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This research investigates factors influencing students' commuting choices to university campuses, focusing on the post-COVID-19 era, attitudes, and socio-economic variables. The study includes original data collected from a total of 785 participants who were surveyed at Shiraz University, located in Iran. The study results indicate that while public transportation and university shuttle buses continue to be widely used for transportation, a considerable proportion of students prefer personal cars, mostly driven by favourable impressions. The closeness to the campus is a crucial factor in this regard, as the students residing within a distance of 3 km exhibit a preference for walking. Moreover, the significance of bio-security factors such as cleanliness and the effective control of crowds for modal choice in the post-COVID-19 era. The study's findings give valuable insights for service providers and university administrators in the development of sustainable commuting programmes that align with the university's environmental goals. [ABSTRACT FROM AUTHOR]

Commuter satisfaction with their chosen mode of transport significantly affects quality of life, well-being, and the sustainability of commuting practices. This study uses a fuzzy-hybrid TOPSIS approach, applied to data from seven functional urban areas in Central Europe. The method effectively creates a composite indicator for assessing satisfaction levels by considering factors such as socioeconomic conditions, geographical features, and mobility-related data. The research analyzes how satisfaction varies according to these factors. Results indicate that commuter satisfaction levels vary across different factors, including age, education, occupation, gender, travel distance, travel time, commuting cost, and income. Notably, those with shorter commuting times and lower expenses tend to report higher satisfaction, while unemployed and low-income commuters, as well as those using active modes of transport, often express lower satisfaction levels. Interestingly, bus riders find their trip more satisfactory than car drivers, but train commuters are the least satisfied of all. Overall, this study provides valuable insights into commuter satisfaction, informing the development of policies and strategies to improve the transport infrastructure and services and promote the choice of sustainable modes.

Transportation inequality poses significant challenges in car-dependent cities in the US, especially for Transit-Dependent Populations (TDPs) who rely on public transportation to meet their travel requirements. Research indicates that despite the rapid growth of ride-hailing services like Uber, TDPs primarily depend on conventional transit options such as buses and metros. This study differentiates between two classifications of ride-hailing services: Private Ride-hailing (PRH), represented by platforms like Uber and Lyft, where individuals hire and pay for their rides, occasionally sharing the journey with guests; and ride-sharing (RS), like UberPool, which allows users to divide travel expenses. However, a more profound comprehension is necessary to clarify why TDPs show a preference for one mode of transportation over another and the factors that influence their decision-making. This study utilises Structural Equation Modelling (SEM) to examine the direct and indirect relationships between explanatory and outcome variables, while investigating modal preferences and usage frequency in 48 densely populated urban areas in the US (N = 384). TDPs choose to use transportation services like Uber because of their effectiveness in reducing both travel and waiting time, in contrast to traditional Fixed-Route Transit Services (FRTS), which are relatively less efficient. TDPs’ inclination towards PRH leads to a greater dependence on ride-hailing services, whereas a preference for FRTS reduces this dependence. Significantly, the study demonstrates that TDPs’ modal preferences are not only influenced by their socioeconomic status or rational decision-making, but also by the complex interaction between these factors. These findings provide valuable information for policymakers who want to evaluate the sustainability of ride-hailing services for TDPs and effectively tackle transportation inequalities.

Airport ground accessibility is an important and integral part of airport planning, which significantly impacts airport attractiveness and its environmental sustainability. In this paper, we propose the combined use of road micro-simulation with meso-scope discrete choice modeling to support the evaluation of airport access interventions. The proposed integrated framework allows us to appraise mode choice and infrastructural interventions simultaneously to accurately assess the performance of airport access road networks in accommodating larger traffic. We validate and demonstrate the benefits of the proposed approach by applying it to a real-world case study based on the Milan–Bergamo Airport (BGY), in which (i) we conduct an ex-post counterfactual analysis to assess the impact of the interventions undertaken to mitigate the large growth (54.6%) in the years 2013–2019, and (ii) evaluate future scenarios up to 2030 considering the additional expected growth and introduction of direct rail services. Results indicate that BGY's ground access interventions have contributed to effectively accommodating traffic growth by significantly mitigating road congestion and associated pollutant emissions. Results also inform on the need and effectiveness of additional interventions to meet the substantial expected future growth. • Airport ground accessibility is an important and integral part of airport planning. • Road micro-simulation with meso-scope discrete choice modeling are propounded. • The hybrid framework appraises mode choice and infrastructural interventions. • This accurately assesses the performance of airport access road networks. • The approach is validated via a case study of the Milan–Bergamo airport. [ABSTRACT FROM AUTHOR]

