Supply Chain Analytics最新文献_第6页

A structural equation modeling framework for exploring the industry 5.0 and sustainable supply chain determinants 探索工业 5.0 和可持续供应链决定因素的结构方程建模框架

Supply Chain Analytics Pub Date : 2024-02-23 DOI: 10.1016/j.sca.2024.100060

Md. Asfaq Jamil , Ridwan Mustofa , Niamat Ullah Ibne Hossain , S.M. Atikur Rahman , Sudipta Chowdhury

{"title":"A structural equation modeling framework for exploring the industry 5.0 and sustainable supply chain determinants","authors":"Md. Asfaq Jamil , Ridwan Mustofa , Niamat Ullah Ibne Hossain , S.M. Atikur Rahman , Sudipta Chowdhury","doi":"10.1016/j.sca.2024.100060","DOIUrl":"https://doi.org/10.1016/j.sca.2024.100060","url":null,"abstract":"<div><p>Sustainable Supply Chain and Industry 5.0 are two important concepts reshaping how businesses operate in the modern world. Together, these two concepts drive the advancement of a highly sustainable and robust worldwide economy. Companies are now becoming more sustainable in supply chain management, using technologies like blockchain and co-bots to track the origin of goods, ensure ethical and sustainable sourcing, and work with humans safely and effectively. This study develops a theoretical model highlighting the determinants of Industry 5.0, Sustainable Supply Chain Practices, by combining theoretical frameworks from the manufacturing, supply chain, and information systems literature. The study's analytic sample comprises 342 responses collected from professionals working in the electronics industry's supply chain. Hypotheses were constructed employing deductive reasoning, leveraging insights gleaned from prior research. The study is conducted utilizing the Structural Equation Modeling (SEM) to substantiate the presumed connections among various constructs, namely, Industry 5.0 innovations, Sustainable Supply Chain Practices (SSCP), Sustainable Supply Chain Performance (SCP), and Supply Chain Risks (SCR). The Structural Equation Modeling analysis results show a direct impact of Industry 5.0 technologies through Sustainable Supply Chain Practices can enhance Supply Chain Performance and mitigate Supply Chain Risks. Combining the two paradigms can foster the development of new business models that prioritize sustainability and contribute to a more equitable and environmentally friendly economy that brings positive change for both businesses and society.</p></div>","PeriodicalId":101186,"journal":{"name":"Supply Chain Analytics","volume":"6 ","pages":"Article 100060"},"PeriodicalIF":0.0,"publicationDate":"2024-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949863524000037/pdfft?md5=ca37ba3c40098df3ff5dab249aea7510&pid=1-s2.0-S2949863524000037-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139992975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A machine learning framework for predicting weather impact on retail sales 预测天气对零售额影响的机器学习框架

Supply Chain Analytics Pub Date : 2024-02-15 DOI: 10.1016/j.sca.2024.100058

H. Chan, M.I.M. Wahab

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引用次数: 0

A bi-objective sustainable vehicle routing optimization model for solid waste networks with internet of things 物联网固体废物网络的双目标可持续车辆路由优化模型

Supply Chain Analytics Pub Date : 2024-02-14 DOI: 10.1016/j.sca.2024.100059

Shabnam Rekabi , Zeinab Sazvar , Fariba Goodarzian

{"title":"A bi-objective sustainable vehicle routing optimization model for solid waste networks with internet of things","authors":"Shabnam Rekabi , Zeinab Sazvar , Fariba Goodarzian","doi":"10.1016/j.sca.2024.100059","DOIUrl":"https://doi.org/10.1016/j.sca.2024.100059","url":null,"abstract":"<div><p>Waste production is growing in most communities due to population expansion. Given the stated issue, managing the Solid Waste (SW) created worldwide would be vital. Effective Waste Management (WM) is essential to preserving the environment and lowering pollution. It aids in resource preservation, greenhouse gas emission reduction, and ecosystem protection. Additionally, the promotion of public health and sanitation is significantly aided by WM procedures. This study presents an integrated procedure to enhance the operations of a WM network for recycling SW. We propose a mathematical model to find the optimal sustainable vehicle routes, allocation, and Sequence Scheduling (SS) problem in the recycling industry to reduce costs and CO<sub>2</sub> emissions and increase job opportunities. The fundamental innovation of this work is considering waste-vehicle and waste-technology compatibility and Internet of Things (IoT) systems in the model to decrease CO<sub>2</sub> emissions and identify compatible waste for recycling centers to produce more final products. An LP-metric and an Epsilon Constraint (EC) approach are used to solve the suggested model. By comparing the two approaches, we have found EC performs better in results and CPU time. As a result, various test problems of different sizes are offered. Accordingly, sensitivity analyses are recommended to assess the suggested model’s effectiveness. Using vehicles compatible with waste reduces CO<sub>2</sub> emissions. Utilizing IoT technology and optimization methods makes it feasible to save costs (20%), have a less destructive impact on the environment (36%), and ultimately increase the sustainability of the WM process.</p></div>","PeriodicalId":101186,"journal":{"name":"Supply Chain Analytics","volume":"5 ","pages":"Article 100059"},"PeriodicalIF":0.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949863524000025/pdfft?md5=9d25a58b62d324ef0e2f9cf4bd94f279&pid=1-s2.0-S2949863524000025-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139748223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Machine Learning Framework for Predicting Weather Impact on Retail Sales 预测天气对零售额影响的机器学习框架

