{"title":"Corrigendum to ‘Origin-destination demand prediction for shared mobility service using fully convolutional neural network’ [Research in Transportation Business & Management, Vol. 64, 101527]","authors":"Karn Patanukhom , Santi Phithakkitnukoon , Merkebe Getachew Demissie","doi":"10.1016/j.rtbm.2025.101548","DOIUrl":"10.1016/j.rtbm.2025.101548","url":null,"abstract":"","PeriodicalId":47453,"journal":{"name":"Research in Transportation Business and Management","volume":"64 ","pages":"Article 101548"},"PeriodicalIF":4.4,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145736849","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 : 2025-10-31DOI: 10.1016/j.rtbm.2025.101535
Xucong Zhong, Yinghong Zhou, Zhijing Yang, Weihao Yang, Zhenxuan Lu
Price-based demand response is a key strategy for managing electric vehicle (EV) charging infrastructure, yet existing approaches face two critical challenges: (1) reliance on simulated traffic data that may not accurately represent real-world charging patterns, and (2) the unpredictability of user behavior challenge algorithms based solely on charging demand and electricity prices. To address these two challenges, this paper proposes a novel, iterative two-step framework that leverages real-world charging data. First, we develop an LSTM with self-attention model to accurately predict charging demand by capturing intricate user behavior patterns. Second, we introduce TransA3C, a novel algorithm that integrates a Transformer into the Asynchronous Advantage Actor–Critic (A3C) framework to optimize dynamic service fee. The core of our approach is a dynamic feedback loop: the predicted demand guides the TransA3C pricing decisions, and the resulting service fee is then used as an input for subsequent demand predictions. This iterative process allows the system to continuously adapt to market fluctuations and user behavior. Experimental results, validated on a large-scale, real-world dataset from a city in China, where the proposed dynamic pricing significantly increases the profit and utilization rate of the charging stations. Furthermore, the proposed framework is scalable and transferable to other urban charging networks with fine-tuning, highlighting its broad practical applicability and potential for widespread deployment in EV charging operations.
{"title":"Dynamic pricing for electric vehicle charging: An iterative two-step approach based on deep reinforcement learning","authors":"Xucong Zhong, Yinghong Zhou, Zhijing Yang, Weihao Yang, Zhenxuan Lu","doi":"10.1016/j.rtbm.2025.101535","DOIUrl":"10.1016/j.rtbm.2025.101535","url":null,"abstract":"<div><div>Price-based demand response is a key strategy for managing electric vehicle (EV) charging infrastructure, yet existing approaches face two critical challenges: (1) reliance on simulated traffic data that may not accurately represent real-world charging patterns, and (2) the unpredictability of user behavior challenge algorithms based solely on charging demand and electricity prices. To address these two challenges, this paper proposes a novel, iterative two-step framework that leverages real-world charging data. First, we develop an LSTM with self-attention model to accurately predict charging demand by capturing intricate user behavior patterns. Second, we introduce TransA3C, a novel algorithm that integrates a Transformer into the Asynchronous Advantage Actor–Critic (A3C) framework to optimize dynamic service fee. The core of our approach is a dynamic feedback loop: the predicted demand guides the TransA3C pricing decisions, and the resulting service fee is then used as an input for subsequent demand predictions. This iterative process allows the system to continuously adapt to market fluctuations and user behavior. Experimental results, validated on a large-scale, real-world dataset from a city in China, where the proposed dynamic pricing significantly increases the profit and utilization rate of the charging stations. Furthermore, the proposed framework is scalable and transferable to other urban charging networks with fine-tuning, highlighting its broad practical applicability and potential for widespread deployment in EV charging operations.</div></div>","PeriodicalId":47453,"journal":{"name":"Research in Transportation Business and Management","volume":"64 ","pages":"Article 101535"},"PeriodicalIF":4.4,"publicationDate":"2025-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145418196","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 : 2025-10-31DOI: 10.1016/j.rtbm.2025.101547
Ting-Hsiang Tseng , Muhammad Dliya'ul Haq , Artya Lathifah , Armando Susanto
This study examines the interaction between system quality, information quality, and perceived suitability of price in shaping customer outcomes such as value, brand image, satisfaction, and repurchase intentions within the ride-sharing industry. It specifically explores the dual moderating role of perceived suitability of price, analyzing how it strengthens and weakens the effects of system and information quality on brand image. Grounded in expectation-confirmation theory (ECT) and perceived value theory, the study utilizes Structural Equation Modeling (SEM) to analyze data collected from 509 ride-sharing users in Indonesia. Findings indicate that system and information quality enhance customer value and brand image, thereby boosting satisfaction and repurchase intentions. Notably, the perceived suitability of price was found to have a dual moderating effect: it enhances the positive impact of system quality on brand image and unexpectedly weakens the influence of information quality on brand image. These findings challenge the typical assumption that favorable price perceptions enhance brand evaluations, offering new insights for aligning service improvements with pricing strategies on digital platforms. In conclusion, these results provide actionable insights for ride-sharing platforms to optimize digital service delivery and pricing strategies, thereby enhancing customer satisfaction and loyalty, which support the development of more sustainable transportation solutions in the ride-sharing sector.