Urban mobility has undergone a transformation with the advent of micromobility vehicles, leading to a multitude of studies investigating the factors that drive early adoption and the sustainability and equity implications. However, in a context where local administrations struggle regarding how to fit different micromobility systems within the urban ecosystem, little is understood about how political regulations impact micromobility users' modal choices This study aims to shed light on the differences between private e-scooters and shared bikes in Barcelona, a city where micromobility options face distinct regulatory frameworks, and also to understand the factors that influence an individual's choice between these two modes of micromobility. The study employs a self-reported intercept survey on 651 micromobility users and builds a logistic binary regression model to examine the characteristics that differentiate e-scooter and shared bike adopters. Results indicate notable differences between adopters of the two modes and suggest that city regulations might play a role in determining the choice of mode. Furthermore, the study finds that while both modes follow similar mode replacement paths, shared bikes have a higher potential to keep users away from cars. These findings contribute to the limited knowledge on the choice between different modes of micromobility and highlight the impact of policy design on diverse population groups. As more cities are banning free-floating from city centres, it is essential to understand how these selective bans and restrictive policies have an impact on micromobility users' modal choices. • Gender and age gap are confirmed to exist in emerging mobility services usage. • Socioeconomic differences might be partially explained by the city restrictive regulatory framework. • Shared bikes might have a higher potential than private e-scooters to keep users away from the car in the long term. • Environmental and social sustainability of micromobility modes is questioned. [ABSTRACT FROM AUTHOR]

Cycling during youth is characterized in many countries by two trends: its decline over the course of several decades (termed the generation effect) and its decline over the life course of individuals (the age effect). This paper addresses the age effect through a survey carried out among young people aged 12–20 (n = 1,358) in a Swiss city. It goes beyond the cyclist/non-cyclist dichotomy and identifies several cases in terms of skills (ability to ride a bike), access (ownership of a bike), and uses (reasons for and frequency of cycling). While most young people (98%) learned how to ride a bike as a child, an important minority do not continue cycling beyond childhood. Among those who continue, the use of the bike often changes over time to become less utilitarian and more recreational and occasional. The main determinants explaining cycling practices among young people are socialization (the parents' cycling practices and level of education), gender, and the spaces of everyday life (place of residence and school). The results point to several levers to foster cycling among young people, to anchor sustainable mobility practices for years to come. [ABSTRACT FROM AUTHOR]

Ride-hailing services (RHS) are widely expected to serve as an alternative to conventional private transportation modes. However, numerous studies on RHS’s impact on private modes’ usage provide inconclusive evidence. Notably, few studies have analyzed RHS’s impacts on modal changes in the context of motorcycle-based societies. This study attempts to identify the critical factors affecting RHS users’ private mode usage (private cars and motorcycles) in response to RHS appearance in Hanoi, Vietnam, a motorcycle-based society. Two empirical analyses were performed with sample data of 642 individuals collected from face-to-face interviews using paper-based questionnaire sheets in Hanoi from December 19 to 21, 2020. The first analysis employed a linear regression model to explain the changes in individuals’ private mode usage before and after RHS adoption. The second analysis estimated a logistic regression model to examine an individual’s private mode choice when RHS are unavailable. Robustness tests were also performed. The results revealed that RHS users’ future vehicle ownership intentions, reasons for using RHS instead of private modes, motorcycle ownership, and public transport usage significantly reduce the impacts of RHS on private mode usage. The reasons for using RHS rather than private modes were found not strong enough to make an essential change to reduce the frequency of private modes usage. The results also showed there is a difference between the RHS’s impacts on motorcycle use and car use. They suggested that policy makers should be aware of the unique factors in motorcycle-based societies such as Hanoi when formulating urban transportation strategies. Finally, the findings further supported an idea that multivariate analyses are more suitable than the simple descriptive statistics method to understand how the motivation for using RHS influences the impacts of RHS on private mode usage.

