Pub Date : 2025-02-01DOI: 10.1016/j.jtrangeo.2024.104093
J. Wust , J. Bekker , M.J. Booysen
The predominant mode of public transport in South Africa originates from the informal sector, specifically “paratransit”. Vehicles carry up to 23 passengers and are still propelled by internal combustion engines. We investigate the feasibility of using electric vehicles without negating the loss of opportunities by drivers and owners. We propose that scheduling of the electric vehicles is one important cornerstone towards electrification. We developed a fast-executing heuristic scheduling algorithm that allows for multiple vehicle depots in the transport network; simultaneous electric and internal combustion engine vehicle deployment; determining the number of charging stations; partial charging; and scheduled charging with intermittent electricity supply. The scheduling algorithm achieves the minimum number of vehicles to execute the passenger demand in shorter total distances, outperforming current approaches. The algorithm demonstrated multi-objective optimisation by minimising the vehicles, the number of charging stations, and the average trip delays of a schedule.
{"title":"Investigating scheduling of minibus taxis in South Africa's eventual electric paratransit","authors":"J. Wust , J. Bekker , M.J. Booysen","doi":"10.1016/j.jtrangeo.2024.104093","DOIUrl":"10.1016/j.jtrangeo.2024.104093","url":null,"abstract":"<div><div>The predominant mode of public transport in South Africa originates from the informal sector, specifically “paratransit”. Vehicles carry up to 23 passengers and are still propelled by internal combustion engines. We investigate the feasibility of using electric vehicles without negating the loss of opportunities by drivers and owners. We propose that scheduling of the electric vehicles is one important cornerstone towards electrification. We developed a fast-executing heuristic scheduling algorithm that allows for multiple vehicle depots in the transport network; simultaneous electric and internal combustion engine vehicle deployment; determining the number of charging stations; partial charging; and scheduled charging with intermittent electricity supply. The scheduling algorithm achieves the minimum number of vehicles to execute the passenger demand in shorter total distances, outperforming current approaches. The algorithm demonstrated multi-objective optimisation by minimising the vehicles, the number of charging stations, and the average trip delays of a schedule.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"123 ","pages":"Article 104093"},"PeriodicalIF":5.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142823263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.jtrangeo.2024.104101
Renrong Xiao , Pengjun Zhao , Kangzheng Huang , Tianyu Ma , Zhangyuan He , Caixia Zhang , Di Lyu
Liquefied natural gas (LNG), as a transitional fossil fuel, plays a vital role in the modern energy transition process. In the context of the Russia–Ukraine geopolitical conflict, studying the evolution pattern and mechanisms of LNG trade networks is crucial for maintaining global energy security, particularly for countries relying on LNG imports. The study is based on multisource big data from 2021 to 2022, including Automatic Identification System (AIS) data, Gdelt news data, and remote sensing satellite data. It utilizes complex network metrics and the temporal exponential random graph model (TERGM) method to analyze the evolution patterns and mechanisms of the global LNG trade network. The research findings indicate the following: (1) The Russia–Ukraine conflict has led to a significant increase in LNG imports by European countries. Many countries have opened temporary direct shipping routes, which has accelerated the decline in the average path length of the network and improved network efficiency. (2) The global LNG trade community trend has been strengthened by the Russia–Ukraine conflict. The number of members within the trading community in which the United States is located has increased, with some European countries moving into this community. (3) The reciprocal structural characteristics of the LNG trade network drive its development, and the expansion of the national port handling capacity ability also drives network growth. Conversely, large differences in geopolitical relations, culture, and levels of governance between countries can hinder global LNG network development. This study provides a theoretical basis and decision-making reference for energy security under major geopolitical conflicts.
