International Journal of Production Economics最新文献_第7页

Impact of network nestedness on resistance and recovery of supply chain resilience 网络筑巢性对供应链弹性抗力和恢复的影响

IF 1 1区工程技术 Q1 ENGINEERING, INDUSTRIAL

International Journal of Production Economics

Pub Date : 2025-11-19 DOI: 10.1016/j.ijpe.2025.109854

Sihang Chen , Junqin Lin , Xiaopo Zhuo , Libo Yin , Jiaxin Shen

Network nestedness, which refers to the hierarchical structure of interconnections within a network, plays an important role in supply chain resilience but remains understudied. We use data from listed firms in China between 2002 and 2022 to construct buyer-supplier networks and measure nestedness using the SNODF metric. We validate SNODF's robustness across varying levels of network completeness. Listed firms are centrally positioned in our networks, making them crucial focal points for analysis. Our empirical results show that network nestedness has a dual effect on supply chain resilience: it weakens short-term resistance to disruptions but enhances long-term recovery. This trade-off arises because hierarchical structures concentrate vulnerability at hub nodes while enabling coordinated resource reallocation after a disruption. We examine two managerial levers that moderate these effects: (1) supplier concentration, an external strategy that attenuates the negative effect on resistance but dampens recovery gains; and (2) corporate digitalization, an internal strategy that mitigates initial losses and enhances recovery. These findings imply that firms should balance two approaches: (1) mitigating risk through supplier diversification to reduce dependence on dominant hubs, and (2) leveraging digital technologies to improve recovery capabilities, thus strengthening long-term resilience.

网络嵌套性是指网络内互连的层次结构，在供应链弹性中起着重要作用，但仍未得到充分研究。我们使用2002年至2022年中国上市公司的数据来构建买方-供应商网络，并使用SNODF度量嵌套性。我们在不同级别的网络完整性上验证了SNODF的健壮性。上市公司在我们的网络中处于中心位置，使它们成为分析的关键焦点。实证结果表明，网络嵌套性对供应链弹性具有双重影响：它削弱了对中断的短期抵抗，但增强了长期恢复。之所以会出现这种权衡，是因为分层结构将漏洞集中在集线器节点上，同时在中断后支持协调的资源重新分配。我们研究了缓和这些影响的两种管理杠杆：(1)供应商集中，这是一种外部战略，可以减轻对阻力的负面影响，但会抑制复苏收益；(2)企业数字化，这是一种内部战略，可以减轻初始损失并提高恢复能力。这些发现表明，企业应该平衡两种方法：(1)通过供应商多样化来降低风险，以减少对主导中心的依赖；(2)利用数字技术来提高恢复能力，从而增强长期弹性。

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引用次数: 0

Integrated production and maintenance planning in imperfect hybrid manufacturing–remanufacturing systems with outsourcing and carbon emissions 考虑外包和碳排放的不完全混合制造-再制造系统的集成生产与维修计划

IF 1 1区工程技术 Q1 ENGINEERING, INDUSTRIAL

International Journal of Production Economics

Pub Date : 2025-11-19 DOI: 10.1016/j.ijpe.2025.109862

Mohammed Merghem , Mohammed Haoues , Ahmed Senoussi , Mohammed Dahane , Nadia Kinza Mouss

This study investigates the integrated planning of production, maintenance, and quality control in a hybrid manufacturing-remanufacturing system, accounting for deterioration, variability in the quality of returned products, carbon emissions, and outsourcing opportunities. The network consists of a manufacturer collaborating with an outsourcing remanufacturing provider. The manufacturer operates a single failure-prone machine to produce new products and to remanufacture returned ones. Recovered products that the manufacturer cannot process are sent to the outsourcing provider for remanufacturing. The system generates harmful emissions, potentially leading to environmental taxes and sanctions. We formulate a mixed-integer nonlinear programming model to determine the optimal integrated manufacturing, remanufacturing, outsourcing, and preventive maintenance plan. Eventually, the proposed strategy minimizes total economic costs and defects and ultimately reduces carbon emissions. We use a global solver for solving small instances, while a genetic algorithm metaheuristic is developed for larger ones. Extensive computational experiments reveal that the developed genetic algorithm is highly efficient, achieving gaps of less than 0.95% within shorter execution times for small instances and significantly outperforming the solver in larger ones. The results show that the integrated outsourcing strategy, combined with accounting for carbon emissions from both new and remanufactured products, significantly reduces the reliance on new products, leading to notable cost savings and environmental benefits. These savings become more pronounced as the number of returns increases.

