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

{"title":"A meta-auction for on-demand transportation procurement in industry 5.0","authors":"Su Xiu Xu ,&nbsp;Zhiheng Zhao ,&nbsp;George Q. Huang ,&nbsp;Yifang Ding ,&nbsp;Ming Li ,&nbsp;Jianghong Feng","doi":"10.1016/j.tre.2024.103842","DOIUrl":"10.1016/j.tre.2024.103842","url":null,"abstract":"<div><div>The Cyber-Physical Internet (CPI) is a cutting-edge concept that brings together physical systems and cyber technologies to enable seamless interaction between the physical and virtual worlds. This innovative approach is revolutionizing the transportation industry by paving the way for a new era of logistics and transport networks. Introducing CPI into the procurement of transport services is leading to a re-evaluation of fundamental issues such as routing, mode choice and real-time pricing. This paper provides an in-depth discussion on the application of transport services procurement auctions in a CPI environment, with the aim of establishing a novel CPI-based trading platform for transport services using CPI technology, and calls the methodology proposed in this paper a <em>meta</em>-auction. The transport route allocation quandary is simplified into an auction model, where carriers truthfully submit unit route costs, and the winning carrier and pricing are determined using the single-unit Vickrey-Clark-Groves (VCG) method. To address scenarios with multiple carriers per network segment node, this paper proposes the multi-unit VCG auction method. Furthermore, the weighted affine VCG auction method is introduced, considering the weight of each network segment route. All three mechanisms are generalized VCG auctions, ensuring incentive compatibility, budget balance, allocation efficiency, and individual rationality. Case studies validate the effectiveness of the proposed methods, offering managerial insights based on key findings that are valuable for industry professionals and researchers in the CPI domain. This study highlights the transformative potential of CPI to revolutionize auctions for the procurement of transport services and underlines the benefits of combining physical and cyber technologies in auction design.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"193 ","pages":"Article 103842"},"PeriodicalIF":8.3,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142532252","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":"Design and selection of recycling strategy considering consumer preference","authors":"Yan-Ting Chen ,&nbsp;Ching-Ter Chang","doi":"10.1016/j.tre.2024.103824","DOIUrl":"10.1016/j.tre.2024.103824","url":null,"abstract":"<div><div>With the escalating issue of plastic pollution, exploring suitable post-consumer plastic waste (PCPW) recycling holds significant importance for global environmental protection. To address this issue, this paper proposes a novel PCPW recycling platform (PRP) that offers two recycling strategies to improve the recycling level of PCPW. Then, we construct a Stackelberg game model to analyze and compare three recycling strategies, <em>i.e.</em>, traditional recycling strategies, only trade-in for cash, and trade-in for cash and for new. Meantime, we consider the impact of consumer preference and government subsidies on recycling strategies. Research finding: (1) The operation of PRP increases the value of PCPW, particularly PRP’s only trade-in for cash has the highest recycling price. (2) PRP’s trade-in for cash and for new can attract more consumers to participate in PCPW recycling under certain conditions. (3) PRP’s only trade-in for cash enables recyclers and remanufacturers to reap greater benefits. To ensure the robustness of our research results, we conduct further analysis to explore the impact of corporate social responsibility (CRS) and the hassle cost. The study also provides management implications for promoting PCPW recycling.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"193 ","pages":"Article 103824"},"PeriodicalIF":8.3,"publicationDate":"2024-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142532248","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":"Transport behavior and government interventions in pandemics: A hybrid explainable machine learning for road safety","authors":"Ismail Abdulrashid ,&nbsp;Reza Zanjirani Farahani ,&nbsp;Shamkhal Mammadov ,&nbsp;Mohamed Khalafalla","doi":"10.1016/j.tre.2024.103841","DOIUrl":"10.1016/j.tre.2024.103841","url":null,"abstract":"<div><div>During a pandemic, transportation authorities and policymakers face significant challenges in identifying and validating new travel behavior and how it affects traffic crash patterns to develop effective safety strategies. A timely assessment of an emergency incident’s long-term impact and the development of appropriate response strategies are critical for managing future occurrences. This study investigates to answer these research questions (RQs):</div><div>RQ1: How do various spatio-temporal risk factors influence traffic crash injury severity during the different phases of the COVID-19 pandemic?