A passenger demand model for air transportation in a hub-and-spoke network

This paper develops an air passenger model that deals with city-pair demand generation and demand assignment in a single framework. Using publicly available and regularly collected panel data, the model captures both time series and cross-sectional variation of air travel demand. The empirical analysis finds that pattern of correlations among alternatives can be described by a three-level nested logit model. Fare, frequency, flight time, direct routing, on-time performance, income, and market distance have significantly effects on air demand. Correcting for the problem of endogenous air fares using instrumental variables yields more plausible estimates of price sensitivity and value of time.     

Border effects for domestic and international Canadian passenger air travel

An augmented gravity model of passenger air travel between five Canadian airports and destinations within and without of Canada reveals a substantial border effect. After controlling for GDP, populations and distance, the number of seats offered on domestic routes is about six times the number on international flights. This result is consistent with the border effects found in studies of international merchandise trade.     

Willingness to pay for safety improvements in passenger air travel

The risk of being involved in an airplane accident is largely ignored in air passengers’ choice models. The reason presumably is that it is hard to operationalize, because objective safety indicators often involve extremely low probabilities that are hard to grasp and interpret by passengers. In this paper, we propose an operationalization that is based on the perception of safety, which is easy to understand and resonates that perceptions often influence decisions stronger than objective variables. We conceptualize that passengers form a safety perception score of a particular flight based on their perception of airline and route attributes and that this score in turn is traded-off against other flight attributes, such as ticket costs, to arrive at a flight choice. In line with this conceptualization, two stated preference experiments are conducted. In a first experiment, combinations of airline and route attributes are evaluated in terms of safety that is captured on a rating scale. In a second experiment, safety perception is treated as an attribute and traded-off against other flight attributes to arrive at a flight choice. The paper presents the results of a regression and a Panel Mixed Logit model estimated from responses obtained from a convenience sample of 161 air passengers recruited in the Netherlands. The results of both models are then combined to calculate the willingness to pay values for improvements made to a range of airline and route attributes, taking into account socio-demographic variables and psychological traits. As expected, the results indicate that the willingness to pay for improving safety decreases with higher initial safety levels.     

Elasticities of demand for leisure air travel: A system modelling approach

In this study, the UK outbound demand for leisure air travel has been examined using a demand system which takes into account the ways in which the expenditure on air fares interacts with both the expenditure on non-fare components of travel abroad and with expenditure on domestic leisure. The findings suggest that there is a strong link between total consumer expenditure and expenditure on air travel with the expenditure elasticity greater than one but that, considered in aggregate, the demand for air travel is moderately inelastic with respect to air fares alone. However, the findings also show that interactions between air travel expenditure, other costs of travel abroad, as well as expenditure on leisure activities in the UK, involve sizeable cross-price elasticities.     

Forecasting air passenger demand with a new hybrid ensemble approach

Analyzing and modeling passenger demand dynamic, which has important implications on the management and the operation in the entire aviation industry, are deemed to be a tough challenge. Air passenger demand, however, exhibits consistently complex non-linearity and non-stationarity. To capture more precisely the aforementioned complex behavior, this paper proposes a hybrid approach VMD-ARMA/KELM-KELM for the short-term forecasting, which consists of variational mode decomposition (VMD), autoregressive moving average model (ARMA) and kernel extreme learning machine (KELM). First, VMD is adopted to decompose the original data into several mode functions so as to reduce their complexity. Then, the unit root test (ADF test) is employed to classify all the modes into the stable and unstable series. Meanwhile, the ARMA and the KELM models are used to forecast both the stationary and non-stationary components, respectively. Lastly, the final result is integrated by another KELM model incorporating the forecasting results of all components. In order to prove and verify the feasibility and robustness of the proposed approach, the passenger demands of Beijing, Guangzhou and Pudong airports are introduced to test the performance. Also, the experimental results show that the novel approach does have a more obviously advantage than other benchmark models regarding both accuracy and robustness analysis. Therefore, this approach can be utilized as a convincing tool for the air passenger demand forecasting.     

