Track: Business Intelligence and Data Analytics

Track Co-chairs:

Taro KAMIOKA, Hitotsubashi University,

Xin LI, City University of Hong Kong,


Description and Topics of Interest:

Business intelligence (BI) and data analytics (DA) are the techniques, technologies, systems, practices, methodologies, and applications that analyze critical business data to help an enterprise better understand its business and market and make timely business decisions (Chen et al. 2012 MISQ). Recently “Big Data”, “Big Data Analytics” and “Artificial Intelligence” have further stirred the interest of researchers and practitioners on using large scale and heterogeneous data to facilitate and direct business operations. It is critical to examine BI & DA in the organizational and managerial contexts to creating higher value for the society.

This track invites papers on various aspects of business intelligence and data analytics, including technologies, strategies, economics, and practices, that advance the understanding of BI and DA. In line with the conference’s theme “Opportunities and Challenges for the Digitized Society,” we are interested in papers that are related to innovative technologies, methodologies, and theories, which can lead to address the new challenges and cherish the new opportunities.

Potential topics include (but are not limited to) the following:

  • Trends in business intelligence/data analytics research
  • Theories that enlighten business intelligence/data analytics & decision-making
  • Business intelligence/data analytics for marketing
  • Business intelligence/data analytics for healthcare
  • Business intelligence/data analytics for business processes management
  • Business intelligence/data analytics for security
  • Data and text mining for emerging BI applications
  • Web mining and Social media analytics
  • Development of business intelligence/data analytics architectures/capabilities
  • Best practices & case studies in business intelligence/data analytics
  • Enablers and inhibitors for business intelligence/data analytics
  • Success factors in business intelligence/data analytics practice
  • Methodologies and processes for managing business intelligence/data analytics activities
  • Global issues in business intelligence/data analytics
  • Issues pertaining to analyst/decision-maker interactions