{"title":"Liquefied natural gas trade network changes and its mechanism in the context of the Russia–Ukraine conflict","authors":"Renrong Xiao , Pengjun Zhao , Kangzheng Huang , Tianyu Ma , Zhangyuan He , Caixia Zhang , Di Lyu","doi":"10.1016/j.jtrangeo.2024.104101","DOIUrl":"10.1016/j.jtrangeo.2024.104101","url":null,"abstract":"<div><div>Liquefied natural gas (LNG), as a transitional fossil fuel, plays a vital role in the modern energy transition process. In the context of the Russia–Ukraine geopolitical conflict, studying the evolution pattern and mechanisms of LNG trade networks is crucial for maintaining global energy security, particularly for countries relying on LNG imports. The study is based on multisource big data from 2021 to 2022, including Automatic Identification System (AIS) data, Gdelt news data, and remote sensing satellite data. It utilizes complex network metrics and the temporal exponential random graph model (TERGM) method to analyze the evolution patterns and mechanisms of the global LNG trade network. The research findings indicate the following: (1) The Russia–Ukraine conflict has led to a significant increase in LNG imports by European countries. Many countries have opened temporary direct shipping routes, which has accelerated the decline in the average path length of the network and improved network efficiency. (2) The global LNG trade community trend has been strengthened by the Russia–Ukraine conflict. The number of members within the trading community in which the United States is located has increased, with some European countries moving into this community. (3) The reciprocal structural characteristics of the LNG trade network drive its development, and the expansion of the national port handling capacity ability also drives network growth. Conversely, large differences in geopolitical relations, culture, and levels of governance between countries can hinder global LNG network development. This study provides a theoretical basis and decision-making reference for energy security under major geopolitical conflicts.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"123 ","pages":"Article 104101"},"PeriodicalIF":5.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142889312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.jtrangeo.2024.104085
Mengyuan Lu , Edgar Jimenez Perez , Keith Mason , Max Z. Li
Spatial and temporal coordination of air-high speed rail (HSR) intermodal networks is important to reduce emission, improve service, enhance efficiency, and reduce costs in the provision of air-HSR integration. This paper constructs a hierarchical optimisation model that first considers a spatial scope to solve the problem of route allocation and frequency choice which minimises total environmental, operational and passenger cost with a Mixed-Integer Linear Programming (MILP) model, based on a demand estimation for passenger trips between city pairs. Then, the second hierarchical level of the model considers a temporal scope to maximise connection opportunities between the resulting air and HSR networks using time windows to adjust frequencies with a Prescriptive Integer Quadratic Programming (PIQP) model. An application to a network of 40 cities in mainland China with both air and HSR transport service shows that the total emission of the network can be reduced by 22 %. Comparative analyses show that optimising for passenger costs favours increased air travel on medium- and long-haul routes, while an emissions-focused approach encourages a shift toward HSR for short and medium distances. Sensitivity analyses on carbon pricing further highlight the potential of gradual price adjustments to incentivise lower-emission modes without requiring additional HSR infrastructure.
{"title":"A hierarchical spatial and temporal optimisation of the air-high speed rail intermodal network","authors":"Mengyuan Lu , Edgar Jimenez Perez , Keith Mason , Max Z. Li","doi":"10.1016/j.jtrangeo.2024.104085","DOIUrl":"10.1016/j.jtrangeo.2024.104085","url":null,"abstract":"<div><div>Spatial and temporal coordination of air-high speed rail (HSR) intermodal networks is important to reduce emission, improve service, enhance efficiency, and reduce costs in the provision of air-HSR integration. This paper constructs a hierarchical optimisation model that first considers a spatial scope to solve the problem of route allocation and frequency choice which minimises total environmental, operational and passenger cost with a Mixed-Integer Linear Programming (MILP) model, based on a demand estimation for passenger trips between city pairs. Then, the second hierarchical level of the model considers a temporal scope to maximise connection opportunities between the resulting air and HSR networks using time windows to adjust frequencies with a Prescriptive Integer Quadratic Programming (PIQP) model. An application to a network of 40 cities in mainland China with both air and HSR transport service shows that the total emission of the network can be reduced by 22 %. Comparative analyses show that optimising for passenger costs favours increased air travel on medium- and long-haul routes, while an emissions-focused approach encourages a shift toward HSR for short and medium distances. Sensitivity analyses on carbon pricing further highlight the potential of gradual price adjustments to incentivise lower-emission modes without requiring additional HSR infrastructure.