{"title":"Beyond price and quality: How perceived price suitability shapes consumer outcomes in ride-sharing services","authors":"Ting-Hsiang Tseng , Muhammad Dliya'ul Haq , Artya Lathifah , Armando Susanto","doi":"10.1016/j.rtbm.2025.101547","DOIUrl":"10.1016/j.rtbm.2025.101547","url":null,"abstract":"<div><div>This study examines the interaction between system quality, information quality, and perceived suitability of price in shaping customer outcomes such as value, brand image, satisfaction, and repurchase intentions within the ride-sharing industry. It specifically explores the dual moderating role of perceived suitability of price, analyzing how it strengthens and weakens the effects of system and information quality on brand image. Grounded in expectation-confirmation theory (ECT) and perceived value theory, the study utilizes Structural Equation Modeling (SEM) to analyze data collected from 509 ride-sharing users in Indonesia. Findings indicate that system and information quality enhance customer value and brand image, thereby boosting satisfaction and repurchase intentions. Notably, the perceived suitability of price was found to have a dual moderating effect: it enhances the positive impact of system quality on brand image and unexpectedly weakens the influence of information quality on brand image. These findings challenge the typical assumption that favorable price perceptions enhance brand evaluations, offering new insights for aligning service improvements with pricing strategies on digital platforms. In conclusion, these results provide actionable insights for ride-sharing platforms to optimize digital service delivery and pricing strategies, thereby enhancing customer satisfaction and loyalty, which support the development of more sustainable transportation solutions in the ride-sharing sector.</div></div>","PeriodicalId":47453,"journal":{"name":"Research in Transportation Business and Management","volume":"64 ","pages":"Article 101547"},"PeriodicalIF":4.4,"publicationDate":"2025-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145418197","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 : 2025-10-28DOI: 10.1016/j.rtbm.2025.101546
Lianxiao Yao, Weidong Chen
The transportation sector is highly sensitive to climatic conditions, and while climate change is expected to affect its productivity, systematic quantitative evidence of such historical impacts remains limited. Utilizing panel data spanning 2000 to 2022 of the transportation industry in 278 Chinese cities, this paper employs a robust econometric model to scrutinize the weather's influence on the transportation industry's total factor productivity. The findings reveal an inverted U-shaped effect resulting from temperature changes on productivity. Higher temperatures prompt decision-makers to adjust labor and capital inputs, reducing total factor productivity. They also disrupt travel patterns, affecting passenger and freight volumes, and alter capital utilization efficiency, further impacting productivity. The research also emphasizes that climate change disproportionately affects regions with relatively backward economic development stages or higher temperatures. Offering evidence on climate change's impact on the transportation industry productivity can provide policymakers with an objective understanding of its vulnerability to climate-related challenges.
