Quantitative Structuring of Academic Staff in HEIs: Analytics Tool for Data-Driven Decision-Making
Decision-making for human resource management is among the important processes determining the Higher Educational Institution’s (HEI) future stability and development. The article presents the process for the design and development of an analytics tool to assist the HEI governing bodies in monitorin...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Sciendo
2025-06-01
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| Series: | Cybernetics and Information Technologies |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/cait-2025-0010 |
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| Summary: | Decision-making for human resource management is among the important processes determining the Higher Educational Institution’s (HEI) future stability and development. The article presents the process for the design and development of an analytics tool to assist the HEI governing bodies in monitoring the academic personnel provision from a quantitative point of view and making decisions about the need to announce appointment and career growth competitions of academic staff members. The tool generates comparative staffing analyses at different HEI levels according to a predefined set of criteria. It allows the governing bodies to track which academic units there is a need for appointments, so that at the same time, the educational process is ensured and the relevant regulatory requirements are met. This enables the optimization and promotion of the efficiency of human resource management processes. The results of the conducted experiments prove the tool’s effectiveness and applicability. |
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| ISSN: | 1314-4081 |