JOURNAL ARTICLE

How Artificial Intelligence can be used in International Human Resources Management: A Case Study.

  • Published In: Global Journal of Business Social Sciences Review (GATR-GJBSSR), 2023, v. 11, n. 1. P. 9 1 of 3

  • Database: Sociology Source Ultimate 2 of 3

  • Authored By: Sommer, Lutz 3 of 3

Abstract

Objective - Artificial Intelligence (AI) tools are becoming more accessible and more manageable in terms of practical implementation, enabling them to be used in many new areas, including the selection of international managers based on their international experience. The choice of personnel in a global environment is a challenge that has been the subject of heated debate for decades, both in practice and theory. Wrong decisions are cost-intensive and possibly contribute to economic failure. The present study aimed to test machine learning algorithms - as sub-disciplines of Artificial Intelligence (AI) - on a low-coding basis. Methodology/Technique – A fictitious use case with a corresponding data set of 75 managers was generated for this purpose. Its applicability in relation to personnel selection for an international task was tested. In the next step, selected AI algorithms were used to test which of these algorithms led to high prediction accuracy. Finding – The results show that with minimal programming effort, the ML algorithm achieved an accuracy of over 80% when selecting suitable managers for international assignments - based on the international experience of this group of people. The linear discriminant analysis has proven particularly relevant, and both the training and validation data provided values above 80%. In summary, ML algorithms' usefulness and feasibility in personnel selection in an international environment could be confirmed. Novelty – It could be confirmed that for implementing the manager selection, freely available algorithms in Python achieve sufficiently good results with an accuracy of 80%. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Global Journal of Business Social Sciences Review (GATR-GJBSSR). 2023/01, Vol. 11, Issue 1, p9
  • Document Type:Article
  • Subject Area:Business and Management
  • Publication Date:2023
  • ISSN:2180-0421
  • DOI:10.35609/gjbssr.2023.11.1(2)
  • Accession Number:162922811
  • Copyright Statement:Copyright of Global Journal of Business Social Sciences Review (GATR-GJBSSR) is the property of Global Academy of Training & Research (GATR) Enterprise and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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