</div><div>RQ2: What are the key risk factors influencing injury severity in automobile crashes during the pre-pandemic, early pandemic, between the first and second waves of the pandemic, and the post-pandemic era?</div><div>RQ3: How do the implemented government policies and interventions during the pandemic affect transport behavior and road safety?</div><div>This study presents a hybrid explainable machine learning approach based on eXtreme Gradient Boosting (XGBoost) and SHapley Additive exPlanation (SHAP) to identify influential traffic crash-related risk factors for injury severity. Additionally, we propose a statistical learning approach using a nonlinear multinomial logit model to jointly analyze the count of automobile traffic crashes by injury severity and assess the impact of the COVID-19 pandemic across different phases. Our findings include a detailed analysis of system-level taxonomies across feature components, as well as the use of aggregate SHAP scores to classify crash data into high-level contributing variables during the pre-pandemic, intra-pandemic, and post-pandemic phases. The expected outcomes include insights such as identifying the best times to implement travel restrictions to reduce traffic accidents, understanding shifts in traffic flow patterns across pandemic phases, and determining effective public health interventions that can reduce both traffic accidents and congestion. Furthermore, the study reveals that the initial pandemic phase saw a significant decrease in traffic volume and accident rates. In contrast, the subsequent pandemic and post-pandemic phases saw an increase in severe accidents due to risky driving behaviors, emphasizing the importance of adaptive safety measures.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"193 ","pages":"Article 103841"},"PeriodicalIF":8.3,"publicationDate":"2024-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142532251","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 placement with carbon cap-and-trade in guaranteed service supply chains","authors":"Yuan Wang ,&nbsp;Jia Shu ,&nbsp;Jingjing Su ,&nbsp;Lu Zhen","doi":"10.1016/j.tre.2024.103813","DOIUrl":"10.1016/j.tre.2024.103813","url":null,"abstract":"<div><div>In this paper, we explore the impact of carbon trading on the safety stock placement optimization in multi-echelon supply chains. The carbon emission in each stage of the supply chain is measured through a function of the service time quoted by the stage as a key variable. Adopting the guaranteed service time modelling framework, we develop a safety stock placement model under the carbon cap-and-trade policy to study the complex trade-off among the carbon cap, the carbon price, and the service time. Based on the different relationship between the unit purchasing and selling carbon prices, we derive the tractable formulations of the proposed model using successive mixed-integer programming approximations. A series of observations through the model implementation on a real-world chain data from Willems (2008) are summarized to understand how the carbon cap and price can affect a firm’s safety stock placement and carbon emissions.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"193 ","pages":"Article 103813"},"PeriodicalIF":8.3,"publicationDate":"2024-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142532250","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 simulation-based optimization approach for the recharging scheduling problem of electric buses","authors":"Chun-Chih Chiu ,&nbsp;Hao Huang ,&nbsp;Ching-Fu Chen","doi":"10.1016/j.tre.2024.103835","DOIUrl":"10.1016/j.tre.2024.103835","url":null,"abstract":"<div><div>This study proposes a simulation-based optimization approach to address the recharging scheduling problem of electric buses to minimize charging waiting time. Poor scheduling could lead to longer waiting times and potentially affect operation schedules regarding time and service quality. This study addresses a simulation-based optimization framework to evaluate various performance metrics during electric bus service, including waiting times, charging costs, and the utilization of charging piles. In this study, we propose a hybrid approach, simplified swarm optimization (SSO), which is an evolutionary algorithm with a backtracking (BT) mechanism and dynamic charging in a simulation framework. Based on the dynamic charging, SSO is used to determine the additional charging in terms of battery capacities, and a BT mechanism is employed to enhance algorithm efficiency and achieve breakthroughs in solution quality. A case study from Taiwan with 43 generated datasets was conducted in deterministic and stochastic situations to compare the effectiveness and efficiency among three charging rules (i.e., full charging rule, flexible charging rule, dynamic charging rule) and two algorithms (i.e., particle swarm optimization and SSO<u>)</u> The results indicate the superior performance in all scenarios by using a statistical test, which offers effective decision support for bus operators’ electric bus recharging scheduling.