Supply Chain Analytics最新文献_第10页

A supply chain risk assessment index for small and medium enterprises in post COVID-19 era 后新冠肺炎时代中小企业供应链风险评估指标

Supply Chain Analytics Pub Date : 2023-09-01 DOI: 10.1016/j.sca.2023.100023

Harish Babu , Susheel Yadav

引用次数: 5

Comparative analysis of lean and agile supply chain strategies for effective vaccine distribution in pandemics: A case study of COVID-19 in a densely populated developing region 大流行期间疫苗有效配送的精益供应链与敏捷供应链策略对比分析——以人口密集发展中地区COVID-19为例

Supply Chain Analytics Pub Date : 2023-09-01 DOI: 10.1016/j.sca.2023.100022

Kasuni R.R. Gomes , H. Niles Perera , Amila Thibbotuwawa , N.P. Sunil-Chandra

{"title":"Comparative analysis of lean and agile supply chain strategies for effective vaccine distribution in pandemics: A case study of COVID-19 in a densely populated developing region","authors":"Kasuni R.R. Gomes , H. Niles Perera , Amila Thibbotuwawa , N.P. Sunil-Chandra","doi":"10.1016/j.sca.2023.100022","DOIUrl":"https://doi.org/10.1016/j.sca.2023.100022","url":null,"abstract":"<div><p>Mass vaccination programs should employ effective strategies to design a resilient vaccine supply chain for immunizing populations quickly and efficiently. The need for more flexible and responsive vaccine supply chain design is highlighted during the pandemic, where authorities are required to effectively execute vaccine distribution. Our study proposes a scientifically driven approach to identify suitable supply chain strategies for vaccine distribution, enhancing the effectiveness of mass vaccination. We propose a two-stage approach for identifying the best supply chain strategy that supports faster vaccine rollouts, reducing infections and deaths during the pandemic. We optimize the vaccine distribution network under both supply chain strategies using Mixed Integer Programming (MIP) for four disruption scenarios in the first stage. Second, we have used systems dynamics simulation and the Susceptible-Exposed-Infectious-Recovered (SEIR) model for pandemics to identify the impact of vaccination. In all disruption scenarios, vaccine distribution using the Lean strategy is less costly, and the Agile strategy reduces lead time and supports faster vaccine rollout. We show achieving a cost-saving or lead-time saving using either supply chain strategy becomes increasingly difficult when the severity of disruptions at storage increases. Our study suggests a novel methodology that determines the most suitable strategy for vaccine distribution which minimizes infections and deaths under several disruption scenarios. The decision-makers can identify appropriate supply chain strategies for vaccine delivery to densely populated developing regions, using the proposed framework which compares supply chain strategies’ impact on vaccine distribution network design.</p></div>","PeriodicalId":101186,"journal":{"name":"Supply Chain Analytics","volume":"3 ","pages":"Article 100022"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49759343","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: 2

A supply chain performance assessment model in multinational enterprises using foreign affiliates statistics 基于国外关联公司统计的跨国企业供应链绩效评估模型

Supply Chain Analytics Pub Date : 2023-09-01 DOI: 10.1016/j.sca.2023.100030

Antonio Frenda , Stefano D’Ottavi

{"title":"A supply chain performance assessment model in multinational enterprises using foreign affiliates statistics","authors":"Antonio Frenda , Stefano D’Ottavi","doi":"10.1016/j.sca.2023.100030","DOIUrl":"https://doi.org/10.1016/j.sca.2023.100030","url":null,"abstract":"<div><p>With a globalized economy, traditional boundaries are becoming both unclear and uncertain, and it is necessary to analytically measure business globalization to estimate the results of the production activity of resident producer units. The value chains that have bound the world economy are now under new strain. This study presents an analysis of data relating to the activities carried out by a company in multinational territories. We study the distribution of the added value of companies and the relationship with their non-domestic activities for statistical purposes; the type of foreign affiliate known as a branch is considered a quasi-enterprise (Eurostat − Manual on Business Demography Statistics, 2007), resident in one country and controlled by a unit resident in another nation. We use two separate sources of sectoral information for a specific year (2019): Foreign Affiliates Statistics (FATS), covering activities of permanent establishments operating among Italian borders under foreign control, and outward FATS covering the activities of Italian branches abroad. Hence it can be difficult to untangle these complex chains of control; as we detail in this work, the integrated use of archives, statistical, administrative, and tax sources, as well as other information (company sites, profiling of the main multinational groups) allows to select the subset of companies potentially interested in the reality of foreign production a priori, to identify affiliates that are not constituting separate legal entities. This study can be used by public decision maker to highlight fiscal elusive strategies and estimate the real share of domestic and foreign (through stable organizations) production.</p></div>","PeriodicalId":101186,"journal":{"name":"Supply Chain Analytics","volume":"3 ","pages":"Article 100030"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49751194","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 new key performance indicator model for demand forecasting in inventory management considering supply chain reliability and seasonality 考虑供应链可靠性和季节性的库存管理需求预测关键绩效指标模型

