Omega-international Journal of Management Science最新文献

{"title":"Data-driven robust two-stage ferry vehicle management at airports","authors":"Huili Zhang ,&nbsp;Xuan An ,&nbsp;Cong Chen ,&nbsp;Nengmin Wang ,&nbsp;Weitian Tong","doi":"10.1016/j.omega.2024.103269","DOIUrl":"10.1016/j.omega.2024.103269","url":null,"abstract":"<div><div>In the face of substantial uncertainties in flight schedules, driven by factors such as heavy traffic flow, extreme weather conditions, and climate change, efficient management of ground support vehicles at airports becomes a critical challenge. This paper delves into the ferry management problem (FMP), where a fleet of ferries, comprising both regular and backup vehicles, is tasked with servicing flights within specified time windows before their arrival or departure. The central aim of the FMP is to optimize ferry vehicle allocation, minimizing total operational cost while ensuring punctual and effective service for each flight. A novel two-stage scenario-based robust model is introduced to effectively capture the potential uncertainties. We present four solution strategies to solve the FMP. The initial two methods, the sample average approximation (SAA) and its robust version (RSAA), focus on reducing computational demands through a selective sampling of scenarios. Our third approach, built on the column-and-constraint generation (C&amp;CG) procedure, guarantees the solution quality by progressively incorporating critical scenarios into the master problem, benefiting from the strategic limitation of scenarios and the transformation of subproblems into minimum-cost maximum-flow problems for efficient solution approximation. Lastly, we introduce a data-driven, on-the-fly heuristic that dynamically adjusts scheduling plans, boosting adaptability to real-time operational fluctuations. Our comprehensive experiments, utilizing real-world datasets, validate the robustness, efficiency, and effectiveness of the proposed algorithms, showcasing their practical applicability in managing airport ground support under uncertain conditions.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"133 ","pages":"Article 103269"},"PeriodicalIF":6.7,"publicationDate":"2024-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143166815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design incentives of extended producer responsibility for electric vehicle producers with competition and cooperation","authors":"Xinna Qi ,&nbsp;Zilong Liu ,&nbsp;Tingting Li","doi":"10.1016/j.omega.2024.103266","DOIUrl":"10.1016/j.omega.2024.103266","url":null,"abstract":"<div><div>To regulate the development of the electric vehicle battery recycling industry, many governments, including China, have proposed the extended producer responsibility (EPR) system, which emphasizes that producers are responsible for the entire life cycle of their own products, especially the recycling of discarded products. As compliance schemes of the EPR system, collective producer responsibility and individual producer responsibility (CPR and IPR, respectively) systems received varying degrees of preference. In this paper, we consider two vehicle producers with a competition-cooperation relationship and investigate the implications of scheme adoption on recycling technology investment. The two vehicle producers compete in the forward supply chain and cooperate in the reverse supply chain under the CPR system. Specifically, the two competing vehicle producers invest in recycling technology separately under the IPR system but negotiate it under the CPR system, and we use the Nash bargaining game model to characterize the negotiation between them. The key findings are as follows: When the recycling-technology-investment effectiveness is relatively low, or the investment effectiveness is high and the brand differentiation between vehicle producers is significant, they reap higher economic benefits under the collective recycling system. In addition, only when the investment effectiveness is relatively high and the brand differentiation is insignificant will environmental benefits (reflected by the recycling technology level) be higher under the collective recycling system. Furthermore, consumers’ preferences for recycling systems are always consistent with those of vehicle producers. Interestingly, when the investment effectiveness is relatively high, under moderate brand differentiation conditions, Pareto improvements in economic benefits, environmental benefits, and consumer surplus can be achieved simultaneously under the collective recycling system, i.e., the two competing vehicle producers can maximize overall social welfare through win-win cooperation.