Transportation Research Part E-Logistics and Transportation Review最新文献

{"title":"Application of blockchain in the secondary market with counterfeiting","authors":"Hubert Pun ,&nbsp;Jayashankar M. Swaminathan ,&nbsp;Jing Jenny Chen","doi":"10.1016/j.tre.2025.104079","DOIUrl":"10.1016/j.tre.2025.104079","url":null,"abstract":"<div><div>It is not uncommon for customers who intend to buy a used product in the secondary market to end up with a counterfeit because they have imperfect information about product authenticity. Blockchain is being piloted as a cutting-edge solution to this challenge. We use a two-period game to study the impact of utilizing blockchain to combat counterfeit products in the secondary market. We show that, even when the cost of implementing blockchain is negligible, the manufacturer can be better off incurring reputation damage than adopting blockchain. Further, the used goods reseller can be worse off from blockchain, even though that seller is not responsible for the implementation cost and benefits from blockchain’s signaling capability. We also demonstrate that the counterfeiter can benefit as a result of blockchain. When the quality of a fake product is sufficiently low, blockchain lowers consumer surplus. The winning situation of blockchain between the manufacturer, reseller, and customers is achieved only when the fake product is of intermediate quality. Blockchain can be powerful in situations when used products have a low perceived quality; otherwise, blockchain may not be ideal.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"197 ","pages":"Article 104079"},"PeriodicalIF":8.3,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143641806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dynamic volunteer assignment: Integrating skill diversity, task variability and volunteer preferences","authors":"Qingchun Meng,&nbsp;Bo Feng,&nbsp;Guodong Yu","doi":"10.1016/j.tre.2025.104068","DOIUrl":"10.1016/j.tre.2025.104068","url":null,"abstract":"<div><div>Non-profit organizations rely critically on volunteers for effective disaster response. Managing diverse skills and varying participation levels of volunteers poses significant challenges, especially under the fluctuating demands and the uncertainty of task completion typical of disaster scenarios. This study introduces a model that dynamically optimizes volunteer allocation, enhancing disaster response efficiency and volunteer engagement. Integrating a multi-task queuing model with a dynamic priority policy within a Markov Decision Process framework, the model aims to minimize costs associated with task backlogs and volunteer services. Utilizing deep neural networks and policy iteration, the model handles large-scale environments and reduces costs through volunteer allocation. This adaptive approach responds to changing task demands, focusing on minimizing the long-term operational costs of volunteer management. Experimental results demonstrate that this dynamic allocation significantly reduces disaster response costs and decreases volunteer participation expenses without requiring additional resources, underscoring the importance for non-profit organizations to strategically manage their volunteer labor, taking into account the attributes of volunteers.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"197 ","pages":"Article 104068"},"PeriodicalIF":8.3,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143636770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Conflicts and cooperation: New product development or co-development in a supply chain","authors":"Rui Yang ,&nbsp;Lin Feng ,&nbsp;Jianxiong Zhang ,&nbsp;Zhuzhu Song","doi":"10.1016/j.tre.2025.104069","DOIUrl":"10.1016/j.tre.2025.104069","url":null,"abstract":"<div><div>The collaborations between manufacturers and retailers through co-development enhance the efficiency of new product development (NPD). We consider the practical concern that the matching degree between new products and consumers remains uncertain at the beginning of NPD and becomes manufacturers’ private information after NPD is completed, which significantly influences the pricing and quality strategies of manufacturers, consequently impacts the co-development investment of retailers. In this paper, by constructing a game-theoretic model involving a manufacturer and a retailer, we examine two pricing modes for the manufacturer: preannounced pricing which is made at the beginning of NPD and responsive pricing which is made after completing NPD. Within these pricing frameworks, we study the manufacturer’s pricing and quality strategies, all while examining how retailer’s engagement in co-development impacts the information structure and the manufacturer’s decisions. Surprisingly, we find that co-development enables the manufacturer to always embrace the preannounced pricing strategy, even if it places the manufacturer at an information disadvantage. In addition, in the absence of co-development, the responsive pricing is not always beneficial for the manufacturer, but it always induces a higher product quality partially due to the strategy distortion in the signaling game under asymmetric information. Finally, co-development will hurt the manufacturer and the retailer when the uncertainty level of the matching degree information is relatively small, while it paves the way for a mutually beneficial “win-win” scenario for both parties when the uncertainty level is relatively large.