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Personnel Selection in a Coffee Shop Company Based on a Multi-Criteria Decision-Aiding and Artificial Intelligence Approach

Author

Listed:
  • Diego Alonso Gastélum-Chavira

    (Department of Economic and Management Sciences, Universidad Autonoma de Occidente, Culiacán 80120, SI, Mexico)

  • Denisse Ballardo-Cárdenas

    (Department of Engineering and Systems, Universidad Autonoma de Occidente, Culiacán 80120, SI, Mexico)

  • Ernesto León-Castro

    (Faculty of Economics and Administrative Sciences, Universidad Catolica de la Santisima Concepcion, Concepcion 4081393, Chile)

Abstract

Human capital management is a strategic element for companies in a globalized world. Therefore, they must use strategies and methods to recruit and select personnel assertively to focus their training, strengthening, and business growth efforts. Personnel selection can be seen as a decision problem and can be addressed in a multi-criteria decision-making context. This work aims to present the selection process of a barista in a Mexican coffee shop. The baristas could be the face of the company to customers, and they could significantly impact their overall experience. The personnel selection process included eleven candidates and three criteria. This process was performed using the ELECTRE-III to model the preferences of a decision-maker and RP2-NSGA-II+H, a multi-objective evolutionary algorithm that exploits fuzzy outranking relations to derive multi-criteria rankings. The ordering obtained with the algorithm did not have any inconsistency concerning the integral preference model, and it allowed for the selection of a candidate to occupy the barista position. The results show the relevance of combining preference modeling with multi-criteria analysis methods for decision-making and artificial intelligence techniques.

Suggested Citation

  • Diego Alonso Gastélum-Chavira & Denisse Ballardo-Cárdenas & Ernesto León-Castro, 2024. "Personnel Selection in a Coffee Shop Company Based on a Multi-Criteria Decision-Aiding and Artificial Intelligence Approach," Mathematics, MDPI, vol. 12(14), pages 1-24, July.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:14:p:2196-:d:1434240
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    References listed on IDEAS

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    3. Brans, J. P. & Vincke, Ph. & Mareschal, B., 1986. "How to select and how to rank projects: The method," European Journal of Operational Research, Elsevier, vol. 24(2), pages 228-238, February.
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