Pub Date : 2025-11-18DOI: 10.1016/j.jtrangeo.2025.104487
Boting Qu , Fen Li , Yuan Gao
Understanding the relationship between the built environment and traffic carbon emissions is essential for sustainable urban development. However, accurately modeling these relationships presents complexities, including capturing intricate spatial interdependencies, modeling dynamic factors, and fully accounting for crucial upstream emissions from electric vehicles (EVs). In this paper, a deep learning Spatiotemporal Graph Convolutional Network (ST-GCN) framework is proposed. Using Xi’an taxi GPS data, the well-to-wheel (WTW) carbon emissions for Electric Taxis (ETs) and Internal Combustion Engine Taxis (ICETs) are first quantified, respectively. These emissions are then modeled in ST-GCN by integrating static built environment, dynamic time-series, and external temporal factors. Utilizing the Integrated Gradients interpretation method, the complex mechanisms influencing emission patterns are identified. Findings reveal distinct ET/ICET emission characteristics and driving mechanisms, spatial heterogeneity, spillover effects, and how neighbor interactions jointly shape emission outcomes. This framework offers insights for accurate, equitable, and synergistic urban emission mitigation policies.
{"title":"Decoding built environment impacts and regional interdependence of urban traffic emissions using interpretable deep learning","authors":"Boting Qu , Fen Li , Yuan Gao","doi":"10.1016/j.jtrangeo.2025.104487","DOIUrl":"10.1016/j.jtrangeo.2025.104487","url":null,"abstract":"<div><div>Understanding the relationship between the built environment and traffic carbon emissions is essential for sustainable urban development. However, accurately modeling these relationships presents complexities, including capturing intricate spatial interdependencies, modeling dynamic factors, and fully accounting for crucial upstream emissions from electric vehicles (EVs). In this paper, a deep learning Spatiotemporal Graph Convolutional Network (ST-GCN) framework is proposed. Using Xi’an taxi GPS data, the well-to-wheel (WTW) carbon emissions for Electric Taxis (ETs) and Internal Combustion Engine Taxis (ICETs) are first quantified, respectively. These emissions are then modeled in ST-GCN by integrating static built environment, dynamic time-series, and external temporal factors. Utilizing the Integrated Gradients interpretation method, the complex mechanisms influencing emission patterns are identified. Findings reveal distinct ET/ICET emission characteristics and driving mechanisms, spatial heterogeneity, spillover effects, and how neighbor interactions jointly shape emission outcomes. This framework offers insights for accurate, equitable, and synergistic urban emission mitigation policies.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"130 ","pages":"Article 104487"},"PeriodicalIF":6.3,"publicationDate":"2025-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145554302","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 : 2025-11-18DOI: 10.1016/j.jtrangeo.2025.104486
Keliang Liu , Jian Chen , Wu Li , Rui Li , Qi Chen
Urban on-street parking violations pose significant challenges to traffic efficiency, safety, and urban management. Identifying their spatio-temporal characteristics and related factors is essential for developing effective governance strategies. However, existing studies have predominantly relied on linear analytical frameworks, and coupled with the limitations of non-continuous data, it is often difficult to capture the objective patterns of parking violations. To address this gap, this study examined 41,344 consecutive records of parking violations collected by monitoring devices over a two-month period. Twenty-two potential influencing factors were extracted from three perspectives: land use, parking supply, and road design. A combination of spatio-temporal analysis methods—including the standard deviational ellipse, hierarchical clustering, and dynamic time warping—was used to reveal the distribution and temporal patterns of parking violations. Furthermore, a gradient boosting decision tree model enhanced by an improved genetic algorithm (IGA-GBDT) was developed to jointly optimize feature selection and hyperparameters, enabling the exploration of nonlinear relationships between violations and their determinants. The results indicate that parking violations are more frequent on weekdays than weekends, with clear peaks during commuting hours. Weekday patterns follow an “expansion–stabilization–contraction” trend, and four distinct temporal clusters were identified across different locations. The IGA-GBDT model reveals nonlinear threshold effects of built environment and road design factors, as well as spatial heterogeneity in their influence on violations. This study provides a new perspective for on-street parking management and offer practical implications for more targeted and adaptive strategies.
