Application of Social Network Analysis to Visualization and Description of Industrial Clusters: A Case of the Textile Industry

Journal of Risk and Financial Management. 2022. Vol. 15. No. 3. Article 129.

Sheresheva M. Y., Valitova L., Sharko E., Buzulukova E. V.

The paper discusses the issues of industrial clusters analysis. Initially, the authors explore theoretical approaches to understanding clusters phenomenon, their identification and analysis. Looking at industrial clusters as network structures connected by various forms of interaction between members, such as ownership linkages, transactions, the presence of common counterparts, participation in arbitration processes, the authors propose to visualize clusters using social network analysis metrics. This approach helps to address one of the main difficulties when contacting the members of industrial clusters, for a subsequent survey or in-depth interviewing. The analysis concludes with a discussion of the proposed method as a way to identify cluster members and determine the most significant ones that are the primary nodes of the network. These key members usually possess enough relevant information about the structure, coordination mechanisms, general strategy, and cluster management system. Therefore, it is possible to limit the list of interviewed respondents without substantial loss of empirical data quality. A case of the textile industry cluster presented in the paper confirms the applicability of social network analysis to the visualization and description of industrial clusters.

Keywords: Russia, social network analysis, inter-organizational networks, textile industry, industrial clusters