Pub Date : 2026-01-09DOI: 10.1016/j.trd.2025.105195
Takuma Oda , Yuji Yoshimura
As climate extremes intensify, outdoor exposure in walkable cities becomes costly, increasing the reliance on door-to-door transportation. Using a multi-year dataset of app-based taxi trips from five Japanese metropolitan areas (2022–2024), we quantify behavioral adaptation to heat and rain. Above 27°C, ride-hailing demand increases near-linearly to 38% at 37°C, a pattern observed across all cities. This demand is strongest among infrequent users and for short-distance trips, particularly in high-density areas with poor transit access for first/last-mile connections. Hourly rainfall elicits a nearly identical response pattern, suggesting a general mobility adaptation mechanism. By translating the demand elasticity of short trips by infrequent users into a welfare metric, we map hidden “heat-mobility stress” hotspots around major rail hubs. Our findings show taxis are crucial buffers for urban mobility in extreme weather, with demand varying by user frequency, trip distance, and transit accessibility.
{"title":"Heat-driven taxi demand reveals hidden mobility stress in walkable cities","authors":"Takuma Oda , Yuji Yoshimura","doi":"10.1016/j.trd.2025.105195","DOIUrl":"10.1016/j.trd.2025.105195","url":null,"abstract":"<div><div>As climate extremes intensify, outdoor exposure in walkable cities becomes costly, increasing the reliance on door-to-door transportation. Using a multi-year dataset of app-based taxi trips from five Japanese metropolitan areas (2022–2024), we quantify behavioral adaptation to heat and rain. Above 27°C, ride-hailing demand increases near-linearly to 38% at 37°C, a pattern observed across all cities. This demand is strongest among infrequent users and for short-distance trips, particularly in high-density areas with poor transit access for first/last-mile connections. Hourly rainfall elicits a nearly identical response pattern, suggesting a general mobility adaptation mechanism. By translating the demand elasticity of short trips by infrequent users into a welfare metric, we map hidden “heat-mobility stress” hotspots around major rail hubs. Our findings show taxis are crucial buffers for urban mobility in extreme weather, with demand varying by user frequency, trip distance, and transit accessibility.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"153 ","pages":"Article 105195"},"PeriodicalIF":7.7,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145928581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2026-01-09DOI: 10.1016/j.trd.2025.105194
Xiatian Iogansen , Christina Gore , Joshua Kneifel , Sindhu Ranganath , John Paul Helveston
This study examines consumer perceptions, knowledge, and adoption patterns of battery electric vehicles (BEVs), using survey data from 1,443 U.S. residents. Findings reveal persistent informational and psychological barriers that hinder adoption among current non-adopters and challenge sustained use among current adopters. A binary logit model distinguishes BEV-only users and BEV-mixed-fuel users, uncovering distinct socio-demographic profiles, motivations, vehicle usage, and charging behaviors often obscured in aggregate analyses. BEV-only users are typically younger, urban, and price-sensitive, often lacking dedicated charging access, whereas mixed-fuel users place greater value on BEVs’ symbolic appeal and mitigate range concerns through access to conventional vehicles. A multinomial logit model of non-adopters shows that BEV-related perceptions, knowledge, incentives, infrastructure access, and personal traits affect adoption intentions in asymmetric ways. These findings highlight the need for flexible modeling and measurement of adoption to capture the complex and varied drivers of BEV resistance and uptake across different consumer groups.