{"title":"Spatio-temporal characteristics and related factors of urban on-street parking violations: A nonlinear perspective","authors":"Keliang Liu , Jian Chen , Wu Li , Rui Li , Qi Chen","doi":"10.1016/j.jtrangeo.2025.104486","DOIUrl":"10.1016/j.jtrangeo.2025.104486","url":null,"abstract":"<div><div>Urban on-street parking violations pose significant challenges to traffic efficiency, safety, and urban management. Identifying their spatio-temporal characteristics and related factors is essential for developing effective governance strategies. However, existing studies have predominantly relied on linear analytical frameworks, and coupled with the limitations of non-continuous data, it is often difficult to capture the objective patterns of parking violations. To address this gap, this study examined 41,344 consecutive records of parking violations collected by monitoring devices over a two-month period. Twenty-two potential influencing factors were extracted from three perspectives: land use, parking supply, and road design. A combination of spatio-temporal analysis methods—including the standard deviational ellipse, hierarchical clustering, and dynamic time warping—was used to reveal the distribution and temporal patterns of parking violations. Furthermore, a gradient boosting decision tree model enhanced by an improved genetic algorithm (IGA-GBDT) was developed to jointly optimize feature selection and hyperparameters, enabling the exploration of nonlinear relationships between violations and their determinants. The results indicate that parking violations are more frequent on weekdays than weekends, with clear peaks during commuting hours. Weekday patterns follow an “expansion–stabilization–contraction” trend, and four distinct temporal clusters were identified across different locations. The IGA-GBDT model reveals nonlinear threshold effects of built environment and road design factors, as well as spatial heterogeneity in their influence on violations. This study provides a new perspective for on-street parking management and offer practical implications for more targeted and adaptive strategies.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"130 ","pages":"Article 104486"},"PeriodicalIF":6.3,"publicationDate":"2025-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145546161","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 : 2025-11-17DOI: 10.1016/j.jtrangeo.2025.104488
Leshan Cai , Qinyu Cui , Ziqi Yang , Jiayu Liu , Kaihan Zhang
The strategic deployment of public electric vehicle charging stations (EVCSs) is imperative for achieving transportation decarbonization. While EVCS accessibility is a critical factor influencing user experience and the adoption of electric vehicles, prior assessments have evaluated EVCS accessibility solely based on residential locations, overlooking the actual daily mobility patterns of vehicle owners. This oversight may result in an underestimate of potential charging opportunities. So this study uses home-workplace (HW) location data derived from mobile phone records to reevaluate EVCS accessibility and its associated equity status. We employed the Gaussian two-step floating catchment area (G2SFCA) to calculate accessibility at both workplace and residential locations and aggregated residents' EVCS accessibility at the residential location. The results indicate that: (1) accessibility improved for 99.94 % of residents, with 21.64 % experiencing an average reduction of 627.67 m in travel distance to EVCS; (2) equity in EVCS accessibility markedly increased, evidenced by a reduction in the Gini coefficient from 0.49 to 0.26; (3) the underlying drivers of the proposed dual-perspective accessibility index reveal that “GDP”, “Building density”, “Traffic flow”, and “Distance to the nearest subway station” show high feature importance scores. Specifically, the home scenario model is also significantly influenced by “Housing age” and “Shopping facilities”, while “Distance to the nearest primary road” and “Plot ratio” are key drivers in the workplace scenario. The findings can help alleviate (potential) consumers' charging anxiety and encourage planners to shift their focus to areas with low EVCS accessibility from both home and workplace. Additionally, the proposed methodology provides actionable insights and can be adapted for broader urban accessibility studies.
