{"title":"Strengthening omnichannel supply chain resilience through circular economy integration: A case-based analysis of disruption preparedness strategies","authors":"Ehsan Torshizi , Mobina Mousapour Mamoudan , Maziar Yazdani","doi":"10.1016/j.omega.2025.103466","DOIUrl":"10.1016/j.omega.2025.103466","url":null,"abstract":"<div><div>The increasing frequency and severity of global disruptions have underscored the structural vulnerabilities of conventional supply chains, particularly those optimized solely for efficiency. This study addresses a critical gap at the intersection of omnichannel logistics and circular economy integration by proposing a unified, resilience-oriented optimization model. The integration of these two paradigms is essential: while omnichannel networks inherently involve complex bidirectional flows, circular economy strategies provide built-in redundancy and resource recirculation capabilities. However, existing literature largely overlooks their combined potential for proactive disruption preparedness. To bridge this gap, we develop a mathematical model that simultaneously optimizes forward logistics (including facility siting, inventory allocation, cross-docking, and multimodal transport) and reverse flows (returns handling, material recovery, and recycling). Circular economy decisions are modeled as endogenous variables that dynamically adapt to disruption scenarios, allowing real-time reconfiguration of fulfillment strategies across online, in-store, and humanitarian channels. The model is validated through a real-world application in a national-scale canned food supply network. Results suggest the model maintains performance across varying disruption intensities and operational scales, revealing key trade-offs between profit efficiency, environmental impact, and service responsiveness. The findings highlight that resilience is most effectively achieved through anticipatory strategies such as capacity flexibility and fulfillment agility, rather than through reactive or compliance-driven measures alone. This study offers a scalable decision-support tool for practitioners and policymakers seeking to design sustainable, adaptive, and disruption-resilient omnichannel supply chains.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"141 ","pages":"Article 103466"},"PeriodicalIF":7.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145840662","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":"How the customer purchase pattern changes when increasing product diversity: Theory and empirical evidence from the airline industry","authors":"Changchun Liu , Xi Xiang","doi":"10.1016/j.omega.2025.103485","DOIUrl":"10.1016/j.omega.2025.103485","url":null,"abstract":"<div><div>This paper examines the impact of introducing a new fare product on consumer purchasing behavior within the established framework of airline price discrimination strategies. Specifically, it analyzes changes in the sales distribution of existing fare products following the implementation of the new option. We first present a model that captures the essential characteristics of airline price discrimination and elucidates how the introduction of a new fare product influences firm revenue, consumer surplus, and customer decision-making. Through close collaboration with industry stakeholders, we identify two critical factors that significantly affect practical pricing strategies and consumer choice behavior: the operational use of load factor metrics and the heterogeneity in customer valuations across different fare products. Building on these industry insights, we investigate how the introduction of a new fare product interacts with load factor constraints and the misestimation of valuation differences between fare products, ultimately shaping consumer responses. In the empirical component of the study, we utilize transaction-level data from a major airline to validate the model’s predictions and derive additional managerial insights. Our analysis reveals a strong association between load factor levels and customer purchasing patterns. Moreover, the accurate estimation of the valuation gap across fare products proves to be a crucial determinant of consumer behavior. The joint analysis of load factor and valuation heterogeneity highlights their intertwined role in shaping observed purchase dynamics, demonstrating that load factor considerations and valuation misalignments jointly influence market outcomes.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"141 ","pages":"Article 103485"},"PeriodicalIF":7.