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

{"title":"Delivery time reliability in on-demand food delivery: Heterogeneity from attribution effects","authors":"Bohao Ma ,&nbsp;Chee-Chong Teo ,&nbsp;Yiik Diew Wong ,&nbsp;Shanshan Sun","doi":"10.1016/j.tre.2025.104335","DOIUrl":"10.1016/j.tre.2025.104335","url":null,"abstract":"<div><div>The popularity of on-demand food delivery (ODFD) has been observed globally, in which platforms connect restaurants with consumers with digital infrastructure and crowdsourced riders. With fierce competition, it is imperative for practitioners to optimize decision-making models which heavily rely on insights into consumer behaviors. Time perception is considered a key determinant of consumers’ ODFD usage. Scarce attention is paid to consumers’ attitudes towards delivery time reliability. Therefore, with a stated choice experiment, this study aims to investigate and monetize consumers’ value of reliability (VOR) by adopting the scheduling-based approach. The study explicitly models random heterogeneity using a mixed logit specification, and systematic heterogeneity with an integrated choice and latent variable model. Specifically, consumers’ attributional attitudes of service outcomes pertaining to different service parties, namely delivery riders, restaurants, and platforms, are incorporated in heterogeneity modeling. The results show that cost and expected delivery time negatively affect ODFD usage utility, while the negative effects of long expected times are significantly weaker for orders placed during peak hours or from distant restaurants. On average, consumers hold positive attitudes toward early delivery, while the attitudes are highly heterogeneous. Moreover, late delivery negatively affects utility of ODFD usage, and the effects are also weaker for orders from distant restaurants. Regarding the attributional effects, the attribution of late delivery to restaurants would intensify the dissatisfaction, while the converse is true for attribution to platforms. In contrast, attribution to delivery riders has no significant effects on consumers’ dissatisfaction. In conclusion, this study contributes to the theoretical development of both reliability perceptions and attribution theory. Besides, empirical observations can effectively support the development of decision support systems in ODFD, allowing practitioners to improve ODFD services with more approaches. The findings would support the integrative optimization of service promise and dispatch algorithms, and context-aware optimization. Furthermore, ODFD practitioners can implement effective psychosocial intervention to manage consumer satisfaction with the findings on attributional effects as well.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"202 ","pages":"Article 104335"},"PeriodicalIF":8.3,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144678861","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":"The 15-minute city concept: An operations research perspective and a research agenda","authors":"Okan Arslan ,&nbsp;Gilbert Laporte","doi":"10.1016/j.tre.2025.104287","DOIUrl":"10.1016/j.tre.2025.104287","url":null,"abstract":"<div><div>The 15-minute city is an urban planning model where residents can access essential services within a 15-minute walk or bike ride. The idea is centered on reconsidering urban planning paradigms through the lens of proximity and accessibility. This paper explores how the concept can be operationalized using tools from operations research. While much of the existing literature has focused on defining and measuring accessibility in proximity-based cities, this work shifts the emphasis toward operational strategies and optimization-based methodologies to implement and manage such urban environments. We survey the relevant operations research literature, identify thematic overlaps with urban planning goals, and propose a research agenda that includes facility location, mobility systems, shared transportation services, and integrated governance models.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"202 ","pages":"Article 104287"},"PeriodicalIF":8.3,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144678863","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":"Environmental and welfare effects of airline fuel tankering strategy","authors":"Chunan Wang ,&nbsp;Shuai Yue ,&nbsp;Weijun Liao ,&nbsp;Qing Ji ,&nbsp;Anming Zhang","doi":"10.1016/j.tre.2025.104337","DOIUrl":"10.1016/j.tre.2025.104337","url":null,"abstract":"<div><div>Fuel tankering refers to loading an aircraft with extra fuel—beyond immediate flight needs—to avoid costly refueling at the destination, taking advantage of inter-airport fuel price differences. This study constructs a game-theoretic model to examine strategic adoption patterns of fuel tankering under competitive market conditions and investigate the associated environmental and welfare effects. We find that, first, the fuel price difference alone does not necessarily induce fuel tankering adoption; rather, the extra fuel consumption and strategic interaction between airlines are also essential factors in the airlines’ decision. Second, a prisoner’s dilemma may emerge where airlines use fuel tankering in equilibrium to save costs, but they end up with lower profits compared to the case where no one adopts the fuel tankering strategy. Third, the use of fuel tankering always results in higher equilibrium consumer surplus, but at the cost of an adverse environmental effect. It may also lead to reduced social welfare. In addition, welfare analysis shows the airlines’ inefficient bias toward fuel tankering. Finally, policy implications are discussed.