Pub Date : 2025-09-19DOI: 10.1016/j.omega.2025.103428
Renata Mansini , Lorenzo Moreschini , Mesut Sayin
With the 2024 US Presidential Election now concluded, the growing complexity of designing effective election campaigns has become clearer. Motivated by the logistical challenges associated with US election campaigns, we introduce the Reward-driven Multi-period Politician Routing Problem. It involves diverse politicians planning their campaigns over multiple days, considering constraints such as clustered locations, time- and location-dependent rewards, budget limits, mandatory rest days, and flexible daily routes that can be either open or closed, with starting and ending locations not known in advance.
We model the problem as a mixed-integer linear program, complemented with several valid inequalities, and innovate by designing new subtour elimination techniques that jointly deal with open and closed paths. We developed 36 new benchmark instances tailored to the US presidential elections. To tackle large-sized instances, we develop a Sequential Route Construction Matheuristic that exploits the multi-period structure of the problem to provide efficient and effective solutions. We incorporate time-dependent reward profiles (concave, convex, linearly decreasing, linearly increasing, and periodic) into the objective function to capture diverse decision-making perspectives. Experimental results show interesting computational issues on the different tested models and the impact of the chosen reward profile on their performance.
{"title":"Optimizing election logistics: A multi-period routing problem embedding time-dependent reward functions","authors":"Renata Mansini , Lorenzo Moreschini , Mesut Sayin","doi":"10.1016/j.omega.2025.103428","DOIUrl":"10.1016/j.omega.2025.103428","url":null,"abstract":"<div><div>With the 2024 US Presidential Election now concluded, the growing complexity of designing effective election campaigns has become clearer. Motivated by the logistical challenges associated with US election campaigns, we introduce the Reward-driven Multi-period Politician Routing Problem. It involves diverse politicians planning their campaigns over multiple days, considering constraints such as clustered locations, time- and location-dependent rewards, budget limits, mandatory rest days, and flexible daily routes that can be either open or closed, with starting and ending locations not known in advance.</div><div>We model the problem as a mixed-integer linear program, complemented with several valid inequalities, and innovate by designing new subtour elimination techniques that jointly deal with open and closed paths. We developed 36 new benchmark instances tailored to the US presidential elections. To tackle large-sized instances, we develop a Sequential Route Construction Matheuristic that exploits the multi-period structure of the problem to provide efficient and effective solutions. We incorporate time-dependent reward profiles (concave, convex, linearly decreasing, linearly increasing, and periodic) into the objective function to capture diverse decision-making perspectives. Experimental results show interesting computational issues on the different tested models and the impact of the chosen reward profile on their performance.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"138 ","pages":"Article 103428"},"PeriodicalIF":7.2,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145219210","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}
Pub Date : 2025-09-17DOI: 10.1016/j.omega.2025.103427
Ruixiao Dong , Xu Guan , Xiaohua Han , Yuan Jiang
The content platforms usually offer monetary rewards to creators to encourage the creation of high-quality content to attract views. This would motivate some creators to incorporate controversial content to generate engagement, which causes the platform’s reputation cost. Therefore, in practice, the platform actively conducts content moderation through various methods. In this paper, we consider two content moderation formats, Pre-Moderation format and Post-Moderation format, depending on whether the moderation takes place before or after the content’s publication. Under Pre-Moderation format, the platform reviews each content before it is released, which makes it less likely to suffer from a high reputation cost. However, the drawback is the potential for mistakenly blocking of high quality content. The platform has the incentive to reward creators to exert effort to attract views only when the platform’s payoff from each view of high-quality content is relatively high. Moreover, a more rigor moderation mechanism may not necessarily benefit the platform and hurt the low-type creators, and a high proportion of controversial-content fans may also not necessarily benefit the low-type creators. Conversely, Post-Moderation format proves more creator-friendly, as it enables each content published without check, though this comes at the expense of a higher reputation cost. Compared to Pre-Moderation format, the platform becomes more likely to provide monetary reward under Post-Moderation format only when the proportion of controversial-content fans is low. The platform’s profit and the creators’ profits can be higher under either moderation format, depending on the monetary reward strategy and the dissemination of low-quality content.
