Pub Date : 2025-10-08DOI: 10.1016/j.omega.2025.103439
Zhaoqi Yang , Shunji Tanaka , Bertrand M.T. Lin
This paper investigates a talent scheduling problem that incorporates daily work capacity constraints and the changeover times between consecutive scenes filmed on the same day. The problem inherently integrates three key optimization challenges: talent scheduling, the traveling salesperson problem, and bin packing. To obtain an optimal solution, we develop two integer linear programming models and a dynamic programming algorithm. Additionally, we introduce a polynomial-time dynamic programming algorithm for the special case where the filming order of all scenes is predetermined. This polynomial-time algorithm is incorporated into a tabu search framework to generate high-quality approximate solutions. Finally, we conduct a computational study to assess the effectiveness and efficiency of all proposed solution approaches. The approach of simplifying the problem structures significantly outperforms other algorithms in solution quality and execution time for large-scale instances.
{"title":"Talent scheduling with daily working capacity and scene changeover times","authors":"Zhaoqi Yang , Shunji Tanaka , Bertrand M.T. Lin","doi":"10.1016/j.omega.2025.103439","DOIUrl":"10.1016/j.omega.2025.103439","url":null,"abstract":"<div><div>This paper investigates a talent scheduling problem that incorporates daily work capacity constraints and the changeover times between consecutive scenes filmed on the same day. The problem inherently integrates three key optimization challenges: talent scheduling, the traveling salesperson problem, and bin packing. To obtain an optimal solution, we develop two integer linear programming models and a dynamic programming algorithm. Additionally, we introduce a polynomial-time dynamic programming algorithm for the special case where the filming order of all scenes is predetermined. This polynomial-time algorithm is incorporated into a tabu search framework to generate high-quality approximate solutions. Finally, we conduct a computational study to assess the effectiveness and efficiency of all proposed solution approaches. The approach of simplifying the problem structures significantly outperforms other algorithms in solution quality and execution time for large-scale instances.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"138 ","pages":"Article 103439"},"PeriodicalIF":7.2,"publicationDate":"2025-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145324668","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 : 2025-10-08DOI: 10.1016/j.omega.2025.103435
Hermilio Vilarinho , Miguel Alves Pereira , Giovanna D’Inverno , Ana S. Camanho
This study presents an innovative approach to assessing service quality in the water supply and wastewater treatment sectors, using directional Benefit-of-the-Doubt (BoD) models tailored to regulator needs. Unlike previous research, this work integrates the regulator preferences throughout the entire evaluation process, from selecting key performance metrics to determining reference weights and validating results through sensitivity analyses. A new index for the Assessment of the Quality of Services (AQS) was constructed using a set of indicators chosen by the regulator, ensuring a direct alignment with regulatory priorities. Additionally, the study examines the relationship between service quality and cost efficiency, the latter computed using the Data Envelopment Analysis (DEA) methodology, to address the inherent tension in the water sector between these often conflicting goals. By providing a comprehensive comparison of wholesale utilities’ performance, the findings highlight that cost efficiency and service quality do not always align. This underscores the need for a balanced regulatory approach that fosters service quality improvements while maintaining cost control, promoting sustainable and effective management of the sector.
