Pub 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":"2026-01-11","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}
Pub 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":"2026-01-11","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}
Transportation demand management policies have the potential to significantly alter individuals’ routine travel behavior. One of the key responses of private car passengers to the implementation of congestion plans is the adjustment of trip departure times. If the management of changing trip departure time shifts is not effective, the emergence of traffic peak periods before and after the plan may exceed current peak traffic levels. A literature review reveals that the investigation of trip departure time adjustments has received limited attention, and behavior regulation strategies to mitigate peak period formation have not been explored. The primary aim of this paper is to develop scenarios integrating transportation demand management strategies to prevent the occurrence of a tipping point. To achieve this, the effects of social and economic factors, travel characteristics, and citizens’ attitudes toward transportation demand management policies on private car passengers’ departure time shifts in the congestion zone have been examined. To estimate the probability of departure time adjustments, 2,256 individuals were interviewed in Shiraz, yielding 13,536 observations through Stated-Preference (SP) analysis. The calibration of the binary logit model has demonstrated that congestion pricing policies, parking fees, reductions in public transportation travel time, and enhancements in bus service quality exert significant influence on departure time modifications. Based on extensive policy considerations, 27 out of the 36 defined scenarios—those generating a peak period outside the congestion plan’s implementation timeframe—have been deemed unsuitable for execution. This paper introduces a novel probability-thresholding framework that operationalizes behavioral model outputs to proactively screen Transport Demand Management (TDM) scenarios for secondary congestion risks — a methodological advancement not previously applied in developing-city contexts.
{"title":"Investigating the effects of changing departure times on controlling secondary traffic peaks during the implementation of a congestion charge zone","authors":"Sedigheh KhorramDehnavi , Salman AghidiKheyrabadi , Ali MorovatiSharifabadi , Alireza NaserSadrabadi","doi":"10.1016/j.cstp.2025.101700","DOIUrl":"10.1016/j.cstp.2025.101700","url":null,"abstract":"<div><div>Transportation demand management policies have the potential to significantly alter individuals’ routine travel behavior. One of the key responses of private car passengers to the implementation of congestion plans is the adjustment of trip departure times. If the management of changing trip departure time shifts is not effective, the emergence of traffic peak periods before and after the plan may exceed current peak traffic levels. A literature review reveals that the investigation of trip departure time adjustments has received limited attention, and behavior regulation strategies to mitigate peak period formation have not been explored. The primary aim of this paper is to develop scenarios integrating transportation demand management strategies to prevent the occurrence of a tipping point. To achieve this, the effects of social and economic factors, travel characteristics, and citizens’ attitudes toward transportation demand management policies on private car passengers’ departure time shifts in the congestion zone have been examined. To estimate the probability of departure time adjustments, 2,256 individuals were interviewed in Shiraz, yielding 13,536 observations through Stated-Preference (SP) analysis. The calibration of the binary logit model has demonstrated that congestion pricing policies, parking fees, reductions in public transportation travel time, and enhancements in bus service quality exert significant influence on departure time modifications. Based on extensive policy considerations, 27 out of the 36 defined scenarios—those generating a peak period outside the congestion plan’s implementation timeframe—have been deemed unsuitable for execution. This paper introduces a novel probability-thresholding framework that operationalizes behavioral model outputs to proactively screen Transport Demand Management (TDM) scenarios for secondary congestion risks — a methodological advancement not previously applied in developing-city contexts.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"23 ","pages":"Article 101700"},"PeriodicalIF":3.3,"publicationDate":"2026-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146077281","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 : 2026-01-08DOI: 10.1016/j.cstp.2026.101709
Hossein Saedi, Ali Abdi Kordani, Hamid Reza Behnood
Social crash costs and the limitations of allocated highway safety budgets are two key factors influencing the prioritization of highway safety projects. To ensure the efficient use of these budgets, expenditures must be optimized to achieve the highest possible impact. This study presents a framework that uses the Empirical Bayesian (EB) method to develop probabilistic models of social crash costs. The framework calculates the exceedance probability of crash costs for various collision types, including rare events, through the Monte Carlo method, a technique within reliability analysis. The framework is applied to Highway 36 in Iran, which spans 186 km. Utilizing a reliability-based risk analysis, all highway segments—comprising 34 tangent and 30 horizontal curve segments—were prioritized for safety improvements. A key outcome of this study, beyond project prioritization, is the creation of exceedance probability curves for social crash costs across different collision types. These curves offer a valuable foundation for informed decision-making in risk mitigation.
