Omega-international Journal of Management Science最新文献

{"title":"Enhanced efficiency assessment in manufacturing: Leveraging machine learning for improved performance analysis","authors":"Maria D. Guillen ,&nbsp;Vincent Charles ,&nbsp;Juan Aparicio","doi":"10.1016/j.omega.2025.103300","DOIUrl":"10.1016/j.omega.2025.103300","url":null,"abstract":"<div><div>This paper introduces EATBoosting, a novel application of gradient tree boosting within the Data Envelopment Analysis (DEA) framework, designed to address undesirable outputs in printed circuit board (PCB) manufacturing. Recognizing the challenge of balancing desirable and undesirable outputs in efficiency assessments, our approach leverages machine learning to enhance the discriminatory power of traditional DEA models, facilitating more precise efficiency estimations. By integrating gradient tree boosting, EATBoosting optimizes the handling of complex data patterns and maximizes accuracy in predicting production functions, thus improving upon the deterministic nature of conventional DEA and Free Disposal Hull methods. The practicality of our approach is demonstrated through its application to a PCB assembly process, highlighting its capacity to discern subtle inefficiencies that traditional methods might overlook. This methodology not only enriches the analytical toolkit available for operational efficiency analysis but also sets a precedent for incorporating advanced machine learning techniques in performance evaluation across various industries. Looking forward, the continued integration of such innovative methods promises to revolutionize efficiency analysis, making it more adaptive to complex industrial challenges and more reflective of real-world production dynamics. This work not only broadens the scope of DEA applications but also invites further research into the integration of machine learning to refine performance measurement and management.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"134 ","pages":"Article 103300"},"PeriodicalIF":6.7,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143436418","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":"Acknowledgement to Reviewers","authors":"","doi":"10.1016/S0305-0483(25)00022-2","DOIUrl":"10.1016/S0305-0483(25)00022-2","url":null,"abstract":"","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"133 ","pages":"Article 103296"},"PeriodicalIF":6.7,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387143","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":"Variable range measure: A new range measure for super-efficiency model based on DDF in presence of nonpositive data","authors":"Hsuan-Shih Lee","doi":"10.1016/j.omega.2025.103295","DOIUrl":"10.1016/j.omega.2025.103295","url":null,"abstract":"<div><div>In order to handle the nonpositive data and increase the discrimination power, we propose a new DDF super-efficiency model called variable range measure (VRM). VRM is translation-invariant and unit-invariant. VRM is feasible when data set contains zero or negative data. The super-efficiency obtained by VRM is less than or equal to two. Range adjusted measure (RAM) makes input contraction and output expansion along the direction vector in a balanced way, but it is target-invariant. The range directional model (RDM) for super-efficiency might be infeasible, but it is target-variant. We combine the advantages of RAM and RDM into VRM so that VRM is target-variant and feasible under super-efficiency. Output vector of the direction vector proposed by Lin and Liu (2019) (LL model) might be zero for some DMUs. VRM overcomes the shortcomings of the LL model. We show that the VRM direction vector is a good proxy of the RAM direction vector by examples.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"134 ","pages":"Article 103295"},"PeriodicalIF":6.7,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387072","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 mixed integer programming approach to address cumulative threats in multi action management plans for biodiversity recovery","authors":"José Salgado-Rojas ,&nbsp;Eduardo Álvarez-Miranda ,&nbsp;Virgilio Hermoso","doi":"10.1016/j.omega.2025.103282","DOIUrl":"10.1016/j.omega.2025.103282","url":null,"abstract":"<div><div>Traditionally, most of the prioritization models used by researchers and practitioners, rely on spatially dichotomous settings for threats, for species and for actions’ benefit; i.e., threats and species are present with equal intensity in some territorial units (while in the other units are not present at all), and actions have impact only on those units where they are applied. However, when dealing with ecological phenomena on large and complex territories, characterized by different areas (such as multiple realms or large river basins) and different spatial connectivity patterns among them, such a dichotomous setting does not capture the spatial (cumulative) diffusion of threats and thus actions’ benefits. Hence, common conservation planning tools are likely to misestimate the benefits of actions and the impact of threats, yielding less effective solutions. In order to address this issue, we develop a framework for designing multi-action prioritization plans featuring threats and actions’ benefit spatial diffusion. Our framework relies on a mathematical programming model that identifies priority areas for the implementation of management actions for multiple threats across a complex and large landscape. We consider the particular case an ecological setting characterized by different realms, multiple threats, and multiple species. We use the Tagus River (Iberian Peninsula) as a case study, including four realms (terrestrial, freshwater, estuary, and marine), where we integrate three different types of spatial connectivity: longitudinal along rivers, and multidimensional in the estuary and marine realms. We simulate the spatial diffusion of threats across the study area using four types of decay models (dispersal kernels): one exponential kernel, two negative triangular kernels (medium and high), and no dispersal. The results show how the MIP-based methodology offers a flexible and practical strategy for incorporating the cumulative effects of threats into action management planning. Furthermore, the primal-MIP heuristic was demonstrated to be a noteworthy alternative for finding good bounds of the original MIP model.