{"title":"Revisiting electric vehicle charging station accessibility: A home and workplace dual-scenario perspective","authors":"Leshan Cai , Qinyu Cui , Ziqi Yang , Jiayu Liu , Kaihan Zhang","doi":"10.1016/j.jtrangeo.2025.104488","DOIUrl":"10.1016/j.jtrangeo.2025.104488","url":null,"abstract":"<div><div>The strategic deployment of public electric vehicle charging stations (EVCSs) is imperative for achieving transportation decarbonization. While EVCS accessibility is a critical factor influencing user experience and the adoption of electric vehicles, prior assessments have evaluated EVCS accessibility solely based on residential locations, overlooking the actual daily mobility patterns of vehicle owners. This oversight may result in an underestimate of potential charging opportunities. So this study uses home-workplace (H<img>W) location data derived from mobile phone records to reevaluate EVCS accessibility and its associated equity status. We employed the Gaussian two-step floating catchment area (G2SFCA) to calculate accessibility at both workplace and residential locations and aggregated residents' EVCS accessibility at the residential location. The results indicate that: (1) accessibility improved for 99.94 % of residents, with 21.64 % experiencing an average reduction of 627.67 m in travel distance to EVCS; (2) equity in EVCS accessibility markedly increased, evidenced by a reduction in the Gini coefficient from 0.49 to 0.26; (3) the underlying drivers of the proposed dual-perspective accessibility index reveal that “GDP”, “Building density”, “Traffic flow”, and “Distance to the nearest subway station” show high feature importance scores. Specifically, the home scenario model is also significantly influenced by “Housing age” and “Shopping facilities”, while “Distance to the nearest primary road” and “Plot ratio” are key drivers in the workplace scenario. The findings can help alleviate (potential) consumers' charging anxiety and encourage planners to shift their focus to areas with low EVCS accessibility from both home and workplace. Additionally, the proposed methodology provides actionable insights and can be adapted for broader urban accessibility studies.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"130 ","pages":"Article 104488"},"PeriodicalIF":6.3,"publicationDate":"2025-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145546039","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 : 2025-11-13DOI: 10.1016/j.jtrangeo.2025.104482
Maria Juschten , Reinhard Hössinger
This study develops and applies a relational accessibility indicator to assess commuting-related public transport (PT) inequalities in the Innviertel, a rural region of Austria, in comparison to other rural and non-rural Austrian areas. By integrating spatial, temporal, and demand-based factors, the indicator measures PT trip attractiveness across different time frames, with a particular focus on the earliest possible connection - a critical but often overlooked dimension for shift-based and time-constrained employment. The PT quality indicator is merged with official commuter flow data to account for the number of commuters affected by limited accessibility. Results reveal significant accessibility disparities, especially for shift workers and secondary-sector employees, due to limited early-morning and night-time PT services. Compared to other rural regions, the Innviertel exhibits longer PT travel times and fewer direct, rail-based commuting connections, reducing its competitiveness against private cars. While data limitations prevent a detailed household-level analysis, the findings suggest that lower-income households in rural Austria may not face systematically worse PT access. Overall, this study highlights the importance of considering both spatial and temporal dimensions in rural PT planning and calls for a stronger integration of housing, transport and economic planning. It proposes policy interventions such as expanded early-morning PT services and employer-susbsidized transport solutions and cross-border PT integration to enhance transport equity and employment accessibility across the region.