{"title":"Consumers ’ perceptions, knowledge, and adoption patterns of battery electric vehicles","authors":"Xiatian Iogansen , Christina Gore , Joshua Kneifel , Sindhu Ranganath , John Paul Helveston","doi":"10.1016/j.trd.2025.105194","DOIUrl":"10.1016/j.trd.2025.105194","url":null,"abstract":"<div><div>This study examines consumer perceptions, knowledge, and adoption patterns of battery electric vehicles (BEVs), using survey data from 1,443 U.S. residents. Findings reveal persistent informational and psychological barriers that hinder adoption among current non-adopters and challenge sustained use among current adopters. A binary logit model distinguishes <em>BEV-only users</em> and <em>BEV-mixed-fuel users</em>, uncovering distinct socio-demographic profiles, motivations, vehicle usage, and charging behaviors often obscured in aggregate analyses. <em>BEV-only users</em> are typically younger, urban, and price-sensitive, often lacking dedicated charging access, whereas <em>mixed-fuel users</em> place greater value on BEVs’ symbolic appeal and mitigate range concerns through access to conventional vehicles. A multinomial logit model of non-adopters shows that BEV-related perceptions, knowledge, incentives, infrastructure access, and personal traits affect adoption intentions in asymmetric ways. These findings highlight the need for flexible modeling and measurement of adoption to capture the complex and varied drivers of BEV resistance and uptake across different consumer groups.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"153 ","pages":"Article 105194"},"PeriodicalIF":7.7,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145928582","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2026-01-09DOI: 10.1016/j.trd.2025.105203
Tianyu Zhang , Gongyuan Lu , Enjian Yao , Xiaobo Liu , Yang Yang
This study examines the potential application of battery swapping (BS) mode in the taxi industry by analyzing the deployment, decarbonization, economics, and transportation service pathways of taxi BS station (T-BSS) projects in various energy and economic scenarios. A comprehensive model is proposed that integrates multi-stage deployment planning with dynamic life-cycle assessment based on grasp, mapping, and quantification of the dynamic evolution of macro energy and economy. T-BSS projects in Tianjin from 0a to 30a are analyzed. The T-BSS project has a normalized carbon emission reduction of more than 90% by 30a, driven by the transformation of the transportation power structure in Deep and the development of battery energy consumption technology in Base/Fast. T-BSS projects demonstrate strong profitability, with 81.6% of 375 scenarios achieving an internal rate of return of more than 12%. However, they face risks, including declining profitability in later phases and substantial disparities in investment returns.
{"title":"Dynamic planning integrating life cycle assessment for taxi battery swapping stations","authors":"Tianyu Zhang , Gongyuan Lu , Enjian Yao , Xiaobo Liu , Yang Yang","doi":"10.1016/j.trd.2025.105203","DOIUrl":"10.1016/j.trd.2025.105203","url":null,"abstract":"<div><div>This study examines the potential application of battery swapping (BS) mode in the taxi industry by analyzing the deployment, decarbonization, economics, and transportation service pathways of taxi BS station (T-BSS) projects in various energy and economic scenarios. A comprehensive model is proposed that integrates multi-stage deployment planning with dynamic life-cycle assessment based on grasp, mapping, and quantification of the dynamic evolution of macro energy and economy. T-BSS projects in Tianjin from 0a to 30a are analyzed. The T-BSS project has a normalized carbon emission reduction of more than 90% by 30a, driven by the transformation of the transportation power structure in Deep and the development of battery energy consumption technology in Base/Fast. T-BSS projects demonstrate strong profitability, with 81.6% of 375 scenarios achieving an internal rate of return of more than 12%. However, they face risks, including declining profitability in later phases and substantial disparities in investment returns.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"153 ","pages":"Article 105203"},"PeriodicalIF":7.7,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145928580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2026-01-08DOI: 10.1016/j.trd.2025.105206
Femke Veerman , Dea van Lierop , Geneviève Boisjoly , Maria Laura Guerrero Balarezo , Martin Trépanier
While carsharing is used more by men than women, little is known about how gender shapes carsharing patterns. Accordingly, this study examines how gender shapes usage patterns. Using Montreal carsharing data, the study analyses distance, duration, and stops per reservation through descriptive statistics, regressions and gender-stratified models. Descriptive statistics show that women, compared to men, travel shorter distances, make fewer stops, yet spend more time per reservation. Multilevel regression analyses confirm these statistically significant gender differences. Women’s shorter distances and longer reservation times may lead to higher costs per kilometre under some pricing structures. Gender-stratified models reveal both gender-specific and shared patterns: women show varied suburban travel patterns, higher residential area income increases men’s distances compared to lower-income areas but has little effect on women’s distances, while both genders show similar temporal patterns. Findings underscore the need for continued research into equitable mobility systems across different contexts.
