TY - JOUR
T1 - Developing Methods to Assess and Monitor Cluster Structures
T2 - The Case of Digital Clusters
AU - Kudryavtseva, Tatiana
AU - Kulagina, Natalia
AU - Lysenko, Alexandra
AU - Berawi, Mohammed Ali
AU - Skhvediani, Angi
N1 - Funding Information:
This research was supported by the Academic Excellence Project 5-100 proposed by Peter the Great St. Petersburg Polytechnic University.
Publisher Copyright:
© 2020
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
KW - Cluster
KW - Innovation
KW - IT cluster
KW - Regional innovation system
KW - Russia
UR - http://www.scopus.com/inward/record.url?scp=85096341217&partnerID=8YFLogxK
U2 - 10.14716/ijtech.v11i4.4191
DO - 10.14716/ijtech.v11i4.4191
M3 - Article
AN - SCOPUS:85096341217
SN - 2086-9614
VL - 11
SP - 667
EP - 676
JO - International Journal of Technology
JF - International Journal of Technology
IS - 4
ER -