Love it or hate it? Deconstructing consumers' attitudes towards AI enabled voice shopping

Abstract

The conversational, social and intelligent capabilities of Artificial Intelligence (AI) enabled voice assistants (VAs) to assist humans have grown. However, their use still remains limited for complex tasks such as shopping. While some studies find that consumers are willing to use them, others report negative reactions that lead to rejection, especially for complex activities. This study aims to bridge the gap between the dichotomous streams of literature by investigating the overall attitude towards the use of AI VAs for a multi-step task that is, shopping. We first identify 27 attitudinal criteria through a comprehensive literature review in light of the Uncanny Valley Theory and the Self Determination Theory. The criteria are organized using the cognitive, affective and conative framework of attitude, and ranked using the Fuzzy Analytical Hierarchy Process. Sensitivity analysis is done to affirm the robustness of the framework. Findings reveal that the behavioral intentions to use (conative criteria) are the strongest, followed by feelings evoked during use (affective criteria), followed by beliefs people hold regarding AI VAs (cognitive criteria). Intention to use AI voice assistants during all stages of the purchase journey takes precedence over negative feelings such as loss of control, unfulfillment and vulnerability. This study reconciles the existing stream of literature on conversational AI and provides managerial implications based on the dimensions of attitude.