Chief Editor
  • Prof. Christina Nikolova, PhD
Editorial Board
  • Prof. Christina Nikolova, PhD - UNWE
  • Prof. Elka Todorova, DSc. - UNWE
  • Prof. Maya Lambovska, DSc. - UNWE
  • Assoc. Prof. Todor Nedev, PhD - UNWE
  • Assoc. Prof. Dorina Kabakchieva, PhD - UNWE
  • Assoc. Prof. Paskal Zhelev, PhD - UNWE
Scientific Secretary
  • Assoc. Prof. Aleksandar Valkov, PhD - UNWE
Coordinator
  • Assist. Prof. Veselina Lyubomirova, PhD - UNWE
International Editorial Board
  • Damian Stantchev, PhD
    Edinburgh NAPIER University, UK

  • Ivaylo Vassilev, PhD
    University of Southampton,UK

  • Prof. Irina Kuzmina-Merlino, PhD
    Transport and Telecommunication Institute, Riga

  • Milan Zdravkovic
    University of Niš, Serbia

  • Prof. Niculae Mihaita, PhD
    Bucharest Academy of Economic Studies, Romania

  • Prof. Ricardo Jardim-Gonçalves, PhD
    UNINOVA institute, New University of Lisbon, Portugal

  • Prof. Ing. Jaroslav Belás, PhD
    Tomas Bata University in Zlín, Czech Republic

  • Prof. John Rijsman, PhD
    Tilburg University

  • Prof. Ing. Zdenek Dvorák, PhD
    University of Zilina, Slovak Republic

  • Prof. Zoran Cekerevac, PhD
    “Union – Nikola Tesla” University in Belgrade, Serbia

A Model for Using ChatGPT in Attracting and Selecting Human Resources
YEARBOOK OF UNWE
year 2024
Issue 1

A Model for Using ChatGPT in Attracting and Selecting Human Resources

Abstract

Technologies are critical to professional success, regardless of our attitude toward them. Digital agility is becoming a leading competency of HR professionals. Expertise in conducting interviews in Microsoft Teams and/or organizing online team meetings is no longer enough. One of the study's main results is that the use of ChatGPT increases the efficiency of the attraction and selection process. The conducted experiment proves that ChatGPT is useful only when the one who uses it has fundamental knowledge of the issues sought in ChatGPT.

JEL: М50, O33

Keywords

risk, artificial intelligence, ChatGPT, attracting and selecting
Download YB.2024.1.05.pdf
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ISSN (print): 1312-5486
ISSN (online): 2534-8949