{"title":"Reliability-based crash risk analysis for prioritizing safety projects","authors":"Hossein Saedi, Ali Abdi Kordani, Hamid Reza Behnood","doi":"10.1016/j.cstp.2026.101709","DOIUrl":"10.1016/j.cstp.2026.101709","url":null,"abstract":"<div><div>Social crash costs and the limitations of allocated highway safety budgets are two key factors influencing the prioritization of highway safety projects. To ensure the efficient use of these budgets, expenditures must be optimized to achieve the highest possible impact. This study presents a framework that uses the Empirical Bayesian (EB) method to develop probabilistic models of social crash costs. The framework calculates the exceedance probability of crash costs for various collision types, including rare events, through the Monte Carlo method, a technique within reliability analysis. The framework is applied to Highway 36 in Iran, which spans 186 km. Utilizing a reliability-based risk analysis, all highway segments—comprising 34 tangent and 30 horizontal curve segments—were prioritized for safety improvements. A key outcome of this study, beyond project prioritization, is the creation of exceedance probability curves for social crash costs across different collision types. These curves offer a valuable foundation for informed decision-making in risk mitigation.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"23 ","pages":"Article 101709"},"PeriodicalIF":3.3,"publicationDate":"2026-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146187499","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 : 2026-01-07DOI: 10.1016/j.cstp.2026.101707
Sharon Shoshany-Tavory, Hillel Bar-Gera
The growing popularity of shared e-scooters promises to enhance the mobility of urban dwellers in an environmentally friendly manner. On the other hand, e-scooters may potentially pose a risk to other road users, particularly pedestrians, and improperly parked vehicles may hinder accessibility. Therefore, to advance the goals of sustainability and mobility, cities should consider how street space should be managed for all travelers. One policy for shared e-scooter parking control is to limit parking to designated corrals. Corral-based parking policies have been adopted by many municipalities, with limited reports on effectiveness. This study provides an in-depth exploration of such policy deployment, governing the highly utilized services offered in the city of Tel-Aviv. By using our suggested framework and big-data spatio-temporal analytics of e-scooters data, we outline success measures, common pitfalls, and demonstrate city-wide patterns and location-specific results. Our discussion offers policy improvement suggestions, addressing design and policies, including corral-centered monitoring, redistribution policy, resilience estimation, and better space utilization. These could benefit municipalities, operators, and monitoring tools suppliers.
{"title":"Pardon me but your e-scooter is in my space: Evaluating the effectiveness of e-scooters parking policies through big data analytics","authors":"Sharon Shoshany-Tavory, Hillel Bar-Gera","doi":"10.1016/j.cstp.2026.101707","DOIUrl":"10.1016/j.cstp.2026.101707","url":null,"abstract":"<div><div>The growing popularity of shared e-scooters promises to enhance the mobility of urban dwellers in an environmentally friendly manner. On the other hand, e-scooters may potentially pose a risk to other road users, particularly pedestrians, and improperly parked vehicles may hinder accessibility. Therefore, to advance the goals of sustainability and mobility, cities should consider how street space should be managed for all travelers. One policy for shared e-scooter parking control is to limit parking to designated corrals. Corral-based parking policies have been adopted by many municipalities, with limited reports on effectiveness. This study provides an in-depth exploration of such policy deployment, governing the highly utilized services offered in the city of Tel-Aviv. By using our suggested framework and big-data spatio-temporal analytics of e-scooters data, we outline success measures, common pitfalls, and demonstrate city-wide patterns and location-specific results. Our discussion offers policy improvement suggestions, addressing design and policies, including corral-centered monitoring, redistribution policy, resilience estimation, and better space utilization. These could benefit municipalities, operators, and monitoring tools suppliers.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"23 ","pages":"Article 101707"},"PeriodicalIF":3.3,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146037380","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}
Recent discussions on transportation project evaluation have increasingly emphasized the importance of incorporating equity considerations. This study developed a travel behavior model that incorporates individual attributes and empirically assessed the distributional impacts of urban rail improvement projects in the Tokyo metropolitan area. Travelers were classified in this area into 24 attributes based on four income classes and six household types, and we estimated mode choice models for home-to-work and home-to-private trips. These models were then used to calculate the logsum accessibility measures, to predict user benefits from urban rail projects completed in 2019 and 2023. Distributional analyses revealed that for home-to-work trips, the median user benefit increased with income, but the interquartile ranges remained similar across most income groups above two million JPY/year. For home-to-private trips, benefits are higher for households with only one or two workers or for higher-income groups, reflecting greater variation in travel behavior and the value of travel time.
