TY - JOUR
T1 - Intelligent e-vendor relationship management for enhancing global b2c e-commerce ecosystems
AU - Lam, H. Y.
AU - Tsang, Y. P.
AU - Wu, C. H.
AU - Chan, C. Y.
N1 - Funding Information:
This study was partially supported by a matching grant under UGC’s Research Matching Grant Scheme (second cycle). Our gratitude is extended to the Big Data Intelligence Centre at The Hang Seng University of Hong Kong, which supported the research. The authors would also like to thank the handling editor and reviewers for their valuable comments and suggestions, which have improved the quality of this paper.
Publisher Copyright:
© 2021 IGI Global. All rights reserved.
PY - 2021/5
Y1 - 2021/5
N2 - Recently, global e-commerce businesses have been blooming due to the convenience they offer, their product range, and the individualized products and services they offer. To maintain an entire ecosystem, effective platform-vendor relationships should be considered, through which e-commerce platforms can provide collaborative packages to vendors. E-vendor relationship management (eVRM) should then be developed to identify, attract, retain, and develop existing and new vendors so that groups of loyal vendors can be managed. However, eVRM in e-commerce is an area that has received less attention. This paper proposes an adaptive e-vendor relationship-management system (AVRMS) to provide decision-making support for the formulation of vendor management strategies. The contribution of this study is that it addresses the missing link of platform-vendor relationship management in global e-commerce environments, while integrating data-driven approaches and artificial intelligence techniques to generate a new synergy for the facilitation of eVRM.
AB - Recently, global e-commerce businesses have been blooming due to the convenience they offer, their product range, and the individualized products and services they offer. To maintain an entire ecosystem, effective platform-vendor relationships should be considered, through which e-commerce platforms can provide collaborative packages to vendors. E-vendor relationship management (eVRM) should then be developed to identify, attract, retain, and develop existing and new vendors so that groups of loyal vendors can be managed. However, eVRM in e-commerce is an area that has received less attention. This paper proposes an adaptive e-vendor relationship-management system (AVRMS) to provide decision-making support for the formulation of vendor management strategies. The contribution of this study is that it addresses the missing link of platform-vendor relationship management in global e-commerce environments, while integrating data-driven approaches and artificial intelligence techniques to generate a new synergy for the facilitation of eVRM.
KW - Fuzzy C-Means Clustering
KW - Global E-Commerce
KW - Vendor Relationship Management
UR - http://www.scopus.com/inward/record.url?scp=85105030482&partnerID=8YFLogxK
U2 - 10.4018/JGIM.2021050101
DO - 10.4018/JGIM.2021050101
M3 - Journal article
AN - SCOPUS:85105030482
SN - 1062-7375
VL - 29
JO - Journal of Global Information Management
JF - Journal of Global Information Management
IS - 3
M1 - 1
ER -