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145735254","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":"Behavior-Based Pricing strategy of quality-differentiated products with imperfect customer recognition capability","authors":"Tao Jiang , Kaigeng Shen , Youwei Guo , Lei Guan","doi":"10.1016/j.omega.2025.103488","DOIUrl":"10.1016/j.omega.2025.103488","url":null,"abstract":"<div><div>The development of data technology has enabled firms to identify and analyze consumers’ purchase history and classify them into new and old customers for price discrimination. However, this type of price discrimination tends to cause customer dissatisfaction and lead to resistance against firms’ data-driven pricing practices. Consequently, it challenges firms’ customer recognition capability. This paper develops a two-period pricing model in which two firms, differing in product quality, investigate the impact of behavior-based pricing (BBP) on firms with varying quality levels when they possess imperfect customer recognition capability. We find, first, that imperfect customer recognition capability causes different effects on price in each period for firms of different quality, depending on the level of product quality differentiation. Second, quality advantages do not always lead to more markets for high-quality firms; low-quality firms are also in a position to gain more markets. Third, due to firms’ customer recognition capability and quality differentiation, when both firms adopt BBP, they will both achieve higher profits and reach a ”win–win” situation. Conversely, if only one firm adopts BBP, it will result in reduced profitability for both firms, leading to a ”lose–lose” scenario. Finally, we have examined consumer surplus and social welfare, and the findings provide a theoretical foundation and policy recommendations for governments to develop regulatory measures against price discrimination in the digital economy era.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"141 ","pages":"Article 103488"},"PeriodicalIF":7.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884133","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":"Target Setting for the Digital Economy in China: A DEA Bargaining Approach with General Production Network Structure","authors":"Ming-Miin Yu , Sebastián Lozano , Kok Fong See","doi":"10.1016/j.omega.2025.103459","DOIUrl":"10.1016/j.omega.2025.103459","url":null,"abstract":"<div><div>Over the past two decades, China's digital economy (DE) has grown significantly, and this is mainly due to investments in digital infrastructure, technological advancements, and government support. Despite this growth, regional disparities and sustainability challenges persist. This study aims to develop a more realistic and equitable target-setting framework for improving DE performance across provinces in China. We propose a generalized Network Data Envelopment Analysis (NDEA) model with a Nash bargaining mechanism, which allows cooperative optimization of inputs, intermediate products, and outputs among stages and subprocesses within a network production structure. The methodological innovation lies in its ability to capture interdependencies among subprocesses and distinguish between desirable, undesirable, and neutral intermediate products, thereby integrating green development considerations. Our empirical results show substantial improvement potential across provinces, with differentiated targets in areas such as energy consumption, software income, and e-commerce sales. The proposed model not only advances methodological development in the NDEA but also provides policymakers with a practical tool for promoting balanced regional development and sustainable digital transformation in China.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"141 ","pages":"Article 103459"},"PeriodicalIF":7.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145788002","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":"The roles of lean and corporate social responsibility in acquisitions","authors":"Yuqi Peng , Zhihao Zhang","doi":"10.1016/j.omega.2025.103483","DOIUrl":"10.1016/j.omega.2025.103483","url":null,"abstract":"<div><div>We study how Lean operations and corporate social responsibility (CSR) jointly influence manufacturers’ decisions to pursue acquisitions. Lean improves efficiency through waste reduction but also removes resource buffers, making firms more cautious about the uncertainty, integration challenges, and potential operational disruptions of acquisitions. In contrast, CSR builds stakeholder trust, buffers risk, and broadens strategic flexibility, which can reduce perceived integration risks and increase willingness to engage in acquisitions. Using data from U.S. manufacturing firms (2005–2016) and bootstrap-based conditional logit models, we find that Lean reduces acquisition likelihood, while CSR attenuates this effect. We further find that the moderating role of CSR can be different, contingent on the multi-dimensional impacts of CSR, where environmental and social CSR dimensions encourage acquisitions, whereas governance discourages them. Theoretical and managerial insights are also discussed.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"141 ","pages":"Article 103483"},"PeriodicalIF":7.