Omega-international Journal of Management Science最新文献_第4页

Data-driven auction design for blockchain-based digital asset trading: A mixed method 基于区块链的数字资产交易数据驱动拍卖设计：一种混合方法

IF 7.2 2区管理学 Q1 MANAGEMENT

Omega-international Journal of Management Science

Pub Date : 2026-06-01 Epub Date: 2025-12-03 DOI: 10.1016/j.omega.2025.103482

Yifang Ding , Su Xiu Xu , Meng Cheng , Sini Guo , Xiang T.R. Kong , George Q. Huang

This paper is motivated by a real project with a leading culture assets and equity swap organization in South China. Our preliminary survey assesses the potential of digital collectibles swap, with professionals aiming to boost liquidity and consumers driven by social attributes and meta-item diversity. In our setting, each agent owns a digital asset and wants another meta-item. However, the traditional Vickrey-Clarke-Groves (VCG) auction runs at a deficit. We thus introduce a novel mechanism that combines the VCG auction with limited supply and platform escrow concepts, called LSE-VCG auction. To improve the surplus of platform (auctioneer), we use limited supply to constrain the number of winners and platform escrow to increase market demand. The LSE-VCG auction and its externality-inclusive variant satisfy both truthful telling and participation rationality. If multilateral matching achieves maximal social welfare, then the substitute condition does not hold (impossibility theorem). We prove that the platform’s surplus can be improved by limited supply in some conditions. Our experimental results show that the VCG auction solely with limited supply could reach greater social welfare, agents’ profits and ratio of swap relative to the sequential Vickrey auctions. Moreover, a mix of limited supply and platform escrow schemes can further improve the platform’s profit and successful trading ratio. For the platform, truthful telling is a desirable strategy that brings high revenues, which promotes a transparent and beneficial auction environment. Besides, the impacts of externalities, auction timing, market size, value distribution and size of XOR bids are investigated. Furthermore, our auction mechanism is likely effective in addressing large-scale problems. Finally, we apply four effective machine learning methods to predict the limited supply number with partial information before the auction.

本文的研究灵感来源于一个华南地区领先的文化资产和股权交换机构的实际项目。我们的初步调查评估了数字收藏品交换的潜力，专业人士的目标是提高流动性，而消费者则受到社会属性和元项目多样性的驱动。在我们的设置中，每个代理拥有一个数字资产，并需要另一个元项。然而，传统的维克里-克拉克-格罗夫斯（VCG）拍卖出现了赤字。因此，我们引入了一种将VCG拍卖与有限供应和平台托管概念相结合的新机制，称为LSE-VCG拍卖。为了提高平台（拍卖商）的剩余，我们用有限的供应来约束中标者的数量，用平台托管来增加市场需求。LSE-VCG拍卖及其外部性包容型拍卖既满足真实陈述，又满足参与理性。如果多边匹配达到最大的社会福利，则替代条件不成立（不可能定理）。证明了在一定条件下，有限供给可以提高平台的剩余量。我们的实验结果表明，相对于连续的Vickrey拍卖，单独有限供应的VCG拍卖可以获得更大的社会福利、代理人利润和互换比率。此外，限量供应与平台托管方案相结合，可以进一步提高平台的利润和交易成功率。对于平台来说，诚实是一种可取的策略，可以带来高收入，从而促进透明和有益的拍卖环境。此外，研究了外部性、拍卖时机、市场规模、价值分布和异或出价规模的影响。此外，我们的拍卖机制可能对解决大规模问题有效。最后，我们应用四种有效的机器学习方法，在拍卖前使用部分信息预测有限供应数量。

