Balanced Development of the University’s Intellectual Capital Based on Fuzzy Multi-Criteria Models
https://doi.org/10.15826/umpa.2025.01.009
Abstract
This study aims to develop and validate fuzzy multi-criteria models designed to facilitate the balanced development of a university intellectual capital. Fuzzy logic tools offer significant advantages in supporting managerial decision-making for intellectual capital development, particularly given its inherent complexity and evolving structure in the digital economy. The proposed models integrate fuzzy fair compromise approaches and multi-criteria optimization with target functions generated through simulation procedures. These models enable the prioritization of intellectual capital development project portfolios based on three key criteria: (1) proportional development, (2) portfolio utility, and (3) resource requirements. We present and analyze test results from applying these models at a large regional university. The findings demonstrate the framework’s effectiveness in supporting strategic decision-making for intellectual capital growth. This research provides university administrators with practical tools to ensure balanced development of institutional intellectual capital across all organizational levels.
Keywords
intellectual capital,
balanced development,
fuzzy model,
multi-criteria model,
simulation model,
fair compromise model
Supporting agencies: The study was sponsored by the Russian Science Foundation (RSF) as a part of research project No. 23-28-01091 (https://rscf.ru/project/23-28-01091/).
About the Authors
K. S. Solodukhin
Vladivostok State University
Russian Federation
Russian Federation
Konstantin S. Solodukhin – Dr. hab. (Economics), Professor, Head of the Strategic Planning Laboratory, Professor of Mathematics and Modeling Department
G. S. Zavalin
Vladivostok State University
Russian Federation
Russian Federation
Georgiy S. Zavalin – Head of Data Mining Department, Intern Researcher at the Strategic Planning Laboratory
D. V. Makarova
Vladivostok State University
Russian Federation
Russian Federation
Daria V. Makarova – Leading Specialist of the Analytical Department, Intern Researcher at the Strategic Planning Laboratory
References
1. Petrov V. V. Universitetskaya avtonomiya i obshchegosudarstvennaya strategiya: sohranenie balansa [University Autonomy and National Strategy: Maintaining a Balance]. Sibirskii filosofskii zhurnal, 2017, vol. 15, nr 2, pp. 123–136. (In Russ.).
2. Vahitov R. R. Avtonomiya i akademicheskie svobody v sovetskih universitetah (1920–50-e) [Autonomy and Academic Freedom in Soviet Universities (from 1920s to 1950s)]. Universitetskoe upravlenie: praktika i analiz, 2024, vol. 28, nr 1, pp. 144–153. doi 10.15826/umpa.2024.01.010. (In Russ.).
3. Fundamental’nost’ i praktiko-orientirovannost’: kak universitetam naiti «slozhnyi balans»? [Fundamental and Practical Orientation: How Can Universities Find a «Difficult Balance»?]. Akkreditaciya v obrazovanii, 2024, nr 1(149), pp. 54–68. (In Russ.).
4. Petrova G. I., Ovsyannikova Yu. N., Plyusnin L. V. Fundamental’nost’ sovremennogo universitetskogo obrazovaniya: podkhody k opredeleniyu i spetsifika soderzhaniya [The Fundamental Nature of Contemporary University Education: Approaches to Definition and Specifics of Content]. Universitetskoe upravlenie: praktika i analiz, 2024, vol. 28, nr 2, pp. 7–16. doi 10.15826/umpa.2024.02.011. (In Russ.).
5. Ivanova Yu. O. Aktual’nye problemy sovremennykh vostochnoevropeiskikh universitetov: nakhozhdenie balansa mezhdu obucheniem, issledovaniyami i «tret’ei rol’yu» [Actual problems of the modern Eastern European universities: finding the balance between teaching, research and third role]. In: Upravlencheskie nauki v sovremennom mire [Management Sciences in the Modern World: Proceedings of the scientific conference]. Saint-Petersburg, ID «Real’naya ekonomika», 2016, vol. 2, pp. 94–98. (In Russ.).
