Mathematical model and methodology for assessing the structural observability of a knowledge management system: A practical case study at United Engine Corporation (UEC)
Abstract
In the context of digital transformation, knowledge management has become a critical factor in the sustainable development of organizations; however, the state of Knowledge Management Systems (KMS) often remains poorly formalized and largely unobservable. A research gap exists in the lack of formalized models capable of diagnosing KMS states based on indirect measurements. This study aims to adapt and validate a mathematical framework of structural observability for diagnosing latent states of a KMS using a limited set of indirect measurements derived from expert data. Observability is herein conceptualized as the structural identifiability of a static measurement model, enabling the unique reconstruction of the latent state vector based on expert-specified structural linkages. The methodology integrates principles of structural observability, expert-based verification of causal relationships among state variables, and the weighted least squares (WLS) estimation technique. To enhance estimation reliability, the procedure incorporates dimensionality reduction of the linkage matrix (via aggregation of highly correlated variables) and calibration of the weighting matrix based on the consistency analysis of expert judgments. The primary scientific contribution lies in the adaptation of structural analysis, expert identification, and linear estimation methods to the KMS diagnostic problem, demonstrating the feasibility of recovering internal KMS states from a limited measurement set using expert data. The model’s practical validation at an industrial enterprise reveals that the key observable factors of the KMS are knowledge formalization, knowledge-sharing intensity, and knowledge-sharing culture. Limitations in the observability of absorptive capacity and knowledge relevance within the employed measurement framework are identified. The practical significance of the study is to provide organizations with a quantitative auditing tool for KMS and a data-driven framework for optimizing monitoring systems.
Acknowledgments
The authors express their gratitude to the managers and specialists of United Engine Corporation (UEC) who participated in the expert assessment within the framework of this study. Their profound knowledge, practical experience, and valuable judgments on organizational mechanisms of knowledge management served as the foundation for the construction and validation of the model, ensuring the reliability and practical significance of the results obtained. The authors also sincerely thank the anonymous reviewer, whose comments and recommendations made it possible to significantly improve the quality of the work and refine its key propositions.
Downloads
References
Cristache, N., Croitoru, G., & Florea, N. V. (2025). The influence of knowledge management on innovation and organizational performance. Journal of Innovation & Knowledge, 10(5), 100793. https://doi.org/10.1016/j.jik.2025.100793
Dedunu, H., Weerasinghe, S., & Wickcramasinghe, A. (2025). Reality is different from what we see: Knowledge management and firm innovation. Journal of Innovation & Knowledge, 10(3), 100693. https://doi.org/10.1016/j.jik.2025.100693
Eromosele, P. O., & Korsakova, T. V. (2024). Knowledge management strategy as a factor of in-creasing effectiveness and competitiveness of an organization. Upravlenie v ekonomicheskikh i sotsialnykh sistemakh, (1(19)), 37–42 (in Russian). https://www.elibrary.ru/download/elibrary_67873816_45973031.pdf
Amaechi, C. V., et al. (2025). A systematic literature review on knowledge management for project risk management in construction. Journal of Building Engineering, 114, 114261. https://doi.org/10.1016/j.jobe.2025.114261
Zelenkov, Y. A. (2018). The effectiveness of Russian organizations: The role of knowledge man-agement and change readiness. Russian Journal of Management, 16(4), 513–536. https://doi.org/10.21638/spbu18.2018.403
Sokolov, D. N., & Zavyalova, E. K. (2018). Integration of strategic resources of an organization in the new economy: A conceptual model. Vestnik of Saint Petersburg University. Management, 17(1), 46–68 (in Russian). https://doi.org/10.21638/11701/spbu08.2018.103
Kolyasnikov, M. S., & Kelchevskaya, N. R. (2020). Knowledge management strategies in compa-nies: Trends and the impact of Industry 4.0. Upravlenets, 11(4), 82–96 (in Russian). https://doi.org/10.29141/2218-5003-2020-11-4-7
Jiang, Z., Shi, J., & Liu, Z. (2025). Digital transformation, knowledge management, and ambidex-trous innovation in the high-speed train industry in China: The role of TMT's digital knowledge. Journal of Business Research, 200, 115634. https://doi.org/10.1016/j.jbusres.2025.115634