{"title":"A composite indicator framework integrating regulator perspectives for assessing water service quality","authors":"Hermilio Vilarinho , Miguel Alves Pereira , Giovanna D’Inverno , Ana S. Camanho","doi":"10.1016/j.omega.2025.103435","DOIUrl":"10.1016/j.omega.2025.103435","url":null,"abstract":"<div><div>This study presents an innovative approach to assessing service quality in the water supply and wastewater treatment sectors, using directional Benefit-of-the-Doubt (BoD) models tailored to regulator needs. Unlike previous research, this work integrates the regulator preferences throughout the entire evaluation process, from selecting key performance metrics to determining reference weights and validating results through sensitivity analyses. A new index for the Assessment of the Quality of Services (AQS) was constructed using a set of indicators chosen by the regulator, ensuring a direct alignment with regulatory priorities. Additionally, the study examines the relationship between service quality and cost efficiency, the latter computed using the Data Envelopment Analysis (DEA) methodology, to address the inherent tension in the water sector between these often conflicting goals. By providing a comprehensive comparison of wholesale utilities’ performance, the findings highlight that cost efficiency and service quality do not always align. This underscores the need for a balanced regulatory approach that fosters service quality improvements while maintaining cost control, promoting sustainable and effective management of the sector.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"138 ","pages":"Article 103435"},"PeriodicalIF":7.2,"publicationDate":"2025-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145265767","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 : 2025-10-08DOI: 10.1016/j.omega.2025.103436
Ziliang Jin , Peixuan Li , Yuanbo Li , Dining Ma , Xuejie Ren , Lingxiao Wu
The imperative to mitigate global warming and reduce greenhouse gas (GHG) emissions has expedited the adoption of shared electric micromobility vehicles and battery swapping in urban transportation systems. This study examines a shared electric micromobility system and proposes a two-stage distributionally robust optimization (DRO) model to assist operators in optimizing battery swapping planning and operations under uncertain battery-swapping demands. To address the budget limitation, we introduce a CVaR-based satisficing index for cost control, facilitating robust target-oriented decision-making. To ensure practical implementation, we further reformulate this model into a tractable form that can be efficiently solved using off-the-shelf solvers. Numerical results derived from real-world data validate the effectiveness of our approach in maintaining total costs within specified budget limits, even under varying levels of uncertainty. Furthermore, the proposed model efficiently manages swapper travel distances for battery swapping while ensuring high service levels across the system, thereby enhancing both efficiency and sustainability. We also conduct numerous numerical experiments to evaluate the reliability of our proposed model by testing it across various parameters. We find that under the three-peak demand pattern, the battery allocation is lower while achieving a higher service level than those obtained under the single-peak pattern.
{"title":"Target-oriented distributionally robust optimization for battery swapping in shared micromobility systems","authors":"Ziliang Jin , Peixuan Li , Yuanbo Li , Dining Ma , Xuejie Ren , Lingxiao Wu","doi":"10.1016/j.omega.2025.103436","DOIUrl":"10.1016/j.omega.2025.103436","url":null,"abstract":"<div><div>The imperative to mitigate global warming and reduce greenhouse gas (GHG) emissions has expedited the adoption of shared electric micromobility vehicles and battery swapping in urban transportation systems. This study examines a shared electric micromobility system and proposes a two-stage distributionally robust optimization (DRO) model to assist operators in optimizing battery swapping planning and operations under uncertain battery-swapping demands. To address the budget limitation, we introduce a CVaR-based satisficing index for cost control, facilitating robust target-oriented decision-making. To ensure practical implementation, we further reformulate this model into a tractable form that can be efficiently solved using off-the-shelf solvers. Numerical results derived from real-world data validate the effectiveness of our approach in maintaining total costs within specified budget limits, even under varying levels of uncertainty. Furthermore, the proposed model efficiently manages swapper travel distances for battery swapping while ensuring high service levels across the system, thereby enhancing both efficiency and sustainability. We also conduct numerous numerical experiments to evaluate the reliability of our proposed model by testing it across various parameters. We find that under the three-peak demand pattern, the battery allocation is lower while achieving a higher service level than those obtained under the single-peak pattern.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"138 ","pages":"Article 103436"},"PeriodicalIF":7.2,"publicationDate":"2025-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145265768","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 : 2025-10-06DOI: 10.1016/j.omega.2025.103432
Anubha Goel , Puneet Pasricha , Juho Kanniainen
In this research, we introduce a novel methodology for the index tracking problem with sparse portfolios by leveraging topological data analysis (TDA). Utilizing persistence homology to measure the riskiness of assets, we introduce a topological method for data-driven learning of the parameters for regularization terms. Specifically, the Vietoris–Rips filtration method is utilized to capture the intricate topological features of asset movements, providing a robust framework for portfolio tracking. Our approach has the advantage of accommodating both and penalty terms without the requirement for expensive estimation procedures. We empirically validate the performance of our methodology against state-of-the-art sparse index tracking techniques, such as Elastic-Net and SLOPE, using a dataset that covers 23 years of S&P 500 index and its constituent data. Our out-of-sample results show that this computationally efficient technique surpasses conventional methods across risk metrics, risk-adjusted performance, and trading expenses in varied market conditions. Furthermore, in turbulent markets, it not only maintains but also enhances tracking performance.