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"192 ","pages":"Article 103835"},"PeriodicalIF":8.3,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142540346","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":"Examining the role of national governance capacity in building the global low-carbon agricultural supply chains","authors":"Hua Shang ,&nbsp;Li Jiang ,&nbsp;Sachin Kumar Mangla ,&nbsp;Xiongfeng Pan ,&nbsp;Malin Song","doi":"10.1016/j.tre.2024.103833","DOIUrl":"10.1016/j.tre.2024.103833","url":null,"abstract":"<div><div>The majority of related research has traditionally focused on examining the individual influences of national governance capacity and technological innovation on carbon emissions and economic performance, neglecting the effects and influence mechanisms on carbon efficiency within agricultural supply chains, which is not conducive to advancing a low-carbon transition that includes agricultural concerns. This study addresses these gaps by investigating the correlation between national governance capacity (considering voice and accountability, political stability and absence of violence/terrorism, government effectiveness, regulatory quality, rule of law and corruption control) and agricultural supply chain carbon efficiency and investigating the influence mechanism and mediating role of technological innovation. The relevant findings are twofold. 1) The impact of national governance capacity and its components on agricultural carbon efficiency follows an inverted U-shaped curve. 2) Technological innovation can act as a mediator between national governance capacity and select factors of voice and accountability, government effectiveness and regulatory quality to enhance agricultural supply chain carbon efficiency. The findings offer valuable insights for policymakers and managers in agricultural supply chain enterprises seeking to transition towards low-carbon agriculture.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"192 ","pages":"Article 103833"},"PeriodicalIF":8.3,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142539813","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":"Pricing strategies in an M/G/m/m loss system: A case study of Incheon International Airport customer services","authors":"Junseok Park ,&nbsp;Ilkyeong Moon","doi":"10.1016/j.tre.2024.103821","DOIUrl":"10.1016/j.tre.2024.103821","url":null,"abstract":"<div><div>This paper studied the optimal pricing strategy based on a highly realistic pricing scheme in order to maximize the revenue of a service modeled as an M/G/m/m loss system. The blocking probability is considered together to prevent compromising the quality of service. Customers’ willingness-to-pay is regarded to be randomly distributed, indicating price-dependent arrival. Considering the severe complexity of the proposed model, the optimal pricing strategy is numerically investigated through computational experiments based on case studies of two actual services currently operated at Incheon International Airport (Seoul, South Korea). The two services represent a congested and quiet situation, allowing for the analysis of opposite cases. The results of the computational experiments clearly demonstrate distinct optimal strategies for the two contrasting situations. The performance of the two services with their current pricing strategies is evaluated, providing managerial insights for the service providers.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"192 ","pages":"Article 103821"},"PeriodicalIF":8.3,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142540257","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":"Towards resilience: Primal large-scale re-optimization","authors":"El Mehdi Er Raqabi ,&nbsp;Yong Wu ,&nbsp;Issmaïl El Hallaoui ,&nbsp;François Soumis","doi":"10.1016/j.tre.2024.103819","DOIUrl":"10.1016/j.tre.2024.103819","url":null,"abstract":"<div><div>Perturbations are universal in supply chains, and their appearance has become more frequent in the past few years due to global events. These perturbations affect industries and could significantly impact production, quality, cost/profitability, and consumer satisfaction. In large-scale contexts, companies rely on operations research techniques. In such a case, re-optimization