Knowledge Management
The goal of this track is to advance our knowledge of the complexity and dynamics of business intelligence/analytics (BIA) into KM for improving organizations’ performance. The emphasis of the track is on how both individual and organizational knowledge can be incorporated into new emerging technologies such as Big Data, Internet of Things (IoTs), voice recognition techniques, blockchain, social network analysis (SNA), artificial intelligence (AI), etc. using KM systems, techniques, and tools.


As seeing the state-of-the-art KM practices (especially knowledge ecosystem), recent literature has highlighted how knowledge can be smartly utilized within and among organizations (e.g., Baskerville et al., 2015) It includes the interplaying fields of KM, marketing, customer services, and new emerging technologies such as IoTs or AI. In nowadays, while the interplay between KM and emerging technologies has been started, there has been little attention to clearly understanding of how it could contribute to the academic and practical fields.

This track solicits various types of research papers using scientific theories, methods and research contexts to contribute to KM research communities. Submissions focusing on the interactions of technical, behavioral, organizational, and/or societal aspects on KM are welcomed. We also welcome a variety of methodological papers using qualitative methods (inclusive of ethnographical approach), experimental design, modeling, empirical research, or mixed methodological approach with qualitative and quantitative methods. Further, regarding the unit of analysis, organizational, inter-organizational, social, or team-level studies will be more welcomed. Case studies relevant to the real world are welcomingly accepted.

Topics of interest include, but are not limited to:
Knowledge Management (KM) in the digital age
Social/behavioral issues in KM
Communities-of-Practice (CoPs)
Cross-cultural aspects of KM
KM and organizational learning
Business processes and software engineering for KM
Emerging trends of information systems in KM
KM and strategic IS planning
Open innovation and cases
Knowledge ecology perspective
Customer centers and customer knowledge
Analytical tools and techniques (e.g., text analytics, sentiment analysis, etc.)
Data mining in the tacit and explicit knowledge
Knowledge Management System (KMS) related issues
KM for strategic decision-making
Trust in KM
Virtual community for KM
Knowledge acquisition, transferring, and sharing
Inter-organizational collaboration
New technology usage for KM (e.g., AI, IoTs, robots, etc)
Service system/architecture for KM


Baskerville, R. L., Kual, M., and Storey, V. C., “Genres of Inquiry in Design-Science Research: Justification and Evaluation of Knowledge Production,” MIS Quarterly, 39(3), 2015, pp. 541-564.


Track Co-Chairs:
Dr. Joon Koh (Chonnam National University, Korea, email:
Dr. Sangcheol(Charles) Park (Daegu University, Korea, email:
Dr. Padmal K. Vitharana (Syracuse University, USA, email:


Track AEs:
Alison Pearce, Northumbria University, UK
Fu Ye, Fudan University, China
Daniel Beimborn, Frankfurt School of Finance & Management, Germany
Weihui Dai, Fudan University. China
Junbum Kwon, UNSW Business School, Australia
J.P. Shim, Georgia State University, USA
Changju Kim, Ritsumeikan University, Japan
Hyun Shik Yoon, Chonnam National University, Korea
Seonjin Shin, Sungkyunkwan University, Korea
Sujeong Choi, Jeonnam Women's Plaza, Korea
Hyunchul Ahn, Kookmin University, Korea
So-Hyun Lee, American University, USA
Byounggu Choi, Kookmin University, Korea
Hyung Koo Lee, HEC Montréal, Canada
Jong Seok Lee, University of Memphis, USA
Soon Jae Kwon, Daegu University, Korea
Sunghan Ryu, Shanghai Jio Tong University, China
Wei Zheng, Northern Illinois University, USA
Baiyin Yang, Tsinghua University, China
Gary N. McLean, Texas A&M University, USA
Chechen Liao, National Chung Cheng University, Taiwan, China
Shu-Hui Chuang, Asia University, Taiwan, China
Yung-Ming Li, National Chiao Tung University, Taiwan, China
Pui-Lai To, National Chiayi University, Taiwan, China
Yonghui Dai, Shanghai International Business and Economics University, China
Kiyong Om, KOREATECH, Korea