{"title":"Risk reduced sparse index tracking portfolio: A topological data analysis approach","authors":"Anubha Goel , Puneet Pasricha , Juho Kanniainen","doi":"10.1016/j.omega.2025.103432","DOIUrl":"10.1016/j.omega.2025.103432","url":null,"abstract":"<div><div>In this research, we introduce a novel methodology for the index tracking problem with sparse portfolios by leveraging topological data analysis (TDA). Utilizing persistence homology to measure the riskiness of assets, we introduce a topological method for data-driven learning of the parameters for regularization terms. Specifically, the Vietoris–Rips filtration method is utilized to capture the intricate topological features of asset movements, providing a robust framework for portfolio tracking. Our approach has the advantage of accommodating both <span><math><msub><mrow><mi>ℓ</mi></mrow><mrow><mn>1</mn></mrow></msub></math></span> and <span><math><msub><mrow><mi>ℓ</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span> penalty terms without the requirement for expensive estimation procedures. We empirically validate the performance of our methodology against state-of-the-art sparse index tracking techniques, such as Elastic-Net and SLOPE, using a dataset that covers 23 years of S&P 500 index and its constituent data. Our out-of-sample results show that this computationally efficient technique surpasses conventional methods across risk metrics, risk-adjusted performance, and trading expenses in varied market conditions. Furthermore, in turbulent markets, it not only maintains but also enhances tracking performance.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"138 ","pages":"Article 103432"},"PeriodicalIF":7.2,"publicationDate":"2025-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145265764","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 : 2025-10-01DOI: 10.1016/j.omega.2025.103434
Siyuan Yang , Kun An , Jeppe Rich
As cities accelerate public transit decarbonization, battery swapping has emerged as a viable alternative to conventional plug-in charging, offering rapid energy replenishment and reduced service disruption for high-frequency electric bus operations. However, this approach requires an inventory of standby batteries, driving up fixed costs. In addition, optimizing battery charging schedules becomes critical to controlling operational expenses under time-varying electricity pricing. This study proposes a comprehensive optimization framework that jointly determines the number of standby batteries, charging schedules, fleet size, and bus schedules across multiple depots and routes. To solve the model efficiently, a Lagrangian-Trip Chain Selection (LTCS) method is developed. The algorithm is validated using empirical data from a real-world bus network in Jiading District, Shanghai, China. The results demonstrate that the proposed method consistently outperforms alternative approaches, particularly in large-scale instances, delivering high-quality, near-optimal solutions within practical computation times. Specifically, the findings reveal that: i) From an economic standpoint, a battery capacity of 280 kWh is the optimal choice for battery swapping in the studied case; ii) A standby battery inventory equal to 60% of the fleet size—just over half the total vehicles—is sufficient to meet operational requirements.
{"title":"Electric bus battery swapping and charging management across multiple depots","authors":"Siyuan Yang , Kun An , Jeppe Rich","doi":"10.1016/j.omega.2025.103434","DOIUrl":"10.1016/j.omega.2025.103434","url":null,"abstract":"<div><div>As cities accelerate public transit decarbonization, battery swapping has emerged as a viable alternative to conventional plug-in charging, offering rapid energy replenishment and reduced service disruption for high-frequency electric bus operations. However, this approach requires an inventory of standby batteries, driving up fixed costs. In addition, optimizing battery charging schedules becomes critical to controlling operational expenses under time-varying electricity pricing. This study proposes a comprehensive optimization framework that jointly determines the number of standby batteries, charging schedules, fleet size, and bus schedules across multiple depots and routes. To solve the model efficiently, a Lagrangian-Trip Chain Selection (LTCS) method is developed. The algorithm is validated using empirical data from a real-world bus network in Jiading District, Shanghai, China. The results demonstrate that the proposed method consistently outperforms alternative approaches, particularly in large-scale instances, delivering high-quality, near-optimal solutions within practical computation times. Specifically, the findings reveal that: i) From an economic standpoint, a battery capacity of 280 kWh is the optimal choice for battery swapping in the studied case; ii) A standby battery inventory equal to 60% of the fleet size—just over half the total vehicles—is sufficient to meet operational requirements.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"138 ","pages":"Article 103434"},"PeriodicalIF":7.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145265763","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 : 2025-09-30DOI: 10.1016/j.omega.2025.103431
P. Ravelojaona , A. Abad , P.N. Alves Junior , F.S. Pinto , I. Costa-Melo
Environmental concerns have increasingly influenced production processes, particularly in recent years, as natural resources become progressively scarce. Among these, water remains the most critical resource, further exacerbated by climate change and its associated challenges, such as frequent droughts, especially in warm and mild-climate regions like Southern Europe. This study analyzes the performance of the Portuguese water supply sector, focusing on a sample of 116 water utilities between 2013 and 2021, representing diverse geographic and management structures. The production process is conceptualized as a non-linear joint-production process, incorporating water losses as an undesirable output within performance evaluations. By applying exponential Hicks-Moorsteen and Malmquist indices within a non-parametric Data Envelopment Analysis framework, this study provides an assessment of the efficiency and productivity trends in the sector. The findings offer insights into how Portuguese water utilities manage resources under environmental and infrastructural constraints, with a focus on reducing water losses and enhancing sustainable practices.
