Air Travel Demand Research Articles

A novel hybrid fuzzy DEA-Fuzzy MADM method for airlines safety evaluation

Safety is a critical element in the air transport industry. Although fatal air accidents are rare compared to other transport industries, the rapid growth in air travel demands has resulted in a growing aviation risk exposure and new challenges in the aviation sector. Although the issue of airline safety is of serious public concern, notably few studies have investigated the safety efficiency of airlines. This paper aims to propose a novel hybrid method using fuzzy data envelopment analysis (DEA) and fuzzy multi-attribute decision making (F-MADM) for ranking the airlines' safety. In this study, fuzzy DEA is utilized to calculate criteria weights, in contrast to the conventional approach of using DEA for measuring the efficiency of alternatives. A ranking of each airline (DMU) on the basis of obtained weights is then assessed using MADM methods. Six MADM methods including Fuzzy SAW, Fuzzy TOPSIS, Fuzzy VIKOR, ARAS-F, COPRAS-F and Fuzzy MULTIMOORA are implemented to rank the alternatives, and finally, the results are compounded with the utility interval technique. This new hybrid method can efficiently overcome the pitfalls of traditional hybrid DEA-MADM models. The method proposed in this study is used to evaluate the safety levels of seven Iranian airlines and to select the safest one.

Do jet fuel price movements help forecast airline fares and the demand for air travel?

ABSTRACTThe paper studies the predictive content of jet fuel prices for the U.S. aviation industry through in-sample and out-of-sample forecasting exercises. Our results suggest the possibility of limited improvements in the predictions of airline fares, and little evidence of predictability from jet fuel prices to measures of air travel demand.

Quantifying the substitutability and complementarity between high-speed rail and air transport

This paper quantifies the substitution and complementary effects of high-speed rail (HSR) on air travel demand in terms of both route traffic and airport enplanement. Employing the difference-in-differences (DID) method, the first part of the analysis measures the effect of new HSR routes on parallel air route traffic with a focus on East Asian regions (Mainland China, Japan, South Korea, and Taiwan). The second part examines the effect of air-HSR integration on passenger enplanement at East Asian airports and compares with that in the Central European market. We find that in general the airport’s access cost (reflected by the distance from central city) has a negative impact on the air traffic. The substitution effects of HSR are the most significant on short- and medium-haul (below 1000 km) air routes while introducing HSR services has encouraged long distance (over 1000 km) air travels in Mainland China. The complementary effect is investigated in the context of air-HSR integration, which has significantly positive impacts on airport enplanement at primary hub airports when fitted with on-site HSR links. The benefit is limited at secondary hubs and regional airports possibly by locations and HSR service frequencies.

Long Term Forecasting of International Air Travel Demand in Nigeria (2018-2028)

This study examines long term forecasting of international air travel demand in Nigeria. Yearly data from 2001 to 2017 were collected from secondary sources. Ordinary Least Square (OLS) regression was used to forecast the ten years (2018 to 2028) demand for international air passenger travel in Nigeria. The demand for international air passenger in Nigeria from year 2001 to 2017 was compared with the forecast. Calculation reveals that the coefficient of determination R2 is 0.815, while the computed reveals that the coefficient of determination R2 is 0.769, this difference can be attributed to approximations to two decimal places for calculated test. The calculated test and computed test reveals that the error term is minimal and the explanation level is high; hence the prediction or forecast is reliable. The forecast for years 2020, 2025 and 2028 are 5,282,453, 6,342,519, and 6,978,559 respectively which are about 48 percent increase, 78 percent increase, and 95 percent increase respectively from demand in year 2017. The forecast of ten years from year 2018 to year 2028 reveals that there will be more increase in the demand for international air passenger travel in Nigeria. The implication of this increment is that existing air transport infrastructures should be upgraded, and new infrastructures should be procured and installed; airport and airline operations should be reviewed and strategized such that they will meet the expectations of airline and airport users. Other concerned business stakeholders should use this data to plan and invest as there is high tendency for profit making.

Scale heterogeneity in discrete choice experiment: An application of generalized mixed logit model in air travel choice

This study explores to what extent scale heterogeneity (i.e., varying standard deviation of the errors across consumers) is important in air travel choice using data from a stated preference discrete choice experiment. We used generalized mixed logit model (GMIXL) that nests scale and taste heterogeneity in the context of air travel ticket choice. We found empirical evidence of the importance of often-neglected scale heterogeneity along with pre-dominant taste heterogeneity. The findings suggests that it is important to account for various forms of heterogeneity with GMIXL to model air travel demand to identify variety of consumer segments, which has implications for airline optimal menu of ticket offerings and pricing strategies.

