Pub Date : 2025-02-11DOI: 10.1016/j.cstp.2025.101390
Md Musfiqur Rahman Bhuiya , Jun Liu , Steven Jones , Qifan Nie
Traffic violations are one of the major causes of road crashes. This study investigates traffic crashes involving traffic sign or signal violations at intersections in Alabama, USA by exploiting a statewide crash database with nearly 60,000 sign or signal violation crashes to inform mitigation strategies. This study aims to identify factors contributing to traffic sign or signal violation crashes at intersections, with a particular focus on local characteristics, including the built environment and socioeconomic factors. Due to the multi-level data structure, this study employs a hierarchical modeling approach to explore the correlates of intersection crashes and develop models by integrating hierarchical modeling with the binary logit model and negative binomial model separately to explain factors contributing to both types of crashes. The modeling results reveal that signal violation and stop sign violation crashes occur more frequently at intersections close to open spaces. Both violation crashes are more likely to occur in block groups with more low-income or under-educated households. Further, the crash frequencies are positively related to the distance from an intersection to its nearest law enforcement agency and negatively related to the number of police officers in an area.
{"title":"Is there any association of local characteristics with traffic signal and stop sign violation induced crashes? A Hierarchical Modeling based study from Alabama, USA","authors":"Md Musfiqur Rahman Bhuiya , Jun Liu , Steven Jones , Qifan Nie","doi":"10.1016/j.cstp.2025.101390","DOIUrl":"10.1016/j.cstp.2025.101390","url":null,"abstract":"<div><div>Traffic violations are one of the major causes of road crashes. This study investigates traffic crashes involving traffic sign or signal violations at intersections in Alabama, USA by exploiting a statewide crash database with nearly 60,000 sign or signal violation crashes to inform mitigation strategies. This study aims to identify factors contributing to traffic sign or signal violation crashes at intersections, with a particular focus on local characteristics, including the built environment and socioeconomic factors. Due to the multi-level data structure, this study employs a hierarchical modeling approach to explore the correlates of intersection crashes and develop models by integrating hierarchical modeling with the binary logit model and negative binomial model separately to explain factors contributing to both types of crashes. The modeling results reveal that signal violation and stop sign violation crashes occur more frequently at intersections close to open spaces. Both violation crashes are more likely to occur in block groups with more low-income or under-educated households. Further, the crash frequencies are positively related to the distance from an intersection to its nearest law enforcement agency and negatively related to the number of police officers in an area.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"19 ","pages":"Article 101390"},"PeriodicalIF":2.4,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143438011","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 : 2025-02-10DOI: 10.1016/j.cstp.2025.101388
Chayanon Phucharoen, Nichapat Sangkaew
This study examines the influence of income support policies (ISPs) in 128 countries on mobility near suppliers of essential goods during the various SARS-CoV-2 control measures in 2020 and 2021. Using Google Mobility and Oxford COVID-19 Government Response Tracker data, we employed a country fixed-effect model to assess ISP effects on mobility from complete lockdown to restriction-free periods. Results show ISPs significantly reduce mobility during semi-lockdowns but increase it during complete lockdowns. In the absence of restrictions, implementing ISPs boosts mobility around essential goods suppliers by 17%, more than in non-ISP stages. Additionally, the study reveals that the impact of ISPs is enhanced in countries with an established electronic finance infrastructure, as measured by the Inclusive Internet Index. This research provides initial evidence for the impact of ISPs on consumption mobility through different restriction measures and emphasises the crucial role of e-finance platforms in optimising government income aid policy during mobility constraint and economic recovery phases.