{"title":"Echoes of catastrophe: The uneven impacts of climate change on China's transportation productivity","authors":"Lianxiao Yao, Weidong Chen","doi":"10.1016/j.rtbm.2025.101546","DOIUrl":"10.1016/j.rtbm.2025.101546","url":null,"abstract":"<div><div>The transportation sector is highly sensitive to climatic conditions, and while climate change is expected to affect its productivity, systematic quantitative evidence of such historical impacts remains limited. Utilizing panel data spanning 2000 to 2022 of the transportation industry in 278 Chinese cities, this paper employs a robust econometric model to scrutinize the weather's influence on the transportation industry's total factor productivity. The findings reveal an inverted U-shaped effect resulting from temperature changes on productivity. Higher temperatures prompt decision-makers to adjust labor and capital inputs, reducing total factor productivity. They also disrupt travel patterns, affecting passenger and freight volumes, and alter capital utilization efficiency, further impacting productivity. The research also emphasizes that climate change disproportionately affects regions with relatively backward economic development stages or higher temperatures. Offering evidence on climate change's impact on the transportation industry productivity can provide policymakers with an objective understanding of its vulnerability to climate-related challenges.</div></div>","PeriodicalId":47453,"journal":{"name":"Research in Transportation Business and Management","volume":"64 ","pages":"Article 101546"},"PeriodicalIF":4.4,"publicationDate":"2025-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145418195","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 : 2025-10-28DOI: 10.1016/j.rtbm.2025.101545
Yanan Li , Yanyan Chen , Yifei Gong , Fuhua Yi , Yinjia Guo , Jiachen Wang
In the context of the “dual carbon” targets of China, effectively reducing carbon emissions in the road freight transportation sector is crucial. Carbon emission trading has emerged as a cost-effective strategy for mitigating carbon emissions, particularly in the context of road freight transport. Currently, the system design of carbon emission trading for road freight transport industry is still unknown. To fill this gap, this study presents a comprehensive policy framework tailored for China's road freight transport sector. The framework includes key components such as data collection and verification processes for carbon emissions, the establishment and distribution of carbon allowances, regulatory mechanisms for carbon emission trading, and an integrated reward and punishment system. Furthermore, the study employs case studies and scenario analyses to examine the operational dynamics of the carbon trading system in road freight transportation. The findings indicate that, to meet compliance requirements and generate additional revenue, freight vehicle operators are incentivized to reduce carbon emissions either by decreasing vehicle miles travelled or by investing in vehicles with lower energy consumption. The purpose of this paper was to provide the theoretical basis for the effective facilitation of carbon emission trading system for China's road freight transport.
{"title":"A carbon emission trading system for China's road freight transport: considering reward and punishment ladders","authors":"Yanan Li , Yanyan Chen , Yifei Gong , Fuhua Yi , Yinjia Guo , Jiachen Wang","doi":"10.1016/j.rtbm.2025.101545","DOIUrl":"10.1016/j.rtbm.2025.101545","url":null,"abstract":"<div><div>In the context of the “dual carbon” targets of China, effectively reducing carbon emissions in the road freight transportation sector is crucial. Carbon emission trading has emerged as a cost-effective strategy for mitigating carbon emissions, particularly in the context of road freight transport. Currently, the system design of carbon emission trading for road freight transport industry is still unknown. To fill this gap, this study presents a comprehensive policy framework tailored for China's road freight transport sector. The framework includes key components such as data collection and verification processes for carbon emissions, the establishment and distribution of carbon allowances, regulatory mechanisms for carbon emission trading, and an integrated reward and punishment system. Furthermore, the study employs case studies and scenario analyses to examine the operational dynamics of the carbon trading system in road freight transportation. The findings indicate that, to meet compliance requirements and generate additional revenue, freight vehicle operators are incentivized to reduce carbon emissions either by decreasing vehicle miles travelled or by investing in vehicles with lower energy consumption. The purpose of this paper was to provide the theoretical basis for the effective facilitation of carbon emission trading system for China's road freight transport.</div></div>","PeriodicalId":47453,"journal":{"name":"Research in Transportation Business and Management","volume":"64 ","pages":"Article 101545"},"PeriodicalIF":4.4,"publicationDate":"2025-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145418200","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 : 2025-10-28DOI: 10.1016/j.rtbm.2025.101550
Yusuf Arslan
This study examines the effect of e-shopper innovativeness (i.e., consumers' tendency to adopt new ideas and technologies before others) on parcel locker (PL) adoption in an emerging market context (Turkey). It introduces a conceptual model incorporating social influence and trust as mediating variables, and transaction costs as a moderating factor. Based on a survey of 363 online shoppers in Sakarya, Turkey, structural equation modeling and PROCESS analyses reveal that innovativeness significantly enhances PL adoption both directly and through increased trust and social influence. However, high perceived transaction costs are found to weaken these effects. The final model explains 76 % of the variance in PL adoption intention. Theoretically, our findings extend the Technology Acceptance Model (TAM)/Unified Theory of Acceptance and Use of Technology (UTAUT) based frameworks by incorporating individual innovativeness into the technology acceptance model and highlighting the mediating roles of trust and social influence. Integrating a transaction cost perspective further provides a more comprehensive view of PL adoption drivers and barriers. Practically, the study suggests that e-commerce and logistics providers should target innovative consumers as early adopters, leverage peer influence, build trust in PL systems, and minimize perceived transaction costs to accelerate parcel locker adoption.
