Pub Date : 2025-12-26DOI: 10.1016/j.tbs.2025.101213
Jens Kandt , Hong Deng , Michelle M. Porter
We examine older adults’ leisure activities and mobility needs in one of the most automobile dependent regions in the Global North, the Canadian prairies. The motivation is to identify chances of independent ageing and sustainable travel as the region undergoes demographic transition while being subject to increased risk of extreme weather events that disrupt mobility. Using the Canadian Longitudinal Study on Ageing (CLSA), we identify six groups having different profiles of out-of-home leisure activities that seem to be essential to social connectedness and well-being. We analyse to which extent these practices depend on driving and digital technologies. We identify two groups who show strong signs of transport-related social exclusion. These groups do not benefit from digital technology and are subject to a dual mobility and digital divide that is exacerbated in the context of strong automobile dependence. Policy solutions need to be built on a holistic perspective involving municipal planning, digital skill development, transit funding and adaptation measures. Technological solutions, notably autonomous services, are likely to play a minor role in addressing pressing challenges in the Canadian prairies.
{"title":"Independent ageing, climate risks and automobile dependence in the Canadian prairies: Evidence from the Canadian Longitudinal Study on Aging","authors":"Jens Kandt , Hong Deng , Michelle M. Porter","doi":"10.1016/j.tbs.2025.101213","DOIUrl":"10.1016/j.tbs.2025.101213","url":null,"abstract":"<div><div>We examine older adults’ leisure activities and mobility needs in one of the most automobile dependent regions in the Global North, the Canadian prairies. The motivation is to identify chances of independent ageing and sustainable travel as the region undergoes demographic transition while being subject to increased risk of extreme weather events that disrupt mobility. Using the Canadian Longitudinal Study on Ageing (CLSA), we identify six groups having different profiles of out-of-home leisure activities that seem to be essential to social connectedness and well-being. We analyse to which extent these practices depend on driving and digital technologies. We identify two groups who show strong signs of transport-related social exclusion. These groups do not benefit from digital technology and are subject to a dual mobility and digital divide that is exacerbated in the context of strong automobile dependence. Policy solutions need to be built on a holistic perspective involving municipal planning, digital skill development, transit funding and adaptation measures. Technological solutions, notably autonomous services, are likely to play a minor role in addressing pressing challenges in the Canadian prairies.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"43 ","pages":"Article 101213"},"PeriodicalIF":5.7,"publicationDate":"2025-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145839638","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 : 2025-12-25DOI: 10.1016/j.tbs.2025.101219
Zhiyuan Sun , Rui Sun , Zehao Wang , Pengpeng Jiao , Yunxuan Li , Jianyu Wang , Huapu Lu
Individuals’ preferences for connecting transport choice at high-speed rail station have evolved during COVID-19, further resulting in new dynamics after COVID-19. Understanding the shifts in the factors influencing connecting transport choice is vital for effective passenger flow evacuation. However, the influence of most factors is heterogeneous, indicating that these factors exert varying impact under different conditions. This phenomenon presents a challenge in accurately capturing these shifts and developing precise countermeasures designed to promote specific modes of connecting transport. Therefore, this study aimed to investigate the context-dependent effects of factors exhibiting heterogeneity in order to elucidate the underlying causes of heterogeneity and to determine the specific impacts of these factors. Taking Beijing South Railway Station, China, as a case study, two cross-sectional surveys were conducted utilizing an identical questionnaire: one during the pandemic and another following its resolution. Then, an enhanced interpretable machine learning framework based on partially constrained temporal modeling approach was developed to elucidate the context-dependent effects while examining the shifts in these effects. Results show that seven factors marked during COVID-19, as well as fifteen factors marked after COVID-19, were retained by feature selection. Among these factors, paymode, carrying luggage, and distance from the station to the intended destination in Beijing emerged simultaneously during and after the COVID-19 pandemic, indicating that these particular factors emerged as important influences on connecting transport choice than others. Furthermore, it was noted that the effects of six factors demonstrated heterogeneity; specifically, one factor stood out particularly during the COVID-19, while five others were identified after the COVID-19. This suggests that in the post-pandemic era, the influence of various factors on connecting transport choice exhibits distinct characteristics across different conditions.
