Method of Formation and Verification of Expert Appraisals to Build Cognitive Maps in Social and Economic Systems
https://doi.org/10.21686/2413-2829-2026-4-35-47
Abstract
In conditions of high uncertainty and poor formalization of social and economic systems cognitive modeling is becoming a key tool in decision-making support. However, the quality of obtained models directly depends on trustworthiness and coordination of initial expert appraisals. The article advances a brand new method of formation and verification of expert appraisals based on 9-level 3D scale, which can simultaneously take into account the importance of initial concept, power and direction of its impact on other elements of the system. To raise inner agreement of the model verification process through analyzing consonance/dissonance is introduced, which can identify and correct internal logic contradictions in expert’s opinions. The mathematic tool of providing appraisals is realized in the form of interval values, which can allow us to formalize the degree of expert confidence in his/her views and raise sustainability of the model to some errors. Pilot research confirmed that the advanced method can improve inner agreement of the cognitive model by 37% and drop subjective component in expert appraisals by 42% in comparison with conventional approaches. The given methodology can be used in tasks of regional economy, strategic management and other fields, where decision-making is needed in conditions of high uncertainty.
About the Author
K. E. Chikunov
Plekhanov Russian University of Economics
Russian Federation
Russian Federation
Kirill E. Chikunov, Post-Graduate Student of the Department for Applied Informatics and Information Security of the PRUE
36 Stremyanny Lane, Moscow, 109992
References
1. Avdeeva Z. K., Kovriga S. V., Makarenko D. I., Maksimov V. I. Kognitivnyy podkhod v upravlenii [Cognitive Approach in Management]. Problemy upravleniya [Management Problems], 2007, No. 3, pp. 2–8. (In Russ.).
2. Arzhenovskiy I. V., Dakhin A. V. Kognitivnaya regionologiya: opyt modelirovaniya regionalnykh sotsialno-ekonomicheskikh protsessov [Cognitive Regionologics: Experience of Modeling Regional Social and Economic Processes]. Regionologiya [Regionologics], 2020, No. 3 (112), pp. 34–49. (In Russ.).
3. Bolotova L. S. Sistemy iskusstvennogo intellekta: modeli i tekhnologii, osnovannye na znaniyakh [Systems of Artificial Intellect: Models and Technologies Based on Knowledge]. Moscow, 2012. (In Russ.).
4. Borisova V. V. O vozmozhnostyakh kognitivnogo modelirovaniya v zadachakh strategicheskogo upravleniya [Concerning Opportunities of Cognitive Modeling in Tasks of Strategic Management]. Innovatsii i investitsii [Innovation and Investment], 2023, No. 4, pp. 78–85. (In Russ.).
5. Gorelova G. V. Kognitivnoe modelirovanie slozhnykh sistem: sostoyanie i perspektivy [Cognitive Modeling of Complicated Systems: State and Prospects]. Sistemnyy analiz i upravlenie v tekhnicheskikh sistemakh [Systemic Analysis and Management in Technical Systems], 2021, No. 1, pp. 5–14. (In Russ.).
6. Konchenkova E. I., Terelyanskiy P. V. Mnogoparametricheskaya klasterizatsiya innovatsionnykh proektov rannikh stadiy razvitiya na rynke venchurnogo investirovaniya setyami iskusstvennykh neyronov: monografiya [Multi-Parametric Clusterization of Innovation Projects of Early Stages of Development on Market of Venture Investment of Nets of Artificial Neurons: monograph]. Novocherkassk, YURGPU (NPI), 2019. (In Russ.).
7. Kostikova A. V., Kuznetsov S. Yu., Terelyanskiy P. V. Primenenie teorii nechetkikh mnozhestv v zadache otsenki konkurentosposobnosti produktsii [Using the Theory of Fuzzy Sets in Task of Assessing Product Competitiveness]. E-Management , 2023, No. 2, pp. 75–82. (In Russ.).
8. Kostikova A. V., Terelyanskiy P. V. Prinyatie resheniy na osnove dinamicheskikh nechetkikh mnozhestv [Decision-Making on the Basis of Fuzzy Sets]. Audit i finansovyy analiz [Audit and Finance Analysis], 2013, No. 1, pp. 449–457. (In Russ.).