{"title":"Content moderation and creator incentives mechanism amidst controversial content surges","authors":"Ruixiao Dong , Xu Guan , Xiaohua Han , Yuan Jiang","doi":"10.1016/j.omega.2025.103427","DOIUrl":"10.1016/j.omega.2025.103427","url":null,"abstract":"<div><div>The content platforms usually offer monetary rewards to creators to encourage the creation of high-quality content to attract views. This would motivate some creators to incorporate controversial content to generate engagement, which causes the platform’s reputation cost. Therefore, in practice, the platform actively conducts content moderation through various methods. In this paper, we consider two content moderation formats, Pre-Moderation format and Post-Moderation format, depending on whether the moderation takes place before or after the content’s publication. Under Pre-Moderation format, the platform reviews each content before it is released, which makes it less likely to suffer from a high reputation cost. However, the drawback is the potential for mistakenly blocking of high quality content. The platform has the incentive to reward creators to exert effort to attract views only when the platform’s payoff from each view of high-quality content is relatively high. Moreover, a more rigor moderation mechanism may not necessarily benefit the platform and hurt the low-type creators, and a high proportion of controversial-content fans may also not necessarily benefit the low-type creators. Conversely, Post-Moderation format proves more creator-friendly, as it enables each content published without check, though this comes at the expense of a higher reputation cost. Compared to Pre-Moderation format, the platform becomes more likely to provide monetary reward under Post-Moderation format only when the proportion of controversial-content fans is low. The platform’s profit and the creators’ profits can be higher under either moderation format, depending on the monetary reward strategy and the dissemination of low-quality content.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"138 ","pages":"Article 103427"},"PeriodicalIF":7.2,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145157159","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}
We study operating room (OR) scheduling with multiple surgical disciplines under uncertain surgery durations, considering time-dependent health urgency, where patient health deteriorates with the waiting time. The problem involves the opening of ORs, assignment of ORs to surgical disciplines, and assignment of surgeries (mandatory and optional surgeries) to ORs over a planning horizon, subject to the discipline-to-OR, discipline parallelism, discipline workload, and surgery deadline restrictions, and OR session capacity chance constraints. To characterize the uncertainty of surgery durations, we introduce a data-driven distributionally ambiguity set based on real surgery data, which incorporates the empirical mean and covariance. We formulate the problem as a distributionally robust chance-constrained model, where distributionally robust chance constraints are imposed on the OR session capacity. To solve the model, we transform it into a tractable mixed-integer linear program, and propose a tailored branch-and-price-and-cut algorithm based on a bounded bidirectional dynamic programming algorithm for the pricing subproblems. We use the limited-node-memory subset row inequalities to enhance the lower bounds found by column generation and apply two enhancement techniques to enhance computing efficiency. We conduct extensive numerical studies on instances generated from real surgery data. The results illustrate the computational superiority of our algorithm to the CPLEX solver, and highlight the benefits of our model over its stochastic programming counterpart and two heuristic scheduling rules. We also perform sensitivity analysis to generate managerial insights from the analytical findings.
{"title":"Distributionally robust multi-period operating room scheduling with multiple surgical disciplines under uncertain surgery durations","authors":"Xiaoyu Xu , Yunqiang Yin , Dujuan Wang , T.C.E. Cheng , Xiutian Sima","doi":"10.1016/j.omega.2025.103420","DOIUrl":"10.1016/j.omega.2025.103420","url":null,"abstract":"<div><div>We study operating room (OR) scheduling with multiple surgical disciplines under uncertain surgery durations, considering time-dependent health urgency, where patient health deteriorates with the waiting time. The problem involves the opening of ORs, assignment of ORs to surgical disciplines, and assignment of surgeries (mandatory and optional surgeries) to ORs over a planning horizon, subject to the discipline-to-OR, discipline parallelism, discipline workload, and surgery deadline restrictions, and OR session capacity chance constraints. To characterize the uncertainty of surgery durations, we introduce a data-driven distributionally ambiguity set based on real surgery data, which incorporates the empirical mean and covariance. We formulate the problem as a distributionally robust chance-constrained model, where distributionally robust chance constraints are imposed on the OR session capacity. To solve the model, we transform it into a tractable mixed-integer linear program, and propose a tailored branch-and-price-and-cut algorithm based on a bounded bidirectional dynamic programming algorithm for the pricing subproblems. We use the limited-node-memory subset row inequalities to enhance the lower bounds found by column generation and apply two enhancement techniques to enhance computing efficiency. We conduct extensive numerical studies on instances generated from real surgery data. The results illustrate the computational superiority of our algorithm to the CPLEX solver, and highlight the benefits of our model over its stochastic programming counterpart and two heuristic scheduling rules. We also perform sensitivity analysis to generate managerial insights from the analytical findings.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"138 ","pages":"Article 103420"},"PeriodicalIF":7.2,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145094753","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}