{"title":"Water losses: A productivity analysis of the water supply in Portugal","authors":"P. Ravelojaona , A. Abad , P.N. Alves Junior , F.S. Pinto , I. Costa-Melo","doi":"10.1016/j.omega.2025.103431","DOIUrl":"10.1016/j.omega.2025.103431","url":null,"abstract":"<div><div>Environmental concerns have increasingly influenced production processes, particularly in recent years, as natural resources become progressively scarce. Among these, water remains the most critical resource, further exacerbated by climate change and its associated challenges, such as frequent droughts, especially in warm and mild-climate regions like Southern Europe. This study analyzes the performance of the Portuguese water supply sector, focusing on a sample of 116 water utilities between 2013 and 2021, representing diverse geographic and management structures. The production process is conceptualized as a non-linear joint-production process, incorporating water losses as an undesirable output within performance evaluations. By applying exponential Hicks-Moorsteen and Malmquist indices within a non-parametric Data Envelopment Analysis framework, this study provides an assessment of the efficiency and productivity trends in the sector. The findings offer insights into how Portuguese water utilities manage resources under environmental and infrastructural constraints, with a focus on reducing water losses and enhancing sustainable practices.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"138 ","pages":"Article 103431"},"PeriodicalIF":7.2,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145265765","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 : 2025-09-30DOI: 10.1016/j.omega.2025.103433
Nicky Rogge, Paul Rowley
The National Football League (NFL) introduced a salary cap in 1994 which significantly affected the payroll efficiency of teams within the league. This paper uses a robust directional distance Data Envelopment Analysis (DEA) model to measure and evaluate the payroll efficiency of the 32 teams of the NFL from 2011–2020. The focus is on investigating if teams are more payroll efficient when spending on star players or spreading their expenditure more equally across their squad. Four DEA-models were defined to analyse spending payroll efficiency relating to the overall allocation of salary, star offensive players, star defensive players, and starting quarterbacks. Inputs were relevant salary cap information, while outputs were performance statistics unique to each category. A relationship was discovered between payroll efficiency in each category and qualification for the playoffs and post-season success. Efficient expenditure on star defensive players was especially important.
{"title":"Is it all about the stars? Spending on star players and success in the National Football League","authors":"Nicky Rogge, Paul Rowley","doi":"10.1016/j.omega.2025.103433","DOIUrl":"10.1016/j.omega.2025.103433","url":null,"abstract":"<div><div>The National Football League (NFL) introduced a salary cap in 1994 which significantly affected the payroll efficiency of teams within the league. This paper uses a robust directional distance Data Envelopment Analysis (DEA) model to measure and evaluate the payroll efficiency of the 32 teams of the NFL from 2011–2020. The focus is on investigating if teams are more payroll efficient when spending on star players or spreading their expenditure more equally across their squad. Four DEA-models were defined to analyse spending payroll efficiency relating to the overall allocation of salary, star offensive players, star defensive players, and starting quarterbacks. Inputs were relevant salary cap information, while outputs were performance statistics unique to each category. A relationship was discovered between payroll efficiency in each category and qualification for the playoffs and post-season success. Efficient expenditure on star defensive players was especially important.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"138 ","pages":"Article 103433"},"PeriodicalIF":7.2,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145265144","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 : 2025-09-27DOI: 10.1016/j.omega.2025.103429
Miao Wang , Feng Li , Zhou Xu , Xianyan Yang , Julong Wang
This study addresses an integrated order selection and fulfillment problem in a multi-resource, multi-product, multi-warehouse system. The focus is to determine which orders to serve and which warehouse(s) to utilize to fulfill each accepted order such that the total profit is maximized. To utilize resources more effectively and improve customer satisfaction by providing customers with more options, the products offered by the firm include both specific and flexible products, with the latter representing a set of alternative specific products. Upon acceptance, each flexible product order is allocated an option within its alternative set. The firm’s profit is calculated by subtracting the total transportation and inventory holding costs from the revenue generated by accepted orders. We propose an exact algorithm that achieves a pseudo-polynomial running time in some practical situations. In addition, a column generation-based heuristic algorithm is introduced to efficiently find near-optimal solutions. The computational results demonstrate the effectiveness of this heuristic algorithm, which not only outperforms a commercial optimization solver in terms of computational times but also exhibits the ability to generate near-optimal solutions. Furthermore, we conduct additional experiments to evaluate the effects of varying order quantities and replenishment settings on the performance of the heuristic algorithm, thereby demonstrating its robustness. Additionally, our experiments illustrate the benefits of offering flexible products and evaluate the value of production–transportation integration by comparing the integrated approach with a conventional sequential approach that addresses assembly and transportation independently.
