State budget revenue generation is the result of the implementation of fiscal policy and the basis for effective government performance. Given that the approaches to generating state budget revenues vary significantly between different countries in terms of the structure of tax revenues and their ratio to non-tax revenues, there is no unified optimal ratio. The article focuses on the study of this issue in Ukraine. Since Ukraine is trying to bring its financial system and, in particular, public finance, as close as possible to the standards and norms of the European Union, it is interesting to model the optimal structure of budget revenues based on the analysis of state revenues in the EU countries. In the article authors suggest the ways to optimizes Ukraine's state budget revenues using the simplex method, which is based on the use of data on their 2007-2019 structure. The main guideline in determining the limits of their optimal volume is the practice of forming national revenues in 25 EU countries over the same period. An additional justification for determining the optimal structure was the use of regression analysis, the results of which were applied to determine the nature and strength of the functional relationships between the income structure and the integral coefficient of structural changes in GDP. Half of the items turned out to have a direct impact, while the other half had a reverse impact on the GDP structure by type of economic activity. Comparison of the obtained optimal values of individual income items with their actual values made it possible to substantiate that the share of internal taxes on goods, services, property and business taxes, as well as an increase in rent payments, needs to be revised upward. In the future, this will require a revision of the regulatory framework for specified taxes and the mechanism for their administration.

This paper aims to quantify the impact of selected demographic, financial, and economic factors on the propensity to do business in the taxi sector of the sharing economy. The sample comprised 375 taxi drivers from the Czech Republic and Slovak Republic. Data were collected using the query method via a questionnaire in April 2022. The structure of the respondents is divided into shared taxi service providers (N = 294) and traditional taxi service providers (N = 69). The study selected 14 factors: demographic (4), financial (7), and economic (3). The SEM approach was applied to evaluate the hypotheses. Shared taxi providers have a stronger propensity to do business than traditional taxi drivers. Demographic characteristics of a traditional taxi driver are the most significant factors with a strong influence on the propensity to do business (βS = 0.525 > βT = 0.425). On the other hand, the financial and economic characteristics of shared taxi drivers strongly influence the propensity to do business (βT = 0.565 > βS = 0.212). The characteristics of the enterprise are on the verge of significance in relation to the tendency to do business with shared taxi drivers, as opposed to traditional taxi drivers. For traditional taxi drivers, there is a strong influence of the characteristics of the enterprise on the propensity to do business (βT = 0.476 > βS = 0.026). This study contributes to understanding how participating in sharing economy may stimulate the propensity to do business.