Pub Date : 2026-03-01Epub Date: 2026-01-11DOI: 10.1016/j.cstp.2026.101711
Ali Najmi , Maliheh Tabasi , Travis Waller , Taha H. Rashidi
A fair distribution of transport benefits has long been a goal of transport agencies and planners seeking to design networks that advance social inclusion and equity. This paper investigates how ethical orientations shape citizens’ preferences for equity in transport investment. Drawing on a Stated Choice experiment with 2,050 Australian residents, an Integrated Choice and Latent Variable (ICLV) model is developed to capture how these latent ethical constructs influence preferences for key transport investment attributes, including distribution of travel costs, safety, environmental sustainability, and fairness across population groups. The findings reveal that respondents’ moral and empathetic orientations significantly affect their evaluation of equity impacts and that socio-demographic attributes further moderate these relationships. The study provides policy insights for reducing regional and socio-economic disparities in mobility outcomes and promoting more inclusive transport investment decisions, contributing to the design of transport systems that are both efficient and grounded in social justice.
{"title":"Toward equity in network design: understanding investment preferences","authors":"Ali Najmi , Maliheh Tabasi , Travis Waller , Taha H. Rashidi","doi":"10.1016/j.cstp.2026.101711","DOIUrl":"10.1016/j.cstp.2026.101711","url":null,"abstract":"<div><div>A fair distribution of transport benefits has long been a goal of transport agencies and planners seeking to design networks that advance social inclusion and equity. This paper investigates how ethical orientations shape citizens’ preferences for equity in transport investment. Drawing on a Stated Choice experiment with 2,050 Australian residents, an Integrated Choice and Latent Variable (ICLV) model is developed to capture how these latent ethical constructs influence preferences for key transport investment attributes, including distribution of travel costs, safety, environmental sustainability, and fairness across population groups. The findings reveal that respondents’ moral and empathetic orientations significantly affect their evaluation of equity impacts and that socio-demographic attributes further moderate these relationships. The study provides policy insights for reducing regional and socio-economic disparities in mobility outcomes and promoting more inclusive transport investment decisions, contributing to the design of transport systems that are both efficient and grounded in social justice.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"23 ","pages":"Article 101711"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145976473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The proposed canal boat transit (CBT) system, designed to connect metro rail and bus services in western Bangkok, was initiated by an academic institution in collaboration with local communities and stakeholders from both the public and private sectors. The initiative aims to support decarbonization efforts and promote sustainable urban mobility. A stated choice experiment explicitly incorporating the waterborne mode was conducted, and a transport mode choice model was estimated using sampling weights on combined revealed and stated preference (RP and SP) survey data through the nested logit trick. The results reveal that, for the proposed CBT mode, the value of time is highest for first-mile travel time (FMTT) at 22.36 (100.82) baht/hour, followed by wait time (WT) at 19.49 (42.79) baht/hour, and in-vehicle travel time (IVTT) at 1.76 (6.79) baht/hour for the low-income (high-income) group. Mode share comparisons before and after the introduction of CBT indicate slight declines across all existing modes, ranging from 0.02% to 0.04%. The estimated elasticities suggest that a 1% reduction in total cost (TC), FMTT, WT, and IVTT would increase CBT demand by 1.9670%, 0.8249%, 0.3173%, and 0.1269%, respectively. A 1% decrease in any CBT attribute would reduce public transit use more than private vehicle use. Simulations were performed to estimate mode share variations across income groups under different levels of CBT attribute reductions. Targeted incentives may integrate fare reductions to enhance affordability, connectivity improvements to improve accessibility, and community-based support programs to attract both lower- and higher-income users and reduce private car dependence.
