The federal republic of Germany: the federal ministry of transport

The continued liberalization of the airline market in the European Community offers the prospect of competition in terms of price, frequency of service and many other attributes. Understanding these factors that influence passenger demand and incorporating them into a demand function poses a substantial theoretical and empirical challenge. A basis for estimating demand functions is the logit model. This paper examines the value of a logit share model in explaining how the share of airlines between airports varies as a function of measured and unmeasured attributes. It shows how demand functions are necessary for understanding a competitive market and evaluates the progress to date in identifying accurate coefficients of the logit function.     

Air carrier demand

Modeling air carrier demand is instrumental to understanding the relative importance of competitive forces that shape the airline environment and determine a carrier's market share. This paper develops a conceptual framework for analyzing carrier demand in a competitive context and applies that framework to study air carrier choice. This framework can be used by carriers to assess the market share and revenue implications of service design, pricing, marketing, and promotional strategies. We adopt an individual traveler choice approach to identify and measure the relative importance of factors which influence air travel demand. Travelers' patterns of air travel, perceptions of carrier service, frequent-flyer program membership, and carrier choice behavior are used to estimate models of individual carrier choice. These models indicate the importance of carrier presence in the origin market, carrier service in a city pair market (share of flights), carrier quality of service reflected in ratings by individual travelers, and traveler loyalty reflected in frequent-flyer program membership on carrier choice. The importance of these variables and the specific quantitative relationship estimated, can be used to estimate the market share impact of service design, pricing, marketing, and promotional changes. The empirical results of this study demonstrate the dramatic impact of frequent-flyer program participation on carrier choice for individual flights. These effects are particularly strong among the most important air carrier market, the frequent business traveler.     

Game-theoretical models for competition analysis in a new emerging liner container shipping market

This paper develops three game-theoretical models to analyze shipping competition between two carriers in a new emerging liner container shipping market. The behavior of each carrier is characterized by an optimization model with the objective to maximize his payoff by setting optimal freight rate and shipping deployment (a combination of service frequency and ship capacity setting). The market share for each carrier is determined by the Logit-based discrete choice model. Three competitive game strategic interactions are further investigated, namely, Nash game, Stackelberg game and deterrence by taking account of the economies of scale of the ship capacity settings. Three corresponding competition models with discrete pure strategy are formulated as the variables in shipment deployment are indivisible and the pricing adjustment is step-wise in practice. A ɛ -approximate equilibrium and related numerical solution algorithm are proposed to analyze the effect of Nash equilibrium. Finally, the developed models are numerically evaluated by a case study. The case study shows that, with increasing container demand in the market, expanding ship capacity setting is preferable due to its low marginal cost. Furthermore, Stackelberg equilibrium is a prevailing strategy in most market situations since it makes players attain more benefits from the accommodating market. Moreover, the deterrence effects largely depend on the deterrence objective. An aggressive deterrence strategy may make potential monopolist suffer large benefit loss and an easing strategy has little deterrence effect.     

Traveler delay costs and value of time with trip chains, flexible activity scheduling and information

The delay costs of traffic disruptions and congestion and the value of travel time reliability are typically evaluated using single trip scheduling models, which treat the trip in isolation of previous and subsequent trips and activities. In practice, however, when activity scheduling to some extent is flexible, the impact of delay on one trip will depend on the actual and predicted travel time on itself as well as other trips, which is important to consider for long-lasting disturbances and when assessing the value of travel information. In this paper we extend the single trip approach into a two trips chain and activity scheduling model. Preferences are represented as marginal activity utility functions that take scheduling flexibility into account. We analytically derive trip timing optimality conditions, the value of travel time and schedule adjustments in response to travel time increases. We show how the single trip models are special cases of the present model and can be generalized to a setting with trip chains and flexible scheduling. We investigate numerically how the delay cost depends on the delay duration and its distribution on different trips during the day, the accuracy of delay prediction and travel information, and the scheduling flexibility of work hours. The extension of the model framework to more complex schedules is discussed.     

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.     

Airline market share and customer service quality: a reference-dependent model

Traditional models that explain the nature of the relationship between customer service quality and airline demand assume that the relationship can be approximated by using smooth or differentiable curves. Suzuki and Tyworth, however, recently argued that this assumption may not be valid, and that, if it is invalid, the model performance can be improved by using non-smooth functions to represent the relationship (Suzuki, Y., Tyworth, J.E., 1998. A theoretical framework for modeling sales-service relationships in the transportation industry. Transportation Research E 34 (2), 87–100). We use their framework to develop a model that represents the relationship between service quality and market share in the airline industry and then empirically compare its performance with conventional airline demand models. The results indicate that the relationship is characterized by a non-smooth curve and that our model provides a significantly better goodness of fit than other conventional demand models.     

