Big data analytics and application for logistics and supply chain management

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.

• Record URL:
  https://doi.org/10.1016/j.tre.2018.03.011
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S1366554518302606
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/13665545
• Supplemental Notes:
  • Abstract reprinted with permission of Elsevier.
• Authors:
  • Govindan, Kannan
  • Cheng, T C E
  • Mishra, Nishikant
  • Shukla, Nagesh
• Publication Date: 2018-6

Language

• English

Media Info

• Media Type: Web
• Features: Appendices; Figures; References; Tables;
• Pagination: pp 343-349
• Serial:
  • Transportation Research Part E: Logistics and Transportation Review
  • Volume: 114
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 1366-5545
  • Serial URL: http://www.sciencedirect.com/science/journal/13665545

Subject/Index Terms

• TRT Terms: Data analysis; Logistics; Supply chain management
• Uncontrolled Terms: Big data
• Subject Areas: Data and Information Technology; Freight Transportation;

Filing Info

• Accession Number: 01673074
• Record Type: Publication
• Files: TRIS
• Created Date: Jun 22 2018 4:42PM