{"title":"Discrete choice modeling for the proposed canal boat transit in western Bangkok, Thailand","authors":"Ampol Karoonsoontawong , Arkar Than Win , Hansa Srilertchaipanij , Kanjanee Budthimedhe , Vasin Kiattikomol , Tassana Boonyoo , Vatanavongs Ratanavaraha , Chai Jaturapitakkul","doi":"10.1016/j.cstp.2026.101733","DOIUrl":"10.1016/j.cstp.2026.101733","url":null,"abstract":"<div><div>The proposed canal boat transit (CBT) system, designed to connect metro rail and bus services in western Bangkok, was initiated by an academic institution in collaboration with local communities and stakeholders from both the public and private sectors. The initiative aims to support decarbonization efforts and promote sustainable urban mobility. A stated choice experiment explicitly incorporating the waterborne mode was conducted, and a transport mode choice model was estimated using sampling weights on combined revealed and stated preference (RP and SP) survey data through the nested logit trick. The results reveal that, for the proposed CBT mode, the value of time is highest for first-mile travel time (FMTT) at 22.36 (100.82) baht/hour, followed by wait time (WT) at 19.49 (42.79) baht/hour, and in-vehicle travel time (IVTT) at 1.76 (6.79) baht/hour for the low-income (high-income) group. Mode share comparisons before and after the introduction of CBT indicate slight declines across all existing modes, ranging from 0.02% to 0.04%. The estimated elasticities suggest that a 1% reduction in total cost (TC), FMTT, WT, and IVTT would increase CBT demand by 1.9670%, 0.8249%, 0.3173%, and 0.1269%, respectively. A 1% decrease in any CBT attribute would reduce public transit use more than private vehicle use. Simulations were performed to estimate mode share variations across income groups under different levels of CBT attribute reductions. Targeted incentives may integrate fare reductions to enhance affordability, connectivity improvements to improve accessibility, and community-based support programs to attract both lower- and higher-income users and reduce private car dependence.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"23 ","pages":"Article 101733"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146187430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-02-02DOI: 10.1016/j.cstp.2026.101739
Katerina Vakrinou, Eleni G. Mantouka, Marios Kanatas, Eleni I. Vlahogianni
This paper examines on-street searching for parking strategies and parking location choices using a stated-preference survey and two modeling approaches: interpretable machine learning models and discrete choice models. While most existing studies focus on regulated or priced parking environments, limited work has analyzed how drivers search for parking together with how they choose a parking location in largely unregulated contexts. The aim of this study is to address this gap by identifying the factors that influence how drivers search for parking and how they trade off search time, walking distance, and parking cost when choosing where to park. The best machine learning model developed achieves an accuracy of 84% in classifying search strategies. Feature importance analysis shows that average parking search duration, parking distance from destination, and vehicle size are significant factors influencing parking search strategies. In the parking location choice models, search duration and parking cost have statistically significant negative effects on choice probability, while walking distance is not statistically significant. Behavioral metrics, including elasticities and willingness-to-pay, reveal that drivers place greater value on reducing search time (€2.54 per minute) than on reducing walking distance. These results support policies that prioritize reducing search effort, such as demand-responsive pricing, residential parking policies, and measures that improve the balance between overutilized on-street parking and underutilized off-street facilities.
{"title":"Understanding searching for parking behavior in urban road networks","authors":"Katerina Vakrinou, Eleni G. Mantouka, Marios Kanatas, Eleni I. Vlahogianni","doi":"10.1016/j.cstp.2026.101739","DOIUrl":"10.1016/j.cstp.2026.101739","url":null,"abstract":"<div><div>This paper examines on-street searching for parking strategies and parking location choices using a stated-preference survey and two modeling approaches: interpretable machine learning models and discrete choice models. While most existing studies focus on regulated or priced parking environments, limited work has analyzed how drivers search for parking together with how they choose a parking location in largely unregulated contexts. The aim of this study is to address this gap by identifying the factors that influence how drivers search for parking and how they trade off search time, walking distance, and parking cost when choosing where to park. The best machine learning model developed achieves an accuracy of 84% in classifying search strategies. Feature importance analysis shows that average parking search duration, parking distance from destination, and vehicle size are significant factors influencing parking search strategies. In the parking location choice models, search duration and parking cost have statistically significant negative effects on choice probability, while walking distance is not statistically significant. Behavioral metrics, including elasticities and willingness-to-pay, reveal that drivers place greater value on reducing search time (€2.54 per minute) than on reducing walking distance. These results support policies that prioritize reducing search effort, such as demand-responsive pricing, residential parking policies, and measures that improve the balance between overutilized on-street parking and underutilized off-street facilities.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"23 ","pages":"Article 101739"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146187389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-01-30DOI: 10.1016/j.cstp.2026.101722
