STRATEGIC FORECAST OF MULTIFACTORIAL IMPACT ON THE EFFICIENCY OF DIVERSIFIED ENTERPRISES

О Zghurska,A Fedorchenko,R Dymenko,V Zalizko,S Kubiv,Ya Larina

doi:10.18371/fcaptp.v5i40.245160

Abstract

Abstract. The purpose of the present scientific research is to perform a strategic forecast of multifactorial impact on the efficiency of diversified enterprises, construction of a multifactorial linear regression model of strategic forecast of profitability level of the studied enterprises, as well as a multifactorial model of logistic regression of strategic forecast of low profitability risks as a result of implementation of innovative strategies of diversified enterprises’ development of in the long run. To achieve this purpose, the main criteria were ranked (Kruskal — Wallis ranking criteria (KWC) to assess the differences between the medians of different samples (c > 2), where KWC is a nonparametric alternative to the F-criterion in the one-factor analysis of variance. If the conditions necessary for the application of the F-criterion in multivariate variance-regression analysis are met, the KWC has the same influence. To build the models, the method of construction of multifactor models of logistic regression with step-by-step inclusion/exclusion of features was used (Stepwise with the inclusion threshold p < 0.1 and the exclusion threshold p > 0.2). The research was conducted on the basis of data from the State Statistics Committee and on the basis of data analysis of the surveyed agro-industrial enterprises. Strategic forecast of the results of multifactorial impact on the efficiency of diversified enterprises was made, based on the formation of a rational management structure of innovative strategies for the development of diversified agro-industrial enterprises. The obtained results allowed to obtain the median indicators of the general set of research objects and a clear bifurcation picture of the strategic development of enterprises for the future. A methodical approach to the implementation of strategic forecasting of multifactorial impact on the efficiency of diversified enterprises, based on the development of strategic guidelines for diversified enterprises taking into account the system of restraining factors of innovative development. This allowed to establish that selection and development of innovative strategies assessment of compliance of internal capabilities of the enterprise (potential of innovative development) with external (market opportunities and threats), with regard to the pace of scientific and technological progress and the resulting change in the elements of micro- and macrosystems of the infrastructure of the enterprise. The multifactorial analysis and construction of the multifactor model of linear regression of strategic forecast of agro-industrial enterprises’ profitability, as well as the multifactorial model of logistic regression of strategic forecast of low profitability risks probability have proved the usefulness of implementation of innovative strategies of competitiveness on domestic and foreign markets. Keywords: agro-industrial enterprise, diversified enterprise, innovative development strategy, optimal strategic decision, strategic forecast. JEL Classification С53, O13, O12 Formulas: 4; fig.: 9; tabl.: 4; bibl.: 33.

Highlights

With the rapid spread of global economic globalization and intellectualization of all spheres of socio-economic development, the latest technologies become the dominant material and technological component, which determines the high level of modern production and sales, the form and content of effective organizational and management structure, and the dynamics of strengthening the competitive advantages of domestic agro-industrial enterprises in domestic and foreign markets.Formation and further innovation and information reorientation of diversified enterprises are in accordance with market conditions of the information society, which in turn dictate the need to ensure vital value and quality indicators of products — one of the main criteria for recognition of national agro-industrial producers in world markets
The development of strategies for the successful development ofdiversified agro-industrial enterprises in a Euro-oriented economy requires the implementation of priority areas of development and identification of potentially new opportunities to ensure competitive advantages in both domestic and foreign markets.In this regard, today there is an objective need to implement a strategic forecast of multifactorial impact on the efficiency of diversified enterprises in the direction of intensification of innovative processes to ensure successful development in the long run
In order to make a strategic forecast of multifactorial impact on the efficiency of diversified enterprises, the key factors were taken into account, namely: a certain agro-industrial enterprise, innovative development strategies

Summary

Introduction

With the rapid spread of global economic globalization and intellectualization of all spheres of socio-economic development, the latest technologies become the dominant material and technological component, which determines the high level of modern production and sales, the form and content of effective organizational and management structure, and the dynamics of strengthening the competitive advantages of domestic agro-industrial enterprises in domestic and foreign markets. Methodology and Data.The strategic forecast of multifactorial impact on the efficiency of diversified enterprises (level of profitability) was made by ranking the main criteria (Kruskal — Wallis ranking criterion (KWC) to assess the differences between the medians of different samples (c > 2). Instead of comparing the average values of Xժ j of all values of the sample from the groups with the total average value of Xժ j, in the KWC the average ranks of each of the groups are compared with the total rank calculated on the basis of all n observations. When these differences are squared, the H-statistic increases. The stepwise on/off feature (Stepwise with an inclusion threshold of p < 0.1 and an exclusion threshold of p > 0.2) was used to select profitability-related features

Results and Discussion

Method

Conclusion