UDC 338.1
4DOI: 10.36871/2618-9976.2024.09.010
Authors
Yury A. Malyukov,
Candidate of Technical Sciences, ViceRector
for Economic Development and Informatization,
A.N. Kosygin Russian State University (Technologies. Design. Art), Moscow, Russia
Alexey O. Nedosekin,
Doctor of economics, candidate of engineering sciences, academician of IAELPS, CEO of LLC Institute
of Financial Technologies, Saint-Petersburg,
Russia
Zinaida I. Abdulaeva,
Candidate of economic sciences, an associate professor of Department of Medical Informatics
and Physics of North-Western
State Medical University named after I.I. Mechnikov, Russia
Iaroslavna O. Ternovaia,
Senior Engineer of the Department of Organizational Support for Innovation Activities
of the Department of Science, The Kosygin State University of Russia, Moscow, Russia
Abstract
The main objective of this work is to develop a new framework for studying sectoral economic systems based on the probabilistic interpretation of two wellknown mathematical formalism: the Fishburn scheme and Markov chains. The methodology is illustrated by a simple algorithm for assigning weights in the Fishburn scheme, and an example of analyzing intraindustry competition in the international oil and gas sector is provided. This example demonstrates how to identify a Markov chain that links three categories of companies within the industry: «pioneers,» «prospectors» and «observers». The evaluation of transition possibilities in the Markov chain matrix is carried out using the Fishburn scheme, where these possibilities are represented as fuzzy (approximate) probabilities. Based on the information obtained, preliminary qualitative conclusions about the dynamics within the industry can be drawn. The study also expands the methodology for constructing probabilistic Markov chains by relying on basic assumptions for assessing transition possibilities. The results obtained in this work are of significant importance for evaluating the economic resilience of enterprises in dynamic conditions.
Keywords
Linguistic normalization, Quasi-statistics, Linguistic variable, Economic stability, Probabilistic markov chain