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"123 ","pages":"Article 104085"},"PeriodicalIF":5.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142790048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The spatial mismatch between coal production and consumption has led to long-distance coal transportation in China, which poses a challenge for balancing the trade-off between carbon reduction and energy security. In response, the spatial restructuring of long-distance transportation and how it contributes to carbon emissions are investigated. The Doubly Constrained Gravity Model is used to estimate the interprovincial coal transportation matrices from 1996 to 2019 and thus measure the coal transportation inflow and outflow radii of provinces and their corresponding carbon emissions. The results show that (1) the inflow radius supports a north-south division of provinces, with a pattern centered on Shanxi, Shaanxi, and Inner Mongolia. The outflow radius supports a coastal-inland division of provinces, with a pattern centered on the Yangtze River Delta region. Overall, the spatial extent of the coal supply in most provinces is shrinking, whereas the extent of demand is expanding. (2) Carbon emissions from coal transportation have increased with the westward shift in coal sources. The interprovincial transportation routes with the highest emissions display a radial pattern, shifting from monocentric to polycentric. (3) An increasing inflow radius suggests a demand-driven emission effect on provinces with advanced manufacturing bases, which have more emissions because of their demand gap. The decreasing outflow radius suggests a supply-driven emission effect. As provinces reduce their coal supply capacity, coal production bases should fill the demand gap, resulting in increased coal transportation emissions.
{"title":"Changes in the distance of interprovincial coal transportation in China and its effect on carbon emissions","authors":"Yiqing Guo, Xiyan Mao, Jianing Wei, Mingyang Liu, Yiqi Chen, Jie Zhou","doi":"10.1016/j.jtrangeo.2025.104139","DOIUrl":"10.1016/j.jtrangeo.2025.104139","url":null,"abstract":"<div><div>The spatial mismatch between coal production and consumption has led to long-distance coal transportation in China, which poses a challenge for balancing the trade-off between carbon reduction and energy security. In response, the spatial restructuring of long-distance transportation and how it contributes to carbon emissions are investigated. The Doubly Constrained Gravity Model is used to estimate the interprovincial coal transportation matrices from 1996 to 2019 and thus measure the coal transportation inflow and outflow radii of provinces and their corresponding carbon emissions. The results show that (1) the inflow radius supports a north-south division of provinces, with a pattern centered on Shanxi, Shaanxi, and Inner Mongolia. The outflow radius supports a coastal-inland division of provinces, with a pattern centered on the Yangtze River Delta region. Overall, the spatial extent of the coal supply in most provinces is shrinking, whereas the extent of demand is expanding. (2) Carbon emissions from coal transportation have increased with the westward shift in coal sources. The interprovincial transportation routes with the highest emissions display a radial pattern, shifting from monocentric to polycentric. (3) An increasing inflow radius suggests a demand-driven emission effect on provinces with advanced manufacturing bases, which have more emissions because of their demand gap. The decreasing outflow radius suggests a supply-driven emission effect. As provinces reduce their coal supply capacity, coal production bases should fill the demand gap, resulting in increased coal transportation emissions.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"123 ","pages":"Article 104139"},"PeriodicalIF":5.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143077695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.jtrangeo.2024.104079
Kailai Wang , Gino J. Lim , Bruce Race , Yunpeng (Jack) Zhang , Lu Gao , Fengxiang (George) Qiao
This study examines the spatial dynamics of warehouse location choice and the interplay between e-commerce, logistics businesses, and supply chain entities in three major urban areas in Texas: Houston, Austin, and Dallas-Fort Worth. We investigate the key factors influencing warehouse selection while accounting for spatial spillover effects (i.e., co-locational relationships), using data from 2003 to 2016. A major finding is that different types of business establishments exert distinct influences on warehouse location choice, varying across spatial scales. Notably, the effects from neighboring spatial units sometimes diverge from the direct impacts. For instance, manufacturing establishments have a positive direct influence on warehouse location choice in all three study areas, while neighboring manufacturing units show negative effects in Austin and Dallas. The analysis also highlights that when spatial interactions among e-commerce facilities, logistics businesses, and supply chain entities in adjacent units are accounted for, several transportation infrastructure and socioeconomic factors lose their statistical significance. The results provide valuable insights for policymakers, industry practitioners, and urban planners for informed warehousing facility allocation and development decisions in Texas metropolitan areas.
