Assessment of tax subjects’ interaction under uncertainty of socio-economic processes

Abstract

Topicality of research into interactions between tax environment subjects is justified by growing uncertainty of changes in socio-economic processes. The aim of this study is to assess interaction between taxpayers, controlling bodies and public authorities in view of dominant paradigms and results of expert and sociological research on subjects with regard to the degree of their influence on tax environment climate. Interaction is defined as a certain type of relations between subjects that result in developing mutual influence which induces corresponding changes of their states. Interaction is essentially a poorly structured category, which dictates a need to use soft modeling and subjective evaluation methods (matrix models). According to the degree of influence on tax environment climate, public authorities are proved to be the most influential subject, while taxpayers are found to be the least influential. Summative value of subjects’ interaction is set as Very Good. It is determined by taxpayers’ data as the best among other subjects. Based on the analysis of dynamics in parameters and activity of interaction subjects it is argued that in order to improve subjects’ interaction productivity, it is appropriate to improve the mechanisms of subjects’ interaction with public authorities of all others.

Modelling tax consciousness evaluation in the context of economic development uncertainty

“…Tax consciousness is evaluated as a factor of fulfilling the tax duty conscientiously [23], or as a result of fulfilling the tax duty [15]. The paper [16], [17] substantiates the model of taxation subjects' tax consciousness on the principles of reflexive interaction and integral estimation, which results in a strategy of raising tax consciousness level. Tax consciousness evaluation tools are represented by the methods of sociological research (questionnaires) whose results are statistically estimated [10], [15], [18], [24], analyzed to identify cause and effect relationships and regularities using the correlation and regression analysis [4], [20], [22], Evolutionary Game Theory [19].…”

“…An attempt to take into account the fuzziness of judgments while evaluating tax consciousness was made in a previous work [13], [15] using fuzzy logic methods (Mamdani algorithm). Since the level of tax consciousness becomes evident in the process of taxation, reflexive management methods proved effective as well [16], [17]. The available experience of applied research on tax consciousness, proving strength of certain cause-effect relationships provides basis for expert methods application including T. Saaty's [27], [30] analytic hierarchy process, which should be given special attention.…”

Machine learning for prediction of emergent economy dynamics

“…The behavior of digital economy agents in the context of COVID-19 requires further research, in particular, using cross-recurrent analysis methods. This article highlights further research by the authors, begun in [4,5,6,7,8,9,10]. The article "Comparative analysis of the stock quotes dynamics for IT and the entertainment industry companies based on the characteristics of memory depth" [11] by Nataliia K. Maksyshko and Oksana V. Vasylieva (figure 3) is devoted to the study and comparative analysis of the stock quotes dynamics for the world's leading companies in the IT sector and the entertainment industry.…”