Trust in word of voice communication: why consumers adhere to purchase recommendations made by smart voice assistants

Abstract

PurposeThis study explores the role of smart voice assistants (SVAs) as purchase recommenders, a phenomenon the authors term “word of voice” (WOV) communication. By integrating human–computer interaction (HCI) literature and electronic word of mouth (eWOM) research, the authors examine what makes consumers trust in SVA-transmitted WOV communication following their initial interactions with their SVAs during a purchase process (i.e. post-trust); and the authors propose that consumers' perceptions of their SVAs' smart capabilities (i.e. cognitive, emotional and social) are critically important for building this trust. Moreover, the study explores the influence of post-trust on consumers' adherence to WOV communication, measured by three types of behavioural intentions.Design/methodology/approachData from a survey of 202 United States (US)-based SVA users who employ them to obtain purchase recommendations were collected and analysed. They confirmed the validity of the measurement scales and provided input for the partial least squares modelling (PLS-SEM).FindingsThe results demonstrated that post-trust in WOV communication partially or totally mediates the effect of smart capabilities on consumer adherence to WOV communication; identified the key role of cognitive, emotional and social smart capabilities for building consumers' post-trust in WOV and demonstrated the influence of this trust on behavioural intentions.Originality/valueThe present study contributes by examining the employment of SVAs as recommenders during the purchase process; the authors term this type of communication WOV. It analyses consumers with experience of using SVAs in their purchase processes, revealing that post-trust in WOV communication is the psychological mechanism that explains how the smart capabilities of SVAs determine consumer adherence to the recommendations they receive.

Subscription intentions for ChatGPT plus: a look at user satisfaction and self-efficacy

“…While existing studies have delved into user adoption of AI-based services (DeLone and McLean, 2003;Hern andez Ortega and Lucia-Palacios, 2023;Huang et al, 2021;Kuberkar and Singhal, 2020;Pillai and Sivathanu, 2020;Yanxia et al, 2023), there's a notable scarcity of research on the willingness to pay for such services, especially as they shift from free to paid models. Our study seeks to fill this gap by examining the specific factors that influence subscription intentions for the paid version of ChatGPT-4.…”