Mathematical methods for evaluating innovative activity at carpet industry enterprises

Abstract

The article examines the rationale and mathematical methods for assessing the innovative activities of carpet manufacturers in order to determine the impact on the economic efficiency of the enterprise. Along with the legislative framework of digitalization of the Republic of Kazakhstan, the article highlights the current state of digitalization in the country. The article also provides financial and operational indicators of the country’s largest carpet manufacturing enterprise. In particular, the author examines the main indicators of the company from the opening of production to the present. The effectiveness of digitalization of carpet production plays an important role in the technological development of the regional spatial-industrial structure, so the production of carpets and carpet products using digital technology has a positive impact on the economy. The article also considers the advantages and disadvantages of the main types of economic and mathematical forecasting. The article offers a regression analysis of economic indicators, as well as conducting a mathematical model analysis between the indicators of the study. In the course of the study, the extrapolation of increasing series of the main indicators of the carpet manufacturing company, as well as the forecasting by trend analysis method were considered. The main indicators of the largest carpet manufacturer in the country were analyzed by extrapolation. As a result, the authors recommended an analysis of the relationship between the selected indicators. The article recommends conducting an analysis to assess the level of reliability of the proposed model after conducting a regression analysis. In this case, the reliability of the model is tested with the regression coefficient, and on the basis of the proposed method, the coefficient of determination is estimated within the 95% reliability level. On the basis of the offered method there is a possibility of forecasting of the main indicators of the carpet and carpet goods production enterprise.