{"title":"Shared cars, gendered patterns: The case of Montréal, Canada","authors":"Femke Veerman , Dea van Lierop , Geneviève Boisjoly , Maria Laura Guerrero Balarezo , Martin Trépanier","doi":"10.1016/j.trd.2025.105206","DOIUrl":"10.1016/j.trd.2025.105206","url":null,"abstract":"<div><div>While carsharing is used more by men than women, little is known about how gender shapes carsharing patterns. Accordingly, this study examines how gender shapes usage patterns. Using Montreal carsharing data, the study analyses distance, duration, and stops per reservation through descriptive statistics, regressions and gender-stratified models. Descriptive statistics show that women, compared to men, travel shorter distances, make fewer stops, yet spend more time per reservation. Multilevel regression analyses confirm these statistically significant gender differences. Women’s shorter distances and longer reservation times may lead to higher costs per kilometre under some pricing structures. Gender-stratified models reveal both gender-specific and shared patterns: women show varied suburban travel patterns, higher residential area income increases men’s distances compared to lower-income areas but has little effect on women’s distances, while both genders show similar temporal patterns. Findings underscore the need for continued research into equitable mobility systems across different contexts.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"153 ","pages":"Article 105206"},"PeriodicalIF":7.7,"publicationDate":"2026-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145928579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2026-01-08DOI: 10.1016/j.trd.2025.105202
Shuojiang Xu , Kelin Zhu , Fangli Zeng , Min Guo , Benying Tan , Yiqing Tian
Maritime transport is a major source of greenhouse gas emissions, and accurately forecasting them is key to formulating targeted policies such as carbon pricing and emission quotas. The accuracy of existing forecasting models is limited by the challenges they face in processing large multi-source datasets. This study introduces a dual large language model (LLM) framework, MarEmisNet-DualLLM, which integrates a time-series-focused LLM for capturing temporal patterns and a general-purpose LLM for integrating domain knowledge, unstructured text, and contextual reasoning. Empirical tests on three real-world maritime datasets demonstrate that it outperforms baseline methods. The framework could be used by the International Maritime Organization, shipping firms, and ports to support mitigation strategies like route optimization and monitor compliance, thereby advancing maritime decarbonization.
{"title":"A dual large language model framework for forecasting maritime greenhouse gas emissions","authors":"Shuojiang Xu , Kelin Zhu , Fangli Zeng , Min Guo , Benying Tan , Yiqing Tian","doi":"10.1016/j.trd.2025.105202","DOIUrl":"10.1016/j.trd.2025.105202","url":null,"abstract":"<div><div>Maritime transport is a major source of greenhouse gas emissions, and accurately forecasting them is key to formulating targeted policies such as carbon pricing and emission quotas. The accuracy of existing forecasting models is limited by the challenges they face in processing large multi-source datasets. This study introduces a dual large language model (LLM) framework, MarEmisNet-DualLLM, which integrates a time-series-focused LLM for capturing temporal patterns and a general-purpose LLM for integrating domain knowledge, unstructured text, and contextual reasoning. Empirical tests on three real-world maritime datasets demonstrate that it outperforms baseline methods. The framework could be used by the International Maritime Organization, shipping firms, and ports to support mitigation strategies like route optimization and monitor compliance, thereby advancing maritime decarbonization.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"153 ","pages":"Article 105202"},"PeriodicalIF":7.7,"publicationDate":"2026-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145928585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2026-01-08DOI: 10.1016/j.trd.2025.105197
Denissa Sari Darmawi Purba, Eleftheria Kontou
Electric vehicle (EV) drivers face range anxiety and long recharging times and navigate sparse public charging networks, which challenge both preemptive and short-notice evacuations. We propose a multi-criteria vulnerability assessment of the coupled EV driver and charging station network during evacuations. We study flooding evacuations in Chicago, IL and hurricane evacuations in Southeast Florida, FL. The sensitivity analysis is conducted to examine the effects of initial battery state of charge (SOC), reduced battery efficiency under adverse weather, EV penetration rates, and home charging accessibility. Our findings show the impact of vehicle and infrastructure-related (charging network, driving range and vehicle heterogeneity) and evacuation-related (network properties, hazard intensity, and warning system type) characteristics to evacuation feasibility and performance. Most EV drivers can evacuate with or without charging during mild and moderate hazards, even with the expected decrease in charging station accessibility and network disruptions. During rare and severe hazards, those with short-range EVs face a higher risk of getting stranded without enough power and reduced charging infrastructure access. The initial SOC of the EV battery determines drivers’ capability to initiate an evacuation.