{"title":"Assessing commuting-related accessibility inequalities in rural Innviertel, Austria","authors":"Maria Juschten , Reinhard Hössinger","doi":"10.1016/j.jtrangeo.2025.104482","DOIUrl":"10.1016/j.jtrangeo.2025.104482","url":null,"abstract":"<div><div>This study develops and applies a relational accessibility indicator to assess commuting-related public transport (PT) inequalities in the Innviertel, a rural region of Austria, in comparison to other rural and non-rural Austrian areas. By integrating spatial, temporal, and demand-based factors, the indicator measures PT trip attractiveness across different time frames, with a particular focus on the earliest possible connection - a critical but often overlooked dimension for shift-based and time-constrained employment. The PT quality indicator is merged with official commuter flow data to account for the number of commuters affected by limited accessibility. Results reveal significant accessibility disparities, especially for shift workers and secondary-sector employees, due to limited early-morning and night-time PT services. Compared to other rural regions, the Innviertel exhibits longer PT travel times and fewer direct, rail-based commuting connections, reducing its competitiveness against private cars. While data limitations prevent a detailed household-level analysis, the findings suggest that lower-income households in rural Austria may not face systematically worse PT access. Overall, this study highlights the importance of considering both spatial and temporal dimensions in rural PT planning and calls for a stronger integration of housing, transport and economic planning. It proposes policy interventions such as expanded early-morning PT services and employer-susbsidized transport solutions and cross-border PT integration to enhance transport equity and employment accessibility across the region.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"130 ","pages":"Article 104482"},"PeriodicalIF":6.3,"publicationDate":"2025-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145528437","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 : 2025-11-13DOI: 10.1016/j.jtrangeo.2025.104480
Alessandro La Delfa, Zheng Han
Within the framework of emerging autonomous mobility, this study examines why car commuters persist with private vehicles despite alternatives, recognizing that identical behavior can arise from distinct mechanisms. As autonomous ride-hailing (ARH) shifts from pilots to fleets projected to exceed 500,000 robotaxis in Chinese cities by 2030, demand models risk systematic forecasting errors by missing how behavioral mechanisms independently shape responses. We test how cue-triggered habit and situational constraints separately influence Shanghai commuters' willingness to adopt self-driving taxis.
We analyzed 2050 revealed- and stated-preference choices from 410 car commuters using a latent-class hybrid choice model integrating habit strength with observable constraints.
Two segments emerge, namely Habitual Loyalists (≈78 %) and Constrained Adapters (≈22 %). Loyalists' automaticity reduces ARH utility and dampens price- and time-sensitivities. Adapters respond to tangible constraints, such as scarce car access and unreliable travel times, and place a substantially higher value on time savings (52 vs 38 CNY/h), making them receptive once these frictions are eased. Loyalists show habitual blindness to alternative modes, whereas Adapters remain cognitively flexible. Habit and constraint effects are stable across Shanghai's core and periphery, and a negative link between structural barriers and habit strength suggests that prolonged friction gradually erodes automatic car routines.
Recognizing mechanism-based heterogeneity improves ARH uptake projections. Disrupting routine cues is prerequisite for shifting Loyalists, whereas reliable, low-wait service in high-friction areas can attract Adapters. The gradual weakening of habit under persistent constraints points to a life-cycle pathway for broader mode shift in other fast-growing cities.
{"title":"Habit or constraint? Car commuters' adoption of autonomous ride-hailing: A hybrid choice approach","authors":"Alessandro La Delfa, Zheng Han","doi":"10.1016/j.jtrangeo.2025.104480","DOIUrl":"10.1016/j.jtrangeo.2025.104480","url":null,"abstract":"<div><div>Within the framework of emerging autonomous mobility, this study examines why car commuters persist with private vehicles despite alternatives, recognizing that identical behavior can arise from distinct mechanisms. As autonomous ride-hailing (ARH) shifts from pilots to fleets projected to exceed 500,000 robotaxis in Chinese cities by 2030, demand models risk systematic forecasting errors by missing how behavioral mechanisms independently shape responses. We test how cue-triggered habit and situational constraints separately influence Shanghai commuters' willingness to adopt self-driving taxis.</div><div>We analyzed 2050 revealed- and stated-preference choices from 410 car commuters using a latent-class hybrid choice model integrating habit strength with observable constraints.</div><div>Two segments emerge, namely Habitual Loyalists (≈78 %) and Constrained Adapters (≈22 %). Loyalists' automaticity reduces ARH utility and dampens price- and time-sensitivities. Adapters respond to tangible constraints, such as scarce car access and unreliable travel times, and place a substantially higher value on time savings (52 vs 38 CNY/h), making them receptive once these frictions are eased. Loyalists show habitual blindness to alternative modes, whereas Adapters remain cognitively flexible. Habit and constraint effects are stable across Shanghai's core and periphery, and a negative link between structural barriers and habit strength suggests that prolonged friction gradually erodes automatic car routines.</div><div>Recognizing mechanism-based heterogeneity improves ARH uptake projections. Disrupting routine cues is prerequisite for shifting Loyalists, whereas reliable, low-wait service in high-friction areas can attract Adapters. The gradual weakening of habit under persistent constraints points to a life-cycle pathway for broader mode shift in other fast-growing cities.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"130 ","pages":"Article 104480"},"PeriodicalIF":6.3,"publicationDate":"2025-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145528436","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}