本研究探讨了制造-再制造混合系统中生产、维修和质量控制的整合计划，考虑了退化、退货质量的可变性、碳排放和外包机会。该网络由制造商与外包再制造供应商合作组成。制造商操作一台容易发生故障的机器生产新产品，并对退回的产品进行再制造。制造商无法加工的回收产品被发送给外包供应商进行再制造。该体系产生有害排放物，可能导致环境税和制裁。我们建立了一个混合整数非线性规划模型来确定最优的集成制造、再制造、外包和预防性维护计划。最终，提出的策略使总经济成本和缺陷最小化，并最终减少碳排放。我们使用全局求解器来解决小实例，而开发了遗传算法元启发式来解决较大的实例。大量的计算实验表明，所开发的遗传算法是高效的，在较小的实例中，在较短的执行时间内实现了小于0.95%的间隙，并且在较大的实例中显著优于求解器。研究结果表明，综合考虑新产品和再制造产品碳排放的外包策略，显著降低了企业对新产品的依赖，带来了显著的成本节约和环境效益。随着回报次数的增加，这些节省变得更加明显。

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引用次数: 0

Integrating industry 4.0 technologies into green supply chains: An empirical investigation of pathways to green innovation and circular economy 工业4.0技术与绿色供应链的整合：绿色创新与循环经济路径的实证研究

IF 1 1区工程技术 Q1 ENGINEERING, INDUSTRIAL

International Journal of Production Economics

Pub Date : 2025-11-17 DOI: 10.1016/j.ijpe.2025.109859

Fakhar Shahzad , Younes Ben Zaied , Qingyu Zhang

Despite the growing recognition of the transformative potential of Industry 4.0 technologies to advance sustainability goals, the existing evidence often needs to pay more attention to the actual integration of these technologies in supply chain dynamics. This study aims to bridge this gap by integrating a practice-based view and supply chain practice view framework to uncover the complex nexus that forms a sustainable circular economy. The required data was collected through a structured questionnaire (n = 358) from supply chain professionals of Pakistani manufacturing firms. The proposed model was tested using partial least squares structural equation modeling, bootstrapping, and importance–performance map analysis. The findings portray the positive role of Industry 4.0 technologies and green supply chain integration in driving green innovation for sustainable products and processes, and provide concrete examples of their practical application in a sustainable circular economy. The outcomes contributed to the development of sustainable business strategies for Industry 4.0 technologies-based green supply chain integration, providing significant theoretical grounds and a practical roadmap for integrating these technologies into the manufacturing supply chain. Importantly, the study's findings directly impact supply chain professionals and provide practical guidance for manufacturers navigating the changing landscape and achieving sustainable goals.

尽管人们越来越认识到工业4.0技术在推进可持续发展目标方面的变革潜力，但现有的证据往往需要更多地关注这些技术在供应链动态中的实际整合。本研究旨在通过整合基于实践的观点和供应链实践的观点框架来弥合这一差距，揭示形成可持续循环经济的复杂联系。所需数据通过结构化问卷（n = 358）从巴基斯坦制造公司的供应链专业人员中收集。采用偏最小二乘结构方程建模、自举和重要性-性能图分析对提出的模型进行了检验。研究结果描绘了工业4.0技术和绿色供应链整合在推动可持续产品和流程的绿色创新方面的积极作用，并提供了它们在可持续循环经济中的实际应用的具体例子。研究结果有助于为基于工业4.0技术的绿色供应链整合制定可持续商业战略，为将这些技术整合到制造业供应链中提供重要的理论依据和实践路线图。重要的是，研究结果直接影响供应链专业人士，并为制造商在不断变化的环境中导航和实现可持续目标提供实用指导。