{"title":"Order selection and fulfillment integration with flexible products","authors":"Miao Wang , Feng Li , Zhou Xu , Xianyan Yang , Julong Wang","doi":"10.1016/j.omega.2025.103429","DOIUrl":"10.1016/j.omega.2025.103429","url":null,"abstract":"<div><div>This study addresses an integrated order selection and fulfillment problem in a multi-resource, multi-product, multi-warehouse system. The focus is to determine which orders to serve and which warehouse(s) to utilize to fulfill each accepted order such that the total profit is maximized. To utilize resources more effectively and improve customer satisfaction by providing customers with more options, the products offered by the firm include both specific and flexible products, with the latter representing a set of alternative specific products. Upon acceptance, each flexible product order is allocated an option within its alternative set. The firm’s profit is calculated by subtracting the total transportation and inventory holding costs from the revenue generated by accepted orders. We propose an exact algorithm that achieves a pseudo-polynomial running time in some practical situations. In addition, a column generation-based heuristic algorithm is introduced to efficiently find near-optimal solutions. The computational results demonstrate the effectiveness of this heuristic algorithm, which not only outperforms a commercial optimization solver in terms of computational times but also exhibits the ability to generate near-optimal solutions. Furthermore, we conduct additional experiments to evaluate the effects of varying order quantities and replenishment settings on the performance of the heuristic algorithm, thereby demonstrating its robustness. Additionally, our experiments illustrate the benefits of offering flexible products and evaluate the value of production–transportation integration by comparing the integrated approach with a conventional sequential approach that addresses assembly and transportation independently.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"138 ","pages":"Article 103429"},"PeriodicalIF":7.2,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145265766","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 : 2025-09-25DOI: 10.1016/j.omega.2025.103430
A. Mehrabi, R. Rahimi M., A. Nikoofard
Therapy sessions are widely recognized as an effective form of treatment, with outcomes sometimes more strongly influenced by the quality of therapist–patient interaction and decision-making than by the specific methods employed, prompting extensive empirical investigation into these dynamics. Existing studies overlook individual differences and long-term effects, relying on generalized findings that miss the complexity of human interactions and therapeutic decision-making. To address these limitations, this study adopts a structured analytical approach that captures the nuanced, evolving nature of therapist–patient interactions and enables long-term insight into how individual behaviors and strategic decisions shape therapeutic trajectories.
Game theory, widely used to optimize and analyze multi-agent decision-making across various domains, provides a powerful framework for this study. By incorporating Nash equilibrium, Bayesian games, and repeated games, the proposed model captures the uncertainty and complexity inherent in real-world interactions. The model highlights the strategic merit of selecting non-cooperative policies under certain conditions and, through simulation analysis, demonstrates that patient behavior has a significantly greater impact on session outcomes compared to that of the therapist. Furthermore, the influence of cooperation becomes more pronounced as the planning horizon extends into the long term. Therapists who adapt their strategies to patient type and behavior can enhance outcomes, while rigidity may hinder progress. The model offers practical value in guiding effective, personalized strategy selection.
