Pub Date : 2025-03-16DOI: 10.1016/j.cstp.2025.101429
Lam Canh Nguyen , Minh Binh Chu , Huy Quang Truong , Huy Gia Dinh , An Thi Binh Duong
This paper explores how Entrepreneurial Action Theory (EAT) enhances our understanding of action development in logistics firms and enriches the knowledge of Critical Success Factors (CSFs) in the logistics sector. Adopting a qualitative approach, the study conducts in-depth interviews with 21 senior employees and managers from logistics firms in Vietnam. This study identifies five dimensions of CSFs and highlights the importance of knowledge in four key areas. Additionally, it identifies four key environmental changes that impact the success of logistics firms. The integration of these findings with EAT leads to a proposed theoretical framework explaining the entrepreneurial actions of logistics firms in their pursuit of success. The paper provides valuable insights into achieving success in the contemporary era and outlines appropriate actions for logistics firms.
{"title":"Exploring entrepreneurial actions of logistics firms for achieving success: An application of entrepreneurial action theory","authors":"Lam Canh Nguyen , Minh Binh Chu , Huy Quang Truong , Huy Gia Dinh , An Thi Binh Duong","doi":"10.1016/j.cstp.2025.101429","DOIUrl":"10.1016/j.cstp.2025.101429","url":null,"abstract":"<div><div>This paper explores how Entrepreneurial Action Theory (EAT) enhances our understanding of action development in logistics firms and enriches the knowledge of Critical Success Factors (CSFs) in the logistics sector. Adopting a qualitative approach, the study conducts in-depth interviews with 21 senior employees and managers from logistics firms in Vietnam. This study identifies five dimensions of CSFs and highlights the importance of knowledge in four key areas. Additionally, it identifies four key environmental changes that impact the success of logistics firms. The integration of these findings with EAT leads to a proposed theoretical framework explaining the entrepreneurial actions of logistics firms in their pursuit of success. The paper provides valuable insights into achieving success in the contemporary era and outlines appropriate actions for logistics firms.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"20 ","pages":"Article 101429"},"PeriodicalIF":2.4,"publicationDate":"2025-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143644581","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 : 2025-03-14DOI: 10.1016/j.cstp.2025.101426
Manuel A. Zambrano-Monserrate , Naila Erum
While many studies have examined the variables driving electric vehicle (EV) adoption, little attention has been paid to the factors influencing daily decisions of EV users. This paper investigates the factors affecting canceled trips and modified routes among EV drivers in Ecuador, offering insights from a developing country context. Key variables, including range anxiety, perception of charging infrastructure, vehicle range, usage frequency, and sociodemographic characteristics, are analyzed. Using a negative binomial model on a sample of 1,249 EV users, the findings reveal that range anxiety and perception of charging infrastructure significantly influence both canceled trips and modified routes. Additionally, greater vehicle range and higher usage frequency reduce the likelihood of modifying routes or canceling trips. Gender also plays a role: men are less likely to cancel trips as vehicle range increases. These findings provide valuable policy insights.
