Generative AI capabilities for green supply chain management improvement: extended dynamic capabilities view

Taufik Kurrahman 1
, 
Feng Ming Tsai 1
, 
Ming K. Lim 2, 3
, 
Kanchana Sethanan 4
, 
M. C. Tseng 3, 4, 5, 6, 7
1
 
2
 
3
 
4
 
5
 
6
 
China Medical University
7
 
Publication type: Journal Article
Publication date: 2025-03-17
Taylor & Francis
scimago Q1
wos Q1
SJR: 1.452
CiteScore: 16.5
Impact factor: 4.9
ISSN: 13675567, 1469848X
Found 
Found 

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Kurrahman T. et al. Generative AI capabilities for green supply chain management improvement: extended dynamic capabilities view // International Journal of Logistics Research and Applications. 2025. pp. 1-28.
GOST all authors (up to 50) Copy
Kurrahman T., Tsai F. M., Lim M. K., Sethanan K., Tseng M. C. Generative AI capabilities for green supply chain management improvement: extended dynamic capabilities view // International Journal of Logistics Research and Applications. 2025. pp. 1-28.
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RIS Copy
TY - JOUR
DO - 10.1080/13675567.2025.2479006
UR - https://www.tandfonline.com/doi/full/10.1080/13675567.2025.2479006
TI - Generative AI capabilities for green supply chain management improvement: extended dynamic capabilities view
T2 - International Journal of Logistics Research and Applications
AU - Kurrahman, Taufik
AU - Tsai, Feng Ming
AU - Lim, Ming K.
AU - Sethanan, Kanchana
AU - Tseng, M. C.
PY - 2025
DA - 2025/03/17
PB - Taylor & Francis
SP - 1-28
SN - 1367-5567
SN - 1469-848X
ER -
BibTex
Cite this
BibTex (up to 50 authors) Copy
@article{2025_Kurrahman,
author = {Taufik Kurrahman and Feng Ming Tsai and Ming K. Lim and Kanchana Sethanan and M. C. Tseng},
title = {Generative AI capabilities for green supply chain management improvement: extended dynamic capabilities view},
journal = {International Journal of Logistics Research and Applications},
year = {2025},
publisher = {Taylor & Francis},
month = {mar},
url = {https://www.tandfonline.com/doi/full/10.1080/13675567.2025.2479006},
pages = {1--28},
doi = {10.1080/13675567.2025.2479006}
}