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"197 ","pages":"Article 104069"},"PeriodicalIF":8.3,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143636771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cooperative game based heterogeneous tasks planning for UAV swarms in edge environments","authors":"Jiajing Gao,&nbsp;Jianyi Zhao,&nbsp;Zheng Zhao,&nbsp;Junkai Cheng,&nbsp;Lu Zhen","doi":"10.1016/j.tre.2025.104065","DOIUrl":"10.1016/j.tre.2025.104065","url":null,"abstract":"<div><div>We investigate the cooperative planning of heterogeneous tasks for UAV swarms in edge environments based on cooperative game theory. To solve this problem, we propose a solution method based on column generation and iteration. A hybrid centralized and distributed solution framework is designed to enhance the efficiency of the overall task allocation system. At the early stage of disaster response, a centralized task allocation method is adopted, combined with a mixed integer planning model for task allocation, and a column generation-based approach is designed to solve the model. As the rescue work advances, a distributed task reallocation approach is adopted by considering the cooperation game, and the Shapley value is used to obtain the revenue allocation when the UAV swarms cooperate. The two phases collaborate with each other and continuously update the task allocation scheme through iterative solving. We design a solution method based on column generation and iteration to obtain task allocation scheme. We verify the advantages of our method in terms of computation time and solution quality through numerical experiments. We also validate the benefits of UAV swarm cooperation. We also examine the effect of variations in the scale and parameters of the instances on the total revenue.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"197 ","pages":"Article 104065"},"PeriodicalIF":8.3,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143641805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating consumer shopping, delivery demands, and last-mile preferences: An integrated MDCEV-HCM approach","authors":"Ali Riahi Samani ,&nbsp;Ahmadreza Talebian ,&nbsp;Sabyasachee Mishra ,&nbsp;Mihalis Golias","doi":"10.1016/j.tre.2025.104067","DOIUrl":"10.1016/j.tre.2025.104067","url":null,"abstract":"<div><div>The effective implementation of innovative last-mile delivery approaches depends on understanding two key elements: (i) consumer demand (who places an online order, where, and how) and (ii) consumers’ delivery needs and preferences. This study, first, proposes a disaggregated online demand modeling framework utilizing Multiple Discrete-Continuous Extreme Values (MDCEV) to estimate consumer shopping behavior and households’ home delivery and pick-up demands across different commodity types. Second, a Hybrid Choice Model (HCM) is introduced to assess the competitiveness of three innovative last-mile delivery modes, (i) Autonomous Delivery Robots, (ii) Crowdsourced Delivery, and (iii)Automated Parcel Lockers, considering consumer attitudes toward these technologies. Subsequently, we conduct elasticity analysis for cost and commodity type, revealing consumers’ Willingness-to-Pay for various last-mile delivery methods. The proposed framework is applied to a dataset acquired through an online survey distributed among residents of the State of Tennessee, USA. Analyzing results show that consumers can be categorized into five latent segments according to their shopping preferences: traditional shoppers, benefit seekers, e-shopping enthusiasts, omnichannel consumers, and Indifferent customers. Results indicate that businesses should focus on delivery time for e-shopping enthusiasts and omnichannel consumers, while accessibility to APLs may encourage traditional shoppers and benefits seekers to transition to online shopping. Also, latent variable analysis shows that while perceived risk hinders adoption, perceived benefits and ease of use drive acceptance. The findings of this study highlight the importance of a tailored approach to adopting innovative delivery solutions, ensuring a balance between cost, accessibility, and consumer priorities to meet evolving demands.