MODEL OF THE BUSINESS PROCESS FOR FORMING RECOMMENDATIONS TO IMPROVE HEI PERFORMANCE IN THE QS WUR RANKING
DOI:
https://doi.org/10.32782/mathematical-modelling/2025-8-2-31Keywords:
key performance indicators, decision-making, ranking, resource optimisation, business process, software component, strategic management, education, model, higher education institutionAbstract
In contemporary conditions, the strategic development of higher education institutions (HEIs) in Ukraine is closely linked to the enhancement of research activities and improvement of teaching and learning processes, which serve as key factors in the modernisation of the national education system. This article presents a model for generating recommendations aimed at improving the performance indicators of higher education institutions in the QS World University Rankings (QS WUR). The research focuses on improving the system of Key Performance Indicators (KPIs) using the case of the National Technical University «Kharkiv Polytechnic Institute» (NTU «KhPI»), with the goal of enhancing the quality of educational, research, and international activities. The purpose of the study is to increase the efficiency of strategic management within higher education institutions through the use of analytical and optimisation methods to produce well-grounded recommendations for improving QS WUR indicators. The methodological foundations of the QS WUR ranking are examined, nine key evaluation indicators of universities are defined, and the dynamics of leading Ukrainian HEIs for the period 2022–2025 are analysed. Methods of strategic analysis were applied to comprehensively study both external and internal factors influencing a university’s position in the QS WUR. The proposed IDEF0 model reflects the interaction between the analytical department, the information system, and the intelligent module (LLM), which ensures the automation of analytics, scenario development, and recommendation generation. The integration of methods of strategic analysis, optimisation modelling, and artificial intelligence enhances the efficiency of management decisions, optimises resource allocation, and supports the formulation of well-substantiated strategies for improving a university’s position in the global ranking. The proposed model serves as a strategic management tool for the development of higher education institutions and can be adapted for various types of universities in Ukraine and abroad. Future research should focus on developing a software prototype of the recommendation system, which would enable integration of the model with real university databases and performance monitoring systems.
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