Open AccessA Model for Predicting User Intention to Use Voice Recognition Technologies at the Workplace in Saudi Arabia
Author(s) -
Khalid Majrashi
Publication year - 2022
Publication title -
international journal of technology and human interaction
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.153
H-Index - 19
eISSN - 1548-3916
pISSN - 1548-3908
DOI - 10.4018/ijthi.2022010107
Subject(s) - technology acceptance model , psychology , affect (linguistics) , social psychology , structural equation modeling , applied psychology , nationality , external variable , usability , computer science , political science , communication , human–computer interaction , machine learning , immigration , law , programming language
The use of voice recognition technologies (VRTs) has been expanding, and these are currently used at workplaces. This study tested a model for predicting users’ intention to use VRTs at workplaces. The model extended the technology acceptance model (TAM) and considered four additional factors—perceived privacy, perceived security, perceived trust, and social norms—and four variables—age, education level, gender, and nationality. We validated the model based on responses from 300 employees working in Saudi Arabia. The results indicated a medium level of acceptance and a valid TAM in its original form. Further, perceived privacy and perceived security are significant predictors of perceived trust and perceived trust is an important predictor of attitudes and intention to use VRTs. The social norms variable was a significant predictor of intention to use and accept VRTs. The results also showed that age and education level significantly affect users’ attitudes toward VRT adoption.