{"title":"Rethinking the context dependent effects of factors on connecting transport choice at high-speed rail station: Evidence from two cross-sectional surveys during and after COVID-19 pandemic","authors":"Zhiyuan Sun , Rui Sun , Zehao Wang , Pengpeng Jiao , Yunxuan Li , Jianyu Wang , Huapu Lu","doi":"10.1016/j.tbs.2025.101219","DOIUrl":"10.1016/j.tbs.2025.101219","url":null,"abstract":"<div><div>Individuals’ preferences for connecting transport choice at high-speed rail station have evolved during COVID-19, further resulting in new dynamics after COVID-19. Understanding the shifts in the factors influencing connecting transport choice is vital for effective passenger flow evacuation. However, the influence of most factors is heterogeneous, indicating that these factors exert varying impact under different conditions. This phenomenon presents a challenge in accurately capturing these shifts and developing precise countermeasures designed to promote specific modes of connecting transport. Therefore, this study aimed to investigate the context-dependent effects of factors exhibiting heterogeneity in order to elucidate the underlying causes of heterogeneity and to determine the specific impacts of these factors. Taking Beijing South Railway Station, China, as a case study, two cross-sectional surveys were conducted utilizing an identical questionnaire: one during the pandemic and another following its resolution. Then, an enhanced interpretable machine learning framework based on partially constrained temporal modeling approach was developed to elucidate the context-dependent effects while examining the shifts in these effects. Results show that seven factors marked during COVID-19, as well as fifteen factors marked after COVID-19, were retained by feature selection. Among these factors, <em>paymode</em>, <em>carrying luggage</em>, and <em>distance from the station to the intended destination in Beijing</em> emerged simultaneously during and after the COVID-19 pandemic, indicating that these particular factors emerged as important influences on connecting transport choice than others. Furthermore, it was noted that the effects of six factors demonstrated heterogeneity; specifically, one factor stood out particularly during the COVID-19, while five others were identified after the COVID-19. This suggests that in the post-pandemic era, the influence of various factors on connecting transport choice exhibits distinct characteristics across different conditions.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"43 ","pages":"Article 101219"},"PeriodicalIF":5.7,"publicationDate":"2025-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145822770","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 : 2025-12-23DOI: 10.1016/j.tbs.2025.101217
Labib Azzouz , Christian Brand , Noel Cass , Ian Philips
E-cargo bikes (ECBs) can play a crucial role in the transition to sustainable transport. Existing research primarily focuses on ECBs in sharing schemes and urban delivery, with limited attention to domestic use. Most studies emphasize mode substitution, often overlooking motivations unique to ECBs and beyond-utility travel motivations. Critically, little is known about ECBs’ role in generating new travel demand. This study explores how ECBs generate new trips, focusing on individual and household motivations that extend beyond purely utilitarian purposes. Trials were conducted with 49 households across three cities: Leeds, Oxford, and Brighton. A mixed-methods approach was employed, emphasizing qualitative data from interviews and supplemented with quantitative insights from travel diaries.
Findings indicate that ECBs enhanced accessibility, leading to increased travel distance and frequency, and enabling travelers to ‘do more.’ Their capacity to transport children and bulky items unlocked induced and latent demand, facilitating trips that otherwise would not have occurred. Beyond utility, ECBs fostered new solo and family travel shaped by a range of intrinsic motivations. They promoted well-being, offered therapeutic outdoor experiences, disrupted daily routines, and supported personal growth, freedom, and autonomy. Caregivers particularly valued ECBs for the control, spontaneity, and flexibility they provided in managing complex household schedules. Parents’ and children’s enjoyment, curiosity, and sense of adventure encouraged additional travel, transforming routine journeys into playful and memorable family experiences. New ECB travel enhanced family bonding, strengthened intra-household cohesion, and increased children’s willingness to participate in activities that might otherwise have been resisted. Households used ECBs to cultivate sustainable travel identities, model pro-environmental behaviors, and instill active mobility norms in children.
The paper reframes induced demand and advances research on travel behavior and motivations. It provides valuable insights for policymakers, researchers, and societies, positioning ECBs as a distinct mode in the transition to sustainable mobility.