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引用次数: 0

Robust shift scheduling with discretionary rest breaks 强有力的轮班安排和自由裁量的休息时间

IF 7.2 2区管理学 Q1 MANAGEMENT

Omega-international Journal of Management Science

Pub Date : 2026-06-01 Epub Date: 2025-12-16 DOI: 10.1016/j.omega.2025.103500

Sara Mattia , Fabrizio Rossi , Stefano Smriglio

Shift scheduling is a critical task in workforce management, which consists of covering the staffing needs by feasible work shifts at minimum labor cost. Work shifts must include rest breaks according to national regulations and collective agreements, significantly impacting the expected Level of Service (LoS) provided to the customers. Therefore, managers tend to preserve the LoS by rigidly scheduling breaks at a centralized level. This affects the well-being of employees, who, especially in large organizations, require more discretion in choosing rest breaks to reduce work stress. This paper presents a two-stage robust optimization model with decision-dependent uncertainty to handle discretionary break assignment. This is a challenging problem both in theory and practice. We formulate it as a bilevel program and develop a tailored heuristic algorithm to find high-quality shift schedules for staffing patterns of several service systems. This methodology allows managers to assess the cost of discretion and to finely determine the best trade-off among discretion, LoS, and labor cost.

轮班调度是劳动力管理中的一项关键任务，它包括在最小的劳动力成本下，通过可行的工作班次来满足员工的需求。根据国家法规和集体协议，工作班次必须包括休息时间，这将严重影响向客户提供的预期服务水平（LoS）。因此，管理人员倾向于通过在集中级别严格安排休息来保护LoS。这影响了员工的幸福感，尤其是在大型组织中，员工需要更谨慎地选择休息时间来减轻工作压力。提出了一种具有决策依赖不确定性的两阶段鲁棒优化模型，用于处理任意断点分配问题。这在理论上和实践上都是一个具有挑战性的问题。我们将其制定为一个双层程序，并开发了一个量身定制的启发式算法，以找到适合多个服务系统人员配置模式的高质量轮班时间表。这种方法允许管理人员评估自由裁量权的成本，并精细地确定自由裁量权、LoS和劳动力成本之间的最佳权衡。

引用次数: 0

A bi-objective sustainable EOQ model with all-units discounts 具有全单位折扣的双目标可持续EOQ模型

IF 7.2 2区管理学 Q1 MANAGEMENT

Omega-international Journal of Management Science

Pub Date : 2026-06-01 Epub Date: 2025-12-16 DOI: 10.1016/j.omega.2025.103503

José M. Gutiérrez, Antonio Sedeño-Noda

A bi-objective sustainable Economic Order Quantity (EOQ) model considering all-units discounts is addressed. Two criteria are considered in the model, namely, the classical cost function of the EOQ and a

{CO}_{2}

emission function, which must be simultaneously minimized. Moreover, all-units discounts are taken into account since they are a very common practice in real world wholesalers/sellers businesses to encourage higher volume sales in order to reduce the inventory level. Therefore, the aim of the new model is to identify the non-dominated solution set (Pareto optimal set).

It will be shown that the Pareto optimal solution set for the new sustainable EOQ variant is not always a convex set (or equivalently, the nondominated solution set could occasionally be non-continuous) and this set is defined by means of cases study (depending on the problem’s variables values).

The new characterization of the Pareto optimal set of the new extension of this bi-objective sustainable EOQ model allows us to define the corresponding Pareto frontier. These findings have been implemented in Python and tested for a randomly generated set of instances.

研究了考虑全单位折扣的双目标可持续经济订货量模型。该模型考虑了两个准则，即EOQ的经典成本函数和CO2排放函数，两者必须同时最小化。此外，所有单位的折扣都被考虑在内，因为这是现实世界中批发商/销售商鼓励更高销量以减少库存水平的一种非常普遍的做法。因此，新模型的目标是识别非支配解集（帕累托最优集）。本文将证明，新的可持续EOQ变量的Pareto最优解集并不总是一个凸集（或等价地，非支配解集偶尔可能是不连续的），并且该集是通过案例研究（取决于问题的变量值）来定义的。该双目标可持续EOQ模型的新扩展的Pareto最优集的新特征使我们能够定义相应的Pareto边界。这些发现已经在Python中实现，并针对随机生成的一组实例进行了测试。