{"title":"Evaluating the distributional impact of urban rail improvements: Logsum accessibility measures incorporating income class and household type","authors":"Yohei Naga , Ryosuke Abe , Hajriyanti Yatmar , Ryoma Gouto","doi":"10.1016/j.cstp.2026.101708","DOIUrl":"10.1016/j.cstp.2026.101708","url":null,"abstract":"<div><div>Recent discussions on transportation project evaluation have increasingly emphasized the importance of incorporating equity considerations. This study developed a travel behavior model that incorporates individual attributes and empirically assessed the distributional impacts of urban rail improvement projects in the Tokyo metropolitan area. Travelers were classified in this area into 24 attributes based on four income classes and six household types, and we estimated mode choice models for home-to-work and home-to-private trips. These models were then used to calculate the logsum accessibility measures, to predict user benefits from urban rail projects completed in 2019 and 2023. Distributional analyses revealed that for home-to-work trips, the median user benefit increased with income, but the interquartile ranges remained similar across most income groups above two million JPY/year. For home-to-private trips, benefits are higher for households with only one or two workers or for higher-income groups, reflecting greater variation in travel behavior and the value of travel time.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"23 ","pages":"Article 101708"},"PeriodicalIF":3.3,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145976474","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 : 2026-01-06DOI: 10.1016/j.cstp.2026.101706
Hagui Abdelhamid
{"title":"Coexisting on the move: Mobility conflicts and urban injustice in the peripheries of Greater Tunis","authors":"Hagui Abdelhamid","doi":"10.1016/j.cstp.2026.101706","DOIUrl":"10.1016/j.cstp.2026.101706","url":null,"abstract":"","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"23 ","pages":"Article 101706"},"PeriodicalIF":3.3,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146187388","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 : 2026-01-03DOI: 10.1016/j.cstp.2026.101705
Luís Rosa, Francisco Borges, Crismeire Isbaex, Carmen Luisa Vásquez, Teresa Batista
Accurate vessel arrival predictions are fundamental to efficient port operations, yet their reliability remains poorly understood. This study examines 15 years of arrival data from the Port of Sines (2009–2023) to assess the accuracy of Estimated Time of Arrival (ETA) predictions and their operational implications. The analysis of vessel movements reveals that precise on-time arrivals occurred in only 1.77 % of cases. While 56.93 % of vessels arrived ahead of schedule, delayed arrivals were disproportionately severe, averaging 6 h and 52 min late. The data shows 1,623 instances of extreme delays exceeding 24 h, highlighting significant forecasting challenges. Terminal specific analysis demonstrates marked variation in performance: The Container Terminal recorded the highest average delay (+10:26 h) and was the only facility where late arrivals outnumbered early ones. It was found that vessels with frequent port calls exhibited substantially better punctuality, indicating that operational knowledge improves scheduling accuracy. These timing discrepancies translate directly into extended anchorage periods, generating measurable economic costs and environmental impacts through increased fuel consumption and emissions. Better forecasting accuracy could significantly reduce the operational inefficiencies that currently outbreak container shipping operations.