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"133 ","pages":"Article 103266"},"PeriodicalIF":6.7,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143166812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A heuristic method for perishable inventory management under non-stationary demand","authors":"Suheyl Gulecyuz ,&nbsp;Barry O’Sullivan ,&nbsp;S. Armagan Tarim","doi":"10.1016/j.omega.2024.103267","DOIUrl":"10.1016/j.omega.2024.103267","url":null,"abstract":"<div><div>Our study considers a perishable inventory system under a finite planning horizon, periodic review, non-stationary stochastic demand, zero lead time, FIFO (first in, first out) issuing policy, and a fixed shelf life. The inventory system has a fixed setup cost and linear ordering, holding, penalty, and outdating costs per item. We introduce a computationally-efficient heuristic which formulates the problem as a network graph, and then calculates the shortest path in a recursive way and by keeping the average total cost per period at minimum. The heuristic firstly determines the replenishment periods and cycles using the deterministic-equivalent shortest path approach. Taking the replenishment plan constructed in the first step as an input, it calculates the order quantities with respect to the observed inventory states as a second step. We conduct numerical experiments for various scenarios and parameters, and compare them to the optimal stochastic dynamic programming (SDP) results. Our experiments conclude that the computation time is reduced significantly, and the average optimality gap between the expected total cost and the optimal cost is 1.87%.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"133 ","pages":"Article 103267"},"PeriodicalIF":6.7,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143166813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A comprehensive methodology combining machine learning and unified robust stochastic programming for medical supply chain viability","authors":"Ömer Faruk Yılmaz ,&nbsp;Yongpei Guan ,&nbsp;Beren Gürsoy Yılmaz ,&nbsp;Fatma Betül Yeni ,&nbsp;Gökhan Özçelik","doi":"10.1016/j.omega.2024.103264","DOIUrl":"10.1016/j.omega.2024.103264","url":null,"abstract":"<div><div>This paper addresses the medical kit allocation problem by employing a unified robust stochastic programming (URSP) approach to enhance medical supply chain (MSC) viability during pandemics. A two-stage methodology is developed to account for the inherent uncertainty of demand. It begins with a machine learning (ML) algorithm for contagion level prediction, which adjusts demand forecasts accordingly. Subsequently, the URSP approach incorporates risk aversion and various types of uncertainty by combining stochastic programming and robust optimization through an adjustable weight in the objective function. As a risk-aversion technique, conditional value-at-risk (CVaR) is employed to restrict shortage levels, providing a more realistic assessment of MSC resilience. To balance cost-effectiveness and robustness against a spectrum of uncertainties, the URSP method leverages the strengths of both stochastic programming and robust optimization. Taguchi's orthogonal array design is utilized to generate cases representing combinations of government policies aimed at mitigating potential risks during future epidemics or pandemics. The effectiveness of the proposed methodology is demonstrated through a comprehensive case study conducted in Türkiye, comparing several modeling approaches. Extensive experiments under different types of uncertainties are performed to assess MSC viability. Computational analysis reveals that the URSP approach provides more robust and computationally tractable solutions than the purely stochastic approach and offers more cost-effective kit allocation decisions than the purely robust approach by allowing decision-makers to fine-tune the robustness level based on their priorities. The insights indicate that integrating ML predictions with URSP significantly enhances MSC viability to withstand deep uncertainties during pandemics.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"133 ","pages":"Article 103264"},"PeriodicalIF":6.7,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143166831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Build or cooperate with a bike-sharing system? Operation mode selection of metro operator with different information sharing strategies","authors":"Chang Zhou ,&nbsp;Xiang Li ,&nbsp;Bo Feng","doi":"10.1016/j.omega.2024.103263","DOIUrl":"10.1016/j.omega.2024.103263","url":null,"abstract":"<div><div>To fill the last-mile service gap, a metro operator possessing superior demand information can either build a public bike system incurring a setup cost or cooperate with an existing bike-sharing company through cost-sharing mechanism to provide <em>metro+bike</em> services, corresponding to self-owned mode (S mode) or partnership mode (P mode), respectively. Note that the metro operator acts as a centralized decision maker with a symmetric information structure under the S mode, whereas with an option to share information or not under the P mode. We model a multistage game framework to investigate how the interplay between information sharing strategy and operation mode selection could create value for a <em>metro+bike</em> system with demand uncertainty. From our analysis, information sharing leaves both the metro operator and the bike-sharing company better off, and such positive effect can be strengthened by accurate demand information, especially for the bike-sharing company. Our results, therefore, suggest more caution in the metro operator’s information strategy to prevent his partner from free-riding. When the sharing strategy is in place, a metro operator with weaker predictive capabilities is typically expected to transfer the risk arising from forecasting errors to a partner by engaging in the P mode. Despite expectations, the result indicates that the cost advantage created by a sufficiently high investment efficiency can potentially offset the information disadvantage, ultimately favoring the S mode. We also solve the dual-mode operation cases that allow public bikes and shared bikes to coexist in the marketplace, thereby forcing service providers to engage in Bertrand price competition. Through comparative analyses, we identify that the incentive for the metro operator to share demand information hinges critically on cost efficiency. To elaborate, information sharing is more likely to occur when convenience investment expectations are pessimistic.