{"title":"Miles with smiles: the role of e-cargo bikes in facilitating new personal and family-oriented travel and relevant beyond-utility motivations","authors":"Labib Azzouz , Christian Brand , Noel Cass , Ian Philips","doi":"10.1016/j.tbs.2025.101217","DOIUrl":"10.1016/j.tbs.2025.101217","url":null,"abstract":"<div><div>E-cargo bikes (ECBs) can play a crucial role in the transition to sustainable transport. Existing research primarily focuses on ECBs in sharing schemes and urban delivery, with limited attention to domestic use. Most studies emphasize mode substitution, often overlooking motivations unique to ECBs and beyond-utility travel motivations. Critically, little is known about ECBs’ role in generating new travel demand. This study explores how ECBs generate new trips, focusing on individual and household motivations that extend beyond purely utilitarian purposes. Trials were conducted with 49 households across three cities: Leeds, Oxford, and Brighton. A mixed-methods approach was employed, emphasizing qualitative data from interviews and supplemented with quantitative insights from travel diaries.</div><div>Findings indicate that ECBs enhanced accessibility, leading to increased travel distance and frequency, and enabling travelers to ‘do more.’ Their capacity to transport children and bulky items unlocked induced and latent demand, facilitating trips that otherwise would not have occurred. Beyond utility, ECBs fostered new solo and family travel shaped by a range of intrinsic motivations. They promoted well-being, offered therapeutic outdoor experiences, disrupted daily routines, and supported personal growth, freedom, and autonomy. Caregivers particularly valued ECBs for the control, spontaneity, and flexibility they provided in managing complex household schedules. Parents’ and children’s enjoyment, curiosity, and sense of adventure encouraged additional travel, transforming routine journeys into playful and memorable family experiences. New ECB travel enhanced family bonding, strengthened intra-household cohesion, and increased children’s willingness to participate in activities that might otherwise have been resisted. Households used ECBs to cultivate sustainable travel identities, model pro-environmental behaviors, and instill active mobility norms in children.</div><div>The paper reframes induced demand and advances research on travel behavior and motivations. It provides valuable insights for policymakers, researchers, and societies, positioning ECBs as a distinct mode in the transition to sustainable mobility.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"43 ","pages":"Article 101217"},"PeriodicalIF":5.7,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145822774","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 : 2025-12-23DOI: 10.1016/j.tbs.2025.101214
Wenxiang Li , Bo Liu , Weiwei Liu , Yang Yang
The rapid growth of ride-hailing services has reshaped urban mobility but also intensified congestion, emissions, and car dependency, raising concerns about sustainability. The metro-integrated multimodal travel (MIMT), enabled by Mobility as a Service (MaaS) platforms, offers promising low-carbon alternatives by integrating metro systems with convenient access and egress modes such as ridesplitting, buses, cycling, and walking. This study aims to develop a pratical analytical framework to assess the substitution potential of MIMT for ride-hailing trips in the era of MaaS. First, a trip reconstruction method is proposed to generate ten types of MIMT alternatives under identical origin–destination (OD) conditions. Second, a multidimensional evaluation model is established to quantify substitution benefits by jointly considering cost savings, carbon emission reductions, and time delays. Third, an interpretable machine learning approach (CatBoost integrated with SHAP and PDP) is applied to identify the travel and built environment factors influencing substitution potential. A case study based on 837,503 ride-hailing trips in Shanghai indicates that 56.46 % of trips could feasibly be replaced by MIMT alternatives. On average, each substituted trip yields a comprehensive benefits of 13.83 CNY, comprising cost savings of 24.03 CNY and carbon emission reductions of 1.29 kg, at the cost of an average travel time increase of 17.51 min. The results further reveal that substitution potential is primarily driven by route nonlinearity, trip distance, and metro accessibility. Travel-related variables account for 61.11 % of explanatory power, while built environment features contribute the remaining 38.89 %. Sensitivity analyses demonstrate that travelers' transition from ride-hailing to MIMT is predominantly influenced by the value of time, with current carbon pricing exerting only a marginal effect. These findings highlight the role of MaaS in promoting multimodal integration and provide actionable insights for policymakers and platform operators to reduce ride-hailing dependency and advance low-carbon urban mobility.
