Pub Date : 2025-03-20DOI: 10.1016/j.tbs.2025.101021
Hang Su, Xiaolei Wang, Min Xu, Xiaoning Zhang
In densely populated urban areas, the spatiotemporal dynamics of public and private transportation lead to intensified competition for limited road space, especially during mass gathering events. To address this issue, we propose an optimal design for a bi-modal transport system that integrates e-hailing and bus services, balancing efficiency, economy, and safety. By incorporating traffic dynamics through Macroscopic Fundamental Diagrams (MFDs) in a bi-modal transport system, we capture variations in traffic flow and passenger behavior. At an aggregate level, the total generalized cost is modeled to include perceived trip costs, operating costs, and safety costs, which fluctuate according to time-varying traffic flow patterns. Through dynamic simulations, we evaluate four boarding space design scenarios. The results show that incorporating e-hailing services into large-scale events increases the complexity of dynamics and the risk of pedestrian accidents in a bi-modal transport system, adding safety costs for passengers. However, by designing separate boarding spaces for each mode, safety costs are significantly reduced, lowering the total costs. This also leads to a substantial reduction in the average cost of e-hailing trips. These findings provide valuable decision support for planning urban boarding spaces, improving service quality, and managing traffic congestion.
{"title":"Boarding space design for passenger evacuation with bus and e-hailing services under a surge in traffic demand","authors":"Hang Su, Xiaolei Wang, Min Xu, Xiaoning Zhang","doi":"10.1016/j.tbs.2025.101021","DOIUrl":"https://doi.org/10.1016/j.tbs.2025.101021","url":null,"abstract":"In densely populated urban areas, the spatiotemporal dynamics of public and private transportation lead to intensified competition for limited road space, especially during mass gathering events. To address this issue, we propose an optimal design for a bi-modal transport system that integrates e-hailing and bus services, balancing efficiency, economy, and safety. By incorporating traffic dynamics through Macroscopic Fundamental Diagrams (MFDs) in a bi-modal transport system, we capture variations in traffic flow and passenger behavior. At an aggregate level, the total generalized cost is modeled to include perceived trip costs, operating costs, and safety costs, which fluctuate according to time-varying traffic flow patterns. Through dynamic simulations, we evaluate four boarding space design scenarios. The results show that incorporating e-hailing services into large-scale events increases the complexity of dynamics and the risk of pedestrian accidents in a bi-modal transport system, adding safety costs for passengers. However, by designing separate boarding spaces for each mode, safety costs are significantly reduced, lowering the total costs. This also leads to a substantial reduction in the average cost of e-hailing trips. These findings provide valuable decision support for planning urban boarding spaces, improving service quality, and managing traffic congestion.","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"33 1","pages":""},"PeriodicalIF":5.2,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143672828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-19DOI: 10.1016/j.tbs.2025.101027
João Filipe Teixeira, Hudyeron Rocha, António Couto
As a consequence of the several negative externalities associated with car usage, there is a growing pressure to promote more sustainable mobility habits through supporting transport alternatives. An increasingly attractive solution is the concept of intermodal mobility, i.e., the combination of different modes of transport in a single trip, leveraging the strengths of each mode to provide a more sustainable and efficient transport option.