Determinants of domestic air travel demand in Nigeria: cointegration and causality analysis

Air transportation is an important factor of development as it facilitates movements within a country and connects the country with other parts of the world. This paper examines the causal relationship between economic variables—Gross Domestic Product per capita (GDP), index of agricultural production, index of manufacturing production and consumer price index—and domestic air travel demand in Nigeria. Annual data for the period 1982–2005, autoregressive distributed lag cointegration approach and Granger short- and long-run causality tests are employed. The results indicate that Gross Domestic Product (GDP) and index of manufacturing production are determinants of air travel in the short- and long-run. Air travel increases with economic growth. Short- and long-run uni-directional Granger causality runs from GDP to air travel. The impulse response function indicates that changes in air travel were due to its own shocks and shocks to GDP. Thus, GDP is a crucial factor that influences the growth of air travel. Government and policymakers need to develop local industries, infrastructures and educational institutions that will provide skilled labour as well as improve the relative business and leisure attractiveness of the economy to the global economic environment. Stakeholders need to invest capital in airport expansion and ensure compliance with international safety and environmental standards. Investment in aviation infrastructure facilities is necessary so as to accommodate the projected growth in domestic air travel demand since the country is gradually recovering from economic recession.

Are passengers less willing to pay for flying turboprops? An empirical test of the “turbo aversion hypothesis”

Turboprop airplanes are known for their fuel efficiency on short-haul routes and thus naturally have a competitive advantage over jets in regional air transport. In Brazil, however, the market share of turboprops has considerably decreased in regional routes since the early 2010s. One possible explanation for this trend is the “turbo aversion hypothesis” (TAH), in which passengers dislike flying in turboprops, making carriers in regional markets more prone to operate either regional or smaller narrow-body jets based on demand-side economics. We empirically test this hypothesis by employing an econometric model of air travel demand in Brazilian regional markets. We find strong evidence rejecting the TAH, suggesting that the cost-side economics of the falling fuel prices apparently fully explains the observed erosion of the turboprop participation in the market.

Visualizing aviation impacts: Modeling current and future flight trajectories with publicly available flight data

As the demand for air travel continues to grow both nationally and internationally, airports seek airfield expansions and new infrastructure to accommodate new aircraft movements. However, airport expansion initiatives – runway extensions and/or new runway construction – directly impact terminal airspace operations. A change in flight paths near the airport affects the population living proximate to the airport, increasing noise levels and exposure to pollutants emitted by low-altitude departures and arrivals. While airspace procedures and their impacts are well-understood by aviation stakeholders, they are often convoluted and technical in nature. To this end, we propose a methodology to visualize terminal airspace trajectories leveraging publicly available data and commonly-used software. The trajectories are extracted via polynomial regression and hyperbolic tangent interpolation is applied to reflect accurate final approach maneuvers. Final visualizations are rendered in ArcGIS, a geographic information system used by many Metropolitan Planning Organizations. These trajectory visualization modules can also be combined with external models that provide noise contour projections and emission level estimations. We present a case study of Chicago O’Hare International Airport (ORD) due to the contentious O’Hare Modernization Program. The resultant interactive and dynamic three-dimensional trajectory airspace maps for ORD rendered via ArcGIS are easy to understand and customize, allowing MPOs to package them into downloadable online modules. MPOs armed with these modules will bridge the critical gap between the technical knowledge presented by authorities touting airport expansions and the residents who are impacted by the expansions.

“Problematizing” carbon emissions from international aviation and the role of alternative jet fuels in meeting ICAO's mid-century aspirational goals

Alternative jet fuels are one of the four mechanisms by the United Nations International Civil Aviation Organization (ICAO) to limit and reduce carbon emissions from international aviation. By using Carol Bacchi's what's the problem represented to be? method of discourse analysis, the objective of this paper was to identify and understand the premises and effects of the problem-solving paradigm underlying ICAO's alternative jet fuel strategy. As a result, three problem representations were identified, from which two out of four underlying assumptions have reinforced ICAO's weak sustainability approach to international aviation's growth and have led to a number of discursive, subjectification and lived effects. The selected method also allowed the authors to identify several options to disrupt those premises in favor of the implementation of more aggressive mitigation and adaptation strategies without constraining air travel demand, including: (i) raising awareness of the environmental impacts of aviation beyond the tailpipe emissions, (ii) improving the understanding of the effects of climate change on the air transport sector, and (iii) reassessing the sectoral approach to the Sustainable Development Goals so as to gain consistency with the aims of the UN 2030 Agenda for Sustainable Development.