6. Dremova O. V., Shcheglova I. A. Tret’ya missiya universitetov v Rossii: trend na (ne)kommertsializatsiyu? [Russian Universities’ Third Mission: A Trend towards (Non)commercialization?]. Universitetskoe upravlenie: praktika i analiz, 2022, vol. 26, nr. 2, pp. 27–37. doi 10.15826/umpa.2022.02.010. (In Russ.).
7. Nguyen Quoc A., Le M. T., Pham H. H. The Impact of the Third Mission on Teaching and Research Performance: Evidence from Academic Scholars in an Emerging Country. SAGE Open, 2021, vol. 11, nr 4, pp. 1–12. doi 10.1177/21582440211054493. (In Eng.).
8. Stepchenkova O. S. Disbalans interesov predpriyatij i universitetov kak ugroza interesam ekonomicheskoj bezopasnosti [Corporation-University Interests Imbalance – Economic Security Threat]. In: Sovremennyi menedzhment: problemy i perspektivy: Sbornik statei po itogam XVIII natsional’noi nauchno-prakticheskoi konferentsii s mezhdunarodnym uchastiem (Sankt-Peterburg, 28–29 sentyabrya 2023 g.) [Modern Management: Problems and Prospects: Proceedings of the XVII National Scientific-Practical Conference with International Participation, Saint Petersburg, 11–12th of September], Saint Petersburg, Saint Petersburg State University of Economics, 2023, pp. 329–334. (In Russ.).
9. Masyuk N. N., Baturina O. A., Bushueva M. A. Strategicheskoe partnerstvo universitetov s biznes-sredoi: balans vzaimnykh interesov [The Strategic Partnership Between the University and the Business Environment: Balance Mutual Interests]. Ekonomika i predprinimatel’stvo, 2014, nr 12-4 (53), pp. 824–829. (In Russ.).
10. Solodukhin K. S. Strategicheskoe upravlenie vuzom kak steikkholder-kompaniei [Strategic management of the university as a stakeholder company]. St. Petersburg: Publishing house of St. Petersburg Polytechnic University, 2009, 289 p. (In Russ.).
11. Gres’ko A. A., Solodukhin K. S. Modeli i metody vybora strategii vzaimodeistviya vuza s gruppami zainteresovannykh storon v usloviyakh neopredelennosti [Models and methods for choosing strategies for university interaction with stakeholder groups in conditions of uncertainty], Vladivostok, VGUES Publishing, 2014, 176 p. (In Russ.).
12. Alekseev O. B., Alekhin A. S., Sanatov D. V., Baryshev R. A. Ispol’zovanie metoda regulirovaniya organizatsionnogo balansa dlya transformatsii upravleniya nauchnoi deyatel’nost’yu v universitete [Using the Organizational Balance Method for Transforming the Management of Scientific Activities in a University]. Universitetskoe upravlenie: praktika i analiz, 2024, vol. 28, nr 1, pp. 99–110. doi 10.15826/ umpa.2024.01.007. (In Russ.).
13. Zvereva O. M., Berg D. B. Triadnyi metod otsenki strukturnogo balansa [Triadic Method for Structural Balance Evaluation]. In: Informatsiya: peredacha, obrabotka, vospriyatie: Materialy mezhdunarodnoi nauchno-prakticheskoi konferentsii (Ekaterinburg, 12–13 yanvarya 2016 g.) [Information: Transmission, Processing, Perception: Proceedings of the International Scientific and Practical Conference, Ekaterinburg, 11–12th of January]. Ekaterinburg, Ural Federal University, 2016, pp. 146–161. (In Russ.).
14. Polikhina N. A., Trostyanskaya I. B., Grishakina E. G., Baikov S. A. Gendernyi balans v sfere vysshego obrazovaniya i nauki: mirovye tendentsii, situatsiya v Rossii [Gender balance in higher education and science: global trends and situation in Russia]. Moscow, Center for Sociological Research, 2020, 62 p. (In Russ.).