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"133 ","pages":"Article 103263"},"PeriodicalIF":6.7,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143166830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dual sourcing under quality improvement uncertainty","authors":"Gang Fang ,&nbsp;Xiang Fang ,&nbsp;Qing-kai Ji ,&nbsp;Jun Li","doi":"10.1016/j.omega.2024.103268","DOIUrl":"10.1016/j.omega.2024.103268","url":null,"abstract":"<div><div>In modern manufacturing, the implementation of dual or multi-sourcing strategies presents challenges concerning the variability in component quality. This study investigates a supply chain where a manufacturer sources components from an incumbent and an entrant supplier, with the latter having lower quality but meeting standards. The entrant aims to enhance quality through research and development (R&amp;D) efforts, which may succeed or fail. Failure in R&amp;D leads the manufacturer to either limit the high-quality component use from the incumbent, offer consistent but lower-performance products in one market, or sell distinct products in two separate markets. We formulate the problem as a two-stage game within defined market structures (single- or two-market) and derive equilibrium solutions for both models. Our findings reveal interesting managerial insights. In both market structures, we surprisingly find that an increase in the likelihood of success for the entrant supplier’s R&amp;D may negatively impact the entrant supplier while benefiting the manufacturer and the other supplier. Dual sourcing is beneficial to the manufacturer in general, except when the entrant supplier is highly uncompetitive in quality. Furthermore, we derive analytical conditions that dictate when each member of the supply chain favors either the single-market model or the two-market model over the other.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"133 ","pages":"Article 103268"},"PeriodicalIF":6.7,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143166832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lot sizing with capacity adjustment using on-site green and grid electricity","authors":"Ayse Akbalik ,&nbsp;Céline Gicquel ,&nbsp;Bernard Penz ,&nbsp;Christophe Rapine","doi":"10.1016/j.omega.2024.103260","DOIUrl":"10.1016/j.omega.2024.103260","url":null,"abstract":"<div><div>This paper investigates from a theoretical point of view how on-site generation of renewable energy can be incorporated in the optimization of a mid-term production and capacity planning problem. Specifically, we consider the generic case of a manufacturer using two energy sources to supply the electricity demand of its plant: an on-site renewable energy source and the electricity grid. The renewable energy source is considered to be free of use, but its available amount of energy fluctuates over time, whereas the grid power is virtually unlimited but incurs a cost per kWh purchased from the external provider. The objective is to satisfy a time-varying demand at a minimal cost over a mid-term horizon. The plant has a stationary nominal production capacity. To deal with the fluctuation of both the demand and the amount of energy supplied by the on-site source, the production capacity can be temporally increased by installing additional capacity, typically by changing the shift pattern or opening more production lines. Increasing the capacity allows to respond to peak demand and to build stock in periods where the energy is cheap but incurs a fixed cost. We study if an optimal solution of this integrated production, capacity, and energy planning problem can be computed efficiently to provide the best compromise. Our objective is to classify the complexity of the deterministic version of the problem. We establish its NP-hardness under mild assumptions and propose three polynomial time algorithms for special cases, according to the amount of energy provided by the renewable source. These algorithms rely on dominance structural properties which allow us to reduce the problem to well-studied lot-sizing problems with capacity or full batch delivery.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"133 ","pages":"Article 103260"},"PeriodicalIF":6.7,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143166817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bed census prediction combining expert opinion and patient statistics","authors":"Hayo Bos ,&nbsp;Stef Baas ,&nbsp;Richard J. Boucherie ,&nbsp;Erwin W. Hans ,&nbsp;Gréanne Leeftink","doi":"10.1016/j.omega.2024.103262","DOIUrl":"10.1016/j.omega.2024.103262","url":null,"abstract":"<div><div>Predictions of bed census are crucial for hospital capacity management choices, encompassing ward sizing, staffing, patient bed assignments, and surgical scheduling. Presently, these predictions heavily rely on doctors’ estimated Expected Discharge Date (EDD). This paper introduces two probabilistic models that integrate EDD with Length of Stay (LoS) distributions derived from data. By employing the Poisson binomial distribution and probabilistic convolution, we generate full census distributions. Applying our approach to real hospital data demonstrates its ability to provide precise predictions, leading to valuable managerial insights.