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引用次数: 0

Blockchain adoption for promoting carbon emission reduction in relation to social comparison and competition 透过社会比较和竞争，推动碳减排

IF 7.2 2区管理学 Q1 MANAGEMENT

Omega-international Journal of Management Science

Pub Date : 2026-06-01 Epub Date: 2025-12-06 DOI: 10.1016/j.omega.2025.103487

Benyong Hu , Fuxia Ren , Xu Chen , Chao Meng

This paper examines the impact and value of blockchain adoption on firms’ carbon emission reduction decisions. Accounting for social comparison between eco-conscious and general consumers, we develop game-theoretic models of producers and consumers under both monopoly and competition conditions, and where low-carbon and traditional (non-low-carbon) products coexist. We first show that the probability of eco-conscious consumers purchasing low-carbon products is raised as blockchain changes the demand structure in the competition market. Interestingly, however, adopting blockchain in the competition market does not necessarily lead to higher carbon emission reduction. This is different from the positive effect of blockchain in the monopoly market that promotes carbon emission reduction. Second, in stark contrast to the monopoly market, we identify that competition is more conducive to the adoption of blockchain and the promotion of carbon emission reduction by a firm. Nevertheless, competition does not always improve consumer surplus—A counterintuitive result. Third, our analysis concludes that, as the fraction of eco-conscious consumers continues to increase, social comparison instead has a dampening effect on firms’ incentives to adopt blockchain and enhance carbon emission reduction. These findings provide a new theoretical mechanism concerning blockchain adoption in promoting sustainability within the social comparison context and a quantitative basis for government carbon regulation.

本文考察了区块链采用对企业碳减排决策的影响和价值。考虑到生态意识消费者和普通消费者之间的社会比较，我们建立了垄断和竞争条件下的生产者和消费者的博弈论模型，其中低碳产品和传统（非低碳）产品并存。我们首先表明，随着区块链改变竞争市场的需求结构，生态意识消费者购买低碳产品的概率提高。然而，有趣的是，在竞争市场中采用区块链并不一定会导致更高的碳减排。这与垄断市场中区块链促进碳减排的积极作用不同。其次，与垄断市场形成鲜明对比的是，我们发现竞争更有利于企业采用区块链和促进碳减排。然而，竞争并不总能提高消费者剩余——这是一个违反直觉的结果。第三，随着生态意识消费者比例的持续增加，社会比较反而对企业采用区块链和加强碳减排的激励产生抑制作用。这些研究结果为社会比较背景下区块链在促进可持续发展中的应用提供了新的理论机制，并为政府碳监管提供了定量依据。

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引用次数: 0

Dynamic stochastic parcel locker assignment with uncertain pick-up times 不确定取件时间的动态随机储物柜分配

IF 7.2 2区管理学 Q1 MANAGEMENT

Omega-international Journal of Management Science

Pub Date : 2026-04-01 Epub Date: 2025-11-25 DOI: 10.1016/j.omega.2025.103478

Simona Mancini , Margaretha Gansterer

Automated parcel lockers are used by logistics providers in order to increase the efficiency of last-mile delivery operations particularly in urban areas. We consider the case of a company that operates lockers and dynamically receives delivery orders that have to be accepted or rejected immediately. On a second decision stage, the set of accepted orders has be assigned to the lockers such that customer compatibility requirements and maximum fulfillment times are respected. As both future arrivals of orders as well as customer pickup-times are unknown, the company faces a dynamic stochastic problem. To generate solutions, we propose a decision framework based on a classification approach. The classifier uses a mixed integer model to learn from optimal solutions within a deterministic setting and exploits this information within the dynamic stochastic process. We assess the proposed method within an extensive computational study where both artificial instances and a real world case are addressed. The obtained results show that the classification-based framework outperforms all benchmark methods, which include (i) scenario sampling, (ii) classical decision trees, and (iii) several deterministic policies. Managerial insights with regard to most important systems’ features within the decision process are derived. The newly proposed decision framework is generalizable such that it can be applied to related dynamic stochastic matching problems.