{"title":"Effect of income support policy on consumption mobility amidst the global pandemic: A country-level panel data analysis","authors":"Chayanon Phucharoen, Nichapat Sangkaew","doi":"10.1016/j.cstp.2025.101388","DOIUrl":"10.1016/j.cstp.2025.101388","url":null,"abstract":"<div><div>This study examines the influence of income support policies (ISPs) in 128 countries on mobility near suppliers of essential goods during the various SARS-CoV-2 control measures in 2020 and 2021. Using Google Mobility and Oxford COVID-19 Government Response Tracker data, we employed a country fixed-effect model to assess ISP effects on mobility from complete lockdown to restriction-free periods. Results show ISPs significantly reduce mobility during semi-lockdowns but increase it during complete lockdowns. In the absence of restrictions, implementing ISPs boosts mobility around essential goods suppliers by 17%, more than in non-ISP stages. Additionally, the study reveals that the impact of ISPs is enhanced in countries with an established electronic finance infrastructure, as measured by the Inclusive Internet Index. This research provides initial evidence for the impact of ISPs on consumption mobility through different restriction measures and emphasises the crucial role of e-finance platforms in optimising government income aid policy during mobility constraint and economic recovery phases.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"19 ","pages":"Article 101388"},"PeriodicalIF":2.4,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143396222","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 : 2025-02-08DOI: 10.1016/j.cstp.2025.101391
Suk Hee Kim , Yongju Yi , Chae Rin Kim , Junghwa Kim
Many cities worldwide are beginning to focus on the Car-Free Policy to increase urban spaces and create sustainable cities considering the public demand for open space. However, existing studies suggest that the car-free day’s operating factors and guidelines focus solely on quantitative data of effectiveness. However, existing studies suggest that the car-free day’s operating factor and guidelines only bring quantitative data of effectiveness to a halt. Therefore, the analysis of the user perception and behavioral change according to the car-free day operation, and the impact of each factor of the event is insufficient. This study analyzes the user perceptions and behavioral changes according to 10 car-free days in Suwon. Using the data collected from the research, we propose improvement strategies by verifying behavioral changes with user perception. We divide 24 measured variables into six categories: types of event, event operation, infrastructure, change in perception, mobility patterns, and visiting hours. Further, this research sets three premises for the proposal, followed by nine hypotheses to determine the further study of the relationship between customer satisfaction, user perception, and behavioral changes according to the car-free day operation. Using structural equation models and examining path analysis, the user perception is mainly influenced by user satisfaction, satisfaction with transportation and infrastructure, and behavioral change is mainly influenced by factors such as visiting hours and changes in perception. This research identified the detailed factors influencing user perception and behavioral change according to a car-free day operation and aims to contribute to the establishment of activating car-free streets. Moreover, the car-free days in Suwon city increased, and by including cohort research methods, further research can be conducted to determine whether car-free days actually cause behavioral changes and whether user perception is improved every year.
{"title":"Will citizen participatory transport policies affect people to use cars less? Empirical evidence from car-free day project in South Korea","authors":"Suk Hee Kim , Yongju Yi , Chae Rin Kim , Junghwa Kim","doi":"10.1016/j.cstp.2025.101391","DOIUrl":"10.1016/j.cstp.2025.101391","url":null,"abstract":"<div><div>Many cities worldwide are beginning to focus on the Car-Free Policy to increase urban spaces and create sustainable cities considering the public demand for open space. However, existing studies suggest that the car-free day’s operating factors and guidelines focus solely on quantitative data of effectiveness. However, existing studies suggest that the car-free day’s operating factor and guidelines only bring quantitative data of effectiveness to a halt. Therefore, the analysis of the user perception and behavioral change according to the car-free day operation, and the impact of each factor of the event is insufficient. This study analyzes the user perceptions and behavioral changes according to 10 car-free days in Suwon. Using the data collected from the research, we propose improvement strategies by verifying behavioral changes with user perception. We divide 24 measured variables into six categories: types of event, event operation, infrastructure, change in perception, mobility patterns, and visiting hours. Further, this research sets three premises