Andry Yuliyanto , Minh Kieu , Fahri Tri Susanto , Arif Rachman Sambuaga
Urban Mobility Hubs serve as strategic locations that integrate sustainable transportation modes, enhance Jakarta’s connectivity, and promote sustainable urban development. Selecting optimal hub sites is challenging, given the interdependencies among transport systems, data limitations, and competing policy priorities. This study proposes an integrated framework that combines Data Envelopment Analysis (DEA) with a Game Theory approach, Tobit regression, and Geographic Information Systems (GIS) to address these complexities. The framework captures competitive cooperative interactions among modes and derives spatial weights to minimise subjectivity in hub assessment. Results indicate that the Light Rail Transit (LRT) system achieves the highest efficiency, while Transjakarta performs less effectively. Spatial analysis highlights Pasar Senen as the most suitable hub, reflecting its multimodal access, dense population, and alignment with Jakarta’s development priorities. The findings underscore the significance of LRT in Jakarta’s public transportation and demonstrate that the proposed framework offers a decision support tool applicable to other megacities seeking equitable, low-emission, and livable mobility solutions.
{"title":"Selecting urban mobility hub locations using data envelopment analysis and geographic information systems","authors":"Andry Yuliyanto , Minh Kieu , Fahri Tri Susanto , Arif Rachman Sambuaga","doi":"10.1016/j.cstp.2026.101722","DOIUrl":"10.1016/j.cstp.2026.101722","url":null,"abstract":"<div><div>Urban Mobility Hubs serve as strategic locations that integrate sustainable transportation modes, enhance Jakarta’s connectivity, and promote sustainable urban development. Selecting optimal hub sites is challenging, given the interdependencies among transport systems, data limitations, and competing policy priorities. This study proposes an integrated framework that combines Data Envelopment Analysis (DEA) with a Game Theory approach, Tobit regression, and Geographic Information Systems (GIS) to address these complexities. The framework captures competitive cooperative interactions among modes and derives spatial weights to minimise subjectivity in hub assessment. Results indicate that the Light Rail Transit (LRT) system achieves the highest efficiency, while Transjakarta performs less effectively. Spatial analysis highlights Pasar Senen as the most suitable hub, reflecting its multimodal access, dense population, and alignment with Jakarta’s development priorities. The findings underscore the significance of LRT in Jakarta’s public transportation and demonstrate that the proposed framework offers a decision support tool applicable to other megacities seeking equitable, low-emission, and livable mobility solutions.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"23 ","pages":"Article 101722"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146187497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-01-29DOI: 10.1016/j.cstp.2026.101729
Mengru Shao , Chao Chen , Tao Feng
Understanding truck drivers’ route choice behavior amid the rapid expansion of freight transport is crucial for road operators to improve their services and secure stable revenue. In addition to the strict delivery schedules, truck drivers’ route choice decisions are highly sensitive to uncertain traffic conditions and policy constraints. However, to what extent operator-led marketing strategies shape their route choice decisions remains insufficiently addressed in the literature. Therefore, this study aims to investigate truck drivers’ route decisions under travel time uncertainty with a particular focus on the effects of promotional marketing strategies. A stated choice experiment was designed to collect truck drivers’ responses under different cargo-delivery contexts to toll and parallel toll-free route alternatives. A hybrid prospect-theoretic Probit model (HPTPM), incorporating interaction effects, is further developed to account for risk attitudes in decision-making under uncertainty. The findings reveal that cargo-delivery context variables, marketing strategies, and risk preferences all significantly shape truck drivers’ route choices, with notable heterogeneity observed across driver groups. Based on these insights, this study provides practical recommendations for road operators, supporting the development of tailored marketing strategies to improve the effectiveness of toll-road management.
