Okay Google, Good to Talk to You… Examining the Determinants Affecting Users’ Behavioral Intention for Adopting Voice Assistants: Does Technology Self-Efficacy Matter?

Dewan Mehrab Ashrafi () and Rubina Easmin
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Dewan Mehrab Ashrafi: East Delta University, Bangladesh
Rubina Easmin: East Delta University, Bangladesh

International Journal of Innovation and Technology Management (IJITM), 2023, vol. 20, issue 02, 1-30

Abstract: This study investigates the impact of attitude and trust on the behavioral intention of adopting artificial intelligence (AI)-based voice-assistant services through the integration of parasocial relationship theory (PSR) and human–computer interaction (HCI) theory. Employing a deductive approach, partial least squares structural equation modeling (PLS-SEM) was performed to assess the proposed model based on 295 participants by using a purposive sampling method. Findings revealed that the functional components significantly impacted users’ attitudes, while social attributes, such as social cognition and electronic word of mouth (e-WOM), were revealed to be critical constituents in driving users’ trust. Moreover, technology self-efficacy (TSE) showed a moderating impact on the relationship between trust and behavioral intention to use voice-assistant services. Based on the findings, the study provides robust and meaningful insights for managers and designers to foster trust and form a positive attitude among the users. Additionally, the outcome of the study adds to the body of research on AI-based technology adoption and interactions by investigating the antecedents of trust and attitudes towards voice-assistant services.

Keywords: Artificial intelligence; trust; attitude; behavioral intention; voice assistants (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1142/S0219877023500049

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