The industry is increasingly confronted with the challenge of process duration uncertainty in production systems. These variations are particularly problematic for manufacturers that utilize Multi-Manned Mixed-Model Assembly Lines, as they can cause significant disruptions that may stop the production line. Our study explores the benefit of walking workers to dynamically adjust the workforce in response to unexpected variations in process durations at different stations, a common scenario in the automotive industry. We model the dynamic workforce assignment decision as a Markov Decision Process (MDP), and this MDP accounts for uncertainties in process times, and it incorporates dynamic task assignment and workers’ movements. This MDP is subsequently translated into a linear program that we integrate into a higher-level Mixed-Integer Linear Programming model responsible for dimensioning the workforce and selecting equipment in the station. This approach results in the creation of assembly lines designed to be resilient in the face of unexpected variations in task process durations. To deal with scalability issues, we employ the Benders decomposition algorithm. The paper also presents a validation with data from a car manufacturer that reinforces the practical applicability of our methodology. Additionally, we provide managerial insights on effectively managing process time uncertainty in automotive production systems, empowering decision-makers with optimization strategies, cost-reduction approaches, and resilience-building techniques to enhance the performance and reliability of Mixed-Model Assembly Lines.
{"title":"Markov Decision Process for Mixed-Model Assembly Line design under process time uncertainty","authors":"Milad Elyasi , Simon Thevenin , Audrey Cerqueus , Alexandre Dolgui","doi":"10.1016/j.omega.2025.103425","DOIUrl":"10.1016/j.omega.2025.103425","url":null,"abstract":"<div><div>The industry is increasingly confronted with the challenge of process duration uncertainty in production systems. These variations are particularly problematic for manufacturers that utilize <em>Multi-Manned Mixed-Model Assembly Lines</em>, as they can cause significant disruptions that may stop the production line. Our study explores the benefit of walking workers to dynamically adjust the workforce in response to unexpected variations in process durations at different stations, a common scenario in the automotive industry. We model the dynamic workforce assignment decision as a <em>Markov Decision Process</em> (MDP), and this MDP accounts for uncertainties in process times, and it incorporates dynamic task assignment and workers’ movements. This MDP is subsequently translated into a linear program that we integrate into a higher-level <em>Mixed-Integer Linear Programming</em> model responsible for dimensioning the workforce and selecting equipment in the station. This approach results in the creation of assembly lines designed to be resilient in the face of unexpected variations in task process durations. To deal with scalability issues, we employ the Benders decomposition algorithm. The paper also presents a validation with data from a car manufacturer that reinforces the practical applicability of our methodology. Additionally, we provide managerial insights on effectively managing process time uncertainty in automotive production systems, empowering decision-makers with optimization strategies, cost-reduction approaches, and resilience-building techniques to enhance the performance and reliability of <em>Mixed-Model Assembly Lines</em>.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"138 ","pages":"Article 103425"},"PeriodicalIF":7.2,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145060191","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}
In this paper, we study a multi-agent scheduling problem for organising the operations within the operating room department. The head of the surgeon group and individual surgeons are together responsible for the surgeon schedule and surgical case planning. The surgeon head allocates time blocks to individual surgeons, whereas individual surgeons determine the planning of surgical cases independently, which might degrade the schedule quality envisaged by the surgeon head. The bilevel optimisation under study seeks an optimal Nash equilibrium solution – a surgeon schedule and surgical case plan that optimise the objectives of the surgeon head, while ensuring that no individual surgeon can improve their own objective within the allocated time blocks. We propose a dedicated branch-and-price that adds lazy constraints to the formulation of surgeon-specific pricing problems to ensure an optimal bilevel feasible solution is retrieved. In this way, the surgeon head respects the objective requirements of the individual surgeons and the solution space can be searched efficiently. In the computational experiments, we validate the performance of the proposed algorithm and its dedicated components and provide insights into the benefits of attaining an equilibrium solution under different scenarios by calculating the price of stability and the price of decentralisation.
