TY - JOUR
T1 - Big Data for supply chain management in the service and manufacturing sectors: Challenges, opportunities, and future perspectives
AU - Zhong, Ray Y.
AU - Newman, Stephen T.
AU - Huang, George Q.
AU - Lan, Shulin
N1 - Funding Information:
Canada, as one of another major country in North America, has put great efforts into Big Data research and applications in SM-SCM. The National Sciences and Engineering Research Council of Canada (NSERC), as the major governmental foundation body, aims to support on advanced studies, promotes, and discovery research as well as to foster innovation in Canadian companies in postsecondary research projects. It could be found that total 7509 projects are awarded with the keyword Big Data searching from the database between the year 2005 and 2013. Table A1 shows the statistics of the awards covered the topic of Big Data in different areas from 2010 to 2014 according to the database from NSERC ( http://www.nserc-crsng.gc.ca/ ).
Funding Information:
As the big wave of governmental promotion of Big Data in SM-SCM, the U.S. National Science Foundation (NSF) got the support of a $25 million fund in core techniques and technologies for advancing Big Data Science and Engineering. NSF sought the research proposals focusing on one or more science and engineering aspects such as data collection and management, data analytics, and e-science collaboration environment in terms of appropriate models, policies, and technologies targeted to services, emergency response and preparedness, clean energy, and advanced manufacturing. It can be found that, since 2005, there are 17,377 (US) and 26 (Non US) projects awarded from the NSF, which are related to the Big Data ( www.nsf.gov/awardsearch/ ). The detailed awards in NSF organizations are shown in Fig. 1 , from which it could be seen that service and engineering fields are the key concentrated areas by US government. Directorate for Computer & Information Science & Engineering, Directorate for Geoscience, and Direct for Mathematical & Physical Sciences, for instance, the awards are 3724, 3390, and 2525 respectively which are the three most awarded directorates, taking up 52.63% of total awards from 2005 to 2015. That could be an explanation why the service and engineering are so energetic from the support of advanced decision-making and wise responses to any situations based on Big Data techniques and technologies.
Funding Information:
This work is supported by National Natural Science Foundation of China (Grant Nos. 51405307 , 61473093 , and 61540030 ) and Project Funded by China Postdoctoral Science Foundation ( 2015M570720 ).
Publisher Copyright:
© 2016 Elsevier Ltd
PY - 2016/11/1
Y1 - 2016/11/1
N2 - 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.
AB - 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.
KW - Big Data
KW - Manufacturing sector
KW - Service applications
KW - Supply Chain Management (SCM)
UR - http://www.scopus.com/inward/record.url?scp=84978977044&partnerID=8YFLogxK
U2 - 10.1016/j.cie.2016.07.013
DO - 10.1016/j.cie.2016.07.013
M3 - Journal article
AN - SCOPUS:84978977044
SN - 0360-8352
VL - 101
SP - 572
EP - 591
JO - Computers and Industrial Engineering
JF - Computers and Industrial Engineering
ER -