for the proposal, followed by nine hypotheses to determine the further study of the relationship between customer satisfaction, user perception, and behavioral changes according to the car-free day operation. Using structural equation models and examining path analysis, the user perception is mainly influenced by user satisfaction, satisfaction with transportation and infrastructure, and behavioral change is mainly influenced by factors such as visiting hours and changes in perception. This research identified the detailed factors influencing user perception and behavioral change according to a car-free day operation and aims to contribute to the establishment of activating car-free streets. Moreover, the car-free days in Suwon city increased, and by including cohort research methods, further research can be conducted to determine whether car-free days actually cause behavioral changes and whether user perception is improved every year.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"20 ","pages":"Article 101391"},"PeriodicalIF":2.4,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143510403","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 : 2025-02-07DOI: 10.1016/j.cstp.2025.101392
Hannah Budnitz, Xiao Li, Helen Morrissey, Tim Schwanen
The availability and adoption of rental e-scooter services, proliferating in cities globally, are spatially and socially uneven. Studies suggest that a majority of users in North American and European cities are men with higher incomes and more education than the average. The use of shared e-scooters by sociodemographic groups that are more likely to have access to a car and a wide range of opportunities raises questions as to whether this new transport technology entrenches inequalities. However, few studies focus on e-scooter use in England, where only shared e-scooters permitted and regulated by the UK’s Department for Transport alongside relevant local governments on a trial basis are legal for travel on the public highway. These services were therefore often introduced to achieve policy objectives, and the government commissioned a national evaluation of the e-scooter trials in English cities to understand their impacts. The evaluation report suggests they are popular among low-income and minority ethnic riders, but highlights the need for further study, such as the one presented here. This article uses a transport poverty framing and a dataset of 3.6 million e-scooter trips taken over 13 months in Bristol to investigate the uneven sociodemographic and spatial patterns of rental e-scooter use. We find that, holding all else equal, more e-scooter trips are taken from areas with larger shares of younger (under 35), black and Asian individuals. However, there are fewer e-scooter trip origins from areas of greater deprivation in Bristol. This suggests that while younger, Black, and Asian populations may be more likely to adopt or have access to e-scooters as a mode of transport, fewer e-scooter trips from areas of greater deprivation indicate potential barriers to access or adoption in these communities.
{"title":"Understanding the uneven use of rental e-scooters and implications for equity: Evidence from England’s largest e-scooter trial","authors":"Hannah Budnitz, Xiao Li, Helen Morrissey, Tim Schwanen","doi":"10.1016/j.cstp.2025.101392","DOIUrl":"10.1016/j.cstp.2025.101392","url":null,"abstract":"<div><div>The availability and adoption of rental e-scooter services, proliferating in cities globally, are spatially and socially uneven. Studies suggest that a majority of users in North American and European cities are men with higher incomes and more education than the average. The use of shared e-scooters by sociodemographic groups that are more likely to have access to a car and a wide range of opportunities raises questions as to whether this new transport technology entrenches inequalities. However, few studies focus on e-scooter use in England, where only shared e-scooters permitted and regulated by the UK’s Department for Transport alongside relevant local governments on a trial basis are legal for travel on the public highway. These services were therefore often introduced to achieve policy objectives, and the government commissioned a national evaluation of the e-scooter trials in English cities to understand their impacts. The evaluation report suggests they are popular among low-income and minority ethnic riders, but highlights the need for further study, such as the one presented here. This article uses a transport poverty framing and a dataset of 3.6 million e-scooter trips taken over 13 months in Bristol to investigate the uneven sociodemographic and spatial patterns of rental e-scooter use. We find that, holding all else equal, more e-scooter trips are taken from areas with larger shares of younger (under 35), black and Asian individuals. However, there are fewer e-scooter trip origins from areas of greater deprivation in Bristol. This suggests that while younger, Black, and Asian populations may be more likely to adopt or have access to e-scooters as a mode of transport, fewer e-scooter trips from areas of greater deprivation indicate potential barriers to access or adoption in these communities.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"19 ","pages":"Article 101392"},"PeriodicalIF":2.4,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143377212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-04DOI: 10.1016/j.cstp.2025.101385