物流供应商使用自动包裹储物柜，以提高最后一英里交付业务的效率，特别是在城市地区。我们考虑一个公司的情况，该公司经营储物柜并动态接收必须立即接受或拒绝的交付订单。在第二个决策阶段，已接受的订单集已分配给储物柜，以便满足客户兼容性要求和最大完成时间。由于未来的订单到达和客户提货时间都是未知的，因此公司面临着一个动态随机问题。为了生成解决方案，我们提出了一个基于分类方法的决策框架。分类器使用混合整数模型从确定性设置中的最优解中学习，并在动态随机过程中利用此信息。我们在广泛的计算研究中评估所提出的方法，其中人工实例和真实世界的案例都得到了解决。得到的结果表明，基于分类的框架优于所有基准方法，包括(i)场景采样，（ii）经典决策树和（iii）几个确定性策略。关于决策过程中最重要的系统特征的管理见解得到了推导。新提出的决策框架具有一定的泛化性，可以应用于相关的动态随机匹配问题。

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引用次数: 0

Cooperation between competing digital content platforms: Open access for content sharing 相互竞争的数字内容平台之间的合作：内容共享的开放访问

IF 7.2 2区管理学 Q1 MANAGEMENT

Omega-international Journal of Management Science

Pub Date : 2026-04-01 Epub Date: 2025-11-24 DOI: 10.1016/j.omega.2025.103480

Wenshuo Zhang , Minqiang Li , Haiyang Feng , Nan Feng

Continuous investment in content by digital content platforms (DCPs) has intensified competition for exclusive content, while subscriber base growth has slowed in an increasingly saturated market. In this context, cooperation through open content access has emerged as a practical strategy for DCPs to sustain further growth. Specifically, a DCP (e.g., HBO Max) may offer subscription-based access to its exclusive content via a competitor’s platform (e.g., Amazon Prime Video) to attract its focal subscribers. This strategy facilitates subscriber multi-homing by providing price discounts and reducing access costs for high-demand subscribers using the other open-access DCP. To examine the cooperation incentives of two competing DCPs, we develop a game-theoretic model that captures each DCP’s strategic decisions regarding open content access, alongside its discount strategy for attracting high-demand subscribers under open content access and its content strategy for securing exclusive content creators. The model explicitly incorporates the strategic interactions between the subscriber and content sides of a two-sided market, accounting for both creator-side and subscriber-side network effects. Our findings reveal that as the network effect on either side strengthens, the equilibrium outcome shifts across different cooperation cases, with one-way cooperation (where only one DCP’s exclusive content is available on the other DCP) replacing two-way cooperation (where each DCP’s exclusive content is accessible on the other DCP) as the equilibrium. A similar shift occurs as competition between the DCPs for content creators intensifies, provided that the content access cost remains relatively low. In contrast, when the content access cost is relatively high, two-way cooperation persists as the equilibrium. In the asymmetric DCP scenario, when the gap between the DCPs’ focal subscriber bases is relatively narrow and the competitive intensity is relatively high, two one-way cooperation cases emerge as equilibria, with either the larger or the smaller DCP serving as the open-access platform. In comparing these two cases, the larger DCP prioritizes the content strategy of setting a higher content price, whereas the smaller DCP focuses on the discount strategy of offering a higher discount rate.