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"202 ","pages":"Article 104337"},"PeriodicalIF":8.3,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144678860","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":"Enhancing urban rail transit resilience: Strategic bus resource allocation","authors":"Yunqiao Xiang ,&nbsp;Yun Wang ,&nbsp;Xuedong Yan ,&nbsp;Haonan Guo ,&nbsp;Yu Zhou","doi":"10.1016/j.tre.2025.104327","DOIUrl":"10.1016/j.tre.2025.104327","url":null,"abstract":"<div><div>Urban rail transit (URT) systems are integral to urban mobility but are susceptible to disruptions that can substantially impact service continuity and passenger convenience. The increasing incidents of URT disruptions necessitate effective strategies to ensure robust and resilient transit operations. Temporarily requisition regular buses to serve as bridging services has become a common strategy to mitigate the adverse effects of URT service disruptions. This study investigates a novel macro-level integration planning problem of regular buses, aiming to optimize both regular bus resource allocation (including depot location, vehicle fleet and vehicle-to-line assignment) and bus bridging services in response to URT disruptions (including the mapping relationships between regular bus depots, requisitioning buses and URT stations), with the goal of minimize operational disruptions and enhance service reliability. A bi-objective integer programming model is developed to integrate regular bus service planning with bus bridging services in response to URT disruptions, minimizing the total deadheading time and reducing the number of unserved passengers. An augmented ε-constraint method, combined with lexicographic optimization and a utopian point, is proposed to generate balanced Pareto optimal solutions. The model is tested through case studies involving both small-scale (part of the Nanchang Metro network) and large-scale (entire Nanchang Metro network, Nanjing Metro network and Chengdu Metro network) disruptions, based on real-world data. Results demonstrate that our approach can produce high-quality solutions that significantly enhance the operational efficiency and responsiveness of bus services to URT disruptions. These strategies ensure smooth operation of regular bus services, mitigate the impacts of URT disruptions, and promote cost-effective utilization of bus resources.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"202 ","pages":"Article 104327"},"PeriodicalIF":8.3,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144678862","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":"Inventory routing problem of automotive parts considering time-varying demands: A machine learning enhanced branch-and-price approach","authors":"Yu Wang ,&nbsp;Renrong Zheng ,&nbsp;Chengji Liang ,&nbsp;Jian Shi","doi":"10.1016/j.tre.2025.104297","DOIUrl":"10.1016/j.tre.2025.104297","url":null,"abstract":"<div><div>With the rise of mass customization and smart manufacturing, the automotive industry is rapidly transitioning to improve responsiveness, manage highly diversified customer orders, and reduce inbound logistics costs. To address this challenge, this paper proposes a new variant of the multi-period inventory routing problem, which focuses on coordinating discrete, time-varying demands for auto parts on the assembly line with predetermined packages at suppliers over a finite short-term time horizon (e.g., on an hourly basis). The objective is to minimize the total transportation and inventory cost by making aperiodic decisions on collection quantities and traveling routes simultaneously for an inbound warehouse near the assembly plant. An integer programming (IP) formulation with time-indexed variables is tailored for the problem to analyze the feasibility conditions. Then, a reformulation is designed to make the problem more tractable, based on which a novel machine learning enhanced branch-and-price algorithm (BPL) is proposed, where prediction-based cuts are embedded to accelerate the pricing procedure. Experiments on real-scale instances demonstrate that the algorithm consistently achieves near-optimal solutions, with a gap of 4.42% on average from the best-found lower bound, and reduces computation time by over 90% compared to directly solving the IP model by CPLEX. The proposed learning technique is computationally efficient, capable of shortening the total calculation time by an average of 13%. This work facilitates timely decision-making and offers new insights into multi-period inventory routing for inbound logistics.