The management process of fiscal policy incorporates a wide analysis of various factors. The dynamic financial approach should be applied in deciding the level of centralization. The article offers the usage of the multicriteria method in selecting fiscal variables as a new instrument for financial evolution. In this article, the hypothesis of decentralization's impact on economic growth is tested to show the growth opportunities. The implications of the fiscal decentralization index on economic growth across the Baltic States for 2005-2017 were examined using a panel data approach with dynamic effects. The Baltic countries (Estonia, Latvia, and Lithuania) are often considered as a single region with similar economic profiles and common political and social values. They are closely related geographically and historically, particularly during the Soviet era. Although their post-Soviet development has been similar, there are significant differences in local administrative systems and government finances. After restoring independence, the three Baltic countries have been reorganizing their public institutions according to western standards. Each country has some differences in organizing the management of local governments. The study's novelty is emphasized by supplementing the analysis with a fiscal decentralization index, including 24 fiscal decentralization indicators. The fiscal decentralization index ranges from 0.29 to 0.51. Lithuania (0,29) has the lowest fiscal decentralization index, the highest – Latvia (0.52) in the Baltic countries. The investigated model has revealed that the facts considered produce a statistically significant effect. Results showed a negative relationship between fiscal decentralization and economic growth in the Baltic States from 2005 to 2017. It should not be forgotten that, in some cases, regions are not capable of implementing green and inclusive growth without the influence of the central government.

Teaching is a specific type of profession with a specific mission. In this study, the motivation level of primary school teachers in Slovakia in the period from 2015 to 2020 was analyzed. A total of 1189 Slovak teachers with a stratified selection were addressed. Cronbach’s Alpha, Tukey’s HSD (honest significant difference), and ANOVA were used to analyze the data obtained. The research results confirm that Slovak teachers are motivated most by relationship and financial factors. Other important motivation factors are atmosphere in the workplace, a good work team, a supervisor’s approach, a fair appraisal system, and a basic salary. The research also confirms that, over the duration of the study, there was a significant change in the average level of motivation factors; however, there was no change in their relative proportion and structure. In relation to gender, significant diachronic differences were confirmed. Research results prove that Slovak teachers have stable requirements in terms of motivation. This study’s findings will further help school management create effective motivation programs for primary school teachers. Regarding the fact that no similar research has been conducted in Slovakia in a long time, the research results presented here are original and unique.

This paper aims to propose a quality assessment model for higher education institutions in the technical–technological field and a system for decision support and optimal management strategies for quality improvement. Obtaining research results is based on surveying stakeholders in higher education and obtaining quantitative data regarding key performance indices. Quantitative data and the genetic algorithm method are applied to determine optimal management strategies for quality improvement. Quality in the higher education sector is among the current issues in the academic community. By monitoring and researching the higher education field and analysing the literature and the current situation in the system of higher education in developing countries, it can be concluded that there is no single way to assess the quality of higher education institutions. This knowledge was a good starting point for the research presented in this paper. Accordingly, the findings include developing a system for quality assessment and the ranking of higher education institutions. Additionally, evaluating the relevance of key performance indicators of higher education institutions differs from different stakeholder perspectives. However, it is possible to develop a system for decision support and the selection of the optimal strategy for improving the performance of study programs and higher education institutions with regard to quality. The practical implications include defining a decision support system that enables the adoption of optimal decisions by the management teams of higher education institutions to improve study programs and the performance of the higher education institutions. The presented system may enable the benchmarking, simulation, and verification of different scenarios for improving the quality and performance of higher education institutions. In this paper, the authors analysed the characteristics, benefits, and drawbacks of different ranking systems to develop and introduce a novel ranking system that suggests weights for the ranking criteria and different perspectives regarding new digital age requirements. The model was tested, and the results are presented to demonstrate the advantages of the developed model. The originality of the research lies in the presented novel model that can be made available to government institutions and serve as a basis for the overall ranking and evaluation of higher education institutions, with the possibility of developing a performance-based funding system. Additionally, other stakeholders can gain an insight into the performance of an institution in relation to their needs and goals.