{"title":"From road waiting to road leading: can toll-road marketing strategies make a difference for truck drivers under uncertain travel times?","authors":"Mengru Shao , Chao Chen , Tao Feng","doi":"10.1016/j.cstp.2026.101729","DOIUrl":"10.1016/j.cstp.2026.101729","url":null,"abstract":"<div><div>Understanding truck drivers’ route choice behavior amid the rapid expansion of freight transport is crucial for road operators to improve their services and secure stable revenue. In addition to the strict delivery schedules, truck drivers’ route choice decisions are highly sensitive to uncertain traffic conditions and policy constraints. However, to what extent operator-led marketing strategies shape their route choice decisions remains insufficiently addressed in the literature. Therefore, this study aims to investigate truck drivers’ route decisions under travel time uncertainty with a particular focus on the effects of promotional marketing strategies. A stated choice experiment was designed to collect truck drivers’ responses under different cargo-delivery contexts to toll and parallel toll-free route alternatives. A hybrid prospect-theoretic Probit model (HPTPM), incorporating interaction effects, is further developed to account for risk attitudes in decision-making under uncertainty. The findings reveal that cargo-delivery context variables, marketing strategies, and risk preferences all significantly shape truck drivers’ route choices, with notable heterogeneity observed across driver groups. Based on these insights, this study provides practical recommendations for road operators, supporting the development of tailored marketing strategies to improve the effectiveness of toll-road management.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"23 ","pages":"Article 101729"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146187498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Flight crew fatigue has been identified as a risk caused by various factors including duty start time, extended duty periods, circadian rhythm disruption, inadequate sleep and rest, workload and lack of in-flight rest facilities. This study extends Mannawaduge et al.’s (2025) application of the flight crew fatigue evaluation framework (FREF) to ascertain perceptions of civil aviation regulations in managing flight crew fatigue in the South Asian region. Semi-structured interviews with five South Asian civil aviation regulators were conducted via Zoom. Interview transcripts were examined using content analysis focusing on how key FREF factors/aspects were implemented in the regulations, the perceived adequacy of their regulations, and any future challenges and recommendations for fatigue management. The results provide valuable insights into each country’s method of managing fatigue (prescriptive/FRMS/combination) and the guidance of the European Union Aviation Safety Agency (EASA) in developing their regulations. Notably, participants acknowledged that some fatigue-related factors (flight time/flight duty period/duty period start time, workload, in-flight rest facilities, fatigue awareness /education, and fatigue reporting processes), were not always explicit in their regulations. Participants identified regulatory challenges in the costs of FRMS implementation, productivity-based salary structures of flight crew and the incorporation of sleep-related scientific factors identified by ICAO Doc 9966 (start time of flight time/flight duty period/duty period, sleep, workload, in-flight rest) into the regulations. Recommendations are provided to develop an effective fatigue management approach for South Asian countries.
{"title":"Regulators’ perceptions of flight crew fatigue management regulations in South Asia","authors":"Chanika D. Mannawaduge , Silvia Pignata , Siobhan Banks , Jillian Dorrian","doi":"10.1016/j.cstp.2025.101686","DOIUrl":"10.1016/j.cstp.2025.101686","url":null,"abstract":"<div><div>Flight crew fatigue has been identified as a risk caused by various factors including duty start time, extended duty periods, circadian rhythm disruption, inadequate sleep and rest, workload and lack of in-flight rest facilities. This study extends <span><span>Mannawaduge et al.’s (2025)</span></span> application of the flight crew fatigue evaluation framework (FREF) to ascertain perceptions of civil aviation regulations in managing flight crew fatigue in the South Asian region. Semi-structured interviews with five South Asian civil aviation regulators were conducted via Zoom. Interview transcripts were examined using content analysis focusing on how key FREF factors/aspects were implemented in the regulations, the perceived adequacy of their regulations, and any future challenges and recommendations for fatigue management. The results provide valuable insights into each country’s method of managing fatigue (prescriptive/FRMS/combination) and the guidance of the European Union Aviation Safety Agency (EASA) in developing their regulations. Notably, participants acknowledged that some fatigue-related factors (flight time/flight duty period/duty period start time, workload, in-flight rest facilities, fatigue awareness /education, and fatigue reporting processes), were not always explicit in their regulations. Participants identified regulatory challenges in the costs of FRMS implementation, productivity-based salary structures of flight crew and the incorporation of sleep-related scientific factors identified by ICAO Doc 9966 (start time of flight time/flight duty period/duty period, sleep, workload, in-flight rest) into the regulations. Recommendations are provided to develop an effective fatigue management approach for South Asian countries.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"23 ","pages":"Article 101686"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146037374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-01-11DOI: 10.1016/j.cstp.2026.101712