Marco Petrelli , Ernesto Cipriani , Umberto Crisalli , Andrea Gemma , Livia Mannini
The present paper proposes a methodology aimed at design bus public network suited to serve high-sensitive zones of the study area with low-impact vehicles. The purpose is to provide a procedure for support a smart electrification of public transport bus network, optimizing the use of electric vehicles where it is most effective to operate them. The new methodology solves a Transit Network Design (TND) problem where the optimization model consists of minimizing costs and resources in a public transport network also including sustainability issues. Therefore, starting from the method presented in Cipriani et al. (2012), the issue is framed as a multi-objective model, combining two objectives: the classic TND objective and the second related to the identification of the use of electric vehicles where it is most effective to operate them. The complexity of such issues needs metaheuristic algorithms application, in which the GA permits to obtain Pareto optimal non dominated solutions for the TND. Such solutions are then exploited as a multi-objective analysis, treating conventional objectives and objectives for a better use of electric vehicles, separately. The methodology has been implemented in a case study in the city of Rome. The findings demonstrate the effectiveness of methodology to design robust public transport supply system suited to serve high-sensitive zones.
{"title":"Transit network design: A sustainability-oriented methodology for the management of large bus networks and low emission zones","authors":"Marco Petrelli , Ernesto Cipriani , Umberto Crisalli , Andrea Gemma , Livia Mannini","doi":"10.1016/j.cstp.2025.101385","DOIUrl":"10.1016/j.cstp.2025.101385","url":null,"abstract":"<div><div>The present paper proposes a methodology aimed at design bus public network suited to serve high-sensitive zones of the study area with low-impact vehicles. The purpose is to provide a procedure for support a smart electrification of public transport bus network, optimizing the use of electric vehicles where it is most effective to operate them. The new methodology solves a Transit Network Design (TND) problem where the optimization model consists of minimizing costs and resources in a public transport network also including sustainability issues. Therefore, starting from the method presented in <span><span>Cipriani et al. (2012)</span></span>, the issue is framed as a multi-objective model, combining two objectives: the classic TND objective and the second related to the identification of the use of electric vehicles where it is most effective to operate them. The complexity of such issues needs metaheuristic algorithms application, in which the GA permits to obtain Pareto optimal non dominated solutions for the TND. Such solutions are then exploited as a multi-objective analysis, treating conventional objectives and objectives for a better use of electric vehicles, separately. The methodology has been implemented in a case study in the city of Rome. The findings demonstrate the effectiveness of methodology to design robust public transport supply system suited to serve high-sensitive zones.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"19 ","pages":"Article 101385"},"PeriodicalIF":2.4,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143402941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-04DOI: 10.1016/j.cstp.2025.101389
Jingyuan Wang, Shintaro Terabe, Hideki Yaginuma
This study presents a novel covariate selection method that combines Maximum Likelihood Estimation (MLE) with the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC), focusing on achieving a balance between model fit and complexity. Our findings emphasize the significant impact of covariates on estimated results in Propensity Score Matching (PSM) analyses. Through case studies, we validate the effectiveness of our proposed method across various PSM approaches, including one-to-one matching, K-nearest neighbors matching, radius matching, kernel matching, and Inverse Probability Weighting (IPW). For researchers constrained to cross-sectional data, our comparisons among different PSM methodologies provide valuable insights. Additionally, we explore the applicability of our method to PSM extensions such as Covariate Balancing Propensity Score (CBPS) and PSM-Difference-in-Differences (DID). Our case study reveals significant causal effects of Japan’s Shinkansen on population changes, with notable growth observed in both cross-sectional and panel data analyses.These findings hold important implications for transportation policy, and we offer recommendations for relevant policymakers based on our results.
