SPEAKER:  王伟泉 教授 ，香港中文大学

TIME/DATE:  2024年6月13日（周四）10：00

CLASSROOM:  同济大厦A座401教室

ABSTRACT:  

Algorithms are being increasingly adopted in online investment communities (OICs) to generate algorithmic predictions of stock performance for OIC content consumers (i.e., investors). Nevertheless, such predictions may pose an identity threat to the OICs’ key content producers (mainly consisting of non-professional human analysts), who analyze and forecast stock performance through their content generation in OICs (i.e., analysis articles). We investigate how analyst content generation is adapted in response to the introduction of algorithmic predictions in OICs. Drawing on identity control theory and coping theory, we theorize analysts’ coping responses under algorithmic identity threat as an algorithm reactance effect, which manifests in two forms, namely, algorithm resistance and self-elevation. We further elaborate on the contingent role of algorithm performance in influencing the intensity of the reactance effect. Applying a regression discontinuity in time design, we empirically tested the theorized reactance effect using a unique dataset from Seeking Alpha, an OIC that rolled out algorithmic predictions in May 2019. We found that analysts exhibited lower forecast quality owing to derogation (i.e., algorithm resistance) when algorithmic predictions were accurate. Moreover, irrespective of algorithm performance, analysts demonstrated growing productivity and self-mention in their analysis articles (i.e., self-elevation). Our study reveals a novel, nuanced algorithm reactance effect in a human–algorithm interaction context and offers managerial implications for next-generation algorithm-empowered OICs.

GUEST BIO:  

Prof. Weiquan Wang is a Professor in the Department of Decisions, Operations and Technology at the Chinese University of Hong Kong (CUHK) Business School. He received his Ph.D. in Management Information Systems from the University of British Columbia, and double-bachelor’s degrees in i) Engineering Physics and ii) Enterprise Management as well as a Master’s degree in Management Science and Engineering from Tsinghua University. Before joining CUHK Business School, he was at the College of Business at the City University of Hong Kong. He served as an associate editor of MIS Quarterly during Jan 2012 and Dec 2015. He is serving on the editorial boards of the Journal of the Association for Information Systems (JAIS) and a few other leading scholarly outlets.