{"title":"Canceled trips and modified routes: Electric vehicle user behavior in Ecuador","authors":"Manuel A. Zambrano-Monserrate , Naila Erum","doi":"10.1016/j.cstp.2025.101426","DOIUrl":"10.1016/j.cstp.2025.101426","url":null,"abstract":"<div><div>While many studies have examined the variables driving electric vehicle (EV) adoption, little attention has been paid to the factors influencing daily decisions of EV users. This paper investigates the factors affecting canceled trips and modified routes among EV drivers in Ecuador, offering insights from a developing country context. Key variables, including range anxiety, perception of charging infrastructure, vehicle range, usage frequency, and sociodemographic characteristics, are analyzed. Using a negative binomial model on a sample of 1,249 EV users, the findings reveal that range anxiety and perception of charging infrastructure significantly influence both canceled trips and modified routes. Additionally, greater vehicle range and higher usage frequency reduce the likelihood of modifying routes or canceling trips. Gender also plays a role: men are less likely to cancel trips as vehicle range increases. These findings provide valuable policy insights.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"20 ","pages":"Article 101426"},"PeriodicalIF":2.4,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143629284","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 : 2025-03-13DOI: 10.1016/j.cstp.2025.101414
Rafael Mariano dos Santos, Mayara Condé Rocha Murça
Demand–capacity imbalances are a major cause of inefficiencies in the air transportation system, accounting for a significant part of flight delays and disruptions. Efficiently addressing these imbalances through air traffic flow management is key for improving system performance. If taken at the strategic level, flow management decisions have the potential to increase operational predictability and reduce costs for airspace users by transferring expected delays to the ground before departure, where it is safer and cheaper to absorb them. However, strategic flow management planning is a challenge for traffic managers due to the stochastic and dynamic nature of airport and airspace capacity. This paper leverages machine learning and optimization methods to develop a decision support framework for strategic air traffic flow management at Sao Paulo/Guarulhos International Airport (GRU) in Brazil. First, an airport capacity prediction model is learned from historical meteorological and throughput data. Random Forests is used in a regression setting for the supervised learning problem, being able to provide not only a point prediction of arrival capacity but also an empirical predictive distribution based on the Quantile Regression Forests approach. An analysis of feature importance reveals that ceiling and convective weather are the most important factors affecting arrival capacity at GRU. A stochastic optimization model for capacity allocation is then used to prescribe the optimal airport acceptance rates for Ground Delay Program planning based on the capacity forecasts and their estimated uncertainty. When applied to an actual test case of demand–capacity imbalance at GRU, the solution provided by the framework is found to generate a reduction in total delay costs of up to 10%, revealing an improvement over the current practice solely based on tactical airborne delays.
{"title":"Airport capacity prediction and optimal allocation for strategic air traffic flow management at Sao Paulo/Guarulhos International Airport","authors":"Rafael Mariano dos Santos, Mayara Condé Rocha Murça","doi":"10.1016/j.cstp.2025.101414","DOIUrl":"10.1016/j.cstp.2025.101414","url":null,"abstract":"<div><div>Demand–capacity imbalances are a major cause of inefficiencies in the air transportation system, accounting for a significant part of flight delays and disruptions. Efficiently addressing these imbalances through air traffic flow management is key for improving system performance. If taken at the strategic level, flow management decisions have the potential to increase operational predictability and reduce costs for airspace users by transferring expected delays to the ground before departure, where it is safer and cheaper to absorb them. However, strategic flow management planning is a challenge for traffic managers due to the stochastic and dynamic nature of airport and airspace capacity. This paper leverages machine learning and optimization methods to develop a decision support framework for strategic air traffic flow management at Sao Paulo/Guarulhos International Airport (GRU) in Brazil. First, an airport capacity prediction model is learned from historical meteorological and throughput data. Random Forests is used in a regression setting for the supervised learning problem, being able to provide not only a point prediction of arrival capacity but also an empirical predictive distribution based on the Quantile Regression Forests approach. An analysis of feature importance reveals that ceiling and convective weather are the most important factors affecting arrival capacity at GRU. A stochastic optimization model for capacity allocation is then used to prescribe the optimal airport acceptance rates for Ground Delay Program planning based on the capacity forecasts and their estimated uncertainty. When applied to an actual test case of demand–capacity imbalance at GRU, the solution provided by the framework is found to generate a reduction in total delay costs of up to 10%, revealing an improvement over the current practice solely based on tactical airborne delays.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"20 ","pages":"Article 101414"},"PeriodicalIF":2.4,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143629283","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 : 2025-03-13DOI: 10.1016/j.cstp.2025.101423
Marcelo Seido Nagano , Thiago Dias de Jesus , Fernando Luis Rossi
The strategic planning of airline networks is critical for maximizing profitability and operational efficiency. Among the key challenges faced by airlines is the Route Selection Problem (RSP)—determining which routes to operate based on demand, economic conditions, and infrastructure—and the Fleet Assignment Problem (FAP)—optimally assigning aircraft to routes to minimize costs. While these problems are typically addressed separately, their integration can yield more robust and profitable solutions. This study presents a novel mathematical model that integrates RSP and FAP using Mixed Integer Linear Programming (MILP) to optimize network profitability and fleet utilization. The model was validated through a case study of a fictional regional airline in Southeast Brazil, analyzing 41 potential locations. The results identified 28 profitable routes, including 11 destinations currently without regular flights and one without an airport. By optimizing fleet allocation and route selection, the model provides a data-driven framework for airlines, policymakers, and investors to enhance network efficiency and identify underserved markets. This study demonstrates that an integrated approach to route selection and fleet assignment can significantly improve decision-making in the airline industry, offering a scalable methodology for network expansion and strategic investment.
