Artificial Intelligence in Human Resources Information Systems: Investigating its Trust and Adoption Determinants
With the rapidly emerging trend of employing Artificial Intelligence technologies within modern economics. This study is an attempt to fill the research gap associated with the factors that have influence with the adoption of artificial intelligence in human resources information systems on HR-leade...
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| Format: | Article |
| Language: | English |
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Faculty of Engineering, University of Debrecen
2020-04-01
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| Series: | International Journal of Engineering and Management Sciences |
| Subjects: | |
| Online Access: | https://ojs.lib.unideb.hu/IJEMS/article/view/5707 |
| _version_ | 1797655828143013888 |
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| author | Bilal Ibrahim Hmoud László Várallyai |
| author_facet | Bilal Ibrahim Hmoud László Várallyai |
| author_sort | Bilal Ibrahim Hmoud |
| collection | DOAJ |
| description | With the rapidly emerging trend of employing Artificial Intelligence technologies within modern economics. This study is an attempt to fill the research gap associated with the factors that have influence with the adoption of artificial intelligence in human resources information systems on HR-leaders intention to use it. It empirically investigates the influences that trust, technological readiness, facilitating condition and performance expectancy on HR-professional’s behavioral intention to use AI in HRM. Besides, examine the moderating effect of age and experience on the proposed associations. Data were collected from by online questionnaire from 185 HR managers. A structural framework was introduced to test the relationship between study latent variables. Result exhibited that trust and performance expectancy has a significant influence on HR-professionals behavioral intention to use AI-HRIS. Trust and technological readiness showed a significant influence on HR-professionals performance expectancy of using AI-HRIS. While facilitating condition, organizational size and technological readiness did not show a significant influence on HR-professionals behavioral intention toward using AI-HRIS. Lastly, Age and Experience did not have a moderating effect on trust and performance expectancy association with the behavioral intention toward using AI-HRIS. The findings of this study contribute to the theory development of information technology diffusion in HRM.
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| first_indexed | 2024-03-11T17:20:17Z |
| format | Article |
| id | doaj.art-1b5706e4fe754a119c3d007e6c5b6b53 |
| institution | Directory Open Access Journal |
| issn | 2498-700X |
| language | English |
| last_indexed | 2024-03-11T17:20:17Z |
| publishDate | 2020-04-01 |
| publisher | Faculty of Engineering, University of Debrecen |
| record_format | Article |
| series | International Journal of Engineering and Management Sciences |
| spelling | doaj.art-1b5706e4fe754a119c3d007e6c5b6b532023-10-19T12:05:24ZengFaculty of Engineering, University of DebrecenInternational Journal of Engineering and Management Sciences2498-700X2020-04-015110.21791/IJEMS.2020.1.65Artificial Intelligence in Human Resources Information Systems: Investigating its Trust and Adoption DeterminantsBilal Ibrahim Hmoud0László Várallyai1University of Debrecen Faculty of Economics and Business, Department of Business InformaticsUniversity of Debrecen Faculty of Economics and Business, Department of Business InformaticsWith the rapidly emerging trend of employing Artificial Intelligence technologies within modern economics. This study is an attempt to fill the research gap associated with the factors that have influence with the adoption of artificial intelligence in human resources information systems on HR-leaders intention to use it. It empirically investigates the influences that trust, technological readiness, facilitating condition and performance expectancy on HR-professional’s behavioral intention to use AI in HRM. Besides, examine the moderating effect of age and experience on the proposed associations. Data were collected from by online questionnaire from 185 HR managers. A structural framework was introduced to test the relationship between study latent variables. Result exhibited that trust and performance expectancy has a significant influence on HR-professionals behavioral intention to use AI-HRIS. Trust and technological readiness showed a significant influence on HR-professionals performance expectancy of using AI-HRIS. While facilitating condition, organizational size and technological readiness did not show a significant influence on HR-professionals behavioral intention toward using AI-HRIS. Lastly, Age and Experience did not have a moderating effect on trust and performance expectancy association with the behavioral intention toward using AI-HRIS. The findings of this study contribute to the theory development of information technology diffusion in HRM. https://ojs.lib.unideb.hu/IJEMS/article/view/5707Artificial IntelligenceHuman Resources Information systemsHuman Resources ManagementInformation Technology |
| spellingShingle | Bilal Ibrahim Hmoud László Várallyai Artificial Intelligence in Human Resources Information Systems: Investigating its Trust and Adoption Determinants International Journal of Engineering and Management Sciences Artificial Intelligence Human Resources Information systems Human Resources Management Information Technology |
| title | Artificial Intelligence in Human Resources Information Systems: Investigating its Trust and Adoption Determinants |
| title_full | Artificial Intelligence in Human Resources Information Systems: Investigating its Trust and Adoption Determinants |
| title_fullStr | Artificial Intelligence in Human Resources Information Systems: Investigating its Trust and Adoption Determinants |
| title_full_unstemmed | Artificial Intelligence in Human Resources Information Systems: Investigating its Trust and Adoption Determinants |
| title_short | Artificial Intelligence in Human Resources Information Systems: Investigating its Trust and Adoption Determinants |
| title_sort | artificial intelligence in human resources information systems investigating its trust and adoption determinants |
| topic | Artificial Intelligence Human Resources Information systems Human Resources Management Information Technology |
| url | https://ojs.lib.unideb.hu/IJEMS/article/view/5707 |
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