THE ROLE OF PERSONALIZATION, RECOMMENDATION SYSTEMS, INFORMATION QUALITY, AND E-SERVICE QUALITY IN IMPROVING SHOPEE USER SATISFACTION: AN SEM-PLS APPROACH
Abstract
User satisfaction has become a crucial factor in the success of e-commerce platforms amid increasingly fierce competition, particularly for Shopee as the platform with the highest number of visits in Indonesia. This study aims to analyze the influence of personalization, recommendation systems, information quality, and electronic service quality (e-service quality) on Shopee user satisfaction through the mediation of Perceived Usefulness (PU) and Perceived Ease of Use (PEOU) within the Technology Acceptance Model (TAM) framework. The research method employed is a quantitative approach with a survey of 430 active Shopee users in the Jabodetabek area who have completed at least two transactions in the last three months. Data were analyzed using Partial Least Square-based Structural Equation Modeling (SEM-PLS) with SmartPLS software. The results show that the recommendation system is the strongest predictor of PU, while e-service quality is the main determinant of PEOU. PU has the most dominant direct influence on user satisfaction, followed by PEOU. All mediation paths proved to be significant, with the recommendation system having the strongest indirect effect through PU. The research model can explain 73.1% of the variance in user satisfaction. It can be concluded that the integration of intelligent technology and basic service quality simultaneously shapes perceptions of usefulness and ease of use, which become the main pillars of e-commerce user satisfaction in Indonesia.
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