Consumer innovativeness and purchase behaviour in AI-enabled voice commerce: parallel mediation by attitude and trust

Abstract This study examines the associations between Motivated Consumer Innovativeness (MCI) and purchase behaviour in AI-enabled voice commerce within a theoretically specified model containing two parallel mediators, attitude and trust. MCI is operationalised through functional, hedonic, social, and cognitive innovativeness, while product involvement and technology anxiety are examined as boundary conditions. Using a quantitative cross-sectional design, survey data from 412 consumers with prior voice assistant shopping experience were analysed using partial least squares structural equation modelling (PLS-SEM). The results indicate that all four MCI dimensions are positively associated with attitude and trust, with cognitive innovativeness showing the largest coefficients for both constructs. Attitude and trust are, in turn, positively associated with purchase behaviour. Product involvement and technology anxiety negatively moderate the associations of attitude and trust with purchase behaviour. These findings are interpreted as associations within the proposed cross-sectional model and not as evidence of temporal or causal mechanisms. The study contributes by applying the multidimensional MCI framework to AI-enabled voice commerce and by distinguishing attitude and trust as parallel statistical mediators linking innovation motives with purchase behaviour.