Fuzzy Set Models for Economic Resilience Estimation
(1) Presented models are proposed for analyzing the resilience of an economic system in a framework of a 4 × 6 matrix, the core of which is a balanced scorecard (BSC). Matrix rows present strategic perspectives, matrix columns present strategic maps. (2) Resilience assessment models are based on fuz...
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MDPI AG
2020-09-01
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Series: | Mathematics |
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Online Access: | https://www.mdpi.com/2227-7390/8/9/1516 |
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author | Alexey Nedosekin Zinaida Abdoulaeva Evgenii Konnikov Alexander Zhuk |
author_facet | Alexey Nedosekin Zinaida Abdoulaeva Evgenii Konnikov Alexander Zhuk |
author_sort | Alexey Nedosekin |
collection | DOAJ |
description | (1) Presented models are proposed for analyzing the resilience of an economic system in a framework of a 4 × 6 matrix, the core of which is a balanced scorecard (BSC). Matrix rows present strategic perspectives, matrix columns present strategic maps. (2) Resilience assessment models are based on fuzzy logic and soft computing, combined with systemic-cybernetic approaches to building presented models. The simplest models are Zadeh linguistic variables that describe key performance indicators (KPIs). The BSC model is an acyclic graph with fuzzy links that are calibrated based on special rules. The information obtained during the simulation is aggregated through a matrix aggregate calculator (MAC). (3) The BSC model was used to assess the economic resilience of a small electrical enterprise in Russia, numbering 2000 people with revenue of approximately 100 million euros per year. The BSC model included about 70 KPIs and 200 fuzzy links. Also, the presented MAC model was applied to obtain linguistic classifiers in five basic industries, using the example of a comparative analysis of 82 international industrial companies. (4) The proposed models allow not only to describe the economic system and its external environment, but also solutions aimed at increasing resilience, within the unified framework. |
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issn | 2227-7390 |
language | English |
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publishDate | 2020-09-01 |
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spelling | doaj.art-c1724bfba5f74bb3b63013d863fd6a922023-11-20T12:38:37ZengMDPI AGMathematics2227-73902020-09-0189151610.3390/math8091516Fuzzy Set Models for Economic Resilience EstimationAlexey Nedosekin0Zinaida Abdoulaeva1Evgenii Konnikov2Alexander Zhuk3International Academy of Ecology Human Security and Nature Sciences (IAELPS) and LLC «C-FINANCE», 198207 St. Petersburg, RussiaGraduate School of Economics and Technologies, Peter the Great St. Petersburg Polytechnic University, 195251 St. Petersburg, RussiaGraduate School of Economics and Technologies, Peter the Great St. Petersburg Polytechnic University, 195251 St. Petersburg, RussiaGraduate School of Economics and Technologies, Peter the Great St. Petersburg Polytechnic University, 195251 St. Petersburg, Russia(1) Presented models are proposed for analyzing the resilience of an economic system in a framework of a 4 × 6 matrix, the core of which is a balanced scorecard (BSC). Matrix rows present strategic perspectives, matrix columns present strategic maps. (2) Resilience assessment models are based on fuzzy logic and soft computing, combined with systemic-cybernetic approaches to building presented models. The simplest models are Zadeh linguistic variables that describe key performance indicators (KPIs). The BSC model is an acyclic graph with fuzzy links that are calibrated based on special rules. The information obtained during the simulation is aggregated through a matrix aggregate calculator (MAC). (3) The BSC model was used to assess the economic resilience of a small electrical enterprise in Russia, numbering 2000 people with revenue of approximately 100 million euros per year. The BSC model included about 70 KPIs and 200 fuzzy links. Also, the presented MAC model was applied to obtain linguistic classifiers in five basic industries, using the example of a comparative analysis of 82 international industrial companies. (4) The proposed models allow not only to describe the economic system and its external environment, but also solutions aimed at increasing resilience, within the unified framework.https://www.mdpi.com/2227-7390/8/9/1516balanced scorecard (BSC)key performance indicators (KPI)4x6 matrixmatrix aggregate calculator (MAC)resilience index (RI) |
spellingShingle | Alexey Nedosekin Zinaida Abdoulaeva Evgenii Konnikov Alexander Zhuk Fuzzy Set Models for Economic Resilience Estimation Mathematics balanced scorecard (BSC) key performance indicators (KPI) 4x6 matrix matrix aggregate calculator (MAC) resilience index (RI) |
title | Fuzzy Set Models for Economic Resilience Estimation |
title_full | Fuzzy Set Models for Economic Resilience Estimation |
title_fullStr | Fuzzy Set Models for Economic Resilience Estimation |
title_full_unstemmed | Fuzzy Set Models for Economic Resilience Estimation |
title_short | Fuzzy Set Models for Economic Resilience Estimation |
title_sort | fuzzy set models for economic resilience estimation |
topic | balanced scorecard (BSC) key performance indicators (KPI) 4x6 matrix matrix aggregate calculator (MAC) resilience index (RI) |
url | https://www.mdpi.com/2227-7390/8/9/1516 |
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