant airline in domestic markets and the only one that has a frequent flyer program (FFP); it faces some competition from two small carriers. Using a unique dataset for Chile, collected by ourselves from airlines websites in 2011 and 2012, we estimate the impact of the dominant airline FFP. For this purpose, we compare for each route the fares between airlines and between weekday trips (that accumulate full miles and are mainly for business purposes) and weekend trips (that accumulate less than full miles and are mainly for leisure purposes). The results show that the differential premium LAN is able to charge for weekday trips due to the FFP is around 35%. Three particularities of the Chilean market help the econometric identification: there is only one hub for all airlines (the capital city of Santiago), there is no business class in domestic flights, and none of the airlines is a low-cost carrier.     

A math-heuristic algorithm for the integrated air service recovery

A sophisticated flight schedule might be easily disrupted due to adverse weather, aircraft mechanical failures, crew absences, etc. Airlines incur huge costs stemming from such flight schedule disruptions in addition to the serious inconveniences experienced by passengers. Therefore, an efficient recovery solution that simultaneously decreases an airline's recovery cost while simultaneously mitigating passenger dissatisfaction is of great importance to the airline industry. In this paper, we study the integrated airline service recovery problem in which the aircraft and passenger schedule recovery problems are simultaneously addressed, with the objective of minimizing aircraft recovery and operating costs, passenger itinerary delay cost, and passenger itinerary cancellation cost.Recognizing the inherent difficulty in modeling the integrated airline service recovery problem within a single formulation (due to its huge solution space and quick response requirement), we propose a three-stage sequential math-heuristic framework to efficiently solve this problem, wherein the flight schedules and aircraft rotations are recovered in the first stage, Then, a flight rescheduling problem and passenger schedule recovery problems are iteratively solved in the next two stages. Time-space network flow representations, along with mixed-integer programming formulations, and algorithms that take advantages of the underlying problem structures, are proposed for each of three stages. This algorithm was tested on realistic data provided by the ROADEF 2009 challenge and the computational results reveal that our algorithm generated the best solution in nearly 72% of the test instances, and a near-optimal solution was achieved in the remaining instances within an acceptable timeframe. Furthermore, we also ran additional computational runs to explore the underlying characteristics of the proposed algorithm, and the recorded insights can serve as a useful guide during practical implementations of this algorithm.     

Airline energy efficiency measures using the Virtual Frontier Network RAM with weak disposability

In this paper, airline energy efficiency is divided into three stages: the operations stage, the services stage and the sales stage. Greenhouse gas emissions are treated as an undesirable output of the services stage. This new three-stage strategic operating framework is a modification of existing models. A new model, Virtual Frontier Network Range Adjusted Measure with weak disposability, is proposed to evaluate the efficiencies of 22 international airlines, from 2008 to 2012. The results show that the new model can establish more reasonable rankings and confirm new benchmarking airlines and that inclusion in the European Union’s Emissions Trading Scheme has had little influence on the improvement of airline energy efficiency.