This study investigated commuting behavior at four technical faculties (BCTF) in Maribor. The main aim was to provide suggestions and solutions for challenges related to active commuting to the BCTF, while promoting advancements in CO2 emission reduction. The research methodology was based on analyses of a questionnaire survey and calculations of CO2 emissions. The results indicate that implementing measures to promote walking, bicycling and the use of city and regional public transport, in conjunction with supportive housing and parking policies, has the potential to eliminate car trips within 0–1 km of the BCTF and reduce car trips from other zones in favor of active commuting by 30% to 50%. These proposed transport scenarios could lead to an annual reduction in CO2 emissions ranging from 17% to 29%. The greatest potential for CO2 savings is observed within 0–5 km of the BCTF, where a shift to walking and bicycling could reduce emissions by up to 44%. The results also highlighted a notable disparity, indicating that students with term-time accommodations emitted 3.5 times and 4.1 times less annual CO2 within 0–5 km of the BCTF compared to students and staff commuting daily from their permanent residences in the city. [ABSTRACT FROM AUTHOR]

Demand estimation and forecasting is an essential step in urban passenger transport planning. Relating the factors that influence the modal choice behavior of individuals facilitates demand estimation. In this study, we develop machine learning models that consider individuals' demographic, socioeconomic, and travel characteristics to justify their mode choice. Two datasets are used to train and validate the models. We use logistic regression and multilayer perceptron models to classify public or private transportation trips. It was observed that a multilayer perceptron model with a low number of parameters could predict modal selection with an accuracy exceeding 90%. We derive an algebraic equation from this result to perform modal selection prediction. Our results show that the models can effectively predict the mode of transportation of individuals based on their demographic and travel characteristics.

The COVID-19 pandemic has adversely affected the transportation sector, leading to a change in travel behavior. One of the most important responses of countries worldwide to slow the spread of the pandemic has been to restrict the movement of people, which has had a considerable effect on transport systems and is likely to affect the modal choices of commuters. The social and economic effects of the COVID-19 epidemic on public transportation encompass beyond service performance and health risks to social equity, financial viability, and sustainable mobility. To assess the likely nature of such a shift, this study attempts to understand mode choice based on the perception of commuters for their work and non-work trips after the lockdown phase due to COVID-19. The Multinomial Logit Model was used in this study to find the association of mode choice with health-related safety perceptions of commuters for private and public transport, and their socio-economic and travel characteristics. Mode choice for private transport was found for work trips, whereas non-motorized transport for non-work (shopping, leisure, etc.) trips up to a distance of 10 km. The model results showed that significant factors for the increase in the usage of private transport and non-motorized transport relative to public transport were physical distancing and hygiene. This study provides results for future transportation policies in the post-COVID period. The results, like emerging positive perceptions of non-motorized modes, are very useful for making better investments in the country to promote sustainable transportation and articulating solutions to address high-risk perceptions associated with public transport modes.

Copyright of Recherche et Cas en Sciences de Gestion is the property of EMS Editions - In Quarto SARL and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Recherche et Cas en Sciences de Gestion is the property of EMS Editions - In Quarto SARL and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Traffic congestion and unsustainable mobility patterns represent a severe issue for most Brazilian cities, with traditional approaches often proving to be scarcely effective in tackling the problem. We argue that a crucial hindrance is represented by the limited attention devoted to "the commuter perspective": only a deeper understanding of the motives behind mobility-related behaviors of citizens would enable policy makers to implement sound mobility plans. We performed an empirical investigation on residents of the city of Florianópolis (n = 436), analyzing the determinants of modal choice. Results confirm the pivotal role exerted by habits, and the willingness of respondents to opt for sustainable transport modes; a peculiar finding is represented by the marginality of social and environmental aspects in shaping commuters' behaviors, and the perceived lack of convenient alternatives that is yet hindering a broad shift which is seen as necessary. Based on the evidence emerging from the study, we provide a contribution to the debate by discussing possible lines of action and policy options that could be implemented. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has adversely affected the transportation sector, leading to a change in travel behavior. One of the most important responses of countries worldwide to slow the spread of the pandemic has been to restrict the movement of people, which has had a considerable effect on transport systems and is likely to affect the modal choices of commuters. The social and economic effects of the COVID-19 epidemic on public transportation encompass beyond service performance and health risks to social equity, financial viability, and sustainable mobility. To assess the likely nature of such a shift, this study attempts to understand mode choice based on the perception of commuters for their work and non-work trips after the lockdown phase due to COVID-19. The Multinomial Logit Model was used in this study to find the association of mode choice with health-related safety perceptions of commuters for private and public transport, and their socio-economic and travel characteristics. Mode choice for private transport was found for work trips, whereas non-motorized transport for non-work (shopping, leisure, etc.) trips up to a distance of 10 km. The model results showed that significant factors for the increase in the usage of private transport and non-motorized transport relative to public transport were physical distancing and hygiene. This study provides results for future transportation policies in the post-COVID period. The results, like emerging positive perceptions of non-motorized modes, are very useful for making better investments in the country to promote sustainable transportation and articulating solutions to address high-risk perceptions associated with public transport modes. • Almost 32% of the people potentially switching to different modes • Drop in choice distribution of metro (68%) is more than bus users (53%) • Increase in choice for NMT mode by 19.68% • Higher travel frequency associated with public transport as mode-choice • Safety measures were significantly associated with health-related safety perception for private transport as modal choice [ABSTRACT FROM AUTHOR]

