Innovative Clusters: Qualitative Assessment of Strategic Potential

Anton Churekov

doi:10.21603/2782-2435-2026-6-1-55-70

UDC

INNOVATIVE CLUSTERS: QUALITATIVE ASSESSMENT OF STRATEGIC POTENTIAL Innovative Clusters: Qualitative Assessment of Strategic Potential

АА Аа

Published in Strategizing: Theory and Practice · Pages 55–70 · Rubric: Sectoral, Industrial, and Corporate Strategizing

DOI: https://doi.org/10.21603/2782-2435-2026-6-1-55-70 · EDN: SGGDCA

Received: 04.09.2025 Accepted: 26.12.2025 Published: 17.02.2026 Language of publication: RUS

Authors

Anton Churekov

ORCID

Anton Churekov

OOO Yakovlev and Solution Partners Russian Federation · Moscow

ORCID

ABSTRACT

Strategic potential assessment integrates both quantitative and qualitative methods. Innovative clusters require innovative analytical tools. The article introduces a new qualitative methodology for assessing the strategic innovative potential of cluster structures that rely on the strategic innovative potential of their parts for the sustainable development and competitiveness of the entire structure. A review of available studies on strategic potential and clustering made it possible to integrate quantitative and qualitative methods into a single assessment tool and test its performance on a specific cluster. Using the method of taxonomic analysis, the author ranked the innovation potential indicators, while the methods of structural analysis and comparison revealed the internal relationships between cluster elements. The experiment yielded a set of practical recommendations for increasing the innovative potential of clusters. The taxonomy method proved especially effective. First, it provided an integrated assessment of the innovative potential for each company within a cluster. Second, it revealed the possibility of tracking the progress of individual indicators and determining their contribution. Third, it established the cause-and-effect relationships between parameters that had a positive or negative impact on the strategic innovative sustainability of each cluster. The new methodology is a universal strategic analysis tool that stimulates innovations, compares cluster parts, and optimizes the task allocation while increasing the transparency and manageability of the entire cluster. Its application may strengthen the role of cluster structures in innovative regional and industrial strategic planning.

KEYWORDS

strategizing, methodology, cluster, qualitative assessment, innovative potential, taxonomy

1. Abdusalamov TA. Vozmozhnosti ispol'zovaniya metodov faktornogo i taksonomicheskogo analiza v otsenke innovatsionnogo potenciala regiona [The possibilities of using factorial and taxonomic analysis methods in assessing the region's innovation potential]. Bulletin of Dagestan State University. 2012;(5):149–152. (In Russ.) https://elibrary.ru/PFJJVP

2. Alabina TA, Golubev MR, Morozova EA. “Strategy” in strategizing: Theoretical approaches to the definition of the concept. Theory and practice of strategizing: III international scientific and practical conference. The series "Economic and Financial Strategy". Moscow: Lomonosov Moscow State University Publishing House, 2020. P. 72–75. (In Russ.) https://elibrary.ru/ILMGGD

3. Bodrunov SD. Zoonomia as a new paradigm of balanced ecological-economic-socio-technological development. Energiia: Ekonomika, Tekhnika, Ekologiia. 2018;(9):32–36. (In Russ.) https://doi.org/10.31857/S023336190001709-5

4. Vlasyuk LI. Economic and mathematical support for regional and sectoral strategizing. Strategizing: Theory and Practice. 2024;4(1):96–109. (In Russ.) https://doi.org/10.21603/2782-2435-2024-4-1-96-109

5. Gornostaeva ZV, Chernysheva YuS, Zhidkov VE. Application of the method of taxonomic analysis to assess the competitiveness of garments for special purposes. KANT. 2017;(3):109–112. (In Russ.) https://elibrary.ru/ZHCSJX

6. Dolonin KA. Sovershenstvovanie innovatsionnykh protsessov vysokotekhnologichnykh promyshlennykh kompleksov na osnove klasternogo podkhoda [Improving the innovation processes of high-tech industrial complexes based on the cluster approach]. Cand. Sci. Econ. diss. Samara; 2021. 185 p. (In Russ.) https://elibrary.ru/AKXDQQ

7. Zhuravlev DM. Strategizing of digital transformation of complex socio-economic systems. Ed. VL Kvint. St. Petersburg: IPC SZIU RANEPA; 2024. 352 p. (In Russ.) https://doi.org/10.55959/978-5-89781-862-4

8. Kvint VL. The concept of strategizing. Vol. 1. St. Petersburg: NWIM RANEPA; 2019. 132 p. (In Russ.)

9. Kvint VL, Bodrunov SD. Strategizing the transformation of society: Knowledge, technology, noonomics. St. Petersburg: Institute of New Industrial Development named after SYu Witte; 2021. 351 p. (In Russ.)