{"title":"E-shopper innovativeness and parcel locker adoption: Mediating roles of social influence and trust, and the moderating impact of transaction costs","authors":"Yusuf Arslan","doi":"10.1016/j.rtbm.2025.101550","DOIUrl":"10.1016/j.rtbm.2025.101550","url":null,"abstract":"<div><div>This study examines the effect of e-shopper innovativeness (i.e., consumers' tendency to adopt new ideas and technologies before others) on parcel locker (PL) adoption in an emerging market context (Turkey). It introduces a conceptual model incorporating social influence and trust as mediating variables, and transaction costs as a moderating factor. Based on a survey of 363 online shoppers in Sakarya, Turkey, structural equation modeling and PROCESS analyses reveal that innovativeness significantly enhances PL adoption both directly and through increased trust and social influence. However, high perceived transaction costs are found to weaken these effects. The final model explains 76 % of the variance in PL adoption intention. Theoretically, our findings extend the Technology Acceptance Model (TAM)/Unified Theory of Acceptance and Use of Technology (UTAUT) based frameworks by incorporating individual innovativeness into the technology acceptance model and highlighting the mediating roles of trust and social influence. Integrating a transaction cost perspective further provides a more comprehensive view of PL adoption drivers and barriers. Practically, the study suggests that e-commerce and logistics providers should target innovative consumers as early adopters, leverage peer influence, build trust in PL systems, and minimize perceived transaction costs to accelerate parcel locker adoption.</div></div>","PeriodicalId":47453,"journal":{"name":"Research in Transportation Business and Management","volume":"64 ","pages":"Article 101550"},"PeriodicalIF":4.4,"publicationDate":"2025-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145418198","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 : 2025-10-25DOI: 10.1016/j.rtbm.2025.101538
Bokai Fan , Yuan Zang
This study investigates the mechanisms through which high-speed rail (HSR) networks facilitate intercity collaborative innovation by agglomeration externalities and network externalities within a unified “agglomeration-network externalities” framework. From the agglomeration perspective, we analyze how HSR access in node cities enhances the quantity, quality, and diversity of intercity innovation cooperation. From the network perspective, we identify four key intercity effects—labor pooling, knowledge spillover, talent mobility, and service sharing—while examining how urban network characteristics and intercity boundary segmentation heterogeneously shape HSR-driven innovation collaboration. Based on the comprehensive perspective of agglomeration-network externalities, we further propose that the HSR network drives intercity collaborative innovation through three mechanisms: efficiency enhancement, global spillover, and synergistic amplification effects. Empirical results demonstrate that HSR significantly improves the scale and quality of intercity collaborative innovation in nodal cities, primarily through knowledge agglomeration, talent concentration, and capital accumulation, though these effects diminish sequentially. However, HSR also reduces average partnership intensity due to frequent restructuring of collaborative ties and knowledge-base convergence. Network analysis reveals that HSR strengthens intercity innovation through four decreasingly potent mechanisms: talent mobility (strongest), labor pooling, service sharing, and knowledge spillovers (weakest). These effects exhibit core-periphery heterogeneity, with the strongest impacts observed between core network cities. Boundary effects follow a hierarchical breakdown pattern, with policy barriers being most resistant, followed by administrative, cultural, and geographical boundaries. Finally, structural optimization of HSR commuting networks amplifies the three key agglomeration-network effects, with synergistic amplification demonstrating the strongest influence, followed by global spillovers and efficiency gains.These findings contribute to the literature by (1) advancing a dual-space theoretical framework for transport infrastructure and innovation diffusion, and (2) providing empirical evidence on the heterogeneous spatial effects of HSR networks. The study offers policy insights for regional innovation planning and HSR network optimization.
