Purchase intention in AI-driven e-commerce: decoding psychological–experiential drivers

Purpose The purpose of this paper is to investigate the psychological–experiential beliefs linkage to understand drivers of purchase intention towards online shopping on artificial intelligence (AI)-enabled platforms. Design/methodology/approach An integrated research model was developed to understand this linkage in AI-driven e-commerce. The data obtained with a structured questionnaire from Indian customers was analyzed for direct path, followed by mediation and moderation analyses using partial least squares structural equation modeling (PLS-SEM) in SmartPLS4. Findings The study identified perceived usefulness, subjective norms, perceived control, faith and customer experience as psychological–experiential determinants of consumer purchase intention in AI-driven e-commerce. Furthermore, AI ease of use and hedonic motivation have significant indirect effect via faith and customer experience. However, socio-demographics are not significant moderators in this research model. Research limitations/implications The generalizability of findings is limited to millennials at sample territory, as young customers are more receptive to shopping using AI-driven platforms. The research advocates for designing intuitive, emotionally-aware and trust-affirming AI interfaces for a positive customer experience, leading to e-shopping in emerging markets. Originality/value The study proposed an integrated model based on technology acceptance model (TAM), theory of planned behavior (TPB) and unified theory of acceptance and use of technology (UTAUT2) to examine the influence of psychological–experiential factors on consumers’ purchase intention. The study endorses a more holistic explanation of this cognitive linkage in context to Indian AI-driven e-commerce.