{"title":"How can metro-integrated multimodal travel substitute for ride-hailing trips in the era of mobility as a service?","authors":"Wenxiang Li , Bo Liu , Weiwei Liu , Yang Yang","doi":"10.1016/j.tbs.2025.101214","DOIUrl":"10.1016/j.tbs.2025.101214","url":null,"abstract":"<div><div>The rapid growth of ride-hailing services has reshaped urban mobility but also intensified congestion, emissions, and car dependency, raising concerns about sustainability. The metro-integrated multimodal travel (MIMT), enabled by Mobility as a Service (MaaS) platforms, offers promising low-carbon alternatives by integrating metro systems with convenient access and egress modes such as ridesplitting, buses, cycling, and walking. This study aims to develop a pratical analytical framework to assess the substitution potential of MIMT for ride-hailing trips in the era of MaaS. First, a trip reconstruction method is proposed to generate ten types of MIMT alternatives under identical origin–destination (OD) conditions. Second, a multidimensional evaluation model is established to quantify substitution benefits by jointly considering cost savings, carbon emission reductions, and time delays. Third, an interpretable machine learning approach (CatBoost integrated with SHAP and PDP) is applied to identify the travel and built environment factors influencing substitution potential. A case study based on 837,503 ride-hailing trips in Shanghai indicates that 56.46 % of trips could feasibly be replaced by MIMT alternatives. On average, each substituted trip yields a comprehensive benefits of 13.83 CNY, comprising cost savings of 24.03 CNY and carbon emission reductions of 1.29 kg, at the cost of an average travel time increase of 17.51 min. The results further reveal that substitution potential is primarily driven by route nonlinearity, trip distance, and metro accessibility. Travel-related variables account for 61.11 % of explanatory power, while built environment features contribute the remaining 38.89 %. Sensitivity analyses demonstrate that travelers' transition from ride-hailing to MIMT is predominantly influenced by the value of time, with current carbon pricing exerting only a marginal effect. These findings highlight the role of MaaS in promoting multimodal integration and provide actionable insights for policymakers and platform operators to reduce ride-hailing dependency and advance low-carbon urban mobility.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"43 ","pages":"Article 101214"},"PeriodicalIF":5.7,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145822775","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 : 2025-12-20DOI: 10.1016/j.tbs.2025.101211
Zhenhua Li , Yi Lu , Jingjing Wang , Yihao Wu
The impact of rail transit infrastructure on residents’ travel satisfaction and subjective well-being has gained increasing attention among researchers and policymakers. However, few studies have used longitudinal data to analyze the causal effects of rail transit systems on travel satisfaction and its underlying mechanisms. This study employed a natural experiment approach, using two waves of survey data (2020 & 2021) from 422 participants in Wuhan, China, to assess the effects of a newly opened subway line on travel satisfaction. Applying a mixed-effects difference-in-differences (DID) method, we found that the new subway line significantly improved residents’ travel satisfaction after accounting for socio-demographic and travel attitude covariates. Mediation analysis revealed that this improvement was primarily driven by increased perceived accessibility to downtown and transit stops or stations, as well as a reduction in the number of out-of-home activities on weekends. Heterogeneous analysis indicated that the subway’s benefits are more pronounced among females, individuals under 60 years old, and those from middle-income households. These findings provide new causal evidence on the link between rail transit infrastructure and travel satisfaction, deepening our understanding of this complex relationship and offering practical insights for formulating strategies to improve urban residents’ quality of life.
