Defining Successful Regional Innovation Clusters

To compete in the global world market, regions must continue to evolve and better understand how best practices support their regional industries, including defining the benchmarks of a successful industry cluster. In a recent academic article from Harvard researchers, Mercedes Delgado, Michael Porter, and Scott Stern unveiled a new algorithm tool that generates and assesses sets of cluster definitions. The new algorithm will be integrated into the U.S. Cluster Mapping Project to help researchers and policymakers cultivate more successful regional clusters.

Funded by a grant from the Economic Development Administration, authors announced the tool – a new clustering algorithm that generates and assesses sets of cluster definitions – in a new research study that includes details on the tool, the findings of study, and recommendations for the tools use.

In Defining Clusters of Related Industries, the authors propose a new set of benchmark cluster definitions that incorporates measures of inter-industry linkages based on co-location patterns, input-output links, and similarities in labor occupations. Using a multiple step process, the new clustering algorithm provides composite scores that assess the quality of each set of cluster definitions.

The algorithm also is intended to capture the inter-industry interdependences of regional clusters. The algorithm was implemented using six-digit NAICS codes and U.S. industry data from 2009. According to the study, the new algorithm was able to outperform existing methods of evaluating inter-industry linkages to the three-digit NAICS level.

The results of the study include the development of a benchmark cluster database (BCD) that includes 51 regional clusters from across the country.  The BCD will be integrated into the U.S. Cluster Mapping Project. Read the paper…