{"title":"Vulnerability assessment of electric vehicles and their charging station network during evacuations","authors":"Denissa Sari Darmawi Purba, Eleftheria Kontou","doi":"10.1016/j.trd.2025.105197","DOIUrl":"10.1016/j.trd.2025.105197","url":null,"abstract":"<div><div>Electric vehicle (EV) drivers face range anxiety and long recharging times and navigate sparse public charging networks, which challenge both preemptive and short-notice evacuations. We propose a multi-criteria vulnerability assessment of the coupled EV driver and charging station network during evacuations. We study flooding evacuations in Chicago, IL and hurricane evacuations in Southeast Florida, FL. The sensitivity analysis is conducted to examine the effects of initial battery state of charge (SOC), reduced battery efficiency under adverse weather, EV penetration rates, and home charging accessibility. Our findings show the impact of vehicle and infrastructure-related (charging network, driving range and vehicle heterogeneity) and evacuation-related (network properties, hazard intensity, and warning system type) characteristics to evacuation feasibility and performance. Most EV drivers can evacuate with or without charging during mild and moderate hazards, even with the expected decrease in charging station accessibility and network disruptions. During rare and severe hazards, those with short-range EVs face a higher risk of getting stranded without enough power and reduced charging infrastructure access. The initial SOC of the EV battery determines drivers’ capability to initiate an evacuation.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"153 ","pages":"Article 105197"},"PeriodicalIF":7.7,"publicationDate":"2026-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145928584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2026-01-06DOI: 10.1016/j.trd.2026.105208
Jin Li , Wentao He , He Zhang , Hao Shi , Huailei Cheng , Lijun Sun
This study quantifies competing climate-change effects, temperature rise versus reduced freezing, on pavement networks using over 35 years of records from more than 1,100 sections. We combine explainable machine learning (ML) with Monte Carlo simulation to propagate global climate model (GCM) projections to future infrastructure impacts, considering the two-layer uncertainty from climate ensemble and ML residuals. Results reveal substantial inter-GCM model differences and occasional opposing trends, underscoring climate projection uncertainty. Trained ML models accurately predict long-term pavement performance; the freezing index and air temperature are the two dominant drivers. Reduced future freezing tends to extend service life, partially offsetting warming’s negative effects. Thus, climate change does not always accelerate pavement deterioration: in some regions (notably wet, freeze-prone zones) and for some time horizons or scenarios, net effects can be neutral or beneficial. In wet, freeze zones, pavement service life is being extended in nearly 65 % simulations under SSP585 by 2050–2060, whereas dry, freeze counterparts only show a figure of around 35 %. These findings indicate that pavement resilience assessments should consider both warming and changing freeze–thaw regimes rather than temperature alone under climate uncertainty and inform local adaptation decisions practically.
