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Factors that influence new generation candidates to engage with and complete digital, AI-enabled recruiting

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  • van Esch, Patrick
  • Black, J. Stewart

Abstract

Recruiting talent has moved from a tactical HR activity to a strategic business priority. This has been driven by shifts in the source of firm value and competitive advantage and the critical role of human capital in those shifts. Technological advances have moved digital, AI-enabled recruiting from a peripheral curiosity to a critical capability. However, we know little about candidates' reactions to AI-enabled recruiting. Consequently, in this study, we examine the role of social media use, intrinsic rewards, fair treatment, and perceived trendiness on the intentions of prospective employees to engage with and complete digital, AI-enabled recruiting processes. The positive relationships between these factors and candidates' engagement with AI-enabled recruiting have several important practical implications for managers. We also examine the larger implications and make general recommendations to firms about using AI-enabled recruiting technology and tools.

Suggested Citation

  • van Esch, Patrick & Black, J. Stewart, 2019. "Factors that influence new generation candidates to engage with and complete digital, AI-enabled recruiting," Business Horizons, Elsevier, vol. 62(6), pages 729-739.
    • Handle: RePEc:eee:bushor:v:62:y:2019:i:6:p:729-739
    DOI: 10.1016/j.bushor.2019.07.004
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    Cited by:

    1. Xu, Yingzi & Shieh, Chih-Hui & van Esch, Patrick & Ling, I-Ling, 2020. "AI customer service: Task complexity, problem-solving ability, and usage intention," Australasian marketing journal, Elsevier, vol. 28(4), pages 189-199.
    2. Pedro César Martínez-Morán & Jose Maria Fernández-Rico Urgoiti & Fernando Díez & Josu Solabarrieta, 2021. "The Digital Transformation of the Talent Management Process: A Spanish Business Case," Sustainability, MDPI, vol. 13(4), pages 1-16, February.
    3. Anna Lena Hunkenschroer & Christoph Luetge, 2022. "Ethics of AI-Enabled Recruiting and Selection: A Review and Research Agenda," Journal of Business Ethics, Springer, vol. 178(4), pages 977-1007, July.
    4. Magdalena Graczyk-Kucharska & Robert Olszewski & Gerhard-Wilhelm Weber, 2023. "The use of spatial data mining methods for modeling HR challenges of generation Z in greater Poland Region," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 31(1), pages 205-237, March.
    5. Prikshat, Verma & Islam, Mohammad & Patel, Parth & Malik, Ashish & Budhwar, Pawan & Gupta, Suraksha, 2023. "AI-Augmented HRM: Literature review and a proposed multilevel framework for future research," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    6. Black, J. Stewart & van Esch, Patrick, 2021. "AI-enabled recruiting in the war for talent," Business Horizons, Elsevier, vol. 64(4), pages 513-524.
    7. Manjul Gupta & Carlos M. Parra & Denis Dennehy, 2022. "Questioning Racial and Gender Bias in AI-based Recommendations: Do Espoused National Cultural Values Matter?," Information Systems Frontiers, Springer, vol. 24(5), pages 1465-1481, October.
    8. Miglena Stoyanova, 2022. "Impact Of Artificial Intelligence On Recruitment Process," INTERNATIONAL SCIENTIFIC AND PRACTICAL CONFERENCE "HUMAN RESOURCE MANAGEMENT", University of Economics - Varna, issue 1, pages 184-191.
    9. Cao, Guangming & Duan, Yanqing & Edwards, John S. & Dwivedi, Yogesh K., 2021. "Understanding managers’ attitudes and behavioral intentions towards using artificial intelligence for organizational decision-making," Technovation, Elsevier, vol. 106(C).
    10. Md Sohel Chowdhury & Dae-seok Kang, 2021. "Modeling Corporate Environmental Responsibility Perceptions and Job-Seeking Intentions: Examining the Underlying Mechanism," Sustainability, MDPI, vol. 13(11), pages 1-15, June.

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