Zhang, R. (2025). Moderating effect of knowledge entrepreneurship in the relationship between knowledge management process and entrepreneurial success. Journal of Innovation & Knowledge, 10(4), 100752. https://doi.org/10.1016/j.jik.2025.100752
Nakash, M., & Bolisani, E. (2025). Making knowledge management transparent: A new perspec-tive on KM processes integration in the organizational framework. Business Process Management Journal, 31(8), 49–66. https://doi.org/10.1108/BPMJ-07-2024-0566
Gavrilova, T. A., Kuznetsova, A. V., Alkanova, O. N., & Grinberg, E. Y. (2024). Visualization of employee competencies using knowledge maps. Russian Journal of Management, 22(1), 86–112. (In Russian). https://doi.org/10.21638/spbu18.2024.104
Azyabi, N. G. (2018). The impact of knowledge management capabilities and processes on SME performance. Business Informatics, 12(3), 39–52. https://doi.org/10.17323/1998-0663.2018.3.39.52
Blagov, E. Y., & Shcherban, S. A. (2019). Managing organizational forgetting: The case of Rus-sian machine-building companies. Vestnik of Saint Petersburg University. Management, 18(2), 261–287. (In Russian). https://doi.org/10.21638/11701/spbu08.2019.205
Starikov, D. A. (2025). A model for evaluating the effectiveness of knowledge management sys-tems in high-technology companies. Vestnik Evraziyskoy Nauki, 17(s2) (in Russian). https://esj.today/PDF/100FAVN225.pdf
Parshintsev, A. A., & Bogdanova, M. V. (2022). Development of methodological support for the effective development of intellectual capital in the knowledge management system of high-tech project-oriented companies. Upravlencheskiy uchet, (2), 146–152 (in Russian). https://uprav-uchet.ru/index.php/journal/article/view/1663/1125
Dneprovskaya, N. V., & Shevtsova, I. V. (2023). A knowledge management system in the strate-gic development of universities. Business Informatics, 17(2), 20–40. https://doi.org/10.17323/2587-814X.2023.2.20.40
Kalabina, E. G., & Belyak, O. Y. (2021). Knowledge-sharing factors in the management of cross-functional teams. Russian Journal of Management, 19(4), 515–547 (in Russian). https://doi.org/10.21638/spbu18.2021.407
Slavin, B. B. (2022). Technologies of collective intelligence in the management of business pro-cesses of an organization. Business Informatics, 16(2), 36–48. https://doi.org/10.17323/2587-814X.2022.2.36.48
Karayev, R. А., & Sadikhova, N. Y. (2020). The advantages of cognitive approach for enterprise management in modern conditions. Business Informatics, 14(2), 36-47. https://doi.org/10.17323/2587-814X.2020.2.36.47
Zelenkov, Y. A. (2024). Organizational knowledge management and large language models. Rus-sian Journal of Management, 22(3), 573–601 (in Russian). https://doi.org/10.21638/spbu18.2024.309
Kuchumov, I. V. (2024). Algebraic models of data and knowledge representation in modern data-base management systems. Computational Nanotechnology, 11(1), 78–84 (in Russian). https://doi.org/10.33693/2313-223X-2024-11-1-78-84
Miroshnichenko, M. A. (2024). The impact of artificial intelligence on the efficiency of document and knowledge management in the banking sector. Estestvenno-gumanitarnye issledovaniya, 3(53), 552–557 (in Russian). https://cyberleninka.ru/article/n/vliyanie-iskusstvennogo-intellekta-na-effektivnost-upravleniya-dokumentami-i-znaniyami-v-bankovskoy-sfere
Trofimova, N. N. (2024). The impact of knowledge management on improving the efficiency of business operations management. Ekonomika i upravlenie: problemy, resheniya, 6(3), 151–157 (in Russian). https://doi.org/10.36871/ek.up.p.r.2024.03.06.019
Latukha, M. O., Selivanovskikh, L. V., & Mitskevich, E. A. (2019). Talent management practices and absorptive capacity of Russian companies. Russian Journal of Management, 17(1), 5–28 (in Russian). https://cyberleninka.ru/article/n/praktiki-upravleniya-talantlivymi-sotrudnikami-i-pogloschayuschaya-sposobnost-rossiyskih-kompaniy
Pleshkova, A. Y. (2024). Knowledge management practices in Russian educational organizations. Russian Journal of Management, 22(1), 113–130 (in Russian). https://doi.org/10.21638/spbu18.2024.105
Popov, E. V., & Aksenova, T. V. (2019). Main trends in knowledge management theory. Universi-ty Management: Practice and Analysis, 23(3), 14–29 (in Russian). https://doi.org/10.15826/umpa.2019.03.016
Antonets, V. A. (2018). Segmentation of the market for knowledge extraction, creation, dissemina-tion, and practical application. University Management: Practice and Analysis, 22(5), 9–21 (in Russian). https://doi.org/10.15826/umpa.2018.05.045
Babin, E. N. (2018). Digitalization of the university: Building an integrated information environ-ment. University Management: Practice and Analysis, 22(6), 44–54 (in Russian). https://doi.org/10.15826/umpa.2018.06.057
Copyright (c) 2026 National Research University Higher School of Economics
This work is licensed under a Creative Commons Attribution 4.0 International License.