{"title":"Rail transit and travel satisfaction: Evidence from a natural experiment in Wuhan","authors":"Zhenhua Li , Yi Lu , Jingjing Wang , Yihao Wu","doi":"10.1016/j.tbs.2025.101211","DOIUrl":"10.1016/j.tbs.2025.101211","url":null,"abstract":"<div><div>The impact of rail transit infrastructure on residents’ travel satisfaction and subjective well-being has gained increasing attention among researchers and policymakers. However, few studies have used longitudinal data to analyze the causal effects of rail transit systems on travel satisfaction and its underlying mechanisms. This study employed a natural experiment approach, using two waves of survey data (2020 & 2021) from 422 participants in Wuhan, China, to assess the effects of a newly opened subway line on travel satisfaction. Applying a mixed-effects difference-in-differences (DID) method, we found that the new subway line significantly improved residents’ travel satisfaction after accounting for socio-demographic and travel attitude covariates. Mediation analysis revealed that this improvement was primarily driven by increased perceived accessibility to downtown and transit stops or stations, as well as a reduction in the number of out-of-home activities on weekends. Heterogeneous analysis indicated that the subway’s benefits are more pronounced among females, individuals under 60 years old, and those from middle-income households. These findings provide new causal evidence on the link between rail transit infrastructure and travel satisfaction, deepening our understanding of this complex relationship and offering practical insights for formulating strategies to improve urban residents’ quality of life.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"43 ","pages":"Article 101211"},"PeriodicalIF":5.7,"publicationDate":"2025-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145789607","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 : 2025-12-18DOI: 10.1016/j.tbs.2025.101215
Zahid Hussain , Wael K.M. Alhajyaseen , Mohammad N.H. Naser , Qinaat Hussain , Charitha Dias , Miho Iryo-Asano
Despite growing global interest in e-scooters as micromobility solutions, limited research has explored factors influencing their adoption in car-dependent, high-income contexts with extreme summer climates. This study addresses this gap through nationwide web-based survey in Qatar, where high private vehicle dependency, summer temperatures exceeding 45 °C, and limited cycling infrastructure as well as limited cycling culture create unique challenges for micromobility integration. The final sample consisted of 2736 respondents (339 e-scooter users and 2397 non-users), capturing usage patterns, demographic information, and non-users’ perceptions of public acceptance and intention to use e-scooters. Among current users, e-scooters were predominantly used for leisure and commuting, with males and notably, individuals without driving licenses using them frequently. Usage patterns differed between ownership types, with shared/rental users predominantly using e-scooters for leisure, while owned e-scooter users primarily used them for commuting. To examine non-users’ perspectives, structural equation modeling was used to assess influence of different factors on usage intention and perceived public acceptance. Findings revealed that regulatory and infrastructure support, along with social influence and preference, were the most significant predictors, while cost and service quality barriers negatively influenced usage intention. Importantly, perceived public acceptance strongly influenced personal intention to use, demonstrating that social legitimacy substantially shapes adoption even in car-oriented contexts. Sociodemographic analysis revealed that car ownership and higher income negatively predicted adoption, while non-license holders, non-Arab residents, and employed individuals showed significantly higher adoption potential. These findings offer valuable insights for policymakers and urban planners in developing targeted interventions to promote safe and sustainable integration of e-scooters. Such interventions include improved infrastructure, effective regulations, competitive pricing, enhanced service quality, and community engagement initiatives. While grounded in Qatar’s context, these findings can be generalized to urban environments globally characterized by high motorization rates, cultural preferences for private vehicles, challenging climatic conditions, and infrastructure limitations.
{"title":"E-scooters in Qatar: Public perception, adoption intentions, and implications for urban mobility policy","authors":"Zahid Hussain , Wael K.M. Alhajyaseen , Mohammad N.H. Naser , Qinaat Hussain , Charitha Dias , Miho Iryo-Asano","doi":"10.1016/j.tbs.2025.101215","DOIUrl":"10.1016/j.tbs.2025.101215","url":null,"abstract":"<div><div>Despite growing global interest in e-scooters as micromobility solutions, limited research has explored factors influencing their adoption in car-dependent, high-income contexts with extreme summer climates. This study addresses this gap through nationwide web-based survey in Qatar, where high private vehicle dependency, summer temperatures exceeding 45 °C, and limited cycling infrastructure as well as limited cycling culture create unique challenges for micromobility integration. The final sample consisted of 2736 respondents (339 e-scooter users and 2397 non-users), capturing usage patterns, demographic information, and non-users’ perceptions of public acceptance and intention to use e-scooters. Among current users, e-scooters were predominantly used for leisure and commuting, with males and notably, individuals without driving licenses using them frequently. Usage patterns differed between ownership types, with shared/rental users predominantly using e-scooters for leisure, while owned e-scooter users primarily used them for commuting. To examine non-users’ perspectives, structural equation modeling was used to assess influence of different factors on usage intention and perceived public acceptance. Findings revealed that regulatory and infrastructure support, along with social influence and preference, were the most significant predictors, while cost and service quality barriers negatively influenced usage intention. Importantly, perceived public acceptance strongly influenced personal intention to use, demonstrating that social legitimacy substantially shapes adoption even in car-oriented contexts. Sociodemographic analysis revealed that car ownership and higher income negatively predicted adoption, while non-license holders, non-Arab residents, and employed individuals showed significantly higher adoption potential. These findings offer valuable insights for policymakers and urban planners in developing targeted interventions to promote safe and sustainable integration of e-scooters. Such interventions include improved infrastructure, effective regulations, competitive pricing, enhanced service quality, and community engagement initiatives. While grounded in Qatar’s context, these findings can be generalized to urban environments globally characterized by high motorization rates, cultural preferences for private vehicles, challenging climatic conditions, and infrastructure limitations.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"43 ","pages":"Article 101215"},"PeriodicalIF":5.7,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145786366","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 : 2025-12-17DOI: 10.1016/j.tbs.2025.101216