{"title":"Ship arrival patterns at the port of Sines: A comparative analysis of ETA and ATA","authors":"Luís Rosa, Francisco Borges, Crismeire Isbaex, Carmen Luisa Vásquez, Teresa Batista","doi":"10.1016/j.cstp.2026.101705","DOIUrl":"10.1016/j.cstp.2026.101705","url":null,"abstract":"<div><div>Accurate vessel arrival predictions are fundamental to efficient port operations, yet their reliability remains poorly understood. This study examines 15 years of arrival data from the Port of Sines (2009–2023) to assess the accuracy of Estimated Time of Arrival (ETA) predictions and their operational implications. The analysis of vessel movements reveals that precise on-time arrivals occurred in only 1.77 % of cases. While 56.93 % of vessels arrived ahead of schedule, delayed arrivals were disproportionately severe, averaging 6 h and 52 min late. The data shows 1,623 instances of extreme delays exceeding 24 h, highlighting significant forecasting challenges. Terminal specific analysis demonstrates marked variation in performance: The Container Terminal recorded the highest average delay (+10:26 h) and was the only facility where late arrivals outnumbered early ones. It was found that vessels with frequent port calls exhibited substantially better punctuality, indicating that operational knowledge improves scheduling accuracy. These timing discrepancies translate directly into extended anchorage periods, generating measurable economic costs and environmental impacts through increased fuel consumption and emissions. Better forecasting accuracy could significantly reduce the operational inefficiencies that currently outbreak container shipping operations.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"23 ","pages":"Article 101705"},"PeriodicalIF":3.3,"publicationDate":"2026-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145924541","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 : 2026-01-01DOI: 10.1016/j.cstp.2025.101704
Mao Changjiang, Luo Jian, Jiang xue, Jiao Shengyang
While numerous studies have investigated the regional economic impacts of high-speed rail (HSR), its role within “twin-core” urban agglomerations in topographically complex regions remains inadequately explored. This study addresses this gap by examining the Chengdu-Chongqing Economic Circle, a representative region characterized by complex mountainous terrain. Utilizing panel data from 2000 to 2020, apply both a multiperiod difference-in-differences (DID) approach and a Geographically and Temporally Weighted Regression (GTWR) model. This methodology elucidates the causal mechanisms and spatiotemporal heterogeneity of HSR’s differential economic effects on core versus peripheral cities.Our findings reveal three key results: (1) Although HSR significantly fosters aggregate regional economic growth, its benefits are distributed highly unevenly, exhibiting a pattern of uneven spatial diffusion. While core cities capture larger direct gains, significant positive spillovers to peripheral cities are identified. This diffusion effect, however, is strongly moderated by rugged terrain, which attenuates spillovers and perpetuates core-periphery disparities. (2) The GTWR model further delineates the underlying causes of this spatial heterogeneity. The complex, rugged topography significantly escalates HSR construction and operational costs, thereby attenuating its positive economic spillovers. Topography thus emerges as a critical moderating variable, accounting for the stark disparity in HSR derived economic benefits between flat and mountainous areas. (3) Mechanism analysis indicates that HSR primarily stimulates economic growth by boosting tertiary sector employment.This study provides causal and spatial empirical evidence for the applicability of the “core-periphery” theory in settings with complex topography. Our conclusions underscore the imperative of incorporating geographical constraints into transportation infrastructure planning. Accordingly, we propose targeted policy recommendations to foster regional coordination, mitigate topographical disadvantages, and advance the superior, integrated development of the Chengdu-Chongqing Economic Circle.
