Supply Chain Analytics最新文献

An explainable decision model for selecting facility locations in supply chain networks 供应链网络中设施选址的可解释决策模型

Supply Chain Analytics Pub Date : 2025-07-19 DOI: 10.1016/j.sca.2025.100148

Tin-Chih Toly Chen , Yu-Cheng Wang , Yi-Chi Wang

{"title":"An explainable decision model for selecting facility locations in supply chain networks","authors":"Tin-Chih Toly Chen , Yu-Cheng Wang , Yi-Chi Wang","doi":"10.1016/j.sca.2025.100148","DOIUrl":"10.1016/j.sca.2025.100148","url":null,"abstract":"<div><div>Suitable facility location selection for customer-required capacity localization is an emerging topic in semiconductor supply chain management. However, this topic has not been thoroughly investigated. For this reason, an explainable artificial intelligence (XAI)-interpreted fuzzy group decision-making (FGDM) approach is proposed in this study to assist a wafer foundry company in selecting suitable facility locations for customer-required capacity localization. The XAI-interpreted FGDM approach aims to overcome the shortcomings of existing visualization tools and techniques for explaining the facility location selection process. To this end, several new visualization tools and methods have been proposed, including hanging gradient bar charts, gradient bidirectional scatterplots, and hanging gradient bar charts for traceable aggregation. After applying the XAI-interpreted FGDM approach to a real case, the new XAI tools enhanced the explainability of the facility location selection process and results. The advantage over the existing XAI tools was up to 36 %. In addition, Shapley additive explanations (SHAP) analysis results showed that the factors that impact the assessment results most may be inconsistent with the original judgments of domain experts.</div></div>","PeriodicalId":101186,"journal":{"name":"Supply Chain Analytics","volume":"11 ","pages":"Article 100148"},"PeriodicalIF":0.0,"publicationDate":"2025-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144662268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A stochastic programming approach to the location of distribution centers for multinational enterprises under demand uncertainty 需求不确定性下跨国企业配送中心选址的随机规划方法

Supply Chain Analytics Pub Date : 2025-07-11 DOI: 10.1016/j.sca.2025.100147

Kuancheng Huang , Wei-Ting Chen , Yu-Ching Wu , Jan-Ren Chen

{"title":"A stochastic programming approach to the location of distribution centers for multinational enterprises under demand uncertainty","authors":"Kuancheng Huang , Wei-Ting Chen , Yu-Ching Wu , Jan-Ren Chen","doi":"10.1016/j.sca.2025.100147","DOIUrl":"10.1016/j.sca.2025.100147","url":null,"abstract":"<div><div>Multinational enterprises (MNEs) often collaborate with local agents to establish initial distribution channels due to their need for market-specific knowledge and experience. As the market matures and upstream suppliers and production plans are solidified, MNEs may transition to developing their distribution systems and supply chain networks. Integrating the transportation network among upstream material suppliers, production facilities, and distribution centers (DCs) becomes crucial at this stage. Since transportation costs constitute a significant portion of enterprise expenses, optimizing upstream transportation is essential for MNEs following this market entry strategy. This study aims to optimize the location decisions of DCs while assuming that suppliers, plants, and retailers have fixed locations. A critical focus is the integration of upstream transportation operations, specifically between suppliers and plants and between plants and DCs, to minimize inefficient empty backhauls. Additionally, demand uncertainty is factored into this long-term strategic design problem. A stochastic programming (SP) model is developed, and a solution procedure based on the Genetic Algorithm (GA) is designed to handle practical-scale problems. Numerical experiments demonstrate that the GA method achieves a solution quality with less than a 1 % gap compared to the optimal solution while also significantly reducing computation time.</div></div>","PeriodicalId":101186,"journal":{"name":"Supply Chain Analytics","volume":"11 ","pages":"Article 100147"},"PeriodicalIF":0.0,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144656680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An analytical exploration of barriers to resilient circular food supply chains using integrated structural methods 利用综合结构方法对弹性循环食品供应链的障碍进行分析探索