This paper examines the mode choice behaviour of occasional couriers providing crowd-shipping (CS) deliveries for e-groceries, with a particular focus on gender heterogeneity. Using a behavioural survey conducted in Kharkiv, Ukraine, in early 2021, combined with simulated travel attributes and discrete choice modelling based on random utility maximisation theory, this study explores how gender influences mode preferences and willingness to pay (WTP) across six transport modes within a crowd-shipping context. The results reveal significant gender-based differences in both mode choice and WTP. Female couriers consistently exhibit a higher WTP across all transport modes compared to their male counterparts. For instance, women's WTP for cycling (90 UAH/h) is substantially higher than men's (59.79 UAH/h), while for car-based deliveries, women's WTP reaches 87.16 UAH/h, compared to 54.94 UAH/h for men. These findings suggest that women require higher compensation, particularly for non-motorised modes, likely due to differences in physical effort required and perceived comfort.
{"title":"Gender heterogeneity in couriers' mode choice behaviours: Crowd-shipping for E-groceries","authors":"Oleksandr Rossolov , Anastasiia Botsman , Serhii Lyfenko , Yusak O. Susilo","doi":"10.1016/j.jtrangeo.2025.104483","DOIUrl":"10.1016/j.jtrangeo.2025.104483","url":null,"abstract":"<div><div>This paper examines the mode choice behaviour of occasional couriers providing crowd-shipping (CS) deliveries for e-groceries, with a particular focus on gender heterogeneity. Using a behavioural survey conducted in Kharkiv, Ukraine, in early 2021, combined with simulated travel attributes and discrete choice modelling based on random utility maximisation theory, this study explores how gender influences mode preferences and willingness to pay (WTP) across six transport modes within a crowd-shipping context. The results reveal significant gender-based differences in both mode choice and WTP. Female couriers consistently exhibit a higher WTP across all transport modes compared to their male counterparts. For instance, women's WTP for cycling (90 UAH/h) is substantially higher than men's (59.79 UAH/h), while for car-based deliveries, women's WTP reaches 87.16 UAH/h, compared to 54.94 UAH/h for men. These findings suggest that women require higher compensation, particularly for non-motorised modes, likely due to differences in physical effort required and perceived comfort.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"130 ","pages":"Article 104483"},"PeriodicalIF":6.3,"publicationDate":"2025-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145528487","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 : 2025-11-12DOI: 10.1016/j.jtrangeo.2025.104481
Pauline van den Berg , E. Owen D. Waygood , Iris van de Craats , Astrid Kemperman
Much research on children's (school) travel focuses on explaining travel mode choice and how that relates to physical activity gained through active travel. However, another key component of children's lives and their travel relates to the social outcomes of travel such as social contact, social cohesion, and social safety. Children's independent and active travel has been shown to be positively related to social contacts with friends and neighbors which in turn is associated with social cohesion and feelings of safety in the neighborhood. However, the precise interrelationships between children's school travel and social aspects are not well understood. Using a Bayesian Belief Network approach, a data mining approach, it is possible to examine how (categorical) variables influence each other, both directly and indirectly. Using data from 601 primary school students and their parents in the Netherlands, a Bayesian Belief Network is estimated to examine the relationships between children's school travel characteristics (distance, mode, and travel party), and social domain factors (social contact with other children, social cohesion, and the perception of social safety). Along with those measures, variables are included related to child and household characteristics (age, gender, children's travel skills, household car ownership) and neighborhood characteristics (perceptions of traffic safety, socio-economic status of the neighborhoods, and population density). The results demonstrate that there is a clear relationship between the social domain factors, which are linked to how children travel. The findings suggest that shorter trips to school would increase social contact during travel, which improves social cohesion and, in turn improves the perception of social safety. Thus, not only do shorter distance trips increase the likelihood of active travel, which contributes to physical health, but they can also improve the social dimension of children's well-being.