15. Raichuk D. Yu. Auditornaya nagruzka PPS v svete mirovogo opyta [Teaching Load in the Light of International Experience]. Vysshee obrazovanie v Rossii, 2016, nr 1, pp. 105–112. (In Russ.).
16. Raichuk D. Yu. O vazhnykh usloviyakh stanovleniya issledovatel’skikh universitetov v Rossii [Key Preconditions Needed for Establishing Research Universities in Russia]. Universitetskoe upravlenie: praktika i analiz, 2015, nr 3 (97), pp. 57–65. (In Russ.).
17. Shenderova S. V. Struktura dokhodov vedushchikh mirovykh i rssiiskikh universitetov: sravnitel’nyi analiz po otkrytym istochnikam [The Income Structures of the Leading World and Russian Universities: The Comparative Analysis on the Open Sources of Information]. Universitetskoe upravlenie: praktika i analiz, 2011, nr 1 (71), pp. 12–18. (In Russ.).
18. Korchagina I. V. Dokhody opornykh universitetov Rossii: dinamika i tendentsii [Russian Flagship Universities’ Incomes: Dynamics and Tendencies]. Universitetskoe upravlenie: praktika i analiz, 2021, vol. 25, nr 2, pp. 141–157. doi 10.15826/umpa.2021.02.020. (In Russ.).
19. Airapetyan A. Dokhody i raskhody vysshikh uchebnykh zavedenii RA [Revenues and Expenditures of the RA Higher Educational Institutions]. Amberd byulleten’, 2021, nr 5 (12), pp. 59–69. (In Russ.).
20. Klyuev A. K., Bagirova A. P., Yashin A. A., Zabokritskaya L. D. Predprinimatel’skoe obrazovanie v universitetakh strany: masshtaby, vidy programm, balans kompetentsii [Entrepreneurial Education in Russian Universities: Scope, Types of Programs, Balance of Competences]. Sovremennaya konkurentsiya, 2017, vol. 11, nr 1 (61), pp. 6–20. (In Russ.).
21. Nedoluzhko O. V. Intellektual’nyi kapital v kategoriyakh prostoi modeli kompensatsionnogo gomeostata [Intellectual Capital in Categories of a Simple Model of Compensatory Homeostat]. Vestnik Tomskogo gosudarstvennogo universiteta. Ekonomika, 2018, nr 41, pp. 55–67. doi 10.17223/19988648/41/4. (In Russ.).
22. Nedoluzhko O. V. Management of Intellectual Capital Development of an Organization Based on the System Contradictions between its Elements. Journal of Social Sciences Research, 2018, special iss. 3, pp. 228–234. (In Eng.).
23. Nedoluzhko O. V. Intellektual’nyi kapital organizatsii v kategoriyakh razvernutoi modeli kompensatsionnogo gomeostata [Intellectual Capital in Categories of Enhanced Model of Compensatory Homeostat]. Azimut nauchnykh issledovanii: ekonomika i upravlenie, 2021, vol. 10, nr 2 (35), pp. 252– 256. doi 10.26140/anie-2021-1002-0049. (In Russ.).
24. Arzhanukhin S. V., Makovich G. V. Modeli povedeniya steikkholderov universiteta v protsesse tsifrovoi transformatsii intellektual’nogo kapitala vuza [University Stakeholders’ Behavior Models in the Digital Transformation Process of the University Intellectual Capital]. Human Progress, 2021, vol. 7, iss, 3. pp. 3. doi 10.34709/IM.173.3. (In Russ.).
25. Kleiner G. B. Intellektual’naya ekonomika tsifrovogo veka [Intellectual Economy of the Digital Age]. Ekonomika i matematicheskie metody, 2020, vol. 56, nr 1, pp. 18–33. doi 10.31857/S042473880008562-7. (In Russ.).