{"title":"Identifying potential routes and airports in Brazil: An integration of the route selection and fleet assignment problems","authors":"Marcelo Seido Nagano , Thiago Dias de Jesus , Fernando Luis Rossi","doi":"10.1016/j.cstp.2025.101423","DOIUrl":"10.1016/j.cstp.2025.101423","url":null,"abstract":"<div><div>The strategic planning of airline networks is critical for maximizing profitability and operational efficiency. Among the key challenges faced by airlines is the Route Selection Problem (RSP)—determining which routes to operate based on demand, economic conditions, and infrastructure—and the Fleet Assignment Problem (FAP)—optimally assigning aircraft to routes to minimize costs. While these problems are typically addressed separately, their integration can yield more robust and profitable solutions. This study presents a novel mathematical model that integrates RSP and FAP using Mixed Integer Linear Programming (MILP) to optimize network profitability and fleet utilization. The model was validated through a case study of a fictional regional airline in Southeast Brazil, analyzing 41 potential locations. The results identified 28 profitable routes, including 11 destinations currently without regular flights and one without an airport. By optimizing fleet allocation and route selection, the model provides a data-driven framework for airlines, policymakers, and investors to enhance network efficiency and identify underserved markets. This study demonstrates that an integrated approach to route selection and fleet assignment can significantly improve decision-making in the airline industry, offering a scalable methodology for network expansion and strategic investment.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"20 ","pages":"Article 101423"},"PeriodicalIF":2.4,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143642213","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 : 2025-03-13DOI: 10.1016/j.cstp.2025.101425
Notan Haldar, Tapas Mistri
Mode choice refers to the way individuals make decisions regarding transportation options, which is essential for urban planning, managing traffic and promoting public welfare. This study investigates the influence of socio-economic factors such as gender, age, family size, education, occupation, income, vehicle ownership and a trip-specific factor as travel distance on transport mode choices in Burdwan, a medium-sized city in India. Using a survey of 250 respondents from five municipal wards, the study categorizes transport modes into non-motorized, public transport, para-transit and private motorized vehicles. Multinomial Logistic Regression analysis highlights that gender, family size, education, income, vehicle ownership and travel distance significantly influence transport preferences. The findings reveal that higher-income and educated individuals favor private vehicles, while lower-income groups rely on non-motorized and para-transit modes. Women demonstrate a preference for e-rickshaws, while men predominantly use private vehicles. The study emphasizes the underutilization of public transport due to inefficiencies and also proposes policy recommendations for enhancing public transport, promoting non-motorized transport infrastructure and integrating diverse transport modes. These recommendations aim to achieve sustainable, inclusive and accessible urban mobility for medium-sized Indian cities.