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引用次数: 0

Positioning of omnichannel inventories to protect revenue 定位全渠道库存以保障收入

IF 1 1区工程技术 Q1 ENGINEERING, INDUSTRIAL

International Journal of Production Economics

Pub Date : 2025-11-15 DOI: 10.1016/j.ijpe.2025.109853

Alborz Hassanzadeh , Victor Martínez-de-Albéniz

Conventional inventory management strategies prove inadequate when confronted with the complexities of omnichannel retailing. Fulfillment from stores and transshipment emerged as alternative methods to supplant the traditional approaches, but unfortunately these methods are often too costly. How to share limited inventory between online and offline channels thus remains a challenging question. We characterize an omnichannel retailer’s inventory sharing policy with limited inventory to be sold during a finite horizon. Inventory reserved for the online channel can later be transferred to the offline inventory pool, but once it is shipped to offline stores, it becomes out of reach for online orders. We use an optimal control framework with limited inventory supply and stochastic demand processes. By recursively solving a series of differential equations, we characterize the optimal inventory positioning policy. We demonstrate that a three-regime time-threshold policy governs the optimal inventory allocation policy; in the central regime, both channels are active and the retailer keeps minimal stock at the stores. During the beginning and end regimes, only one channel is open and has positive inventory. While traditional inventory management techniques tend to favor a high fill rate and availability, our approach focuses on positioning inventory where it generates the most revenue, which depends on the remaining time in the season. Interestingly, this approach sometimes leads to strategic revenue protection decisions wherein it may be more profitable to preclude sales from a lower-margin channel with higher customer reach.

传统的库存管理策略在面对全渠道零售的复杂性时被证明是不够的。商店配送和转运成为替代传统方法的替代方法，但不幸的是，这些方法往往过于昂贵。因此，如何在线上和线下渠道之间共享有限的库存仍然是一个具有挑战性的问题。我们描述了一个全渠道零售商的库存共享策略，在有限的范围内销售有限的库存。为在线渠道保留的库存稍后可以转移到离线库存池，但一旦运往离线商店，在线订单就无法获得这些库存。我们使用了有限库存供应和随机需求过程的最优控制框架。通过递归求解一系列微分方程，刻画了最优库存定位策略。我们证明了一个三状态时间阈值策略支配着最优库存分配策略；在中央模式下，两个渠道都是活跃的，零售商在商店保持最小的库存。在开始和结束期间，只有一个渠道是开放的，并且有正库存。虽然传统的库存管理技术倾向于高填充率和可用性，但我们的方法侧重于将库存定位在产生最多收入的地方，这取决于季节的剩余时间。有趣的是，这种方法有时会导致战略收益保护决策，其中排除来自利润率较低但客户覆盖面较高的渠道的销售可能更有利可图。

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引用次数: 0

Uncovering the risks of digital supply chains: A large language model framework for semantic identification and validation 揭示数字供应链的风险：用于语义识别和验证的大型语言模型框架

