A study on passengers' airport choice behavior using hybrid choice model: A case study of Seoul metropolitan area,South Korea

Improving explanatory power is significantly important to understand variables that affect attitudes and perceptions in the decision process. This paper estimates not only tangible attributes but also intangible perceptions and attitudes using a hybrid-choice model to study air passengers' flight choice behavior. The empirical study was conducted for the choice behavior of air passengers at Seoul Metropolitan Area, South Korea. The analysis uses a two-level Nested Logit model in order to examine which factors have more effect on passengers’ choice of airport and airline simultaneously by using airport and airline choice attributes. The study also estimated the parameters in the equations relating the latent variable by using Structural Equation Model (SEM). The results indicate that the models with latent variables have improved Goodness-of-Fit when compared to classical discrete choice models and effectively capture psychological factors that affect choice behavior of passengers.     

Topological evolution of a metropolitan rail transport network: The case of Stockholm

The structure of transport networks is the outcome of a large number of infrastructure investment decisions taken over a long time span. Network indicators are widely used for characterizing transport network topology and its performance as well as provide insights on possible developments. Little is known however on how rail bound public transport networks and their network indicators have evolved into their current form. This study conducts a longitudinal analysis of the topological evolution of a multimodal rail network by investigating the dynamics of its topology for the case of Stockholm in 1950–2025. The starting year marks the opening of the metro system while the end year is set to mark the completion of the current development plan. Based on a compilation of network topology and service properties, a year-on-year analysis of changes in global network efficiency and directness as well as local nodal centrality were conducted. Changes in network topology exhibit smooth long-term technological and spatial trends as well as the signature of top-down planning interventions. Stockholm rail network evolution is characterized by contraction and stagnation periods followed by network extensions and is currently undergoing a considerable densification, marking a shift from peripheral attachment to preferential attachment.     

Determinants of transport mode choice in metropolitan areas the case of the metropolitan area of the Valley of Mexico

The following paper examines the determinants of transport mode choice for trips in the Metropolitan Area of the Mexican Valley. Using a data set from the Mexican household travel survey (Encuesta Origen - Destino) conducted in 2017 and multinomial logistic regression, the influence of transportation supply, spatial characteristics and socio-economic factors on individual mode choice is estimated. To our knowledge, this is the first analysis of mobility behaviour in the Metropolitan Area of the Mexican Valley with this newly developed data set.The main findings show that a better Mass Rapid Transit infrastructure is not consistently positively associated with the likelihood of using this service. While a better road infrastructure is promoting the use of Mass Rapid Transit services over driving, it is negatively linked with the likelihood of walking and bicycling. These slow modes are mainly interfered with the distance to the city centre: the further away from the centre, the higher the likelihood of walking and bicycling instead of using the car.With respect to socio-economic characteristics of individuals, women and the young found to have a higher likelihood of using public transport than the car. In contrast, having children is negatively associated with the likelihood of using public transport. Moreover, a higher education of individuals is found to be positively associated with car use, while car availability is negatively associated with all other transport mode options.     

Weather and rail delays: Analysis of metropolitan rail in Dublin

With changes in the global climate, the occurrence of severe weather events appears to be becoming ever more frequent. As a result of this, vital transport networks are becoming increasingly exposed to disruption or disablement due to weather related incidents. In order to adapt to these changing conditions it is important to gain an understanding of how weather currently impacts transport systems. This paper presents the results of a statistical analysis of the impact of weather conditions on the performance of metropolitan commuter rail based upon observations made on the Dublin Area Rapid Transit (DART) rail system. Utilising a dataset comprising daily performance observations for 30 train services operating across the DART network, this research applies a number of multiple regression models to gain an understanding of the role of weather, temporal effects, and resulting interactions, on delays experienced by the network. While research in this area has traditional focused on the impact of single events, this study presents an examination of the role of multiple factors and their interactions. With regard to temporal effects, the largest delays are observed in the last third of the year, with peak delays occurring in November. Delays due to adverse weather conditions are observed, with rain being the primary factor related to poor performance. Interactions between different weather conditions, particularly wind and rain, as well as between weather conditions and the month in which a journey took place were also observed to be significant and resulting in delays to services.     