Are Passengers Less Willing to Pay for Flying Turboprops? An Empirical Test of the 'Turbo Aversion Hypothesis'

Turboprop airplanes are known for their fuel efficiency on short-haul routes and thus naturally have a competitive advantage over jets in regional air transport. In Brazil, however, the market share of turboprops has considerably decreased in regional routes since the early 2010s. One possible explanation for this trend is the “turbo aversion hypothesis” (TAH), in which passengers dislike flying in turboprops, making carriers in regional markets more prone to operate either regional or smaller narrow-body jets based on demand-side economics. We empirically test this hypothesis by employing an econometric model of air travel demand in Brazilian regional markets. We find strong evidence rejecting the TAH, suggesting that the cost-side economics of the falling fuel prices apparently fully explains the observed erosion of the turboprop participation in the market.

Prediction of air travel demand using a hybrid artificial neural network (ANN) with Bat and Firefly algorithms: a case study

During the past few decades, many researchers have studied the issue of air travel demand in different countries. On the other hand, the development of airports requires considerable space in the vicinity of cities which needs planning and huge investment. However, development of air travel through different airports will be affected by various factors such as population growth and economic development. The purpose of this study is to predict air travel demand in Iran. Data were provided by the Civil Aviation Organization of Islamic Republic of Iran from 2011 to 2015. Collected information includes airports of the country and destination cities all across the country. For this purpose, the artificial neural network (ANN) is used to predict the air travel demand by considering income elasticity and population size in each zone. Evolutionary meta-heuristic algorithms have been implemented in order to improve the performance of ANN. Bat and Firefly algorithms are new meta-heuristic algorithms which have been examined in this study. The results show that the use of these algorithms increases adaptation rate of neural network (NN) prediction with real data. The coefficient of determination increases from 0.2 up to about 0.9 while using the meta-heuristics NN. This represents the high rate of efficiency using this new method.

The implications of high-speed railways on air passenger flows in China

The High-speed Railway (HSR) network in China is the largest in the world, competing intensively with airlines for inter-city travel. Panel data from 2007 to 2013 for 138 routes with HSR-air competition were used to identify the ex-post impacts of the entry of HSR services, the duration of operating HSR services since entry, and the specific impacts of HSR transportation variables such as travel time, frequency, and ticket fares on air passenger flows in China. The findings show that the entry of new HSR services in general leads to a 27% reduction in air travel demand. After two years of operating HSR services, however, the negative impact of HSR services on air passenger flows tends to further increase. The variations of the frequency in the temporal dimension and the travel time in the spatial dimension significantly affect air passenger flows. Neither in the temporal nor spatial dimensions are HSR fares strongly related to air passenger flows in China, due to the government regulation of HSR ticket prices during the period of analysis. The impacts of different transportation variables found in this paper are valuable to consider by operational HSR companies in terms of scheduling and planning of new routes to increase their competitiveness relative to airlines.

Investigating the impact of catchment areas of airports on estimating air travel demand: A case study of regional Western Australia

The aviation industry in Western Australia (WA) plays a vital role in the economic and social development of the state. However, accurate forecasts for passenger movements are not available to policy makers due to lack of relevant air travel demand information. The objective of this study is to estimate the domestic air passenger seat numbers between airport-pairs based on online flight information in regional WA based on a gravity model using Poisson pseudo-maximum likelihood estimation (PPML). Particularly, we aim to investigate the impact of distance, airfare, catchment areas, population, tourism and mining sector on forecasting air passenger seat numbers in order to inform and guide policy making.This research collected appropriate data and produced valid models that represent air passenger seat numbers offered on regular public transport (RPT) air services in regional WA. The models consider both geographic and service-related variables, such as the catchment area of airports, population and number of tourists in the airport's catchment area. Two kinds of airport catchment areas are generated in this study, based on Thiessen polygon and two and half hours' driving distance. The Thiessen polygon catchment areas cover the whole WA regions, while the 2.5 h's driving catchment area covers only 32 percent of the WA region. The size of the catchment area can affect the magnitude of factors, and therefore influence the modelling results. When deciding the catchment area for the study, it is important to take the spatial distribution of factors into considerations. For both Thiessen polygon and two and half hours' driving distance catchment area, the model results illustrate that distance between airports, airfare of the flight, population of the origin airport's catchment area and the number of operating mine sites of the destination airport's catchment area are significantly correlated with domestic air travel seat capacity provided. Given the guidance from policy documents and policy makers, the results will improve the understanding of the key parameters of regional passenger aviation services and help to guide policy makers considering regional passenger aviation issues. The outcome of this study would be useful for and guide policy development.

