Supply Chain Analytics最新文献

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A multi-echelon closed-loop supply chain model with multi-recovery systems and carbon regulation 具有多回收系统和碳调控的多级闭环供应链模型

Supply Chain Analytics

Pub Date : 2025-02-22 DOI: 10.1016/j.sca.2025.100109

Dimas Nurbani Harefah , Wakhid Ahmad Jauhari , Cucuk Nur Rosyidi , Dana Marsetiya Utama

This study develops a multi-echelon closed-loop supply chain (CLSC) optimization model for durable products by considering refurbishment, recycling processes, and carbon regulation. A mixed integer linear programming (MILP) is developed for CLSC network design involving suppliers, manufacturers, refurbishment centers, recycling centers, disposal centers, assembly centers, collection centers, and retailers. A carbon cap-and-trade policy is adopted to lessen the emissions emitted from some activities in CLSC. The objectives of the study are to determine the optimal allocations of echelons and to investigate the influences of collection rate, refurbishment rate, recycling rate and carbon policy on CLSC. A numerical example is presented to illustrate the application of the proposed model, and a sensitivity analysis is provided to investigate the effect of key parameters on the model’s behavior and system performance. The results show that the changes in collection, refurbishment, and recycling rates significantly influence the optimal allocation decisions. The results also show that by adopting a carbon cap-and-trade policy, CLSC can benefit both economically and environmentally. However, the level of benefits obtained will depend significantly on the size of the carbon cap and the selling or buying price of carbon in the market.

本研究通过考虑翻新、回收流程和碳排放法规，为耐用产品建立了一个多梯队闭环供应链（CLSC）优化模型。研究开发了一个混合整数线性规划（MILP），用于设计涉及供应商、制造商、翻新中心、回收中心、处理中心、装配中心、收集中心和零售商的 CLSC 网络。采用碳排放总量控制与交易政策来减少供应链中某些活动的排放量。研究的目的是确定梯队的最优分配，并研究收集率、翻新率、回收率和碳政策对 CLSC 的影响。本研究提供了一个数值示例来说明拟议模型的应用，并进行了敏感性分析，以研究关键参数对模型行为和系统性能的影响。结果表明，收集率、翻新率和回收率的变化会对最优分配决策产生重大影响。结果还表明，通过采用碳限额交易政策，加勒比海地区碳中心可以在经济和环境两方面获益。然而，收益水平在很大程度上取决于碳上限的大小以及碳在市场上的买卖价格。

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引用次数: 0

A DEMATEL approach for analysing the interdependence among the efficiency barriers in the agri-fresh produce supply chains 用DEMATEL方法分析农业生鲜产品供应链中效率壁垒之间的相互依赖性

Supply Chain Analytics

Pub Date : 2025-02-19 DOI: 10.1016/j.sca.2025.100106

Reji John, Ashish Kumar Singh

Managing the efficiency of an agri-fresh produce supply chain is challenging and intricate due to the numerous barriers affecting it locally and globally. This study aims to enumerate the potential barriers to efficiency in the agri-fresh produce supply chains, especially when managing fruits and vegetables. We also focus on the interdependence among these barriers. We follow an in-depth literature review and identify barriers with the help of experts. The Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach establishes the interdependence among the identified barriers. The study reveals that numerous scattered farmers with small land areas and unorganized intermediaries, followed by barriers related to fresh food safety and quality, act as the most influential barriers, and barriers related to value addition and food processing are the least significant. Out of 13 finalized barriers, eight are cause and five are effect barriers. The study’s results provide immense insight into all Agri-fresh produce supply chain network parties, enabling them to optimize their activities and reduce food waste. Policymakers can use this information to create supportive policies that address multiple barriers simultaneously, leading to more effective and comprehensive solutions. The lack of studies on the interdependence of barriers causing inefficiency in the agri-fresh produce supply chain makes the work original and unique. The authors considered the response of farmers, fruit and vegetable retailers, wholesalers, and mediators for the development of the initial mutual influence matrix.

由于在本地和全球范围内影响农产品供应链的众多障碍，管理农产品供应链的效率具有挑战性和复杂性。本研究旨在列举农业新鲜农产品供应链中效率的潜在障碍，特别是在管理水果和蔬菜时。我们还关注这些障碍之间的相互依存关系。我们遵循深入的文献综述，并在专家的帮助下确定障碍。决策试验和评估实验室（DEMATEL）方法确定了已确定障碍之间的相互依存关系。研究发现，影响最大的障碍是生鲜食品安全和质量方面的障碍，影响最小的障碍是附加值和食品加工方面的障碍。在最终确定的13个障碍中，8个是原因障碍，5个是结果障碍。该研究的结果为所有农业新鲜农产品供应链网络各方提供了巨大的见解，使他们能够优化他们的活动并减少食物浪费。决策者可以利用这些信息制定支持性政策，同时解决多种障碍，从而找到更有效、更全面的解决方案。由于缺乏对导致农产品供应链效率低下的壁垒相互依赖的研究，使得该研究具有独创性和独特性。作者考虑了农民、水果和蔬菜零售商、批发商和中介对初始相互影响矩阵的反应。