数字内容平台（dcp）对内容的持续投资加剧了对独家内容的竞争，而在日益饱和的市场中，用户基础增长放缓。在此背景下，通过开放内容获取进行合作已成为数字内容提供商维持进一步增长的一项切实可行的战略。具体来说，DCP（例如HBO Max）可能会通过竞争对手的平台（例如Amazon Prime Video）提供基于订阅的独家内容访问，以吸引其重点用户。该策略通过为使用其他开放访问DCP的高需求用户提供价格折扣和降低访问成本来促进用户多归巢。为了研究两个竞争的DCP的合作动机，我们开发了一个博弈论模型，该模型捕捉了每个DCP关于开放内容访问的战略决策，以及在开放内容访问下吸引高需求用户的折扣策略和确保独家内容创作者的内容策略。该模型明确地结合了双边市场中订阅者和内容方之间的战略互动，考虑了创作者和订阅者双方的网络效应。研究发现，随着双方网络效应的增强，均衡结果在不同合作情况下发生变化，单向合作（只有一个DCP的独家内容可以在另一个DCP上获得）取代双向合作（每个DCP的独家内容可以在另一个DCP上获得）成为均衡。在内容访问成本相对较低的情况下，dcp之间对内容创作者的竞争加剧，也会出现类似的转变。相反，当内容访问成本较高时，双向合作作为均衡仍然存在。在非对称DCP场景下，当DCP焦点用户群之间的差距较窄且竞争强度较高时，出现两种单向合作均衡，即较大的DCP或较小的DCP作为开放接入平台。在比较这两种情况时，较大的DCP优先考虑设定较高内容价格的内容策略，而较小的DCP则侧重于提供较高折扣率的折扣策略。

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引用次数: 0

A branch-and-price approach for computing the minimum number of pairwise comparisons in multicriteria selection based on convex cones 基于凸锥的多准则选择中两两比较最小次数计算的分支-价格方法

IF 7.2 2区管理学 Q1 MANAGEMENT

Omega-international Journal of Management Science

Pub Date : 2026-04-01 Epub Date: 2025-11-24 DOI: 10.1016/j.omega.2025.103481

Özgür Özpeynirci , Selin Özpeynirci

We study the multiple criteria selection problem (MCSP), where the aim is to identify the most preferred alternative among a set of known alternatives evaluated on multiple criteria. While several methods have been developed for MCSP, which utilize pairwise comparisons, it remains unknown how close these approaches are to the theoretical minimum number of pairwise comparisons required. To address this gap, we propose a computational framework that determines the theoretical lower bound on the number of pairwise comparisons required under the assumption that the DM’s value function is known. Although this assumption is not realistic for real-world decision support, it is essential for establishing a rigorous performance standard against which algorithms can be evaluated. While this framework provides a basis for benchmarking interactive algorithms, its applicability is specific to pairwise comparison procedures that utilize convex cones.

The benchmark is formulated as a large-scale integer programming problem and solved via a branch-and-price approach, where column generation is used to generate only the most promising convex cones. We further extend the model to incorporate transitivity, which can reduce the number of comparisons but increases computational effort. Extensive computational experiments are conducted across diverse problem instances. Beyond providing benchmark values, the results reveal structural patterns—such as when the optimal solution relies primarily on 2-point or 3-point cones, and when higher-level cones are required. These insights not only strengthen the role of the benchmark as a theoretical reference, but also offer practical guidance for designing more efficient algorithms for MCSP.

我们研究了多标准选择问题（MCSP），其目的是在一组已知的备选方案中识别出最受欢迎的备选方案。虽然已经开发了几种用于MCSP的方法，这些方法利用两两比较，但仍然不知道这些方法与理论所需的两两比较的最小数量有多接近。为了解决这一差距，我们提出了一个计算框架，该框架在假设DM的值函数已知的情况下确定所需两两比较次数的理论下界。尽管这个假设对于现实世界的决策支持来说是不现实的，但它对于建立一个严格的性能标准是必要的，根据这个标准可以对算法进行评估。虽然这个框架为交互式算法的基准测试提供了基础，但它的适用性仅限于利用凸锥的两两比较过程。该基准被表述为一个大规模整数规划问题，并通过分支-价格方法解决，其中列生成用于仅生成最有希望的凸锥。我们进一步扩展了模型，加入了传递性，这可以减少比较的次数，但增加了计算量。在不同的问题实例中进行了广泛的计算实验。除了提供基准值之外，结果还揭示了结构模式，例如当最优解决方案主要依赖于2点或3点锥时，以及当需要更高级别的锥时。这些见解不仅加强了基准的理论参考作用，而且为设计更高效的MCSP算法提供了实践指导。