Tourist Aviation Emissions: A Problem of Collective Action

While transportation currently accounts for 23% of total global energy-related CO2 emissions, transport emissions are projected to double by 2050, driven significantly by continued high growth in global passenger demand for air travel. Addressing high growth in aviation emissions is critical to climate stabilization. Currently we rely on individual decisions to forego air travel as the means of reducing these high-risk emissions. In this paper we argue that encouraging voluntary responses to such risks cannot succeed because of the nature of human reason and the structure of the problem itself. We use decision-making theory to explore why individuals have been generally unwilling or unable to act upon these risks, and collective action theory to illustrate the futility of relying on uncoordinated actors in such cases. Participation in the high-carbon air travel regime is a social convention, and transition from social conventions requires coordination among players. Our theoretical discussions lead us to conclude that it is our moral duty to promote coordinated collective action, via national or global policy mechanisms, to address tourist aviation emissions. We offer various avenues of future research to advance this moral duty.

미관찰 지역 특성을 고려한 내국인 국제선 항공수요 추정 모형

미관찰 지역 특성을 고려한 내국인 국제선 항공수요 추정 모형

Immigration and inbound air travel demand in Canada

This paper investigates the impact of immigration on inbound air transport demand in Canada. Air travelers to Canada from 68 countries were regressed against the number of Canadian residents born overseas from 1990 to 2015 with 5-year intervals. The regressions were controlled by population, GDP per capita of country of origin, geographical distance between the major airports and visa requirements. The panel data fixed and random effects models both support the hypothesis that immigration is a major determinant of inbound arrivals in Canada. This is especially true for new immigrants and immigrants from China.

Evidence of directional price discrimination in the U.S. airline industry

This paper explores possible determinants that may affect an airline’s decision to charge passengers different roundtrip fares depending on trip origin, a case of directional price discrimination. Such fare differences cannot be the result of differences in cost, as the cost of flying a roundtrip passenger does not significantly differ depending on direction. It is argued that directional fare differences result from airlines recognizing that passenger price elasticities differ between route endpoints. A price discriminating airline will then charge a higher roundtrip fare at the endpoint where the passenger price elasticity of demand is comparatively lower. Evidence is found suggesting that airlines do use differences in income to price discriminate when setting roundtrip fares. Fares are found to be $0.18-$0.43 higher on average for each $1000 difference in average per capita income between origin and destination metro areas. This finding is sensible assuming that higher incomes reduce the price elasticity of demand for air travel, with richer passengers being less sensitive to the cost of travel.

Socio-economic mobility and air passenger demand in the U.S.

In this research, we examine how socio-economic mobility affects domestic passenger enplanement volumes at U.S. airports. In addition to metrics such as income and population levels, socio-economic mobility has been identified as an important characteristic of the socio-economic fabric of market areas. As such, it is a potentially significant determinant of demand for goods and services, including air travel. Drawing on data from the U.S. domestic airline industry and newly available measures of socio-economic mobility, we empirically discern how the latter affects both yields and passenger counts at U.S. airports. The results offer compelling evidence that greater mobility is associated with lower air fares. In addition, our findings suggest that greater passenger volumes are also lower in areas marked by higher socio-economic mobility, all else equal. Collectively, our results document the significance of socio-economic mobility as a determinant of air travel demand and thereby highlight the importance of considering it in the context of forecasting, demand management and, ultimately, infrastructure planning.

Determinants of air travel demand: The role of low-cost carriers, ethnic links and aviation-dependent employment

This paper presents a comprehensive gravity model in which the most important determinants for air travel demand have been identified using a two-stage least squares technique. Besides including the standard demand factors like GDP, population and tourism, the effects of other determinants such as domestic traffic, low-cost carrier (LCC) activity and public service obligations are also estimated. The profound contribution of the paper lies in the inclusion of two innovative variables in the estimations: ethnic links and aviation-dependent employment. The econometric results show that both ethnic links between countries and the share of aviation-dependent employment increase passenger demand. Moreover, the results confirm that LCC presence leads to a significant increase in passenger demand, particularly on routes where Europe’s largest LCCs, Ryanair and easyJet, are active.

Modelling of queuing process at airport check-in system: a case study of Manchester and Leeds-Bradford airports

This study built a Simulation Model (SM) using SimEvents toolbox in MATLAB for implementing Analytical Models (AM) of queuing process at airport check - in system. Air travel demand data for Manchester and Leeds - Bradford airports in 2014 were adopted for validation of the model. There was no statistical differenc e between utilisation factor (UF) and service times of AM and SM outputs. Differences in AM and SM outputs for average queue length, average waiting time on queue and average number of arrivals and throughputs were attributed to variations in discrete time events considered by SM in contrary to the AM which assumed constant values for the process. The SM exhibited stochastic behaviour which actually depicts reality hence produces more reliable results. Stochastic analysis methods are therefore recommended for queuing analysis to achieve accurate results. The SM is therefore recommended to give Airport managers prior knowledge of system performance for planning and improved level of service (LOS) at airports. Key words : Airport check - in system , discrete tim e events, analytical models, simulation model, SimEvents toolbox