High-speed rail and air transport competition and cooperation: A vertical differentiation approach

This paper considers vertical differentiation between air transport and high-speed rail (HSR) with different ranges of travel distance to analyze the air-HSR competition effects on fares, traffic volumes and welfare, as well as the conditions under which air-HSR cooperation is welfare-enhancing. The analysis is conducted in a hub-and-spoke network with a network carrier, an HSR operator, and a spoke airline, taking into account potential hub airport capacity constraint. We find that air-HSR competition in the connecting market may result in the network airline charging an excessively high price in the HSR-inaccessible market. This effect is present even when the HSR-inaccessible route is a duopoly-airline market. On the other hand, air-HSR cooperation increases fares in the connecting market, and an improvement in rail speed or air-HSR connecting time reduces airfare on the routes where HSR and the airline compete. When the airline cannot serve all the markets due to limited hub airport capacity, it would withdraw from the market in which it has less competitive advantage over HSR. Finally, air-HSR cooperation is more likely to be welfare-improving when the hub airport is capacity constrained, and when either air transport or HSR exhibits strong economies of traffic density.     

Network-wide adaptive tolling for connected and automated vehicles

This article proposes Δ-tolling, a simple adaptive pricing scheme which only requires travel time observations and two tuning parameters. These tolls are applied throughout a road network, and can be updated as frequently as travel time observations are made. Notably, Δ-tolling does not require any details of the traffic flow or travel demand models other than travel time observations, rendering it easy to apply in real-time. The flexibility of this tolling scheme is demonstrated in three specific traffic modeling contexts with varying traffic flow and user behavior assumptions: a day-to-day pricing model using static network equilibrium with link delay functions; a within-day adaptive pricing model using the cell transmission model and dynamic routing of vehicles; and a microsimulation of reservation-based intersection control for connected and autonomous vehicles with myopic routing. In all cases, Δ-tolling produces significant benefits over the no-toll case, measured in terms of average travel time and social welfare, while only requiring two parameters to be tuned. Some optimality results are also given for the special case of the static network equilibrium model with BPR-style delay functions.     

Modelling public transport on‐board congestion: comparing schedule‐based and agent‐based assignment approaches and their implications

Transit systems are subject to congestion that influences system performance and level of service. The evaluation of measures to relieve congestion requires models that can capture their network effects and passengers' adaptation. In particular, on‐board congestion leads to an increase of crowding discomfort and denied boarding and a decrease in service reliability. This study performs a systematic comparison of alternative approaches to modelling on‐board congestion in transit networks. In particular, the congestion‐related functionalities of a schedule‐based model and an agent‐based transit assignment model are investigated, by comparing VISUM and BusMezzo, respectively. The theoretical background, modelling principles and implementation details of the alternative models are examined and demonstrated by testing various operational scenarios for an example network. The results suggest that differences in modelling passenger arrival process, choice‐set generation and route choice model yield systematically different passenger loads. The schedule‐based model is insensitive to a uniform increase in demand or decrease in capacity when caused by either vehicle capacity or service frequency reduction. In contrast, nominal travel times increase in the agent‐based model as demand increases or capacity decreases. The marginal increase in travel time increases as the network becomes more saturated. Whilst none of the existing models capture the full range of congestion effects and related behavioural responses, existing models can support different planning decisions. Copyright © 2016 John Wiley & Sons, Ltd.     

Hub location in the South-Atlantic airline market: A spatial competition game

The paper analyzes the airlines’ hub location problem through a spatial competition game played in two stages. First, airlines sequentially choose the location of their hub and second, they compete offering direct or connecting services between each city-pair. Different outcomes in the first stage will affect competition in the second, and as a consequence, the market share that airlines can obtain.Given actual demand patterns, results of the model are applied to the South-Atlantic airline market. We study the subgame perfect equilibriums obtained as a result of competition in each city-pair to anticipate where airlines will probably locate their hubs once an “open skies” policy is adopted in this market.     