{"title":"Examining spatial patterns and economic interactions of logistics activities across three Texas metropolitan areas","authors":"Kailai Wang , Gino J. Lim , Bruce Race , Yunpeng (Jack) Zhang , Lu Gao , Fengxiang (George) Qiao","doi":"10.1016/j.jtrangeo.2024.104079","DOIUrl":"10.1016/j.jtrangeo.2024.104079","url":null,"abstract":"<div><div>This study examines the spatial dynamics of warehouse location choice and the interplay between e-commerce, logistics businesses, and supply chain entities in three major urban areas in Texas: Houston, Austin, and Dallas-Fort Worth. We investigate the key factors influencing warehouse selection while accounting for spatial spillover effects (i.e., co-locational relationships), using data from 2003 to 2016. A major finding is that different types of business establishments exert distinct influences on warehouse location choice, varying across spatial scales. Notably, the effects from neighboring spatial units sometimes diverge from the direct impacts. For instance, manufacturing establishments have a positive direct influence on warehouse location choice in all three study areas, while neighboring manufacturing units show negative effects in Austin and Dallas. The analysis also highlights that when spatial interactions among e-commerce facilities, logistics businesses, and supply chain entities in adjacent units are accounted for, several transportation infrastructure and socioeconomic factors lose their statistical significance. The results provide valuable insights for policymakers, industry practitioners, and urban planners for informed warehousing facility allocation and development decisions in Texas metropolitan areas.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"123 ","pages":"Article 104079"},"PeriodicalIF":5.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142823257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.jtrangeo.2025.104112
Rui An , Zhaomin Tong , Bo Tan , Qiangqiang Xiong , Yuanyuan Luo , Yaolin Liu , Linchuan Yang , Xiping Yang
Transit-oriented development encourages metropolises to alleviate jobs-housing separation (JHS) by optimizing the built environment (BE). Researchers have found that BE exerts different effects on home- and work-oriented JHS, but their statistical models ignored the nonlinear and spatially nonstationary features of the relationship. In this study, we collected location-based service data to identify commuters and aggregated them to 188 metro station areas from a home or work orientation. We then defined a parameter β to measure JHS following the distance decay law, added three-dimensional (3D) indicators to the “Node-Place-Function” system to describe the BE, and applied the LightGBM-SHAP after multi-model comparison to learn and visualize their complex relationships. We identified three types of BE variables: 1) exhibiting important effects only on one orientation, 2) exhibiting similar effects on two orientations, and 3) exhibiting opposite effects on two orientations. Particularly, we designed a new visualization framework for SHAP that synergizes nonlinear dependency with the spatial distribution, which can provide threshold targets and spatial ranges for policy regulation simultaneously. For example, Hanyang should increase its shared bicycle density to 900 vehicles/km2 to meet the travel needs of residents, while Jianghan should provide affordable housing (<180,00 yuan/m2) to meet the housing needs of workers. Our findings aim to encourage planners to consider nonlinear determined thresholds in regulating actual spaces, which can directly support the refined urban management under limited resource condition.