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引用次数: 0

Multi-driver transportation scheduling for improving supply chain resilience 提高供应链弹性的多驾驶员运输调度

IF 7.2 2区管理学 Q1 MANAGEMENT

Omega-international Journal of Management Science

Pub Date : 2026-04-01 Epub Date: 2025-11-13 DOI: 10.1016/j.omega.2025.103461

Shaojun Lu , Yiyu Song , Min Kong , Chaoming Hu , Amir M. Fathollahi-Fard , Maxim A. Dulebenets

Optimizing transportation scheduling enhances the flexibility of resource allocation and transport operations, thereby reducing delays and costs while improving the resilience of supply chains. This study investigates a transportation scheduling problem aimed at minimizing the maximum completion time, incorporating key real-world considerations such as multiple drivers, loading and unloading times, round-trip transportation, distributed logistics centers, and the deterioration effect. Several structural properties of the problem are derived through a comprehensive preliminary analysis. Building on these properties, an exact algorithm for task sequencing is developed, and a Mixed-Integer Linear Programming model is formulated. A lower bound for the problem is also established. Given the NP-hard nature of the problem, we propose an enhanced Variable Neighborhood Search (VNS) algorithm, which integrates the exact algorithm with four neighborhood structures to accelerate convergence and improve solution quality. Experimental results indicate that the proposed intelligent algorithm significantly outperforms five state-of-the-art metaheuristics in both convergence speed and solution quality. This study further integrates deep learning to predict the best runtime of the proposed intelligent algorithm across problems of varying scales, which can reduce computational time in practical optimization scenarios. Sensitivity analysis highlights the critical influence of normal transportation times and the deterioration coefficient on scheduling performance, offering valuable theoretical insights for supply chain management. The findings of this research contribute to optimizing transportation task scheduling, enhancing supply chain resilience, and promoting sustainable development goals in supply chain management.

优化运输调度可以提高资源配置和运输作业的灵活性，从而减少延误和成本，同时提高供应链的弹性。本文研究了一个以最小化最大完工时间为目标的运输调度问题，并结合了多个驾驶员、装卸时间、往返运输、分布式物流中心和劣化效应等关键现实考虑因素。通过全面的初步分析，导出了问题的几个结构性质。在此基础上，提出了一种精确的任务排序算法，并建立了混合整数线性规划模型。并给出了问题的下界。针对该问题的NP-hard特性，本文提出了一种增强的可变邻域搜索（VNS）算法，该算法将精确算法与四种邻域结构相结合，以加速收敛并提高解的质量。实验结果表明，该算法在收敛速度和解质量上都明显优于五种最先进的元启发式算法。本研究进一步整合深度学习来预测所提出的智能算法在不同规模问题中的最佳运行时间，从而减少实际优化场景中的计算时间。敏感性分析强调了正常运输时间和恶化系数对调度绩效的重要影响，为供应链管理提供了有价值的理论见解。研究结果有助于优化运输任务调度，增强供应链弹性，促进供应链管理的可持续发展目标。

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引用次数: 0

Adaptation strategies-based supply chain viability optimization under bidirectional ripple effects 双向连锁效应下基于适应策略的供应链生存力优化

IF 7.2 2区管理学 Q1 MANAGEMENT

Omega-international Journal of Management Science

Pub Date : 2026-04-01 Epub Date: 2025-11-17 DOI: 10.1016/j.omega.2025.103467

Wei Pu , Xiangbin Yan , Shuang Ma

Long-term disruptions can trigger ripple effects across the supply chain, impacting both upstream and downstream stakeholders. To mitigate the consequences of such bidirectional ripple effects, including financial losses, consumer dissatisfaction, and declines in supply chain performance, an efficient optimization framework is required to enhance supply chain viability (SCV) through the integration of agility, resilience, and sustainability.

