Dmytro Zherlitsyn

The paper considers the possibilities of optimizing the search for agricultural information based on Shannon information entropy criterion. A comparison of the degree of uncertainty of information search through the Internet – search systems with similar indicators of Ukrainian agricultural websites. According to the number of hit count in Ukraine in July 2020 to the search engine, which consists of 10 sources, and to agricultural websites (43 sources) by estimating entropy, a conclusion was made about the significant degree of dispersion of agricultural information sources. It should be emphasized that the artificial division into 4 categories (AgroMedia, Agrotrade web resources, Information and advisory resources, Specialized web resources) did not improve the situation according to the degree of uncertainty compared to the search engine system. As for the entropy index, for almost all 4 categories of entropy indices (heterogeneity or diversity) is close to the case of uniform distribution, i.e., the same hit count of all possible resources (their number for all categories is approximately the same 10-11). As a result of the analysis of the potential client base of electronic consulting, it can be quantified as 4,700,000 of agricultural households and about 50,000 small and medium-sized farms. The transition to the land market is likely to lead to a substantial increase in the number of the latter. It was demonstrated that the current educational level of household owners indicates both the need to increase this indicator and the presence of a close relationship with the existing system of professional advisory in Ukraine, which operates in recent years through self-sufficiency and uncertain financial support from central and regional authorities. The existing official database of advisors should be restructured in line with the call of the times to reduce the degree of uncertainty in finding a specialist of the desired profile.

The article considers a method for solving an information asymmetry problem that is relevant for the banking sector. The authors compare bank products and services in which tariff packages are consist of different informational components. The principal feature of the proposed method is to focus on obtaining a subjective evaluation of the attractiveness of the Bank’s offers for specific target groups. This makes the proposed method relevant for Central and commercial banks, as well as for consumers of banking products. Since complex tariff packages of different banks contain not only many indicators but also different sets, it is impossible to directly compare them. The proposed method allows solving the main informational problems of traditional methods for comparing banking products. Using the Fuzzy Inference System (FIS) allows a flexible approach to the aggregation of singular indicators of tariff packages and simplifies the expert procedures. To make rules for fuzzy inference, linguistic constructions close to the natural language can be used. This makes it easier to fill the knowledge base. To solve the set tasks, a methodology for constructing hierarchical FIS is used. In comparison with non-hierarchical FIS it can reduce the requirements to the number of rules in fuzzy inference rule base and system implementation time. The experiments with the fuzzy inference system, which implements a corporate credit cards tariff packages comparison of four Ukrainian banks, showed the effectiveness of the proposed approach. The obtained numerical results are adequately interpreted for the highlighted groups of banking product consumers