Omega-international Journal of Management Science最新文献_第5页

Managing inventory and financing decisions under ambiguity 在不明确的情况下管理库存和融资决策

IF 7.2 2区管理学

Omega-international Journal of Management Science Pub Date : 2026-04-01 Epub Date: 2025-11-12 DOI: 10.1016/j.omega.2025.103460

Cheng Qian , Zhaolin Li , Qi Fu

{"title":"Managing inventory and financing decisions under ambiguity","authors":"Cheng Qian , Zhaolin Li , Qi Fu","doi":"10.1016/j.omega.2025.103460","DOIUrl":"10.1016/j.omega.2025.103460","url":null,"abstract":"<div><div>This study proposes a robust optimization framework to address the persistent challenges faced by micro and small enterprises (MSEs) in raising capital due to high levels of demand ambiguity. We examine a robust newsvendor model in which the firm has insufficient initial capital and needs to raise capital from an external fund provider. Without knowing the precise demand distribution, both the firm and the fund provider adopt a max–min decision rule based on the mean and variance of the demand. The firm aims to maximize his expected worst-case profit by determining the production quantity, while the fund provider offers equity or loan financing, seeking a fair market-determined return on the contributed capital. We derive the robust production quantity and financing agreements under both equity and loan financing. We show that equity financing attains the system-optimal outcome under distributional ambiguity, and propose a simple formula for the robust interest rate under loan financing. We further generalize our analysis to consider collateral and initial capital, and extend the base model to a robust principal–agent setting where the firm can exert an unobservable effort to influence demand. In the latter case, we show that equity financing outperforms loan financing across a wide range of parameter values, contrary to the existing literature without demand ambiguity. Our analysis offers guidance for practitioners and policymakers seeking effective strategies to promote growth while safeguarding fund providers in the MSE sector.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"140 ","pages":"Article 103460"},"PeriodicalIF":7.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145616286","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}

引用次数: 0

IF 7.2 2区管理学

Omega-international Journal of Management Science Pub Date : 2026-04-01 Epub Date: 2025-11-19 DOI: 10.1016/j.omega.2025.103475

Yishan Han , Biao Xu , Yao Wang , Shanxing Gao

{"title":"Towards popularity-aware recommendation: A multi-behavior enhanced framework with orthogonality constraint","authors":"Yishan Han , Biao Xu , Yao Wang , Shanxing Gao","doi":"10.1016/j.omega.2025.103475","DOIUrl":"10.1016/j.omega.2025.103475","url":null,"abstract":"<div><div>Top-<span><math><mi>K</mi></math></span> recommendation involves inferring latent user preferences and generating personalized recommendations accordingly, which is now ubiquitous in various decision systems. Nonetheless, recommender systems usually suffer from severe <em>popularity bias</em>, leading to the over-recommendation of popular items. Such a bias deviates from the central aim of reflecting user preference faithfully, compromising both customer satisfaction and retailer profits. Despite the prevalence, existing methods tackling popularity bias still have limitations due to the considerable accuracy-debias tradeoff and the sensitivity to extensive parameter selection, further exacerbated by the extreme sparsity in positive user-item interactions.</div><div>In this paper, we present a <strong>Pop</strong>ularity-aware top-<span><math><mi>K</mi></math></span> recommendation algorithm integrating multi-behavior <strong>S</strong>ide <strong>I</strong>nformation (PopSI), aiming to enhance recommendation accuracy and debias performance simultaneously. Specifically, by leveraging multiple user feedback that mirrors similar user preferences and formulating it as a three-dimensional tensor, PopSI can utilize all slices to capture the desiring user preferences effectively. Subsequently, we introduced a novel orthogonality constraint to refine the estimated item feature space, enforcing it to be invariant to item popularity features thereby addressing our model’s sensitivity to popularity bias. Comprehensive experiments on real-world e-commerce datasets demonstrate the general improvements of PopSI over state-of-the-art debias methods with a marginal accuracy-debias tradeoff and scalability to practical applications.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"140 ","pages":"Article 103475"},"PeriodicalIF":7.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145571183","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}

引用次数: 0

Novel causal decision models for human-centric virtual reality platform selection in supply chain risk management 供应链风险管理中以人为中心的虚拟现实平台选择的新因果决策模型

IF 7.2 2区管理学

Omega-international Journal of Management Science Pub Date : 2026-04-01 Epub Date: 2025-10-24 DOI: 10.1016/j.omega.2025.103455

Hamidreza Seiti , Mostafa Shabani , Hossein Ghanbari , Sarah Ben-Amor , Ibrahim A. Hameed