{"title":"Revealing the relationship between 2D/3D built environment and jobs-housing separation coupling nonlinearity and spatial nonstationarity","authors":"Rui An , Zhaomin Tong , Bo Tan , Qiangqiang Xiong , Yuanyuan Luo , Yaolin Liu , Linchuan Yang , Xiping Yang","doi":"10.1016/j.jtrangeo.2025.104112","DOIUrl":"10.1016/j.jtrangeo.2025.104112","url":null,"abstract":"<div><div>Transit-oriented development encourages metropolises to alleviate jobs-housing separation (JHS) by optimizing the built environment (BE). Researchers have found that BE exerts different effects on home- and work-oriented JHS, but their statistical models ignored the nonlinear and spatially nonstationary features of the relationship. In this study, we collected location-based service data to identify commuters and aggregated them to 188 metro station areas from a home or work orientation. We then defined a parameter β to measure JHS following the distance decay law, added three-dimensional (3D) indicators to the “Node-Place-Function” system to describe the BE, and applied the LightGBM-SHAP after multi-model comparison to learn and visualize their complex relationships. We identified three types of BE variables: 1) exhibiting important effects only on one orientation, 2) exhibiting similar effects on two orientations, and 3) exhibiting opposite effects on two orientations. Particularly, we designed a new visualization framework for SHAP that synergizes nonlinear dependency with the spatial distribution, which can provide threshold targets and spatial ranges for policy regulation simultaneously. For example, Hanyang should increase its shared bicycle density to 900 vehicles/km<sup>2</sup> to meet the travel needs of residents, while Jianghan should provide affordable housing (<180,00 yuan/m<sup>2</sup>) to meet the housing needs of workers. Our findings aim to encourage planners to consider nonlinear determined thresholds in regulating actual spaces, which can directly support the refined urban management under limited resource condition.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"123 ","pages":"Article 104112"},"PeriodicalIF":5.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142968036","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.jtrangeo.2025.104111
Wei Dong , Naidi Wang , Yu Dong , Jason Cao
Previous studies often overlook nonlinear relationships between built environment characteristics and travel satisfaction, and few examine the interaction effects of these characteristics on travel satisfaction. Using gradient boosting decision trees on a dataset of 1167 respondents collected from Harbin, China, in 2021, we estimated the nonlinear and interaction effects of built environment characteristics on travel satisfaction. We found that perceived built environment attributes, such as infrastructure and safety for walking, aesthetics, physical barriers, and land-use mix, are key predictors of residents' travel satisfaction, and their relationships are mostly nonlinear. Furthermore, built environment characteristics exhibit three patterns of interaction effects on travel satisfaction: compensation, suppression, and reinforcement. These findings can help planners better assess the costs and benefits of environmental improvement plans.
{"title":"Examining the nonlinear and interactive effects of built environment characteristics on travel satisfaction","authors":"Wei Dong , Naidi Wang , Yu Dong , Jason Cao","doi":"10.1016/j.jtrangeo.2025.104111","DOIUrl":"10.1016/j.jtrangeo.2025.104111","url":null,"abstract":"<div><div>Previous studies often overlook nonlinear relationships between built environment characteristics and travel satisfaction, and few examine the interaction effects of these characteristics on travel satisfaction. Using gradient boosting decision trees on a dataset of 1167 respondents collected from Harbin, China, in 2021, we estimated the nonlinear and interaction effects of built environment characteristics on travel satisfaction. We found that perceived built environment attributes, such as infrastructure and safety for walking, aesthetics, physical barriers, and land-use mix, are key predictors of residents' travel satisfaction, and their relationships are mostly nonlinear. Furthermore, built environment characteristics exhibit three patterns of interaction effects on travel satisfaction: compensation, suppression, and reinforcement. These findings can help planners better assess the costs and benefits of environmental improvement plans.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"123 ","pages":"Article 104111"},"PeriodicalIF":5.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142968037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.jtrangeo.2025.104118
Meng Liu, Sylvia Y. He
Transport electrification is a critical step toward energy conservation and emission reduction. However, the central challenge for electrifying transportation remains insufficient and unsuitable configurations of public charging infrastructure. Understanding the charging behavior of electric taxi (e-taxi) drivers from an urban planning perspective is important for planning public charging infrastructure. In light of this, our study extracts e-taxi drivers' charging behavior from the large-scale GPS trajectory data of a fully electrified taxi fleet, considers two major concerns of e-taxi drivers (charging and ridership), and examines the specific nonlinear, threshold, and interaction effects of the built environment, temporal factors, and taxi ridership on e-taxi drivers' usage of charging stations. The results indicate that the built environment represents the largest contributing factor, followed by temporal factors and taxi ridership. Meanwhile, the three variables of interest demonstrate significant nonlinear, threshold, and interactive effects on charging behavior. Research findings from this study can provide insights for future research and offer quantitative support for administrators and planners wanting to deploy appropriate and precise planning strategies that incorporate the charging preferences of e-taxi drivers to improve the effectiveness of spatial planning for public charging stations.
