ESTIMATION OF THE EFFICIENCY OF TECHNOLOGY DEVELOPMENT REGIONS BY ARTIFICIAL NEURAL NETWORKS AND LOGISTICS REGRESSION ANALYSIS ON THE BASIS OF DATA ENVELOPMENT ANALYSIS

Technology development regions are the places where technological knowledge is produced and commercialized by sharing the experiences of university and industry with together. Technological development regions or technoparks those are at the center of technology policies of the countries are a matter which is important for our country as it is all over the world and continuous investments are made to establish new technoparks. In this study, it is aimed to develop two different models that predict the efficiency of the technology development zones and to compare the predictive performances of these models using Artificial Neural Networks-Data Envelopment Analysis and Logistic Regression Analysis-Data Envelopment Analysis models. Based on the input variables, the future performance of a new technology development zone is estimated. The results of the analysis have showed that Artificial Neural Networks classify the efficient and non-efficient technology development regions as 100% correctly while the classification performance of the Logistic Regression Analysis is 89.7%