The Use of Artificial Intelligence (AI) in Talent Acquisition: The Case of Greek Luxury Hotels
Authors: Marinakou, E., Giousmpasoglou, C. and Papavasileiou, E.F.
Journal: Strategic Change
Volume: 34
Issue: 4
Pages: 533-543
eISSN: 1099-1697
DOI: 10.1002/jsc.2632
Abstract:This study introduces a framework for the adoption of Artificial Intelligence (AI) driven technology to talent acquisition processes in luxury hotels. This qualitative study employed 23 semi-structured interviews to explore the perceptions of professionals on AI in luxury hotels in Greece. The findings highlight the benefits of AI-enabled technologies in talent acquisition, including speed, reliability and enhanced candidate communication, however, human interaction remains pivotal at critical stages. The model proposed includes six stages in the AI-Talent Acquisition process, serving as a practical guide for practitioners and researchers. This study contributes to the AI-HRM strategic change field by offering theoretical and practical insights. To the best of the authors' knowledge, it represents one of the initial empirical attempts to develop a comprehensive AI-Talent Acquisition framework, providing valuable implications for ongoing research and implementation in this domain.
https://eprints.bournemouth.ac.uk/40678/
Source: Scopus
The Use of Artificial Intelligence (AI) in Talent Acquisition: The Case of Greek Luxury Hotels
Authors: Marinakou, E., Giousmpasoglou, C. and Papavasileiou, E.F.
Journal: STRATEGIC CHANGE-BRIEFINGS IN ENTREPRENEURIAL FINANCE
Volume: 34
Issue: 4
Pages: 533-543
eISSN: 1099-1697
ISSN: 1086-1718
DOI: 10.1002/jsc.2632
https://eprints.bournemouth.ac.uk/40678/
Source: Web of Science (Lite)
The Use of Artificial Intelligence (AI) in Talent Acquisition: The Case of Greek Luxury Hotels
Authors: Marinakou, E., Giousmpasoglou, C. and Papavasileiou, E.
Journal: Strategic Change
Volume: 33
Issue: 6
Pages: 1-11
Publisher: Wiley-Blackwell
eISSN: 1099-1697
ISSN: 1086-1718
DOI: 10.1002/jsc.2632
Abstract:This study introduces a framework for the adoption of Artificial Intelligence (AI) driven technology to talent acquisition processes in luxury hotels. This qualitative study employed 23 semi-structured interviews to explore the perceptions of professionals on AI in luxury hotels in Greece. The findings highlight the benefits of AI-enabled technologies in talent acquisition, including speed, reliability and enhanced candidate communication, however, human interaction remains pivotal at critical stages. The model proposed includes six stages in the AI-Talent Acquisition process, serving as a practical guide for practitioners and researchers. This study contributes to the AI-HRM strategic change field by offering theoretical and practical insights. To the best of the authors' knowledge, it represents one of the initial empirical attempts to develop a comprehensive AI-Talent Acquisition framework, providing valuable implications for ongoing research and implementation in this domain.
https://eprints.bournemouth.ac.uk/40678/
https://onlinelibrary.wiley.com/journal/10991697
Source: Manual
The use of artificial intelligence (AI) in talent acquisition: The case of Greek luxury hotels
Authors: Marinakou, E., Giousmpasoglou, C. and Papavasileiou, E.F.
Journal: Strategic Change
Publisher: Wiley-Blackwell
ISSN: 1086-1718
Abstract:This study introduces a framework for the adoption of Artificial Intelligence (AI) driven technology to talent acquisition processes in luxury hotels. This qualitative study employed 23 semi-structured interviews to explore the perceptions of professionals on AI in luxury hotels in Greece. The findings highlight the benefits of AI-enabled technologies in talent acquisition, including speed, reliability and enhanced candidate communication, however, human interaction remains pivotal at critical stages. The model proposed includes six stages in the AI-Talent Acquisition process, serving as a practical guide for practitioners and researchers. This study contributes to the AI-HRM strategic change field by offering theoretical and practical insights. To the best of the authors' knowledge, it represents one of the initial empirical attempts to develop a comprehensive AI-Talent Acquisition framework, providing valuable implications for ongoing research and implementation in this domain.
https://eprints.bournemouth.ac.uk/40678/
Source: BURO EPrints