Adoption of smart voice assistants technology among Airbnb guests: a revised self-efficacy-based value adoption model (SVAM)

Cao, D ORCID: https://orcid.org/0000-0002-2614-3726, Sun, Y, Goh, E, Wang, R and Kuiavska, K, 2022. Adoption of smart voice assistants technology among Airbnb guests: a revised self-efficacy-based value adoption model (SVAM). International Journal of Hospitality Management, 101: 103124. ISSN 0278-4319

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Abstract

Smart technology applications in hospitality can leverage user experience values only if they are motivated to adopt the provided technology. This study aimed to understand Airbnb guests’ intentions to adopt smart voice assistants (SVAs) like Amazon Alexa or Google Home. Underpinned by social cognitive theory (SCT), a revised self-efficacy-based value adoption model (SVAM) was developed for the study. A survey sample of 255 UK Airbnb guests was analysed using PLS-SEM statistical technique. The results indicate that perceived functional value, perceived emotional value and perceived privacy risk were the significant determinants for Airbnb guests’ intention to adopt SVAs, while the effect of perceived social value was insignificant. Self-efficacy directly influenced SVA adoption intention among Airbnb guests and indirectly via the perceived values. Our multiple group analysis suggests that self-efficacy on perceived functional value contrasted significantly between everyday users and occasional users. This study is one of the pioneering empirical studies investigating guests’ technology adoption behaviour in the Airbnb context. Specifically, the revised SVAM model advances SCT literature and contributes to understanding smart technology adoption associated with Airbnb guests. Also, this study provides practical implications for Airbnb stakeholders to enhance the Airbnb guest experience value by using Airbnb smart technology applications.

Item Type:	Journal article
Publication Title:	International Journal of Hospitality Management
Creators:	Cao, D., Sun, Y., Goh, E., Wang, R. and Kuiavska, K.
Publisher:	Elsevier BV
Date:	February 2022
Volume:	101
ISSN:	0278-4319
Identifiers:	Number Type 10.1016/j.ijhm.2021.103124 DOI 1604261 Other
Divisions:	Schools > Nottingham Business School
Record created by:	Jeremy Silvester
Date Added:	03 Nov 2023 15:34
Last Modified:	13 Dec 2024 03:00
URI:	https://irep.ntu.ac.uk/id/eprint/50252

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