{"title":"Intermodal mobility: A psychometric and behavioural analysis of public transport users in Porto Metropolitan Area","authors":"João Filipe Teixeira, Hudyeron Rocha, António Couto","doi":"10.1016/j.tbs.2025.101027","DOIUrl":"https://doi.org/10.1016/j.tbs.2025.101027","url":null,"abstract":"As a consequence of the several negative externalities associated with car usage, there is a growing pressure to promote more sustainable mobility habits through supporting transport alternatives. An increasingly attractive solution is the concept of intermodal mobility, i.e., the combination of different modes of transport in a single trip, leveraging the strengths of each mode to provide a more sustainable and efficient transport option.","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"27 1","pages":""},"PeriodicalIF":5.2,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143672830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-18DOI: 10.1016/j.tbs.2025.101016
Furqan A. Bhat, Ashish Verma
In spite of many countries pushing for electrification of their mobilities by incentivising buyers and manufacturers, penetration rates of electric vehicles are still very less and hence, the electric vehicles represent only a minor proportion of aggregate motorised vehicles. Thus, for fruitful penetration of electric vehicles in developing economies such as India, this study analyses the factors affecting the adoption behaviour of electric vehicles using novel first and second order structural equation models developed based on a modified framework from the behavioural reasoning theory and the valence framework. Unlike the previous studies where the focus has been on certain target groups, this study uses data collected from 1243 “potential electric car buyers” of Bengaluru, India to study the influence of socio-demographic variables and certain latent factors viz. environmental enthusiasm, social values, technological enthusiasm, monetary benefits, environmental benefits, lack of infrastructural readiness, perceived fee, and perceived risks on consumers’ intention to adopt electric four-wheelers. The results reveal environmental enthusiasm, social image, technological enthusiasm, monetary benefits, and environmental benefits to have significant positive impact on electric vehicle adoption intention while perceived fee, perceived risks, and the lack of infrastructural readiness are found to hinder the adoption of electric vehicles. Moreover, socio-demographic variables are also found to be significant determinants of electric vehicle adoption behaviour. This study provides some very important implications for policy and decision makers that can help in widespread adoption of electric vehicles.
{"title":"What drives the adoption of electric four-wheelers in India? An investigation of the reasons for and against","authors":"Furqan A. Bhat, Ashish Verma","doi":"10.1016/j.tbs.2025.101016","DOIUrl":"10.1016/j.tbs.2025.101016","url":null,"abstract":"<div><div>In spite of many countries pushing for electrification of their mobilities by incentivising buyers and manufacturers, penetration rates of electric vehicles are still very less and hence, the electric vehicles represent only a minor proportion of aggregate motorised vehicles. Thus, for fruitful penetration of electric vehicles in developing economies such as India, this study analyses the factors affecting the adoption behaviour of electric vehicles using novel first and second order structural equation models developed based on a modified framework from the behavioural reasoning theory and the valence framework. Unlike the previous studies where the focus has been on certain target groups, this study uses data collected from 1243 “potential electric car buyers” of Bengaluru, India to study the influence of socio-demographic variables and certain latent factors viz. environmental enthusiasm, social values, technological enthusiasm, monetary benefits, environmental benefits, lack of infrastructural readiness, perceived fee, and perceived risks on consumers’ intention to adopt electric four-wheelers. The results reveal environmental enthusiasm, social image, technological enthusiasm, monetary benefits, and environmental benefits to have significant positive impact on electric vehicle adoption intention while perceived fee, perceived risks, and the lack of infrastructural readiness are found to hinder the adoption of electric vehicles. Moreover, socio-demographic variables are also found to be significant determinants of electric vehicle adoption behaviour. This study provides some very important implications for policy and decision makers that can help in widespread adoption of electric vehicles.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"40 ","pages":"Article 101016"},"PeriodicalIF":5.1,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143642730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-18DOI: 10.1016/j.tbs.2025.101023
Adir Solomon , Johannes De Smedt , Monique Snoeck
Digital navigation services are extensively employed to provide travelers with recommendations for reaching their destinations. However, most current navigation services primarily focus on time and distance when suggesting routes, neglecting the consideration of the value of travel time (VTT). VTT represents a mobility paradigm that recognizes travel time as an opportunity for various activities, such as work tasks or leisurely pursuits like listening to music. The incorporation of VTT facilitates the provision of personalized recommendations tailored to travelers’ individual preferences. In this study, we assess travelers’ VTT using four distinct elements: paid work, personal tasks, enjoyment, and fitness. To infer VTT, we propose an innovative approach that fuses features extracted from different contexts, including physical conditions (e.g., weather) and traveler attributes (e.g., gender, age). These extracted features are then input into our suggested machine learning framework, which comprises boosted decision trees and deep learning Transformers. The results demonstrate that our framework provides the most accurate VTT predictions when compared to traditional machine learning models and rule-based baselines. Additionally, the analysis of travelers’ VTT predictions reveals several intriguing patterns that contribute to a better understanding of their decision-making process when selecting a travel route.