Ming Yao, Xinchun Lu, Shuchao Cao
Electric vehicles (EVs) play a pivotal role in advancing sustainable transportation, with ongoing improvements in driving range and charging infrastructure reshaping user expectations—shifting focus from basic functionality to enhanced service experience. Therefore, to examine EV users’ charging behavior, a comprehensive questionnaire survey was performed in this paper. Based on the discrete choice modeling, a Binary Logit (BL) model under the assumption of homogeneous user preferences, and a Latent Class Logit (LC) model considering the unobserved heterogeneity are established. Key findings reveal that charging decisions are significantly influenced by state of charge (SOC), pricing, queueing time, and station accessibility, reflecting user sensitivity to both economic and service-quality factors. Additionally, individual characteristics including age, risk aversion, and ownership of fixed charging locations exert substantial moderating effects. Willingness-to-pay (WTP) analysis further demonstrates that users prioritize service enhancements over mere cost reductions. The LC model delineates two distinct user segments: Class 1 (37.7 %), comprising younger, cost- and efficiency-driven early adopters (predominantly male), and Class 2 (62.3 %), characterized by older, risk-averse users (with higher female representation) who prioritize reliability and initiate charging at lower SOC to mitigate uncertainty. The results underscore the importance of integrating service experience and user heterogeneity into EV infrastructure planning, which provides actionable insights for policymakers and stakeholders to develop tailored, user-centric charging solutions.
{"title":"Modeling EV charging behavior: The impact of service experience and user heterogeneity","authors":"Ming Yao, Xinchun Lu, Shuchao Cao","doi":"10.1016/j.tbs.2025.101216","DOIUrl":"10.1016/j.tbs.2025.101216","url":null,"abstract":"<div><div>Electric vehicles (EVs) play a pivotal role in advancing sustainable transportation, with ongoing improvements in driving range and charging infrastructure reshaping user expectations—shifting focus from basic functionality to enhanced service experience. Therefore, to examine EV users’ charging behavior, a comprehensive questionnaire survey was performed in this paper. Based on the discrete choice modeling, a Binary Logit (BL) model under the assumption of homogeneous user preferences, and a Latent Class Logit (LC) model considering the unobserved heterogeneity are established. Key findings reveal that charging decisions are significantly influenced by state of charge (SOC), pricing, queueing time, and station accessibility, reflecting user sensitivity to both economic and service-quality factors. Additionally, individual characteristics including age, risk aversion, and ownership of fixed charging locations exert substantial moderating effects. Willingness-to-pay (WTP) analysis further demonstrates that users prioritize service enhancements over mere cost reductions. The LC model delineates two distinct user segments: Class 1 (37.7 %), comprising younger, cost- and efficiency-driven early adopters (predominantly male), and Class 2 (62.3 %), characterized by older, risk-averse users (with higher female representation) who prioritize reliability and initiate charging at lower SOC to mitigate uncertainty. The results underscore the importance of integrating service experience and user heterogeneity into EV infrastructure planning, which provides actionable insights for policymakers and stakeholders to develop tailored, user-centric charging solutions.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"43 ","pages":"Article 101216"},"PeriodicalIF":5.7,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145786069","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 : 2025-12-14DOI: 10.1016/j.tbs.2025.101168
Yantao Huang, Natalia Zuniga-Garcia, Kara M. Kockelman
This study assesses long-distance (LD) travel demand in near-future scenarios where automated vehicles (AVs) are easily available. Stated and revealed preference data were obtained from 1,004 American adults. The survey includes questions about general LD trip-making behavior with AVs, after investigating the possibility of using AVs to substitute for respondents’ recent LD trips (over 75-miles one-way) prior to the COVID-19 pandemic. After cleaning and weighting the responses, respondents’ willingness to use AVs for a past LD trip are shared, and their future travel behaviors with AVs are explored via statistical models. Ordered logit regression model results suggest AVs would increase the trip-making frequency of high-income households, households with more children, and young people who are part-time employed. The multinomial logit model for overnight stopping suggests that high-income travelers prefer staying overnight in hotels, while young and solo-drivers are expected to more often stay overnight in moving AVs. Mornings departures are preferred for LD travel - both with and without AVs, but some travelers shift to later departures when AVs become available, particularly those who are employed full-time and/or have more children in their household. Results of the mode choice model for mid-range LD travel (200 to 500 miles) suggest those who are unmarried and/or employed full time prefer AVs, while those over age 65 do not. Car and AV cost are the most practically significant variables impacting people’s mode choices, and aircraft and AVs are more appealing than human-driven vehicles for trips over 500 miles long.
