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Using artificial intelligence for hiring talents in a moderated mechanism

Author

Listed:
  • Muhaiminul Islam

    (University of Dhaka)

  • Md. Mahbubur Rahman

    (University of Dhaka)

  • Md. Abu Taher

    (University Grants Commission of Bangladesh)

  • G. M. Azmal Ali Quaosar

    (Department of Management Studies, Comilla University)

  • Md. Aftab Uddin

    (University of Chittagong)

Abstract

Globally, artificial intelligence (AI) occupies a burgeoning space among recruiters as it replaces many of the recruitment and selection tasks while hiring the talents. Despite the existence and acceptance of AI being unprecedented among savvy recruiters, the study of it in developing countries’ contexts is still at a fancy stage. Particularly, the extant literature documented that very little is known about the intention and actual use (AU) of AI to hire talents with the intervening effects of voluntariness of usage (VU), tenure, and education of the recruiters elsewhere. Hence, using the doctrine of the extended unified theory of acceptance and use of technology (UTAUT), the present study aims to unpack the intention and AU of AI among hiring professionals in the context of Bangladesh, a developing country in the South Asian region. A multi-item questionnaire survey was employed to collect the data of recruiters from talent acquisition departments in both manufacturing and service organizations with a convenience sampling technique. We used partial least square-based structural equation modeling (PLS-SEM) version 4.0.8.9 to analyze the data. Results showed that performance expectancy (PE), facilitating conditions (FC), and hedonic motivation (HM) have a significant influence on the intention to use (IU) AI (p

Suggested Citation

  • Muhaiminul Islam & Md. Mahbubur Rahman & Md. Abu Taher & G. M. Azmal Ali Quaosar & Md. Aftab Uddin, 2024. "Using artificial intelligence for hiring talents in a moderated mechanism," Future Business Journal, Springer, vol. 10(1), pages 1-16, December.
    • Handle: RePEc:spr:futbus:v:10:y:2024:i:1:d:10.1186_s43093-024-00303-x
    DOI: 10.1186/s43093-024-00303-x
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