Specialization of regional clusters and innovative behavior: a case study

Abstract

PurposeThe purpose of this paper is to study the specialization of regional clusters and their innovative behaviour, in a particular Portuguese region.Design/methodology/approachA regional case study (Region Centro of Portugal) is used, employing secondary and primary data in order to measure specialized critical mass of a region's clusters and analyze their innovative behavior following the European Cluster Observatory (ECO) methodology.FindingsCombining the different nature of data (primary and secondary), this paper identifies the specialized critical mass of a region's cluster, makes statements about the role of clusters in a regional context, and demonstrates how a regional clustering approach is important to understanding the innovative process. Based on an empirical survey, three types of clusters were found: basic, intermediate and advanced.Research limitations/implicationsAmong the research limitations is the undersized sample of primary data which does not allow deep findings to be drawn about the innovative behavior of the clusters in a general way. Therefore, future research should focus on this area, extending the empirical analysis presented here to add qualitative indicators on innovative behaviour, to calculate the impact of absorptive capacity in the case of regional clusters.Practical implicationsThis study provides a consistent methodology of cluster operation which could be useful for undertaking comparative work within regions' clusters across different sectors and countries, to reinforce the importance of the current discussion of policy clusters, and to identify specific requirements and needs of each cluster in order to improve the quality of decision making and to draw some policy implications.Originality/valueThis paper is the first to measure specialized critical mass of a region's clusters at the enterprise level and to explain cluster innovative behaviour, combining primary and secondary, based on ECO criteria. Furthermore, it provides initial empirical evidence and an amount of significant findings to support managers and policymakers in the understanding of regional and innovation clustering of small to medium‐sized enterprises.