Date: 14^th June, 2019

Time: 8:50-10:20 a.m.

Venue: Room 1417, The Administration Building, Zhejiang University

【Speaker Introduction】

Xiao Ma is an Assistant Professor of Business Analytics in the C. T. Bauer College of Business at the University of Houston. He holds a Ph.D. in Business from the University of Wisconsin-Madison. Xiao’s research focuses on the problems of online gambling behavior and proper interventions, behavior analytics in online labor and knowledge communities, emerging phenomena & theory development in Information Systems, methodological issues in management research, etc. His latest research interests include healthcare analytics, and using natural experiments to reveal managerial implications of digital system design change. Mostly recently, Xiao has also expanded his research focus into the areas of artificial intelligence and deep-learning algorithms, exploring how business research can leverage the advanced computational methods. His research has appeared in premier information systems journals, including Information Systems Research, Journal of Management Information Systems, and Journal of the Association for Information Systems.

【Lecture Abstract】

The instant access to gambling anytime, anywhere, has made online gambling highly habitual. As a result, some online gamblers choose to volitionally enable the website-provided disruptive IT features to control their gambling routines. The objective of this study is to examine the role of these features in regulating online gambling behavior. Drawing on theories of habitual automaticity and habit disruption, we theorize the efficacy and mechanism of disruptive features while taking into account heterogeneity in individual regularity and game type. We tested the model using data collected over 10 years from 3,526 users of a gambling website. First, we found that individuals’repetitive gambling patterns weakened as the duration of exposure to disruptive features increased. Second, the behavior of more regular gamblers was more resistant to the disruptive features. Third, disruptive features were less effective on sports games compared with casino games. Overall, the present study contributes to the IS literature by clarifying how simple IT features may disrupt unwanted and difficult-to-break online gambling habits. Our findings are also likely to apply to broader areas of online services in which the application in question is integrated into everyday life and the system can offer a disruptive mechanism.