{"title":"Novel causal decision models for human-centric virtual reality platform selection in supply chain risk management","authors":"Hamidreza Seiti , Mostafa Shabani , Hossein Ghanbari , Sarah Ben-Amor , Ibrahim A. Hameed","doi":"10.1016/j.omega.2025.103455","DOIUrl":"10.1016/j.omega.2025.103455","url":null,"abstract":"<div><div>This study addresses the complexities of selecting the optimal Virtual Reality (VR) platform for risk management in Supply Chain Management (SCM), emphasizing the significance of human-centric attributes in this decision-making process. As SCM encompasses the strategic coordination of suppliers, manufacturers, and distributors, the integration of advanced technologies, including VR, becomes essential for enhancing operational efficiency and resilience in today’s dynamic market environments. This paper proposes a novel MADM model that incorporates the R.Graph method to account for the interactions between criteria. We developed two distinct algorithms: the first directly calculates ranks based on attribute interactions, while the second modifies weights to reflect these interactions. By focusing on user experience, accessibility, collaboration features, and other relevant attributes, the model aims to facilitate a comprehensive evaluation of VR platforms. The application of qualitative input data allows for a more nuanced analysis, particularly in scenarios where quantitative data is limited. This research contributes to the understanding of how VR technologies can be leveraged to enhance risk management within supply chains, ultimately fostering greater resilience and adaptability. The findings underscore the importance of aligning technology with organizational objectives and user needs, paving the way for innovation and improved performance in the metaverse. The selected platforms for this study are Bentley Synchro XR and Augmentir, which were identified as the top VR technologies for construction SCM risk management based on our evaluation.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"140 ","pages":"Article 103455"},"PeriodicalIF":7.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145537173","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}

引用次数: 0

UNHRD’s humanitarian support in South Asia via Multistage Stochastic Programming 联合国开发计划署通过多阶段随机规划对南亚的人道主义支持

IF 7.2 2区管理学

Omega-international Journal of Management Science Pub Date : 2026-04-01 Epub Date: 2025-11-15 DOI: 10.1016/j.omega.2025.103464

Ruoyu Hu, Douglas Alem, Aakil Caunhye

{"title":"UNHRD’s humanitarian support in South Asia via Multistage Stochastic Programming","authors":"Ruoyu Hu, Douglas Alem, Aakil Caunhye","doi":"10.1016/j.omega.2025.103464","DOIUrl":"10.1016/j.omega.2025.103464","url":null,"abstract":"<div><div>One of the main tasks of the United Nations Humanitarian Response Depot (UNHRD) relies on allocating relief aid to save people who suffer from disasters. This task is particularly challenging in areas like South Asia, where relief aid efforts are confronted with complex transportation conditions, significant socioeconomic disparities, and the frequent occurrence of disasters, not to mention that financial resources are often scarce. In this paper, we develop a novel Multistage Stochastic Programming model to help UNHRD support critical decisions regarding site selection and relief aid allocation. Differently from the main literature, where these decisions are often made within a two-stage paradigm, our three-stage perspective takes into account in-kind donation campaigns that are triggered depending on the disaster impact and its effects, and is paramount to improving the effectiveness and fairness of the disaster relief operation. Our objective function maximizes the effectiveness of the disaster relief operation, defined as the extent to which it fulfills the needs of the population. Considering that different regions often exhibit distinct coping capacities, the effectiveness measure also factors in a vulnerability score to encourage relief aid allocation to the most in-need populations. The overall results show the importance of in-kind donation to achieve a more equitable relief aid allocation plan and the benefit of targeting more vulnerable regions under severely scarce resources.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"140 ","pages":"Article 103464"},"PeriodicalIF":7.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145571184","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}

引用次数: 0

Two-stage robust optimization approach for integrated supply chain planning with hybrid-dark stores 混合暗店集成供应链规划的两阶段鲁棒优化方法

IF 7.2 2区管理学

Omega-international Journal of Management Science Pub Date : 2026-04-01 Epub Date: 2025-11-27 DOI: 10.1016/j.omega.2025.103479

Youngchul Shin , Younsoo Lee

{"title":"Two-stage robust optimization approach for integrated supply chain planning with hybrid-dark stores","authors":"Youngchul Shin , Younsoo Lee","doi":"10.1016/j.omega.2025.103479","DOIUrl":"10.1016/j.omega.2025.103479","url":null,"abstract":"<div><div>The rapid growth of e-commerce has led to the emergence of dark stores, where traditional brick-and-mortar stores are repurposed into micro-fulfillment centers to meet online demand. Recently, a growing number of retailers have adopted hybrid-dark stores (HDSs), which operate simultaneously as physical retail outlets and fulfillment centers, enabling flexible space allocation and internal inventory transfers across both areas. While this dual functionality offers greater operational agility, it also introduces significant complexity into supply chain operations, particularly under demand uncertainty. To address this challenge, we propose a two-stage robust optimization approach for supply chain planning with HDSs. In the first stage, a target-oriented robust optimization framework determines binary production and space allocation decisions. In the second stage, adaptive recourse actions are taken for the remaining continuous decisions. Computational experiments demonstrate that the proposed approach consistently outperforms benchmark models in terms of cost efficiency and adaptability under demand uncertainty. Furthermore, sensitivity analyses provide managerial insights for practitioners managing supply chains with HDSs.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"140 ","pages":"Article 103479"},"PeriodicalIF":7.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145681766","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}