9. Lapshina I. V., Titarenko I. N. Arkticheskaya geopolitika Rossii v razreze kognitivnogo modelirovaniya: analiz sovremennogo sostoyaniya [Arctic Geo-Policy of Russia in View of Cognitive Modeling: Analyzing Current Standing]. Informatsionnye tekhnologii i vychislitelnye sistemy [Information Technologies and Computing Systems], 2023, No. 7 (103), pp. 45–58. (In Russ.).
10. Larichev O. I. Teoriya i metody prinyatiya resheniy, a takzhe khronika sobytiy v volshebnykh stranakh [Theory and Methods of Decision-Making and Chronicle of Events in Enchanted Countries]. Moscow, Logos, 2003. (In Russ.).
11. Mikryukov A. A., Mazurov M. E. Metodicheskiy apparat kognitivnogo modelirovaniya sotsialno-ekonomicheskoy sistemy (universiteta) [Methodological Tool of Cognitive Modeling of Social and Economic Systems (University)]. Statistika i Ekonomika [Statistics and Economics], 2022, No. 4, pp. 67–78. (In Russ.).
12. Mikryukov A. A., Mazurov M. E., Suzdalskiy D. A., Chikunov K. E. Aktualnye voprosy kognitivnogo modelirovaniya slabostrukturirovannykh i plokho formalizuemykh sistem [Acute Issues of Cognitive Modeling of Weakly-Structured and Poorly Formalized Systems]. Vestnik Rossiyskogo ekonomicheskogo universiteta imeni G. V. Plekhanova [Vestnik of the Plekhanov Russian University of Economics], 2025, No. 3 (141), pp. 52–60. (In Russ.).
13. Pospelov D. A. Situatsionnoe upravlenie: teoriya i praktika [Situational Management: Theory and Practice]. Moscow, Nauka, 1986. (In Russ.).
14. Saati T. L. Prinyatie resheniy. Metod analiza ierarkhiy [Decision-Making. Method of Hierarchy Analysis]. Moscow, Radio and Communication, 1993. (In Russ.).
15. Terelyanskiy P. V. Teoriya i metody prinyatiya resheniy [Theory and Practice of Decision-Making]. Volgograd, the Volgograd State Technical University, 2016. (In Russ.).
16. Terelyanskiy P. V., Kostikova A. V. Prinyatie resheniy na osnove dinamicheskikh nechetkikh mnozhestv [Decision-Making on the Basis of Dynamic Fuzzy Sets]. Audit i finansovyy analiz [Audit and Finance Analysis], 2013, No. 1, pp. 449–457. (In Russ.).
17. Torsunov D. A., Chikunov K. E., Danko T. P., Mikryukov A. A. Kognitivnaya model ustoychivogo razvitiya arkticheskogo regiona [Cognitive Model of Sustainable Development in the Arctic Region]. XII Mezhdunarodnaya nauchno-prakticheskaya konferentsiya imeni A. I. Kitova «Informatsionnye tekhnologii i matematicheskie metody v ekonomike i upravlenii» (ITiMM-2023). 23–24 marta 2023 g. Sbornik statey [The 12th International Conference named after A. I. Kitov ‘Information Technologies and Mathematic Methods in Economics and Management’ (IT&MM-2023). March 23–24, 2023: collection of articles], in 2 books. Moscow, Plekhanov Russian University of Economics, 2023. Book 2, pp. 217–224. (In Russ.).
18. Danko T. P., Chaikovskaya L. A., Epstein N. D., Kovalenko N. N., Chikunov K. E. Assessing the Impact of Living Standards on Managing the Development Potential of the Arctic Zones. Strategies and Trends in Organizational and Project Management , edited by P. V. Trifonov, M. V. Charaeva. Cham, Springer, 2022. (Lecture Notes in Networks and Systems; vol. 380), pp. 3–11.
19. Steinbacher M., Raddant M., Karimi F. et al. Advances in the agent-based modeling of economic and social behavior. SN Business & Economics , 2021, Vol. 1, article 99.
20. Structure of Decision: The Cognitive Maps of Political Elites, edited by R. Axelrod. Princeton, N. J., Princeton University Press, 1976.
21. Triantaphyllou E. Multi-Criteria Decision Making Methods: A Comparative Study. Dordrecht, Kluwer Academic Publishers, 2000.
Review
For citations:
Chikunov K.E. Method of Formation and Verification of Expert Appraisals to Build Cognitive Maps in Social and Economic Systems. Vestnik of the Plekhanov Russian University of Economics. 2026;23(4):35-47. (In Russ.) https://doi.org/10.21686/2413-2829-2026-4-35-47
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