Siddhartha Mukhopadhyay, Goutam Sen
While the complete lockdown and closure of Railway transportation help control the spread of highly infectious diseases such as SARS, MERS, Ebola, COVID-19, and Monkeypox, it directly causes distress in people’s lives or indirectly. The study aims to develop a scientific partial lockdown approach to strategize the control of passenger traffic in the suburban train network of the Indian Railways. We use a stochastic agent-based model to understand the trade-off between various traffic levels in a railway network and the state’s health infrastructure. This problem is entirely new in the academic literature, but has gained a lot of importance due to sudden outbreaks of infectious diseases in the recent past. The study uses COVID-19 infection parameters in the Kharagpur-Howrah suburban train route in eastern India and allows various traffic levels for the agent-based simulation. The simulation calculated the impact of the resulting infection caseload due to existing infected people and additional train traffic for the first nine blocks along the route (strategy 1). Using further interventions such as age-specific restrictions, the simulation is redeployed to report the resulting caseloads against the existing healthcare capacity of these blocks (strategy 2). The study reveals that suburban train services in high-traffic areas like Kharagpur-2 increase infection cases by up to 0.77% among vulnerable populations. However, blocks with meager traffic, like Kolaghat, have meager variation. Age-wise movement restrictions, such as restricting children and citizens over 60, reduce caseloads. The optimal traffic levels for Kharagpur-2 were 40% and 50% compared to pre-COVID-19 levels, based on healthcare availability data.
{"title":"Partial lockdown strategies for suburban trains in Indian Railways","authors":"Siddhartha Mukhopadhyay, Goutam Sen","doi":"10.1016/j.cstp.2026.101712","DOIUrl":"10.1016/j.cstp.2026.101712","url":null,"abstract":"<div><div>While the complete lockdown and closure of Railway transportation help control the spread of highly infectious diseases such as SARS, MERS, Ebola, COVID-19, and Monkeypox, it directly causes distress in people’s lives or indirectly. The study aims to develop a scientific partial lockdown approach to strategize the control of passenger traffic in the suburban train network of the Indian Railways. We use a stochastic agent-based model to understand the trade-off between various traffic levels in a railway network and the state’s health infrastructure. This problem is entirely new in the academic literature, but has gained a lot of importance due to sudden outbreaks of infectious diseases in the recent past. The study uses COVID-19 infection parameters in the Kharagpur-Howrah suburban train route in eastern India and allows various traffic levels for the agent-based simulation. The simulation calculated the impact of the resulting infection caseload due to existing infected people and additional train traffic for the first nine blocks along the route (strategy 1). Using further interventions such as age-specific restrictions, the simulation is redeployed to report the resulting caseloads against the existing healthcare capacity of these blocks (strategy 2). The study reveals that suburban train services in high-traffic areas like Kharagpur-2 increase infection cases by up to 0.77% among vulnerable populations. However, blocks with meager traffic, like Kolaghat, have meager variation. Age-wise movement restrictions, such as restricting children and citizens over 60, reduce caseloads. The optimal traffic levels for Kharagpur-2 were 40% and 50% compared to pre-COVID-19 levels, based on healthcare availability data.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"23 ","pages":"Article 101712"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146037381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As cities worldwide face mounting climate challenges, understanding e-bicycle experiences in car-dependent regions is crucial for sustainable transportation planning. This study examines factors that promote or hinder e-bicycle usage in metro-Detroit, Michigan through an innovative methodological approach combining Content Analysis, Text Mining (TF-IDF), and Biterm Topic Modeling (BTM). Our analysis of open-ended survey responses from current e-bicyclists revealed distinct linguistic and thematic patterns: positive experiences centered around terms like “e-bike” “ride,” and “save” corresponding to thematic categories of car substitution (24%), increased riding (21%), and commuting (21%), while negative experiences concentrated around “driver” and “battery,” reflecting driver hostility (36%) and bike performance issues (28%). The BTM uncovered how these elements interact within cohesive experiential themes, where enhanced mobility, health benefits, and sustainable transportation options reinforce positive experiences, while technical limitations interact with infrastructure deficiencies and social barriers to create compound adoption challenges. Our findings illuminate how e-bicycle adoption in car-centric regions requires addressing interconnected technical, social, and infrastructure factors simultaneously rather than as isolated variables, providing crucial insights for policymakers seeking to promote sustainable transportation transitions in North American cities.