引用次数: 0

A communication on the paper “An alternative weight sensitivity analysis for PROMETHEE II rankings” 关于论文“PROMETHEE II排名的另一种权重敏感性分析”的交流

IF 7.2 2区管理学

Omega-international Journal of Management Science Pub Date : 2026-04-01 Epub Date: 2025-11-16 DOI: 10.1016/j.omega.2025.103465

Evangelos Triantaphyllou , Richard O’Shea , Yves De Smet , Nguyen Anh Vu Doan

引用次数: 0

Discrete location models with customers’ choice and path improvements 具有客户选择和路径改进的离散位置模型

IF 7.2 2区管理学

Omega-international Journal of Management Science Pub Date : 2026-02-01 Epub Date: 2025-11-04 DOI: 10.1016/j.omega.2025.103458

Inmaculada Espejo , Alfredo Marín

{"title":"Discrete location models with customers’ choice and path improvements","authors":"Inmaculada Espejo , Alfredo Marín","doi":"10.1016/j.omega.2025.103458","DOIUrl":"10.1016/j.omega.2025.103458","url":null,"abstract":"<div><div>We examine several facility location problems within a directed network involving two distinct cost types. The first, referred to as the “customer cost”, represents the expense each customer considers when selecting a facility to obtain service (e.g., delivery time or a measure of quality degradation). Consequently, once facilities are established, each customer chooses the one that minimizes their individual cost. The second type, termed the “company cost”, encompasses all expenses incurred by the company due to customer allocation to their chosen facilities. Additionally, the company possesses a budget that can be allocated to reduce company costs associated with the network’s arcs (the so-called arcs upgrading).</div><div>The company’s objective is to simultaneously determine facility locations and distribute the budget (or a portion of it) across the network arcs to minimize the total company cost. This total company cost comprises the post-upgrading company costs and the invested budget, while accounting for customer reactions after facility placement.</div><div>Different problem variants emerge based on the facility location criteria and customers’ choice strategy. In this paper, we address the following problems: the <span><math><mi>p</mi></math></span>-median problem, a two-stage facility location problem, a single-allocation hub location problem, and a tree-of-hubs location problem — all incorporating customers’ choice and arc upgrading.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"139 ","pages":"Article 103458"},"PeriodicalIF":7.2,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145474873","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}

引用次数: 0

Distributionally robust joint inventory and pricing control across products 分布健壮的联合库存和跨产品的价格控制

IF 7.2 2区管理学

Omega-international Journal of Management Science Pub Date : 2026-02-01 Epub Date: 2025-11-01 DOI: 10.1016/j.omega.2025.103443

Jianjun Xu , Xinyu Bi , Shaoxiang Chen , Feng Liu

{"title":"Distributionally robust joint inventory and pricing control across products","authors":"Jianjun Xu , Xinyu Bi , Shaoxiang Chen , Feng Liu","doi":"10.1016/j.omega.2025.103443","DOIUrl":"10.1016/j.omega.2025.103443","url":null,"abstract":"<div><div>We study a single-period, two-item joint inventory and pricing control problem under demand uncertainty, where only the means and variances of product demands are known. The model incorporates cross-price effects, meaning that the demand for each product is influenced by the prices of both products. To address this, we develop a distributionally robust optimization framework that determines ordering and pricing decisions to maximize the worst-case expected profit over all demand distributions consistent with the known moments. Under certain conditions, we derive closed-form optimal solutions. Theoretical analysis reveals that the economic relationships between products may differ from the perspectives of retailers and customers. We also extend the model to capture additional practical considerations such as customer behavior and supply unreliability. To evaluate the proposed approach, we conduct numerical experiments that demonstrate the closeness of our closed-form solutions to the optimal policies under the true distribution in cases with mild variances, as well as to the results derived from deterministic demand and the Sample Average Approximation method. Furthermore, we analyze the impact of distributional misspecification and find that our DRO-based solutions are more robust. Sensitivity analysis further shows that while variance has a moderate impact on expected profit, increasing variance leads to a greater discrepancy between the worst-case and true expected profit.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"139 ","pages":"Article 103443"},"PeriodicalIF":7.2,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145474874","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}