Determinants of air travel demand in Middle Income Countries

The aim of this paper is to calculate the effects of air travel demand determinants in Middle Income Countries (MICs). Through static and dynamic panel data models from 32 countries during the period from 2002 to 2008, we found that the income elasticity is the most important determinant and that it is slightly higher than one. Income growth multiplied by income elasticity accounts for 75 percent of total passenger growth. Public policies such as an open skies agreements with the European Union have a positive effect on passenger growth, whereas structural changes, such as Low Cost Carrier (LCC) growth, have a marginal effect.     

Dynamic analysis of air travel demand in competitive island markets

This paper describes a dynamic demand model, referred to as dynamic abstract mode model, for estimating both the short- and long-term responses of air passengers to changes in relative air-sea travel cost components in competitive markets. The implementation of the model in the competitive market of Aegean islands in Greece demonstrates the importance of considering the past volumes of air passengers and relative travel cost components to explain current air travel demand.     

Freight transportation demand elasticities: a geographic multimodal transportation network analysis

This paper presents direct and cross-elasticity estimates of the demands for three freight transportation modes: rail, road and inland waterways. They are computed for 10 different categories of goods with a detailed multimodal network model of Belgian freight transports. The model, which minimises the generalised cost of transportation tasks defined by O-D matrices, assigns traffic flows to the different modes, transport means and routes. Successive simulations with different relative costs permit the computation of specific arc-elasticities. In contrast with the usual methodologies, the present methodology is not based on a statistical analysis of disaggregate data on actual modal choices and transport tariffs. This is a particularly useful feature since such data are mostly not available for freight transports in Europe. Furthermore, it fully takes into account the detailed characteristics of the network, all available routes and combinations of modes, as well as the specific localisation of activities within the network. Its estimates are compared with previously published estimates, and, in particular, with Abdelwahab's results published (1998) in this journal.     

What is driving the continued growth in demand for air travel? Customer value of air transport

This article introduces the concept of customer value as a driving factor for continued growth in demand and eliminates a subversion of the customer-value theory for the air-transport industry. This theoretical framework includes risk as subcomponents of perceived relative benefits as well as perceived relative costs. Based on data of a survey the weight of the different influential factors is evaluated. Management implications as well as methodological learning for the measurement of customer value are derived. The key conclusion thereby is that a stronger focus on customer value will be a key challenge of airline management. Important developments take place at the lower and upper end of the price and quality ranges. Thereby the orientation should be directed by the real, often hidden and not only to the stated preferences of customers.     

The implications of environmental costs on air passenger demand for different airline business models

Various environmental measures, including both regulations and fiscal instruments, have been used at airports globally to reduce the impacts of aircraft noise as well as aircraft engine emissions. Internationally, it is recognized that the costs of environmental and social externalities of air transport must be internalized and paid for by the aviation industry and its users. The use of noise related charges or taxes, which theoretically should be based on their respective social costs, has been proved to be effective at some European airports. This research aims to investigate the impacts of environmental costs, through environmental charges, on air passenger demand for different airline business models. The paper presents the mathematical models measuring the social costs of aircraft noise and engine emissions as a basis for setting up environmental charges. Six intra-European short-haul routes in two city pairs, namely London–Amsterdam and London–Paris, are selected for the empirical analysis. The environmental charges are then hypothetically applied to airlines with two different business models, full service carriers (British Airways and Air France-KLM) and low cost airlines (EasyJet). The results show that the potential percentages of demand reduction for both leisure and business passengers would be higher for Easyjet's markets, although with less environmental cost per passenger.     

Impact analysis of September 11 on air travel demand in the USA

This study uses an intervention model to look at the impact of the September 11, 2001 terrorist attack on air transport passenger demand in the US. The result showed that both domestic and international air traffic was significantly impacted for 1 and 2 months, respectively. The impact pattern was thus abrupt and temporary, instead of gradual and permanent. The approach also provides better forecasts than the seasonal ARIMA benchmark.     