{"title":"E-taxi drivers' charging behavior: Effects of the built environment, temporal factors, and ridership","authors":"Meng Liu, Sylvia Y. He","doi":"10.1016/j.jtrangeo.2025.104118","DOIUrl":"10.1016/j.jtrangeo.2025.104118","url":null,"abstract":"<div><div>Transport electrification is a critical step toward energy conservation and emission reduction. However, the central challenge for electrifying transportation remains insufficient and unsuitable configurations of public charging infrastructure. Understanding the charging behavior of electric taxi (e-taxi) drivers from an urban planning perspective is important for planning public charging infrastructure. In light of this, our study extracts e-taxi drivers' charging behavior from the large-scale GPS trajectory data of a fully electrified taxi fleet, considers two major concerns of e-taxi drivers (charging and ridership), and examines the specific nonlinear, threshold, and interaction effects of the built environment, temporal factors, and taxi ridership on e-taxi drivers' usage of charging stations. The results indicate that the built environment represents the largest contributing factor, followed by temporal factors and taxi ridership. Meanwhile, the three variables of interest demonstrate significant nonlinear, threshold, and interactive effects on charging behavior. Research findings from this study can provide insights for future research and offer quantitative support for administrators and planners wanting to deploy appropriate and precise planning strategies that incorporate the charging preferences of e-taxi drivers to improve the effectiveness of spatial planning for public charging stations.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"123 ","pages":"Article 104118"},"PeriodicalIF":5.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143396229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This article investigates the impact of the Israeli-Hamas conflict on maritime sector stocks using an event study approach, highlighting the sector's vulnerability during crises. Analyzing 32 companies across container, tanker, and dry bulk sub-sectors, we employ the Fama and French three-factor model to assess how maritime stocks respond to conflict-related news. Our findings reveal predominantly adverse stock reactions, particularly in the container and tanker segments, with the dry bulk sub-sector less affected. Notably, container shipping stocks showed significant declines following missile attacks on cargo vessels. Conversely, the market response to positive news, such as a ceasefire between Israel and Hamas, was muted, suggesting that good news impacts trading behaviour less than bad news. This study underscores the importance of monitoring news during major crises for theoretical and practical implications in the maritime industry, as it significantly influences stock performance.