{"title":"Navigating uncertainty in human interaction: A management science approach using Bayesian games in therapy","authors":"A. Mehrabi, R. Rahimi M., A. Nikoofard","doi":"10.1016/j.omega.2025.103430","DOIUrl":"10.1016/j.omega.2025.103430","url":null,"abstract":"<div><div>Therapy sessions are widely recognized as an effective form of treatment, with outcomes sometimes more strongly influenced by the quality of therapist–patient interaction and decision-making than by the specific methods employed, prompting extensive empirical investigation into these dynamics. Existing studies overlook individual differences and long-term effects, relying on generalized findings that miss the complexity of human interactions and therapeutic decision-making. To address these limitations, this study adopts a structured analytical approach that captures the nuanced, evolving nature of therapist–patient interactions and enables long-term insight into how individual behaviors and strategic decisions shape therapeutic trajectories.</div><div>Game theory, widely used to optimize and analyze multi-agent decision-making across various domains, provides a powerful framework for this study. By incorporating Nash equilibrium, Bayesian games, and repeated games, the proposed model captures the uncertainty and complexity inherent in real-world interactions. The model highlights the strategic merit of selecting non-cooperative policies under certain conditions and, through simulation analysis, demonstrates that patient behavior has a significantly greater impact on session outcomes compared to that of the therapist. Furthermore, the influence of cooperation becomes more pronounced as the planning horizon extends into the long term. Therapists who adapt their strategies to patient type and behavior can enhance outcomes, while rigidity may hinder progress. The model offers practical value in guiding effective, personalized strategy selection.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"138 ","pages":"Article 103430"},"PeriodicalIF":7.2,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145157158","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 : 2025-09-24DOI: 10.1016/j.omega.2025.103412
Zhixuan Cai , Tianhu Deng , Christopher S. Tang
Recent research has examined the decentralized decisions of two independent parties when the system output is co-produced, i.e., the output depends on the efforts exerted by both parties. In this paper, we present a general modeling framework to reexamine the robustness of the results obtained from this stream of research. To model the decision-making process in a decentralized co-production system, we use the Constant Elasticity of Substitution (CES) function to model the output co-produced from the two parties and consider both simultaneous-move and sequential-move games. We also compare the equilibrium efforts exerted by rational firms and the optimal efforts exerted by presumptive firms. Here, each rational firm makes decisions by anticipating the other firm’s rational decision, whereas each presumptive firm makes decisions based on a prior belief about the other firm’s decision. We show that both simultaneous-move and sequential-move games yield similar structural results. First, the effort exerted by each rational (or presumptive) firm increases with the firm’s “returns on effort investment”. Second, while the efforts exerted by presumptive firms are not in equilibrium, we find that these off-equilibrium efforts can result in higher payoffs than the efforts exerted by rational firms when the prior beliefs are sufficiently high and effort cost factors are sufficiently low. We also apply these results to reexamine some key findings obtained in the recent literature whose co-production model can be viewed as special cases of the CES output function. We find that the existing results based on the special case may not hold under the general CES functions. Hence, our general model and results provide new insights. Finally, we demonstrate how our general model can be applied to examine other settings arising from product development and capacity planning decisions involving two independent parties with self-interests.
{"title":"Rational versus presumptive decisions in a decentralized co-production system: Solutions and applications","authors":"Zhixuan Cai , Tianhu Deng , Christopher S. Tang","doi":"10.1016/j.omega.2025.103412","DOIUrl":"10.1016/j.omega.2025.103412","url":null,"abstract":"<div><div>Recent research has examined the decentralized decisions of two independent parties when the system output is co-produced, i.e., the output depends on the efforts exerted by both parties. In this paper, we present a general modeling framework to reexamine the robustness of the results obtained from this stream of research. To model the decision-making process in a decentralized co-production system, we use the <em>Constant Elasticity of Substitution</em> (CES) function to model the output co-produced from the two parties and consider both simultaneous-move and sequential-move games. We also compare the equilibrium efforts exerted by <em>rational</em> firms and the optimal efforts exerted by <em>presumptive</em> firms. Here, each <em>rational</em> firm makes decisions by anticipating the other firm’s rational decision, whereas each <em>presumptive</em> firm makes decisions based on a prior belief about the other firm’s decision. We show that both simultaneous-move and sequential-move games yield similar structural results. First, the effort exerted by each <em>rational (or presumptive)</em> firm increases with the firm’s “returns on effort investment”. Second, while the efforts exerted by <em>presumptive</em> firms are not in equilibrium, we find that these off-equilibrium efforts can result in higher payoffs than the efforts exerted by <em>rational</em> firms when the prior beliefs are sufficiently high and effort cost factors are sufficiently low. We also apply these results to reexamine some key findings obtained in the recent literature whose co-production model can be viewed as special cases of the CES output function. We find that the existing results based on the special case may not hold under the general CES functions. Hence, our general model and results provide new insights. Finally, we demonstrate how our general model can be applied to examine other settings arising from product development and capacity planning decisions involving two independent parties with self-interests.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"138 ","pages":"Article 103412"},"PeriodicalIF":7.2,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145157160","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}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号