Modeling commuting mode choice jointly with work start time and work duration

This paper presents a joint trivariate discrete-continuous-continuous model for commuters’ mode choice, work start time and work duration. The model is designed to capture correlations among random components influencing these decisions. For empirical investigation, the model is estimated using a data set collected in the Greater Toronto Area (GTA) in 2001. Considering the fact that work duration involves medium- to long-term decision making compared to short-term activity scheduling decisions, work duration is considered endogenous to work start time decisions. The empirical model reveals many behavioral details of commuters’ mode choice, work start time and duration decisions. The primary objective of the model is to predict workers’ work schedules according to mode choice, which is considered a skeletal activity schedule in activity-based travel demand models. However, the empirical model reveals many behavioral details of workers’ mode choices and work scheduling. Independent application of the model for travel demand management policy evaluations is also promising, as it provides better value in terms of travel time estimates.     

Activity-based market equilibrium for capacitated multimodal transport systems

Empirical studies have shown that demand for multimodal transport systems is highly correlated with activity schedules of individuals. Nonetheless, existing analytical equilibrium models of multimodal systems have only considered trip-based demand. We propose a new market equilibrium model that is sensitive to traveler activity schedules and system capacities. The model is based on a constrained mixed logit model of activity schedule choice, where each schedule in the choice set is generated with a multimodal extension of the household activity pattern problem. The extension explicitly accounts for both passenger choices of activity participation and multimodal choices like public transit, walking, and vehicle parking. The market equilibrium is achieved with Lagrangian relaxation to determine the optimal dual price of the capacity constraint, and a method of successive averages with column generation finds an efficient choice set of activity schedules to assign flows over the dynamic network load capacities. An example illustrates the model and algorithm, effects similar to Vickrey’s morning commute model can be observed as a special case. A case study of the Oakville Go Transit station access “last mile” problem in the Greater Toronto Area is conducted with 166 survey samples reflecting 3680 individuals. Results suggest that a $10 fixed parking fee at Oakville station would lead to a reduction of access auto share from 54.8% to 49.5%, an increase in access transit share from 20.7% to 25.9%, and a disutility increase of 11% for the of single-activity residents of Oakville.     

Integrated airline planning: Robust update of scheduling and fleet balancing under demand uncertainty

The airline schedule planning problem is defined as the sequence of decisions that need to be made to obtain a fully operational flight schedule. Historically, the airline scheduling problem has been sequentially solved. However, there have already been many attempts in order to obtain airline schedules in an integrated way. But due to tractability issues it is nowadays impossible to determine a fully operative and optimal schedule with an integrated model which accounts for all the key airline related aspects such as competitive effects, stochastic demand figures and uncertain operating conditions. Airlines usually develop base schedules, which are obtained much time in advance to the day of operations and not accounting for all the related uncertainty. This paper proposes a mathematical model in order to update base schedules in terms of timetable and fleet assignments while considering stochastic demand figures and uncertain operating conditions, and where robust itineraries are introduced in order to ameliorate miss-connected passengers. The proposed model leads to a large-scale problem which is difficult to be solved. Therefore, a novel improved and accelerated Benders decomposition approach is proposed. The analytical work is supported with case studies involving the Spanish legacy airline, IBERIA. The presented approach shows that the number of miss-connected passengers may be reduced when robust planning is applied.     

Modeling the competition among air-travel itinerary shares: GEV model development

This study reports the results of aggregate air-travel itinerary share models estimated using data from all East West markets in the United States and Canada. These models predict airline ridership at the itinerary level and aid carriers in long and intermediate term decision-making. Official and comprehensive schedule and bookings data is used to estimate generalized extreme value models capturing the inter-itinerary competition dynamic along three dimensions: time of day, carrier and level-of-service (nonstop, direct, single-connect, double-connect). Models incorporate one, two or three of these dimensions simultaneously. Model structures considered include multinomial logit and variations of the nested logit model (two-level nested logit, two-level weighted nested logit, three-level nested logit, three-level weighted nested logit and nested weighted nested logit). Independent variables for the models measure various itinerary service characteristics such as level-of-service, connection quality, carrier attributes, aircraft type, and departure time. Additionally, the advanced models yield inverse logsum and/or weight parameter estimates capturing the underlying competitive dynamic among air-travel itineraries. The results are intuitive, and the advanced models outperform the more basic specifications with regard to statistical tests and behavioral interpretations, giving insight into the competitive dynamic of air-carrier itineraries.     

