How AI Adoption Transforms Technology Acceptance into Online Purchase Behavior: An Integrated UTAUT–Technology Acceptance Model

Abstract

Artificial intelligence (AI) is increasingly integrated into digital commerce through intelligent services that support consumer purchasing. However, limited empirical evidence explains how technology acceptance translates into AI adoption and subsequent online purchase behavior, particularly in digital MSMEs. This study examines the relationships among effort expectancy, performance expectancy, AI adoption, and online purchase behavior, positioning AI adoption as a behavioral link between technology acceptance and purchasing outcomes. A quantitative explanatory study was conducted using a cross-sectional survey of 126 consumers selected through purposive sampling. Respondents had used an AI-based service or feature, interacted with a digital MSME, and made an online purchase. Data were collected using a five-point Likert-scale questionnaire and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that performance expectancy significantly and positively affects AI adoption (β = 0.657, p < 0.001), whereas effort expectancy does not significantly affect AI adoption (β = 0.101, p = 0.123). Effort expectancy significantly and positively affects online purchase behavior (β = 0.265, p < 0.001), as does performance expectancy (β = 0.168, p = 0.026). AI adoption also significantly and positively affects online purchase behavior (β = 0.317, p < 0.001). These findings indicate that perceived performance benefits are more important for AI adoption, while both performance and ease of use contribute to online purchasing. The study contributes by positioning AI adoption as a behavioral mechanism connecting technology acceptance with online purchase behavior and offers practical implications for developing AI-enabled digital commerce services.