Background: Many cities are putting cycling at the centre of their sustainable transportation policies after the COVID pandemic. Cycling is seen as a desirable mode of transport in dense and compact areas and needs to be promoted accordingly. However, to date, only a handful of different bikeability indexes exist attempting to map biking conditions and the built environment’s potential to promote biking as a modal choice on a city scale. Methods: In this article, we use objective GIS data to map bikeability potential in the city of Barcelona. To do so we extracted the main bikeability components from an adhoc cycling survey and then create an index using ten spatial indicators. This bikeability index is mapped at a 100 × 100 m scale in the city of Barcelona. We then use actual travel behavior data extracted from a local representative travel survey to test the reliability of the index in predicting daily bike use. Results: Results confirm the validity of the bikeability index as a predictor of the frequency of cycling. People living in areas with higher levels of built environment features associated with bikeability such as dedicated infrastructure, low accident rates and small slopes are more likely to use the bike more often. Conclusions: Results validate our approach providing new methods to be used in further biking studies and a useful tool for policy and decision making. The use of our new bikeaiblity index is especially indicated for highly-dense, compact, Mediterranean-style cities.

The study of commuting behavior at the University of Maribor (UM) was the subject of our research, which focused on the building complex of the four technical faculties (BCTF) and was based on the analysis of two questionnaire surveys (with 1057 and 462 respondents, respectively) and the transport policies implemented at the study site from 2010 to 2020. The research aimed to identify the factors influencing student and staff mode choice/shift over a decade period and to understand the weaknesses, strengths, and opportunities for improving sustainable mobility at the university. Since 2010, active commuting has predominated among students, while car use has decreased by 22%. Female students were 16% more likely to walk than their peers, while male students were 5% and 12% more likely to use bicycles and cars, respectively. Active commuting and car use by staff have not changed since 2010, and there was an insignificant difference between genders, 63% of whom used cars. Mode shifts were primarily related to trip origins, subsidization of bus use, availability or unavailability of free parking, and parking fees. Questionnaire responses were a powerful tool for finding the most effective interventions to manage transport at universities. The results also suggest that transport policies can be more effective if they are planned in coordination with housing policies. [ABSTRACT FROM AUTHOR]

The modal choice, the third step of the historical four-stage model (FSM), determines the flows for each mode of transportation. It is generally stimated from the discrete choice models, which require re-building trips conditions for all alternatives, even those marginal. This paper proposes a new alternative based on machine learning methods and resampling techniques to estimate the modal choice by considering the extreme minority mode of transportation, such as intermodal combinations (e.g., car + public transit, bike + public transit). We have proposed two learning algorithms: the decision tree (DT) and the multinomial logistic regression (MNLR). Afer resampling the dataset, the DT presents better predictions (70% of global accuracy and f1-score closes to 70% for all modes of transportation) than the MNLR (35% of global accuracy). [ABSTRACT FROM AUTHOR]

Universitas Gadjah Mada (UGM) in Indonesia brings thousands of new students annually. This greatly affects the use of transportation modes and the need for modes of transportation to the campus. This study aims to determine the modes of transportation used by students to campus, factors that influence the choice of transportation modes, and the needs of student transportation modes. This study uses a quantitative approach with descriptive analysis and Cramer's V correlation test. The results of the study show that the transportation modes used by Universitas Gadjah Mada’s students as a means of transportation to the campus are mostly private (70.5%). Factors that influence the choice of modes of transportation are private vehicle ownership, driving license ownership, monthly allowance, residence, frequency of use of transportation modes, time of movement, distance traveled, transportation modes changing, travel time, transportation costs, security/safety, timeliness, and speed. The modes of transportation needed by students are motorbikes and online transportation/ride-hailing service. The transportation characteristics that are most needed by students are fast, cheap, and comfortable. As many as 89.4% of students agreed and as many as 10.6% of students did not agree if there were vehicles provided by the campus.

