The impact of AI-generated knowledge on user knowledge avoidance in OKCs: the moderating role of AI literacy andplatform trust

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Authors: Jiaxuan Li, Qinjian Yuan
Cited by: 6
References: 64

Abstract

Purpose This study aims to reveal the psychological mechanisms of online knowledge communities (OKCs) users confronted with artificial intelligence-generated knowledge (AI-K) and the triggering mechanisms of knowledge decisions (e.g. knowledge avoidance). Design/methodology/approach Based on the stimulus-organism-response model, the study used a three-stage experimental design: Experiment 1 (n = 186) verified the direct effect of AI-K on knowledge avoidance and the serial mediating role of cognitive load and perceived distrust; Experiment 2 (n = 256) introduced AI literacy as a moderating variable to test its effect on cognitive load, and Experiment 3 (n = 246) explored the moderating role of platform trust on the relationship between perceived distrust and knowledge avoidance. Findings The results show that disclosing AI-K in OKCs positively influences users’ knowledge avoidance, which is influenced by the serial mediating effects of cognitive load and perceived distrust. In addition, the study finds that AI literacy negatively moderates users’ cognitive load on AI-K. Platform trust negatively moderates users’ perceived distrust of AI-K. Originality/value This study revealed the serial mediating effect of AI-K triggering knowledge avoidance, which bridges the theoretical gap in the relationship between AI-K and knowledge avoidance. It provides support for the OKCs platform to optimize the deployment of AI-K and provides a basis for improving the efficiency of knowledge services in OKCs.

Fields of Study & Subjects

Knowledge Management and Sharing AI in Service Interactions Technology Adoption and User Behaviour

Publication details

Journal / source
Journal of Knowledge Management
Publisher
Emerald
Volume
30
Issue
2
Pages
584–608
Publication date
7 January 2026
Language
EN