{"title":"Inferring travel time preferences through a contextual feature fusion approach","authors":"Adir Solomon , Johannes De Smedt , Monique Snoeck","doi":"10.1016/j.tbs.2025.101023","DOIUrl":"10.1016/j.tbs.2025.101023","url":null,"abstract":"<div><div>Digital navigation services are extensively employed to provide travelers with recommendations for reaching their destinations. However, most current navigation services primarily focus on time and distance when suggesting routes, neglecting the consideration of the value of travel time (VTT). VTT represents a mobility paradigm that recognizes travel time as an opportunity for various activities, such as work tasks or leisurely pursuits like listening to music. The incorporation of VTT facilitates the provision of personalized recommendations tailored to travelers’ individual preferences. In this study, we assess travelers’ VTT using four distinct elements: paid work, personal tasks, enjoyment, and fitness. To infer VTT, we propose an innovative approach that fuses features extracted from different contexts, including physical conditions (e.g., weather) and traveler attributes (e.g., gender, age). These extracted features are then input into our suggested machine learning framework, which comprises boosted decision trees and deep learning Transformers. The results demonstrate that our framework provides the most accurate VTT predictions when compared to traditional machine learning models and rule-based baselines. Additionally, the analysis of travelers’ VTT predictions reveals several intriguing patterns that contribute to a better understanding of their decision-making process when selecting a travel route.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"40 ","pages":"Article 101023"},"PeriodicalIF":5.1,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143642731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-17DOI: 10.1016/j.tbs.2025.100986
Jason Soria , Seung Eun Choi , Xinyi Wang , Patricia L. Mokhtarian
As restrictions eased coming out of the COVID-19 pandemic, travel behavior began settling into a “new normal”, due in large measure to trends in internet-based activities. Growth in teleworking, grocery delivery, and online retail during the pandemic has changed how people travel. The relationships between teleworking, activity engagement, household characteristics, personal attitudes, and expectations toward travel as the pandemic wound down invite rigorous investigation. Importantly, changes in work and non-commute activity engagement may signal the need for significant policy considerations. While many studies have focused on the adoption of teleworking, with its direct impacts on commute travel, this research investigates non-commute travel, specifically by car. Using data collected from three North American regions in the summer of 2022 (N = 2,108), we develop a latent class choice model to examine the factors associated with workers’ expectations to decrease, keep the same, or increase non-commute travel by car “as the pandemic continues to wind down”. We find diverging impacts of explanatory variables on non-commute travel expectations between the two latent classes identified. Specifically, we find that teleworking, online and in-person activity frequency, residential location, and household characteristics have different, and nearly opposite, impacts on future non-commute travel when controlling for survey respondents’ attitudes toward travel.
{"title":"What kinds of people expect to travel by car more, or less, for non-commute purposes in the post-pandemic era? A latent class approach","authors":"Jason Soria , Seung Eun Choi , Xinyi Wang , Patricia L. Mokhtarian","doi":"10.1016/j.tbs.2025.100986","DOIUrl":"10.1016/j.tbs.2025.100986","url":null,"abstract":"<div><div>As restrictions eased coming out of the COVID-19 pandemic, travel behavior began settling into a “new normal”, due in large measure to trends in internet-based activities. Growth in teleworking, grocery delivery, and online retail during the pandemic has changed how people travel. The relationships between teleworking, activity engagement, household characteristics, personal attitudes, and expectations toward travel as the pandemic wound down invite rigorous investigation. Importantly, changes in work and non-commute activity engagement may signal the need for significant policy considerations. While many studies have focused on the adoption of teleworking, with its direct impacts on <em>commute</em> travel, this research investigates <em>non-commute</em> travel, specifically by car. Using data collected from three North American regions in the summer of 2022 (N = 2,108), we develop a latent class choice model to examine the factors associated with workers’ expectations to decrease, keep the same, or increase non-commute travel by car “as the pandemic continues to wind down”. We find diverging impacts of explanatory variables on non-commute travel expectations between the two latent classes identified. Specifically, we find that teleworking, online and in-person activity frequency, residential location, and household characteristics have different, and nearly opposite, impacts on future non-commute travel when controlling for survey respondents’ attitudes toward travel.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"40 ","pages":"Article 100986"},"PeriodicalIF":5.1,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143642729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-17DOI: 10.1016/j.tbs.2025.101022
Fuad Yasin Huda , Graham Currie , Allan Pimenta , Liton Md Kamruzzaman
The Driverless Car (DC) has the potential to revolutionize the mode choice behaviour of downtown or CBD (Central Business District) commuters. This group generally experience high parking costs, which can potentially be eliminated due to the self-parking capabilities of DCs to access free-parking zones. However, it is unclear how this will impact mode switch behaviour in the DC era, and particularly, how current parking payment mechanisms (self vs. employer paid) will interact with future mode switch behaviour. This paper addresses these gaps by collecting and analysing data from 528 Melbourne CBD car commuters. Results from panel logistic regression indicate that on aggregate, 54% car commuters would opt to DC commuting. However, this proportion increases to 61% among self-paid parking commuters but drops to 47.6% for those with employer-paid parking, indicating a significant association between current parking payment arrangements and future intentions to use DCs for CBD commutes. Regression results show that travel cost, parking payment arrangement, individuals place of residence, DC demonstration approach and the degree of DC awareness have statistically significant impact on mode switch decision. Results will assist transport practitioners and legislators in understanding the association between parking payment arrangements and mode switch behaviour, along with the factors influencing this mode switch. This insight will also help policy advisors to plan in advance proactive travel demand and parking management planning with DCs in CBDs.
