From Social Proof to Diagnostic Tool: Unraveling the Uncertainty-Reduction Pathway of User-Generated Content
Mots-clés :
User-Generated Content (UGC), Uncertainty Reduction Theory, Purchase Intention, Online Retail, Product Uncertainty, CB-SEMRésumé
Although studies have largely examined and established the effect of UGC (User-Generated Content) on purchase intention, psychological mechanisms driving this effect, through which UGC influences consumer decisions, remain underexplored. This research moves beyond the studies grounded exclusively in trust and emotion, focusing on a model positions product uncertainty reduction as the pivotal mediating process linking UGC characteristics to purchase intention in online retail. Embedded in Uncertainty Reduction Theory, investigation explores how three key UGC characteristics-trustworthiness, valence, and information richness-systematically alleviate dimensions of product uncertainty: performance, description, and fit, respectively. Data were collected through an online survey from 455 Tunisian active online shoppers. Results were analyzed by means of CB-SEM. Findings reveal a powerful mediating pathway whereby UGC characteristics explain 68% of the variance in uncertainty reduction, which in turn significantly predicts purchase intention (R² = 0.59). Importantly, the effects are differentiated: information richness most strongly reduces performance and description uncertainty, while valence is the primary driver of fit uncertainty reduction. Trustworthiness consistently underpins all dimensions. These results develop theory by detailing the cognitive, uncertainty-driven mechanisms of UGC and afford managers actionable insights into how to tailor UGC strategies based on different product types and consumer concerns.
Téléchargements
Téléchargements
Publiée
Numéro
Rubrique
Licence
Merci de créditer les auteurs lors de toute citation : Safa MEDIMAGH (2025)

Ce travail est disponible sous licence Creative Commons Attribution - Pas d’Utilisation Commerciale 4.0 International.














