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Multi-Attribute Decision-Making for Intelligent Allocation of Human Resources in Industrial Projects

Author

Listed:
  • Iuliana Grecu

    (Department of Entrepreneurship and Management, Faculty of Entrepreneurship, Business Engineering and Management, National University of Science and Technology Politehnica Bucharest, 020943 Bucharest, Romania)

  • Roxana-Mariana Nechita

    (Department of Entrepreneurship and Management, Faculty of Entrepreneurship, Business Engineering and Management, National University of Science and Technology Politehnica Bucharest, 020943 Bucharest, Romania
    Department of Biomedical Mechatronics and Robotics, National Institute of Research and Development in Mechatronics and Measurement Technique, 021631 Bucharest, Romania)

  • Oliver Ulerich

    (Department of Biomedical Mechatronics and Robotics, National Institute of Research and Development in Mechatronics and Measurement Technique, 021631 Bucharest, Romania
    School of Doctoral Studies in Industrial Engineering and Robotics, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania)

  • Corina-Ionela Dumitrescu

    (Department of Economics, Faculty of Entrepreneurship, Business Engineering and Management, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania)

Abstract

Effective project management depends on a deep understanding of the human attributes that influence project success. This study aims to quantify the causal relationships between human resource variables in order to establish a prioritisation criterion for workforce allocation in industrial projects. Traditional statistical models often overlook the multidimensional nature of these factors, limiting their effectiveness in complex planning contexts. To address this, the Decision-Making Trial and Evaluation Laboratory method is used to assess and prioritise the key competencies required of project personnel. The analysis is based on an extensive literature review of management and industrial project studies, combined with data collected from experienced managers through structured questionnaires. Respondents assessed how different human resource attributes interact and influence each other. The results show that personal motivation, innovation, education, work–life balance, flexibility and adaptability are dominant causal factors. Stakeholder relations, conflict management, negotiation skills, objectivity and impartiality are more reactive. This study is differentiated in that it analyses a complex network of 400 influence relationships, providing a more comprehensive perspective than previous research. By integrating a structured decision-making approach, the results contribute to both the academic literature and practical applications, supporting more effective workforce planning and improved performance in industrial projects.

Suggested Citation

  • Iuliana Grecu & Roxana-Mariana Nechita & Oliver Ulerich & Corina-Ionela Dumitrescu, 2025. "Multi-Attribute Decision-Making for Intelligent Allocation of Human Resources in Industrial Projects," Administrative Sciences, MDPI, vol. 15(5), pages 1-25, May.
    • Handle: RePEc:gam:jadmsc:v:15:y:2025:i:5:p:181-:d:1656417
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    References listed on IDEAS

    as
    1. Murat Gunduz & Mohammed Almuajebh, 2020. "Critical Success Factors for Sustainable Construction Project Management," Sustainability, MDPI, vol. 12(5), pages 1-17, March.
    2. Marc Becker & Dominik Mahr & Gaby Odekerken-Schröder, 2023. "Customer comfort during service robot interactions," Service Business, Springer;Pan-Pacific Business Association, vol. 17(1), pages 137-165, March.
    3. Sungbum Chun & Jinsun Lim & Heeyeob Kang & Wonshick Ryu, 2025. "Facilitation or Replacement: ICT Use in Leisure Constraints Negotiation During the Digital Transformation Era," Sustainability, MDPI, vol. 17(4), pages 1-19, February.
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