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145683750","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":"User ecology: The optimal ecology construction and product upgrade strategies","authors":"Yusheng Wang , Yongjian Li , Fangchao Xu","doi":"10.1016/j.omega.2025.103511","DOIUrl":"10.1016/j.omega.2025.103511","url":null,"abstract":"<div><div>Firms are now promoting interactions among users by constructing user ecology, thereby fostering a intra-user network effect to enhance the value proposition of their products. However, compatibility, a pivotal attribute of such ecology, may potentially transform this potent network effect into a double-edged sword, particularly from the upgrade perspective. This study develops a stylized model to explore the interplay between upgrade strategy and user ecology construction. Initially, we analyze the optimal upgrade strategies for firms, distinguishing between those with no/partial/comprehensive user ecology. Subsequently, we carry out the analysis of the optimal design for the user ecology. Moreover, we explore the effectiveness of strategically disposing of partial ecology. The primary findings illustrate the importance of upgrade costs in scenarios without user ecology, where the line-extension strategy dominants the replacement strategy. In the presence of user ecology, we elucidate the demand aggregation effect that may hinder users from buying a new-generation product. Consequently, the replacement strategy emerges as optimal when product differentiation is low. Intriguingly, the existence of user ecology may impede firms from introducing new-generation products. The construction of user ecology provides advantages for firms in emerging markets but may be detrimental in mature markets. Furthermore, our results highlight that comprehensive user ecology may compromise firm’s profit. Disposing of partial ecology strategically can enhance performance, especially when both network effect and product differentiation are low. Lastly, we further investigate the impact of repeat purchases, proportion of new users, and compatibility of the ecology on the main results.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"141 ","pages":"Article 103511"},"PeriodicalIF":7.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145976939","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":"The stochastic production routing problem with adaptive routing and service level constraints","authors":"Ali Kermani, Jean-François Cordeau, Raf Jans","doi":"10.1016/j.omega.2025.103496","DOIUrl":"10.1016/j.omega.2025.103496","url":null,"abstract":"<div><div>Demand uncertainty poses a challenge to most companies in manufacturing and services as it can lead to significant profit losses if not addressed properly. To deal with this risk, companies may adopt specific service level targets to satisfy at least a certain proportion of their demand while considering operational constraints and minimizing the total cost. In this study we address the stochastic production routing problem (PRP) with adaptive routing and service level constraints. The PRP unifies the production, inventory and routing decisions into an integrated problem aimed at improving coordination across different parts of the system. We consider four different types of service levels, where each type uses a specific metric based on assumptions aligning with the needs of the company. These metrics encompass aspects such as the occurrence of stockouts or allowed ratios of backlogs or backorders to average demand. A two-stage stochastic formulation is proposed for each type of service level. Setup decisions are made in the first stage, and production, inventory, and routing decisions are adapted after demand realization. Considering routing decisions in the second stage increases flexibility while lowering overall costs. However, the resulting optimization problem is more challenging to solve than the case where routing decisions are made in the first stage. To address this issue, we introduce an iterative matheuristic algorithm designed to yield high-quality solutions within a reasonable computation time. The effectiveness of the proposed heuristic algorithm is demonstrated through extensive experiments, highlighting its potential to assist companies in managing demand uncertainty and enhancing operational efficiency.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"141 ","pages":"Article 103496"},"PeriodicalIF":7.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145840660","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":"Robust infrastructure design for Carbon Capture Utilization and Storage considering carbon emission uncertainty","authors":"Bei Lin , Xiaoyu Ji , Yingtong Wang , Yingfu He","doi":"10.1016/j.omega.2026.103512","DOIUrl":"10.1016/j.omega.2026.103512","url":null,"abstract":"<div><div>Carbon Capture, Utilization, and Storage (CCUS) is pivotal for achieving carbon neutrality, while its large-scale, cost-effective deployment faces challenges regarding infrastructure integration, emission uncertainty, and policy design. This study proposes a novel hierarchical adaptive robust optimization framework for the robust infrastructure design for CCUS under carbon emission uncertainty. Methodologically, the framework integrates strategic hub location with robust infrastructure and flow planning through a bilevel decomposition: an upper-level K-means++ clustering-based heuristic endogenously identifies hub configurations, while a lower-level adaptive robust model optimizes pipeline establishment, storage selection, and transport flows. To ensure computational tractability, we develop an Enhanced Column-and-Constraint Generation algorithm