{"title":"A bilevel approach to integrated surgeon scheduling and surgery planning solved via branch-and-price","authors":"Broos Maenhout , Přemysl Šůcha , Viktorie Valdmanova , Ondřej Tkadlec , Jana Thao Rozlivkova","doi":"10.1016/j.omega.2025.103424","DOIUrl":"10.1016/j.omega.2025.103424","url":null,"abstract":"<div><div>In this paper, we study a multi-agent scheduling problem for organising the operations within the operating room department. The head of the surgeon group and individual surgeons are together responsible for the surgeon schedule and surgical case planning. The surgeon head allocates time blocks to individual surgeons, whereas individual surgeons determine the planning of surgical cases independently, which might degrade the schedule quality envisaged by the surgeon head. The bilevel optimisation under study seeks an optimal Nash equilibrium solution – a surgeon schedule and surgical case plan that optimise the objectives of the surgeon head, while ensuring that no individual surgeon can improve their own objective within the allocated time blocks. We propose a dedicated branch-and-price that adds lazy constraints to the formulation of surgeon-specific pricing problems to ensure an optimal bilevel feasible solution is retrieved. In this way, the surgeon head respects the objective requirements of the individual surgeons and the solution space can be searched efficiently. In the computational experiments, we validate the performance of the proposed algorithm and its dedicated components and provide insights into the benefits of attaining an equilibrium solution under different scenarios by calculating the price of stability and the price of decentralisation.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"138 ","pages":"Article 103424"},"PeriodicalIF":7.2,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145094754","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}
Pub Date : 2025-09-11DOI: 10.1016/j.omega.2025.103408
Yang Xu , Yu Zhang , Jiancheng Lyu
Existing literature has underscored the financing advantages intrinsic to crowdfunding, often overlooking its pivotal risk transfer function. By factoring in elements of loss aversion, our study formulates a comprehensive crowdfunding model to discern disparities between the crowdfunding and traditional financing model in mitigating the production risk. In the traditional financing model, the entrepreneur navigates a strategic trade-off between the financing cost and production risk by judiciously allocating the asset–liability portfolio between personal funds and loan capital. Conversely, the crowdfunding model entails the entrepreneur pre-selling the products, thereby positioning buyers as the bearer of risk. Our results indicate that crowdfunding does not universally emerge as the dominant strategy. When the production cost is high and product value is low, the entrepreneur is advised to leverage crowdfunding to curtail financing expenses and mitigate demand uncertainty. This, however, entails transferring the production risk to buyers, necessitating the entrepreneur to set a more modest product price. When the production cost is low or the product value is high, the traditional financing model outshines crowdfunding. Introducing crowdfunding will trigger a precipitous decline in buyers’ willingness to pay and an unwarranted erosion of marginal returns. This elucidates why products unveiled on crowdfunding platforms frequently exhibit a lack of substantial value. Additionally, we introduce the deferred payment mechanism to augment crowdfunding efficacy and unveil its role in risk sharing. We also analyze in detail how the optimal prepayment ratio is affected by capital constraints, product attributes, risks, and market size. Finally, we explore five intriguing extensions: heterogeneous buyer valuations, the market size follows uniform distribution, hybrid financing, quality endogeneity, and partial consumers in crowdfunding market, yielding valuable insights.