{"title":"Exploring the socio-economic determinants of transport mode choice: A case study of Burdwan city, India","authors":"Notan Haldar, Tapas Mistri","doi":"10.1016/j.cstp.2025.101425","DOIUrl":"10.1016/j.cstp.2025.101425","url":null,"abstract":"<div><div>Mode choice refers to the way individuals make decisions regarding transportation options, which is essential for urban planning, managing traffic and promoting public welfare. This study investigates the influence of socio-economic factors such as gender, age, family size, education, occupation, income, vehicle ownership and a trip-specific factor as travel distance on transport mode choices in Burdwan, a medium-sized city in India. Using a survey of 250 respondents from five municipal wards, the study categorizes transport modes into non-motorized, public transport, <em>para</em>-transit and private motorized vehicles. Multinomial Logistic Regression analysis highlights that gender, family size, education, income, vehicle ownership and travel distance significantly influence transport preferences. The findings reveal that higher-income and educated individuals favor private vehicles, while lower-income groups rely on non-motorized and <em>para</em>-transit modes. Women demonstrate a preference for e-rickshaws, while men predominantly use private vehicles. The study emphasizes the underutilization of public transport due to inefficiencies and also proposes policy recommendations for enhancing public transport, promoting non-motorized transport infrastructure and integrating diverse transport modes. These recommendations aim to achieve sustainable, inclusive and accessible urban mobility for medium-sized Indian cities.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"20 ","pages":"Article 101425"},"PeriodicalIF":2.4,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143644582","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 : 2025-03-10DOI: 10.1016/j.cstp.2025.101424
Marta Borowska-Stefańska , Vasile Grama , Edyta Masierek , Cezar Morar , Szymon Wiśniewski
Emergency shelters in urban areas play an important role in providing temporary refuge to the population in military conflicts. The aim of this article is to examine the spatial alignment of shelters to the population distribution in the event of a war in Galaţi (Romania). The capacity of the emergency shelters, the possible number of evacuees and the transport behaviour of the inhabitants are the three main factors considered in these studies. The survey was conducted using the CATI technique with a sample of 405 residents (from 1 March to 12 April 2023). The results indicate that only a relatively small percentage of residents are willing to self-evacuate. Despite this, the situation can still be considered favourable as self-evacuation may cause a number of problems if many people who have no knowledge about wartime evacuation procedures use their own cars to self-evacuate. The analysis of the distribution of emergency services (fire brigades and the police force) in the city reveals that it is adequate relative to the population distribution. However, these forces are limited in number and can quickly become overwhelmed without proper management. Furthermore, the capacity of the existing emergency shelters in the studied city is insufficient, both for self-evacuation on foot or by car. Thus, new locations for emergency shelters have been recommended to be located in existing facilities in order to accommodate the largest possible number of people in the shortest possible time. The approach taken in this study can also be adopted to serve in other urban areas facing similar risks, emphasising the need for a tailored crisis management strategy that takes into account specific regional and population dynamics.
{"title":"Evacuation planning in urban areas: A case study in Galați under military conflict conditions","authors":"Marta Borowska-Stefańska , Vasile Grama , Edyta Masierek , Cezar Morar , Szymon Wiśniewski","doi":"10.1016/j.cstp.2025.101424","DOIUrl":"10.1016/j.cstp.2025.101424","url":null,"abstract":"<div><div>Emergency shelters in urban areas play an important role in providing temporary refuge to the population in military conflicts. The aim of this article is to examine the spatial alignment of shelters to the population distribution in the event of a war in Galaţi (Romania). The capacity of the emergency shelters, the possible number of evacuees and the transport behaviour of the inhabitants are the three main factors considered in these studies. The survey was conducted using the CATI technique with a sample of 405 residents (from 1 March to 12 April 2023). The results indicate that only a relatively small percentage of residents are willing to self-evacuate. Despite this, the situation can still be considered favourable as self-evacuation may cause a number of problems if many people who have no knowledge about wartime evacuation procedures use their own cars to self-evacuate. The analysis of the distribution of emergency services (fire brigades and the police force) in the city reveals that it is adequate relative to the population distribution. However, these forces are limited in number and can quickly become overwhelmed without proper management. Furthermore, the capacity of the existing emergency shelters in the studied city is insufficient, both for self-evacuation on foot or by car. Thus, new locations for emergency shelters have been recommended to be located in existing facilities in order to accommodate the largest possible number of people in the shortest possible time. The approach taken in this study can also be adopted to serve in other urban areas facing similar risks, emphasising the need for a tailored crisis management strategy that takes into account specific regional and population dynamics.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"20 ","pages":"Article 101424"},"PeriodicalIF":2.4,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143594177","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 : 2025-03-10DOI: 10.1016/j.cstp.2025.101401
Qiling Zou , Sean Qian , Duane Detwiler , Rajeev Chhajer
The rise in penetration of electric vehicles (EV) presents new challenges for infrastructure management due to the intertwining of the transportation system with the electric power system through charging infrastructure. The integration of EVs into the transportation network requires a dynamic transportation network modeling approach that considers the impacts of EV charging. Existing studies often suffer from drawbacks such as static traffic models, limited network size, and unrealistic assumptions about traffic demand and EV behavior. The study proposes a holistic framework that incorporates essential components related to EVs such as charging stations, EV charging routing, charging behavior, and energy consumption, into a dynamic traffic model for large-scale networks. The framework is applied to a large-scale transportation network in the Central Ohio region. The high granularity dynamic traffic model is calibrated with real-world traffic data and vehicle registration data, resulting in more accurate estimations of traffic flow and energy consumption. Based on the calibrated model, different scenarios are analyzed and the results reveal spatiotemporal variations in the utilization of the charging station and the patterns of neighborhood electricity consumption. Furthermore, the study analyzes the impacts of the EV penetration ratio, the roadside charging ratio, the coverage ratio of the fast charging station on the energy consumption across the network, the emission of greenhouse gases, and the waiting times at the charging stations. The proposed flexible framework provides a foundation for future studies to refine submodels and explore the interdependency between traffic and electric power systems more comprehensively.