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"202 ","pages":"Article 104297"},"PeriodicalIF":8.3,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144670407","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":"Demand uncertainty aware curbside space allocation planning in shared-use transportation networks","authors":"Shanjeeda Akter,&nbsp;HM Abdul Aziz","doi":"10.1016/j.tre.2025.104245","DOIUrl":"10.1016/j.tre.2025.104245","url":null,"abstract":"<div><div>Efficient management of curbside space is gaining more attention as cities confront increasing traffic, curbside requirements, and mobility patterns. Given their increasing significance in meeting diverse shared-use mobility requirements, the absence of optimal planning on curbside areas can lead to networkwide negative impacts. This study examines demand uncertainty for planning at several temporal resolutions. Our developed approach identifies the optimal curbside space allocation planning strategies to enhance passenger-level services, considering the <em>Curb Productivity Index</em> and the uncertain arrival distribution of Shared-Use Mobility (SUM) service units throughout the curbside networks. We integrated a core optimization module to adjust capacity over various time scales and find the optimal allocation plan. Further, we integrated a sample-based heuristic to allow decision-making at multiple levels of granularity (allocating space hourly versus adjustments occurring every five minutes due to interconnected infrastructure technologies or analogous factors). The proposed solution methodology is demonstrated for a network of curbsides with known demand distribution parameters (truncated Normal with mean and standard deviation for hourly demand). The results suggest that the allocation plans are highly sensitive to the decision interval (minutes vs. one-hour), and the coarse-resolution decision-making may overestimate the performance of a curbside allocation plan, underscoring the need for fine-resolution allocation plans in cities.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"202 ","pages":"Article 104245"},"PeriodicalIF":8.3,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144670430","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":"A data-driven approach for spatio-temporal causal analysis in large-scale urban traffic networks","authors":"Pingping Dong ,&nbsp;Xiaoning Zhang ,&nbsp;Xiaoge Zhang","doi":"10.1016/j.tre.2025.104244","DOIUrl":"10.1016/j.tre.2025.104244","url":null,"abstract":"<div><div>Understanding causal relationships between traffic states throughout the system is of great significance for enhancing traffic management and optimization in urban traffic networks. Unfortunately, few studies in the literature have systematically analyzed causal structure characterizing the evolution of traffic states over time and gauged the importance of traffic nodes from a causal perspective, particularly in the context of large-scale traffic networks. Moreover, the dynamic nature of traffic patterns necessitates a robust method to reliably discover causal relationships, which are often overlooked in existing studies. To address these issues, we propose a Spatio-Temporal Causal Structure Learning and Analysis (STCSLA) framework for analyzing large-scale urban traffic networks at a mesoscopic level from a causal lens. The proposed framework comprises three main components: decomposition of spatio-temporal traffic data into localized traffic subprocesses; a Bayesian Information Criterion-guided spatio-temporal causal structure learning combined with temporal-dependencies preserving sampling for deriving reliable causal graph to uncover time-lagged and contemporaneous causal effects; establishing several causality-oriented indicators to identify causally critical nodes, mediator nodes, and bottleneck nodes in traffic networks. Experimental results on both a synthetic dataset and the real-world Hong Kong traffic dataset demonstrate that the proposed STCSLA framework accurately uncovers time-varying causal relationships and identifies key nodes that play various causal roles in influencing traffic dynamics. These findings underscore the potential of the proposed framework to improve traffic management and provide a comprehensive causality-driven approach for analyzing urban traffic networks.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"202 ","pages":"Article 104244"},"PeriodicalIF":8.3,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144670428","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":"Competitive strategies in digital service capability: Self-Development vs. Cooperation","authors":"Tao Zhou ,&nbsp;Kai Li ,&nbsp;Bohai Liu ,&nbsp;Fulong Xie ,&nbsp;Liping Xu ,&nbsp;Han Zhang","doi":"10.1016/j.tre.2025.104291","DOIUrl":"10.1016/j.tre.2025.104291","url":null,"abstract":"<div><div>We examine various competition modes arising from the deployment of the digital service capabilities by two competing digital companies in smart product service systems, and analyze the effects of digital service value-addition, the alignment between smart products and digital services on the operations of rival parties. We construct game-theoretic competition models to derive the optimal deployment strategy for digital companies’ digital service capabilities, as well as to determine the optimal digital service level and pricing strategy. According to the sub-game perfect equilibrium outcomes derived from a specific competition mode, our findings uncover that even if a party’s digital service capability is weaker, its digital company still possesses the potential to outperform its rival in terms of profitability. Additionally, an increase in value-addition offered by digital services can undermine digital companies’ profitability. Likewise, the heightened alignment between smart products and digital services can be detrimental to digital companies. Furthermore, our analysis unveils that when the digital service capabilities of both competitors are strong, one of the digital companies will deviate from the symmetrical digital service capability deployment strategy, resulting in an asymmetrical equilibrium in which one company invests internally to develop a digital service capability, while the other partners with an external provider. On the contrary, when the digital service capabilities are weak, both competing digital companies opt to invest internally to deploy the digital service capability. However, this symmetrical equilibrium strategy ultimately places both digital companies in a prisoner’s dilemma.