Authors: Anindito Bhattacharya, Ishita Deb, Samarpita Roy
Abstract: Artificial Intelligence (AI)-enabled recommendation systems have become an integral component of online shopping by delivering personalized product suggestions that enhance consumers' shopping experiences. Despite their widespread adoption, limited research has examined the behavioural factors influencing consumers' intention to use these systems in the Indian context. This study investigates the determinants of AI-enabled recommendation system adoption among Indian online shoppers using the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework. A quantitative, cross-sectional research design was employed, and primary data were collected from 201 respondents through a structured online questionnaire using convenience and snowball sampling techniques. The collected data were analysed using descriptive statistics, reliability analysis, correlation analysis, and multiple regression analysis. The findings indicate that the proposed model explains 73.2% of the variance in behavioural intention (R² = 0.732). Habit, price value, hedonic motivation, and effort expectancy emerged as significant positive predictors of consumers' behavioural intention to adopt AI-enabled recommendation systems, while performance expectancy, social influence, and facilitating conditions showed comparatively weaker effects in the combined regression model. The results further reveal a strong positive relationship between behavioural intention and actual use of AI recommendation systems, confirming the applicability of the UTAUT2 framework in explaining AI adoption behaviour. The study highlights that consumers continued use of AI-driven recommendation systems is influenced not only by functional benefits but also by enjoyment, perceived value, and habitual usage. These findings provide valuable implications for e-commerce platforms and marketers in designing user-centric, engaging, and trustworthy AI-powered recommendation systems that encourage sustained consumer adoption and enhance the online shopping experience.
DOI: http://doi.org/10.5281/zenodo.20812976