Supply Chain Analytics Pub Date : 2025-07-09 DOI: 10.1016/j.sca.2025.100144

Emel Yontar

{"title":"An analytical exploration of barriers to resilient circular food supply chains using integrated structural methods","authors":"Emel Yontar","doi":"10.1016/j.sca.2025.100144","DOIUrl":"10.1016/j.sca.2025.100144","url":null,"abstract":"<div><div>This study addresses the critical research problem of how to achieve resilience in food supply chains transitioning from linear to circular models. While circular food supply chains aim to enhance sustainability, reduce waste, and improve resource efficiency, they face complex systemic barriers that make resilience a challenging goal. To explore these barriers, the research adopts a hybrid methodological framework combining Interpretive Structural Modeling (ISM), MICMAC analysis (Cross-Impact Matrix Multiplication Applied to Classification), and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method. This integrative approach enables the identification and classification of key obstacles based on their hierarchical structure and interdependence. The findings reveal that legal uncertainties and lack of incentives, financial difficulties, and technological immaturity are the most influential root barriers undermining Circular Economy-oriented Food Supply Chain Resilience (FSCR). These insights provide a structured understanding of the cause-effect relationships between challenges, offering practical guidance for policymakers, practitioners, and researchers seeking to build resilient and circular food supply chains amid increasing global disruptions.</div></div>","PeriodicalId":101186,"journal":{"name":"Supply Chain Analytics","volume":"11 ","pages":"Article 100144"},"PeriodicalIF":0.0,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144597511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An optimization framework for sustainable closed-loop supply chains with green investment and recovery policy 具有绿色投资和回收政策的可持续闭环供应链优化框架

Supply Chain Analytics Pub Date : 2025-07-08 DOI: 10.1016/j.sca.2025.100146

Wakhid Ahmad Jauhari , Dhea Naomi Kenlaksita , Nughthoh Arfawi Kurdhi , Dana Marsetiya Utama

{"title":"An optimization framework for sustainable closed-loop supply chains with green investment and recovery policy","authors":"Wakhid Ahmad Jauhari , Dhea Naomi Kenlaksita , Nughthoh Arfawi Kurdhi , Dana Marsetiya Utama","doi":"10.1016/j.sca.2025.100146","DOIUrl":"10.1016/j.sca.2025.100146","url":null,"abstract":"<div><div>Sustainability in closed-loop supply chains (CLSCs) is becoming a significant focus due to increasing environmental pressures and carbon regulations. While numerous studies have examined aspects such as carbon emissions, green technology, and the quality of used products, gaps remain in integrating these elements, particularly concerning the influence of collection quality on emissions, various recovery policies, and contract-based coordination mechanisms for sharing green technology investments. This study aims to develop a comprehensive supply chain model by integrating these factors through three main mechanisms: centralized coordination, decentralized, and green technology revenue investment sharing (GRIS) contracts. The model employs a mathematical formulation that considers green technology investment, collection rate, the quality of used products, and carbon emissions. Simulations were conducted with sensitivity analysis to evaluate the impact of parameters such as carbon tax, selling price sensitivity coefficient, green technology investment, and collection effort on system performance. Results indicate that the centralized coordination model excels in maximizing total profit and operational stability when compared to the decentralized model. However, it is more sensitive to changes in parameters. GRIS contracts offer flexibility in profit redistribution between producers and retailers without compromising the system efficiency. The findings also indicate that investments in green technology and collection efforts significantly contribute to enhanced collection quality and reduced carbon emissions, with more pronounced effects in the centralized model. This research offers a comprehensive approach to tackling sustainability challenges in CLSC, providing practical insights for industry stakeholders and policymakers in developing strategies that promote both economic and environmental sustainability.</div></div>","PeriodicalId":101186,"journal":{"name":"Supply Chain Analytics","volume":"11 ","pages":"Article 100146"},"PeriodicalIF":0.0,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144605471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An analytical framework for optimizing supply chain operations with lean practices 用精益实践优化供应链操作的分析框架