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"197 ","pages":"Article 104067"},"PeriodicalIF":8.3,"publicationDate":"2025-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143629590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data-driven robust strategic sourcing considering supply-side competition: Insights into blockchain adoption for coordination","authors":"Samuel Yousefi,&nbsp;Mohammad Reza Khodoomi,&nbsp;Babak Mohamadpour Tosarkani","doi":"10.1016/j.tre.2025.103977","DOIUrl":"10.1016/j.tre.2025.103977","url":null,"abstract":"<div><div>Given the increasing vulnerability of global supply chains (SCs) to disruptions, improving resilience through strategic sourcing is crucial for maintaining continuity and adaptability in dynamic markets. Integrating blockchain technology (BT) can further support these efforts by ensuring data integrity, transparency, and real-time visibility across SCs. This study develops a data-driven robust multi-objective programming (DDRMOP) model to explore the role of BT in designing sourcing strategies and creating effective partnerships in the face of uncertainties. The DDRMOP employs a data-driven robust optimization approach utilizing principal component analysis and robust kernel density estimation to formulate uncertainty sets for market demand. The model aims to minimize SC coordination costs, defective rates, and delivery delays while enhancing sourcing efficiency by selecting the most sustainable and BT-friendly suppliers. A Nash game-enabled data envelopment analysis is incorporated into this model to investigate sourcing efficiency under competitive dynamics and demand uncertainty simultaneously. This integration provides insights into how these dynamics influence the trade-off between cost efficiency and SC resilience. As the DDRMOP model includes three conflicting objectives, the augmented ε-constraint method is adopted to analyze the impact of each function on strategic sourcing across multiple products. The findings highlight the importance of BT and sustainability in forming reliable partnerships between the buyer and suppliers to enhance dynamic SC capabilities during disruptions. BT-friendly suppliers are preferred for their alignment with sustainability and information coordination goals. Although supply-side competition may increase coordination costs and operational complexities, it ultimately improves overall sourcing efficiency.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"197 ","pages":"Article 103977"},"PeriodicalIF":8.3,"publicationDate":"2025-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143636769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrigendum to “The interplay of blockchain and channel structure with consideration of cyber-security in a platform supply chain” [Transp. Res. E: Logist. Transp. Rev. 197 (2025) 104045]","authors":"Ling Li ,&nbsp;Shiyi Yan ,&nbsp;Shuxia Peng ,&nbsp;Pengwen Hou","doi":"10.1016/j.tre.2025.104085","DOIUrl":"10.1016/j.tre.2025.104085","url":null,"abstract":"","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"197 ","pages":"Article 104085"},"PeriodicalIF":8.3,"publicationDate":"2025-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143760476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling and analyzing ride-hailing market equilibrium considering drivers’ multi-homing choice behavior","authors":"Chang Gao ,&nbsp;Yineng Wang ,&nbsp;Fang He ,&nbsp;Xi Lin","doi":"10.1016/j.tre.2025.104055","DOIUrl":"10.1016/j.tre.2025.104055","url":null,"abstract":"<div><div>The success of ride-hailing services has engendered the rise of multiple service platforms in a competitive market. To this end, drivers are widely observed delivering services on more than one platform simultaneously to maximize their profits, referred to as the “multi-homing” behavior. Drivers’ spontaneous multi-homing has the potential to mitigate market fragmentation but may also intensify their competition for passengers across platforms. This study aims to address the impacts brought by multi-homing drivers on the stakeholders of ride-hailing services. We employ a game-theoretical framework to model the choice of freelance drivers on whether and how to multi-home, as well as the decision of passengers on which platform to attend in an asymmetric market with loyal drivers. On account of the multi-homing behavior, we specifically identify the effective supply of platforms dictating the matching efficiency behind the seeming blossom of supply. On this basis, we compare the equilibrated market under drivers’ multi-homing behavior with a monopoly market and another equilibrated market having drivers single-homing on one platform. Our finding suggests that compared to a monopoly, multi-homing alleviates the wild-goose chase (WGC) dilemma and benefits all stakeholders in supply shortages due to its weaker matching efficiency, resulting in a rational demand level and more available vehicles. In contrast to the benchmark where drivers single-home, multi-homing enhances overall system performance due to the enlarged pool of vacant vehicles for passengers. Specifically, it strengthens the supply advantage of dominant platforms in more balanced markets, while facilitating the expansion of weaker platforms in highly asymmetric markets with a moderate freelance fleet. Extensive numerical results derived from real-world datasets indicate that multi-homing becomes a viable strategy for freelance vehicles in markets with limited supply, and multi-homing contributes to the growth of less influential platforms in practice.