Proposal for modeling social robot acceptance by retail customers: CAN model + technophobia

Abstract

Acceptance of social robots (SRs) in retail is a new field of research in marketing arising from the dilemma between the potential benefits of SRs and the possibility that shoppers will reject them. The main aim of this paper is to advance in the modeling of new technology (NT) acceptance by proposing an extension of the integrative Cognitive-Affective-Normative (CAN) model that improves its explanatory and predictive power by including technophobia (TE) with a view to understanding SR acceptance in retail. The CAN + TE model is tested with a sample of 1069 individuals, resulting in an R2 of 0.73, surpassing the explanatory power of classical models. Emotions – specifically, pleasure – and TE are found to be the biggest drivers of SR acceptance for retail customers, followed by performance expectancy and social influence. Arousal and effort expectancy have no significant effect. These findings have theoretical implications for NT modeling and practical implications for reviving retail – which has been hit hard by the pandemic – opening research lines in both contexts related to the future of SRs.