State supports for clustering in Turkey: A proposed clustering model for the TR82 region

Clustering is a topic that has been adopted as a very successful approach in national competitiveness and development policies and has recently attracted the attention of researchers. In this context, in this thesis study, it has been revealed as a result of the researches that the clusters formed in certain geographical regions provide competitive advantage in sectors where their unique aspects are revealed. Therefore, it is thought that this thesis study may be useful in terms of the implementation and adoption of the clustering approach in regions with sectoral concentration. Clustering structures, which are among the activities to be carried out by governments as a result of changes in technological developments and globalization, are used as one of the tools for regional development and global competition. Recently, policies have been established by governments in order for cluster structures to achieve successful results and sustainability. In this context, in Turkey, as stated in the study, support is still provided for the cluster structure and the actors in the cluster in the past and today. In this study, an exemplary clustering model proposal has been tried to be created over the sectors in the manufacturing industry in TR82 Region. First, clustering potential in four sectors among the manufacturing sectors was identified by using the three-star analysis method. Then, the current situation of these four sectors in TR82 Region was analyzed by comparing with other level 2 regions. The distribution of sectors by provinces and districts was examined and the concentration of sectors in a particular district or region, competitiveness and innovation capacity in the sector were examined by making use of the District Analyses study, which forms the basis for the 2014 - 2023 Regional Plan. As a result of the analysis, two sub-clusters were identified and a sample clustering model proposal was created on the TR82 Region, taking into account the effects of enterprise-specific information and government supports on cluster formation