{"title":"Impacts of vehicle electrification on large-scale transportation and charging infrastructure: A dynamic network modeling approach","authors":"Qiling Zou , Sean Qian , Duane Detwiler , Rajeev Chhajer","doi":"10.1016/j.cstp.2025.101401","DOIUrl":"10.1016/j.cstp.2025.101401","url":null,"abstract":"<div><div>The rise in penetration of electric vehicles (EV) presents new challenges for infrastructure management due to the intertwining of the transportation system with the electric power system through charging infrastructure. The integration of EVs into the transportation network requires a dynamic transportation network modeling approach that considers the impacts of EV charging. Existing studies often suffer from drawbacks such as static traffic models, limited network size, and unrealistic assumptions about traffic demand and EV behavior. The study proposes a holistic framework that incorporates essential components related to EVs such as charging stations, EV charging routing, charging behavior, and energy consumption, into a dynamic traffic model for large-scale networks. The framework is applied to a large-scale transportation network in the Central Ohio region. The high granularity dynamic traffic model is calibrated with real-world traffic data and vehicle registration data, resulting in more accurate estimations of traffic flow and energy consumption. Based on the calibrated model, different scenarios are analyzed and the results reveal spatiotemporal variations in the utilization of the charging station and the patterns of neighborhood electricity consumption. Furthermore, the study analyzes the impacts of the EV penetration ratio, the roadside charging ratio, the coverage ratio of the fast charging station on the energy consumption across the network, the emission of greenhouse gases, and the waiting times at the charging stations. The proposed flexible framework provides a foundation for future studies to refine submodels and explore the interdependency between traffic and electric power systems more comprehensively.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"20 ","pages":"Article 101401"},"PeriodicalIF":2.4,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143636294","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 : 2025-03-05DOI: 10.1016/j.cstp.2025.101421
Chetna Rathee , Shubhajit Sadhukhan
The construction of highway infrastructure is essential for fostering economic growth, promoting connectivity, and influencing regional planning. This study assesses the consequences of roads (highways) in Haryana State, India, concentrating on highway lengths, highway density, modal distribution, economic performance, road safety, and environmental impacts. The research adheres to the Cross-Industry Standard Process for Data Mining (CRISP-DM) framework to ensure a methodical approach for the analysis. A quantitative analysis utilising correlation analysis and k-means clustering was performed to evaluate the relationship between highway growth and identified parameters. The research employs district-level data from 2003 to 2023, obtained from MoRTH (2023), the Statistical Abstract of Haryana (2024), and the National Crime Records Bureau (2024). The findings demonstrate a significant association between highway length and GDP, highlighting the importance of highways in economic advancement. The k-means clustering method categorised districts into five unique clusters, revealing regional inequalities in infrastructure development, economic progress, and accident frequencies. The study highlights an increase in road accidents in high-traffic districts and a rise in PM2.5 and CO2 emissions, emphasizing sustainability challenges. The study offers a framework for assessing highway impacts and suggests policy solutions with immediate, short-term, and long-term applications to tackle regional inequities, road safety issues, and environmental sustainability. The investigation formulates a framework for the examination of highway impacts and suggests policy interventions to policymakers, urban planners, transport authorities, and regional development agencies that can be implemented in the short, medium, and long term to mitigate regional disparities, environmental sustainability, and road safety concerns.
