Multi-factor model of in-house planning of high-tech russian companies in industrial regions

Economic & mathematical methods and models

In this paper, we have confirmed the importance of improving the tools of in-house capital planning in the digital economy. The relevance of the research topic is related to the change in the structure and weight of the parameters in the models of internal planning of industrial enterprises, which are governed by the priorities of the national policy at the macro- and meso-levels. The improvement of in-house planning tools should allow reallocating the existing limited resources of an economic entity in the best possible way. The paper considers the theoretical and practical features of the composition and structure of the parameters that affect the effectiveness of agreements between market players. The features revealed allow identifying the factors of the uncertainty of external and internal environments, as well as the readiness of the market entities to institutional changes with the parameters of internal planning. The object of the study are high-tech domestic companies that operate in industrial regions and form the fourth techno-economic paradigm within the digital economy. The aim of the study is to build a multi-factor model of the influence of institutional asymmetry arising in the digital economy on the implementation of the fourth techno-economic paradigm (INDUSTRY 4.0). This model allows to form a vector of criteria for in-house planning of high-tech domestic companies. We have chosen the main criteria using STEP-analysis. We have used the following methods of scientific cognition: deduction, data analysis, uncertainty estimation and modelling. Along with the methods listed, we have used a systematic approach to processing the materials of the study, a multicriterial approach was applied for preparing modern instruments of in-house capital planning in the developing digital economy in high-tech domestic companies. Within the framework of this study and the constructed linear trends and correlation equations, a multi-factor model of the influence of institutional asymmetry was obtained. Using a multicriterial approach, this model will reconcile the interests of market participants to achieve the goal of strategic in-house planning. The direction of further research involves testing the tools we have constructed in planning the activities of market participants at the meso- and micro-levels.