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"133 ","pages":"Article 103282"},"PeriodicalIF":6.7,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143166784","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":"Homing strategies for asymmetric sellers on differentiated platforms","authors":"Xiang Li,&nbsp;Meiqi Wang","doi":"10.1016/j.omega.2025.103284","DOIUrl":"10.1016/j.omega.2025.103284","url":null,"abstract":"<div><div>With the flourishing development of e-marketplace platforms, sellers’ homing strategies have attracted considerable attention and require careful evaluation of the market environment, especially considering platform competition. This study explores two asymmetric sellers' homing and pricing strategies on two asymmetric platforms. The platforms and sellers are differentiated in their credits and boast varied consumers’ willingness to pay. We identify the competition-mitigating effects of utilizing an inferior platform and adopting single-homing strategies. We indicate that such effects should be carefully considered in balance with the valuation-enhancing effect of choosing a superior platform and the market-expanding effect of adopting multi-homing strategy. Moreover, in some situations, the benefits of seller prioritization of platform occupancy and implementation of an “either-or” policy (i.e., mandatory single-homing policy for sellers) can be less than expected. These results enhance our understanding of homing strategy optimization in the face of competition between sellers and platforms.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"133 ","pages":"Article 103284"},"PeriodicalIF":6.7,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143166786","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":"Strategic buyer stockpiling in supply chains under uncertain product availability and price fluctuation","authors":"Shanshan Li ,&nbsp;Yong He ,&nbsp;Shibo Jin ,&nbsp;Xue Yan","doi":"10.1016/j.omega.2025.103283","DOIUrl":"10.1016/j.omega.2025.103283","url":null,"abstract":"<div><div>Due to concerns about potential product shortages and price increases from an unforeseen production disruption of uncertain length, strategic buyers might decide to stockpile extra products. Such stockpiling behavior could amplify the disruption-induced imbalance between demand and supply, leading to new stockpiling-driven shortages. This paper studies the interaction between product shortages and stockpiling behavior, and the identification and optimization of such stockpiling behavior. Firstly, considering both strategic and non-strategic buyers, the forecasting of stockpiling-driven product shortage is analyzed. Then, by maximizing the perceived value of hoarding for strategic buyers, a stockpiling time model and strategies are proposed. The stockpiling-driven shortages fall into three patterns, mainly depending on the proportion of strategic buyers in the market, the intensity and duration of production interruption, and the product availability linked to the uninterrupted manufacturer. The optimal stockpiling strategy may appear in five scenarios, i.e., “stockpiling at the beginning of disruption”, “stockpiling before the product price rises”,“stockpiling when the product price rises”, “stockpiling after the product price rises”, and “non-stockpiling”. The decision mainly depends on the trade-off between the determined inventory holding cost at the present stage and the uncertain future loss caused by price increases and stock-outs. To be specific, inventory holding cost, the length of product shortages triggered by strategic buyers’ dynamic stockpiling behavior, and the shortfall level in real-time production linked with buyer composition, disruption intensity, and manufacturer's capability.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"133 ","pages":"Article 103283"},"PeriodicalIF":6.7,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143166785","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":"Multi-view reject inference for semi-supervised credit scoring with consistency training and three-way decision","authors":"Haoxin Tang,&nbsp;Decui Liang","doi":"10.1016/j.omega.2025.103280","DOIUrl":"10.1016/j.omega.2025.103280","url":null,"abstract":"<div><div>In credit scoring, reject inference based on semi-supervised learning has shown better performance compared to those based on statistical methods. However, the problem of inconsistent data distribution between accepted and rejected samples still exists during model training, which may violate the smoothness assumption of semi-supervised learning. Besides, multi-view learning has demonstrated its effectiveness, but its validity in reject inference still needs to be verified. Therefore, this paper proposes a multi-view reject inference approach (MRIA) based on three-way decision and consistency training. Specifically, with the aid of three-way decision, we sift valuable rejected samples from the profitability and accuracy objects, which brings the rejected samples better approximate the smooth assumption of semi-supervised learning. Then, based on the above-mentioned two objects, we construct multi-views by utilizing feature selection and train the reject inference model using consistency training, which can enhance the reliability and robustness. Finally, a dynamic fusion method built on the distance to model (DM) is employed for multi-view fusion. This paper not only theoretically demonstrates that high-quality data augmentation consistency training can result in a smaller error bound for the reject inference tasks, but also verifies the effectiveness of MRIA via a series of experimental analysis.