A Alsharhan
Technology acceptance drivers for AR smart glasses in the middle east : a quantitative study
Alsharhan, A; Salloum, SA; Aburayya, A
Authors
SA Salloum
A Aburayya
Abstract
This study aims to establish Middle East users' perspectives on the major factors that impact their
decision to adopt Augmented Reality AR smart glasses (ARSG). Thus, an online questionnaire was
designed and sent directly to the respondents, and 584 valid data points were collected from individuals living in the Middle East. The data were analyzed using Pearson correlations and Exploratory
Factor Analysis (EFA) techniques using SPSS. Eleven hypotheses were tested using Multiple Regression analysis, where seven independent variables out of eleven were confirmed to have a significant impact on the perceived adoption of ARSG. The results indicate that four of the independent
variables including Pre-Market Knowledge, Image, Own privacy and Technology innovativeness
show the significant impact on ARSG adoption at the 1% significant level. In addition, the results
indicate that three of the social and technological factors include Perceived Ease of use, Perceived
usefulness and Other's privacy show the significant effect on ARSG adoption at the 5% significant
level. Among the 7 social and technological factors, the results suggest that technology innovation
expresses the strongest effect on ARSG adoption with the highest coefficient value of 0.413 (b =
0.413, t = 12.881, ρ < 0.01). Moreover, user intention is significantly impacted by gender and place
of living but not by education or age. The research also provides pre-market insights on users' personal types that represent who will most likely adopt the new smart glasses and that differentiate
them based on their priorities. To the best of our knowledge, this is among the first works to investigate technology acceptance drivers of AR smart glasses in the Middle East.
Citation
Alsharhan, A., Salloum, S., & Aburayya, A. (2022). Technology acceptance drivers for AR smart glasses in the middle east : a quantitative study. International journal of data and network science (Online), 6(1), 193-208. https://doi.org/10.5267/J.IJDNS.2021.9.008
Journal Article Type | Article |
---|---|
Acceptance Date | Sep 6, 2021 |
Online Publication Date | Sep 9, 2021 |
Publication Date | Jan 1, 2022 |
Deposit Date | Jan 11, 2022 |
Publicly Available Date | Jan 11, 2022 |
Journal | International Journal of Data and Network Science |
Print ISSN | 2561-8148 |
Volume | 6 |
Issue | 1 |
Pages | 193-208 |
DOI | https://doi.org/10.5267/J.IJDNS.2021.9.008 |
Publisher URL | https://doi.org/10.5267/J.IJDNS.2021.9.008 |
Related Public URLs | http://growingscience.com/ijds/ijds.html |
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