AI-Driven Recommendations and Purchase Intentions in Social Media Marketing: The Mediating Role of Perceived Ease of Use

Abstract

AI-driven recommendationsis a robust tool in social media marketing that provides tailored content to consumers based on their data and behaviour. It enhances their online experience and satisfaction. The purpose of the study is to explore the effect ofperceived usefulnessand perceived ease of use of AI-driven recommendations on consumers’ purchase intentions in social media marketing. The study also aims to analyse the mediating role of perceived ease of use in the influence of perceived usefulness of AI-driven recommendationson purchase intention in social media marketing. This research is explanatory in nature and uses quantitative methods. The study is based on primary data. It was collected from 58 consumers in Kanniyakumari District. The primary data were gathered online using a well-structured questionnaire.The study utilises the Technology Acceptance Model (TAM) to explain the relationship between perceived usefulness as well as ease of use, and purchase intention in social media marketing. The statistical tools used in this study are percentage, mean score ranking, median, mode, Spearman’s rank correlation, multiple linear regression and bootstrapped mediation analysis.The statistical analyses were performed using Jamovi v2.7.24. The findings of the study revealed that perceived usefulness and perceived ease of use had a significant positive effect on purchase intentions.Further, perceived ease of use partially mediated the relationship between perceived usefulness and purchase intentions in social media marketing.