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University Hiring Policies Geared Towards The Use Of Artificial Intelligence: A Theoretical Model Applied To The Italian Case

Author

Listed:
  • POLLIFRONI Massimo

    (University of Turin)

  • IOANA Adrian

    (National University of Science and Technology Politehnica Bucharest)

  • CANUTA (BUCUROIU) Ionela Luminita

    (National University of Science and Technology Politehnica Bucharest)

Abstract

The Italian university system is governed by Law No. 240/2010, which regulates among other things, the organization and recruitment of university staff, incorporating the principles of quality and transparency established by the "Bologna Process". On September 20th, 2024, the Minister of Universities and Research (subsequently MUR), through the issuance of Decree No. 1591, established a working group of experts charged with reforming the current legislation to address some of the critical issues that had emerged over the years. Among the first results of the working group there is the Draft Law No. 1518, presented on May 2025 by MUR, regarding the revision of the procedures for evaluating, and recruiting the university staff dedicated to research and teaching. The background of the paper is therefore represented by the current e-recruiting practices and those proposed by the Draft Law No 1518 and the study follows the "Aprioristic Theory", a theory based on principles that are collateral to empirical evidence, such as ethics, transparency and creativity. Following this approach, the result of the work is the creation of a theoretical e-recruiting model capable of overcoming existing critical issues (and potential ones arising from the announced reform), that uses current Information and Communication Technologies (ICT) integrated with an ethical use of Artificial Intelligence (AI). The conclusions are supported, on the one hand, by empirical evidence from the private sector, which supports the proposed model, and, on the other, by the awareness that the proposal can only be improved through synergistic collaboration between the public institutions and the scientific academies involved in the process of change.

Suggested Citation

  • POLLIFRONI Massimo & IOANA Adrian & CANUTA (BUCUROIU) Ionela Luminita, 2025. "University Hiring Policies Geared Towards The Use Of Artificial Intelligence: A Theoretical Model Applied To The Italian Case," Revista Economica, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 77(2), pages 105-117, December.
  • Handle: RePEc:blg:reveco:v:77:y:2025:i:2:p:105-117
    DOI: 10.56043/reveco-2025-0017
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    References listed on IDEAS

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    1. Agnes Grudniewicz & David Moher & Kelly D. Cobey & Gregory L. Bryson & Samantha Cukier & Kristiann Allen & Clare Ardern & Lesley Balcom & Tiago Barros & Monica Berger & Jairo Buitrago Ciro & Lucia Cug, 2019. "Predatory journals: no definition, no defence," Nature, Nature, vol. 576(7786), pages 210-212, December.
    2. Dan Anghel, 2023. "New Perspectives for Human and Artificial Intelligence Interactions for Leadership e-Recruitment," Societies, MDPI, vol. 13(3), pages 1-11, February.
    3. Hood, Christopher, 1995. "The "new public management" in the 1980s: Variations on a theme," Accounting, Organizations and Society, Elsevier, vol. 20(2-3), pages 93-109.
    4. Massimo Pollifroni, 2015. "E-Government towards Transparency: A Comparative Analysis Applied To the Italian Public Sector," Accounting and Management Information Systems, Faculty of Accounting and Management Information Systems, The Bucharest University of Economic Studies, vol. 14(1), pages 217-233, March.
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    JEL classification:

    • I28 - Health, Education, and Welfare - - Education - - - Government Policy
    • M1 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration
    • M54 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics - - - Labor Management

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