The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Knowledge Sharing in Supply Chain
Abstract
This paper examines knowledge sharing in supply chain by developing analytical models to minimize knowledge sharing uncertainty. Analogies from thermodynamics are used to describe the phenomenon in supply chain knowledge sharing. The study finds that distance and sender capacity are important to reduce knowledge sharing uncertainty. Furthermore, higher contact frequency between the sender and the receiver without considering sender capacity is proven to be insignificant to reduce uncertainty. This mechanism provides a new approach to explicate knowledge sharing in supply networks. It also serves as a deep-rooted opening point for supplementary empirical assessment. The mechanism facilitates managers to expand their understanding of composite circumstances embedded into global supply networks to share their knowledge. With enhanced understanding, managers can spotlight their actions, increasing their firms’ competitiveness. This study provides a deeper theoretical understanding of knowledge sharing in supply networks with a practical approach.
Related Content
|
Yu Bin, Xiao Zeyu, Dai Yinglong.
© 2024.
34 pages.
|
|
Liyin Wang, Yuting Cheng, Xueqing Fan, Anna Wang, Hansen Zhao.
© 2024.
21 pages.
|
|
Tao Zhang, Zaifa Xue, Zesheng Huo.
© 2024.
32 pages.
|
|
Dharmesh Dhabliya, Vivek Veeraiah, Sukhvinder Singh Dari, Jambi Ratna Raja Kumar, Ritika Dhabliya, Sabyasachi Pramanik, Ankur Gupta.
© 2024.
22 pages.
|
|
Yi Xu.
© 2024.
37 pages.
|
|
Chunmao Jiang.
© 2024.
22 pages.
|
|
Hatice Kübra Özensel, Burak Efe.
© 2024.
23 pages.
|
|
|