IF 1 1区工程技术 Q1 ENGINEERING, INDUSTRIAL

International Journal of Production Economics

Pub Date : 2025-11-14 DOI: 10.1016/j.ijpe.2025.109858

Jiaqi Fang , Bixiang Su , Shuzhen Wang , Bin Wang

This study proposes a semantic framework powered by Large Language Models (LLMs) to detect and quantify latent, technology-induced risks embedded in unstructured corporate disclosures under ongoing digital transformation. While existing methods often fail to capture key supply chain risks such as external shocks, operational disruptions, and digital system failures, structured prompts guide GPT-based models to extract standardized and interpretable risk indicators. These indicators are validated through panel regressions and behavioral inventory simulations using the classical (s, S) policy. Empirical results show that LLM-derived measures explain 10 %–15 % more variance in firm-level market volatility, digital investment, and inventory decisions than traditional Bag-of-Words (BoW) methods. External risks significantly predict stock return volatility (β = 0.173) and international revenue share (β = −0.477), while digital risks are associated with higher management costs and increased patent output. Simulation results show that inventory buffers expand and total inventory costs rise by up to 18 % under elevated risk exposure. The findings provide a theoretically grounded and practically viable framework for semantic risk identification, advancing intelligent supply chain analytics.

本研究提出了一个由大型语言模型（llm）提供支持的语义框架，以检测和量化正在进行的数字化转型中嵌入在非结构化公司披露中的潜在技术引发的风险。虽然现有方法往往无法捕捉关键的供应链风险，如外部冲击、运营中断和数字系统故障，但结构化提示可以指导基于gpt的模型提取标准化和可解释的风险指标。这些指标通过面板回归和使用经典（s, s）策略的行为清单模拟进行验证。实证结果表明，与传统的词汇袋（BoW）方法相比，llm衍生的方法在企业层面的市场波动、数字投资和库存决策方面的解释差异要高出10% - 15%。外部风险显著预测股票收益波动率（β = 0.173）和国际收入份额（β = - 0.477），而数字风险与更高的管理成本和增加的专利产出相关。仿真结果表明，在风险敞口增加的情况下，库存缓冲空间扩大，总库存成本上升高达18%。研究结果为语义风险识别提供了理论基础和实际可行的框架，促进了智能供应链分析。

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引用次数: 0

Joint bunker fuel and freight revenue management in liner shipping: A decision-focused learning approach 班轮运输中的联合燃油和货运收益管理：以决策为中心的学习方法

IF 1 1区工程技术 Q1 ENGINEERING, INDUSTRIAL

International Journal of Production Economics

Pub Date : 2025-11-13 DOI: 10.1016/j.ijpe.2025.109857

Nitish Bhide , Jasashwi Mandal , Ramesh Kumar , Manoj K. Tiwari

The volatility of bunker fuel prices significantly impacts the maritime industry due to increasing regulatory complexities and market uncertainties. This study focuses on addressing these challenges by identifying bunker price prediction as a critical area of impact for improving operational efficiency and decision robustness. A comprehensive optimization model has been proposed to determine optimal ship speed and bunkering strategies both within and outside Emission Control Areas (ECAs). The traditional two-stage method involves training predictive models for bunker price, with the predictions being used as input parameters to solve the optimization problem. However, the loss function in this two-stage method does not consider the effect of predictions on the downstream decision-making problem. Therefore, this study adopts an integrated framework, Decision-Focused Learning (DFL) that unifies prediction and optimization processes into a cohesive approach. Unlike traditional sequential approaches, this method embeds the predictive model directly within the optimization process. It is comparatively more capable of handling data-driven optimization problems than traditional two-stage methods. In this study, computational experiments show that how DFL outperforms traditional methods, achieving 1.29% lower Normalized Regret, which translates to predictions resulting in approximately

$ 22, 730

higher profit for liner services. These findings offer valuable managerial insights into improving efficiency and sustainability in liner shipping operations by making better decisions under real world uncertainties.

