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

Ray Y. Zhong, Stephen T. Newman, George Q. Huang, Shulin Lan

Research output: Contribution to journalArticle

193 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)572-591
JournalComputers and Industrial Engineering
Volume101
Early online date15 Jul 2016
DOIs
Publication statusPublished - Nov 2016

Keywords

  • Big Data
  • Manufacturing sector
  • Service applications
  • Supply Chain Management (SCM)

Fingerprint Dive into the research topics of 'Big Data for supply chain management in the service and manufacturing sectors: Challenges, opportunities, and future perspectives'. Together they form a unique fingerprint.

  • Cite this