Mohammed Amin Almaiah
Measuring Institutions’ Adoption of Artificial Intelligence Applications in Online Learning Environments: Integrating the Innovation Diffusion Theory with Technology Adoption Rate
Almaiah, Mohammed Amin; Alfaisal, Raghad; Salloum, Said A.; Hajjej, Fahima; Shishakly, Rima; Lutfi, Abdalwali; Alrawad, Mahmaod; Al Mulhem, Ahmed; Alkhdour, Tayseer; Al-Maroof, Rana Saeed
Authors
Raghad Alfaisal
Said A. Salloum
Fahima Hajjej
Rima Shishakly
Abdalwali Lutfi
Mahmaod Alrawad
Ahmed Al Mulhem
Tayseer Alkhdour
Rana Saeed Al-Maroof
Contributors
CJ Bouras
Editor
Abstract
Artificial intelligence applications (AIA) increase innovative interaction, allowing for a more interactive environment in governmental institutions. Artificial intelligence is user-friendly and embraces an effective number of features among the different services it offers. This study aims to investigate users’ experiences with AIA for governmental purposes in the Gulf area. The conceptual model comprises the adoption properties (namely trialability, observability, compatibility, and complexity), relative advantage, ease of doing business, and technology export. The novelty of the paper lies in its conceptual model that correlates with both personal characteristics and technology-based features. The results show that the variables of diffusion theory have a positive impact on the two variables of ease of doing business and technology export. The practical implications of the current study are significant. We urge the concerned authorities in the governmental sector to understand the significance of each factor and encourage them to make plans, according to the order of significance of the factors. The managerial implications provide insights into the implementation of AIA in governmental systems to enhance the development of the services they offer and to facilitate their use by all users.
Journal Article Type | Article |
---|---|
Acceptance Date | Oct 10, 2022 |
Online Publication Date | Oct 12, 2022 |
Publication Date | Oct 12, 2022 |
Deposit Date | Dec 7, 2022 |
Publicly Available Date | Dec 7, 2022 |
Journal | Electronics |
Electronic ISSN | 2079-9292 |
Publisher | MDPI |
Volume | 11 |
Issue | 20 |
Pages | 3291 |
DOI | https://doi.org/10.3390/electronics11203291 |
Publisher URL | https://doi.org/10.3390/electronics11203291 |
Additional Information | Funders : King Faisal University and Princess Nourah bint Abdulrahman University Projects : unspecified |
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Licence
http://creativecommons.org/licenses/by/4.0/
Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/
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