incorporating a modified outer approximation method. We validate the framework using realistic case studies, yielding several insights. First, emission uncertainty plays only a subordinate role in strategic hub selection, as both hub configurations and major pipelines remain stable across uncertainty budgets. This finding suggests that planners can make investment decisions with confidence. Second, storage choices are highly sensitive to the interplay between oil prices and sink-specific subsidies, underscoring the need for flexible and diversified storage portfolios. Third, dynamic subsidies that adjust based on oil market conditions can effectively shift storage toward saline aquifers at modest fiscal costs. This proposed framework thus provides a decision-support tool for CCUS planning, offers quantitative evidence for policy design, and enables CCUS planning decisions to align with societal carbon neutrality goals.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"141 ","pages":"Article 103512"},"PeriodicalIF":7.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145976938","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}
Florian Linß , Mike Hewitt , Janis S. Neufeld , Udo Buscher
{"title":"Multi-objective optimization with order acceptance for the cumulative job shop scheduling problem in agribusiness","authors":"Florian Linß , Mike Hewitt , Janis S. Neufeld , Udo Buscher","doi":"10.1016/j.omega.2025.103504","DOIUrl":"10.1016/j.omega.2025.103504","url":null,"abstract":"<div><div>Developing new crop species is crucial for addressing global food challenges and improving agricultural efficiency. In agribusiness, this process involves systematically growing and assessing numerous crop variants under controlled conditions to determine their yield potential and adaptability. Formally, this is a job shop scheduling problem because the crops can be understood as jobs that may have different processing sequences on the resources (e.g., greenhouses). However, since the resources can process several jobs simultaneously, a cumulative job shop problem arises. The primary objective is to maximize the number of accepted jobs from a job pool with given release and due dates. The secondary objective is to minimize delays in job processing, i.e., the jobs’ waiting times, as earlier completion of jobs allows for faster feedback and refinement of future crop variants, ultimately improving the overall testing and development process. In this paper, we formulate this problem as a mixed integer and constraint programming problem. We also show how it can be solved with a flexible hierarchical approach, even for very large problem instances. Comprehensive computational experiments first show that available machine capacity has a greater influence on the objectives than the length of the processing time windows, resulting from the difference between the due and release dates. Secondly, a deviation from the maximum number of accepted jobs disproportionately reduces delays.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"141 ","pages":"Article 103504"},"PeriodicalIF":7.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884134","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 hierarchical Markov decision framework for enhancing critical infrastructure resilience under sequential interdictions","authors":"Zeyu Liu , Xueping Li , Anahita Khojandi","doi":"10.1016/j.omega.2025.103486","DOIUrl":"10.1016/j.omega.2025.103486","url":null,"abstract":"<div><div>The resilience of critical infrastructure systems (CIS) has drawn great attention in recent years due to the increasing number of man-made threats and natural disasters. Although CIS resilience has been extensively studied in the literature, significant gaps still exist, where stochastic attacks, facility interdependencies, and preventive resource allocations have yet to be thoroughly and holistically investigated, limiting the practicality of state-of-the-art research. In this study, we propose a novel two-stage hierarchical optimization framework to enhance CIS resilience under multi-level dependencies. The framework optimizes planning decisions including CIS network design and resource allocation, together with dynamic defense strategies against sequential attacks, resulting in a complex nonlinear optimization model with integer variables. We further derive mathematical properties and design two decomposition-based solution algorithms. Through comprehensive experiments, we show that our decomposition algorithms significantly outperform modern commercial solvers in terms of solution quality and efficiency. Utilizing analytical results, the proposed nested decomposition improves the objective value by over 102% compared with an existing nonlinear approach. A case study is conducted using real-world data from a mid-sized city in the U.S. to provide practical insights, validating the effectiveness of the dynamic policies from our framework against benchmarks.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"141 ","pages":"Article 103486"},"PeriodicalIF":7.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145788043","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}