Predicting the impact of Trans Java Toll Roads on demand for intercity air travel in Indonesia

This paper aims to explore the factors influencing a potential air passenger shift to autos due to the completion of the Trans Java Toll Road and an increase in airfares. The study focuses on intercity trips for nonbusiness purposes. A face-to-face interview survey of 751 air passengers was conducted in three main airports on Java Island, Indonesia. Both the theory of planned behavior and the discrete choice model were applied to understand the factors for influencing toll road use among air passengers. The empirical results reveal that psychological factors, consisting of attitudes, subjective norms, and perceived moral obligations significantly influenced intentions to use the toll road. Meanwhile, perceived control of external resources was essential for airline passengers in their intention to use toll roads. Sociodemographic factors such as age, gender, income, frequency of airplane use, travel time, and cost also significantly influenced the decision to drive. Female, older passengers, high-income passengers, and frequent flyers were more likely to continue flying. The finding confirms that the Trans Java Toll Road affected a decline in air demand on Java Island. However, traveling with family members, rather than airfare hikes, became a more substantial reason for air passengers to switch to driving the toll roads. This research found that air passengers were inelastic related to changes in travel time, while 6% were willing to switch due to airfare increases of 10%.     

The impact of carbon emission fees on passenger demand and air fares: A game theoretic approach

The implementation of an environmental market-based measure on U.S. aviation industry is studied. Under this policy, each airline pays a carbon fee for the carbon dioxide emissions it generates. The impact on ticket prices and corresponding market shares is investigated via the joint estimation of an air travel demand model and an airlines' behavior model. In the demand model, aggregate air traffic data is used to determine the marginal effects of flight attributes that are specific to itinerary, airline and airport on market share. The airline's behavior model incorporates the carbon fee in the airline marginal cost. After the implementation of the carbon policy, the increased cost forces airlines to adjust ticket prices in order to maximize profits. The results obtained by the proposed model indicate a moderate price increase which strongly depends on the per tonne carbon price. Air travel demand falls from 2.4% to 21% depending on the carbon price level.     

An airport operations proposal for a pandemic-free air travel

The aviation industry needs to work on the resilience of air travel against health threats and regain passenger trust. This paper proposes a pandemic-free travel concept based on creating an infectious diseases free zone in the airport terminal building through screening of passengers, crews and airport workers. This research shows that infectious disease detection methods applicable at the airport could be available in a short timeframe, at affordable cost and in scale. The potential location of passenger health screening, facilitation requirements, health responsibilities delegation and appropriate usage of industry standards for regulations are key elements to a potential implementation that would be phased and long term.     

Income and distance elasticities of values of travel time savings: New Swiss results

This paper presents the findings of a study looking into the valuation of travel time savings (VTTS) in Switzerland, across modes as well as across purpose groups. The study makes several departures from the usual practice in VTTS studies, with the main one being a direct representation of the income and distance elasticity of the VTTS measures. Here, important gains in model performance and significantly different results are obtained through this approach. Additionally, the analysis shows that the estimation of robust coefficients for congested car travel time is hampered by the low share of congested time in the overall travel time, and the use of an additional rate-of-congestion coefficient, in addition to a generic car travel time coefficient, is preferable. Finally, the analysis demonstrates that the population mean of the indicators calculated is quite different from the sample means and presents methods to calculate those, along with the associated variances. These variances are of great interest as they allow the generation of confidence intervals, which can be extremely useful in cost-benefit analyses.     

Transit accessibility for commuters considering the demand elasticities of distance and transfer

In this paper, a “by transit accessibility (BTA)” measure to evaluate the impacts of travel distance and transfer tolerance on the convenience of commuting by transit on a regional scale is proposed. Considering the spatiotemporal factors for commuting efficiency evaluation, the timetable-dependent passenger carrying capacity of the transit station and the time-varying passenger demand at originating sites have been formulated into the BTA model. Moreover, the proposed BTA measure could reflect the commuting trip demand elasticity, which is caused by travel distance and transfer tolerance. In the meantime, this BTA measure can provide an important basis for transit timetable adjustment in the study area during different time periods. The proposed measure is tested on a small transit network to display its function, and finally, it is applied to an empirical case to draw practical findings.     

