A textual data-driven method to measure the capabilities and core paths of different digital technologies to improve supply chain resilience

Zhimei Lei; Liu Bingbing; Ming K. Lim; Yui Yip Joseph Lau

A textual data-driven method to measure the capabilities and core paths of different digital technologies to improve supply chain resilience

Zhimei Lei, Liu Bingbing, Ming K. Lim, Yui Yip Joseph Lau

Division of Business and Hospitality Management (BHM)

Research output: Contribution to journal › Article › peer-review

Original language	English
Journal	International Journal of Logistics Research and Applications
Publication status	Accepted/In press - 2024

Cite this

@article{dd87783367554e1b9328907bb40024ee,

title = "A textual data-driven method to measure the capabilities and core paths of different digital technologies to improve supply chain resilience",

author = "Zhimei Lei and Liu Bingbing and Lim, {Ming K.} and Lau, {Yui Yip Joseph}",

year = "2024",

language = "English",

journal = "International Journal of Logistics Research and Applications",

issn = "1367-5567",

publisher = "Taylor and Francis Ltd.",

}

TY - JOUR

T1 - A textual data-driven method to measure the capabilities and core paths of different digital technologies to improve supply chain resilience

AU - Lei, Zhimei

AU - Bingbing, Liu

AU - Lim, Ming K.

AU - Lau, Yui Yip Joseph

PY - 2024

Y1 - 2024

M3 - Article

SN - 1367-5567

JO - International Journal of Logistics Research and Applications

JF - International Journal of Logistics Research and Applications

ER -