26. Nedoluzhko O. V. Tendentsii razvitiya teorii i metodologii intellektual’nogo kapitala organizatsii v tsifrovoi ekonomike [Development Trends in the Theory and Methodology of Organization’s Intellectual Capital in the Digital Economy]. Vestnik Akademii znanii, 2024, nr 2 (61), pp. 316–323. (In Russ.).
27. Bilich F., da Silva R. Valuation and optimization of the impact of intellectual capital on organizational performance. Portuguese Journal of Management Studies, 2008, vol. XIII, iss. 3, pp. 341–359. (In Eng.).
28. Dasilva R., Gomes L., Bilich F. Valuation and optimization of intellectual capital: a multicriteria analysis. REAd, 2006, vol. 12, nr 2, pp. 1–16. (In Eng.).
29. Nazarov D. M. Metodologiya nechetko-mnozhestvennoi otsenki implitsitnykh faktorov v deyatel’nosti organizatsii [Methodology of Fuzzy Set Evaluation of Implicit Factors in Organizational Activities]. Ekaterinburg, Ural State Economic University Press, 2016, 193 p. (In Russ.).
30. Nazarov D. M. Model’ otsenki implitsitnykh faktorov na osnove nechetko-mnozhestvennykh opisanii [The Evaluation Model of Implicit Factors on the Basis of Fuzzyset Descriptions]. Izvestiya DVFU. Ekonomika i upravlenie, 2016, nr 4 (80), pp. 3–17. doi 10.5281/zenodo.220793. (In Russ.).
31. Nazarov D. M. Model’ refleksivnogo otbora implitsitnykh pokazatelei upravlencheskoi deyatel’nosti organizatsii [Model of reflexive selection of implicit indicators of management activities of an organization]. Vestnik SPbGU. Ekonomika, 2017, vol. 33, nr 3, pp. 498–518. doi 10.21638/11701/ spbu05.2017.308. (In Russ.).
32. Zavalin G. S., Nedoluzhko O. V., Solodukhin K. S. Formirovanie kauzal’nogo polya pokazatelei razvitiya intellektual’nogo kapitala organizatsii: kontseptsiya i nechetkaya ekonomiko-matematicheskaya model’. Business Informatics, 2023, vol. 17, nr 3, pp. 53–69. doi 10.17323/2587814X.2023.3.53.69 (In Eng.).
33. Hurtado S. M., Laserna E. Z., Pedroza D. L. Aproximación a la medición del capital intelectual organizacional aplicando sistemas de lógica difusa. Cuadernos de Administración, 2010, vol. 23, nr 40, pp. 35–68. doi 10.11144/ Javeriana.cao23–40.amci. (In Span.).
34. Kale S. Fuzzy Intellectual Capital Index for Construction Firms. Journal of Construction Engineering and Management, 2009, vol. 135, iss. 6, pp. 508–517. doi 10.1061/(ASCE)CO.1943– 7862.0000014. (In Eng.).
35. Arvan M., Omidvar A., Ghodsi R. Intellectual Capital Evaluation Using Fuzzy Cognitive Maps: A Scenario-based Development Planning. Expert Systems with Application, 2016, vol. 55, pp. 21–36. doi 10.1016/j.eswa.2015.12.0 44. (In Eng.).
36. Tkachenko E., Rogova E., Bodrunov S., Klimov V. Ganieva M. Tools for Assessment of Intellectual Assets of Enterprise Based on Fuzzy Information. In: Advances in Economics, Business and Management Research, International Conference on Trends of Technologies and Innovations in Economic and Social Studies (Tomsk, 28–30th of June 2017), Tomsk, Atlantis Press, 2017, vol. 38, pp. 671– 677. doi 10.2991/ttiess-17.2017.110. (In Eng.).