Understanding the roles of rail stations: Insights from network approaches in the London metropolitan area

In strategic transport planning, rail stations play different roles at different scales, particularly in large cities and metropolitan regions, where movement structure shows polycentric patterns. However, there is a general lack of evidence-based studies investigating the relative network roles of rail stations. Therefore, this paper aims to explore rail stations' roles within and beyond metropolitan communities in London. Drawing on the Transport for London's newly released NUMBAT passenger origin-destination data, we unravel the travel structure and identify the stations' roles through network methods, community detection and Z-P scores. Our research has three results: First, London's passenger movement network can be subdivided into seven communities. The majority of stations within the same communities are geographically localised with few exceptions. Second, stations play distinct roles in handling the patterns of movement at different scales. Typically, there exists a set of stations that are significant for connecting between metropolitan communities, because the disruption of those stations will have a greater impact on overall network efficiency and affect a larger and more diverse group of passengers. Third, a classification of rail stations is developed based on stations' commitment at two scales. This classification allows planners to have a finer level of understanding of the network role of the stations and thus develop and adjust tailored (re)development strategies.     

Experience conditioning in commuter modal choice modelling – Does it make a difference?

This paper investigates the impact of decision maker’s experience on model elasticities and predicted market share, using data collected in Sydney on commuter mode choice. Usage frequency is used as a proxy for experience and two separate mode choice models are estimated – one with experience conditioning choice and one without. Key model outputs are compared and we find that differences in the value of travel time savings and model elasticities are very marked. This suggests that ignoring experience that one has with each alternative in their choice set may be a candidate source of error in travel demand forecasts. We develop a method to obtain the level of experience for use in application of choice models to increase their prediction power.     

Logistics sprawl in the Brussels metropolitan area: Toward a socio-geographic typology

Logistics activities are concentrated around cities, for the purpose of accessing and serving these important markets. However, at a more refined level, because of land prices, availability and modern logistics schemes, suburban locations are preferred. This trend, the so-called logistics sprawl, creates land consumption, longer supply chains and jobs shifts. This article analyses the geography of logistics in the Brussels metropolitan area and highlights this suburbanization, notwithstanding the fact that some particularities appear, due to the Brussels, Belgian and European contexts. In a second step, we construct a spatial typology to understand the fine evolution of the Brussels metropolitan logistics space. These results reinforce our knowledge of logistics geography and add a frequently neglected institutional dimension to the extant literature on the subject – wholesale trade activities.     

Urban sprawl and travel to work: the case of the metropolitan area of Madrid

The relationships between urban sprawl and journey to work in the metropolitan area of Madrid are analysed. Three elements of urban sprawl are addressed (metropolitan expansion, low-density and work and leisure facilities in suburban areas) and are related to the main characteristics of mobility (flow networks, mode-choice, and travel times). The conclusion reached is that the elements defining the new metropolitan morphology are related to an unsustainable mobility model, which increases commuter numbers, distances, and car use.     

Consequences of logistics sprawl: Order or chaos? - the case of a parcel service company in Paris metropolitan area

Logistics sprawl is the phenomenon driving warehouses and freight terminals further and further away from city centers, for reasons that are mostly dependent on urban planning, field price and economies of scale. In the past, studies have already described logistics sprawl in Paris Metropolitan area. These studies have concluded that logistic facilities far from Paris city center increased the distance travelled, and by extension, CO₂ emissions. This study does not question logistics sprawl in Paris metropolitan area but questions its consequences.This study presents a point of view on the location of cross-docking terminals. One main parcel service carrier was studied through a database strong of 600,000 inputs including pick-ups and deliveries for two months in the Paris metropolitan area. This study is not intended to be representative of all merchandise flows but makes it possible to understand the running of one significant actor. This project aims at determining the optimum terminals location according to two criteria: minimization of the total distance as calculated by the Euclidean distance (as the crow flies) between terminals and points of pick-up/ delivery, and the number of authorized terminals. The number of terminals is modified to study its relationship with the spatial distribution of its clients.Interestingly, we found that optimized locations for this parcel service carrier are located outside of Paris city center. Those locations minimize the total distance to the clients, and thus, are the best places to limit pollution. The reason is that the carrier manages this perimeter through a polycentric organization. Paris Metropolitan area is viewed as several sectors and not as a whole for this carrier. It is therefore unknown how the carrier's performance has evolved over time, but its current organization is close to the optimal situation.     