{"title":"Quantifying the counteracting impacts of climate change on large-scale pavement infrastructure serviceability","authors":"Jin Li , Wentao He , He Zhang , Hao Shi , Huailei Cheng , Lijun Sun","doi":"10.1016/j.trd.2026.105208","DOIUrl":"10.1016/j.trd.2026.105208","url":null,"abstract":"<div><div>This study quantifies competing climate-change effects, temperature rise versus reduced freezing, on pavement networks using over 35 years of records from more than 1,100 sections. We combine explainable machine learning (ML) with Monte Carlo simulation to propagate global climate model (GCM) projections to future infrastructure impacts, considering the two-layer uncertainty from climate ensemble and ML residuals. Results reveal substantial inter-GCM model differences and occasional opposing trends, underscoring climate projection uncertainty. Trained ML models accurately predict long-term pavement performance; the freezing index and air temperature are the two dominant drivers. Reduced future freezing tends to extend service life, partially offsetting warming’s negative effects. Thus, climate change does not always accelerate pavement deterioration: in some regions (notably wet, freeze-prone zones) and for some time horizons or scenarios, net effects can be neutral or beneficial. In wet, freeze zones, pavement service life is being extended in nearly 65 % simulations under SSP585 by 2050–2060, whereas dry, freeze counterparts only show a figure of around 35 %. These findings indicate that pavement resilience assessments should consider both warming and changing freeze–thaw regimes rather than temperature alone under climate uncertainty and inform local adaptation decisions practically.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"153 ","pages":"Article 105208"},"PeriodicalIF":7.7,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145928583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2026-01-05DOI: 10.1016/j.trd.2025.105201
Yufang Fu, Qing Chen, Bojun Gu, Peng Tian
Faced with the constant changes in carbon policies, consumer markets, and the climatic environment, the sustainable low-carbon transition of the shipping industry has become a key challenge in global carbon emission reduction. Utilizing Itô stochastic differential equation theory, this study develops a tripartite stochastic evolutionary game incorporating Gaussian white noise to simulate uncertainties in abatement process, analyzes strategic interactions among governments, shippers, and carriers, and explores the influence of key parameters and policy mechanisms on the system. The results indicate that increased intensities of stochastic disturbances weaken the stability of emission reduction strategies. Implementing regulation, enhancing consumers’ low-carbon preferences, and establishing compensation mechanisms can boost the emission reduction willingness of shippers and carriers, reducing strategic fluctuations. Moreover, reasonable carbon subsidies alongside a hybrid carbon tax and emissions trading system, with allocation ratios aligned with the decarbonization progress of the shipping industry, are critical for reducing emissions and maintaining strategic stability.
{"title":"Carbon emission reduction strategy in shipping industry: A stochastic evolutionary game analysis","authors":"Yufang Fu, Qing Chen, Bojun Gu, Peng Tian","doi":"10.1016/j.trd.2025.105201","DOIUrl":"10.1016/j.trd.2025.105201","url":null,"abstract":"<div><div>Faced with the constant changes in carbon policies, consumer markets, and the climatic environment, the sustainable low-carbon transition of the shipping industry has become a key challenge in global carbon emission reduction. Utilizing Itô stochastic differential equation theory, this study develops a tripartite stochastic evolutionary game incorporating Gaussian white noise to simulate uncertainties in abatement process, analyzes strategic interactions among governments, shippers, and carriers, and explores the influence of key parameters and policy mechanisms on the system. The results indicate that increased intensities of stochastic disturbances weaken the stability of emission reduction strategies. Implementing regulation, enhancing consumers’ low-carbon preferences, and establishing compensation mechanisms can boost the emission reduction willingness of shippers and carriers, reducing strategic fluctuations. Moreover, reasonable carbon subsidies alongside a hybrid carbon tax and emissions trading system, with allocation ratios aligned with the decarbonization progress of the shipping industry, are critical for reducing emissions and maintaining strategic stability.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"153 ","pages":"Article 105201"},"PeriodicalIF":7.7,"publicationDate":"2026-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145897876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2026-01-03DOI: 10.1016/j.trd.2025.105204
Jie Gao , Yuze Qian , Toshiyuki Yamamoto , Marco Helbich
This study examined the gender-stratified mediating role of residential dissonance (mismatches between perceived actual and ideals) in relationships between built environment and transport-related active travel in Nagoya, Japan, using structural equation modeling. For men, safety-related positive dissonance (where perceived safety met or exceeded ideals) was positively associated with cycling frequency. For women, car-alternatives-related positive dissonance (where offering better conditions for non-car modes) was directly associated with higher cycling frequency. The effects of built environment showed further gender differences. For men, shorter subway proximity increased cycling frequency, an effect reinforced by safety-related positive dissonance. Land use diversity increased walking frequency through aesthetics-related positive dissonance. For women, longer distances to stations were indirectly associated with more walking frequency by reduced accessibility-related positive dissonance. Overall, residential dissonance is a critical, gender-stratified mediator in the built environment-active travel relationships. The distinct pathways for men and women emphasize the necessity of gender-responsive urban planning.
