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

{"title":"Stochastic modeling and design of truck platooning strategies considering platoon dynamics","authors":"Rashika Gupta ,&nbsp;Devika Koonthalakadu Baby ,&nbsp;Debjit Roy ,&nbsp;Shankar C. Subramanian ,&nbsp;Sandip Chakrabarti","doi":"10.1016/j.tre.2026.104684","DOIUrl":"10.1016/j.tre.2026.104684","url":null,"abstract":"<div><div>Road transportation via trucks is a dominant mode for long-haul freight transport across countries. However, due to their significant dependence on fossil fuels, trucks are a large contributor to carbon emissions. Hence, new technology-driven solutions such as truck platoons are gaining momentum. While platoons promise to reduce fuel costs and emissions, they may increase transportation time due to additional coordination delays, such as the time required for platoon formation. In this research, we examine the performance trade-offs between platoon fuel savings and excess delay costs resulting from waiting for platoon formation among three platoon formation strategies: intermittent, continuous, and opportunistic. We develop a novel Closed Queuing Network model that captures the dynamics of platoons, as well as the stochasticity in truck travel times, and provides realistic estimates of platoon wait times and vehicle throughput. The platoon formation delays and size-dependent travel times are modeled using merging and load-dependent nodes, respectively, and analyzed through a continuous-time Markov chain. Our study provides key insights into the impact of increasing platoon size on performance measures, including system throughput and mean waiting time. With platooning, the network throughput capacity is reduced; however, fuel savings are realized. For a given network topology, we can identify an optimal platoon formation strategy that maximizes the throughput and fuel efficiency, while simultaneously minimizing vehicle waiting costs.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"208 ","pages":"Article 104684"},"PeriodicalIF":8.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146033369","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":"An integrated framework of vessel demand shifting and port capacity utilization for congestion mitigation","authors":"Haowen Lei ,&nbsp;Shuai Jia","doi":"10.1016/j.tre.2025.104660","DOIUrl":"10.1016/j.tre.2025.104660","url":null,"abstract":"<div><div>Port congestion remains a critical hurdle for global maritime logistics, particularly as opportunities for infrastructure expansion become increasingly limited. In this study, we introduce a unified optimization framework that coordinates vessel service demand with port capacity, empowering the mitigation of port congestion. The integrated framework comprises three key components: A demand shifting model that optimizes vessel arrival distributions over time; a descriptive queueing model that characterizes vessel arrival and service processes, enabling a holistic evaluation of congestion levels; and a resource management model that effectively allocates available port resources to vessels by leveraging a data-driven throughput envelope calibrated from port operational data. To address the computational challenges posed by the integration these models, we develop a bi-level iterative solution algorithm that iteratively enhances the coordination between demand-side and supply-side decisions, achieving a satisfactory performance with respect to tractability and scalability. Empirical validation is performed using a large-scale, real-world operational dataset from a major container port in Shanghai. Our algorithm proves highly scalable, solving large-scale instances 20–30 times faster than Gurobi and achieving near-optimal solutions (e.g., optimality gaps as low as 0.91 %). The framework delivers economic value with a substantial reduction of total system costs (ranging from 14.47 %-16.67 %) over a non-integrated baseline. The results highlight the practical value and generalizability of the unified approach for enhancing the efficiency and resilience of port systems.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"208 ","pages":"Article 104660"},"PeriodicalIF":8.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145940544","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":"With whom to ally? Alliance strategy for EV battery supplier considering echelon utilization and disassembly recycling","authors":"Zhangzhen Fang ,&nbsp;Yuhan Guo ,&nbsp;Gaoxiang Lou ,&nbsp;Zhixuan Lai ,&nbsp;Haicheng Ma ,&nbsp;Li Zhou","doi":"10.1016/j.tre.2025.104656","DOIUrl":"10.1016/j.tre.2025.104656","url":null,"abstract":"<div><div>The rapid expansion of the electric vehicle (EV) industry has heightened the need for sustainable and efficient closed-loop supply chains (CLSC) that can simultaneously improve economic returns and mitigate environmental impacts. To address this challenge, this study develops a game-theoretic model from the perspective of the power battery supplier and examines four inter-firm alliance modes: Non-alliance (N), supplier-manufacturer alliance (SM), supplier-recycler alliance (SR), and comprehensive alliance (SMR). The results reveal that (1) in the forward supply chain, suppliers under the SM and SMR modes consistently achieve higher battery capacity and EV sales. In the reverse supply chain, suppliers in alliance modes (SM, SR, SMR) are able to pay lower recycling prices while securing higher recycling quantities. (2) When recycling competition is weak, alliance with the manufacturer improves economic performance, whereas that with the recycler enhances environmental outcomes; however, the two benefits cannot be achieved simultaneously. By contrast, under intense recycling competition, forming a comprehensive alliance allows suppliers to improve both environmental and economic performance. (3) When extending the analysis to include suppliers’ investment in echelon utilization technology innovation, increased recycling competition intensity leads to a decline in the supplier’s echelon utilization performance, thereby amplifying the advantage of the comprehensive alliance.