Identification and Visualization of Clusters Using Network Theory Methods: The Case of the Greek Production System

The interest in clusters in the economy and regional space, which has persisted for nearly three decades, has reignited the understanding of the economy as a system of interdependencies between industries. Although the concept of clusters can be traced back to contributions dating from the early 20th century, they have become a central focus of regional development policies in recent decades, as they have been linked to enhancements of innovation, the knowledge economy, and ultimately, territorial competitiveness. Arguably, the most effective and comprehensive way to present the systemic nature of the economy is through input–output tables. The main feature of these tables, on which this work is based, is that they describe the relationships and flows between industries (or products) during the production process. These fundamental relationships among the industries in the production system are depicted in the inter-industry (and intra-industry) transaction matrix of an economy’s input–output tables. To analyze these relationships, we use network theory, in the context of which the transaction matrix can be seen as the adjacency matrix of a directed, weighted graph (or network) with loops. In this study, clusters are identified for the case of Greece, using two different approaches based on the modularity of the network, utilizing the 2010 input–output tables for this country. As a result, five clusters of industries that structure the country’s production system across 62 industries are identified, which are also presented through graphical visualizations.