can support companies in achieving resilience by enabling them to simulate several what-if scenarios and adapt to changing circumstances and challenges in real-time. In this paper, we design a generic and scalable resilience re-optimization framework. We model perturbations, recovery decisions, and the resulting re-optimization problem, which maximizes resilience. We leverage the primal information through fixing, warm-start, valid inequalities, and machine learning. We conduct extensive computational experiments on a real-world, large-scale problem. The findings highlight that local optimization is enough to recover after perturbations and demonstrate the power of our proposed framework and solution methodology.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"192 ","pages":"Article 103819"},"PeriodicalIF":8.3,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142540258","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":"Modeling a ride-sourcing market with a third-party platform integrator under batch matching mechanisms","authors":"Ce Wang,&nbsp;Jintao Ke","doi":"10.1016/j.tre.2024.103803","DOIUrl":"10.1016/j.tre.2024.103803","url":null,"abstract":"<div><div>This paper develops a mathematical model to characterize a generalized ride-sourcing market with a third-party integrator and multiple competitive ride-sourcing platforms. Different from earlier works which normally assume instant matching strategies, our model can characterize the integrator’s and platforms’ decisions on choosing flexible matching strategies under batch matching mechanisms and their influences on the market equilibrium. Through theoretical analytics and numerical studies, this study reveals that the introduction of a third-party platform integrator is not always beneficial but may be detrimental to the system in certain situations. For example, an inefficient matching strategy chosen by the integrator may lead to a lose-lose situation where both the customers hailing rides through the integrator or the individual platforms experience longer waiting times. In addition, we show that a ride-sourcing platform with a high market share may refuse to join the integrator since the efficiency gains brought by the integrator do not outweigh the losses caused by its losing market share. The managerial insights obtained from this work can assist both the integrator and individual ride-sourcing platforms in developing more efficient operational strategies in terms of pricing and matching strategies.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"192 ","pages":"Article 103803"},"PeriodicalIF":8.3,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142540259","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 collaborative healthcare resource allocation in pandemics","authors":"Jiehui Jiang ,&nbsp;Dian Sheng ,&nbsp;Xiaojing Chen ,&nbsp;Qiong Tian ,&nbsp;Feng Li ,&nbsp;Peng Yang","doi":"10.1016/j.tre.2024.103828","DOIUrl":"10.1016/j.tre.2024.103828","url":null,"abstract":"<div><div>Severe shortages of healthcare resources are major challenges in pandemics, especially in their early stages. To improve emergency management efficiency, this paper proposes a novel rolling predict-then-optimize framework that includes three interactive modules, i.e., data-driven demand prediction, healthcare resource allocation, and parameter rolling update. Such a framework uses historical data to dynamically update the control parameters of the proposed Net-SEIHRD model, which predicts the healthcare needs of each region by jointly considering government interventions and cross-regional travel behaviors. Based on the forecasted healthcare resource demand in real-time, an optimization model is then formulated to realize coordinated resource allocation across multiple regions by minimizing the total generalized cost. To facilitate model solving, the proposed mixed integer nonlinear programming model is converted into an equivalent mixed integer linear model by using some linearization techniques. Finally, the proposed method is applied to the SARS-CoV-2 emergency response and collaborative allocation of healthcare resources in Shanghai, China. The results show that the proposed prediction model can effectively predict the peak and scale of the spread of the virus. Compared with the traditional LM and SEIHR models, the prediction accuracy of the Net-SEIHRD model is improved by 10.76% and 24.11%, respectively. Moreover, coordinated relief activities across regions, such as patient transfer and drug-sharing can improve the efficiency of pandemic control and save social costs.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"192 ","pages":"Article 103828"},"PeriodicalIF":8.3,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142540256","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}