37. Ahmad F., Naseem Sh., Alyas T. et al. Forecastingof Intellectual Capital by Measuring Innovation Using Adaptive Neuro-Fuzzy Inference System. International Review of Applied Sciences, 2015, vol. 2, nr 1, pp. 1–13. (In Eng.).
38. Calabrese A., Costa R., Menichini T. Using Fuzzy AHP to Manage Intellectual Capital Assets: An Application to the ICT Service Industry. Expert Systems with Applications, 2013, vol. 40, iss. 9, pp. 3747–3755. doi 10.1016/j.eswa.2012.12.081. (In Eng.).
39. Jannatifar H., Shahi M. K., Morad J. M. Assessing Intellectual Capital Management by Fuzzy TOPSIS. Management Science Letters, 2012, vol. 2, iss. 6, pp. 1991– 2000. doi 10.5267/j.msl.2012.06.022. (In Eng.).
40. Rohani A., Keshavarz E., Keshavarz A. Prioritising (Ranking) of Indexes for Measuring Intellectual Capital using FAHP and Fuzzy TOPSIS Techniques. International Journal of Industrial and Systems Engineering, 2014, vol. 21, nr 3, pp. 356–378. doi 10.1504/IJISE.2015.072271. (In Eng.).
41. Chen H. Measuring Intellectual Capital using Fuzzy Analytic Hierarchy Process. International Journal of Innovation and Learning, 2008, vol. 6, nr 1, pp. 51–61. doi 10.1504/ IJIL.2009.021682. (In Eng.).
42. Veltri S., Mastroleo G., Schaff hauser-Linzatti M. Measuring intellectual capital in the university sector using a fuzzy logic expert system. Knowledge Management Research & Practice, 2012, vol. 12, iss. 2, pp. 1–18. doi 0.1057/ kmrp.2012.53. (In Eng.).
43. Pokrovskaia N., Margulyan Ya., Lvin Yu., Bulatetskaia A. Neuro-Technologies and Fuzzy Logic for Intellectual Capital Evaluation in Education and Business. In: IOP Conference Series: Materials Science and Engineering, International Scientific Conference “Digital Transformation on Manufacturing, Infrastructure and Service” (St. Petersburg, 21–22th of November 2019), St. Petersburg: IOP Publishing, 2020, vol. 940. doi 10.1088/1757–899X/940/1/012090. (In Eng.).
44. Lee Sh.-H. Using Fuzzy AHP to Develop Intellectual Capital Evaluation Model for Assessing their Performance Contribution in a University. Expert Systems with Applications, 2010, vol. 37, iss. 7, pp. 4941–4947. doi 10.1016/j.eswa.2009.12.020. (In Eng.).
45. Khalili Y., Fakhari H., Malekian E., Aghajani H. Intellectual Capital Indicators Ranking in The Universities of Iran using Delphi Fuzzy Technique. Risk Governance & Control Financial Markets & Institutions, 2017, vol. 7, iss. 2, pp. 147–157. doi 0.22495/rgcv7i2c1p3.
46. Nedoluzhko O. V., Solodukhin K. S. Kolichestvennaya otsenka intellektual’nogo kapitala universiteta na osnove nechetkoi modeli [Quantitative Evaluation of University Intellectual Capital Based on Fuzzy Model]. Universitetskoe upravlenie: praktika i analiz, 2024. vol. 28, nr 1. pp. 34–49. doi 10.15826/umpa.2024.01.003. (In Russ.).
47. Makarova D. V., Nedoluzhko O. V., Solodukhin K. S., Zavalin G. S. Fuzzy Optimization Models for Intellectual Capital Enhancing Project Portfolio Selection under Risk. Journal of System and Management Sciences, 2024, vol. 14, nr 7, pp. 1–19. doi 10.33168/JSMS.2024.0701. (In Eng).
