eWOM QUALITY AND TRUST IN SOCIAL COMMERCE: PREDICTING INDIAN MILLENNIALS' PURCHASE INTENTION

Abstract

Think about the last time a friend’s Instagram post subtly convinced you to buy something. You probably didn’t reach for a product manual or call customer service. Instead, you skimmed through user reviews, noticed how many people had already purchased it, and let that quiet social signal tip the balance. This everyday experience lies at the heart of social commerce—a marketplace where peer influence, user-generated content, and platform design come together to shape what we buy.

While this phenomenon feels intuitive, the precise ways these forces interact—especially in a country as large, diverse, and culturally rich as India—remain only partially understood. This study seeks to deepen that understanding by integrating two well-established theoretical lenses: the Technology Acceptance Model (TAM) and the Elaboration Likelihood Model (ELM). Drawing on survey data from 387 Indian millennial online shoppers, we develop and test a unified model of social commerce adoption using Partial Least Squares Structural Equation Modeling (PLS-SEM).

The results reveal that perceived usefulness (β = 0.38, p < 0.001), social influence (β = 0.29, p < 0.001), and consumer trust (β = 0.35, p < 0.001) significantly drive purchase intention, while perceived risk acts as a notable deterrent (β = −0.24, p < 0.001). Importantly, we find that the quality of electronic word-of-mouth (eWOM) does not influence purchase intention directly. Instead, it works entirely through building consumer trust (β = 0.41, p < 0.001), highlighting a full mediation effect.

Together, the model explains 54.6% of the variance in purchase intention and 49.3% in consumer trust. These findings contribute to the literature by offering fresh insights into social commerce dynamics within an emerging market context that has received relatively limited attention. For practitioners, the results provide clear guidance on where to focus platform investments—from strengthening trust-building mechanisms to improving review quality—for maximum impact on buying behavior.