Fuzzy logic approach to SWOT analysis for economics tasks and example of its computer realization

• Author: Chernov V., Dorokhov O., Dorokhova L.
• Pages: 317-326

Bulletin of the Transilvania University of Braşov

Series V: Economic Sciences • Vol. 9 (58) No. 1 - 2016

Fuzzy logic approach to SWOT analysis for economics

tasks and example of its computer realization

Vladimir CHERNOV1, Oleksandr DOROKHOV2, Liudmyla DOROKHOVA3

Abstract: The article discusses the widely used classic method of analysis, forecasting and

decision-making in the various economic problems, called SWOT analysis. As known, it is a

qualitative comparison of multicriteria degree of Strength, Weakness, Opportunity, Threat

for different kinds of risks, forecasting the development in the markets, status and prospects

of development of enterprises, regions and economic sectors, territorials etc. It can also be

successfully applied to the evaluation and analysis of different project management tasks -

investment, innovation, marketing, development, design and bring products to market and so

on. However, in practical competitive market and economic conditions, there are various

uncertainties, ambiguities, vagueness. Its making usage of SWOT analysis in the classical

sense not enough reasonable and ineffective. In this case, the authors propose to use fuzzy

logic approach and the theory of fuzzy sets for a more adequate representation and post-

treatment assessments in the SWOT analysis. In particular, has been short showed the

mathematical formulation of respective task and the main approaches to its solution. Also

are given examples of suitable computer calculations in specialized software Fuzicalc for

processing and operations with fuzzy input data. Finally, are presented considerations for

interpretation of the results.

Key-words: fuzzy SWOT analysis, qualitative methods, economic uncertainly, fuzzy

modelling, linguistic assessments, risks forecasting

1. Introduction

The In solving the a wide range of economic problems by researchers, especially in

the early stages, usually used a standard set of well-known and proven methods of

analysis, forecasting and decision-making. Among them, in particular, it is worth

mentioning statistical methods, simulation tools and other types of modelling,

1 Vladimir State University, Department of Computer Science and Management in Technical and

Economic Systems, Vladimir, Russia, vladimir.chernov44@mail.ru

2 Simon Kuznets Kharkiv National University of Economics, Department of Information Systems,

Kharkiv, Ukraine, aleks.dorokhov@meta.ua

3 National Pharmaceutical University, Department of Management and Marketing in Pharmacy,

Kharkiv, Ukraine, liudmyladorokhova@gmail.com