{"title":"Self vs employer paid parking impact on mode choice – The Melbourne downtown commute in an era of driverless cars","authors":"Fuad Yasin Huda , Graham Currie , Allan Pimenta , Liton Md Kamruzzaman","doi":"10.1016/j.tbs.2025.101022","DOIUrl":"10.1016/j.tbs.2025.101022","url":null,"abstract":"<div><div>The Driverless Car (DC) has the potential to revolutionize the mode choice behaviour of downtown or CBD (Central Business District) commuters. This group generally experience high parking costs, which can potentially be eliminated due to the self-parking capabilities of DCs to access free-parking zones. However, it is unclear how this will impact mode switch behaviour in the DC era, and particularly, how current parking payment mechanisms (self vs. employer paid) will interact with future mode switch behaviour. This paper addresses these gaps by collecting and analysing data from 528 Melbourne CBD car commuters. Results from panel logistic regression indicate that on aggregate, 54% car commuters would opt to DC commuting. However, this proportion increases to 61% among self-paid parking commuters but drops to 47.6% for those with employer-paid parking, indicating a significant association between current parking payment arrangements and future intentions to use DCs for CBD commutes. Regression results show that travel cost, parking payment arrangement, individuals place of residence, DC demonstration approach and the degree of DC awareness have statistically significant impact on mode switch decision. Results will assist transport practitioners and legislators in understanding the association between parking payment arrangements and mode switch behaviour, along with the factors influencing this mode switch. This insight will also help policy advisors to plan in advance proactive travel demand and parking management planning with DCs in CBDs.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"40 ","pages":"Article 101022"},"PeriodicalIF":5.1,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143642728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-13DOI: 10.1016/j.tbs.2025.101001
Filippos Adamidis, Christelle Al Haddad, Mohamed Abouelela, Constantinos Antoniou
The increasing use of private automobiles in cities has been linked with negative environmental effects, accidents and public space misuse. Several mitigation measures have been proposed, and fewer have been implemented, aiming to push drivers from using cars or to attract them to alternative modes of transport. This study overcomes literature gaps by developing a mode choice model that incorporates owned, public and shared modes under bundles of car-reducing measures, aspiring to achieve a shift from private cars towards modes with milder externalities, while also accounting for attitudinal factors. For this purpose, an online survey was conducted in Munich, Germany, collecting information about the respondents’ choices with car use constraints, their current travel behaviour, their sociodemographic characteristics and attitudes towards car ownership and the environment. Using exploratory factor analysis (EFA) and hybrid choice modelling (HCM), we determined that mode choices are not only influenced by the attributes of the modes but also by the personal characteristics of the respondents, their underlying attitudes and long-term mobility decisions. The obtained model was applied to a sensitivity analysis highlighting the proposed measures’ potential to reduce the share of private cars. The results revealed that improving conditions for active mobility and reducing the speed limit for road traffic could yield the highest reduction in private car use among the proposed measures. This study could have important behavioural implications for policymakers and lays the ground for an extensive simulation-based policy assessment.
