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• Artificial Intelligence in Human Resources Information Systems: Investigating its Trust and Adoption Determinants

  749-765

  Bilal Ibrahim Hmoud

  László Várallyai

  Views:

  3732

  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.

• What Drives The Diffusion of AI Recruitment Systems in Swiss HRM? The Importance of Technological Expertise, Innovative Climate, Competitive Pressure, Employees’ Expectations and Contextual Factors

  1-43.

  Guillaume Revillod

  Views:

  76

  This study examines organizational, environmental, and contextual factors influencing the diffusion of artificial intelligence recruitment systems in human resources management within Swiss organizations. Based on a survey provided to 324 private and public Swiss HR professionals, it explores how some technology-organization-environment theoretical framework predictors' as well as innovative climate provided by organizations influence the three stages – evaluation, adoption, and routinization ­– of diffusion of this innovation. To do this, the following article is based on a PLS-SEM structural equation model. Its main findings are that technological expertise, innovative climate, competitive pressure, and expectations regarding future use of the tool by organizations working in the same field are directly linked to the spread of this type of AI tool. However, public-sector organizations are more reluctant about using this type of tool. This aversion can, however, be moderated by an innovative climate and the fact that the HR function plays an active part in an organization's strategic direction. This said, this article makes a significant contribution to the literature about the diffusion of emerging technologies in organizations.