{"title":"E-bicyclist experiences in motor city: A mixed computational and content analysis approach for understanding sustainable micromobility","authors":"Greg Rybarczyk , Alyssa Sklar , Lorne Platt , Xiang Yan","doi":"10.1016/j.cstp.2025.101581","DOIUrl":"10.1016/j.cstp.2025.101581","url":null,"abstract":"<div><div>As cities worldwide face mounting climate challenges, understanding e-bicycle experiences in car-dependent regions is crucial for sustainable transportation planning. This study examines factors that promote or hinder e-bicycle usage in metro-Detroit, Michigan through an innovative methodological approach combining Content Analysis, Text Mining (TF-IDF), and Biterm Topic Modeling (BTM). Our analysis of open-ended survey responses from current e-bicyclists revealed distinct linguistic and thematic patterns: positive experiences centered around terms like “e-bike” “ride,” and “save” corresponding to thematic categories of car substitution (24%), increased riding (21%), and commuting (21%), while negative experiences concentrated around “driver” and “battery,” reflecting driver hostility (36%) and bike performance issues (28%). The BTM uncovered how these elements interact within cohesive experiential themes, where enhanced mobility, health benefits, and sustainable transportation options reinforce positive experiences, while technical limitations interact with infrastructure deficiencies and social barriers to create compound adoption challenges. Our findings illuminate how e-bicycle adoption in car-centric regions requires addressing interconnected technical, social, and infrastructure factors simultaneously rather than as isolated variables, providing crucial insights for policymakers seeking to promote sustainable transportation transitions in North American cities.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"22 ","pages":"Article 101581"},"PeriodicalIF":3.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144916923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01Epub Date: 2025-09-19DOI: 10.1016/j.cstp.2025.101615
Corey Johnson , Jianfeng Zheng , Shemar Reid , Nicholas Campbell , Majda Rahhali , Claire Irungu
After the colossal impact of Hurricane Ian in 2022, this prompted the need to investigate the extent of the damage and, more importantly, the policies implemented to mitigate against it. That tropical storm, while passing over Jamaica, intensified into a hurricane as it hit North America in mid-September of 2022. As such, this research was conducted over the final quarter of the year 2022. As hurricanes and natural disasters morph, some regions face greater risks of flooding and a rise in sea level that occurs subsequent to it. The tropical region of the Caribbean faces these coastal disasters annually, in some cases biannually. In the Caribbean Sea, all the countries located centrally are islands. Their ports are essential as it is the only physical contact they have with each other and the rest of the world. Therefore, the damage they incur and the prevention methods must be of high importance to different regulatory bodies. This paper will analyse the frequent occurrence of natural disasters, including flooding induced by hurricanes/heavy rainfall and the rise in sea level. The way the occurrence is handled was tabulated based on a series of interviews from various governing bodies on the island. From this, the Hurricane Aftermath Evaluation Method was created, a method that holds five main variables: type of damage, extent of infrastructure damage, port downtime, impact on economy and strategies for recovery and mitigation. The study concludes that the Port of Kingston is highly susceptible to coastal disasters, and oftentimes, the infrastructure and regulatory bodies alike are grossly underprepared to combat them. Therefore, reconstruction of the drainage system must be done along with further study and improvement to the surrounding infrastructure currently in place.