{"title":"Regional impact assessment of highways and policy Interventions: Lessons from Haryana, India","authors":"Chetna Rathee , Shubhajit Sadhukhan","doi":"10.1016/j.cstp.2025.101421","DOIUrl":"10.1016/j.cstp.2025.101421","url":null,"abstract":"<div><div>The construction of highway infrastructure is essential for fostering economic growth, promoting connectivity, and influencing regional planning. This study assesses the consequences of roads (highways)<!--> <!-->in Haryana State, India, concentrating on highway lengths,<!--> <!-->highway density, modal distribution, economic performance, road safety, and environmental impacts. The research adheres to the Cross-Industry Standard Process for Data Mining (CRISP-DM) framework to ensure<!--> <!-->a methodical approach for the analysis. A quantitative analysis utilising correlation analysis and k-means clustering was performed to evaluate the relationship between highway growth and identified parameters. The research employs district-level data from 2003 to 2023, obtained from MoRTH (2023), the Statistical Abstract of Haryana (2024), and the National Crime Records Bureau (2024). The findings demonstrate a significant association between highway length and GDP, highlighting the importance of highways in economic advancement. The k-means clustering method categorised districts into five unique clusters, revealing regional inequalities in infrastructure development, economic progress, and accident frequencies. The study highlights an increase in road accidents in high-traffic districts and a rise in PM2.5 and CO<sub>2</sub> emissions, emphasizing sustainability challenges. The study offers a framework for assessing highway impacts and suggests policy solutions with immediate, short-term, and long-term applications to tackle regional inequities, road safety issues, and environmental sustainability. The investigation formulates a framework for the examination of highway impacts and suggests policy interventions to policymakers, urban planners, transport authorities, and regional development agencies that can be implemented in the short, medium, and long term to mitigate regional disparities, environmental sustainability, and road safety concerns.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"20 ","pages":"Article 101421"},"PeriodicalIF":2.4,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143594201","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}
Thailand’s rapid expansion of its national transportation network has fueled significant growth in the truck freight business, which now accounts for 70% of the country’s freight. However, this growth has also intensified the overloaded truck problem, as businesses seek to reduce costs and gain competitive advantages by exceeding legal weight limits. This study investigates the root causes of truck overloading, focusing on enforcement gaps and policy shortcomings. By analyzing actual truck weight data collected during 2019–2023 through Bridge Weigh-in-Motion (BWIM) technology, which operates covertly beneath bridges, significant discrepancies were found between state weigh station reports and real-world data. These discrepancies are primarily due to weigh station avoidance, often facilitated by bribery. The study highlights how these enforcement gaps weaken law enforcement and hinder effective policy implementation. To address these challenges, the study recommends adopting automated weighing systems, such as BWIM, and introducing an overweight fee permit system. These measures aim to enhance the effectiveness of law enforcement, reduce the potential for corruption, and support sustainable and balanced transport management. The findings provide actionable insights for policymakers and state agencies to develop robust and cost-effective solutions to the overloaded truck problem in Thailand.
