TY  - GEN
N2  - The objective of the book is to adopt the application of data analytics to enhance the sustainability and resilience of the green supply chain networks. To demonstrate the applicability and usefulness of the method, the book adopts different data analytic models and approaches against the backdrop of case studies. In summary, this book attempts to address the question of methods, tools, and techniques that can be used to create resilient, anti-fragile, reliable, and invulnerable green supply chain networks.
DO  - 10.1007/978-3-031-29823-3
DO  - doi
AB  - The objective of the book is to adopt the application of data analytics to enhance the sustainability and resilience of the green supply chain networks. To demonstrate the applicability and usefulness of the method, the book adopts different data analytic models and approaches against the backdrop of case studies. In summary, this book attempts to address the question of methods, tools, and techniques that can be used to create resilient, anti-fragile, reliable, and invulnerable green supply chain networks.
T1  - Data analytics for supply chain networks /
DA  - 2023.
CY  - Cham, Switzerland :
AU  - Hossain, Niamat Ullah Ibne,
VL  - v. 11
CN  - HD38.5
PB  - Springer,
PP  - Cham, Switzerland :
PY  - 2023.
N1  - Includes index.
ID  - 1469923
KW  - Business logistics
KW  - Big data.
SN  - 9783031298233
SN  - 3031298233
TI  - Data analytics for supply chain networks /
LK  - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-29823-3
UR  - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-29823-3
ER  -