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"208 ","pages":"Article 104656"},"PeriodicalIF":8.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145956534","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":"Integrating six feeder modes with the metro system: Insights from on-demand and pooled services","authors":"Linchuan Yang","doi":"10.1016/j.tre.2025.104659","DOIUrl":"10.1016/j.tre.2025.104659","url":null,"abstract":"<div><div>Understanding travel patterns of feeder modes for metro systems is crucial for addressing first-mile challenges and advancing sustainable urban mobility. Existing research predominantly examines traditional transit modes (e.g., buses) and emerging on-demand transport services (e.g., ride-hailing) separately, with limited comparative analysis between the two. Furthermore, most studies do not distinguish between solo trips and pooled trips, leading to potential misestimation of the impact of each trip type. Drawing on multi-source data from Shenzhen, this study analyzes the access patterns of six feeder modes (i.e., solo ride-hailing, ride-pooling, solo taxis, taxi-pooling, buses, and free-floating bike-sharing) and their integration with the metro system. We employ the eXtreme Gradient Boosting (XGBoost) and SHapley Additive exPlanations (SHAP) models to evaluate the impacts of these feeder modes on metro ridership, and analyze how on-demand transport services fill gaps in the metro-bus network based on the coverage extension ratio and travel time ratio. Our findings reveal: (1) Solo taxis represent the fastest feeder mode; (2) As access distance increases, the cost advantage of ride-hailing diminishes, while the speed advantage of taxis becomes more pronounced; (3) Ride-pooling contributes to increased metro usage in non-central areas; (4) On-demand transport services can effectively address gaps in the metro-bus network. This study provides policy implications for optimizing transportation resource allocation and enhancing first-mile connectivity for metro systems.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"208 ","pages":"Article 104659"},"PeriodicalIF":8.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146014595","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":"Inducing information provision on hybrid fresh produce e-commerce platforms via supplier freshness-keeping effort","authors":"Lunhai Liang ,&nbsp;Fei Ye ,&nbsp;T.C. Edwin Cheng","doi":"10.1016/j.tre.2026.104711","DOIUrl":"10.1016/j.tre.2026.104711","url":null,"abstract":"<div><div>This paper investigates the interplay between a platform’s information sharing decisions and its business mode selections and demonstrates how suppliers’ freshness-keeping efforts affect this interplay in a fresh produce supply chain with a supplier and a platform. We develop a theoretical model with stochastic and freshness-dependent demand, which the supplier can maintain product freshness through freshness-keeping efforts. The platform may share private demand information to support the supplier’s freshness-keeping decision and operates three business modes, namely the reselling mode (R), agency mode (A), and hybrid mode (H). Our findings show that under Mode A, the platform always voluntarily shares information, achieving a win–win outcome for both the platform and the supplier. Under Modes R and H, although information sharing drives up the wholesale price, the platform still prefers to share information when the supplier’s freshness-keeping efficiency is sufficiently high. Specifically, under Mode H, a dual-threshold information-sharing policy emerges: even when freshness-keeping efficiency is moderate, the platform shares information only when the commission rate is moderate. Furthermore, we find that information sharing motivates the supplier to enhance freshness-keeping efforts, which in turn improves product freshness. This mechanism termed the freshness-keeping improvement effect of information sharing functions as a critical incentive for the platform to voluntarily share demand information.<!--> <!-->Additionally, adopting Mode H may increase the wholesale price and exacerbate the double-marginalization problem when the commission rate is sufficiently low. Finally, we find that the platform and the supplier can reach consensus on the HS strategy (i.e., Mode H with information sharing) and subsequently achieve a win–win outcome only when the commission rate is moderate. However, information sharing may hinder consensus on adopting Mode H and narrow the win–win region.​.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"208 ","pages":"Article 104711"},"PeriodicalIF":8.