{"title":"Geopolitical uncertainty and shipping stock returns: An event study of the Israel-Hamas conflict","authors":"Mutaju Isaack Marobhe , Jonathan Mukiza Kansheba , Ziaul Haque Munim","doi":"10.1016/j.jtrangeo.2025.104122","DOIUrl":"10.1016/j.jtrangeo.2025.104122","url":null,"abstract":"<div><div>This article investigates the impact of the Israeli-Hamas conflict on maritime sector stocks using an event study approach, highlighting the sector's vulnerability during crises. Analyzing 32 companies across container, tanker, and dry bulk sub-sectors, we employ the Fama and French three-factor model to assess how maritime stocks respond to conflict-related news. Our findings reveal predominantly adverse stock reactions, particularly in the container and tanker segments, with the dry bulk sub-sector less affected. Notably, container shipping stocks showed significant declines following missile attacks on cargo vessels. Conversely, the market response to positive news, such as a ceasefire between Israel and Hamas, was muted, suggesting that good news impacts trading behaviour less than bad news. This study underscores the importance of monitoring news during major crises for theoretical and practical implications in the maritime industry, as it significantly influences stock performance.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"123 ","pages":"Article 104122"},"PeriodicalIF":5.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143388378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.jtrangeo.2025.104149
Hui Kong , Hao Chao , Wenyan Fu , Diao Lin , Yongping Zhang
Extensive research has been conducted on the usage patterns and potential impacts of shared micromobility, yet the distinct relationships with public transit between shared bikes and shared E-bikes – the two main micromobility modes in China – remain unexplored. Examining the potentially distinct modal shift patterns away from public transit is essential to understand the landscape of different micromobility modes and their different disruptions to traditional transportation modes. To bridge this gap, this study analyzed shared micromobility trip data from Ningbo, China, aiming to quantify the relationship between shared micromobility and public transit, and differentiate between the interactions of shared bikes and E-bikes with public transit. We employed a geospatial-based approach to categorize each shared micromobility trip into three types: Modal Substitution (MS), Modal Integration (MI), and Modal Complementation (MC), based on their interactions with buses and subways. Then we explored the spatial and temporal patterns of the shares of MS, MI, and MC trips, and investigated factors influencing these varied relationships using Spatial Autoregressive (SAR) models. Our findings indicate that shared E-bikes more frequently substitute for public transit, whereas shared bikes are predominantly used in MC roles. There are notable temporal and spatial variations in the usage of shared E-bikes and bikes: temporally, there is a morning peak of shared E-bikes that substitute public transit, and spatially, E-bike sharing has a higher concentration of substitution in suburbs while bike sharing has a higher concentration of complementation in the outer areas. The observed differences between E-bikes and bikes regarding their relationship with public transit are largely influenced by trip distance, speed, and public transit characteristics. This study highlights the importance of recognizing the diverse interactions between different shared micromobility modes and public transit, and sheds light on the development and management of shared micromobility and public transit systems.
{"title":"Relationship between shared micromobility and public transit: The differences between shared bikes and shared E-bikes","authors":"Hui Kong , Hao Chao , Wenyan Fu , Diao Lin , Yongping Zhang","doi":"10.1016/j.jtrangeo.2025.104149","DOIUrl":"10.1016/j.jtrangeo.2025.104149","url":null,"abstract":"<div><div>Extensive research has been conducted on the usage patterns and potential impacts of shared micromobility, yet the distinct relationships with public transit between shared bikes and shared <em>E</em>-bikes – the two main micromobility modes in China – remain unexplored. Examining the potentially distinct modal shift patterns away from public transit is essential to understand the landscape of different micromobility modes and their different disruptions to traditional transportation modes. To bridge this gap, this study analyzed shared micromobility trip data from Ningbo, China, aiming to quantify the relationship between shared micromobility and public transit, and differentiate between the interactions of shared bikes and <em>E</em>-bikes with public transit. We employed a geospatial-based approach to categorize each shared micromobility trip into three types: Modal Substitution (MS), Modal Integration (MI), and Modal Complementation (MC), based on their interactions with buses and subways. Then we explored the spatial and temporal patterns of the shares of MS, MI, and MC trips, and investigated factors influencing these varied relationships using Spatial Autoregressive (SAR) models. Our findings indicate that shared <em>E</em>-bikes more frequently substitute for public transit, whereas shared bikes are predominantly used in MC roles. There are notable temporal and spatial variations in the usage of shared <em>E</em>-bikes and bikes: temporally, there is a morning peak of shared E-bikes that substitute public transit, and spatially, E-bike sharing has a higher concentration of substitution in suburbs while bike sharing has a higher concentration of complementation in the outer areas. The observed differences between E-bikes and bikes regarding their relationship with public transit are largely influenced by trip distance, speed, and public transit characteristics. This study highlights the importance of recognizing the diverse interactions between different shared micromobility modes and public transit, and sheds light on the development and management of shared micromobility and public transit systems.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"123 ","pages":"Article 104149"},"PeriodicalIF":5.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143378273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}