{"title":"Reveal the new function of crowdfunding: Production risk transfer mechanism","authors":"Yang Xu , Yu Zhang , Jiancheng Lyu","doi":"10.1016/j.omega.2025.103408","DOIUrl":"10.1016/j.omega.2025.103408","url":null,"abstract":"<div><div>Existing literature has underscored the financing advantages intrinsic to crowdfunding, often overlooking its pivotal risk transfer function. By factoring in elements of loss aversion, our study formulates a comprehensive crowdfunding model to discern disparities between the crowdfunding and traditional financing model in mitigating the production risk. In the traditional financing model, the entrepreneur navigates a strategic trade-off between the financing cost and production risk by judiciously allocating the asset–liability portfolio between personal funds and loan capital. Conversely, the crowdfunding model entails the entrepreneur pre-selling the products, thereby positioning buyers as the bearer of risk. Our results indicate that crowdfunding does not universally emerge as the dominant strategy. When the production cost is high and product value is low, the entrepreneur is advised to leverage crowdfunding to curtail financing expenses and mitigate demand uncertainty. This, however, entails transferring the production risk to buyers, necessitating the entrepreneur to set a more modest product price. When the production cost is low or the product value is high, the traditional financing model outshines crowdfunding. Introducing crowdfunding will trigger a precipitous decline in buyers’ willingness to pay and an unwarranted erosion of marginal returns. This elucidates why products unveiled on crowdfunding platforms frequently exhibit a lack of substantial value. Additionally, we introduce the deferred payment mechanism to augment crowdfunding efficacy and unveil its role in risk sharing. We also analyze in detail how the optimal prepayment ratio is affected by capital constraints, product attributes, risks, and market size. Finally, we explore five intriguing extensions: heterogeneous buyer valuations, the market size follows uniform distribution, hybrid financing, quality endogeneity, and partial consumers in crowdfunding market, yielding valuable insights.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"138 ","pages":"Article 103408"},"PeriodicalIF":7.2,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145117721","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}
Pub Date : 2025-09-10DOI: 10.1016/j.omega.2025.103423
Kebing Chen , Qinyi Zhang , Shengbin Wang
This paper develops three channel models consisting of an online retailer and an offline counterpart, including the multichannel model, the buy-online pick-up in-store (BOPS) model, and the buy-online return in-store (BORS) model. First, we examine the impacts of online return rate and consumers’ return cost on the performance and optimal strategies of the retailers for each channel model. Then, we explore the conditions for the online retailer to adopt the omnichannel strategy (i.e., BOPS, BORS) and evaluate the resulting impact on the offline retailer’s profit. Next, we conduct the comparative analysis on the optimal decisions and performance of both online and offline retailers pre- and post-implementation of BOPS/BORS. Moreover, we also explore the scenario where the offline retailer offers coupons and consumers exhibit free-riding behavior. Our findings reveal that the choice between adopting BOPS or BORS depends on the return rate and return processing cost. Under the same external conditions (i.e., return rate, consumers’ return cost), a low return processing cost can prompt a stronger inclination toward BORS for the online retailer, whereas a higher cost push him to choose BOPS. After the implementation of omnichannel, the offline retailer’s profit from initial products is reduced, but the cross-selling opportunities are increased. Through the robustness analysis of the model, the motivation for adopting an omnichannel strategy remains largely unchanged when the offline retailer also offers coupons, although the threshold values are changed. Furthermore, the omnichannel motivation is influenced by the prevalence of free-riding behavior when such behaviors are taken into account.
{"title":"Online coupon and offline service efforts in omnichannel retailing with cross-channel effect","authors":"Kebing Chen , Qinyi Zhang , Shengbin Wang","doi":"10.1016/j.omega.2025.103423","DOIUrl":"10.1016/j.omega.2025.103423","url":null,"abstract":"<div><div>This paper develops three channel models consisting of an online retailer and an offline counterpart, including the multichannel model, the buy-online pick-up in-store (BOPS) model, and the buy-online return in-store (BORS) model. First, we examine the impacts of online return rate and consumers’ return cost on the performance and optimal strategies of the retailers for each channel model. Then, we explore the conditions for the online retailer to adopt the omnichannel strategy (i.e., BOPS, BORS) and evaluate the resulting impact on the offline retailer’s profit. Next, we conduct the comparative analysis on the optimal decisions and performance of both online and offline retailers pre- and post-implementation of BOPS/BORS. Moreover, we also explore the scenario where the offline retailer offers coupons and consumers exhibit free-riding behavior. Our findings reveal that the choice between adopting BOPS or BORS depends on the return rate and return processing cost. Under the same external conditions (i.e., return rate, consumers’ return cost), a low return processing cost can prompt a stronger inclination toward BORS for the online retailer, whereas a higher cost push him to choose BOPS. After the implementation of omnichannel, the offline retailer’s profit from initial products is reduced, but the cross-selling opportunities are increased. Through the robustness analysis of the model, the motivation for adopting an omnichannel strategy remains largely unchanged when the offline retailer also offers coupons, although the threshold values are changed. Furthermore, the omnichannel motivation is influenced by the prevalence of free-riding behavior when such behaviors are taken into account.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"138 ","pages":"Article 103423"},"PeriodicalIF":7.2,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145094927","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}
Pub Date : 2025-09-09DOI: 10.1016/j.omega.2025.103426
Mohsen Afsharian , Peter Bogetoft
Benchmarking is a key tool in regulatory frameworks for assessing the efficiency of network industries. In this context, identifying outliers is crucial, as their presence can significantly distort benchmarking outcomes and the resulting firm incentives. This paper focuses on two types of performance-related outliers: influential units – firms that define the frontier and significantly affect the efficiency scores of others, and atypical units – firms that have unusual input–output profiles but little or no influence on the rest of the sample. Using the German electricity sector as a case study, we examine the methodology of the Bundesnetzagentur (BNetzA), a pioneer in regulatory benchmarking. We show that its reliance on standard dominance and super-efficiency analysis fails to distinguish between these two types, which may result in misaligned incentives. To address this gap, we propose two methodological refinements – a revised dominance measure and a radius-based super-efficiency approach – embedded in a transparent procedure tailored to regulatory benchmarking. The proposed approach is designed to support a more consistent and targeted application of performance-based rewards, while remaining fully compatible with existing regulatory procedures.