{"title":"Social contact, social cohesion, and social safety outcomes of children's school travel","authors":"Pauline van den Berg , E. Owen D. Waygood , Iris van de Craats , Astrid Kemperman","doi":"10.1016/j.jtrangeo.2025.104481","DOIUrl":"10.1016/j.jtrangeo.2025.104481","url":null,"abstract":"<div><div>Much research on children's (school) travel focuses on explaining travel mode choice and how that relates to physical activity gained through active travel. However, another key component of children's lives and their travel relates to the social outcomes of travel such as social contact, social cohesion, and social safety. Children's independent and active travel has been shown to be positively related to social contacts with friends and neighbors which in turn is associated with social cohesion and feelings of safety in the neighborhood. However, the precise interrelationships between children's school travel and social aspects are not well understood. Using a Bayesian Belief Network approach, a data mining approach, it is possible to examine how (categorical) variables influence each other, both directly and indirectly. Using data from 601 primary school students and their parents in the Netherlands, a Bayesian Belief Network is estimated to examine the relationships between children's school travel characteristics (distance, mode, and travel party), and social domain factors (social contact with other children, social cohesion, and the perception of social safety). Along with those measures, variables are included related to child and household characteristics (age, gender, children's travel skills, household car ownership) and neighborhood characteristics (perceptions of traffic safety, socio-economic status of the neighborhoods, and population density). The results demonstrate that there is a clear relationship between the social domain factors, which are linked to how children travel. The findings suggest that shorter trips to school would increase social contact during travel, which improves social cohesion and, in turn improves the perception of social safety. Thus, not only do shorter distance trips increase the likelihood of active travel, which contributes to physical health, but they can also improve the social dimension of children's well-being.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"130 ","pages":"Article 104481"},"PeriodicalIF":6.3,"publicationDate":"2025-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145515683","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 : 2025-11-10DOI: 10.1016/j.jtrangeo.2025.104454
Weiqin Hu , Jia Shi , Chuan Pang , Jihong Chen , Zheng Wan , Zhihuan Wang
Amid evolving geopolitical uncertainties, the Maritime Silk Road shipping network faces mounting systemic disruptions. This study proposes a macro-level resilience optimization framework that integrates complex network theory with resilience triangle theory to evaluate and enhance the resilience of Maritime Silk Road shipping network. The framework simulates four disruption types—random attacks (e.g., ship collisions), degree attacks (e.g., strikes at hub ports), strength attacks (e.g., route capacity constraints), and betweenness centrality attacks (e.g., blockages of critical corridors)—and assesses three recovery strategies: Degree Recovery, Betweenness Recovery, and Strength Recovery. Empirical findings reveal: (1) the strength recovery strategy consistently outperforms other strategies, especially under degree-based, strength-based, and random disruptions, by restoring high-throughput routes; (2) Long-distance, cross-regional connections—such as those between the Mediterranean and Northern Europe, or between East Asia and Southeast Asia—play a vital role in resilience enhancement, particularly under high economic budgets. These insights provide actionable guidance for policymakers and port authorities, emphasizing the need to incorporate resilience considerations into infrastructure planning, prioritize strategic hubs (e.g., Qingdao, Zhoushan, Bangkok, Hamburg), and balance investment feasibility with network resilience. The proposed framework is generalizable and can be extended to other global shipping networks to support resilience-oriented decision-making under systemic risks.
