Big Data for supply chain management in the service and manufacturing sectors: Challenges, opportunities, and future perspectives

被引:345
作者
Zhong, Ray Y. [1 ]
Newman, Stephen T. [2 ]
Huang, George Q. [3 ]
Lan, Shulin [3 ]
机构
[1] Univ Auckland, Dept Mech Engn, Auckland, New Zealand
[2] Univ Bath, Dept Mech Engn, Bath, Avon, England
[3] Univ Hong Kong, Dept Ind & Mfg Syst Engn, HKU ZIRI Lab Phys Internet, Hong Kong, Hong Kong, Peoples R China
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
Big Data; Service applications; Manufacturing sector; Supply Chain Management (SCM); DATA MODEL; ANALYTICS; INFORMATION; LOGISTICS; HADOOP; IDEAS;
D O I
10.1016/j.cie.2016.07.013
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Data from service and manufacturing sectors is increasing sharply and lifts up a growing enthusiasm for the notion of Big Data. This paper investigates representative Big Data applications from typical services like finance & economics, healthcare, Supply Chain Management (SCM), and manufacturing sector. Current technologies from key aspects of storage technology, data processing technology, data visualization technique, Big Data analytics, as well as models and algorithms are reviewed. This paper then provides a discussion from analyzing current movements on the Big Data for SCM in service and manufacturing world-wide including North America, Europe, and Asia Pacific region. Current challenges, opportunities, and future perspectives such as data collection methods, data transmission, data storage, processing technologies for Big Data, Big Data-enabled decision-making models, as well as Big Data interpretation and application are highlighted. Observations and insights from this paper could be referred by academia and practitioners when implementing Big Data analytics in the service and manufacturing sectors. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:572 / 591
页数:20
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