{"title":"Mode choices under car-reducing scenarios: Measurable factors and latent attitudes","authors":"Filippos Adamidis, Christelle Al Haddad, Mohamed Abouelela, Constantinos Antoniou","doi":"10.1016/j.tbs.2025.101001","DOIUrl":"10.1016/j.tbs.2025.101001","url":null,"abstract":"<div><div>The increasing use of private automobiles in cities has been linked with negative environmental effects, accidents and public space misuse. Several mitigation measures have been proposed, and fewer have been implemented, aiming to push drivers from using cars or to attract them to alternative modes of transport. This study overcomes literature gaps by developing a mode choice model that incorporates owned, public and shared modes under <em>bundles</em> of car-reducing measures, aspiring to achieve a shift from private cars towards modes with milder externalities, while also accounting for attitudinal factors. For this purpose, an online survey was conducted in Munich, Germany, collecting information about the respondents’ choices with car use constraints, their current travel behaviour, their sociodemographic characteristics and attitudes towards car ownership and the environment. Using exploratory factor analysis (EFA) and hybrid choice modelling (HCM), we determined that mode choices are not only influenced by the attributes of the modes but also by the personal characteristics of the respondents, their underlying attitudes and long-term mobility decisions. The obtained model was applied to a sensitivity analysis highlighting the proposed measures’ potential to reduce the share of private cars. The results revealed that improving conditions for active mobility and reducing the speed limit for road traffic could yield the highest reduction in private car use among the proposed measures. This study could have important behavioural implications for policymakers and lays the ground for an extensive simulation-based policy assessment.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"40 ","pages":"Article 101001"},"PeriodicalIF":5.1,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143610181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Compared to hurricane evacuation travel, considerably less is known about travel by those who remain in the at-risk area and experience utility/infrastructure disruptions. How do people adapt their activities/travels in the aftermath especially with the impact of a power outage at home? With data collected after Hurricane Irma (2017), this study focuses on understanding commuters’ and non-workers’ activity participation and the interrelationships among those activities, by testing the significance of variables typically used in activity-based travel demand modeling studies. Its purpose is to compare the modeling results with those from past studies made in normal situations so that potential behavior changes (reflected by the parameter significance) can be observed. This study employs structural equation modeling (SEM) to capture the complex interrelationships among activities. Two major findings from this study are that (1) people are more likely to engage in multiple out-of-home discretionary activities (include dining, social visits, and leisure activities) during a hurricane-induced power outage at home and (2) commuters provided with flexible working arrangements (such as telecommuting) are more likely to work a shorter day during the period. Increased out-of-home discretionary activity participation and decreased working duration are likely to cause activity/trip pattern changes from an aggregate view. Such changes can affect the decision-making of public agencies, such as the priority placed on different locations for debris removal and power restoration. This study serves as a starting point and contributes to future studies making more in-depth investigations into post-impact travel and travel during infrastructure disruptions.
{"title":"Out-of-home activity adaptations of commuters and non-workers to the power outage at home induced by hurricane Irma","authors":"Ruijie “Rebecca” Bian , Pamela Murray-Tuite , Kris Wernstedt , Seth Guikema","doi":"10.1016/j.tbs.2025.101017","DOIUrl":"10.1016/j.tbs.2025.101017","url":null,"abstract":"<div><div>Compared to hurricane evacuation travel, considerably less is known about travel by those who remain in the at-risk area and experience utility/infrastructure disruptions. How do people adapt their activities/travels in the aftermath especially with the impact of a power outage at home? With data collected after Hurricane Irma (2017), this study focuses on understanding commuters’ and non-workers’ activity participation and the interrelationships among those activities, by testing the significance of variables typically used in activity-based travel demand modeling studies. Its purpose is to compare the modeling results with those from past studies made in normal situations so that potential behavior changes (reflected by the parameter significance) can be observed. This study employs structural equation modeling (SEM) to capture the complex interrelationships among activities. Two major findings from this study are that (1) people are more likely to engage in multiple out-of-home discretionary activities (include dining, social visits, and leisure activities) during a hurricane-induced power outage at home and (2) commuters provided with flexible working arrangements (such as telecommuting) are more likely to work a shorter day during the period. Increased out-of-home discretionary activity participation and decreased working duration are likely to cause activity/trip pattern changes from an aggregate view. Such changes can affect the decision-making of public agencies, such as the priority placed on different locations for debris removal and power restoration. This study serves as a starting point and contributes to future studies making more in-depth investigations into post-impact travel and travel during infrastructure disruptions.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"40 ","pages":"Article 101017"},"PeriodicalIF":5.1,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143610183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-11DOI: 10.1016/j.tbs.2025.101018
