Network Structures of Cargo Airlines - An Empirical and a Modelling Approach

The development of efficient air freight networks is an upcoming challenge. The present book approaches this problem for cargo airlines by characterising and classifying their network structures and by developing a model for an airline\u27s strategic network design. The book provides results which are of value for airline professionals (network efficiency analysis), policy makers (policy impact assessment) and researchers (cargo airline network design model)

Airline Emission Charges: Effects on Airfares, Service Quality, and Aircraft Design

This paper explores the effect of airline emissions charges on airfares, airline service quality, aircraft design features, and network structure, using a detailed and realistic theoretical model of competing duopoly airlines. These impacts are derived by analyzing the effects of an increase in the effective price of fuel, which is the path by which emissions charges will alter airline choices. The results show that emission charges will raise fares, reduce flight frequency, increase load factors, and raise aircraft fuel efficiency, while having no effect on aircraft size. Given that these adjustments occur in response to the treatment of an emissions externality that is currently unaddressed, they represent efficient changes that move society closer to a social optimum.emissions, airlines

Airline Emission Charges: Effects on Airfares, Service Quality, and Aircraft Design

This paper explores the effect of airline emissions charges on airfares, airline service quality, aircraft design features, and network structure, using a detailed and realistic theoretical model of competing duopoly airlines. These impacts are derived by analyzing the effects of an increase in the effective price of fuel, which is the path by which emissions charges will alter airline choices. The results show that emission charges will raise fares, reduce flight frequency, increase load factors, and raise aircraft fuel efficiency, while having no effect on aircraft size. Given that these adjustments occur in response to the treatment of an emissions externality that is currently unaddressed, they represent efficient changes that move society closer to a social optimum.Emissions; Global warming; Airlines

Study of the full-service and low-cost carriers network configuration

Purpose: The network strategies used by airline carriers have been a recurring subject in air transport research. The aim of this paper is to investigate the relationship between the different operational characteristics of the airline and its route network configuration. Design/methodology/approach: The two main airline carrier typologies - Full-Service and Low-Cost carriers – are analysed using empirical models developed on complex network research relating them to the business model of the airlines. Findings and Originality/value: Just in Europe, one can differentiate between Full-Service and Low-Cost Carriers by complex network analyses. In this process, it has been also found that new concept Low-Cost Carriers, such as Vueling, have network properties closer to Full-Service Carriers. Research limitations/implications: This paper has a limited sample, as includes 26 airline case studies from Europe, United States and Asia. Practical implications: The analysis carried out in this research can help to the assessment of the evolution of the strategies of airline carriers, and has also operational implications, since the configuration of an airline route network can determine its resilience to attacks and errors.Social implications: A better understanding of the properties of airline route networks can benefit airlines, passengers and another stakeholders of the air transport industry. Originality/value: Current research on air transport networks has only considered the global or regional level, but few studies have addressed the study of airline transport networks, and its relationship with their business model.Peer Reviewe

Attractiveness-based airline network models with embedded spill and recapture

Purpose: In airline revenue management, the modeling of the spill and recapture effects is essential for an accurate estimation of the passenger flow and the revenue in a flight network. However, as most current approaches toward spill and recapture involve either non-linearity or a tremendous amount of additional variables, it is computationally intractable to apply those techniques to the classical network design and capacity planning models. Design/methodology: We present a new framework that incorporates the spill and recapture effects, where the spill from an itinerary is recaptured by other itineraries based on their attractiveness. The presented framework distributes the accepted demand of an itinerary according to the currently available itineraries, without adding extra variables for the recaptured spill. Due to its compactness, we integrate the framework with the classical capacity planning and network design models. Findings: Our preliminary computational study shows an increase of 1.07% in profitability anda better utilization of the network capacity, on a medium-size North American airline provided by Sabre Airline Solutions. Originality/value: Our investigation leads to a holistic model that tackles the network design and capacity planning simultaneously with an accurate modeling of the spill and re- capture effects.Furthermore, the presented framework for spill and recapture is versatile and can be easily applied to other disciplines such as the hospitality industry and product line design (PLD) problems.Peer Reviewe

Estimating Customer Lifetime Value Using Machine Learning Techniques

With the rapid development of civil aviation industry, high-quality customer resources have become a significant way to measure the competitiveness of the civil aviation industry. It is well known that the competition for high-value customers has become the core of airline profits. The research of airline customer lifetime value can help airlines identify high-value, medium-value and low-value travellers. What is more, the airline company can make resource allocation more rational, with the least resource investment for maximum profit return. However, the models that are used to calculate the value of customer life value remain controversial, and how to design a model that applies to airline company still needs to be explored. In the paper, the author proposed the optimised China Eastern Airlines passenger network value assessment model and examined its fitting degree with the TravelSky value score. Besides, the author combines China Eastern Airlines passenger network value assessment model score with loss model score to help airlines find their significant customers

Assessment of New Hub-and-spoke and Point-to-point Airline Network Configurations

This paper aims to provide new measures of airline network configuration with a view to analyse effectively the complexity of modern carriers' network design. It studies network configurations in the airline sector by taking into account both spatial and temporal dimensions. The spatial dimension is measured by using both the Gini index and the Freeman index, which originate from social science research. The temporal dimension is measured by the connectivity ratio, i.e. the share of indirect connections over the total number of connections. According to these indicators, the configuration of the largest full-service carriers and the largest low-cost carriers in Europe is investigated. The results show that the temporal dimension provides a clear distinction between full-service carriers and low-cost carriers; while the spatial dimension appears useful when identifying the peculiarities within groups

Airline planning benchmark problems—Part II : passenger groups, utility and demand allocation

This paper is the second of two papers entitled “Airline Planning Benchmark Problems”, aimed at developing benchmark data that can be used to stimulate innovation in airline planning, in particular, in flight schedule design and fleet assignment. The former has, to date, been under-represented in the optimisation literature, due in part to the difficulty of obtaining data that adequately reflects passenger choice, and hence schedule revenue. Revenue models in airline planning optimisation only roughly approximate the passenger decision process. However, there is a growing body of literature giving empirical insights into airline passenger choice. Here we propose a new paradigm for passenger modelling, that enriches our representation of passenger revenue, in a form designed to be useful for optimisation. We divide the market demand into market segments, or passenger groups, according to characteristics that differentiate behaviour in terms of airline product selection. Each passenger group has an origin, destination, size (number of passengers), departure time window, and departure time utility curve, indicating willingness to pay for departure in time sub-windows. Taking as input market demand for each origin–destination pair, we describe a process by which we construct realistic passenger group data, based on the analysis of empirical airline data collected by our industry partner. We give the results of that analysis, and describe 33 benchmark instances produced

Disentangling the European airlines efficiency puzzle: a network data envelopment analysis approach

© 2015 Elsevier Ltd. In recent years the European airline industry has undergone critical restructuring. It has evolved from a highly regulated market predominantly operated by national airlines to a dynamic, liberalized industry where airline firms compete freely on prices, routes, and frequencies. Although several studies have analyzed performance issues for European airlines using a variety of efficiency measurement methods, virtually none of them has considered two-stage alternatives - not only in this particular European context but in the airline industry in general. We extend the aims of previous contributions by considering a network Data Envelopment Analysis (network DEA) approach which comprises two sub-technologies that can share part of the inputs. Results show that, in general, most of the inefficiencies are generated in the first stage of the analysis. However, when considering different types of carriers several differences emerge - most of the low-cost carriers' inefficiencies are confined to the first stage. Results also show a dynamic component, since performance differed across types of airlines during the decade 2000-2010