An Analysis of Regional Industries’ Cluster Mapping and Development Strategy
|Author||Jaegon Park, Changuk Byun, Sang-ho Lee||Date||2016.02.01||Page||18|
Regional industrial policies in Korea have been pursued based on clusters. Projects encompassing various programs such as establishment of innovative infrastructure, R&Ds and training of labor force have been operated. In addition, in terms of supporting projects, total periodic support has been provided. The government has operated selective industrial policies in a way that selects strategic industries and then focuses resources on the industries. In the course of operating the regional industrial policies, following issues were raised.
First, cluster-based policies and selective industrial policies are similar in that both policies target specific clusters and industries, but while selective industrial policies focus on the protection and the growth of specific industries, cluster-based policies put emphasis on the connection with related industries and formation of value chains. Industrial policies focus on the narrow scope of
industries, but it can be said that cluster-based policies have a wider area of support as the policies put emphasis on the creation of value chains’ front back related industries. Therefore it is required to shift from selective industrial policies to cluster-based policies.
Second, it is needed to identify and analyze clusters. Operating cluster-based policies, up to date specification degree (location index), concentration level (importance compared with that of the entire country), growth and productivity in the level of industries were used for the analysis. However, in order to identify clusters with geographical concentration of related industries, it is needed to include indices to assess correlations between industries.
Third, as correlations between industries were reviewed, networks of specific areas were analyzed as well. When targeting a specific area, there are advantages of being able to find out connections between industries in the specific area, but there are disadvantages of not being able to compare with other regions. In this sense, cluster identification methods that can compare various regions are needed.
To overcome this problem, first this study identifies and analyzes clusters from the viewpoint of geographical concentration of related industries. To this end, as indices of considering correlations between industries, input-output linkage, similarity of occupations and relations between locations of businesses and employees are explicitly included. Secondly, clusters distributed in regions were identified through mapping. Third, in the methods to identify clusters, this study attempted to identify clusters not at the regional level but compared various regions in the country. By doing so, this study is able to cross-correlate various regions. Fourth is about analyzing the impact of clusters on regional economies.
Clusters have positive effects from externality but also have negative effects caused by external diseconomy such as congestion costs. This study analyzes this and suggests implications on cluster-based regional industrial policies.