{"title":"From ‘tale of two cities’ to ‘economic circle’: an assessment of the differential effects of high-speed railway on the economic growth of Chengdu-Chongqing twin-city economic circle","authors":"Mao Changjiang, Luo Jian, Jiang xue, Jiao Shengyang","doi":"10.1016/j.cstp.2025.101704","DOIUrl":"10.1016/j.cstp.2025.101704","url":null,"abstract":"<div><div>While numerous studies have investigated the regional economic impacts of high-speed rail (HSR), its role within “twin-core” urban agglomerations in topographically complex regions remains inadequately explored. This study addresses this gap by examining the Chengdu-Chongqing Economic Circle, a representative region characterized by complex mountainous terrain. Utilizing panel data from 2000 to 2020, apply both a multiperiod difference-in-differences (DID) approach and a Geographically and Temporally Weighted Regression (GTWR) model. This methodology elucidates the causal mechanisms and spatiotemporal heterogeneity of HSR’s differential economic effects on core versus peripheral cities.Our findings reveal three key results: (1) Although HSR significantly fosters aggregate regional economic growth, its benefits are distributed highly unevenly, exhibiting a pattern of uneven spatial diffusion. While core cities capture larger direct gains, significant positive spillovers to peripheral cities are identified. This diffusion effect, however, is strongly moderated by rugged terrain, which attenuates spillovers and perpetuates core-periphery disparities. (2) The GTWR model further delineates the underlying causes of this spatial heterogeneity. The complex, rugged topography significantly escalates HSR construction and operational costs, thereby attenuating its positive economic spillovers. Topography thus emerges as a critical moderating variable, accounting for the stark disparity in HSR derived economic benefits between flat and mountainous areas. (3) Mechanism analysis indicates that HSR primarily stimulates economic growth by boosting tertiary sector employment.This study provides causal and spatial empirical evidence for the applicability of the “core-periphery” theory in settings with complex topography. Our conclusions underscore the imperative of incorporating geographical constraints into transportation infrastructure planning. Accordingly, we propose targeted policy recommendations to foster regional coordination, mitigate topographical disadvantages, and advance the<!--> <!-->superior, integrated development of the Chengdu-Chongqing Economic Circle.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"23 ","pages":"Article 101704"},"PeriodicalIF":3.3,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145883559","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 : 2025-12-31DOI: 10.1016/j.cstp.2025.101703
Caterina Caramuta, Alessia Grosso, Giovanni Longo
The severe repercussions of the Red Sea crisis on supply chains, as well as the disruptions caused by the Covid-19 pandemic and the Russia-Ukraine conflict, have highlighted once again their great vulnerability, especially in the face of major and unpredictable shocks. The impacts of these latter have therefore urged decision makers to define resiliency strategies to cope with the uncertainty characterizing the operating environment. With reference to a transport node, in this paper the scenario development approach has been adopted to formally investigate possible futures for the Port of Trieste, Italy, which was affected by the consequences of the recent geopolitical disruptions in the Middle East, at the Bab Al-Mandab Strait. Notably, the 2 × 2 matrix technique was used to envision potential scenarios after identifying two critical uncertainties, which represent the most impacting and yet uncertain driving forces of the problem at hand. In this way, based on the level of the traffic flow stability and of the adequacy of port transport infrastructures, four different scenarios have been depicted in qualitative terms and then, their implications have been discussed to propose the Port Authority some recommendations on possible counteractions. The results of the study suggest that valuable initiatives should consider risk sharing through public–private partnerships, the diversification of port services and the rapid implementation of technological advancements.
{"title":"Mitigating uncertainty due to the Red Sea Crisis: A scenario development application to the Port of Trieste, Italy","authors":"Caterina Caramuta, Alessia Grosso, Giovanni Longo","doi":"10.1016/j.cstp.2025.101703","DOIUrl":"10.1016/j.cstp.2025.101703","url":null,"abstract":"<div><div>The severe repercussions of the Red Sea crisis on supply chains, as well as the disruptions caused by the Covid-19 pandemic and the Russia-Ukraine conflict, have highlighted once again their great vulnerability, especially in the face of major and unpredictable shocks. The impacts of these latter have therefore urged decision makers to define resiliency strategies to cope with the uncertainty characterizing the operating environment. With reference to a transport node, in this paper the scenario development approach has been adopted to formally investigate possible futures for the Port of Trieste, Italy, which was affected by the consequences of the recent geopolitical disruptions in the Middle East, at the Bab Al-Mandab Strait. Notably, the 2 × 2 matrix technique was used to envision potential scenarios after identifying two critical uncertainties, which represent the most impacting and yet uncertain driving forces of the problem at hand. In this way, based on the level of the traffic flow stability and of the adequacy of port transport infrastructures, four different scenarios have been depicted in qualitative terms and then, their implications have been discussed to propose the Port Authority some recommendations on possible counteractions. The results of the study suggest that valuable initiatives should consider risk sharing through public–private partnerships, the diversification of port services and the rapid implementation of technological advancements.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"23 ","pages":"Article 101703"},"PeriodicalIF":3.3,"publicationDate":"2025-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145883558","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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