{"title":"Port and road network development post coastal disaster: Hurricane Ian flooding of port of Kingston, Jamaica","authors":"Corey Johnson , Jianfeng Zheng , Shemar Reid , Nicholas Campbell , Majda Rahhali , Claire Irungu","doi":"10.1016/j.cstp.2025.101615","DOIUrl":"10.1016/j.cstp.2025.101615","url":null,"abstract":"<div><div>After the colossal impact of Hurricane Ian in 2022, this prompted the need to investigate the extent of the damage and, more importantly, the policies implemented to mitigate against it. That tropical storm, while passing over Jamaica, intensified into a hurricane as it hit North America in mid-September of 2022. As such, this research was conducted over the final quarter of the year 2022. As hurricanes and natural disasters morph, some regions face greater risks of flooding and a rise in sea level that occurs subsequent to it. The tropical region of the Caribbean faces these coastal disasters annually, in some cases biannually. In the Caribbean Sea, all the countries located centrally are islands. Their ports are essential as it is the only physical contact they have with each other and the rest of the world. Therefore, the damage they incur and the prevention methods must be of high importance to different regulatory bodies. This paper will analyse the frequent occurrence of natural disasters, including flooding induced by hurricanes/heavy rainfall and the rise in sea level. The way the occurrence is handled was tabulated based on a series of interviews from various governing bodies on the island. From this, the Hurricane Aftermath Evaluation Method was created, a method that holds five main variables: type of damage, extent of infrastructure damage, port downtime, impact on economy and strategies for recovery and mitigation. The study concludes that the Port of Kingston is highly susceptible to coastal disasters, and oftentimes, the infrastructure and regulatory bodies alike are grossly underprepared to combat them. Therefore, reconstruction of the drainage system must be done along with further study and improvement to the surrounding infrastructure currently in place.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"22 ","pages":"Article 101615"},"PeriodicalIF":3.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145109288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01Epub Date: 2025-09-19DOI: 10.1016/j.cstp.2025.101617
Simon Louis Opit, Karen Witten
This research investigates the challenges to collaboration government agencies face in delivering active travel infrastructure as part of neighbourhood regeneration projects. Through a sociotechnical systems lens, we examine the influence of governance structures, decision-making processes, and institutional norms on inter-agency collaboration. Drawing on document analysis and key informant interviews, we identify opportunities and challenges faced by housing and transport agencies in coordinating the design and delivery of active travel infrastructure. Challenges include a disconnect between strategic objectives and funding mechanisms, bureaucratic inertia and complexity, and a reliance on informal networks within a complex regulatory structure. Despite these challenges, the research highlights the value of forums for knowledge exchange and relational approaches to collaboration, as well as the potential for pragmatic solutions such as collaborative working groups to overcome structural barriers within sociotechnical regimes. Achieving mode shift towards healthier and more sustainable forms of transport requires formalised effective mechanisms for integration of land use and transport planning. Our findings have implications for policymakers, practitioners, and stakeholders involved in shaping urban environments and promoting active mobility as a viable transportation option.
{"title":"Overcoming barriers to delivering active travel infrastructure: inter-agency collaboration in a state-led neighbourhood redevelopment","authors":"Simon Louis Opit, Karen Witten","doi":"10.1016/j.cstp.2025.101617","DOIUrl":"10.1016/j.cstp.2025.101617","url":null,"abstract":"<div><div>This research investigates the challenges to collaboration government agencies face in delivering active travel infrastructure as part of neighbourhood regeneration projects. Through a sociotechnical systems lens, we examine the influence of governance structures, decision-making processes, and institutional norms on inter-agency collaboration. Drawing on document analysis and key informant interviews, we identify opportunities and challenges faced by housing and transport agencies in coordinating the design and delivery of active travel infrastructure. Challenges include a disconnect between strategic objectives and funding mechanisms, bureaucratic inertia and complexity, and a reliance on informal networks within a complex regulatory structure. Despite these challenges, the research highlights the value of forums for knowledge exchange and relational approaches to collaboration, as well as the potential for pragmatic solutions such as collaborative working groups to overcome structural barriers within sociotechnical regimes. Achieving mode shift towards healthier and more sustainable forms of transport requires formalised effective mechanisms for integration of land use and transport planning. Our findings have implications for policymakers, practitioners, and stakeholders involved in shaping urban environments and promoting active mobility as a viable transportation option.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"22 ","pages":"Article 101617"},"PeriodicalIF":3.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145219760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号