Developing Methods to Assess and Monitor Cluster Structures: The Case of Digital Clusters

Tatiana Kudryavtseva, Natalia Kulagina, Alexandra Lysenko, Mohammed Ali Berawi, Angi Skhvediani

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

The purpose of this work is to develop a methodology to assess and monitor cluster structures. The authors’ proposed method assesses the level of cluster structure development by considering cluster transformation analysis in the information and communication sectors of the regional economy, prerequisites for cluster formation, and the current level of digital cluster development in the region. To evaluate the prerequisites of digital economy cluster formation, an integral indicator is calculated and a multi-parameter approach is used to evaluate cluster effectiveness. The integral indicator includes 17 values calculated using the scorecard evaluation method. To make conclusions about the stages of IT cluster development, the authors provide the scale used to interpret integral indicator values. This scale classifies cluster development using four levels: beginner, elementary, intermediate, and advanced. A comparative analysis of IT cluster development in the Kaluga and Bryansk regions of the Russia reveals that IT clusters in Kaluga are at an advanced level of development due to its highly developed infrastructure and work flow organization, while IT clusters in Bryansk are at the beginner stage. This shows that Kaluga has a more effective industrial policy for clusters. The proposed methodology allows researchers to compare clusters from different regions and monitor their development.

Original languageEnglish
Pages (from-to)667-676
Number of pages10
JournalInternational Journal of Technology
Volume11
Issue number4
DOIs
Publication statusPublished - 2020

Keywords

  • Cluster
  • Innovation
  • IT cluster
  • Regional innovation system
  • Russia

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