UDC 338
DOI: 10.36871/2618-9976.2023.06.010
Authors
Yury A. Malyukov,
Candidate of Technical Sciences, Russian State University named after A.N. Kosygin (Technology.
Design. Art), Moscow, Russia
Alexey O. Nedosekin,
Doctor of Economics Sciences, PhD in Technical Sciences, Academician of IAELPS, Institute of Financial
Technologies, Saint-Petersburg,
Russia
Zinaida I. Abdulaeva,
PhD in Economic Sciences, Associate Professor, NorthWestern
State Medical University
named after I.I. Mechnikov, SaintPetersburg,
Russia
Abstract
The authors of this article propose to consider the development of a methodology for normalizing the key activity levels of industrial enterprises based on linguistic normalization of factors by methods of fuzzy sets theory. The method is based on annual reporting of XNUMX of the world's largest industrial enterprises concentrated in XNUMX industry classes. XNUMX business activity factors are analyzed. The reporting is collected for the period of XNUMX. For each business activity factor, over XNUMX measurements are collected, which are acceptable for generalization within the framework of statistical histograms. Processing such histograms allows us to form a scale of linguistic norms from five qualitative gradations for each factor in the assessment. Building systems of linguistic gradations for XNUMX industry classes and collected standards allow a new assessment of the complex properties of enterprises: economic resilience, competitiveness, financial viability. A computational example of assessing the economic resilience of the ABC electrical company is considered. In the time period, statistics tend to become obsolete, so it is necessary to develop a methodology for excluding irrelevant measurements from the statistical base. The authors' research is addressed to industrial enterprises of a wide spectrum that would like to correlate their own performance indicators with group results of leading world companies.
Keywords
Linguistic normalization, Quasistatistics, Linguistic variable (L. Zadeh)