{"title":"Long-distance travel impacts of automated vehicles: A survey of American households","authors":"Yantao Huang, Natalia Zuniga-Garcia, Kara M. Kockelman","doi":"10.1016/j.tbs.2025.101168","DOIUrl":"10.1016/j.tbs.2025.101168","url":null,"abstract":"<div><div>This study assesses long-distance (LD) travel demand in near-future scenarios where automated vehicles (AVs) are easily available. Stated and revealed preference data were obtained from 1,004 American adults. The survey includes questions about general LD trip-making behavior with AVs, after investigating the possibility of using AVs to substitute for respondents’ recent LD trips (over 75-miles one-way) prior to the COVID-19 pandemic. After cleaning and weighting the responses, respondents’ willingness to use AVs for a past LD trip are shared, and their future travel behaviors with AVs are explored via statistical models. Ordered logit regression model results suggest AVs would increase the trip-making frequency of high-income households, households with more children, and young people who are part-time employed. The multinomial logit model for overnight stopping suggests that high-income travelers prefer staying overnight in hotels, while young and solo-drivers are expected to more often stay overnight in moving AVs. Mornings departures are preferred for LD travel - both with and without AVs, but some travelers shift to later departures when AVs become available, particularly those who are employed full-time and/or have more children in their household. Results of the mode choice model for mid-range LD travel (200 to 500 miles) suggest those who are unmarried and/or employed full time prefer AVs, while those over age 65 do not. Car and AV cost are the most practically significant variables impacting people’s mode choices, and aircraft and AVs are more appealing than human-driven vehicles for trips over 500 miles long.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"43 ","pages":"Article 101168"},"PeriodicalIF":5.7,"publicationDate":"2025-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145759417","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 : 2025-12-13DOI: 10.1016/j.tbs.2025.101212
Anastasios Skoufas, Erik Jenelius
Public transportation (PT) plays a crucial role in catering to the mobility needs of school students. However, the disparities of PT travel characteristics among different socioeconomic groups have been underexplored. In this study, we explore disparities in PT usage, after-school activity participation, journey length, and on-board crowding among different socioeconomic groups as well as between different educational stages (primary, secondary). We specifically focus on home-to-school and school-to-activity PT journeys utilizing automated data sources (smart card data). Results from the case study of Region Stockholm show that travel time and crowding exposure vary across the case study area. Specifically, school students coming from areas with higher income levels, higher shares of cooperative housing, or lower vehicle ownership tend to need less time to travel to school. In terms of student categorization, secondary students with diverse socioeconomic backgrounds tend to travel longer to school compared to primary students. Concerning journeys to after-school activities using PT, results reveal that school students from areas with high vehicle ownership and education or lower employment levels, as well as students from suburban/rural areas, have lower odds of using PT. The findings can assist policy makers and PT agencies in designing more equitable and youth-friendly PT systems, improving access to schools and to after-school activity locations.