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"197 ","pages":"Article 104055"},"PeriodicalIF":8.3,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143627569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Coopetitive Resilience: Integrating Cyber Threat Intelligence Platforms in Critical Supply Chains","authors":"Sobhan Arisian ,&nbsp;Kourosh Halat ,&nbsp;Ashkan Hafezalkotob ,&nbsp;Reenu Maskey","doi":"10.1016/j.tre.2025.104043","DOIUrl":"10.1016/j.tre.2025.104043","url":null,"abstract":"<div><div>This study proposes a novel contractual framework that integrates flexible cooperative procurement strategies within a Cyber Threat Intelligence Platform (CTIP) to address cyber-attack-induced disruptions in critical supply chains (CSCs). The framework examines the role of government in moderating CTIPs to facilitate information sharing, incentivize cybersecurity investments, and promote collaboration among competing CSCs. Our findings demonstrate the effectiveness of this approach in enhancing operational resilience while balancing profitability and economic welfare (EW). To validate these insights, we conduct a case study on cyber disruptions affecting Australia’s health and medical procurement sector. The results reveal that flexible minimum order quantity (MOQ) contracts provide greater EW benefits, particularly in high-risk environments, compared to fixed-quantity separate procurement models. Furthermore, this mechanism fosters <em>coopetitive resilience</em> by enabling CSCs to balance competition with cooperation, thereby strengthening their cyber readiness and collective ability to mitigate disruptions. Adjusting MOQ thresholds, government subsidies, and the level of cyber intelligence sharing may further enhance these benefits. Aligning CTIP regulations and targeted interventions with the distinct risk profiles of firms is crucial for optimizing outcomes in the face of cyber disruptions. This approach is particularly vital in critical sectors such as food, pharmaceuticals, and healthcare, where the timely availability of products is essential to safeguarding public safety and health.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"197 ","pages":"Article 104043"},"PeriodicalIF":8.3,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143627571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-Agent reinforcement learning framework for addressing Demand-Supply imbalance of Shared Autonomous Electric Vehicle","authors":"Chengqi Liu ,&nbsp;Zelin Wang ,&nbsp;Zhiyuan Liu ,&nbsp;Kai Huang","doi":"10.1016/j.tre.2025.104062","DOIUrl":"10.1016/j.tre.2025.104062","url":null,"abstract":"<div><div>A critical issue in the operation of one-way station-based Shared Autonomous Electric Vehicles (SAEVs) is addressing the supply–demand imbalance. Supply-side relocations can transfer vehicles from areas with excess supply to areas with higher demand, thereby satisfying more passenger needs and increasing operator profits. To tackle the limitations of current algorithms, which fail to effectively capture similar relocation actions through spatio-temporal relationships, this paper designs a zone-based Dynamic Clustering-Driven Multi-Agent Reinforcement Learning (DC-MARL) model. The approach uses dynamic clustering to pre-cluster historical states for each time step and classifies them in real-time during training and testing. A heterogeneous action space is designed, and an optimization method is employed to determine the specific vehicles for final relocation, mapping the actions to vehicle relocation. An Entity-Agent Reshaped algorithm based on Multi-Agent Deep Deterministic Policy Gradient (EAR-MADDPG) is proposed, along with treatments to enhance cooperation among agents. Experimental results on the Suzhou Industrial Park (SIP) network demonstrate that the proposed method achieves better performance with fewer relocations compared to rule-based relocation and RL-based methods. The proposed method increases profit by 11.80% over the threshold method and by 4.25% over the advanced static clustering method.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"197 ","pages":"Article 104062"},"PeriodicalIF":8.3,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143609993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}