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The future and social impact of Big Data Analytics in Supply Chain Management: Results from a Delphi study

机译：大数据分析在供应链管理中的未来和社会影响：Delphi研究的结果

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摘要

The continuously growing amount of available data has accelerated the emergence of numerous business intelligence applications that are summarized under the term Big Data Analytics (BDA). BDA is especially relevant to the domain of Supply Chain Management (SCM) as it provides the tools to support decision-making in increasingly global, volatile and dynamic value networks. However, its application challenges traditional institutional arrangements as well as roles that are related to the management of data. The underlying empirical study addresses this challenge with the application of a multi-method approach that is embedded in Organizational Information Processing Theory (OIPT). A Delphi survey was conducted to integrate expert assessments of projections up to the year 2035 and fuzzy c-means clustering was applied to identify future scenarios that span the future of BDA in SCM. The study suggests that BDA will improve demand forecasts, reduce safety stocks and improve the management of supplier performance. However, supply chain (SC) processes will become increasingly automated and traditional tasks of SCM will be partially substituted as a result. Consequently, the transition of the traditional role of SCM within organizations will increase the importance of human intuition, trust and strategic decision-making.
机译：可用数据量的不断增长加速了以大数据分析（BDA）术语概括的众多商业智能应用程序的出现。 BDA与供应链管理（SCM）领域特别相关，因为它提供了工具来支持日益全球化，波动和动态的价值网络中的决策。但是，它的应用挑战了传统的制度安排以及与数据管理相关的角色。潜在的实证研究通过嵌入组织信息处理理论（OIPT）中的多方法方法的应用来应对这一挑战。进行了Delphi调查，以整合专家对截至2035年的预测的评估，并应用模糊c均值聚类来确定跨越SCM中BDA未来的未来方案。该研究表明，BDA将改善需求预测，减少安全库存并改善供应商绩效管理。但是，供应链（SC）流程将变得越来越自动化，因此将部分替代SCM的传统任务。因此，SCM在组织内部传统角色的转变将增加人类直觉，信任和战略决策的重要性。

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