Accessibility and equality evaluations have been primarily focused on residential location. However, workplace location might be an equivalent contributor to inequalities in the travel experience and accessibility. Traditionally, transport planning connects high-demand areas with the best-quality and capacity transport infrastructures. Literature supports that employment centers (EC) receive mainly workers in certain middle-to high-income occupations. This condition results in a type of segregation pattern associated with trip destinations and modal choice similar to those reported for the household location. This paper investigates commuting from a different standpoint, emphasizing the need to consider workplace location and employment distribution within cities. We identify five main EC in Bogotá, Colombia, and explore their association with the commuting mode choice of three population groups using mixed logit models. Results indicate that people who work in any EC tend to use more public transport (PT). Nevertheless, the probability of selecting PT differs among groups. Specifically, for low-income commuters, PT represents lower utility than that for middle-income commuters if their job is located in an EC. The fact that the population most likely to be public transport captive does not find this alternative as attractive as the middle-income segment needs further investigation for better policymaking.

Universities generate significant transport flows on a daily basis. Transport represents a core challenge for the attractiveness of universities but also for their ecological footprint. This paper addresses the mobility practices of students and staff at the University of Lausanne, Switzerland, through a series of 13 annual surveys. The majority of the university community use public transport, which is explained by investments in infrastructures, the development of their carrying capacity (frequency and size of vehicles) and also the staggering of the start time of classes that has flattened peak hours. The efficiency of public transport and a parking policy have more than halved the modal share of the car. Cycling has experienced a notable growth unlike motorized two-wheelers and walking. The paper then addresses how mobility practices diverge within the university community. Modal choices can be explained when the effects of gender, age, income, territorial context (distance and mobility offer) but also values (as reflected by several differences between faculties) are looked at together. Overall, the paper brings knowledge to the issue of mobility on university campuses and the levers that could turn them into sustainable communities.

COVID-19 (Coronavirus disease 2019) brought about a huge change in the behaviour and mobility of citizens in all parts of the world. This change was mainly a consequence of the strong measures of isolation and social distancing taken by the different governments in most countries through the world. The specific measures adopted in each country, in combination with the particular characteristics of the spread of the virus, generated differentiated, although similar, behavioural changes. This article presents the analysis of a survey carried out in Spain in March 2020, where citizens were asked about their mobility preferences before, during and after the lockdown due to the virus. In turn, questions were asked about the preferred modes of transport in each of the situations and the perception of safety on public transport in their current conditions. The mobility questions were differentiated between commuting to work or studies, shopping and leisure. The results show that public transport was the most affected transport mode, with a considerable increase in the use of the bicycle and walking trips. At the same time, changes were observed in the behaviour of shopping trips, including a considerable decrease on the use of large supermarkets. Citizens perceived great uncertainty in planning leisure trips, the consequence of which could be that a higher proportion of people not being able to carry out their planned trips. • A large part of the trips planned by citizens could not be carried out by COVID-19. • Public transport was the most affected transport system by the COVID-19 pandemic. • COVID-19 affected citizens' shopping behaviour. • Modal shifts in transport were different depending on the size of the city. • Public transport will need measures to guarantee security against the virus to return to normal conditions. [ABSTRACT FROM AUTHOR]