48. Mazelis L. S. Lavrenyuk K. I. Formirovanie investitsionnoi strategii upravleniya chelovecheskim kapitalom kafedry universiteta na osnove nechetkoi dinamicheskoi modeli [Formation of an Investment Strategy of Human Capital Management Departments of the University on Basis of Fuzzy Dynamic Model]. Universitetskoe upravlenie: praktika i analiz, 2015, nr 4 (98), pp. 76–86. (In Russ.).
49. Mazelis L., Lavrenyuk K. Devising A Fuzzy Model for Compiling a Plan of Activities Aimed at Developing Human Capital in University. Eastern-European Journal of Enterprise Technologies, 2017, vol. 4, nr 3, pp. 35–44. doi 10.15587/17294061.2017.103979. (In Eng.).
50. Lavrenyuk K. I., Mazelis L. S., Kryukov V. V. Optimizatsionnye modeli investirovaniya v chelovecheskii kapital kafedry universiteta [Optimization Models of Investing in Human Capital of the University Department]. Vladivostok, VGUES Publishing, 2016, 160 p. (In Russ.).
51. Mazelis L. S., Solodukhin K. S., Tarantaev A. D. Fuzzy Optimization Models for Project Portfolio Rolling Planning Taking into Account Risk and Stakeholder Interests. The Journal of Social Sciences Research, 2018, vol. 2018, special iss. 3, pp. 201–210. doi 10.32861/jssr.spi3.201.210. (In Eng.).
52. Mazelis L. S., Solodukhin K. S., Chen A. Ya. Nechetkie modeli optimizatsii portfelya proektov universiteta s uchetom vliyaniya na kharakteristiki otnoshenii so steikkholderami [Fuzzy Models for Optimizing a University’s Project Portfolio inclusive of Characteristics of Relationships with Stakeholders]. Universitetskoe upravlenie: praktika i analiz, 2017, vol. 21, nr 5, pp. 51–63. (In Russ.).
53. Mazelis L. S., Solodukhin K. S., Chen A. Ya., Tarantaev A. D. Fuzzy Multi-Period Models for Optimizing an Institution’s Project Portfolio Inclusive of Risks and Corporate Social Responsibility. Global Journal of Pure and Applied Mathematics, 2016, vol. 12, nr 5, pp. 4089–4105. (In Eng.).
54. Novak V., Perfilieva I., Dvorak A. Insight into Fuzzy Modeling. Wiley, 2016, 269 p. (In Eng.).
55. Kobelev N. B. Osnovy imitatsionnogo modelirovaniya slozhnykh ekonomicheskikh system [Fundamentals of simulation modeling of complex economic systems], Moscow, Delo, 2003. (In Russ.).
56. Solodukhin K. S. Fuzzy Strategic Decision-Making Models Based on Formalized Strategy Maps. AEBMR-Advances in Economics, Business and Management Research, 2019, vol. 47, Proceedings of the International Scientific Conference «Far East Con» (ISCFEC 2018), pp. 543–547. doi 10.2991/iscfec-18.2019.136. (In Eng.).
57. Mazelis L. S., Solodukhin K. S. Nechetkaya model’ analiza riskov razvitiya sotsial’no-ekonomicheskoi sistemy na osnove steikkholderskogo podkhoda [Fuzzy Model of Socio-Economic System Development Risks Analysis on the Stakeholder Approach Basis. Vestnik Tyumenskogo gosudarstvennogo universiteta. Sotsial’no-ekonomicheskie i pravovye issledovaniya, 2017, vol. 3, nr 3, pp. 242–260. doi 10.21684/24117897-2017-3-3-242-260. (In Russ.).
Review
For citations:
Solodukhin K.S., Zavalin G.S., Makarova D.V. Balanced Development of the University’s Intellectual Capital Based on Fuzzy Multi-Criteria Models. University Management: Practice and Analysis. 2025;29(1):131–144. (In Russ.) https://doi.org/10.15826/umpa.2025.01.009
Views:
27
Email this article 