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引用次数: 0

A game theoretic model for dual supply chains with green and non-green products and bi-directional free-riding and carbon policy 具有绿色和非绿色产品以及双向搭便车和碳政策的双供应链博弈论模型

Supply Chain Analytics

Pub Date : 2025-02-07 DOI: 10.1016/j.sca.2025.100103

Sanchari Ganguly , Pritha Das , Manoranjan Maiti

Cap-and-trade regulation is a strategy to reduce carbon emissions (CEs). During production, CEs are reduced by green technology. In a dual-channel supply chain (DCSC), customers try a product at an offline store but purchase it online (showrooming effect). Additionally, using internet information services, some customers purchase offline (ropo effect). Due to demand uncertainty, neutrosophic fuzzy sets are used to appropriately express a parameter’s impreciseness. We develop a game-theoretic model where a manufacturer produces non-green and green products using carbon reduction technology, sells the products through a traditional retailer (offline), and owns an online channel for imprecise market demands. Customers free-ride from both the channels. The CE from transportation and the non-green products are considered. For carbon costs, a cap and trade policy is adopted. The neutrosophic fuzzy variables indicate the impreciseness of the demand, bidirectional free-riding, and product greenness. These variables determine channel members’ truth, indeterminacy, and falsity degrees. Different models with some prices (inconsistent and consistent) and service efforts as decision variables are analyzed using the Stackelberg game approach. After the derivation of the corresponding equilibrium equations, numerical experiments are presented to verify the validity of our conclusions. The findings show that although free-riding is detrimental to the retailer, it becomes advantageous if its direction is altered. The profit of the retailer with consistent prices is higher than the inconsistent one. Opposite outcomes are observed for the manufacturer. The channel members’ profits are more under the neutrosophic fuzzy environment than deterministic/fuzzy. Some managerial insights and conclusions are presented.

限额与交易法规是一种减少碳排放的策略。在生产过程中，绿色技术降低了能耗。在双渠道供应链（DCSC）中，顾客在线下商店试用产品，但在网上购买（展厅效应）。此外，利用互联网信息服务，一些客户在线下购买（ropo效应）。由于需求的不确定性，采用中性模糊集来适当地表达参数的不精确性。我们建立了一个博弈论模型，其中制造商使用碳减排技术生产非绿色和绿色产品，通过传统零售商（线下）销售产品，并拥有在线渠道以满足不精确的市场需求。客户可以从这两个渠道免费获得服务。考虑了交通运输和非绿色产品的CE。在碳成本方面，采取了限额与交易政策。中性模糊变量表示需求的不精确性、双向搭便车和产品绿色度。这些变量决定了通道成员的真实、不确定和虚假程度。使用Stackelberg博弈方法分析了具有某些价格（不一致和一致）和服务努力作为决策变量的不同模型。在推导了相应的平衡方程后，通过数值实验验证了结论的有效性。研究结果表明，尽管搭便车对零售商是有害的，但如果它的方向改变，它就会变得有利。价格一致的零售商的利润高于价格不一致的零售商。对于制造商，观察到相反的结果。渠道成员的利润在中性模糊环境下比在确定性/模糊环境下更多。提出了一些管理见解和结论。

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A robotic process automation model for order-handling optimization in supply chain management 供应链管理中订单处理优化的机器人过程自动化模型

Supply Chain Analytics

Pub Date : 2025-01-17 DOI: 10.1016/j.sca.2025.100102

Ahm Shamsuzzoha , Sini Pelkonen

This study proposes a robotic process automation (RPA) model to streamline and optimize order-handling procedures in supply chain management. The current manual approach to order handling poses challenges, including limited accessibility and significant cognitive demands on employees. An information systems design methodology is applied to analyze and improve the process, with data gathered through semi-structured interviews to address these issues. The findings highlight that reducing manual labor alleviates workload imbalances and saves time in supply chain automation. Moreover, automating repetitive tasks through well-designed software bots minimizes the risk of human error. While this research focuses on applying RPA in order handling, future studies should explore the potential of artificial intelligence-driven RPA to enhance process automation further.

