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The article describes the management model of complex socioeconomic systems, based on the synthesis of information that characterizes economic systems. To summarize the information, it is proposed to use the Rasch model for estimating latent variables. The management structure of complex economic systems is considered on the basis of generalization of system indicators according to the Rasch model. The mathematical basis for solving the problem is described, including taking into account the importance of the criteria. The case is considered when the values of indicators of the economic system are obtained from a variety of information sources. The results of computational experiments are presented, which allow analyzing the main properties of estimates of generalized indicators of economic systems. Computational experiments have shown that estimates of generalized indicators of objects are measured on a linear scale, are highly accurate and resistant to changes in the source data.

The paper reveals the essence of digital changes and digital transformation. It was possible to determine the essence of strategic approaches to business transformation in the turbulent conditions of digital transformations and outline ways to build strategies for digital transformations. The paper analyzed the factors influencing the implementation of digital transformation strategies of the financial sector. Based on the capabilities of the external environment, a brief analysis of new opportunities for digital transformation in the field of financial services was carried out. An attempt was made to develop approaches to creating strategic digital transformations of financial companies, as well as develop a competitive strategy for the consistent development of a specific financial organization based on strategic digital changes in the digital transformation environment of the industry.

The paper presents a method for calculating the preferred approach when evaluating intellectual property, taking into account local confidence factors, which makes it possible to obtain the final value of intellectual property with high probability and accuracy, using three wellknown approaches. This method has a high practical significance, since all evaluators have to constantly face the choice of the preferred approach. Local confidence factors have been developed with the respect to the type of intellectual property, the type of production, the stage of the life cycle, the purpose of using the object, the value of the indicator deviation from the average value. The influencing factor determines the local confidence factor for each method of evaluation separately through the established functional dependence. The method used neural network modeling, which allows quickly solving a whole range of problems in a single method. Using the proposed method, it is possible to automatically calculate the weighting coefficients of the income, cost, and comparative method, ensuring the necessary accuracy of the final value.

The paper clarifies the concepts of “renewable” and “alternative” energy, classifies alternative energy sources, summarizes their preference over traditional energy sources. The paper considers the issue of using wind power and solar energy as the most acceptable alternative energy sources for the construction of agricultural facilities. A detailed analysis of the strengths and weaknesses of the wind and solar installations applying was carried out.