大数据——基于事实的实时决策:供应链中的下一个大事件

Q3 Business, Management and Accounting

International Journal of Business Performance and Supply Chain Modelling Pub Date : 2019-07-10 DOI:10.1504/IJBPSCM.2019.10022633

Sandhya Rai

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引用次数: 2

摘要

大数据已经成为企业的命脉。企业逐渐认识到，如果所有流入企业的数据都能被捕获和分析，那么它们可能被证明是一个有价值的信息来源。数据创造价值的想法并不新鲜;企业一直希望从数据中获得洞察力，以便做出实时的、基于事实的决策。在供应链领域，公司正在使用大数据分析来管理仓储、运输、库存管理、交付、需求预测和调度等活动。为此，他们正在应用各种数据分析工具和技术。本文的目的是详细探讨所有这些应用，并确定在上游和下游供应链中使用的工具和技术，并开发大数据在供应链管理(SCM)中应用的理论框架。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Big data - real time fact-based decision: the next big thing in supply chain

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).

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来源期刊

International Journal of Business Performance and Supply Chain Modelling Business, Management and Accounting-Business and International Management

CiteScore

2.00

自引率

0.00%

发文量

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.