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Pub Date : 2025-12-11DOI: 10.1016/j.tbs.2025.101201
Zijian Yang , Guocong Zhai , N.N. Sze , Hongliang Ding , Nikolai Bobylev , Hongtai Yang
Numerous studies have examined the effectiveness of urban transportation planning policies such as park-and-ride, transit-oriented development, and multimodal transportation hubs in promoting public transit use. In the past decades, bike sharing, both dockless and docking systems, has been increasingly popular as a green transport mode, connecting to public transit. However, the influence of socioeconomic conditions, land-use factors, transport infrastructure, and station characteristics on bike-and-ride remains underexplored, particularly across different patterns of bike-and-ride. In this study, an integrated random forest (RF) and geographically weighted regression (GWR) model is applied to capture nonlinear relationships and spatial heterogeneity between bike-and-ride usage and explanatory variables, including socioeconomic variables, land-use factors, transportation infrastructure, and metro characteristics, based on the integrated bike sharing and metro ridership data in Chengdu, China. Additionally, a novel similarity metric, Dynamic Time Warping (DTW), is applied to classify the metro stations based on the temporal pattern of bike-and-ride trips at all stations. Hence, four clusters of metro stations with a varying pattern of bike-and-ride trips are established. The results show that the importance of determinants and their association with bike-and-ride vary significantly among different clusters of metro stations. This study proposes a fine-grained analytical framework for bike-and-ride, providing theoretical and empirical support for station function classification.
许多研究已经检验了城市交通规划政策的有效性，如停车换乘、交通导向发展和多式联运枢纽，以促进公共交通的使用。在过去的几十年里，共享单车作为一种连接公共交通的绿色交通方式，无论是无桩还是有坞系统，都越来越受欢迎。然而，社会经济条件、土地利用因素、交通基础设施和车站特征对自行车骑行的影响仍未得到充分探讨，特别是在不同的自行车骑行模式中。本文基于成都市共享单车和地铁出行数据，采用随机森林（RF）和地理加权回归（GWR）模型，分析了共享单车使用与社会经济变量、土地利用因子、交通基础设施和地铁特征等解释变量之间的非线性关系和空间异质性。在此基础上，提出了一种新的相似性度量——动态时间扭曲（Dynamic Time Warping， DTW），基于各车站的骑车出行时间模式对地铁站进行分类。因此，建立了四个具有不同模式的自行车和骑行的地铁站群。结果表明，在不同的地铁车站群中，决定因素的重要性及其与骑车出行的关系存在显著差异。本研究提出了自行车骑行的细粒度分析框架，为车站功能分类提供理论和实证支持。
{"title":"Exploring different patterns of bike-and-ride trips and influencing factors using geographically weighted random forest","authors":"Zijian Yang , Guocong Zhai , N.N. Sze , Hongliang Ding , Nikolai Bobylev , Hongtai Yang","doi":"10.1016/j.tbs.2025.101201","DOIUrl":"10.1016/j.tbs.2025.101201","url":null,"abstract":"<div><div>Numerous studies have examined the effectiveness of urban transportation planning policies such as park-and-ride, transit-oriented development, and multimodal transportation hubs in promoting public transit use. In the past decades, bike sharing, both dockless and docking systems, has been increasingly popular as a green transport mode, connecting to public transit. However, the influence of socioeconomic conditions, land-use factors, transport infrastructure, and station characteristics on bike-and-ride remains underexplored, particularly across different patterns of bike-and-ride. In this study, an integrated random forest (RF) and geographically weighted regression (GWR) model is applied to capture nonlinear relationships and spatial heterogeneity between bike-and-ride usage and explanatory variables, including socioeconomic variables, land-use factors, transportation infrastructure, and metro characteristics, based on the integrated bike sharing and metro ridership data in Chengdu, China. Additionally, a novel similarity metric, Dynamic Time Warping (DTW), is applied to classify the metro stations based on the temporal pattern of bike-and-ride trips at all stations. Hence, four clusters of metro stations with a varying pattern of bike-and-ride trips are established. The results show that the importance of determinants and their association with bike-and-ride vary significantly among different clusters of metro stations. This study proposes a fine-grained analytical framework for bike-and-ride, providing theoretical and empirical support for station function classification.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"43 ","pages":"Article 101201"},"PeriodicalIF":5.7,"publicationDate":"2025-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145731902","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}
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