Computational Design Science: A Critical Information Systems Research Area Contributing to Artificial Intelligence and Data Science

Speaker: Professor Michael Chau, Innovation and Information Management, HKU Business School, The University of Hong Kong

Time: Wednesday, May 6, 2026, 9:30-11:00 a.m.

Venue: Guoshun Campus, Starr Building, Room 301

Moderator: Professor Yunlu Yin, Professor Wenwen Li

Abstract:
In the era of artificial intelligence (AI) and data science, the demand for advanced AI methods and systems capable of analyzing large-scale, diverse, and granular data to address major challenges in business and society is more pressing than ever. Situated at the intersection of information technology, business, and the social sciences, the information systems (IS) discipline is uniquely positioned to lead frontier research that develops advanced AI solutions for important business and societal issues. However, the potential of IS to contribute to this critical area has not yet been fully realized, largely because the relevance and importance of computational design science (CDS) research have not been adequately recognized.

As a specific genre of design science, CDS seeks to develop novel computational algorithms and methods to solve business and societal problems with significant impact. Existing literature has discussed how to conduct and evaluate design science research in general terms, but it has provided limited guidance for the conduct and assessment of CDS research in particular. Against this background, this study examines the relationship between CDS, AI, and data science, and argues that CDS is a vital area of IS research that can make substantial methodological contributions not only to AI and data science, but also to the IS knowledge base. It further identifies the issues that have prevented the IS community from fully appreciating the relevance and significance of CDS research. By addressing these issues, the study clarifies what CDS research is and what its contributions entail, emphasizing that CDS research should be evaluated on the basis of its methodological contributions. In addition, it explicitly defines the identity of CDS research, especially by specifying how it differs from machine learning (ML) research in computer science and from applied ML studies in other business fields. Finally, it proposes a holistic template that provides clear and comprehensive guidance for IS scholars preparing CDS papers.

Bio: Michael Chau is a Professor in the Faculty of Business and Economics (HKU Business School) at The University of Hong Kong. His research focuses on the interdisciplinary intersection of information systems, computer science, business analytics, and information science, with particular emphasis on the applications of artificial intelligence and machine learning in business, education, and social domains. He has published more than 90 papers in leading journals in information systems and related disciplines. He has received multiple awards for his research and is a member of the AIS College of Senior Scholars. He currently serves as Editor-in-Chief of the International Journal of Information Management and as Senior Editor of MIS Quarterly. He also serves as AIS Vice-President (Region 3) and Conference Chair of PACIS 2027, and previously served as Program Chair of PACIS 2024 and ICIS 2013. He received his PhD in Management Information Systems from the University of Arizona and his BSc in Computer Science and Information Systems from The University of Hong Kong.