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146071724","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":"Balancing service quality and riders’ welfare in on-demand delivery order dispatching: an integrated rolling horizon and differentiated incentive approach","authors":"Fuyu Cao ,&nbsp;Yichen Qin ,&nbsp;Hongtao Hu ,&nbsp;Xuting Sun ,&nbsp;Kam K.H. Ng","doi":"10.1016/j.tre.2026.104685","DOIUrl":"10.1016/j.tre.2026.104685","url":null,"abstract":"<div><div>As on-demand food delivery plays an important role in daily service, it also poses significant challenges in developing real-time optimization solutions. Overwhelming customer orders require real-time rider dispatch and route scheduling dynamically, while meal preparation delays disrupt the scheduled routing plan of riders. The resulting delivery lateness incurs penalties to riders. To balance delivery service quality and riders’ welfare, this paper proposes an order exchange mechanism which enables riders to return the delayed orders back to the platform. The platform then identifies potential riders willing to undertake the returned orders with differentiated incentives. Four mixed integer linear programming (MILP) models are formulated to capture the sequential interactive decisions of the platform and riders. A dynamic order returning and dispatching method is designed and embedded with the rolling horizon approach, managing both the returned orders and the newly arriving orders adaptively. Meanwhile, aimed at balancing riders’ individual welfare, we introduce an equity metric and establish a bi-objective order dispatching model, subsequently employing the <em>ε</em>-constraint approach with a linearization technique. A tailored Artificial Bee Colony (ABC) algorithm solves instances based on a new town in Shanghai Megacity, China. Numerical experiments demonstrate that the order exchange mechanism enhances scheduling flexibility and ensures welfare equity. Interestingly, incorporating equity considerations reveals that generous pricing strategies paradoxically improve the overall system efficiency and ultimately reduce the total operational costs. Policy recommendations based on these findings are provided for on-demand delivery service platforms to strategically manage their riders and delivery orders.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"208 ","pages":"Article 104685"},"PeriodicalIF":8.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146000916","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":"Joint optimization of flood water routing and congestion-aware evacuation scheduling","authors":"Sina Bahrami ,&nbsp;Mehdi Nourinejad ,&nbsp;Matthew J. Roorda ,&nbsp;Yafeng Yin","doi":"10.1016/j.tre.2025.104645","DOIUrl":"10.1016/j.tre.2025.104645","url":null,"abstract":"<div><div>Urban flood emergencies pose significant risks to human safety and infrastructure operability, particularly in smart cities with interdependent systems. This study proposes an integrated optimization model for coordinating water and transportation networks during flood evacuations. The model simultaneously determines optimal reservoir discharge rates and dynamic vehicular evacuation schedules to maximize the number of evacuees within the limited warning time. Water flow is modeled using the Muskingum-Cunge flood-routing method to simulate flood propagation through a river-reservoir system, while traffic flow is captured via the Cell Transmission Model, which accounts for congestion dynamics and road capacities. The problem is formulated as a nonlinear program and solved through a linear relaxation using generalized Benders decomposition. A case study of the Town of High River, Canada, illustrates the model’s practical utility. Results show that the integrated strategy extends warning times, reduces congestion, and lowers the number of individuals exposed to flood risks compared to uncoordinated approaches. By enabling real-time, infrastructure-aware evacuation planning, the proposed framework offers a scalable decision-support tool for emergency managers. This work contributes to the growing body of research on the management of city infrastructures under disruption and supports the development of resilient and coordinated evacuation strategies in smart urban environments.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"208 ","pages":"Article 104645"},"PeriodicalIF":8.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145886032","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":"Optimizing driver’s discount order acceptance strategies: A policy-improved deep deterministic policy gradient framework","authors":"Hanwen Dai ,&nbsp;Chang Gao ,&nbsp;Fang He ,&nbsp;Congyuan Ji ,&nbsp;Yanni Yang","doi":"10.1016/j.tre.2025.104628","DOIUrl":"10.1016/j.tre.2025.104628","url":null,"abstract":"<div><div>The rapid expansion of platform integration has emerged as an effective solution to mitigate market fragmentation by consolidating multiple ride-hailing platforms into a single application. To address heterogeneous passenger preferences, third-party integrators provide Discount Express service delivered by express drivers at lower trip fares. For the individual platform, encouraging broader participation of drivers in Discount Express services has the potential to expand the accessible demand pool and improve matching efficiency, but often at the cost of reduced