{"title":"Big data - real time fact-based decision: the next big thing in supply chain","authors":"Sandhya Rai","doi":"10.1504/IJBPSCM.2019.10022633","DOIUrl":null,"url":null,"abstract":"Big data has become the life blood of the organisations. Organisations are gaining an understanding that if all the data that streams into businesses are captured and analysed, then they may prove to be a valuable source of information. The thought of data creating value is not new; businesses have always wanted to derive insight from data for making real time, fact-based decisions. In the domain of supply chain, companies are using big data analytics to manage activities like warehousing, transportation, inventory management, delivery, demand forecasting and scheduling. For this they are applying various data analytics tools and techniques. The aim of this paper is to explore all these application in detail and identify the tools and techniques that are used across upstream and downstream supply chain and develop a theoretical framework of application of big data in supply chain management (SCM).","PeriodicalId":37630,"journal":{"name":"International Journal of Business Performance and Supply Chain Modelling","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Business Performance and Supply Chain Modelling","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJBPSCM.2019.10022633","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Business, Management and Accounting","Score":null,"Total":0}
引用次数: 2
Abstract
Big data has become the life blood of the organisations. Organisations are gaining an understanding that if all the data that streams into businesses are captured and analysed, then they may prove to be a valuable source of information. The thought of data creating value is not new; businesses have always wanted to derive insight from data for making real time, fact-based decisions. In the domain of supply chain, companies are using big data analytics to manage activities like warehousing, transportation, inventory management, delivery, demand forecasting and scheduling. For this they are applying various data analytics tools and techniques. The aim of this paper is to explore all these application in detail and identify the tools and techniques that are used across upstream and downstream supply chain and develop a theoretical framework of application of big data in supply chain management (SCM).
期刊介绍:
IJBPSCM covers original, high-quality and cutting-edge research on all aspects of supply chain modelling, aiming at bridging the gap between theory and practice with applications analysing the real situation to improve business performance. Topics covered include Business performance modelling, strategy Vendor/supplier selection, supplier development, purchasing management Supply chain management (SCM), green supply chain modelling Reverse logistics, closed loop/knowledge-based supply chains, 3PL/4PL Sustainable/quality based/agile/leagile/intelligent SCM Supply chain performance/optimisation/risk/decision making/support systems AI, information sharing in SCM, systems approach to SCM Coordinated/global/flexible SCM, risk mitigation strategies Stochastic supply chain games IT-enabled SCM, fuzzy modelling, data mining Supply chain network management, modelling/simulation, implementation Training/education, information security, RFID Supply chain analysis, transportation decisions, vehicle routing, bullwhip effect Logistics in disaster management Cross-country comparison.