{"title":"High-speed rail networks and intercity collaborative innovation: An agglomeration-network externalities perspective","authors":"Bokai Fan , Yuan Zang","doi":"10.1016/j.rtbm.2025.101538","DOIUrl":"10.1016/j.rtbm.2025.101538","url":null,"abstract":"<div><div>This study investigates the mechanisms through which high-speed rail (HSR) networks facilitate intercity collaborative innovation by agglomeration externalities and network externalities within a unified “agglomeration-network externalities” framework. From the agglomeration perspective, we analyze how HSR access in node cities enhances the quantity, quality, and diversity of intercity innovation cooperation. From the network perspective, we identify four key intercity effects—labor pooling, knowledge spillover, talent mobility, and service sharing—while examining how urban network characteristics and intercity boundary segmentation heterogeneously shape HSR-driven innovation collaboration. Based on the comprehensive perspective of agglomeration-network externalities, we further propose that the HSR network drives intercity collaborative innovation through three mechanisms: efficiency enhancement, global spillover, and synergistic amplification effects. Empirical results demonstrate that HSR significantly improves the scale and quality of intercity collaborative innovation in nodal cities, primarily through knowledge agglomeration, talent concentration, and capital accumulation, though these effects diminish sequentially. However, HSR also reduces average partnership intensity due to frequent restructuring of collaborative ties and knowledge-base convergence. Network analysis reveals that HSR strengthens intercity innovation through four decreasingly potent mechanisms: talent mobility (strongest), labor pooling, service sharing, and knowledge spillovers (weakest). These effects exhibit core-periphery heterogeneity, with the strongest impacts observed between core network cities. Boundary effects follow a hierarchical breakdown pattern, with policy barriers being most resistant, followed by administrative, cultural, and geographical boundaries. Finally, structural optimization of HSR commuting networks amplifies the three key agglomeration-network effects, with synergistic amplification demonstrating the strongest influence, followed by global spillovers and efficiency gains.These findings contribute to the literature by (1) advancing a dual-space theoretical framework for transport infrastructure and innovation diffusion, and (2) providing empirical evidence on the heterogeneous spatial effects of HSR networks. The study offers policy insights for regional innovation planning and HSR network optimization.</div></div>","PeriodicalId":47453,"journal":{"name":"Research in Transportation Business and Management","volume":"64 ","pages":"Article 101538"},"PeriodicalIF":4.4,"publicationDate":"2025-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145418202","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 : 2025-10-25DOI: 10.1016/j.rtbm.2025.101534
Bien Van Nguyen , Duy Quy Nguyen-Phuoc , Nhat Dinh Quang Vo , Diep Ngoc Su , Oscar Oviedo-Trespalacios
Urban transportation in Vietnam, dominated by fossil fuel-powered motorbikes, is causing severe air pollution, contributing to climate change, and posing a threat to public health. In response to these challenges, promoting the transition from traditional motorbikes to electric motorcycles (EMs) is considered a sustainable transportation solution, aligning with the global trend toward green development. However, to expand market share and enhance the acceptance of electric motorcycles, a deeper understanding of consumer perception and behavior is essential. This study aims to develop and test a research model based on the cognitive–affective–conative framework. Data collected from 506 conventional motorbike users in Vietnam were analyzed using the SEM method. The study employs a second-order model, grounded in the cognitive–affective–conative framework, to evaluate the relationship between perceived value and perceived cost with the intention to use electric motorcycles, mediated by the role of anticipated emotions. The findings clarify the role of perceived value and perceived cost in shaping customers' anticipated emotions, which significantly influence their intention to switch to electric motorcycles. These insights not only provide valuable information for manufacturers and policymakers but also contribute to shaping development and marketing strategies for electric motorcycles in the future.
