TY - JOUR
T1 - Adoption of smart voice assistants technology among Airbnb guests
T2 - A revised self-efficacy-based value adoption model (SVAM)
AU - Cao, Dongmei
AU - Sun, Yan
AU - Goh, Edmund
AU - Wang, Rachel
AU - Kuiavska, Kate
PY - 2022/2/1
Y1 - 2022/2/1
N2 - 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.
AB - 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.
KW - self-efficacy
KW - smart voice assistant
KW - perceived value
KW - privacy risk
KW - technology adoption
UR - http://www.scopus.com/inward/record.url?scp=85121135276&partnerID=8YFLogxK
U2 - 10.1016/j.ijhm.2021.103124
DO - 10.1016/j.ijhm.2021.103124
M3 - Article
SN - 0278-4319
VL - 101
JO - International Journal of Hospitality Management
JF - International Journal of Hospitality Management
M1 - 103124
ER -