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Home > Tracks
Track 16: Knowledge Management and Business Intelligence

  • Track Chairs
    Atreyi Kankanhalli
    National University of Singapore
    atreyi@comp.nus.edu.sg
    Michael Chau
    University of Hong Kong
    mchau@business.hku.hk
  • Track Description

    Advances in ICT, data explosion and information overload, employee turnover, and the need for organizations to better utilize their intellectual capital have led to increased interest in knowledge management (KM) and business intelligence (BI) domains. With massive amounts of information being added to corporate databases and the Internet every day, effective and efficient knowledge discovery and its management has become imperative. Thus, organisations are increasingly motivated to develop systems to leverage their knowledge and information for intelligent decision making and competitive advantage. These include diverse technologies ranging from corporate yellow pages, to social computing tools, to advanced web mining systems.

    Yet, there is much that remains to be understood about KM and BI systems such as how to develop the justification for these systems, dealing with different kinds of knowledge, integrating with existing systems, enabling processes and structures, and assessing outcomes in different organizational contexts. This track thus wishes to explore managerial, technical, and behavioral issues relating to KM and BI systems including strategy, design, development, and outcomes. We welcome both theoretical and empirical papers that employ diverse methodologies and philosophical perspectives to significantly advance our knowledge in these areas.

    Topics of interest include, but are not limited to:

    • KM and BI strategies
    • Design, development and use of KM systems
    • Knowledge discovery and sharing in organizations
    • KM in virtual teams and distributed contexts
    • Knowledge exchange in communities of practice
    • Capturing and sharing knowledge in social networks
    • KM processes and structures
    • KM and KM systems impacts
    • Inter-organizational KM systems
    • KM culture and environment
    • Data, text, and Web mining for BI
    • Web intelligence and Web analytics
    • Data integration from multiple sources
    • Visualization and HCI research for BI
    • Information extraction and report generation
    • Data warehouse design and development
    • Real-time decision making
    • BI performance metrics
  • Associate Editors

    • Gee Woo Bock, Sungkyunkwan University, Korea
    • Jinwei Cao, University of Delaware, USA
    • Patrick Fan, Virginia Tech, USA
    • Xiao Fang, University of Utah, USA
    • Khim Yong Goh, National University of Singapore, Singapore
    • Murray Jennex, San Diego State University, USA
    • K D Joshi, Washington State University, USA
    • Seung Hyun Kim, National University of Singapore, Singapore
    • Jason Li, Drexel University, USA
    • Stephen Liao, City University of Hong Kong, China
    • Byron Marshall, Oregon State University, USA
    • Loo Geok Pee, Tokyo Institute of Technology, Japan
    • Chee Wei Phang, Fudan University, China
    • Dmitri Roussinov, University of Strathclyde, UK
    • Kishore Sengupta, Insead, France
    • Ramesh Sharda, Oklahoma State University, USA
    • Stefan Smolnik, European Business School, Germany
    • Vijayan Sugumaran, Oakland University, USA
    • Juliana Sutanto, ETH Zurich, Switzerland
    • Sharon Tan, National University of Singapore, Singapore
    • Alan Wang, Virginia Tech, USA
    • Chih-Ping Wei, National Taiwan University, Taiwan
    • Jennifer Xu, Bentley University, USA
    • Lina Zhou, University of Maryland - Baltimore County, USA
    • Yilu Zhou, George Washington University, USA


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