Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/78418
Title: Big data analytics and application for logistics and supply chain management
Authors: Govindan, K
Cheng, TCE 
Mishra, N
Shulda, N
Keywords: Big data analytics
Supply chain management
Logistics
Issue Date: 2018
Publisher: Pergamon Press
Source: Transportation research. Part E, Logistics and transportation review, June 2018, v. 114, p. 343-349 How to cite?
Journal: Transportation research. Part E, Logistics and transportation review 
Abstract: This special issue explores big data analytics and applications for logistics and supply chain management by examining novel methods, practices, and opportunities. The articles present and analyse a variety of opportunities to improve big data analytics and applications for logistics and supply chain management, such as those through exploring technology-driven tracking strategies, financial performance relations with data driven supply chains, and implementation issues and supply chain capability maturity with big data. This editorial note summarizes the discussions on the big data attributes, on effective practices for implementation, and on evaluation and implementation methods.
URI: http://hdl.handle.net/10397/78418
ISSN: 1366-5545
EISSN: 1878-5794
DOI: 10.1016/j.tre.2018.03.011
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

2
Citations as of Dec 14, 2018

Page view(s)

18
Citations as of Dec 10, 2018

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.