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"202 ","pages":"Article 104291"},"PeriodicalIF":8.3,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144670429","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":"Platform-empowered collaboration delivery model for express companies and rural passenger transport operators in rural areas","authors":"Weizhen Rao,&nbsp;Xiaohe Miao,&nbsp;Peng Liu,&nbsp;Lu Liu","doi":"10.1016/j.tre.2025.104311","DOIUrl":"10.1016/j.tre.2025.104311","url":null,"abstract":"<div><div>The rapid surge in e-commerce parcel volume has intensified demands for cost-effective and high-quality express delivery services in rural areas. This study proposes a platform-enabled collaborative delivery model that integrates express companies and rural passenger transport operators to improve last-mile logistics. Our goal is to facilitate efficient collaboration among stakeholders through platform-supported route planning and cost-sharing, with cost savings quickly estimated for decision-making. To assess the benefits of shared transport resources, we adopt a Shapley value-based cooperative game approach to determine cost allocation. This requires solving mixed-integer programming models for all possible alliance structures to compute characteristic functions. A mixed-integer linear programming model is formulated to address the multi-owner collaborative delivery vehicle routing problem with combined passenger and freight transport (MOCDVRP-CPFT), which quantifies delivery costs for each alliance configuration. A tailored solution framework is developed, incorporating batch processing, customer clustering, and an adaptive large neighbourhood search (ALNS) algorithm to generate high-quality solutions across all alliances. Six representative case studies in eastern, central, and western China using real-world data confirm the effectiveness of the proposed model, with the most significant savings observed in the western region. Based on the results, we offer region-specific policy suggestions to facilitate the implementation of CPFT in varying rural contexts. This study highlights the potential of digitally enabled, short-term collaborative alliances as a practical approach to improving rural logistics coordination and delivery efficiency.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"202 ","pages":"Article 104311"},"PeriodicalIF":8.3,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144670427","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":"Simultaneous estimation of induced, diverted, and ex-post demand for railway passengers: an interpretable machine learning framework based on constrained computational graphs","authors":"Xin Wu ,&nbsp;Xinyu Wang ,&nbsp;Taehooie Kim ,&nbsp;Khaled Saleh ,&nbsp;Huiling Fu ,&nbsp;Chenfeng Xiong","doi":"10.1016/j.tre.2025.104283","DOIUrl":"10.1016/j.tre.2025.104283","url":null,"abstract":"<div><div>Passenger flow on train lines is driven by how travelers respond to service offerings and constraints within the railway system, shaped primarily by three factors: <strong>Diverted demand</strong> refers to a shift in travelers’ choices toward different train lines, quantified by analyzing changes in the probability of selecting a particular train line within a given line plan. <strong>Induced demand</strong> arises when improvements in service quality led to an increase in passenger demand within a railway system. <strong>Ex-post demand</strong> occurs when seat capacity constraints force travelers to make choices that deviate from their initial preferences. This paper aims to develop a systematic and theoretically consistent methodology to estimate the three types of demand that drive overall demand variation. To integrate these estimation modules, a computational graph-based learning architecture is proposed to solve the railway passenger demand estimation (RPDE) problem. The RPDE problem simultaneously estimates passenger boarding and alighting at stations, OD trips between stations, and passenger flows loaded onto train lines. The behavioral parameters associated with travel time, ticket price, and line frequency are also calibrated. A novel four-stage adapted alternating direction method of multipliers (ADMM), enhanced by backpropagation, is proposed to solve the RPDE problem to ensure consistency between modules and enable efficient solutions. We demonstrate the effectiveness of the method through scenario analyses, quantifying the composition of the demand, and revealing their implications for policymaking. A real-world case study in the Beijing-Shanghai high-speed rail corridor is used to demonstrate the applicability of the proposed approach.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"202 ","pages":"Article 104283"},"PeriodicalIF":8.3,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144670409","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}