As a response to the increasing threat to sport events from climate change and expectations around climate change mitigation, sport event managers increasingly engage in environmentally-related initiatives that aim to reduce GHG emissions. One of the major contributors to GHG emissions at large sport events is spectators' travel and, thus, their associated modal choices. Building on the Sport Logistics Framework (SLF) and using the case study of Rapid Vienna, the largest football club in Austria, this study investigates spectators' modal choice to systematically assess the total GHGs emitted by spectators at a professional football home game. Data was obtained from two sources: a) an extensive data set collected on Rapid Vienna season ticket holders, and b) three surveys at home games which, together, constituted 3317 valid responses. The calculation of the GHG emissions resulted in 99,548 kg GHG emissions per home game or 6.0 kg GHG emissions per spectator. It was also found that 42.4 per cent spectators arriving by car emit 71.6 per cent of GHG emissions, while in contrast, 52.8 per cent of spectators using public transport emit 27.1 per cent of GHG emissions. The results also indicate that the possession of an annual public transport ticket seems to determine travel behavior, i.e. the majority of spectators with an annual ticket are using it, while spectators without a ticket are using a car. As such, this paper not only provides an opportunity for academics and managers to benchmark the data in order to identify initiatives to reduce the impact of GHG emissions, but also allows for the systematic measuring of the environmental impact of fan and spectator travel. • Fan travel to professional football games is a major contributor to GHG emissions. • We assess fans' modal choices and their carbon footprint at a football home game. • The home game emits a total 99,548 kg GHG emissions or 6.0 kg GHG emissions per fan. • We found that 42.4% fans arriving by car emit 71.6% of GHG emissions. • The study allows for benchmarking and systematic measuring of fan travel behavior. [ABSTRACT FROM AUTHOR]

Abstract Purpose The purpose of this paper is to examine the impact of distance on choosing between intermodal rail-road and unimodal road transport and to examine the hypothesis that distance is an important factor influencing the mode choice in freight transport. Methods In order to make comparisons between the two options, the ideas and elements of the analytical transport system modelling found in the literature are used. The calculation of break-even distances is based on a Monte Carlo simulation that takes randomly generated shipper and consignee locations in two separated market areas, independently of a certain transport corridor, into account. Results The results confirm the importance of distance for the mode choice and show there is not only one but in fact many break-even distances between the two options. They vary considerably depending on different travel plans, and the transport infrastructure conditions. Conclusions Despite assumptions inevitable in such general analysis, the results show that intermodal transport can provide a competitive alternative to unimodal road transport, even over relatively very short distances if the drayage costs are not too high. We believe the paper can help improve understanding of competitiveness in the freight transport sector and may also be useful for policy- and other decision-makers to better evaluate the opportunities and competitiveness of intermodal rail-road transport.

Metropolitan university campuses (MUCs) are of interest for policymaking given their general highly car-oriented nature, and the subsequent need to promote policies that enhance sustainable accessibility outcomes. Hence, a growing body of research has emerged over the last decade focusing on travel behavior associated with those metropolitan enclaves. However, limited attention has been paid to distance decay effects on modal choice in the context of MUCs, and that is the main focus of the present research. Based on a representative travel survey, this study analyses the effect of distance to the closest railway station on the decision to use public transportation to travel to the main campus of the Autonomous University of Barcelona (UAB). Changes in the distance decay effect per sociodemographic group and trip characteristics are also analyzed. Results suggest that the effect of distance decay is key to understand the modal choice among noncaptive commuters, but that the magnitude and spatial dimension of this effect varies deeply along socioeconomic variables and commuting practices such as the university role. Findings show specific profile-based distance thresholds of modal choice that will contribute to our understanding of both future travel patterns among UAB members and the design of efficient transportation policies. [ABSTRACT FROM AUTHOR]

Is built environment the most influential factor on travel behavior when compared to individual socioeconomic characteristics? This paper extends the empirical knowledge by providing and comparing quantitative estimates of these various effects on both commuting distance and mode choice in a European city spatial context, while using up-to-date and novel methodology. Eight indicators of built and social environment are identified in order to characterize clusters of residential locations, giving a rich view of spatial and social diversity of locations. To disentangle the causal effects of residential self-selection and built environment, both sample selection and specific matching preprocessing (“coarsened exact matching”, a novel approach in the field) are implemented. Regarding commuting distance, the true effect of built and social environment appears modest with an increase of distance in the range of 10-20%. It comes behind individual socioeconomic characteristics such as car availability and skill. Regarding commuting mode choice, again the true effect of built and social environment is modest, with a near 20%pt increase of car share and around 10%pt decrease or public transport share for the most prominent effects, and it comes behind car availability. These results suggest the primary importance of directly influencing car use, if not car ownership, in the European context, while trying to modify the built environment would provide only limited results.

