Research and Development (R&D) and innovation have a significant impact on the competitiveness of countries. Science and Technology Parks (STPs) are an important component of R&D and innovation ecosystems of countries and they aim to increase the university-industry collaboration. This study addresses the efficiency analysis of STPs in Turkey using Data Envelopment Analysis (DEA). For this purpose, an input-oriented DEA model is used to obtain efficiency scores of STPs and 5 of 22 STPs are

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... to be efficient. After that, to examine the strong and weak areas of STPs six additional Data Envelopment Analysis (DEA) models are considered. According to these models, STPs exhibits lower performance in the efficiency of revenue and patents. Finally, STPs are clustered based on efficiency scores as Marketers, Researchers and Low-performers using K-means clustering and we made suggestions for each cluster. The motivation of this study is contributing to policies for increasing the performance and the impact of the STPs in Turkey.