Open Access
| Issue |
BIO Web Conf.
Volume 228, 2026
Biospectrum 2025: International Conference on Biotechnology and Biological Science
|
|
|---|---|---|
| Article Number | 09002 | |
| Number of page(s) | 13 | |
| Section | Concepts of Law and Management in Biotechnology | |
| DOI | https://doi.org/10.1051/bioconf/202622809002 | |
| Published online | 11 March 2026 | |
- A.V. Mokina, T.N. Dobrodomova, E.P. Druzhnikova. Methods for assessing regional clustering, Vol.11, No.2. (2025) [Google Scholar]
- N. Dhondt, L. Vandevelde, A. Greet. European review of the potential role of industrial clusters in the energy system when leveraging energy synergies. J.: Ener. Rep., V. olume 14, December (2025) [Google Scholar]
- K. Kim, P. Zhang. Enhancing spatiotemporal demand prediction in transportation systems through region generation using soft clustering. Transportation Research Part C: Emerging Technologies, Volume 179, October, 105258 (2025) [Google Scholar]
- O.A. Silich. Assessment of the potential for formation and development of regional clusters based on fuzzy set theory. Bulletin of NSEU, No.1 (2016) [Google Scholar]
- A.A. Pankratov, R.A. Musaev, S.V. Badina (2021) Approaches to identifying, measuring, and forecasting cluster effects. J.: Problems of Forecasting, No.3 (2016). [Google Scholar]
- D.K. Begimova. Foreign experience in the use of cluster policy for regional development. Scien.-electr. jour. Economics and Innovative Technologies, No.2, March-April (2021). [Google Scholar]
- R. Ruiga Irina, S. Kovzunova Evgeniya. A conceptual approach to assessing the cluster potential of regions based on the use of intelligent information systems. J.: Nat. Inter.: Prior. & Sec., 2(431), February (2024) [Google Scholar]
- T.A. Shibaeva. Assessment of cluster and network structures of regional economy. Fundamental Research, No.3 (2018) [Google Scholar]
- H. Wang, Y. Zhao, Sh. Li, Z. Liu, X. Zhang. Deep Crop Clustering: A deep unsupervised clustering approach by adopting nearest and farthest neighbors for crop mapping. ISPRS Jour. of Photogr. and Rem. Sens., 224 (2025). [Google Scholar]
- R. Fernandez-Escobedo, H. Cuevas-Vargas. The Digital Industrial Cluster in a post-pandemic era: Exploring its theoretical deployment and potential benefits. 10th International Conference on Information Technology and Quantitative Management, Procedia Computer Science, 221 (2023) [Google Scholar]
- A.M. Sodikov, D.K. Begimova. Assessment of the clustering potential of regional economy networks. J.: Scien. & Innov. Devel., 4 (2022). [Google Scholar]
- R.C. García, G. Galán, M. Martín. Optimizing spatial clustering for supply chain networks. J.: Comp. & Chem. Engin., Volume 201, October, 109251 (2025) [Google Scholar]
- A. Eynan, B. Mantin. Quality and pricing decisions under clustered targeting. Europ. Jour. of Oper. Res., online 3 October (2025). [Google Scholar]
- M.E. Porter. Location, competition, and economic development: Local clusters in a global economy. J.: Economic Development Quarterly, 14, 1 (2000). [Google Scholar]
- C. Ketels. Recent research on competitiveness and clusters: What are the implications for regional policy? Cambr. Jour. of Reg., E. con. & Soc., 6, 2 (2013) [Google Scholar]
- T. Andersson, S. Schwaag-Serger, J. Sörvik, E.W. Hansson. The Cluster Policies Whitebook. IKED, Malmö (2004). [Google Scholar]
- Ö. Sölvell. Clusters: Balancing Evolutionary and Constructive Forces. Ivory Tower Publishers, Stockholm (2008) [Google Scholar]
- T.L. Saaty. The Analytic Hierarchy Process. McGraw-Hill, New York (1980) [Google Scholar]
- B. Islamov, K. Shadmanov. Industrial clustering development in Uzbekistan: Challenges and prospects. // Central Asian Economic Review, 3, 2 (2021). [Google Scholar]
- K.Ruziev, P.Midmore. Connectedness and SME financing in transition economies: Evidence from Central Asia. Res. in Intern. Bus. & Fin., 35 (2015) [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.