{"title":"Overloaded truck problem in Thailand: Investigating Root Causes, Enforcement Gaps, and Policy Solutions","authors":"Angkanawadee Pinkaew , Punnathorn Siriwatwechakul , Tospol Pinkaew","doi":"10.1016/j.cstp.2025.101402","DOIUrl":"10.1016/j.cstp.2025.101402","url":null,"abstract":"<div><div>Thailand’s rapid expansion of its national transportation network has fueled significant growth in the truck freight business, which now accounts for 70% of the country’s freight. However, this growth has also intensified the overloaded truck problem, as businesses seek to reduce costs and gain competitive advantages by exceeding legal weight limits. This study investigates the root causes of truck overloading, focusing on enforcement gaps and policy shortcomings. By analyzing actual truck weight data collected during 2019–2023 through Bridge Weigh-in-Motion (BWIM) technology, which operates covertly beneath bridges, significant discrepancies were found between state weigh station reports and real-world data. These discrepancies are primarily due to weigh station avoidance, often facilitated by bribery. The study highlights how these enforcement gaps weaken law enforcement and hinder effective policy implementation. To address these challenges, the study recommends adopting automated weighing systems, such as BWIM, and introducing an overweight fee permit system. These measures aim to enhance the effectiveness of law enforcement, reduce the potential for corruption, and support sustainable and balanced transport management. The findings provide actionable insights for policymakers and state agencies to develop robust and cost-effective solutions to the overloaded truck problem in Thailand.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"20 ","pages":"Article 101402"},"PeriodicalIF":2.4,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143594200","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 : 2025-03-05DOI: 10.1016/j.cstp.2025.101422
Yeni Noviyanti Sagala, Samantha Jamson, Ruth Madigan
Indonesia has high motorcycle dependence, especially among young riders who rely on them for access to education. The number of young riders aged 15–19 involved in crashes is higher than in any other age group. Despite this, there have been limited attempts to comprehensively understand the behaviour of these road users. This study is the first to use the Motorcycle Rider Behaviour Questionnaire (MRBQ) to determine which rider behaviours may predict crash risk in an Indonesian population. In addition, the impact of demographic variables such as age, gender, licensing status (licensed or unlicensed) and area of residence (urban or rural) on young Indonesian riders (N = 7,081) crash risk was also examined. Negative binomial regression analysis revealed that crash risk was positively associated with both intentional and unintentional unsafe behaviours, including “errors”, “speed”, and “unsociable riding”. Interestingly, a common theme in the “errors” identified involved the participant not paying attention to their surroundings. This suggests that even though these errors may be unintentional, there is a possibility to develop targeted safety interventions, such as combined rider awareness and riding skills training. Finally, the results revealed that many of those surveyed were riding on public roads before they reached the legal age for riding, and failed to obtain a license even when they could legally do so. Overall, this study provides valuable insights into the factors affecting the safety of young motorcyclists in Indonesia, taking into account the culture and environmental considerations unique to this country.
{"title":"Which unsafe riding behaviours are associated with traffic offences and crashes? A study of young Indonesian motorcyclists","authors":"Yeni Noviyanti Sagala, Samantha Jamson, Ruth Madigan","doi":"10.1016/j.cstp.2025.101422","DOIUrl":"10.1016/j.cstp.2025.101422","url":null,"abstract":"<div><div>Indonesia has high motorcycle dependence, especially among young riders who rely on them for access to education. The number of young riders aged 15–19 involved in crashes is higher than in any other age group. Despite this, there have been limited attempts to comprehensively understand the behaviour of these road users. This study is the first to use the Motorcycle Rider Behaviour Questionnaire (MRBQ) to determine which rider behaviours may predict crash risk in an Indonesian population. In addition, the impact of demographic variables such as age, gender, licensing status (licensed or unlicensed) and area of residence (urban or rural) on young Indonesian riders (N = 7,081) crash risk was also examined. Negative binomial regression analysis revealed that crash risk was positively associated with<!--> <!-->both<!--> <!-->intentional and unintentional unsafe behaviours, including “errors”, “speed”, and “unsociable riding”.<!--> <!-->Interestingly,<!--> <!-->a common theme in the “errors” identified involved the participant not paying attention to their surroundings. This suggests that even though these errors may be unintentional, there is a possibility to develop targeted safety interventions, such as combined rider awareness and riding skills training. Finally, the results revealed that many of those surveyed were riding on public roads before they reached the legal age for riding, and failed to obtain a license even when they could legally do so. Overall, this study provides valuable insights into the factors affecting the safety of young motorcyclists in Indonesia, taking into account the culture and environmental considerations unique to this country.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"20 ","pages":"Article 101422"},"PeriodicalIF":2.4,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143594199","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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