{"title":"Outliers and rewards in regulation: Insights from German electricity benchmarking","authors":"Mohsen Afsharian , Peter Bogetoft","doi":"10.1016/j.omega.2025.103426","DOIUrl":"10.1016/j.omega.2025.103426","url":null,"abstract":"<div><div>Benchmarking is a key tool in regulatory frameworks for assessing the efficiency of network industries. In this context, identifying outliers is crucial, as their presence can significantly distort benchmarking outcomes and the resulting firm incentives. This paper focuses on two types of performance-related outliers: influential units – firms that define the frontier and significantly affect the efficiency scores of others, and atypical units – firms that have unusual input–output profiles but little or no influence on the rest of the sample. Using the German electricity sector as a case study, we examine the methodology of the <em>Bundesnetzagentur</em> (BNetzA), a pioneer in regulatory benchmarking. We show that its reliance on standard dominance and super-efficiency analysis fails to distinguish between these two types, which may result in misaligned incentives. To address this gap, we propose two methodological refinements – a revised dominance measure and a radius-based super-efficiency approach – embedded in a transparent procedure tailored to regulatory benchmarking. The proposed approach is designed to support a more consistent and targeted application of performance-based rewards, while remaining fully compatible with existing regulatory procedures.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"138 ","pages":"Article 103426"},"PeriodicalIF":7.2,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145108768","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}
Pub Date : 2025-09-04DOI: 10.1016/j.omega.2025.103422
Decheng Wang , Zhihui Fan , Yarong Liu , Ilkyeong Moon
Trailer detention at delivery locations, frequently caused by the time-consuming (un)packing process, presents a significant challenge in container drayage. Despite extensive research on container drayage, the specific issues stemming from trailer detention remain relatively underexplored. This study addresses a trailer-detention-constrained multi-trailer drop-and-pull container drayage problem, incorporating flexible service starting times and time windows. The detained trailers differ from standard trailers as they require only a single pickup operation within the planning horizon, rather than the typical two-step delivery and subsequent pickup. These pickup operations must be completed within specified time windows due to their potential to disrupt logistics efficiency and often require time-sensitive handling. Furthermore, time windows are imposed on normal trailer deliveries, as these operations initiate the (un)packing process, which can impact the operational efficiency of customer activities. The problem involves tractors capable of towing multiple trailers, utilizing the drop-and-pull method for detachment and reattachment. Tractors possess the flexibility to select their service starting times. To address the inherent complexity of this problem, a mixed-integer programming model is developed alongside a tailored heuristic algorithm. The algorithm leverages a modified Clarke-and-Wright algorithm to generate both rapid and high-quality initial solutions. It strategically integrates the mathematical model, ensuring solution quality is maintained without compromising computational efficiency. To further enhance solution efficiency, a route-based release-fix-optimize method is implemented. Extensive computational experiments validate the efficacy of the proposed methods and examine the impact of time windows and detained inbound and outbound requests on transportation plans, offering valuable insights for effectively managing logistics systems.