{"title":"The role of residential dissonance in active travel: Gendered evidence from Japan","authors":"Jie Gao , Yuze Qian , Toshiyuki Yamamoto , Marco Helbich","doi":"10.1016/j.trd.2025.105204","DOIUrl":"10.1016/j.trd.2025.105204","url":null,"abstract":"<div><div>This study examined the gender-stratified mediating role of residential dissonance (mismatches between perceived actual and ideals) in relationships between built environment and transport-related active travel in Nagoya, Japan, using structural equation modeling. For<!--> <!-->men, safety-related positive dissonance (where perceived safety <em>met</em> or<!--> <!-->exceeded ideals) was positively associated with cycling frequency. For women, car-alternatives-related positive dissonance (where offering<!--> <!-->better<!--> <!-->conditions for non-car modes) was directly associated with higher cycling frequency. The<!--> <!-->effects of built environment showed further gender differences.<!--> <!-->For men, shorter subway proximity increased cycling frequency, an effect reinforced by safety-related positive dissonance. Land use diversity increased walking frequency through aesthetics-related<!--> <!-->positive dissonance.<!--> <!-->For women, longer distances to stations were indirectly<!--> <!-->associated with more walking frequency by reduced accessibility-related<!--> <!-->positive dissonance. Overall, residential dissonance is a critical, gender-stratified mediator in the built environment-active travel relationships. The distinct pathways for men and women emphasize the necessity of gender-responsive urban planning.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"152 ","pages":"Article 105204"},"PeriodicalIF":7.7,"publicationDate":"2026-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145885884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2026-01-02DOI: 10.1016/j.trd.2025.105199
Chuan Ding , Tiantian Liu , Xinyu Zhou , Liya Yang , Sufeng Wu
Revisiting concerns over climate change have prompted research into the linkage between the built environment (BE) and travel behavior, aiming to provide evidence-based support for altering the urban fabric to reduce motorized travel. Numerous studies have examined the nonlinear associations between the BE attributes and motorized travel, but few efforts have fully accounted for the spatial context issues (i.e., spatial heterogeneity and spatial dependence). To fill this gap, this study proposes a semi-parametric multilevel model with conditional autoregressive (CAR) specification to re-estimate the nonlinear impacts of BE attributes on motorized travel while addressing the spatial context issues. We applied it to the household travel survey data from Beijing, China. Our findings indicate that including spatial heterogeneity and dependence in the nonlinear analysis leads to a superior model fit. The zonal BE attributes have clearly nonlinear impacts on household vehicle kilometers traveled (VKT) even after controlling for the significant spatial effects.
{"title":"Incorporating spatial context in nonlinear relationship between built environment and driving behavior","authors":"Chuan Ding , Tiantian Liu , Xinyu Zhou , Liya Yang , Sufeng Wu","doi":"10.1016/j.trd.2025.105199","DOIUrl":"10.1016/j.trd.2025.105199","url":null,"abstract":"<div><div>Revisiting concerns over climate change have prompted research into the linkage between the built environment (BE) and travel behavior, aiming to provide evidence-based support for altering the urban fabric to reduce motorized travel. Numerous studies have examined the nonlinear associations between the BE attributes and motorized travel, but few efforts have fully accounted for the spatial context issues (i.e., spatial heterogeneity and spatial dependence). To fill this gap, this study proposes a semi-parametric multilevel model with conditional autoregressive (CAR) specification to re-estimate the nonlinear impacts of BE attributes on motorized travel while addressing the spatial context issues. We applied it to the household travel survey data from Beijing, China. Our findings indicate that including spatial heterogeneity and dependence in the nonlinear analysis leads to a superior model fit. The zonal BE attributes have clearly nonlinear impacts on household vehicle kilometers traveled (VKT) even after controlling for the significant spatial effects.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"152 ","pages":"Article 105199"},"PeriodicalIF":7.7,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145885886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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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