Supply Chain Analytics Pub Date : 2023-09-01 DOI: 10.1016/j.sca.2023.100026

Yasin Tadayonrad, Alassane Balle Ndiaye

{"title":"A new key performance indicator model for demand forecasting in inventory management considering supply chain reliability and seasonality","authors":"Yasin Tadayonrad, Alassane Balle Ndiaye","doi":"10.1016/j.sca.2023.100026","DOIUrl":"https://doi.org/10.1016/j.sca.2023.100026","url":null,"abstract":"<div><p>Forecasting demand and determining safety stocks are key aspects of supply chain planning. Demand forecasting involves predicting future demand for a product or service using historical data and other external and internal drivers. Stockouts and excess production can be reduced by accurately forecasting demand. This allows companies to plan production, inventory, and logistics more effectively. Companies maintain safety stocks in their inventory to protect against unexpected changes in demand or supply. A company must find the appropriate safety stock level to meet customer demands while avoiding excess inventory and carrying costs. Forecasting demand and determining safety stocks work together to help companies reduce costs, improve customer service, and optimize inventory levels. Key Performance Indicators (KPIs) are commonly used to measure model performance. Classical forecasting models mostly concern themselves with minimizing forecast errors. However, the impact on inventory costs is not directly considered. In this paper, we introduce a Key Performance Indicator to be used in the demand forecasting process that produces more efficient results in terms of inventory costs. We also propose a novel approach to determining the best level for safety stock. This approach considers logistic network supply reliability and seasonality indices identified within historical demand patterns. We use real-life data and show that the proposed method can improve efficiency in forecasting and safety stock levels by reducing the risk of stockouts and excess inventory.</p></div>","PeriodicalId":101186,"journal":{"name":"Supply Chain Analytics","volume":"3 ","pages":"Article 100026"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49758864","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: 1

A mathematical optimization model for cluster-based single-depot location-routing e-commerce logistics problems 基于集群的单仓库选址路径电子商务物流问题的数学优化模型

Supply Chain Analytics Pub Date : 2023-09-01 DOI: 10.1016/j.sca.2023.100019

Alireza Amini, Michael Haughton

引用次数: 1

An integrated multi-criteria decision-making and multivariate analysis towards sustainable procurement with application in automotive industry 面向可持续采购的综合多准则决策和多变量分析及其在汽车工业中的应用

Supply Chain Analytics Pub Date : 2023-09-01 DOI: 10.1016/j.sca.2023.100033

Sudipta Ghosh , Chiranjib Bhowmik , Sudipta Sinha , Rakesh D. Raut , Madhab Chandra Mandal , Amitava Ray

{"title":"An integrated multi-criteria decision-making and multivariate analysis towards sustainable procurement with application in automotive industry","authors":"Sudipta Ghosh , Chiranjib Bhowmik , Sudipta Sinha , Rakesh D. Raut , Madhab Chandra Mandal , Amitava Ray","doi":"10.1016/j.sca.2023.100033","DOIUrl":"https://doi.org/10.1016/j.sca.2023.100033","url":null,"abstract":"<div><p>Green Supply Chain Management (GSCM) has emerged as a paramount issue in modern business organizations striving to become environmentally sustainable. Suppliers are pivotal in building a green supply chain. Green supplier selection (GSS) is a complex task involving several steps, from evaluation to final selection. This research aims to select spare parts suppliers of an automotive company based on their GSCM practices. Fourteen critical criteria are extracted from extant literature and refined through a Delphi study. The data was collected through interviews with industry experts using structured questionnaires. This study proposes integrated multi-criteria decision-making (MCDM) and multivariate analysis method with internal consistency checks. The Principal Component Analysis (PCA) is used to calculate criteria weights. A Simple Additive Weighting (SAW) method ranks the suppliers based on weighted criteria. The result shows that “collaboration with suppliers for green purchasing” is the most influential parameter for GSS. The outcome of this research may aid managers in selecting the most suitable green suppliers in the automotive industry by attaining sustainability. The proposed framework can be replicated to select suppliers in other industries.</p></div>","PeriodicalId":101186,"journal":{"name":"Supply Chain Analytics","volume":"3 ","pages":"Article 100033"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49751200","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: 2

Order-up-to-level inventory optimization model using time-series demand forecasting with ensemble deep learning 基于集成深度学习的时间序列需求预测的订货级库存优化模型