Rapid growth of the older population worldwide, coupled with their overreliance on automobile and its negative consequences for the environment and for their wellbeing, has encouraged research on travel behavior of this age group. This study contributes to the literature by providing an integrated analysis of the effects of sociodemographic, built environmental, psycho-social, trip, and activity space attributes on shopping trip mode choice of older adults in Helsinki Metropolitan Area. Data was collected using an online map-based survey. Two person-based activity space models were developed, in addition to the commonly used 500-m buffer, to measure activity space and built environmental attributes. Integrated Choice and Latent Variable (ICLV) models were utilized to explore modal choice. Although the use of activity space models did not significantly increase the fit of ICLV models, it provided different information. Walkability index showed a positive significant effect on walking trips in individualized residential exposure model. A positive effect on transit use or biking was found in individual home range and 500-m buffer. The shape and dispersion of activity spaces affected mode choice as well. Green space influenced the goal of being physically active which in turn affected mode choice. Three personal goals of being physically active, having cultural and social affairs, and caring for others influenced mode choice. Results indicate the priority of the use of activity space and hybrid choice models in understanding travel behavior. Findings of this study can guide policies aiming to increase the use of more sustainable modes among this age group. [ABSTRACT FROM AUTHOR]

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The need for transportation facilities and infrastructure that is quite large in the city of Surabaya to the city of Malang is the impact of population growth and increased activity in the city. To support economic, social, trade and education activities between the two cities, public transportation facilities are needed that can meet the needs of the community in terms of comfort and safety. Fulfillment of comfort factors in the use of public transportation such as cheap travel costs, speed of travel time, and accuracy of operational schedules, is expected to increase the interest of travelers to use public vehicles more often than private vehicles. The analysis method used, among others, Descriptive Analysis aims to identify the characteristics of users of the Surabaya-Malang and bus modes, then the Logistic Regression Analysis and Binomial Logit Difference Analysis aim to Obtain a model of selection of bus and train modes in the Surabaya-Malang route, then proceed Sensitivity Analysis which aims to determine the sensitivity of the model of the response of the traveler in determining the choice if there is a change in each attribute of the trip. The results of logistic regression analysis and binomial logit difference, it can be concluded that, attribute / variable X2 (travel time) is the attribute / variable that most influences the mode selection. The sensitivity analysis results can be concluded as follows: Sensitivity to travel costs, the possibility of respondents prefer to use the train mode is greater than the bus. Sensitivity to time, the possibility of respondents prefer to use the train mode is greater than the bus. Sensitivity to the departure schedule (headway), the possibility of respondents choosing to use the train mode will be greater than the bus, if the difference in the headway is between 90-165 minutes. However, if the difference in headway is above 165 minutes, then the respondent will switch to choosing the bus mode.

Identification of optimum routes and mode of transport play vital roles in freight transport decision making. This paper presents the research carried out for the modelling and analysis of intermodal transport network. The study evaluates the trade-offs associated with different modes of freight transportation. Geographic Information System (GIS) and MATLAB were applied to design the hypothetical intermodal freight transportation network, modelling, analysis and user-interface design. An optimum route and transport mode for different pairs of origins and destinations were determined across decision objectives such as distance, time, emission and cost. The trade-offs among different modes of freight transportation were explored. Based on the assumptions of this study, the results showed that the road was the fastest mode, while waterway was not only the most costefficient but also was the most environmental-friendly transport mode in terms of carbon dioxide emission. Although the transport network of the study was small size and hypothetical, this paper demonstrates the potentiality of this methodology for analysing larger and real intermodal networks.

This paper aims to identify Brazilian southern industrial producers' preferences for freight transport service attributes by analyzing and quantifying their mode choice on domestic shipments among road and maritime alternatives. Using stated preference (SP) data, discrete choice models were estimated with a behavioral approach based on the Random Utility Theory. The best model was the nested logit, including a correlation between the unobserved component of the utility of the cabotage alternatives. Shippers' inelasticity to modal shifts suggests that it is hard to achieve relevant modality shifts by reducing cabotage freight and improving the maritime service level. [ABSTRACT FROM AUTHOR]