本研究提出一个机器人流程自动化（RPA）模型，以简化和优化供应链管理中的订单处理程序。当前手工处理订单的方法带来了挑战，包括有限的可访问性和对员工的重大认知要求。信息系统设计方法应用于分析和改进过程，并通过半结构化访谈收集数据来解决这些问题。研究结果强调，减少体力劳动可以缓解工作量不平衡，节省供应链自动化的时间。此外，通过精心设计的软件机器人自动化重复性任务可以最大限度地减少人为错误的风险。虽然本研究侧重于将RPA应用于订单处理，但未来的研究应探索人工智能驱动的RPA的潜力，以进一步提高流程自动化。

引用次数: 0

An investigation of foreign affiliates and supply chain productivity in the European Union industrial sectors 对欧盟工业部门的外国子公司和供应链生产率的调查

Supply Chain Analytics

Pub Date : 2025-01-14 DOI: 10.1016/j.sca.2025.100101

Antonio Frenda , Abdoulaye Kané

This study examines the relationship between foreign affiliates and labour productivity in the supply chains of construction and manufacturing sectors. Labour productivity is calculated using EUKLEMS & INTANProd database of the Luiss Lab of European Economics, while foreign affiliates abroad data are taken from Eurostat. Based on 19 EU countries from 2010 to 2019, we demonstrate how turnover per employee in foreign subsidiaries controlled by the reporting country positively and significantly impacts labour productivity in the construction sector supply chains. Foreign direct investment from these European countries also positively and significantly impacts labour productivity in sectors’ supply chains. Public decision-makers can use this study to highlight elusive fiscal strategies and outline the actual share of domestic and foreign productivity for industrial economic sector supply chains by considering the impact of permanent establishments.

本研究考察了建筑和制造业供应链中外国子公司与劳动生产率之间的关系。劳动生产率是用EUKLEMS &；INTANProd数据库来自路易斯欧洲经济实验室，而国外分支机构的数据来自欧盟统计局。基于2010年至2019年19个欧盟国家的数据，我们展示了报告国控制的外国子公司的人均营业额如何对建筑行业供应链的劳动生产率产生积极而显著的影响。来自这些欧洲国家的外国直接投资也对行业供应链的劳动生产率产生了积极而显著的影响。公共决策者可以利用这项研究来强调难以捉摸的财政战略，并通过考虑常设机构的影响，概述工业经济部门供应链中国内外生产力的实际份额。

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A Bayesian best-worst approach with blockchain integration for optimizing supply chain efficiency through supplier selection 基于区块链集成的供应链效率优化贝叶斯最佳-最差方法

Supply Chain Analytics

Pub Date : 2025-01-02 DOI: 10.1016/j.sca.2024.100100

Azam Modares , Vahideh Bafandegan Emroozi , Pardis Roozkhosh , Azade Modares

Supplier selection is a complex Multi-Criteria Decision-Making (MCDM) problem where decision-maker (DM) preferences heavily influence decision criteria and outcomes. Suitable suppliers capable of meeting performance criteria are central to successful Blockchain Technology (BT) implementation. Numerous qualitative factors influence blockchain adoption within organizations, particularly in the communication between retailers and suppliers via Blockchain, where qualitative uncertainties abound. This study aims to develop a robust system within a probabilistic and fuzzy framework to integrate DMs’ judgments amidst uncertainty effectively. Leveraging the Bayesian best-worst method (BWM), optimal weights for evaluating supplier criteria are determined. This method employs Markov-chain Monte Carlo (MCMC) to calculate the probability of preferring one criterion over another, facilitating confidence level elucidation between criterion pairs and enhancing criteria rankings. Supplier ranking is performed using the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. The efficacy of the proposed approach is demonstrated through a case study utilizing real data from the railway supply chain. Results indicate the model’s effectiveness in optimizing supplier selection and enhancing supply chain performance.

供应商选择是一个复杂的多准则决策（MCDM）问题，其中决策者的偏好严重影响决策标准和结果。合适的供应商能够满足性能标准是区块链技术（BT）成功实施的核心。许多定性因素影响着组织内部区块链的采用，特别是在零售商和供应商之间通过区块链进行沟通时，其中存在大量定性不确定性。本研究旨在建立一个稳健的系统，在概率和模糊的框架内，有效地整合决策者在不确定性中的判断。利用贝叶斯最佳-最差方法（BWM），确定了评估供应商标准的最优权重。该方法采用马尔可夫链蒙特卡罗（MCMC）来计算一个标准优于另一个标准的概率，促进了标准对之间的置信度阐明，提高了标准排名。采用模糊TOPSIS法对供应商进行排序。利用铁路供应链的实际数据，通过一个案例研究证明了所提出方法的有效性。结果表明，该模型在优化供应商选择和提高供应链绩效方面是有效的。

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Supply Chain Analytics

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