{"title":"A trailer-detention-constrained multi-trailer drop-and-pull container drayage problem with flexible service starting time and time windows","authors":"Decheng Wang , Zhihui Fan , Yarong Liu , Ilkyeong Moon","doi":"10.1016/j.omega.2025.103422","DOIUrl":"10.1016/j.omega.2025.103422","url":null,"abstract":"<div><div>Trailer detention at delivery locations, frequently caused by the time-consuming (un)packing process, presents a significant challenge in container drayage. Despite extensive research on container drayage, the specific issues stemming from trailer detention remain relatively underexplored. This study addresses a trailer-detention-constrained multi-trailer drop-and-pull container drayage problem, incorporating flexible service starting times and time windows. The detained trailers differ from standard trailers as they require only a single pickup operation within the planning horizon, rather than the typical two-step delivery and subsequent pickup. These pickup operations must be completed within specified time windows due to their potential to disrupt logistics efficiency and often require time-sensitive handling. Furthermore, time windows are imposed on normal trailer deliveries, as these operations initiate the (un)packing process, which can impact the operational efficiency of customer activities. The problem involves tractors capable of towing multiple trailers, utilizing the drop-and-pull method for detachment and reattachment. Tractors possess the flexibility to select their service starting times. To address the inherent complexity of this problem, a mixed-integer programming model is developed alongside a tailored heuristic algorithm. The algorithm leverages a modified Clarke-and-Wright algorithm to generate both rapid and high-quality initial solutions. It strategically integrates the mathematical model, ensuring solution quality is maintained without compromising computational efficiency. To further enhance solution efficiency, a route-based release-fix-optimize method is implemented. Extensive computational experiments validate the efficacy of the proposed methods and examine the impact of time windows and detained inbound and outbound requests on transportation plans, offering valuable insights for effectively managing logistics systems.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"138 ","pages":"Article 103422"},"PeriodicalIF":7.2,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145026483","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}
Pub Date : 2025-09-03DOI: 10.1016/j.omega.2025.103418
Kemeng Liu , Gang Li
Social influence, such as snobbish and conformity effects, is believed to play a fundamental role in conspicuous consumption. The rapidly growing market for second-hand luxury products, particularly in the form of consumer-to-consumer (C2C) resale, presents a new opportunity for the conspicuous goods industry. To evaluate the impact of the C2C resale market on conspicuous consumption, we develop a monopoly model over two usage periods, where two types of conspicuous consumers can trade used products on the resale market. We first examine the implications of social influence on conspicuous goods, providing insights into how such products are priced. Then the impact of the C2C resale market on luxury market performance is explored. Interestingly, we find that it prompts different strategic behaviors among snobs and conformists, generating the “trendsetting-following effect.” Furthermore, social externalities within the conspicuous framework amplify the value enhancement effect and mitigate the cannibalization effect of secondary markets on the retailer, ultimately driving market expansion and boosting the retailer’s profit. Although the presence of a secondary market lowers the retail price in the primary market, it increases the retailer’s profit under certain conditions, while it always boosts consumer surplus and social welfare, resulting in a win-win-win situation for consumers, the retailer, and society.
{"title":"Trendsetting in conspicuous consumption: The impact of a resale market","authors":"Kemeng Liu , Gang Li","doi":"10.1016/j.omega.2025.103418","DOIUrl":"10.1016/j.omega.2025.103418","url":null,"abstract":"<div><div>Social influence, such as snobbish and conformity effects, is believed to play a fundamental role in conspicuous consumption. The rapidly growing market for second-hand luxury products, particularly in the form of consumer-to-consumer (C2C) resale, presents a new opportunity for the conspicuous goods industry. To evaluate the impact of the C2C resale market on conspicuous consumption, we develop a monopoly model over two usage periods, where two types of conspicuous consumers can trade used products on the resale market. We first examine the implications of social influence on conspicuous goods, providing insights into how such products are priced. Then the impact of the C2C resale market on luxury market performance is explored. Interestingly, we find that it prompts different strategic behaviors among snobs and conformists, generating the “trendsetting-following effect.” Furthermore, social externalities within the conspicuous framework amplify the value enhancement effect and mitigate the cannibalization effect of secondary markets on the retailer, ultimately driving market expansion and boosting the retailer’s profit. Although the presence of a secondary market lowers the retail price in the primary market, it increases the retailer’s profit under certain conditions, while it always boosts consumer surplus and social welfare, resulting in a win-win-win situation for consumers, the retailer, and society.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"138 ","pages":"Article 103418"},"PeriodicalIF":7.2,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145057232","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}