Supply Chain Analytics Pub Date : 2025-07-06 DOI: 10.1016/j.sca.2025.100145

Amber Batwara , Shailesh Kediya , Ravindra A. Kayande

{"title":"An analytical framework for optimizing supply chain operations with lean practices","authors":"Amber Batwara , Shailesh Kediya , Ravindra A. Kayande","doi":"10.1016/j.sca.2025.100145","DOIUrl":"10.1016/j.sca.2025.100145","url":null,"abstract":"<div><div>Integrating lean principles into supply chain (SC) management has gained significant attention, but the emphasis on sustainability remains limited. This study addresses this gap by introducing a comprehensive Supply Chain Value Stream Mapping (SC-VSM) framework to enhance sustainability performance while maintaining operational efficiency. SC-VSM combines lean tools and techniques to streamline processes, reduce waste, and foster continuous improvement within a holistic supply chain system. A detailed literature review identifies key lean practices applicable to SC management, emphasizing the need for a strategic approach to align operational goals, build trust-based partnerships, and address technological uncertainties. The proposed SC-VSM framework is validated through a Fly Ash Brick Manufacturing Plant case study. The study evaluates the framework's effectiveness in optimizing processes, minimizing waste, and enhancing sustainability outcomes. The findings highlight SC-VSM's practical advantages in achieving sustainable supply chain goals, particularly for small and medium-sized enterprises. This research closes the theoretical and practical gap in lean SC management by providing a validated model that integrates sustainability into supply chain operations.</div></div>","PeriodicalId":101186,"journal":{"name":"Supply Chain Analytics","volume":"11 ","pages":"Article 100145"},"PeriodicalIF":0.0,"publicationDate":"2025-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144579409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An analytics-driven circular supply chain framework integrating quality, warranty, and human efficiency 一个分析驱动的循环供应链框架，集成了质量、保证和人力效率

Supply Chain Analytics Pub Date : 2025-07-05 DOI: 10.1016/j.sca.2025.100140

Lalji Kumar, Uttam Kumar Khedlekar

{"title":"An analytics-driven circular supply chain framework integrating quality, warranty, and human efficiency","authors":"Lalji Kumar, Uttam Kumar Khedlekar","doi":"10.1016/j.sca.2025.100140","DOIUrl":"10.1016/j.sca.2025.100140","url":null,"abstract":"<div><div>This paper presents an advanced human-centric circular supply chain optimization framework that integrates economic, environmental, and behavioral dimensions into a unified multi-objective model. By jointly optimizing selling price, product quality, warranty duration, and production cycle time, the model captures the intricate trade-offs between profitability and sustainability-related penalties. A distinctive feature of the framework is the incorporation of a Human Efficiency Index and a circularity-based return function, enabling dynamic modeling of skill-driven waste minimization and quality-sensitive consumer behavior. The resulting nonlinear optimization problem is addressed using four powerful metaheuristic algorithms—Teaching-Learning-Based Optimization (TLBO), TLBO with Learning Rate, Non-dominated Sorting Genetic Algorithm II (NSGA-II), and Multi-Objective Particle Swarm Optimization (MOPSO). Extensive numerical simulations demonstrate the efficacy of the TLBO-based methods in achieving high-profit, low-penalty solutions, while statistical analyses confirm their robustness and superiority through the Friedman test and the Wilcoxon signed-rank test. From a managerial perspective, the model offers critical insights for aligning operational decisions with sustainability-oriented goals by demonstrating the nonlinear effects of human efficiency and product lifecycle attributes on supply chain performance. From a policy standpoint, the findings advocate for institutional mechanisms that incentivize investment in skill development, recycling, and circularity-driven design practices. Furthermore, the social relevance of this work lies in its contribution to Industry 5.0 paradigms, where inclusive, sustainable, and human-empowered production systems are prioritized. This research thus provides a robust, actionable framework for decision-makers seeking to design resilient and circular supply chains that promote long-term economic value and social welfare.</div></div>","PeriodicalId":101186,"journal":{"name":"Supply Chain Analytics","volume":"11 ","pages":"Article 100140"},"PeriodicalIF":0.0,"publicationDate":"2025-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144588252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An EPQ-based optimization approach to variable-rate screening in supply chain production systems 基于epq的供应链生产系统可变率筛选优化方法

