Abstract

Abstract. The purpose of the article is to study and analyze the competitive status of industrial enterprises (on the example of enterprises in the Kryvyi Rih region). Determining the long-term forecast of competitiveness on the basis of extrapolation of performance indicators of an industrial enterprise with the required accuracy. A methodological approach to long-term forecasting of competitiveness on the basis of extrapolation and the use of identification of discrete time series, which allowed to determine the predictive values of factors influencing the competitive status of the enterprise to make effective strategic management decisions. Modern methods of making effective strategic decisions are largely based on the use of forecasting methods, using appropriate statistical material. At the same time, such an approach requires the fulfillment of conditions, the neglect of which leads to the distortion of the obtained conclusions. In particular, this applies to the requirements relating to the identification of discrete time series. For the first time, the application of discrete time series identification is proposed, which is the basis for determining the forecast indicators of enterprise competitiveness on the basis of extrapolation. Analytical dependences on the competitive position of the industrial enterprise of the Kryvyi Rih region and the corresponding factors of influence are constructed. The main components of the impact on competitiveness are analyzed: sales volume; net profit; market share in the product market; intensity of competition in the industry; the ratio of market share of the enterprise being analyzed to the market leader. The results of the study are used in the practice of managers of relevant enterprises in making effective decisions in the system of strategic management. The use of identification of discrete time series allowed to conduct an appropriate assessment of the competitive status of the enterprise and the relevant factors of influence. It is offered to consider the competitive status, to an information and analytical component of competitiveness of the industrial enterprise. Keywords: enterprise, competitive status, forecast, identification, time series, extrapolation. JEL Classification C19, D29 Formulas: 6; fig.: 4; tabl.: 2; bibl.: 31.

Highlights

  • In forecasting, extrapolation is applied to studying time series

  • When it comes to industrial enterprises, data volumes are not large as a rule, this being primarily explained by information being provided in the form of discrete time series with the time interval of one year

  • The application of the extrapolation method allowed to determine the predicted values of factors influencing the competitive position of the enterprise

Read more

Summary

Introduction

Ɋɮɨɪɦɨɜɚɧɨ ɦɟɬɨɞɨɥɨɝɿɱɧɢɣ ɩɿɞɯɿɞ ɞɨ ɩɟɪɫɩɟɤɬɢɜɧɨɝɨ ɩɪɨɝɧɨɡɭɜɚɧɧɹ ɤɨɧɤɭɪɟɧɬɨɫɩɪɨɦɨɠɧɨɫɬɿ ɧɚ ɡɚɫɚɞɚɯ ɟɤɫɬɪɚɩɨɥɹɰɿʀ ɬɚ ɜɢɤɨɪɢɫɬɚɧɧɹ ɿɞɟɧɬɢɮɿɤɚɰɿʀ ɞɢɫɤɪɟɬɧɢɯ ɱɚɫɨɜɢɯ ɪɹɞɿɜ, ɳɨ ɞɨɡɜɨɥɢɥɨ ɜɢɡɧɚɱɢɬɢ ɩɪɨɝɧɨɡɧɿ ɡɧɚɱɟɧɧɹ ɱɢɧɧɢɤɿɜ ɜɩɥɢɜɭ ɧɚ ɤɨɧɤɭɪɟɧɬɧɢɣ ɫɬɚɬɭɫ ɩɿɞɩɪɢɽɦɫɬɜɚ ɡɚɞɥɹ ɭɯɜɚɥɟɧɧɹ ɟɮɟɤɬɢɜɧɢɯ ɫɬɪɚɬɟɝɿɱɧɢɯ ɭɩɪɚɜɥɿɧɫɶɤɢɯ ɪɿɲɟɧɶ. Ɍɩɟɪɲɟ ɡɚɩɪɨɩɨɧɨɜɚɧɨ ɡɚɫɬɨɫɭɜɚɧɧɹ ɿɞɟɧɬɢɮɿɤɚɰɿʀ ɞɢɫɤɪɟɬɧɢɯ ɱɚɫɨɜɢɯ ɪɹɞɿɜ, ɳɨ ɽ ɩɿɞʉɪɭɧɬɹɦ ɜɢɡɧɚɱɟɧɧɹ ɩɪɨɝɧɨɡɧɢɯ ɩɨɤɚɡɧɢɤɿɜ ɤɨɧɤɭɪɟɧɬɨɫɩɪɨɦɨɠɧɨɫɬɿ ɩɿɞɩɪɢɽɦɫɬɜɚ ɧɚ ɡɚɫɚɞɚɯ ɟɤɫɬɪɚɩɨɥɹɰɿʀ. Ȼɢɤɨɪɢɫɬɚɧɧɹ ɿɞɟɧɬɢɮɿɤɚɰɿʀ ɞɢɫɤɪɟɬɧɢɯ ɱɚɫɨɜɢɯ ɪɹɞɿɜ ɞɨɡɜɨɥɢɥɨ ɩɪɨɜɟɫɬɢ ɜɿɞɩɨɜɿɞɧɟ ɨɰɿɧɸɜɚɧɧɹ ɤɨɧɤɭɪɟɧɬɧɨɝɨ ɫɬɚɬɭɫɭ ɩɿɞɩɪɢɽɦɫɬɜɚ ɿ ɜɿɞɩɨɜɿɞɧɢɯ ɮɚɤɬɨɪɿɜ ɜɩɥɢɜɭ. The characteristic feature of extrapolation in the narrow meaning is that it can lean heavily on a rather small amount of data, this being often connected with properties of processes under study When it comes to industrial enterprises, data volumes are not large as a rule, this being primarily explained by information being provided in the form of discrete time series with the time interval of one year. Zhuk investigates issues of revenue forecasting and its place in activities of an enterprise and performs extrapolation-based forecasting of the enterprise’s earnings [11]

Objectives
Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call