Bogdan Kapatsila , Dea van Lierop , Francisco J. Bahamonde Birke , Emily Grisé
Public transit crowding has a significant influence on riders’ satisfaction and needs to be tackled using both demand and supply management approaches. In this study, we focus on the policy response to public transit crowding using various customer incentive schemes. By analyzing data from a stated preference survey collected in Metro Vancouver, Canada, during the COVID-19 pandemic, we identified the differences in preferences for various incentive schemes on public transit and assessed the relationship between the riders’ eagerness to modify their travel patterns in response to crowding and the likelihood to respond to incentives that influence them to do the same. Our findings suggest that people who favor incentives tend to be more likely to change their travel behavior in response to crowding and that incentives that reduce the cost of travel on public transit have more potential to shift riders’ travel time, while other incentives (like participation in a raffle, or smartphone game points) have a more pronounced effect on the decision to travel via a less crowded public transit route. Demographic-specific preferences for various incentive schemes were also identified; for example, individuals in the 20–34 age group were found to be more likely to respond to incentives, while full-time workers had a lower propensity to do that. The findings of this study are aimed at public transit agencies interested in employing policy instruments to manage transit crowding and researchers seeking to advance the knowledge about the influence of personal preferences on travel behavior.
{"title":"The effect of incentives on the actions transit riders make in response to crowding","authors":"Bogdan Kapatsila , Dea van Lierop , Francisco J. Bahamonde Birke , Emily Grisé","doi":"10.1016/j.tbs.2025.101018","DOIUrl":"10.1016/j.tbs.2025.101018","url":null,"abstract":"<div><div>Public transit crowding has a significant influence on riders’ satisfaction and needs to be tackled using both demand and supply management approaches. In this study, we focus on the policy response to public transit crowding using various customer incentive schemes. By analyzing data from a stated preference survey collected in Metro Vancouver, Canada, during the COVID-19 pandemic, we identified the differences in preferences for various incentive schemes on public transit and assessed the relationship between the riders’ eagerness to modify their travel patterns in response to crowding and the likelihood to respond to incentives that influence them to do the same. Our findings suggest that people who favor incentives tend to be more likely to change their travel behavior in response to crowding and that incentives that reduce the cost of travel on public transit have more potential to shift riders’ travel time, while other incentives (like participation in a raffle, or smartphone game points) have a more pronounced effect on the decision to travel via a less crowded public transit route. Demographic-specific preferences for various incentive schemes were also identified; for example, individuals in the 20–34 age group were found to be more likely to respond to incentives, while full-time workers had a lower propensity to do that. The findings of this study are aimed at public transit agencies interested in employing policy instruments to manage transit crowding and researchers seeking to advance the knowledge about the influence of personal preferences on travel behavior.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"40 ","pages":"Article 101018"},"PeriodicalIF":5.1,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143592225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-10DOI: 10.1016/j.tbs.2025.100992
Hao Yin , Elisabetta Cherchi
This paper presents a study on cross-national heterogeneity between the UK and China in the preferences for Automated Taxis (ATs) and its determinants. A stated choice survey (including level of service, in-vehicle features and social conformity attributes) and a set of psychological statements (to measure trust, hedonic motivation and injunctive norms) were designed and distributed in both countries. Hybrid choice models were estimated to jointly quantify the effects of both objective and psychological factors after controlling for scale. Results confirm strong heterogeneity between the UK and China in the preference for AT and its determinants, also after controlling for differences in individual-related characteristics. Other than travel time and cost, our results confirm the importance of waiting time also in the choice of AT and show the importance of new elements such as in-vehicle features, customer reviews and to less extent the number of customers. Significant heterogeneity is found between the UK and China in all these elements with the exception of in-vehicle features. Among the three latent variables analysed, trust emerges as the most significantly different. The impact of trust in the UK is four times higher than in China, whereas the impact of hedonic motivation is roughly twice as large and the impact of injunctive norms is the same. The marginal rate of substitution suggests that policies aiming at targeting latent constructs might be more effective in the UK than in China.
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