Travel-time reliability impacts on railway passenger demand: a revealed preference analysis

We study the impact of travel-time reliability on trips made by railway passengers. Unlike most of the studies in this area, which make use of stated preference survey data, we use a revealed preference data set obtained by measuring the railway reliability and the number of season-ticket holders on the Dutch railway network. We make use of six travel-time reliability indicators, including the standard deviation and the 80th minus the 50th percentile of travel time. Our results indicate that the 80th minus the 50th percentile indicator best explains the fluctuations in the number of season-ticket holders. A 10% improvement of this indicator results in a 1.47% increase in the number of season-ticket holders.     

Airline demand distributions: passenger revenue management and spill

Both revenue management and airline schedule optimization need to characterize the distribution of likely demand outcomes. Sources have proposed both Gamma and Normal shapes for these distributions. Data suggests that a model combining both distributions is appropriate. The model explains when the Gamma shape will dominate and when the Normal will determine the shape. One consequence of this understanding is that Gamma shapes are probably better for revenue management and Normal for spill modeling. However, it takes a compound process combining the two to generate all the observed characteristics of various cases.     

A literature review and citation analyses of air travel demand studies published between 2010 and 2020

Accurate forecasting of air travel demand is vital for the resource planning of the air transportation industry. Therefore, identifying contributing factors and understanding the effect of these factors in causing the variation of air travel demand have been one of the key focus areas in air transportation research. This article reviews 87 air travel demand studies published from 2010 to 2020 and summarizes these studies using their input data and primary analytical methods. We also devise and conduct three citation analyses to further explore the relationships among the reviewed studies. Our review finds that a typical empirical study of air travel demand analysis would focus on the demand at the national level, employ time-series data concerning socio-economic and airline operational factors and use time-series based methods to estimate the relationship among the selected time-series. These studies are mostly applying existing analytical frameworks to specific problems rather than developing original methods, therefore their relationship to each other is parallel rather than sequential. A small number of references are frequently cited by the reviewed studies primarily because of their methodological contribution to time-series analysis. A common limitation of existing literature is that very few reviewed studies provide validation of their analyses. In addition, methods that are not regression or time-series based have very limited application in this area so far, so are the non-convention data such as mobility data or social media data. Besides providing a systematic summary of recent publications in a specific field, this review uses a relatively objective and replicable framework to compare and link studies by their references, which can be visualized by the figures included in this review. This review is expected to benefit future researchers that are interested in either air transportation or the application of time-series forecasting in an applied domain.     

Testing the differentiated impact of the COVID-19 pandemic on air travel demand considering social inclusion

The economic downturn and the air travel crisis triggered by the recent coronavirus pandemic pose a substantial threat to the new consumer class of many emerging economies. In Brazil, considerable improvements in social inclusion have fostered the emergence of hundreds of thousands of first-time fliers over the past decades. We apply a two-step regression methodology in which the first step consists of identifying air transport markets characterized by greater social inclusion, using indicators of the local economies’ income distribution, credit availability, and access to the Internet. In the second step, we inspect the drivers of the plunge in air travel demand since the pandemic began, differentiating markets by their predicted social inclusion intensity. After controlling for potential endogeneity stemming from the spread of COVID-19 through air travel, our results suggest that short and low-density routes are among the most impacted airline markets and that business-oriented routes are more impacted than leisure ones. Finally, we estimate that a market with 1% higher social inclusion is associated with a 0.153%–0.166% more pronounced decline in demand during the pandemic. Therefore, markets that have benefited from greater social inclusion in the country may be the most vulnerable to the current crisis.