由于监管复杂性和市场不确定性的增加，船用燃料价格的波动对海运业产生了重大影响。本研究的重点是通过将燃料价格预测作为提高运营效率和决策稳健性的关键影响领域来解决这些挑战。提出了一种综合优化模型，以确定船舶在排放控制区内外的最优航速和加油策略。传统的两阶段方法包括训练燃料价格预测模型，并将预测结果作为输入参数来解决优化问题。然而，这种两阶段方法中的损失函数没有考虑预测对下游决策问题的影响。因此，本研究采用决策聚焦学习（Decision-Focused Learning， DFL）这一整合框架，将预测和优化过程统一为一个内聚的方法。与传统的顺序方法不同，该方法将预测模型直接嵌入到优化过程中。相对于传统的两阶段方法，它更能处理数据驱动的优化问题。在这项研究中，计算实验显示了DFL如何优于传统方法，实现了1.29%的归一化遗憾，这转化为预测，班轮服务的利润增加了约22,730美元。这些发现为班轮运输业务在现实世界不确定性下做出更好的决策，从而提高效率和可持续性提供了有价值的管理见解。

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引用次数: 0

Responding to upstream uncertainty: How does supplier risk-taking affect client ESG performance? 应对上游不确定性：供应商的风险承担如何影响客户的ESG绩效？

IF 1 1区工程技术 Q1 ENGINEERING, INDUSTRIAL

International Journal of Production Economics

Pub Date : 2025-11-13 DOI: 10.1016/j.ijpe.2025.109856

Jing Zhou , Tingwei Wu , Kaiwen Wu

With environmental, social, and corporate governance (ESG) issues gaining global prominence, it is increasingly recognized that sustainable practices must extend beyond individual organizations to encompass their entire supply chains. This study investigates the impact of supplier risk-taking on the ESG performance of client firms, highlighting how supply chain transmission influences corporate sustainability initiatives. Using data from Chinese listed firms from 2009 to 2023, our results reveal that supplier risk-taking positively influences the ESG performance of client firms. This positive effect is found to be progressively strengthened as corporate reputation and supplier dependence increase but gradually weakened with rising investor confidence. These findings not only deepen the understanding of the supply chain's role in shaping corporate ESG performance but also highlight ESG as a proactive strategy for client firms to anticipate and mitigate risks transmitted from suppliers. This offers valuable insights for managers and policymakers seeking to enhance sustainable practices through effective supply chain risk management.

随着环境、社会和公司治理（ESG）问题在全球日益突出，人们越来越认识到，可持续实践必须超越单个组织，涵盖其整个供应链。本研究探讨了供应商承担风险对客户公司ESG绩效的影响，强调了供应链传递如何影响企业的可持续发展举措。利用2009 - 2023年中国上市公司的数据，我们的研究结果表明，供应商风险承担对客户公司的ESG绩效有正向影响。随着企业声誉和供应商依赖性的增加，这种积极作用逐渐增强，但随着投资者信心的增强，这种积极作用逐渐减弱。这些发现不仅加深了对供应链在塑造企业ESG绩效中的作用的理解，而且强调了ESG作为客户公司预测和减轻供应商传递的风险的主动战略。这为管理者和决策者寻求通过有效的供应链风险管理来加强可持续实践提供了宝贵的见解。

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引用次数: 0

Digital twins in supply chain management: Scope and methodological issues 供应链管理中的数字孪生：范围和方法问题

IF 1 1区工程技术 Q1 ENGINEERING, INDUSTRIAL

International Journal of Production Economics

Pub Date : 2025-11-12 DOI: 10.1016/j.ijpe.2025.109842

Latifa Benhamou , Vincent Giard , Samir Lamouri

This paper investigates the implementation of Digital Twins (DTs) in Supply Chain Management (SCM), highlighting the gap between their conceptual promise and practical applications. DTs are recognised for their potential to correct real-time deviations and anticipate and prevent disruptions as they emerge; however, operational deployments in SCM remain rare. Numerous studies mislabel simulation models or Digital Shadows (DSs) as DTs, blurring essential distinctions. To address this issue, this paper adopts a praxeological approach that aims to situate observed implementations within their decision-making context. From this perspective, we propose a novel methodological framework that integrates the historical evolution of supply chain information and decision systems with a multi-dimensional analysis grid, outlining technological progress from simulators to DSs and DTs. This grid evaluates core DT functionalities (simulation, detection, anticipation and correction) across 51 empirical case studies, providing granular insights into maturity levels and AI-enhanced patterns. The results show that most models support monitoring and decision-making, but only 16 % achieve closed-loop capabilities typical of fully functional DTs, mainly in closed systems. In contrast, open systems still depend on human intervention, although AI can increasingly support such contexts. This praxeological approach provides critical and evidence-based snapshots of actual implementations. It offers researchers a clarified conceptual lens and practitioners empirically grounded guidance, outlining avenues for future inquiry and a reflective framework to guide the development and governance of DTs in supply chains.