{"title":"Covariate selection in propensity score matching: A case study of how the Shinkansen has impacted population changes in Japan","authors":"Jingyuan Wang, Shintaro Terabe, Hideki Yaginuma","doi":"10.1016/j.cstp.2025.101389","DOIUrl":"10.1016/j.cstp.2025.101389","url":null,"abstract":"<div><div>This study presents a novel covariate selection method that combines Maximum Likelihood Estimation (MLE) with the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC), focusing on achieving a balance between model fit and complexity. Our findings emphasize the significant impact of covariates on estimated results in Propensity Score Matching (PSM) analyses. Through case studies, we validate the effectiveness of our proposed method across various PSM approaches, including one-to-one matching, K-nearest neighbors matching, radius matching, kernel matching, and Inverse Probability Weighting (IPW). For researchers constrained to cross-sectional data, our comparisons among different PSM methodologies provide valuable insights. Additionally, we explore the applicability of our method to PSM extensions such as Covariate Balancing Propensity Score (CBPS) and PSM-Difference-in-Differences (DID). Our case study reveals significant causal effects of Japan’s Shinkansen on population changes, with notable growth observed in both cross-sectional and panel data analyses.These findings hold important implications for transportation policy, and we offer recommendations for relevant policymakers based on our results.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"19 ","pages":"Article 101389"},"PeriodicalIF":2.4,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143388014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-04DOI: 10.1016/j.cstp.2025.101386
Tara McGuicken , Lorraine Whitmarsh , Samuel Hampton
Ambitious national targets for reducing transport emissions require effective policies that disturb entrenched unsustainable travel behaviours, in particular car use. One approach policymakers can adopt is to leverage transport environment disruptions as opportunities to destabilise habits and facilitate shifts in travel behaviour. A framework consisting of four key dimensions of disruptions (plannedness, scale, frequency, and duration) is presented. The current study investigates whether UK transport policymakers and practitioners currently recognise opportunities in transport environment disruptions across these dimensions, and the factors facilitating or preventing this approach. Through qualitative analysis of in-depth interviews with 23 transport practitioners from various UK transport organisations and key strategic documents, the findings reveal that while practitioners acknowledge the potential of disruptions in the transport environment to foster behavioural shifts to some extent, general approaches are limited in their conceptualisations of disruptions. Recommendations emphasise the need for comprehensive strategies that leverage disruptions driven by bold political leadership to overcome car dependency and achieve sustainable transport goals.
{"title":"Transport disruptions as opportunities for behaviour change: A qualitative evaluation of UK policy and practice","authors":"Tara McGuicken , Lorraine Whitmarsh , Samuel Hampton","doi":"10.1016/j.cstp.2025.101386","DOIUrl":"10.1016/j.cstp.2025.101386","url":null,"abstract":"<div><div>Ambitious national targets for reducing transport emissions require effective policies that disturb entrenched unsustainable travel behaviours, in particular car use. One approach policymakers can adopt is to leverage transport environment disruptions as opportunities to destabilise habits and facilitate shifts in travel behaviour. A framework consisting of four key dimensions of disruptions (plannedness, scale, frequency, and duration) is presented. The current study investigates whether UK transport policymakers and practitioners currently recognise opportunities in transport environment disruptions across these dimensions, and the factors facilitating or preventing this approach. Through qualitative analysis of in-depth interviews with 23 transport practitioners from various UK transport organisations and key strategic documents, the findings reveal that while practitioners acknowledge the potential of disruptions in the transport environment to foster behavioural shifts to some extent, general approaches are limited in their conceptualisations of disruptions. Recommendations emphasise the need for comprehensive strategies that leverage disruptions driven by bold political leadership to overcome car dependency and achieve sustainable transport goals.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"19 ","pages":"Article 101386"},"PeriodicalIF":2.4,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143349028","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 : 2025-01-31DOI: 10.1016/j.cstp.2025.101387
Eduardo Bilbao Pavón , Luis Alonso Pastor , Alejandro Padilla , Mayra Gamboa , Kent Larson
This study focuses on addressing the mobility challenges faced by developing regions of Latin America as data collection and the composition of formal and informal transportation. In this article, a tool is developed using a Machine Learning (ML) model that is able to learn and predict the patterns for choosing one mobility choice over another based on a student survey of the University of Guadalajara (UdeG). The study helps to understand which are the most relevant factors influencing mobility choice at one of the largest universities in Latin America, with travel time and number of household vehicles being the most determinant factors. The tool effectiveness is validated by the creation of two scenarios that simulate changes in mobility choices by relocating individuals closer to their destinations. The conducted experiment demonstrates a tendency towards walking and a significant decrease in private auto usage by relocating people closer to their destinations. The creation of this tool aims to help public institutions in making better decisions to develop a better society with reduced pollution, enhanced social impacts and climate change effects.