Supply Chain Analytics Pub Date : 2025-07-05 DOI: 10.1016/j.sca.2025.100143

Amir Hossein Nobil , Erfan Nobil , Ericka Zulema Rodríguez Calvo , Mostafa Hajiaghaei-Keshteli

{"title":"An EPQ-based optimization approach to variable-rate screening in supply chain production systems","authors":"Amir Hossein Nobil , Erfan Nobil , Ericka Zulema Rodríguez Calvo , Mostafa Hajiaghaei-Keshteli","doi":"10.1016/j.sca.2025.100143","DOIUrl":"10.1016/j.sca.2025.100143","url":null,"abstract":"<div><div>This study presents a comprehensive framework for optimizing the Economic Production Quantity (EPQ) with variable screening rates under two distinct inspection scenarios: Sufficient-Inspection-Rate (IRS) and Insufficient-Inspection-Rate (IRI). In the IRS scenario, the production system employs a high screening rate exceeding the production rate, enabling immediate inspection post-production to segregate imperfect and perfect items. Conversely, the IRI scenario features a slower screening rate relative to production, with inspection occurring post-production completion. The study incorporates inspection costs, and the percentage of imperfect items detected using decreasing exponential functions dependent on screening rate. A Sequential Quadratic Programming (SQP) approach is employed to solve both nonlinear models efficiently.</div><div>The analysis demonstrates that adopting a high screening rate (Model I) offers significant production efficiency and cost-effectiveness advantages. For instance, the total cost under the IRS scenario is approximately $394,522, which is notably lower than that of the IRI scenario. A comprehensive sensitivity analysis shows that holding cost, defect rate, and inspection parameters significantly influence both the production quantity and total cost, with the IRI scenario being more sensitive to these changes. These findings underscore the importance of selecting appropriate inspection strategies based on operational constraints and cost dynamics.</div></div>","PeriodicalId":101186,"journal":{"name":"Supply Chain Analytics","volume":"11 ","pages":"Article 100143"},"PeriodicalIF":0.0,"publicationDate":"2025-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144597512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A multi-objective analytical framework for sustainable blood supply chain optimization 可持续血液供应链优化的多目标分析框架

Supply Chain Analytics Pub Date : 2025-06-27 DOI: 10.1016/j.sca.2025.100142

Agus Mansur , Taufiq Hidayat , Novrianty Rizky , Ivan Darma Wangsa

{"title":"A multi-objective analytical framework for sustainable blood supply chain optimization","authors":"Agus Mansur , Taufiq Hidayat , Novrianty Rizky , Ivan Darma Wangsa","doi":"10.1016/j.sca.2025.100142","DOIUrl":"10.1016/j.sca.2025.100142","url":null,"abstract":"<div><div>This study presents a multi-objective optimization model for blood supply chain (BSC) management, aiming to maximize total profit and fulfillment rate and minimize carbon emissions. The model is formulated as a mixed-integer linear program (MILP) and solved using the weighted sum method. The BSCM is structured as a multi-echelon network involving blood mobiles, local blood centers, regional blood banks (RBBs), hospitals, and healthcare facilities. Assumptions include deterministic demand and fixed blood shelf life. A case study in East Kalimantan, Indonesia, shows a total revenue of Indonesian Rupiah (IDR) of 13.07 billion and a total cost of IDR 8.58 billion, resulting in a profit of IDR 4.49 billion. The fulfillment rates for hospitals and healthcare facilities are 109.13 % and 154.57 %, respectively. Total emissions reach 203.94-kilogram CO<sub>2</sub> equivalent (kg CO<sub>2</sub>e), mainly from production. Sensitivity analysis highlights the impact of demand, capacity, and pricing on supply chain performance. Furthermore, transshipment among RBBs plays a vital role in balancing inventory levels, though excessive transshipment may lead to increased costs and emissions.</div></div>","PeriodicalId":101186,"journal":{"name":"Supply Chain Analytics","volume":"11 ","pages":"Article 100142"},"PeriodicalIF":0.0,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144518426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An inventory optimization model for reliable and sustainable supply chains under trade credit and carbon constraints 贸易信用和碳约束下可靠可持续供应链的库存优化模型

