How artificiality and intelligence affect voice assistant evaluations - Guha, Abhijit; Bressgott, Timna; Grewal, Dhruv; Mahr, Dominik; Wetzels, Martin; Schweiger, Elisa (Journal of the Academy of Marketing Science, 2023)
AbstractWidespread, and growing, use of artificial intelligence (AI)–enabled voice assistants (VAs) creates a pressing need to understand what drives VA evaluations. This article proposes a new framework wherein perceptions of VA artificiality and VA intelligence are positioned as key drivers of VA evaluations. Building from work on signaling theory, AI, technology adoption, and voice technology, the authors conceptualize VA features as signals related to either artificiality or intelligence, which in turn affect VA evaluations. This study represents the first application of signaling theory when examining VA evaluations; also, it is the first work to position VA artificiality and intelligence (cf. other factors) as key drivers of VA evaluations. Further, the paper examines the role of several theory-driven and/ or practice-relevant moderators, relating to the effects of artificiality and intelligence on VA evaluations. The results of these investigations can help firms suitably design their VAs and suitably design segmentation strategies.