The concept of automated cars is rapidly becoming a reality. Yet there has been very little analysis of the impacts of such developments on the performance of urban transport systems. These impacts are potentially complex. On the positive side, automation has the potential to increase road capacity, make driving available to more people, and reduce accidents and emissions. On the negative side, it could attract users away from public transport, walking and cycling, substantially increase traffic levels and stimulate urban sprawl. These impacts cannot currently be measured empirically and, by the time that they can, it will be too late to change the implementation model to rectify any resulting problems. Predictive assessments are therefore needed. This paper considers the possible impacts of automated vehicles, predicts their effects on the urban land use and transport system, and discusses the policy implications. We focus on automation of the car fleet, and do not consider the potential of automation of public transport or freight. We consider the literature on the range of attributes of automated vehicles which might affect transport and land use patterns, and suggest potential outcomes for each over the period to 2050. These include the proportion of automated vehicles in the car fleet, whether automated vehicles are privately purchased or publicly shared, the impacts on network capacity, the reduced need to pay for and walk from parking places, the potential reduction in the value of in-vehicle time and the potential use by current non-drivers. We represent these attributes in an expanded causal link diagram of the urban land use and transport system and import those causal links into the MARS system dynamics model. We determine from the literature a level for each attribute, and test the impacts in a set of ten scenarios using an updated MARS model of Leeds. Based on our input assumptions, we find that car-km in 2050 could be over 50% higher than in the business as usual scenario. Public transport use could fall by 18%, threatening accessibility for those dependent on it, while walking and cycling could fall by 13%, reducing their health benefits. Overall person-km would rise, suggesting a reduction in sustainability. A requirement that all automated cars are shared vehicles could reduce these adverse impacts somewhat, but the effects are sensitive to the charge per km. Our use of a single value for each attribute means that our analysis is exploratory, but the size of the resulting impacts demonstrates the importance of understanding the scale of systems response to each of the attributes which we have considered. It will be important to manage the way in which automated cars are introduced into urban areas, if they are not to lead to a worsening of the urban environment, accessibility and health. A requirement to make all such vehicles part of shared fleets offers one way forward, but more work is needed to understand the way in which use of such fleets should be charged. • We review the literature on the possible demand-side and supply-side impacts of autonomous automobiles on urban transport and land use under private and shared ownership, and on the likely scale of such impacts. • We enhance a System Dynamics Land Use – Transport Interaction Model, MARS, to reflect the causal effects of the majority of these impacts. • We apply the enhanced model to the city of Leeds, UK, to test the effects of each potential impact on its own and of all impacts combined, under both fully private and fully shared ownership. • We find a clear synergistic effect between the impacts, leading to considerably higher levels of automobile use under automation; we predict car-km to increase by 56% for private ownership and 41% under shared ownership by 2050 when compared with business as usual. Total person-km rise by 39% and 32% respectively, while use of public transport, walking and cycling fall, indicating a move to a less sustainable future. • We explore the impacts on land use, suggesting that, while private ownership will add to urban sprawl, shared ownership might have the opposite effect. We discuss the policy implications. [ABSTRACT FROM AUTHOR]

The task of producing a generic model of the modal choice decision making process is a challenging one. Modal choice is strongly influenced by the infrastructure limitations and geographical constraints of the area in which the decision is being made. With this in mind, addressing modal choice on an individual basis for each region may be the optimal solution. This is the approach adopted in this paper. The creation of a modal choice model is a multistage process of which this paper addresses the first stage, the production a framework of the decision making process. Firstly, a number of criteria that are commonly used in modal choice models are identified. Then a number of gaps in the criteria utilized in previous papers are established. Subsequently, the method used to produce a framework of the decision making process within North West England’s Atlantic Gateway is outlined. Through consultation with transport industry experts in North West England, an initial list of sixty eight papers was reduced to thirty six that were considered to be of specific relevance to modern day freight transportation within their region. The criteria used in each of these papers were then, along with further industry input, used to create the foundation on which a modal choice framework specific to the Atlantic Gateway could be built. A greater understanding of what influences modal choice within this region will allow informed decisions to be made by policy makers on how to more efficiently utilize the available modes of freight transport. Having established this, future work can then go on to build upon these findings. This paper recommends that future work is performed to establish the weights of each criteria and sub-criteria within the framework. This should then be followed by establishing industry’s perceptions of the best and worst alternatives for moving freight within the Atlantic Gateway.

Increasing the attractiveness of a railway transport system requires improving accessibility to train stations. In particular, it means promoting environmentally friendly access modes and implementing a management policy of parking offer.Understanding how people reach railway stations is a key challenge for authorities to identify the levers for action. International scientific work has analyzed access travels to stations according to individuals' characteristics, access distances, levels of transport services including parking offer, and station environment. However, these research studies are not representative of French behaviors, which are not well known.This paper aims to qualify the potential link between access modes to French railway stations, rail service level and spatial environment of stations. It presents an assessment of the modal shares of access travel to French stations according to their profile (transport and urban profiles). This evaluation provides a methodological approach for local authorities to support accessibility issues of local railway stations, without needing to carry out field surveys.