Supply Chain Analytics Pub Date : 2025-06-23 DOI: 10.1016/j.sca.2025.100132

Ankur Saurav, Vijender Yadav, Chandra Shekhar

{"title":"An inventory optimization model for reliable and sustainable supply chains under trade credit and carbon constraints","authors":"Ankur Saurav, Vijender Yadav, Chandra Shekhar","doi":"10.1016/j.sca.2025.100132","DOIUrl":"10.1016/j.sca.2025.100132","url":null,"abstract":"<div><div>The adoption of environmentally sound supply chain management strategies is gaining prominence in response to increasing sustainability efforts in emerging economies. As global environmental degradation escalates, industries are compelled to replace conventional products with green and reliable alternatives. This research introduces a dual-objective strategy aimed at minimizing operational costs while ensuring environmental preservation, focusing on identifying optimal approaches for production firms to achieve cost reduction alongside sustainability within the supply chain. It enables strategic insights in supply chain management to optimize inventory decisions, enhance financial adaptability, and ensure environmental compliance while maintaining profitability and reliability. Additionally, the study examines the impact of a two-level trade credit policy for a supplier-manufacturer-customer supply chain across nine scenarios based on credit periods. Four key contributions include (i) the evaluation of product greenness, reliability, price, and advertising on demand and deterioration rates; (ii) the analysis of reliability’s effect on production systems; (iii) the assessment of green technologies and cap-and-tax policies in emissions reduction; and (iv) the exploration of a partial two-level trade credit policy within a reliable production-based supply chain framework. The objective is to determine optimal investments in green technology, production run time, and cycle time to minimize total system costs, supported by numerical examples and graphical illustrations, offering insights for sustainable supply chain development in emerging economies.</div></div>","PeriodicalId":101186,"journal":{"name":"Supply Chain Analytics","volume":"11 ","pages":"Article 100132"},"PeriodicalIF":0.0,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144490151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A two-layer approach to analyzing imbalance in signed supply chain networks using probability-based triad census 基于概率的三元统计的两层供应链网络不平衡分析方法

Supply Chain Analytics Pub Date : 2025-06-23 DOI: 10.1016/j.sca.2025.100141

Mansooreh Mirzaie , Maryam Nooraei Abadeh , Sondos Bahadori , Ji Zhang

{"title":"A two-layer approach to analyzing imbalance in signed supply chain networks using probability-based triad census","authors":"Mansooreh Mirzaie , Maryam Nooraei Abadeh , Sondos Bahadori , Ji Zhang","doi":"10.1016/j.sca.2025.100141","DOIUrl":"10.1016/j.sca.2025.100141","url":null,"abstract":"<div><div>Signed supply chain networks are essential for representing relationships between entities in commercial activities. Imbalances in these relationships can lead to significant consequences, including financial losses and reputational damage. This paper presents a two-layer analytical framework designed to identify and address imbalances in signed supply chain networks. The approach begins by mapping the initial Person-Other-X (P-O-X) layer onto the network’s signed nodes, establishing a foundational framework for the analysis. Throughout the network’s evolution, the method rigorously tracks its dynamics, focusing on assessing and improving the overall balance of the supply chain network. The analysis employs probability-based triad motifs to evaluate the impact of strategic sign changes on the network’s structure. This provides valuable insights into how alterations to supplier-manufacturer, distributor-customer, or other critical relationships affect the network’s stability. Sensitivity analysis is used to identify essential nodes or regions where sign changes substantially impact the network’s structural patterns. A comparative study of the probability-based Triad Census is conducted to understand the effects of sign changes on the network structure. Key contributions include the identification of influential nodes using centrality metrics and the impact of their sign changes on structural balance. The study’s findings emphasize the significant role of Betweenness Centrality in fostering balanced relationships within the supply chain network. This underscores the importance of key nodes, such as critical suppliers or distribution centers, in ensuring the overall stability and performance of the commercial network. Finally, this proactive strategy ensures a smoother flow of goods through the network, ultimately boosting performance and competitiveness in the marketplace.</div></div>","PeriodicalId":101186,"journal":{"name":"Supply Chain Analytics","volume":"11 ","pages":"Article 100141"},"PeriodicalIF":0.0,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144490112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0