本文研究了数字孪生（DTs）在供应链管理（SCM）中的实施，突出了其概念承诺与实际应用之间的差距。DTs因其纠正实时偏差和预测和防止出现中断的潜力而得到认可；然而，在SCM中的操作部署仍然很少见。许多研究错误地将仿真模型或数字阴影（DSs）标记为dt，模糊了本质上的区别。为了解决这个问题，本文采用了一种行动学方法，旨在将观察到的实现置于决策环境中。从这个角度来看，我们提出了一个新的方法框架，该框架将供应链信息和决策系统的历史演变与多维分析网格相结合，概述了从模拟器到决策系统和决策系统的技术进步。该网格评估了51个实证案例研究中的核心DT功能（模拟、检测、预测和校正），提供了对成熟度级别和人工智能增强模式的细粒度见解。结果表明，大多数模型支持监控和决策，但只有16%的模型实现了全功能dt的典型闭环能力，主要是在封闭系统中。相比之下，开放系统仍然依赖于人为干预，尽管人工智能可以越来越多地支持这种情况。这种行为学方法提供了实际实现的关键和基于证据的快照。它为研究人员提供了一个明确的概念视角，为实践者提供了基于经验的指导，概述了未来调查的途径，并为指导供应链中直销的发展和治理提供了一个反思框架。

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引用次数: 0

Nudging the last mile: Combining behavioral insights and monetary incentives for sustainable delivery choices 推动最后一英里：结合行为洞察力和可持续交付选择的金钱激励

IF 1 1区工程技术 Q1 ENGINEERING, INDUSTRIAL

International Journal of Production Economics

Pub Date : 2025-11-11 DOI: 10.1016/j.ijpe.2025.109855

Eleonora Rizzitello , Giovanna Lo Nigro , Simona Mancini , Margaretha Gansterer

Last-mile delivery, the final leg of the supply chain to consumers, significantly impacts the environment, particularly in the grocery sector, due to the perishable nature of food items often necessitating expedited delivery methods. The role of consumer behavior in this process has been overlooked, and their preferences in a trade-off between the benefits of grocery home delivery and the environment have yet to be clarified. This paper bridges this gap by integrating behavioral logistics with key drivers of green consumer behavior to optimize grocery delivery, leveraging primary consumer data to enhance efficiency and minimize environmental impact. Using a two-part methodology, the research combines a controlled experiment and an optimization model. By partnering with an Italian supermarket, this research examines the impact of financial incentives, green nudges, and peer collaboration on consumer grocery delivery choices and routing optimization. The findings reveal that moral green nudges outweigh financial incentives and amplify the effect, and peer influence drives the adoption of shared and more sustainable delivery systems. The optimization model quantifies these behavioral insights, demonstrating cost reductions of up to 42.5% through flexible delivery scheduling and 76.8% via a shared cart mechanism. The findings provide valuable insights for practitioners and policymakers willing to intervene in the crossing of consumer choices and grocery delivery efficiency by presenting an innovative and ready-to-implement solution, which we denote as “the shared cart”. In showing the importance of social pressure for collaborative pro-environmental behavior, the shared cart practically embodies the potential for safeguarding the environment, while enabling cost-saving for last-mile delivery in the grocery sector.