{"title":"How value, cost, and emotions drive electric motorcycle adoption in Vietnam: A cognitive–affective–conative approach","authors":"Bien Van Nguyen , Duy Quy Nguyen-Phuoc , Nhat Dinh Quang Vo , Diep Ngoc Su , Oscar Oviedo-Trespalacios","doi":"10.1016/j.rtbm.2025.101534","DOIUrl":"10.1016/j.rtbm.2025.101534","url":null,"abstract":"<div><div>Urban transportation in Vietnam, dominated by fossil fuel-powered motorbikes, is causing severe air pollution, contributing to climate change, and posing a threat to public health. In response to these challenges, promoting the transition from traditional motorbikes to electric motorcycles (EMs) is considered a sustainable transportation solution, aligning with the global trend toward green development. However, to expand market share and enhance the acceptance of electric motorcycles, a deeper understanding of consumer perception and behavior is essential. This study aims to develop and test a research model based on the cognitive–affective–conative framework. Data collected from 506 conventional motorbike users in Vietnam were analyzed using the SEM method. The study employs a second-order model, grounded in the cognitive–affective–conative framework, to evaluate the relationship between perceived value and perceived cost with the intention to use electric motorcycles, mediated by the role of anticipated emotions. The findings clarify the role of perceived value and perceived cost in shaping customers' anticipated emotions, which significantly influence their intention to switch to electric motorcycles. These insights not only provide valuable information for manufacturers and policymakers but also contribute to shaping development and marketing strategies for electric motorcycles in the future.</div></div>","PeriodicalId":47453,"journal":{"name":"Research in Transportation Business and Management","volume":"64 ","pages":"Article 101534"},"PeriodicalIF":4.4,"publicationDate":"2025-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145418199","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 : 2025-10-25DOI: 10.1016/j.rtbm.2025.101542
Jinsoo Hwang , Heather Markham Kim , Jinpyo Park , Noman Sahito , Ja Young Jacey Choe
{"title":"Corrigendum to “Tourist perceptions of robotaxis through perceived risk theory and technology acceptance model: Focusing on the ICT development index” Research in Transportation Business & Management, Volume 64, January 2026, 101526, start page 1–15","authors":"Jinsoo Hwang , Heather Markham Kim , Jinpyo Park , Noman Sahito , Ja Young Jacey Choe","doi":"10.1016/j.rtbm.2025.101542","DOIUrl":"10.1016/j.rtbm.2025.101542","url":null,"abstract":"","PeriodicalId":47453,"journal":{"name":"Research in Transportation Business and Management","volume":"64 ","pages":"Article 101542"},"PeriodicalIF":4.4,"publicationDate":"2025-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145736848","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 : 2025-10-24DOI: 10.1016/j.rtbm.2025.101544
Pengxiang Ding , Suwei Feng , Dorina Pojani
This study examines the effects of China's The Transit Metropolis Pilot (TMP) program on carbon emissions across 273 cities from 2006 to 2019, a quasi-natural experimental design and a staged difference-in-differences model are used. This study draws several noteworthy conclusions: (1) The TMP program has proven effective in directly reducing carbon emissions in China. In comparison to non-pilot cities, the pilots have achieved a commendable 13.4 % reduction in carbon emission intensity and an 8.3 % decrease in total carbon emissions. (2) Notably, the program's impact is more pronounced in larger cities and in the western regions of the country. (3) TMP has a lasting effect on carbon emissions, persisting for one to five years after the pilot implementation. And (4) The TMP program affects emissions indirectly through ‘Avoid-Shift-Improve’ mechanisms, which include restrictions on car purchase/use, enhancements in public transport, investments in urban technology, and the adoption of new energy vehicles.
{"title":"The impact of China's Transit Metropolis Pilot program on carbon emissions","authors":"Pengxiang Ding , Suwei Feng , Dorina Pojani","doi":"10.1016/j.rtbm.2025.101544","DOIUrl":"10.1016/j.rtbm.2025.101544","url":null,"abstract":"<div><div>This study examines the effects of China's The Transit Metropolis Pilot (TMP) program on carbon emissions across 273 cities from 2006 to 2019, a quasi-natural experimental design and a staged difference-in-differences model are used. This study draws several noteworthy conclusions: (1) The TMP program has proven effective in directly reducing carbon emissions in China. In comparison to non-pilot cities, the pilots have achieved a commendable 13.4 % reduction in carbon emission intensity and an 8.3 % decrease in total carbon emissions. (2) Notably, the program's impact is more pronounced in larger cities and in the western regions of the country. (3) TMP has a lasting effect on carbon emissions, persisting for one to five years after the pilot implementation. And (4) The TMP program affects emissions indirectly through ‘Avoid-Shift-Improve’ mechanisms, which include restrictions on car purchase/use, enhancements in public transport, investments in urban technology, and the adoption of new energy vehicles.</div></div>","PeriodicalId":47453,"journal":{"name":"Research in Transportation Business and Management","volume":"64 ","pages":"Article 101544"},"PeriodicalIF":4.4,"publicationDate":"2025-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145364810","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}
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