引用次数: 0

Sorting electric vehicles via online review: A BERT-based behavioral three-way decision model with cardinal-ordinal preferences 基于在线评论的电动汽车分类：基于bert的基数-序数偏好行为三向决策模型

IF 7.2 2区管理学

Omega-international Journal of Management Science Pub Date : 2026-02-01 Epub Date: 2025-10-20 DOI: 10.1016/j.omega.2025.103441

Yiqiang Mu, Dun Liu, Zhihui Zhang

{"title":"Sorting electric vehicles via online review: A BERT-based behavioral three-way decision model with cardinal-ordinal preferences","authors":"Yiqiang Mu, Dun Liu, Zhihui Zhang","doi":"10.1016/j.omega.2025.103441","DOIUrl":"10.1016/j.omega.2025.103441","url":null,"abstract":"<div><div>The electric vehicle (EV) industry plays a crucial role in the global transition to a low-carbon economy. As the EV market rapidly grows and competition intensifies, consumer feedback represented by online reviews is emerging as a critical factor in shaping EV evaluations and driving market success. To address the challenges of EV assessment we propose a novel BERT-driven behavioral three-way decision (BBTWD) model that integrates cardinal consensus and ordinal preferences. The key methodological contributions include (1) the EV-BERT model, a domain-specific sentiment analysis model that incorporates manually labeled EV review data; (2) the cardinal-ordinal preference modeling approach, which combines the minimum consensus cost model (MCCM) and the weighted Borda count method; and (3) the BBTWD method, which integrates the TODIM and three-way decision method to simultaneously account for the risk-aversion and loss-aversion behaviors of the decision-makers. Two case studies demonstrate the effectiveness and robustness of our method. Specifically, the ranking similarity between the proposed model and baseline methods exceeds 0.893 under both the weighted Spearman correlation measure and the weighted similarity measure. Moreover, our method outperforms existing approaches in sentiment analysis, particularly in terms of identifying negative sentiment. In addition, we assess the impact of weight uncertainty and behavioral factors on both the ranking and classification results through simulation and sensitivity analyses. The results confirm the robustness and practicality of the proposed method. This study advances EV evaluation methodologies by bridging sentiment analysis, preference modeling, and behavioral decision-making, offering actionable insights for both consumers and EV manufacturers.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"139 ","pages":"Article 103441"},"PeriodicalIF":7.2,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145365181","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}

引用次数: 0

A Deep & Cross Network-based framework for online food delivery time prediction with driver-specific information 基于深度和交叉网络的基于司机特定信息的在线食品配送时间预测框架

IF 7.2 2区管理学

Omega-international Journal of Management Science Pub Date : 2026-02-01 Epub Date: 2025-11-12 DOI: 10.1016/j.omega.2025.103457

Genshen Fu , Yujie Chi , Li Zheng , Zuo-Jun Max Shen

{"title":"A Deep & Cross Network-based framework for online food delivery time prediction with driver-specific information","authors":"Genshen Fu , Yujie Chi , Li Zheng , Zuo-Jun Max Shen","doi":"10.1016/j.omega.2025.103457","DOIUrl":"10.1016/j.omega.2025.103457","url":null,"abstract":"<div><div>In online food delivery operations, accurate delivery time prediction is crucial, as it underpins effective resource allocation and ensures customer satisfaction. While prediction models can be trained using historical delivery data, there is significant room for improving accuracy, especially in incorporating driver-specific information. However, this task faces several challenges: (1) limited data availability and privacy concerns, (2) driver heterogeneity and data dispersion, and (3) tacit driver knowledge and feature engineering complexity. To tackle these issues, we introduce a Deep & Cross Network-based (DCN-based) framework. This framework utilizes limited driver-specific information and dispersed data to automate feature engineering and enhance prediction accuracy, enabling a more personalized and precise prediction process. It leverages both low-order feature interactions, captured by the Cross Network, and high-order interactions from the Deep Neural Network (DNN), effectively balancing interpretability and predictive power. Extensive experiments using real-world data from Zomato demonstrate that our approach with driver-specific information significantly outperforms both traditional and state-of-the-art models, achieving superior results across all regression accuracy metrics. The best performance yields a root mean square error (RMSE) of 3.6660, representing a 35.93% improvement over models without driver-specific information. Furthermore, the framework’s automatic feature engineering provides deeper insights into the interactions between driver information and external factors, offering a valuable tool for improving online food delivery operations.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"139 ","pages":"Article 103457"},"PeriodicalIF":7.2,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145525915","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}

引用次数: 0