To strengthen the adaptive capacity and long-term viability of supply chain networks, we propose an adaptation strategies-based optimization framework. These adaptation strategies include utilizing third-party logistics (3PL) and implementing self-healing mechanisms. We then develop a two-stage multi-period stochastic programming model incorporating these strategies. This model explicitly captures bidirectional ripple effects by integrating the forward and backward propagation of dynamic disruptions. Additionally, we develop an advanced multi-objective particle swarm optimization (AMOPSO) solution method for solving the two-stage multi-period stochastic programming.

Using real-world data from China’s small appliances industry during COVID-19, we demonstrate the applicability of the proposed optimization model in enhancing SCV and mitigating bidirectional ripple effects, and the efficiency and robustness of the developed AMOPSO solution method. The optimal results reveal improvements of 3.22% in agility, 17.03% in resilience, and 23.02% in sustainability. Thus, the proposed optimization framework can improve supply chain viability under bidirectional ripple effects. The framework, along with the developed adaptation strategies-based stochastic optimization model and AMOPSO solution method, provides a novel approach to supply chain viability optimization and offers a practical decision-support method to original equipment manufacturers (OEMs) under bidirectional ripple effects.

长期的中断会引发整个供应链的连锁反应，影响上游和下游的利益相关者。为了减轻这种双向连锁反应的后果，包括财务损失、消费者不满和供应链绩效下降，需要一个有效的优化框架，通过整合敏捷性、弹性和可持续性来提高供应链的可行性（SCV）。为了增强供应链网络的适应能力和长期生存能力，我们提出了一个基于适应策略的优化框架。这些适应策略包括利用第三方物流（3PL）和实施自我修复机制。然后，我们开发了一个包含这些策略的两阶段多周期随机规划模型。该模型通过整合动态中断的正向和反向传播来明确捕获双向涟漪效应。此外，针对两阶段多周期随机规划问题，提出了一种先进的多目标粒子群优化（AMOPSO）方法。利用2019冠状病毒病期间中国小家电行业的实际数据，我们证明了所提出的优化模型在增强SCV和减轻双向连锁反应方面的适用性，以及所开发的AMOPSO解决方法的效率和鲁棒性。优化结果表明，敏捷性提高3.22%，弹性提高17.03%，可持续性提高23.02%。因此，本文提出的优化框架可以提高供应链在双向连锁效应下的生存能力。该框架与已建立的基于自适应策略的随机优化模型和AMOPSO求解方法一起，为供应链生存力优化提供了一种新的途径，为双向连锁效应下的原始设备制造商（oem）提供了实用的决策支持方法。

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引用次数: 0

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 Q1 MANAGEMENT

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

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.

本研究提出了一个稳健的优化框架，以解决微型和小型企业（mse）在筹集资金方面面临的持续挑战，这是由于高度的需求模糊性。我们研究了一个强大的报摊模型，其中公司没有足够的初始资本，需要从外部资金提供者筹集资金。在不知道确切需求分布的情况下，企业和资金提供者都采用基于需求均值和方差的最大最小决策规则。企业的目标是通过确定生产数量来最大化其预期最坏情况下的利润，而资金提供者提供股权或贷款融资，寻求市场决定的公平的出资回报。推导出了股权融资和贷款融资下的稳健生产数量和融资协议。我们证明了在分配不明确的情况下，股权融资达到了系统最优的结果，并提出了贷款融资下稳健利率的简单公式。我们进一步将我们的分析推广到考虑抵押品和初始资本，并将基本模型扩展到稳健的委托代理设置，在该设置中，企业可以施加不可观察的努力来影响需求。在后一种情况下，我们表明股权融资在广泛的参数值范围内优于贷款融资，与没有需求歧义的现有文献相反。我们的分析为从业者和政策制定者提供了指导，以寻求有效的策略来促进增长，同时保护MSE部门的资金提供者。

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