Home  Journals  Regional Economics: Theory and Practice  4(487) - 2021 April

A conceptual approach to assessing the cluster potential of regions based on the use of intelligent information systems

Vol. 19, Iss. 4, APRIL 2021

Article PDF Version

Received: 11 March 2021

Received in revised form: 16 March 2021

Accepted: 19 March 2021

Available online: 15 April 2021

Subject Heading: SUSTAINABLE DEVELOPMENT OF REGIONS

JEL Classification: R12, R58

Pages: 693–717

https://doi.org/10.24891/re.19.4.693

Subject. This article discusses the role of intelligent information systems in assessing the cluster potential of regions.
Objectives. The article aims to develop methodological tools to assess the cluster potential of regions applying intelligent information systems, and test them using the Siberian Federal District regions as a case study.
Methods. For the study, we used econometric and expert assessment methods.
Results. The article proposes a stepwise algorithm for assessing the cluster potential of regions, taking into account the appropriate methodological and mathematical apparatus. It presents a cumulative indicator of the development potential of cluster groups.
Conclusions. The proposed methodological, and information and analysis tools can serve as a basis for decision-making on cluster policy development at the regional level.

Keywords: regional economics, cluster and network associations, information and analysis system, evaluation indicators

References:

1. Götz M. The Industry 4.0 Induced Agility and New Skills in Clusters. Foresight and STI Governance, 2019, vol. 13, no. 2, pp. 72–83. URL: Link
2. Terstriep J., Lüthje C. Innovation, Knowledge and Relations – On the Role of Clusters for Firms' Innovativeness. European Planning Studies, 2018, vol. 26, iss. 11 pp. 2167–2199. URL: Link
3. Perényi Á. Diagnosing Cluster Competitiveness Using Firm-Level Data in the Profit–Growth Nexus Framework. Acta Oeconomica, 2016, vol. 66, iss. 3, pp. 439–463. URL: Link
4. Njøs R., Jakobsen S.-E. Cluster Policy and Regional Development: Scale, Scope and Renewal. Regional Studies, Regional Science, 2016, vol. 3, iss. 1, pp. 146–169. URL: Link
5. Fowler C.S., Kleit R.G. The Effects of Industrial Clusters on the Poverty Rate. Economic Geography, 2014, vol. 90, iss. 2, pp. 129–154. URL: Link
6. Huseynova K. Quantitative and Qualitative Assessment of the Region's Competitiveness. International Journal of Scientific & Engineering Research, 2016, vol. 7, iss. 5, pp. 736–738. URL: Link
7. Porter M.E. Konkurentsiya [On Competition]. Moscow, Vil'yams Publ., 2005, 608 p.
8. Pechatkin V.V. [A method of assessment and analysis of the clustering potential of regional economy]. Ekonomicheskii analiz: teoriya i praktika = Economic Analysis: Theory and Practice, 2010, vol. 9, iss. 28, pp. 42–48. URL: Link (In Russ.)
9. Pospelova I.N. [Evaluation of clustering potential of processing industries in the Altai region]. Vestnik Altaiskogo gosudarstvennogo agrarnogo universiteta = Bulletin of Altai State Agricultural University, 2016, no. 11, pp. 184–188. URL: Link (In Russ.)
10. Bachinina Yu.P., Andronova I.V. Klasternyi podkhod v obespechenii konkurentosposobnosti regiona: monografiya [Cluster approach to ensure the region's competitiveness: a monograph]. Tyumen, Industrial University of Tyumen Publ., 2010, 120 p.
11. Kitova O.V., Kolmakov I.B., Dyakonova L.P. et al. Hybrid Intelligent System of Forecasting of the Socio-Economic Development of the Country. International Journal of Applied Business and Economic Research, 2016, vol. 14, iss. 9, pp. 5755–5756. URL: Link
12. Beilin I.L. [Digital econometric modeling of gross regional product and manufacturing industries of the region with a high value of petrochemical cluster]. Regional'naya ekonomika: teoriya i praktika = Regional Economics: Theory and Practice, 2019, vol. 17, iss. 8, pp. 1490–1510. (In Russ.) URL: Link
13. Hu Y., Chan A.P.C., Le Y. Pragmatic Framework of Programme Organizational Capability for Delivering Megaprojects at Design and Construction Phases: A Chinese Client Perspective. The Engineering Project Organization Journal, 2015, vol. 5, iss. 2–3, pp. 49–62. URL: Link
14. Evteeva E.V. [Intelligent information management and data collection system of the company]. Vestnik Volzhskogo universiteta im. V.N. Tatishcheva = Vestnik of Volzhsky University named after V.N. Tatishev, 2015, no. 1, pp. 24–30. URL: Link (In Russ.)
15. Balasankar V., Penumatsa S.V., Terlapu P.R.V. Intelligent Socio-Economic Status Prediction System Using Machine Learning Models on Rajahmundry A.P., SES Dataset. Indian Journal of Science and Technology, 2020, vol. 13, iss. 37, pp. 3820–3842. URL: Link
16. Чорноус Г.А. Агентна модель інтелектуальної інформаційної системи управління в економіці // Вісник Київського національного університету імені Тараса Шевченка. Економіка. 2016. № 178. С. 41–47. URL: Link
17. Pogorelov N.E., Reizenbuk K.E., Pimonov A.G. [Intelligent information system for the analysis and prediction of stock's quotes]. Vestnik Kuzbasskogo gosudarstvennogo tekhnicheskogo universiteta = Bulletin of Kuzbass State Technical University, 2012, no. 6, pp. 118–122. URL: Link (In Russ.)
18. Alzoubi H.M. The Role of Intelligent Information System in e-Supply Chain Management Performance. International Journal of Multidisciplinary Thought, 2018, vol. 7, iss. 2, pp. 363–370. URL: Link

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