Supply Chain Analytics Pub Date : 2023-09-01 DOI: 10.1016/j.sca.2023.100024

Mahya Seyedan , Fereshteh Mafakheri , Chun Wang

{"title":"Order-up-to-level inventory optimization model using time-series demand forecasting with ensemble deep learning","authors":"Mahya Seyedan , Fereshteh Mafakheri , Chun Wang","doi":"10.1016/j.sca.2023.100024","DOIUrl":"https://doi.org/10.1016/j.sca.2023.100024","url":null,"abstract":"<div><p>Inventory control aims to meet customer demands at a given service level while minimizing cost. As a result of market volatility, customer demand is generally changing, and ignoring this uncertainty could lead to under or over-estimation of inventories resulting in shortages or inefficiencies. Inventory managers need batch ordering such that the ordered items arrive before the depletion of stocks due to the lead time between the ordering point and delivery. Therefore, to meet demand while optimizing the cost of the inventory system, firms must forecast future demands to address ordering uncertainties. Traditionally, it was challenging to predict such uncertainties with high accuracy. The availability of high volumes of historical data and big data analytics have made it easier to overcome such a challenge. This study aims to predict future demand in the case of an online retail industry using ensemble deep learning-based forecasting methods with a comparison of their performance. Compared to single-model learning, ensemble learning could improve the accuracy of predictions by combining the best performance of each model. Also, the advantages of deep learning and ensemble learning are combined in ensemble deep learning models, allowing the final model to be more generalizable. Finally, safety stocks are estimated using the forecasted demand distribution, optimizing the inventory system under a cycle service level objective.</p></div>","PeriodicalId":101186,"journal":{"name":"Supply Chain Analytics","volume":"3 ","pages":"Article 100024"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49751237","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: 3

Supply chain risk management: A content analysis-based review of existing and emerging topics 供应链风险管理:对现有和新出现的主题进行基于内容分析的审查

Supply Chain Analytics Pub Date : 2023-09-01 DOI: 10.1016/j.sca.2023.100031

Ali Emrouznejad , Sina Abbasi , Çiğdem Sıcakyüz

{"title":"Supply chain risk management: A content analysis-based review of existing and emerging topics","authors":"Ali Emrouznejad , Sina Abbasi , Çiğdem Sıcakyüz","doi":"10.1016/j.sca.2023.100031","DOIUrl":"https://doi.org/10.1016/j.sca.2023.100031","url":null,"abstract":"<div><p>This paper presents a systematic review of the literature on Supply Chain Risk (SCR) research, focusing on content-based analysis. The study comprehensively examines the general factors associated with key themes and trends in supply chain risk management, encompassing the identification and assessment of risks, risk mitigation strategies, and the influence of emerging technologies on Supply Chain Risk Management (SCRM). The review provides an overview of current and emerging topics in SCRM, while also introducing categorization frameworks to address research gaps and provide a roadmap for future studies, thereby generating valuable insights in this field. The review highlights the significance of effective SCRM in ensuring business continuity and resilience, emphasizing the need for organizations to adopt a proactive approach to risk management. The paper concludes by identifying areas for future research, including the development of novel risk management frameworks and the integration of emerging technologies into supply chain risk management practices. Additionally, a comprehensive evaluation of each classification is presented, highlighting overlooked aspects and unexplored domains, and offering recommendations for potential next steps in SCRM research.</p></div>","PeriodicalId":101186,"journal":{"name":"Supply Chain Analytics","volume":"3 ","pages":"Article 100031"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49767355","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: 8

A comprehensive systematic review of the literature on the impact of the COVID-19 pandemic on supply chains 对COVID-19大流行对供应链影响的文献进行了全面系统的综述

Supply Chain Analytics Pub Date : 2023-09-01 DOI: 10.1016/j.sca.2023.100025

Tariq Aljuneidi , Shahid Ahmad Bhat , Youssef Boulaksil

引用次数: 3

An optimal replenishment cycle and order quantity inventory model for deteriorating items with fluctuating demand 需求波动的变质物品最优补货周期和订货数量库存模型

Supply Chain Analytics Pub Date : 2023-09-01 DOI: 10.1016/j.sca.2023.100021

Hui-Ling Yang

{"title":"An optimal replenishment cycle and order quantity inventory model for deteriorating items with fluctuating demand","authors":"Hui-Ling Yang","doi":"10.1016/j.sca.2023.100021","DOIUrl":"https://doi.org/10.1016/j.sca.2023.100021","url":null,"abstract":"<div><p>Suppliers often prefer to offer their retailers a delay period in payment to attract more sales and promote revenue in a supply chain. The retailers usually ask their customers to pay a portion of purchasing cost when receiving the product (<em>i</em>.<em>e</em>., a downstream partial trade credit) to reduce the default risk. On the other hand, the suppliers provide discounts for bulk purchases, and the retailer has enough capital to purchase more goods than can be stored in its warehouse. The retailer must store the excess quantities in a rented warehouse if the storage capacity is limited. A two-warehouse inventory system is needed to model this problem. In reality, the demand rate fluctuates with time, and the relevant cost is usually affected by the present value of time. This study focuses on the limited storage capacity inventory model for deteriorating items with fluctuating demand, downstream partial trade credit transactions, and discounted cash-flow considerations. The aim is to find the optimal replenishment cycle and order quantity and keep the present value of the total relevant cost per unit of time as low as possible. We further present numerical examples to demonstrate the applicability and develop managerial insights.</p></div>","PeriodicalId":101186,"journal":{"name":"Supply Chain Analytics","volume":"3 ","pages":"Article 100021"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49758861","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: 1