Big data analytics in supply chain management between 2010 and 2016: Insights to industries

被引:309
|
作者
Tiwari, Sunil [1 ]
Wee, H. M. [2 ]
Daryanto, Yosef [2 ,3 ]
机构
[1] Natl Univ Singapore, Logist Inst Asia Pacific, 21 Heng Mui Keng Terrace, Singapore 119613, Singapore
[2] Chung Yuan Christian Univ, Dept Ind & Syst Engn, Chungli, Taiwan
[3] Univ Atma Jaya Yogyakarta, Dept Ind Engn, Yogyakarta, Indonesia
关键词
Big data analytics; Supply chain management; Big data application; PREDICTIVE ANALYTICS; DATA SCIENCE; CHALLENGES; OPTIMIZATION; LOGISTICS; SUSTAINABILITY; DESIGN; MODEL;
D O I
10.1016/j.cie.2017.11.017
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This paper investigates big data analytics research and application in supply chain management between 2010 and 2016 and provides insights to industries. In recent years, the amount of data produced from end-to-end supply chain management practices has increased exponentially. Moreover, in current competitive environment supply chain professionals are struggling in handling the huge data. They are surveying new techniques to investigate how data are produced, captured, organized and analyzed to give valuable insights to industries. Big Data analytics is one of the best techniques which can help them in overcoming their problem. Realizing the promising benefits of big data analytics in the supply chain has motivated us to write a review on the importance/impact of big data analytics and its application in supply chain management. First, we discuss big data analytics individually, and then we discuss the role of big data analytics in supply chain management (supply chain analytics). Current research and application are also explored. Finally, we outline the insights to industries. Observations and insights from this paper could provide the guideline for academia and practitioners in implementing big data analytics in different aspects of supply chain management.
引用
收藏
页码:319 / 330
页数:12
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