Supply Chain Analytics Pub Date : 2024-02-01 DOI: 10.1016/j.sca.2024.100058

H. Chan, M.I.M. Wahab

引用次数: 0

An optimization model for sustainable multi-product multi-echelon supply chain networks with U-shaped assembly line balancing under uncertainty 不确定性条件下 U 型装配线平衡的可持续多产品多基地供应链网络优化模型

Supply Chain Analytics Pub Date : 2023-12-26 DOI: 10.1016/j.sca.2023.100057

Mehrzad Sheibani , Sadegh Niroomand

{"title":"An optimization model for sustainable multi-product multi-echelon supply chain networks with U-shaped assembly line balancing under uncertainty","authors":"Mehrzad Sheibani , Sadegh Niroomand","doi":"10.1016/j.sca.2023.100057","DOIUrl":"https://doi.org/10.1016/j.sca.2023.100057","url":null,"abstract":"<div><p>This study presents an integrated supply chain network with suppliers, manufacturers, assemblers, and customers. The proposed model considers a U-shaped assembly line with three sustainability objective functions. We consider assumptions considering different types of raw materials, multiple products, location selection of manufacturers, location selection of assemblers, and capacity of suppliers. The problem is formulated non-linear and then linearized as a multi-objective model. Some cost and demand parameters are considered uncertain and are represented by fuzzy sets and theory. The proposed uncertain model is first converted to a multi-objective crisp model by applying the modified robust possibilistic programming approach. Then, the obtained crisp multi-objective model is solved by an interactive-fuzzy optimization approach in the literature. For computational study, some test problems are generated and solved using an original deterministic formulation and the crisp form of the uncertain formulation. The obtained results are analyzed and compared according to the objective function values. Finally, an extensive sensitivity analysis is performed on the parameters of the models.</p></div>","PeriodicalId":101186,"journal":{"name":"Supply Chain Analytics","volume":"5 ","pages":"Article 100057"},"PeriodicalIF":0.0,"publicationDate":"2023-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949863523000560/pdfft?md5=cd211d8df17a2533e3a937f1f5a4d854&pid=1-s2.0-S2949863523000560-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139100964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An exploration of quantitative models and algorithms for vehicle routing optimization and traveling salesman problems 车辆路线优化和旅行推销员问题的定量模型和算法探索

Supply Chain Analytics Pub Date : 2023-12-21 DOI: 10.1016/j.sca.2023.100056

Oskari Lähdeaho , Olli-Pekka Hilmola

引用次数: 0

A systematic review of collaboration in supply chain 4.0 with meta-synthesis method 基于元综合方法的供应链4.0协作系统综述

Supply Chain Analytics Pub Date : 2023-12-01 DOI: 10.1016/j.sca.2023.100052

Aminmasoud Bakhshi Movahed, Alireza Aliahmadi, Mohammadreza Parsanejad, Hamed Nozari

{"title":"A systematic review of collaboration in supply chain 4.0 with meta-synthesis method","authors":"Aminmasoud Bakhshi Movahed, Alireza Aliahmadi, Mohammadreza Parsanejad, Hamed Nozari","doi":"10.1016/j.sca.2023.100052","DOIUrl":"https://doi.org/10.1016/j.sca.2023.100052","url":null,"abstract":"<div><p>A systematic literature review is conducted to analyze and synthesize studies on supply chain collaboration in Industry 4.0 between 2010 and 2023. 152 documents were selected from various databases. The meta-synthesis method categorizes 8 Initiators, 8 Barriers, 7 dimensions, and 4 Outcomes of collaboration. The findings show that collaboration in supply chain 4.0, with the activation of drivers and enablers such as Industry 4.0 technologies, Information and communication technology infrastructure, and with the control of barriers such as Personal benefits and Operational and structural issues can utilize information and communication technologies to highlight sustainable performance and trust throughout the supply chain. The study develops the existing literature and persuades businesses and the scientific community to investigate the power of collaboration in supply chain partner activities. The analytical model in this study focusing on four main sections, can serve as a basis for conducting new research in the development of collaboration.</p></div>","PeriodicalId":101186,"journal":{"name":"Supply Chain Analytics","volume":"4 ","pages":"Article 100052"},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949863523000511/pdfft?md5=9545b00b8396d61239ac118ab86a6647&pid=1-s2.0-S2949863523000511-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138466565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A hybrid fuzzy decision-making trial and evaluation laboratory and multi-criteria decision-making approach for successful implementation of supply chain collaboration strategies 供应链协同战略成功实施的混合模糊决策试验与评价实验室和多准则决策方法