{"title":"Assessment and optimization of shipping network resilience in the maritime silk road regions","authors":"Weiqin Hu , Jia Shi , Chuan Pang , Jihong Chen , Zheng Wan , Zhihuan Wang","doi":"10.1016/j.jtrangeo.2025.104454","DOIUrl":"10.1016/j.jtrangeo.2025.104454","url":null,"abstract":"<div><div>Amid evolving geopolitical uncertainties, the Maritime Silk Road shipping network faces mounting systemic disruptions. This study proposes a macro-level resilience optimization framework that integrates complex network theory with resilience triangle theory to evaluate and enhance the resilience of Maritime Silk Road shipping network. The framework simulates four disruption types—random attacks (e.g., ship collisions), degree attacks (e.g., strikes at hub ports), strength attacks (e.g., route capacity constraints), and betweenness centrality attacks (e.g., blockages of critical corridors)—and assesses three recovery strategies: Degree Recovery, Betweenness Recovery, and Strength Recovery. Empirical findings reveal: (1) the strength recovery strategy consistently outperforms other strategies, especially under degree-based, strength-based, and random disruptions, by restoring high-throughput routes; (2) Long-distance, cross-regional connections—such as those between the Mediterranean and Northern Europe, or between East Asia and Southeast Asia—play a vital role in resilience enhancement, particularly under high economic budgets. These insights provide actionable guidance for policymakers and port authorities, emphasizing the need to incorporate resilience considerations into infrastructure planning, prioritize strategic hubs (e.g., Qingdao, Zhoushan, Bangkok, Hamburg), and balance investment feasibility with network resilience. The proposed framework is generalizable and can be extended to other global shipping networks to support resilience-oriented decision-making under systemic risks.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"130 ","pages":"Article 104454"},"PeriodicalIF":6.3,"publicationDate":"2025-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145485574","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 : 2025-11-08DOI: 10.1016/j.jtrangeo.2025.104477
Peter Shobayo , Chenghua Yang , Felipe Bedoya-Maya , Adrien Nicolet , Edwin van Hassel , Bilge Atasoy , Thierry Vanelslander
Container logistics is under increasing pressure to deliver efficient and sustainable hinterland transport. Achieving this requires improving the performance of environmentally friendly modes, such as inland waterway transport. This study examines the potential of cargo consolidation as a strategy to tackle suboptimal filling rates of containers, one of the most persistent inefficiencies in the Rhine-Alpine Corridor. We develop an integrated optimization model that holistically accounts for the operational and spatial requirements of consolidation, assessing the sensitivity of the strategy to labor costs, fuel prices, value of time, and vessel costs. The results show that, despite additional handling and coordination costs, consolidation can reduce overall transport costs by up to 4 % and attract as much as 42 % more container volumes to IWT on specific origin-destination connections. Vessel occupation rates emerge as a decisive factor in determining consolidation benefits, while cost parameters such as labor and fuel prices strongly influence outcomes. The research illustrates how optimizing this strategy can contribute to the sustainability of port-hinterland container transport and discusses the conditions required for its realization.
{"title":"Improving a cargo consolidation strategy for port-hinterland transport via inland waterways","authors":"Peter Shobayo , Chenghua Yang , Felipe Bedoya-Maya , Adrien Nicolet , Edwin van Hassel , Bilge Atasoy , Thierry Vanelslander","doi":"10.1016/j.jtrangeo.2025.104477","DOIUrl":"10.1016/j.jtrangeo.2025.104477","url":null,"abstract":"<div><div>Container logistics is under increasing pressure to deliver efficient and sustainable hinterland transport. Achieving this requires improving the performance of environmentally friendly modes, such as inland waterway transport. This study examines the potential of cargo consolidation as a strategy to tackle suboptimal filling rates of containers, one of the most persistent inefficiencies in the Rhine-Alpine Corridor. We develop an integrated optimization model that holistically accounts for the operational and spatial requirements of consolidation, assessing the sensitivity of the strategy to labor costs, fuel prices, value of time, and vessel costs. The results show that, despite additional handling and coordination costs, consolidation can reduce overall transport costs by up to 4 % and attract as much as 42 % more container volumes to IWT on specific origin-destination connections. Vessel occupation rates emerge as a decisive factor in determining consolidation benefits, while cost parameters such as labor and fuel prices strongly influence outcomes. The research illustrates how optimizing this strategy can contribute to the sustainability of port-hinterland container transport and discusses the conditions required for its realization.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"130 ","pages":"Article 104477"},"PeriodicalIF":6.3,"publicationDate":"2025-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145462083","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 : 2025-11-08DOI: 10.1016/j.jtrangeo.2025.104479