Traveler satisfaction in rapid rail systems: The case of Istanbul metro

Multifaceted characteristics of urban travel have an impact on the passengers' overall satisfaction with the transport system. In this study, we investigate the interrelationships among traveler satisfaction, travel and traveler characteristics, and service performance in a multimodal network that comprises of a trunk line and its feeder lines. We analyze the factors influencing the choices of access to rail transit stations and the satisfaction of transit travelers with the rapid rail transit systems. We quantitatively study these relationships and demonstrate the complexity of evaluating transit service performance. Since the interrelationships among variables affecting this system are mainly stochastic, we analyze the satisfaction with transit system problem using a Bayesian Belief Network (BBN), which helps capture the causality among variables with inherent uncertainty. Using the case of Istanbul, we employ the BBN as a decision support tool for policy-makers to analyze the rapid rail transit services and determine policies for improving the quality and the level of service to increase the satisfaction with transit system. In the case study, satisfaction with accessibility and access mode variables are found to be more effective variables than total travel time for travel time satisfaction, confirming the significant role of access in multimodal travels.     

Errors in variables in multinomial choice modeling: A simulation study applied to a multinomial logit model of travel mode choice

Modeling travel demand is a vital part of transportation planning and management. Level of service (LOS) attributes representing the performance of transportation system and characteristics of travelers including their households are major factors determining the travel demand. Information on actual choice and characteristics of travelers is obtained from a travel survey at an individual level. Since accurate measurement of LOS attributes such as travel time and cost components for different travel modes at an individual level is critical, they are normally obtained from network models. The network-based LOS attributes introduce measurement errors to individual trips thereby causing errors in variables problem in a disaggregate model of travel demand. This paper investigates the possible structure and magnitude of biases introduced to the coefficients of a multinomial logit model of travel mode choice due to random measurement errors in two variables, namely, access/egress time for public transport and walking and cycling distance to work. A model was set up that satisfies the standard assumptions of a multinomial logit model. This model was estimated on a data set from a travel survey on the assumption of correctly measured variables. Subsequently random measurement errors were introduced and the mean values of the parameters from 200 estimations were presented and compared with the original estimates. The key finding in this paper is that errors in variables result in biased parameter estimates of a multinomial logit model and consequently leading to poor policy decisions if the models having biased parameters are applied in policy and planning purposes. In addition, the paper discusses some potential remedial measures and identifies research topics that deserve a detailed investigation to overcome the problem. The paper therefore significantly contributes to bridge the gap between theory and practice in transport.     

Warehouse location choice: A case study in Los Angeles,CA

The purpose of this research is to understand how and why warehouses have changed location over time from central urban areas to the urban periphery: spatial decentralization. Over the last decade, the logistics industry has been restructured to transport large volumes of goods more quickly and reliably. Concurrently, the warehousing industry experienced changes in facility size and location: large warehouses have been built on the urban outskirts. This spatial shift is attributed to inventory and transport cost trade-offs: the gains from lower land prices and scale operation outweigh the increase in transport costs as warehouses decentralized from central urban areas. As a case study, I examine location choices of 5364 warehousing facilities in Los Angeles, CA. I hypothesize that (a) the location choice varies by facility size and (b) the location choice logic has changed over time. Results suggest significant differences in the effect of location choice factors over facility size and over time. For warehouses built before 1980, the most influential factors are local market, labor, and seaport/intermodal terminal proximity. In contrast, for warehouses built after 2000, lower land price and airport/intermodal terminal proximity have the greatest effects.     

A multi-view of the daily urban rhythms of human mobility in the Tokyo metropolitan area

The purpose of this study was to clarify the spatiotemporal structure of human mobility patterns in the Tokyo metropolitan area (TMA), and to reveal the regional characteristics and differences of dynamic mobility behaviour therein, from the individual, location, and time-use perspectives. Furthermore, this study aimed to describe daily urban rhythms in terms of human mobility. For these purposes, we constructed a GIS microscope by handling our geo-tagged big data based on the person-trip data. Through a multi-view study, we affirmed that the spatiotemporal mobility patterns had a certain consistency at different scales. Results suggested that the human mobility patterns expressed a typical inter-regional functional complementarity and a certain daily rhythm under the layout of TMA’s quadruple concentric ring structure. By grasping the multidimensional dynamic pattern of human behaviour, researchers, the general public, and policymakers can be brought into alignment towards the goal of sustainable urban planning.     