Integrated modeling of high performance passenger and freight train planning on shared-use corridors in the US

This paper studies strategic level train planning for high performance passenger and freight train operations on shared-use corridors in the US. We develop a hypergraph-based, two-level approach to sequentially minimize passenger and freight costs while scheduling train services. Passenger schedule delay and freight lost demand are explicitly modeled. We explore different solution strategies and conclude that a problem-tailored linearized reformulation yields superior computational performance. Using realistic parameter values, our numerical experiments show that passenger cost due to schedule delay is comparable to in-vehicle travel time cost and rail fare. In most cases, marginal freight cost increase from scheduling more passenger trains is higher than marginal reduction in passenger schedule delay cost. The heterogeneity of train speed reduces the number of freight trains that can run on a corridor. Greater tolerance for delays could reduce lost demand and overall cost on the freight side. The approach developed in the paper could be applied to other scenarios with different parameter values.     

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.     

Flight delays,capacity investment and social welfare under air transport supply-demand equilibrium

This paper analyzes benefits from aviation infrastructure investment under competitive supply-demand equilibrium. The analysis recognizes that, in the air transportation system where economies of density is an inherent characteristic, capacity change would trigger a complicated set of adjustment of and interplay among passenger demand, air fare, flight frequency, aircraft size, and flight delays, leading to an equilibrium shift. An analytical model that incorporates these elements is developed. The results from comparative static analysis show that capacity constraint suppresses demand, reduces flight frequency, and increases passenger generalized cost. Our numerical analysis further reveals that, by switching to larger aircraft size, airlines manage to offset part of the delay effect on unit operating cost, and charge passengers lower fare. With higher capacity, airlines tend to raise both fare and frequency while decreasing aircraft size. More demand emerges in the market, with reduced generalized cost for each traveler. The marginal benefit brought by capacity expansion diminishes as the capacity-demand imbalance becomes less severe. Existing passengers in the market receive most of the benefit, followed by airlines. The welfare gains from induced demand are much smaller. The equilibrium approach yields more plausible investment benefit estimates than does the conventional method. In particular, when forecasting future demand the equilibrium approach is capable of preventing the occurrence of excessive high delays.     

Airline network choice and market coverage under high-speed rail competition

While the existing literature has focused on the short-term impacts, this paper investigates the long-term impacts of high-speed rail (HSR) competition on airlines. An analytical model is developed to study how an airline may change its network and market coverage when facing HSR competition on trunk routes. We show that prior to HSR competition, an airline is more likely to adopt a fully-connected network and cover fewer fringe markets if the trunk market is large. Under HSR competition, the airline will, for a given network structure, have a greater incentive to cover more fringe (regional or foreign) markets if the trunk market is large, or the airline network is close to hub-and-spoke. Further, the airline will, for any given market coverage, move towards a hub-and-spoke network when the trunk market is large, or the number of fringe markets covered by the airline network is large. Both effects are more prominent when the decreasing rate of airline density economies is large. We further show that HSR competition can induce the airline to adopt network structure and market coverage that are closer to the socially optimal ones, thereby suggesting a new source of welfare gain from HSR based on its long-term impacts on airlines. Implications for operators, policy makers and specific countries (such as China) are also discussed.     

The evening commute with cars and transit: Duality results and user equilibrium for the combined morning and evening peaks

This paper extends Vickrey’s (1969) commute problem for commuters wishing to pass a bottleneck for both cars and transit that share finite road capacity. In addition to this more general framework considering two modes, the paper focuses on the evening rush, when commuters travel from work to home. Commuters choose which mode to use and when to travel in order to minimize the generalized cost of their own trips, including queueing delay and penalties for deviation from a preferred schedule of arrival and departure to and from work. The user equilibrium for the isolated morning and evening commutes are shown to be asymmetric because the schedule penalty in the morning is the difference between the departure and wished curves, and the schedule penalty in the evening is the difference between the arrival and wished curves. It is shown that the system optimum in the morning and evening peaks are symmetric because queueing delay is eliminated and the optimal arrival curves are the same as the departure curves.The paper then considers both the morning and evening peaks together for a single mode bottleneck (all cars) with identical travelers that share the same wished times. For a schedule penalty function of the morning departure and evening arrival times that is positive definite and has certain properties, a user equilibrium is shown to exist in which commuters travel in the same order in both peaks. The result is used to illustrate the user equilibrium for two cases: (i) commuters have decoupled schedule preferences in the morning and evening and (ii) commuters must work a fixed shift length but have flexibility when to start. Finally, a special case is considered with cars and transit: commuters have the same wished order in the morning and evening peaks. Commuters must use the same mode in both directions, and the complete user equilibrium solution reveals the number of commuters using cars and transit and the period in the middle of each rush when transit is used.