{"title":"Predicting mobility choice and community connectivity in Latin America","authors":"Eduardo Bilbao Pavón , Luis Alonso Pastor , Alejandro Padilla , Mayra Gamboa , Kent Larson","doi":"10.1016/j.cstp.2025.101387","DOIUrl":"10.1016/j.cstp.2025.101387","url":null,"abstract":"<div><div>This study focuses on addressing the mobility challenges faced by developing regions of Latin America as data collection and the composition of formal and informal transportation. In this article, a tool is developed using a Machine Learning (ML) model that is able to learn and predict the patterns for choosing one mobility choice over another based on a student survey of the University of Guadalajara (UdeG). The study helps to understand which are the most relevant factors influencing mobility choice at one of the largest universities in Latin America, with travel time and number of household vehicles being the most determinant factors. The tool effectiveness is validated by the creation of two scenarios that simulate changes in mobility choices by relocating individuals closer to their destinations. The conducted experiment demonstrates a tendency towards walking and a significant decrease in private auto usage by relocating people closer to their destinations. The creation of this tool aims to help public institutions in making better decisions to develop a better society with reduced pollution, enhanced social impacts and climate change effects.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"19 ","pages":"Article 101387"},"PeriodicalIF":2.4,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143368295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-31DOI: 10.1016/j.cstp.2025.101384
Johanna Marie Kunsmann, Peter Letmathe
Even though Germany’s carsharing market has experienced rapid growth in recent years, the actual share of carsharing usage in daily mobility remains low. However, in terms of individual transportation, the use of carsharing as an alternative to private vehicle ownership could lead to a more sustainable mobility system. To realize environmental and social benefits, consumers’ awareness of the potential financial benefits has to be enhanced, as financial considerations are a decisive and under-researched factor for changes in mobility habits. To close this gap, our study provides a transparent economic analysis of those individual transportation solutions by employing a Total Cost of Usage (TCU) model for the permanent carsharing usage and a Total Cost of Ownership (TCO) model for private vehicle ownership based on real-world market data from the German economic area. Additionally, we assess the impact of higher residential parking fees, and the impact of changes in residual values of private vehicles, as well as of changes in carsharing tariffs. Overall, the results indicate a high financial competitiveness of carsharing compared to vehicle ownership in all vehicle segments and across different driver profiles. In particular, the targeted design of policy instruments, such as an increase in residential parking fees strengthens the economic advantages of carsharing and may trigger consumers to switch from private vehicle ownership to carsharing as a more sustainable individual mobility solution.
