Assessing the impacts of peer-to-peer recommender system on online shopping: PLS-SEM approach

Peer-to-peer recommender systems play a critical role in online shopping in Vietnam. This paper aims to identify the relationship between Recommendation Quality and Purchase Intention and the moderating effects of Attitude and Trust on this relationship. Partial Least Squares Structural Equation Modeling was used as a research method. The sample consisted of 365 respondents who frequently use recommender system when shopping online. Data were collected using non-probability sampling method. The questionnaire is delivered to online customers who frequently rely on peer-to-peer recommender systems to make a purchase decision. The results show that Recommendation Transparency, Recommendation Accuracy, Recommendation Novelty, and Recommendation Diversity are positively related to Recommendation Quality. Consequently, Recommendation Quality has a positive impact on Attitude, Trust, and Purchase Intention. Besides, Attitude has a positive impact on online Purchase Intention. Trust also has a positive impact on online Purchase Intention. Practical implications are proposed to improve the impacts of peer-to-peer recommender systems on online shopping.