TY - JOUR
T1 - Big data analytics and application for logistics and supply chain management
AU - Govindan, Kannan
AU - Cheng, T. C.E.
AU - Mishra, Nishikant
AU - Shukla, Nagesh
PY - 2018
Y1 - 2018
N2 - 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.
AB - 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.
KW - Big data analytics
KW - Logistics
KW - Supply chain management
U2 - 10.1016/j.tre.2018.03.011
DO - 10.1016/j.tre.2018.03.011
M3 - Editorial
AN - SCOPUS:85046661218
SN - 1366-5545
VL - 114
SP - 343
EP - 349
JO - Transportation Research Part E: Logistics and Transportation Review
JF - Transportation Research Part E: Logistics and Transportation Review
ER -