Exploring the Additional Factors Driving Behavioural Intention and User Behaviour in AI-Powered E-Commerce among Young Consumers: A UTAUT Model Approach

Abstract

Purpose: This study explores how the use of AI tools impacts the purchasing behavior of young Indian consumers aged 18–35 years on e-commerce websites. It seeks to analyze how performance expectancy, effort expectancy, social influence, and facilitating conditions affect behavioral intentions and use behavior. Besides, it probes the moderating effects of age, psychological factors, privacy concerns, and role of special events, offers, and coupons in converting product consideration into actual sales.

Design/methodology/Approach: The present investigation employs Structural Equation Modelling (SEM) to examine the data obtained from an online survey conducted among young Indian consumers. This study utilizes the Unified Theory of Acceptance and Use of Technology (UTAUT) framework to investigate the connections between the specified dependent variables and their influence on consumer purchasing decisions.

Findings: Findings of the results demonstrate that the influence of AI-driven personalized recommendations, effort expectancy, social influence, facilitating conditions, and psychological factors on behavioural intentions and use behaviour of young consumers are quite significant. The privacy concern and user experience are very critical moderating factors. At the same time, seasonal deals and rewards can become decisive factors to convert the consideration set into actual purchases, especially for younger consumers.

Originality/value: This research enhances the existing body of literature by utilizing the UTAUT framework to investigate the influence of AI tools on consumer purchasing behavior within the Indian e-commerce sector. It specifically examines the interplay among seasonal promotions, psychological influences, and privacy apprehensions, providing insights into how these factors inform the buying choices of younger consumers.