Zijian Guo , Mei-Po Kwan , Jian Liu , Xintao Liu
Bike sharing is a convenient, cheap, and flexible service for inner-city trips. Its flexibility enables users to adjust their travel choices based on individual circumstances, such as time sensitivity in travel (TST). For instance, when pressed for time, cyclists tend to choose the optimal routes to minimize the travel duration. TST significantly influences individual travel behaviors. Yet, few studies have recognized it as a key factor in comparative research on travel behavior, particularly from a city-level perspective. In this work, we draw upon the concept of “extra travel time” (the difference between optimal and actual travel time) to characterize two types of TST-related trips: the minimum for direct-type trips and the maximum for loop-type trips. Further divided by long- and short-duration, trips can be classified into four groups: long-direct, short-direct, long-loop, and short-loop trips. We then conduct a comparison of travel behavior based on these groups. Through observing their patterns, we pair them with varying TST scenarios. Then, we utilize Shenzhen's bike-sharing data in 2021 to compare the travel behavior of the four trip types in terms of statistical, temporal, and spatial distributions. Next, the relationships between travel durations (long or short) and land use patterns are examined using the random forest-based SHAP method. The results show that long-loop trips are associated with low TST, whereas direct-type trips and short-loop trips are often linked to high TST. For loop-type trips, proximity to green spaces (within a certain range) or water bodies is linked to longer travel durations, indicating a low TST scenario, while proximity to industrial zones, schools, or urban villages corresponds to shorter durations and high TST. This study provides insights into time sensitivity, travel behaviors, and land use, contributing to better urban planning and the optimization of bike-sharing systems.
{"title":"Time sensitivity and travel behavior patterns: Insights from Shenzhen's shared bike data","authors":"Zijian Guo , Mei-Po Kwan , Jian Liu , Xintao Liu","doi":"10.1016/j.jtrangeo.2025.104479","DOIUrl":"10.1016/j.jtrangeo.2025.104479","url":null,"abstract":"<div><div>Bike sharing is a convenient, cheap, and flexible service for inner-city trips. Its flexibility enables users to adjust their travel choices based on individual circumstances, such as time sensitivity in travel (TST). For instance, when pressed for time, cyclists tend to choose the optimal routes to minimize the travel duration. TST significantly influences individual travel behaviors. Yet, few studies have recognized it as a key factor in comparative research on travel behavior, particularly from a city-level perspective. In this work, we draw upon the concept of “extra travel time” (the difference between optimal and actual travel time) to characterize two types of TST-related trips: the minimum for direct-type trips and the maximum for loop-type trips. Further divided by long- and short-duration, trips can be classified into four groups: long-direct, short-direct, long-loop, and short-loop trips. We then conduct a comparison of travel behavior based on these groups. Through observing their patterns, we pair them with varying TST scenarios. Then, we utilize Shenzhen's bike-sharing data in 2021 to compare the travel behavior of the four trip types in terms of statistical, temporal, and spatial distributions. Next, the relationships between travel durations (long or short) and land use patterns are examined using the random forest-based SHAP method. The results show that long-loop trips are associated with low TST, whereas direct-type trips and short-loop trips are often linked to high TST. For loop-type trips, proximity to green spaces (within a certain range) or water bodies is linked to longer travel durations, indicating a low TST scenario, while proximity to industrial zones, schools, or urban villages corresponds to shorter durations and high TST. This study provides insights into time sensitivity, travel behaviors, and land use, contributing to better urban planning and the optimization of bike-sharing systems.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"130 ","pages":"Article 104479"},"PeriodicalIF":6.3,"publicationDate":"2025-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145462084","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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