AI-Recommendation and UTAUT2 Factors in Shaping Consumer Attitudes and Purchase Intentions in E-Commerce

Celine Miyuki Gunawan; Metta Padmalia

doi:10.37034/jems.v8i3.486

Authors

Celine Miyuki Gunawan Universitas Ciputra
Metta Padmalia Universitas Ciputra

DOI:

https://doi.org/10.37034/jems.v8i3.486

Keywords:

AI-Based Recommendation, Performance Expectancy, Effort Expectancy, Hedonic Motivation, Intention to Purchase

Abstract

The rapid growth of smartphone usage has increased consumer access to digital marketplaces such as Shopee, where AI recommendation systems are widely used to enhance user experience. However, the extent to which AI recommendation and UTAUT2 constructs influence consumer attitude and purchase intention in e-commerce remains insufficiently explored. This study aims to examine the role of AI recommendation (AIR), performance expectancy (PE), effort expectancy (EE), and hedonic motivation (HM) in shaping consumer attitude (ATE) and purchase intention (ITP). This study employs a quantitative approach using survey data collected from 463 Shopee users in Indonesia. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM).The results show that AI recommendation, effort expectancy, and hedonic motivation positively influence consumer attitude, while performance expectancy has a significant negative effect. In addition, consumer attitude, AI recommendation, performance expectancy, and effort expectancy positively influence purchase intention, whereas hedonic motivation negatively affects purchase intention. These findings suggest that purchase intention is influenced not only by affective responses but also by functional evaluations of technology. This study contributes to the literature on AI recommendation and UTAUT2 in the e-commerce context and provides practical insights for optimizing AI-driven personalization strategies to improve consumer engagement and conversion.

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