A study on travelers' transport mode choice behavior using the mixed logit model: A case study of the Seoul-Jeju route

This study is to analyze passengers' choice of the mode of transportation when air transportation is in competition with high speed rail (HSR). The Seoul-Jeju route analyzed as an empirical case study, in which the construction of an undersea tunnel to connect Seoul and Jeju city by HSR has been considered. The study also included two new variables, ‘safety of transportation’ and ‘availability of duty free shopping’ in addition to traditional transport choice variables such as travel time, travel costs and frequency of service to reflect special characteristics of the market. As data gathering tools, SP techniques and mixed logit model, for analytical methodology, were utilized. The authors found that the goodness of fit of the models was improved with new variables. The models also showed that the characteristics of business passengers and leisure passengers in choosing the mode of transportation were different. Business passengers were apt to choose a safety secured mode of transportation regardless of fare while leisure passengers preferred to use duty free shops more than business passengers.     

The geography of freight-related accidents in the era of E-commerce: Evidence from the Los Angeles metropolitan area

Due to the burgeoning demand for freight movement in the era of e-commerce, freight related road safety threats have been growing in both urban and suburban areas, despite the improved general traffic safety over the past decades. The empirical evidence on how freight trucks related crashes are distributed across neighborhoods and correlated to spatially varying factors is, however, highly limited. This article uses data from the Los Angeles region in 2018 to analyze the spatial patterns of freight trucks related traffic crashes and examines the major factors that contribute to those patterns using spatial econometric models. Maps show that freight trucks related crashes are highly associated with major freight generators but less clustered than the overall traffic crashes. Results from the spatial Durbin model indicate that access to freight generators, economic attributes, land uses, road infrastructure, and road network variables all contribute to the spatial distribution of freight trucks related crashes. The findings could help transport planners understand the dynamics of freight trucks related traffic safety and develop operational measures for mitigating the impacts of growing goods movement on local communities.     

The impact of light rail on congestion in Denver: A reappraisal

In a recent analysis, Bhattacharjee and Goetz (2012) assert that the development of a light rail system in the Denver, Colorado metro area resulted in short-term reductions in traffic on some highway routes in Denver, and that it reduced the growth of highway traffic on major highways near the light rail network by 10% age points between 1992 and 2008. We point out several flaws in their analyses and reanalyze their data. We find no credible evidence that development of light rail reduced highway traffic, nor that it reduced the growth of highway traffic. We also show that light rail, by a large margin, carries too few passengers to have the effect that they assert.     

Small community airport choice behavior analysis: A case study of GTR

The issue of airport selection attracts considerable attention. However, most studies focus on using advanced discrete choice models to analyze airport choice behavior in metropolitan areas with several closely located, competing airports. This paper addresses passengers’ choice behavior in selecting between local small community airports and more distant major commercial airport. It looks at factors affecting air travelers’ airport choice behavior in cities with small community air service. Data relating to the Golden Triangle Regional Airport in Mississippi is used in logistic regressions to identify the key factors that influence air travelers’ airport choices. Ticket price, experience with Golden Triangle Regional Airport and flight schedule were found to be the strongest effects.     

Spatio-temporal patterns of subjectively reported congestion in Tel Aviv metropolitan area

Traffic congestion is still one of the major problems of urban transportation. It is the aggregate outcome of individual, subjective, decisions in a changing traffic environment.The individual’s decision making is affected, among other factors, by experience and direct information from the surrounding environment, or indirectly from the media. The subjective map created from this information provides the cognitive environment within which the driver makes decisions. This study examines the spatio-temporal changes in the subjective map of reported congestion as formed by radio broadcasts in the Tel Aviv metropolitan area. It aims to evaluate the spatio-temporal stability of the emerged congestion patterns as a basis for subjective decision making, and to explain its variability as a necessary base for any effort to relieve congestion. Results show that non-recurrent heavy congestion is likely to be unstable. The spatio-temporal fluctuations of congestion were found to associate with traffic volumes caused mainly by weekly-based commuters which include university students, soldiers, and government employees. Reported information was found suitable for longitudinal research, the only kind which enables a broad understanding of the spatio-temporal pattern and dynamics of traffic congestion.     

Gay men's holiday destination choice: a case of risk and avoidance

Gay men are subject to discrimination and social disapproval in many parts of the world. This paper examines the possible impact of this on choice of holiday destination, drawing on the concepts of risk and destination avoidance. A number of interviews were held with gay men and it was concluded that risk of adverse reactions and of the need to modify behaviour were significant issues in destination avoidance and choice. It is possible, as a consequence, to classify holiday‐taking by gay men into a typology including gay‐centric and gay‐related. In addition, it is appropriate to modify existing models of risk‐avoidance through the addition of the risks that are more applicable to gay men than to other tourists. Copyright © 2002 John Wiley & Sons, Ltd.