10. Mitrokhin VV, Simaeva IK. Taxonomic efficiency analysis of banking policies of credit institutions in the republic of mordovia. Finno-Ugric World. 2013;(4):117–120. (In Russ.) https://elibrary.ru/SGQRXJ

11. Mullina VYa. Upravlenie investirovaniem innovatsionnykh proektov v rossiiskoi ekonomike [Investment management of innovative projects in the Russian economy]. Cand. Sci. Econ. diss. Kazan; 2020. 184 p. (In Russ.) https://elibrary.ru/ICYMOG

12. Sasaev NI. Formation of industrial strategizing methodology; ed. VL Kvint. St. Petersburg: NWIM RANEPA; 2024. 212 p. (In Russ.) https://elibrary.ru/ZFBSHH

13. Shatalkin AI. Taksonomiya: Osnovaniya, printsipy i pravila [Taxonomy: Foundations, principles and rules]. Moscow: The Association of Scientific Publications of the KMC; 2012. 600 p. (In Russ.)

14. Shmeleva AS. Metody i instrumenty gibkogo upravleniya tsifrovymi innovatsionnymi proektami [Methods and tools for flexible management of digital innovation projects]. Cand. Sci. Econ. diss. Saint-Petersburg; 2022. 243 p. (In Russ.) https://elibrary.ru/TMSYEL

15. Chaudhry M, Shafi I, Mahnoor M, Ramírez Vargas DL, Thompson EB, et al. A systematic literature review on identifying patterns using unsupervised clustering algorithms: A data mining perspective. Symmetry. 2023;15(9):1679. https://doi.org/10.3390/sym15091679

16. Muro M, Kulkarni S. America’s advanced industries: New trends. Washington: Brookings Institution, Metropolitan Policy Program; 2015. 36 p.

17. Schützler O, Schlüter J. Comparing methods for the evaluation of cluster structures in multidimensional analyses. Data and methods in corpus linguistics: Comparative approaches. Cambridge: Cambridge University Press; 2022. P. 259–288.

JATS XML

Chairman of the International Editorial Board

Vladimir Kvint

Editor-in-Chief

Albert Bakhtizin

albert.bakhtizin@gmail.com

Editorial board member

Anna Khvorostyanaya

Khvorostyanayaas@gmail.com

GOST

Churekov A. A. Innovative Clusters: Qualitative Assessment of Strategic Potential // . 2026. pp. 55-70. DOI: https://doi.org/10.21603/2782-2435-2026-6-1-55-70. EDN: SGGDCA. (Date of access 19.08.2026).

MLA

Anton Churekov. "Innovative Clusters: Qualitative Assessment of Strategic Potential." (2026): 55-70. DOI: https://doi.org/10.21603/2782-2435-2026-6-1-55-70. EDN: SGGDCA.

APA

Churekov A. A. (2026). Innovative Clusters: Qualitative Assessment of Strategic Potential. , 55-70. https://doi.org/10.21603/2782-2435-2026-6-1-55-70 EDN: SGGDCA.

Chicago

Anton Churekov. "Innovative Clusters: Qualitative Assessment of Strategic Potential." , no. (2026): 55-70. https://doi.org/10.21603/2782-2435-2026-6-1-55-70. EDN: SGGDCA.

WIKI

{{cite journal | author = Churekov A. A. | title = Innovative Clusters: Qualitative Assessment of Strategic Potential | journal = | year = 2026 | pages = 55-70 | doi = 10.21603/2782-2435-2026-6-1-55-70 }} EDN: SGGDCA

Copy

Export: BibTeX EndNote RefMan RusMARC

INNOVATIVE CLUSTERS: QUALITATIVE ASSESSMENT OF STRATEGIC POTENTIAL Innovative Clusters: Qualitative Assessment of Strategic Potential

Confirmation