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№ 2 (2026)
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Научные статьи

SANOAT KLASTERLARIDA INNOVATSION TARMOQLAR SAMARADORLIGINI BAHOLASHNING KOʻP MEZONLI USULLARI

DOI 10.67668/mj/2026iss2/1808

Опубликован 2026-07-06

Авторы
Mamadaliyev Anazxon Ziyodillayevich
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Аннотация

Ushbu maqolada sanoat klasterlarida innovatsion tarmoqlar samaradorligini baholashning koʻp mezonli usullari ilmiy jihatdan tahlil qilindi. Tadqiqotda klaster innovatsiyasini tavsiflovchi tarmoqlar va hamkorlik, bilim dinamikasi, innovatsion salohiyat hamda biznes natijadorligi asosiy baholash yoʻnalishlari sifatida qabul qilindi. Baholash jarayonida iyerarxiyalar tahlili, entropiya usuli, TOPSIS va DEA yondashuvlarini birlashtiruvchi metodologik yechim asoslandi. Olingan natijalar integrallashgan baholash tizimi klasterlar oʻrtasidagi innovatsion samaradorlikni ishonchli taqqoslash, ustuvor rivojlanish yoʻnalishlarini aniqlash hamda boshqaruv qarorlarini ilmiy asoslash imkonini berganini koʻrsatdi. Taklif etilgan yondashuv sanoat klasterlarining raqobatbardoshligi va innovatsion rivojlanishini baholashda amaliy ahamiyat kasb etdi.

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Библиографические ссылки

  1. Delgado, M., Porter, M. E., & Stern, S. (2014). Clusters, convergence, and economic performance. Research Policy, 43(10), 1785-1799. https://doi.org/10.1016/j.respol.2014.05.007
  2. Silva Bezerra, P. R., Freitas da Costa, M., & de Barros Jerônimo, T. (2026). Innovation evaluation in industrial clusters: a literature review. Revista de Gestão, 33, 1-15. https://doi.org/10.1108/REGE-07-2025-0100
  3. Experience of Uzbekistan in organizing the activities of cotton-textile clusters. (2024). American Journal of Applied Science and Technology. https://inlibrary.uz/index.php/ajast/article/view/44177
  4. Development strategies of the textile industry of Uzbekistan. Texas Journal of Engineering and Technology. https://zienjournals.com/index.php/tjet/article/download/3099/2589/3077
  5. A systematic literature review on the use of multicriteria decision making methods for small and medium-sized enterprises innovation assessment. (2025). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12290298/
  6. Kosfeld, R. (2023). Research and development intensive clusters and regional competitiveness. Growth and Change, 54(2). https://onlinelibrary.wiley.com/doi/10.1111/grow.12676
  7. McDonald, F., Huang, Q., Tsagdis, D., & Tüselmann, H. J. (2007). Is there evidence to support Porter-type cluster policies? Regional Studies, 41(1), 39-49. https://doi.org/10.1080/00343400601136284
  8. Cohen, W. M., & Levinthal, D. A. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35(1), 128-152. https://doi.org/10.2307/2393553
  9. Liu, C.-F., Jiang, Q., & Raffoul, Y. N. (2024). Evaluation of regional innovation capacity based on social network analysis and entropy-based GC-TOPSIS. Discrete Dynamics in Nature and Society, 2024, 3149746. https://doi.org/10.1155/2024/3149746
  10. Evaluation of city innovation capability using the TOPSIS-based order relation method: The case of Liaoning province, China. (2020). Technology in Society. https://www.sciencedirect.com/science/article/abs/pii/S0160791X19303859
  11. Innovation efficiency evaluation of industrial technology research institute based on three-stage DEA. (2023). Expert Systems with Applications. https://www.sciencedirect.com/science/article/abs/pii/S0957417423005067
  12. Assessing regional differences in green innovation efficiency of industrial enterprises in China. (2019). International Journal of Environmental Research and Public Health, 16(6), 940. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6466068/
  13. A survey on multi criteria decision making methods and its applications. (2013). American Journal of Information Systems, 1(1). https://pubs.sciepub.com/ajis/1/1/5/
  14. A comprehensive and systematic review of multi-criteria decision-making (MCDM) methods to solve decision-making problems: Two decades from 2004 to 2024. (2025). Spectrum of Decision Making and Applications. https://dmap-journal.org/index.php/dmap/article/view/24
  15. OECD, European Union, & Joint Research Centre. (2008). Handbook on constructing composite indicators: Methodology and user guide. OECD Publishing. https://doi.org/10.1787/9789264043466-en
  16. Greco, S., Ishizaka, A., Tasiou, M., & Torrisi, G. (2019). On the methodological framework of composite indices: A review of the issues of weighting, aggregation, and robustness. Social Indicators Research, 141(1), 61-94. https://doi.org/10.1007/s11205-017-1832-9
  17. Evaluation of new quality productive forces in Henan province based on improved entropy weight-TOPSIS method and deep learning. (2025). Scientific Reports, 15. https://doi.org/10.1038/s41598-025-19309-8
  18. Evaluating technology innovation capabilities of companies based on entropy-TOPSIS: The case of solar cell companies. (2022). Information Technology and Management, 23(2). https://doi.org/10.1007/s10799-021-00344-6
  19. Comparison of the criteria affecting the digital innovation performance of the European Union (EU) member and candidate countries with the entropy weight-TOPSIS method. (2024). Technological Forecasting and Social Change, 200. https://www.sciencedirect.com/science/article/pii/S0040162523007795
  20. ]Evaluation of innovation efficiency of high-tech enterprise based on DEA and Malmquist index under the background of sustainable development. (2024). Asia Pacific Journal of Innovation and Entrepreneurship, 18(4), 340-356. https://doi.org/10.1108/APJIE-10-2023-0190
  21. Digital economy, industrial agglomeration, and green innovation efficiency: Empirical analysis based on Chinese data. (2023). Journal of Applied Economics, 26(1). https://doi.org/10.1080/15140326.2023.2289723
  22. Analysis of efficiency of regional innovation systems taking into account regional development. (2019). Advances in Economics, Business and Management Research (CSSDRE 2018). Atlantis Press. https://www.atlantis-press.com/article/25896391.pdf
  23. Innovation efficiency in the Spanish service sectors, and open innovation. (2022). https://www.sciencedirect.com/science/article/pii/S2199853122008319
  24. Cotton textile industry: cluster development in Uzbekistan. (2023). E3S Web of Conferences. https://www.e3sconferences.org/articles/e3sconf/pdf/2023/89/e3sconf_ipfa2023_01002.pdf

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