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Business Intelligence and Data Analytics
Track Co-chairs:

Taro KAMIOKA, Hitotsubashi University, t.kami@r.hit-u.ac.jp

Xin LI, City University of Hong Kong, xin.li@cityu.edu.hk


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


Associate Editors (in alphabetical order)

Daning Hu, University of Zurich
Harris Wu, Old Dominion University
Jie Ren, Fordham University
Jiexun Li, Western Washington University
Jing Wang, Hong Kong University of Science and Technology
Joyce Yi-Hui Lee, Yuan-Ze University
Kaiquan Xu, Nanjing University
Kunpeng Zhang, University of Maryland
Najmul Islam, University of Turku
Qiang Wei, Tsinghua University
Robert P. Schumaker, University of Texas at Tyler
Shaokun Fan, Oregen State University
Tommi Tapanainen, Pusan National University
Zhe Shan, University of Cincinnati