最后一英里配送是供应链的最后一段，对环境的影响很大，特别是在食品杂货行业，因为食品的易腐性往往需要加速配送方法。消费者行为在这一过程中的作用一直被忽视，他们在食品杂货送货上门的好处和环境之间的权衡偏好尚未得到澄清。本文通过整合行为物流与绿色消费者行为的关键驱动因素来优化杂货配送，利用原始消费者数据来提高效率并最大限度地减少对环境的影响，从而弥合了这一差距。本研究采用两部分方法，将对照实验和优化模型相结合。通过与一家意大利超市合作，本研究考察了财政激励、绿色推动和同行合作对消费者食品杂货配送选择和路线优化的影响。研究结果显示，道德上的绿色推动超过了经济激励，并放大了效果，同行影响推动了采用共享和更可持续的交付系统。优化模型量化了这些行为洞察，表明通过灵活的交货计划可降低高达42.5%的成本，通过共享推车机制可降低76.8%的成本。研究结果为从业者和政策制定者提供了有价值的见解，他们愿意通过提出一种创新的、随时可以实施的解决方案（我们称之为“共享购物车”）来干预消费者选择和杂货配送效率的交叉。在展示社会压力对协同环保行为的重要性方面，共享购物车实际上体现了保护环境的潜力，同时为食品杂货行业的最后一英里配送节省了成本。

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引用次数: 0

Impact of pricing and replenishment decisions on food waste at stores and households 定价和补给决策对商店和家庭食物浪费的影响

IF 1 1区工程技术 Q1 ENGINEERING, INDUSTRIAL

International Journal of Production Economics

Pub Date : 2025-11-10 DOI: 10.1016/j.ijpe.2025.109851

Bouchra Bacha , Yann Bouchery , M. Zied Babai , Zied Jemai

A strategy often used by retailers to reduce in-store waste of perishables consists of discounting the less-fresh products. However, this strategy can lead to excessive purchases of less fresh products, which ends up in household waste disposal. The perishable inventory literature often ignores this phenomenon, i.e., the waste at households, by considering only in-store waste. In this article, we investigate the impact of the selling price and ordering decisions on food waste at the store and households for perishable products with fixed lifetime. We consider a periodic order-up-to-level (OUTL) inventory control policy where the demand is modeled using customer choice behavior derived from a utility function that incorporates household waste risk. The probability of products’ waste at households is modeled using the quality deterioration of products and the sensitivity of consumers to expired products and food waste. The selling price and the OUTL are determined with the objective of maximizing the expected profit. Our numerical results show that food-waste dynamics and profitability are jointly affected by consumer behavior and inventory policies, rather than pricing alone. By integrating household waste probabilities into retail decision-making, retailers can anticipate cannibalization, design promotions that minimize system-wide waste, and align sustainability with profitability, yielding coordination insights that retailer-only models cannot capture.

零售商经常使用的一种策略是对不太新鲜的产品进行折扣，以减少店内易腐食品的浪费。然而，这种策略可能导致过度购买不太新鲜的产品，最终成为家庭垃圾。易腐库存文献往往忽略了这一现象，即家庭的浪费，只考虑了店内浪费。在本文中，我们研究了销售价格和订购决策对商店和家庭中固定寿命的易腐产品的食物浪费的影响。我们考虑了一个定期订货到级（OUTL）库存控制策略，其中需求是使用从包含家庭垃圾风险的效用函数派生的客户选择行为建模的。利用产品质量恶化和消费者对过期产品和食物垃圾的敏感性，对家庭产品浪费的概率进行建模。以期望利润最大化为目标确定销售价格和OUTL。我们的数值结果表明，食物浪费的动态和盈利能力是由消费者行为和库存政策共同影响的，而不仅仅是价格。通过将家庭垃圾概率整合到零售决策中，零售商可以预测同类相食的情况，设计促销活动，最大限度地减少系统范围内的浪费，并将可持续性与盈利能力结合起来，从而产生只有零售商模型无法捕捉的协调见解。

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引用次数: 0