{"title":"Car ownership versus carsharing? An analysis comparing socio-economic and policy factors of carsharing and car ownership","authors":"Johanna Marie Kunsmann, Peter Letmathe","doi":"10.1016/j.cstp.2025.101384","DOIUrl":"10.1016/j.cstp.2025.101384","url":null,"abstract":"<div><div>Even though Germany’s carsharing market has experienced rapid growth in recent years, the actual share of carsharing usage in daily mobility remains low. However, in terms of individual transportation, the use of carsharing as an alternative to private vehicle ownership could lead to a more sustainable mobility system. To realize environmental and social benefits, consumers’ awareness of the potential financial benefits has to be enhanced, as financial considerations are a decisive and under-researched factor for changes in mobility habits. To close this gap, our study provides a transparent economic analysis of those individual transportation solutions by employing a Total Cost of Usage (TCU) model for the permanent carsharing usage and a Total Cost of Ownership (TCO) model for private vehicle ownership based on real-world market data from the German economic area. Additionally, we assess the impact of higher residential parking fees, and the impact of changes in residual values of private vehicles, as well as of changes in carsharing tariffs. Overall, the results indicate a high financial competitiveness of carsharing compared to vehicle ownership in all vehicle segments and across different driver profiles. In particular, the targeted design of policy instruments, such as an increase in residential parking fees strengthens the economic advantages of carsharing and may trigger consumers to switch from private vehicle ownership to carsharing as a more sustainable individual mobility solution.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"19 ","pages":"Article 101384"},"PeriodicalIF":2.4,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-27DOI: 10.1016/j.cstp.2025.101381
Matthew Wigginton Bhagat-Conway , Luke Pullo , Kai Monast
Demand-response transit is the backbone of many rural transit systems. Demand-response transit provides riders with curb-to-curb service, not following fixed routes or schedules. While automated and semi-automated demand response scheduling has existed for decades, many agencies create schedules manually, using some form of computer-assisted schedule management. However, some transit agencies have recently adopted “microtransit” scheduling software packages that place an increasingly strong focus on fully automating the creation of schedules, and providing same-day service. In this article, we evaluate the recent implementation of automated scheduling software at two rural agencies in North Carolina.
We visited both agencies and conducted in-depth observations of their scheduling staff’s use of the software, as well as interviews with management. We found that neither agency used automated scheduling features of their software extensively. There were two main reasons for this. Firstly, automated scheduling was not seen as necessary; schedulers are experts on their regions and customers, and can create efficient schedules manually. Secondly, automated scheduling did not always match the service pattern of the agency, for instance by insufficiently prioritizing shared rides.
Agencies considering software purchases should consider what their needs and desires for a microtransit or automated scheduling system are. This process should involve both management and scheduling staff, to ensure the purchased system meets the needs of the agency. Automated scheduling and microtransit systems may not be a good fit for all agencies, particularly if existing scheduling practices are already working well.
{"title":"Evaluating the effectiveness of automated scheduling at rural transit agencies in north carolina","authors":"Matthew Wigginton Bhagat-Conway , Luke Pullo , Kai Monast","doi":"10.1016/j.cstp.2025.101381","DOIUrl":"10.1016/j.cstp.2025.101381","url":null,"abstract":"<div><div>Demand-response transit is the backbone of many rural transit systems. Demand-response transit provides riders with curb-to-curb service, not following fixed routes or schedules. While automated and semi-automated demand response scheduling has existed for decades, many agencies create schedules manually, using some form of computer-assisted schedule management. However, some transit agencies have recently adopted “microtransit” scheduling software packages that place an increasingly strong focus on fully automating the creation of schedules, and providing same-day service. In this article, we evaluate the recent implementation of automated scheduling software at two rural agencies in North Carolina.</div><div>We visited both agencies and conducted in-depth observations of their scheduling staff’s use of the software, as well as interviews with management. We found that neither agency used automated scheduling features of their software extensively. There were two main reasons for this. Firstly, automated scheduling was not seen as necessary; schedulers are experts on their regions and customers, and can create efficient schedules manually. Secondly, automated scheduling did not always match the service pattern of the agency, for instance by insufficiently prioritizing shared rides.</div><div>Agencies considering software purchases should consider what their needs and desires for a microtransit or automated scheduling system are. This process should involve both management and scheduling staff, to ensure the purchased system meets the needs of the agency. Automated scheduling and microtransit systems may not be a good fit for all agencies, particularly if existing scheduling practices are already working well.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"19 ","pages":"Article 101381"},"PeriodicalIF":2.4,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143102821","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}
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