profit margins. This study aims to dynamically manage drivers’ acceptance of Discount Express from the perspective of an individual platform, incorporating the spatiotemporal demand-supply patterns. The lack of historical data under the new business model necessitates online learning. However, early-stage exploration through trial and error can be costly in practice, highlighting the need for reliable early-stage performance in real-world deployment. To address these challenges, this study formulates the decision regarding the proportion of drivers accepting discount orders as a continuous control task. In response to the high stochasticity, the opaque matching mechanisms employed by third-party integrator, and the limited availability of historical data, we propose an innovative policy-improved deep deterministic policy gradient (pi-DDPG) framework. The proposed framework incorporates a refiner module to boost policy performance during the early training phase, leverages a convolutional long short-term memory network to effectively capture complex spatiotemporal patterns, and adopts a prioritized experience replay mechanism to enhance learning efficiency. A customized simulator based on a real-world dataset is developed to validate the effectiveness of the proposed pi-DDPG. Numerical experiments demonstrate that pi-DDPG achieves superior learning efficiency and significantly reduces early-stage training losses, enhancing its applicability to practical ride-hailing scenarios.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"208 ","pages":"Article 104628"},"PeriodicalIF":8.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145940519","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":"Too big to stay? The restructuring of Italy’s flag carrier and its consequences on airline pricing","authors":"Angela S. Bergantino ,&nbsp;Mattia Borsati ,&nbsp;Xavier Fageda ,&nbsp;Mario Intini","doi":"10.1016/j.tre.2026.104695","DOIUrl":"10.1016/j.tre.2026.104695","url":null,"abstract":"<div><div>Airline financial distress is a global phenomenon, yet its market implications remain underexplored. A notable case is the restructuring of Italy’s flag carrier, <em>Alitalia</em>, which went bankrupt and ceased operations on October 14, 2021. The following day, <em>ITA Airways</em> took over, inheriting parts of <em>Alitalia</em>’s network while operating under a distinct governance and management structure. This article examines how this transition has affected Italy’s aviation market and fare dynamics. By estimating price regressions at the route level using monthly fare data from 2017 to 2023, and by accounting for the non-random selection of routes retained by the airline after the reorganization, we find that the restructuring led to lower fares in the domestic market but higher prices on international routes, particularly for long-haul flights. In response to competitive pressures, <em>ITA</em> has adopted a more complex pricing strategy: functioning as a low-cost carrier domestically while raising fares on long-haul routes.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"208 ","pages":"Article 104695"},"PeriodicalIF":8.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146033368","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":"Linear carrot-and-stick: Compensation design with ordering delegation and demand updating","authors":"Yugang Yu ,&nbsp;Xiaoting Jiao ,&nbsp;Libo Sun","doi":"10.1016/j.tre.2026.104689","DOIUrl":"10.1016/j.tre.2026.104689","url":null,"abstract":"<div><div>Delegating ordering to the salesforce leverages local market knowledge but complicates incentive alignment. Motivated by data from a major Amazon apparel seller, we study a Linear Carrot-and-Stick (LCS) scheme that couples a sales commission (“carrot”) with a leftover inventory penalty (“stick”). Using weekly SKU-level transaction data from June 2017 to May 2019, we observe that the adoption of LCS decreased the firm’s total shipments and sales relative to the prior Linear Pure-Commission Scheme (LPS). To interpret these patterns and offer design guidance, we develop a two-period principal-agent model in which the salesperson updates demand forecasts based on realized outcomes and also chooses the effort and places orders. We show that the optimal commission reflects the salesperson’s ability to convert effort into sales, while the penalty ratio balances overstocking liabilities with understocking opportunity costs, akin to the critical ratio in the newsvendor problem. To ensure that the salesforce utility remains competitive despite inventory penalties, we examine a utility protection mechanism, finding that higher values for both the components, carrot and stick, are essential for retaining a valuable person who faces attractive employment alternatives. A numerical study of the partner’s top-selling SKUs indicates that LCS can deliver a win-win outcome, improving both firm profitability and salesperson motivation compared to LPS. We further extend the analysis to information asymmetry, target-based demand updating, Bayesian demand updating, and a two-product setting, all of which widely confirm the robustness of our findings.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"208 ","pages":"Article 104689"},"PeriodicalIF":8.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146014564","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}