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"133 ","pages":"Article 103262"},"PeriodicalIF":6.7,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143167373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Personalized recommendation, behavior-based pricing, or both? Examining privacy concerns from a cost perspective","authors":"Chi Zhou ,&nbsp;Danyang Bai ,&nbsp;Tieshan Li ,&nbsp;Jing Yu","doi":"10.1016/j.omega.2024.103223","DOIUrl":"10.1016/j.omega.2024.103223","url":null,"abstract":"<div><div>In the era of the big data, e-commerce increasingly adopts personalized recommendation and behavior-based pricing (BBP) strategies to enhance consumer experience, while also raising concerns about privacy. This study examines the impact of privacy costs on the effectiveness of those strategies using a two-period Hotelling model. The results indicate that retailers who combine personalized recommendation with BBP strategies can achieve higher prices and profits compared to those who do not employ these strategies, particularly when there are significant differences in privacy costs. Our study further reveals that relying solely on personalized recommendation without incorporating BBP may lead to decreases profit. Moreover, the accuracy of recommendations and variations in privacy costs significantly influence retailers’ strategy choices, emphasizing the importance of these factors in gaining a competitive advantage. This research provides valuable insights for online retailers on how to effectively position themselves in the market while addressing consumer privacy concerns, offering a new perspective on the comprehensive impacts of personalized recommendation and BBP strategies in the business landscape.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"133 ","pages":"Article 103223"},"PeriodicalIF":6.7,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143166781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Risk control strategies for inventory pledge financing on cross-border e-commerce platforms empowered by the digital economy","authors":"Aolin Leng ,&nbsp;Maolin Sun ,&nbsp;Jinzhao Shi","doi":"10.1016/j.omega.2024.103251","DOIUrl":"10.1016/j.omega.2024.103251","url":null,"abstract":"<div><div>With the development of cross-border e-commerce (CBEC), CBEC-based inventory pledge financing (CBEC-based IPF) has gradually emerged, where exporters can apply for financing from cross-border e-commerce platforms (CBECPs) with their stocks in overseas warehouses. Due to the intensification of information asymmetry caused by overseas pledges and the impact of exchange rate fluctuations on repayments and settlements, such businesses face increased credit and market risks. Fortunately, the digital economy can empower CBECPs to achieve “post-loan risk management”, such as using big data technology to monitor exporters’ post-loan business activities on the platform and reduce their “credit default risk”, or utilizing online marketing technologies such as search engine optimization and homepage recommendations to promote the sales of exporters’ pledged goods and lower their “market sales risk”. We focus on risk control issues in the CBEC-based IPF under the empowerment of the digital economy. The pre-loan risk control measures consider the setting of the pledge rate, while the post-loan risk control measures towards credit and market risks consider, respectively, the platform's online credit supervision and product sales assistance for exporters in light of the digital economy. On the basis of considering exchange rate fluctuations, we use optimization method to build decision models of a CBECP under two scenarios, i.e., “only control pre-loan risk” and “joint control pre- and post-loan risk”, and find that compared to the former, the latter is more profitable for the CBECP, indicating that the digital economy can empower the CBECP to achieve more comprehensive risk control and improve economic benefits. Furthermore, in the case of the CBECP paying equal risk control cost, its optimal choices for credit and market risk control measures are provided. The results show that when and only when the market risk control is cheaper enough and the budget is limited, the CBECP chooses market risk control; otherwise, it always implements credit risk control. We also extend the model to study the case when the CBECP pays equal risk control level in the post-loan risk control, and conduct numerical experiments to verify the above conclusions. Our findings strongly suggest CBECPs to adopt the “joint pre- and post-loan risk control” in the CBEC-based IPF business, and provide them strategies for choosing between post-loan credit and market risk control measures.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"133 ","pages":"Article 103251"},"PeriodicalIF":6.7,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143166783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}