Supply Chain Analytics Pub Date : 2023-11-30 DOI: 10.1016/j.sca.2023.100053

Rakesh Kumar Malviya , Ravi Kant , Praveen Kumar , Swapnil Lahane , Akshay A. Pujara

{"title":"A hybrid fuzzy decision-making trial and evaluation laboratory and multi-criteria decision-making approach for successful implementation of supply chain collaboration strategies","authors":"Rakesh Kumar Malviya , Ravi Kant , Praveen Kumar , Swapnil Lahane , Akshay A. Pujara","doi":"10.1016/j.sca.2023.100053","DOIUrl":"https://doi.org/10.1016/j.sca.2023.100053","url":null,"abstract":"<div><p>This study proposes an integrated framework for successfully implementing collaboration strategies in supply chain (SC) management using a fuzzy decision-making trial and evaluation laboratory (DEMATEL) and multi-criteria decision-making (MCDM) approach. The study analyses and measures the successful possibility of SC collaboration implementation in small and medium enterprises (SMEs). The fuzzy DEMATEL is used to evaluate the weight of each criterion, and fuzzy MCDM is used to assess the possible success rates of the collaboration strategies. The result shows that top management support and commitment, SC strategic planning, information sharing, goal congruence, organizational compatibility, and decision synchronization are major factors responsible for SC collaboration success in SMEs. This study helps predict the effectiveness of collaboration strategies and indicates remedial activities in the existing collaborative environment by undertaking corrective actions and measures to increase implementation success.</p></div>","PeriodicalId":101186,"journal":{"name":"Supply Chain Analytics","volume":"5 ","pages":"Article 100053"},"PeriodicalIF":0.0,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949863523000523/pdfft?md5=0948d7b3c90f0782da8c5ffd2d774a56&pid=1-s2.0-S2949863523000523-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138501498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Exploitation of material consolidation trade-offs in multi-tier complex supply networks 多层复杂供应网络中材料整合权衡的开发

Supply Chain Analytics Pub Date : 2023-11-19 DOI: 10.1016/j.sca.2023.100050

Vinod Kumar Chauhan , Muhannad Alomari , James Arney , Ajith Kumar Parlikad , Alexandra Brintrup

{"title":"Exploitation of material consolidation trade-offs in multi-tier complex supply networks","authors":"Vinod Kumar Chauhan , Muhannad Alomari , James Arney , Ajith Kumar Parlikad , Alexandra Brintrup","doi":"10.1016/j.sca.2023.100050","DOIUrl":"https://doi.org/10.1016/j.sca.2023.100050","url":null,"abstract":"<div><p>While consolidation strategies form the backbone of many supply chain optimisation problems, exploitation of multi-tier material relationships through consolidation remains an understudied area, despite being a prominent feature of industries that produce complex made-to-order products. In this paper, we propose an optimisation framework for exploiting multi-to-multi relationship between tiers of a supply chain. The resulting formulation is flexible such that quantity discounts, inventory holding, and transport costs can be included. The framework introduces a new trade-off between tiers, leading to cost reductions in one tier but increased costs in the other, which helps to reduce the overall procurement cost in the supply chain. A mixed integer linear programming model is developed and tested with a range of small to large-scale test problems from aerospace manufacturing. Our comparison to benchmark results shows that there is indeed a cost trade-off between two tiers, and that its reduction can be achieved using a holistic approach to reconfiguration. Costs are decreased when second tier fixed ordering costs and the number of machining options increase. Consolidation results in reduced inventory holding costs in all scenarios. Several secondary effects such as simplified supplier selection may also be observed.</p></div>","PeriodicalId":101186,"journal":{"name":"Supply Chain Analytics","volume":"4 ","pages":"Article 100050"},"PeriodicalIF":0.0,"publicationDate":"2023-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949863523000493/pdfft?md5=aba4c0088aa577c9e215afa41012c42c&pid=1-s2.0-S2949863523000493-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138436355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

An integrated integer programming and forecasting model with geographic information systems for spray operations of West Nile disease insecticides 基于地理信息系统的西尼罗病杀虫剂喷洒作业集成整数规划与预测模型

Supply Chain Analytics Pub Date : 2023-11-08 DOI: 10.1016/j.sca.2023.100049

Hokey Min , Emanuel Melachrinoudis

引用次数: 0