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"133 ","pages":"Article 103280"},"PeriodicalIF":6.7,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143166847","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":"When learning from limited experience takes off: Linear/curvilinear relationships between decision-making comprehensiveness and sustainable supply chain performance under contingent conditions","authors":"Tessa Tien Nguyen ,&nbsp;Angelina Nhat Hanh Le ,&nbsp;Wesley J. Johnston ,&nbsp;Julian Ming Sung Cheng","doi":"10.1016/j.omega.2025.103285","DOIUrl":"10.1016/j.omega.2025.103285","url":null,"abstract":"<div><div>Studies examining the effect of sustainability decision-making comprehensiveness among supply chain alliances on sustainable supply chain management (SSCM) performance have been underrepresented in the current literature. This linking relationship is investigated herein through the theoretical lens of the Organizational Learning Curve (OLC) and Learning from Limited Experience (LLE), and detailed insights under contingent conditions are also provided. The field research is based on a mixed-method approach, including two sequential studies—a quantitative survey followed by a qualitative study in Vietnam. Their results confirm and validate the proposed <em>J</em>-shaped, curvilinear effects of sustainability decision-making comprehensiveness on economic and social sustainability performances and a linear effect on environmental sustainability performance. Moreover, competitive intensity and opportunism moderate these direct effect relationships. We contribute to a crucial gap within the SSCM literature and expand the applications of both OLC and LLE while drawing up a set of practical guidelines in the studied subject matter.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"134 ","pages":"Article 103285"},"PeriodicalIF":6.7,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143214718","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":"Economic and environmental impacts of ecolabeling under different product cost structures","authors":"Sai Zhao,&nbsp;Hongbo Duan","doi":"10.1016/j.omega.2025.103275","DOIUrl":"10.1016/j.omega.2025.103275","url":null,"abstract":"<div><div>The environmental quality of a product is often a credence attribute for consumers, remaining unobservable even after purchase and use. To enhance consumer trust, firms can adopt ecolabels initiated by third-party organizations. This paper investigates the impact of ecolabeling on firms, consumers, and the environment in a differentiated market under different product cost structures. Two product types are analyzed based on the costs of quality improvement: marginal cost-intensive products (MIPs) and development-intensive products (DIPs). We find that for MIPs, both firms consistently choose the same certification strategy, whereas for DIPs, asymmetric strategies may occur in equilibrium under certain labeling standards. When both firms adopt certification (i.e., full adoption), ecolabeling can (weakly) reduce firm profits and consumer surplus. However, when only one firm adopts the label (i.e., partial adoption), it generally benefits the certified firm and consumers. Although the introduction of ecolabeling helps to improve the environment, a higher labeling standard does not necessarily translate to better environmental outcomes. Actually, in a highly competitive market with strong consumer environmental awareness, inducing partial adoption with a high standard is more effective than achieving full adoption with a low standard. Additionally, we extend our model to incorporate more general settings, such as cost asymmetry, price competition, consumer heterogeneity, and partial consumer trust in uncertified products, to enhance our managerial insights.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"133 ","pages":"Article 103275"},"PeriodicalIF":6.7,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143166849","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":"Using explainable deep learning to improve decision quality: Evidence from carbon trading market","authors":"Yang Zhao,&nbsp;Jianzhou Wang,&nbsp;Shuai Wang,&nbsp;Jingwei Zheng,&nbsp;Mengzheng Lv","doi":"10.1016/j.omega.2025.103281","DOIUrl":"10.1016/j.omega.2025.103281","url":null,"abstract":"<div><div>To achieve the United Nations Sustainable Development Goals (SDGs), reducing global greenhouse gas emissions is a top priority. Academia and industry have recognized the importance of carbon market management in promoting low-carbon development. However, traditional methods exhibit limitations in balancing accuracy and explainability, thereby reducing trust between users and decision-making models. To address this, we develop a data-driven model to enhance decision quality. Specifically, we evaluate and compare deep learning (DL) algorithms of various structures to explore the most appropriate techniques for modeling high-dimensional nonlinear carbon price data. Furthermore, we incorporate model-agnostic interpretation techniques to infer the contribution of the influencing factors to carbon prices. The results indicate that the predictive performance of the DL algorithm after feature selection and parameter optimization significantly improves. The findings reveal Internet big data and geopolitical risks as key features of carbon prices, complementing traditional indicators such as energy prices, economy, and climate, which exhibit lagged effects, regional heterogeneity, and interaction. These findings deepen our understanding of carbon price formation mechanisms and bolster managers’ ability to utilize artificial intelligence for effective decision-making, thereby supporting the achievement of the SDGs.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"133 ","pages":"Article 103281"},"PeriodicalIF":6.7,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143166848","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}