You Sound Like an Expert: How Assertiveness in Prior Contributions Shapes Subsequent Engagement in Online Knowledge Communities
(A2026-133182)

AUTHORS

Yu Feng, The University of Hong Kong; Cong Wang, Peking University; Qiaowei Shen, Peking University; Phyliss Jia Gai, Guanghua School of Management, Peking University

ABSTRACT

Online knowledge communities rely on sustained user contributions to thrive. Drawing on expectation states theory, we propose that the assertiveness of prior contributors elevates the perceived expertise of those contributors relative to one's own, thereby reducing the perceived value of additional contributions and deterring novel contributions. A randomized experiment (and a supplemental replication study) documents that high (vs. low) assertiveness undermines the perceived value of further contribution, given the same problem and substantive content of prior contribution. This effect is mediated by the perceived expertise of the existing contributor relative to oneself and attenuates for individuals with greater self-expertise. An archival study of 149,107 question-answer pairs from an online medical knowledge community demonstrates that while high assertiveness of existing contributions garners more acknowledgment, it substantially reduces the likelihood of novel contributions by other users. These effects of assertiveness on subsequent contributions are amplified when they are coupled with higher-quality content. When the focal task does not involve a collective goal that demands joint efforts from individuals, assertiveness has no impact on further contributions. Our findings elucidate the mechanisms and boundary conditions under which assertiveness hinders diverse contributions, providing critical design and managerial implications for online knowledge communities.