How does information overload influence psychological organism and information avoidance intention on mobile social media: application of stimulus-organism-response paradigm

Purpose As mobile social media permeates daily existence through ubiquitous connectivity, information overload (IO) has emerged as a critical environmental stimulus reshaping the engagement dynamic. Applying the stimulus-organism-response SOR framework, this study examines how IO activates psychological mechanisms (organism), specifically negative emotion (NE), dissatisfaction, information anxiety (IA) and information regret (IR), that subsequently predict information avoidance intention (response). Design/methodology/approach This study investigated the usage of mobile social media among 876 Chinese users and conducted descriptive analysis, confirmatory factor analysis and structural equation modeling on the data obtained from the survey. Subsequently, the findings were subjected to rigorous theoretical and practical discourse to extract meaningful insights from the data analysis. Findings Analysis of the data indicates that IO exerts a significant effect on users’ NE, dissatisfaction, IA and IR. The NE and dissatisfaction negatively influence users’ information avoidance intention. Furthermore, there is a positive relationship between IR and information avoidance intention. Research limitations/implications The obtained results augment the theoretical understanding of predictors for information avoidance intention and provide valuable insights for vested parties, encompassing mobile social media platforms and content providers, on efficacious strategies to ameliorate these deleterious effects. Originality/value This study complements empirical research on IO and avoidance, elucidating the sophisticated mechanism through which IO influences information avoidance intention via psychological organism processes. Notably, this study incorporates novel psychological constructs that are ubiquitously prevalent yet academically overlooked in mobile social media ecosystems, thereby substantively extending the SOR paradigm.