Exploring the Determinants of Users’ Continuance Usage Intention of Smart Voice Assistants

Journal article

Authors/Editors

DEBAJYOTI PAL

Strategic Research Themes

Digital Transformation (Strategic Research Themes)

Publication Details

Author list: Pal D., Babakerkhell M.D., Zhang X.

Publisher: Institute of Electrical and Electronics Engineers

Publication year: 2021

Journal: IEEE Access (2169-3536)

Volume number: 9

Start page: 162259

End page: 162275

Number of pages: 17

ISSN: 2169-3536

eISSN: 2169-3536

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85120915457&doi=10.1109%2fACCESS.2021.3132399&partnerID=40&md5=54db48b9123238a4283c78e22520b4cd

Languages: English-Great Britain (EN-GB)

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Abstract

The use of personal voice-assistants like Amazon Alexa and Google Assistant has been on the rise recently. To ensure a long-term success and widespread diffusion of these products it is important to evaluate their continued usage scenario instead of the initial adoption intention. Majority of research evaluating the continuance usage scenario do so via an expectation-confirmation approach. However, in this work a user engagement-based approach is taken for evaluating the utilitarian and hedonic attitudes of the users towards the continued usage scenario. This is augmented with additional contextual constructs like trust, privacy risk, and satisfaction. At present, there is little empirical evidence of user engagement with voice-assistants. Moreover, the present work focuses on the continuance usage of late adopters by considering two unique personal factors (slowness of adoption and skepticism). By evaluating the engagement aspect of the laggard group, the current findings contribute to theory by providing a better understanding of how the proposed antecedents determine the continuance intention. Data is collected from 244 late adopters of voice-assistants who use these devices in their daily life for building the research framework. All the proposed hypotheses are supported except the effect of privacy risk. The implications for both theory and practice are provided based on the findings. Author

Keywords

Bibliographies, Focusing, late adopters, Mood, Task analysis, user engagement, Virtual assistants, voice-assistants