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  Citation Number 10
 Views 75
 Downloands 20
VERİ ZARFLAMA ANALİZİ TEMELLİ YAPAY SİNİR AĞLARI VE LOJİSTİK REGRESYON ANALİZİ İLE TEKNOLOJİ GELİŞTİRME BÖLGELERİNİN ETKİNLİKLERİNİN TAHMİNLENMESİ
2019
Journal:  
Hacettepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi
Author:  
Abstract:

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%.

Keywords:

Analysis of data deployment and logistical regression analysis assessment of the effects of the areas of technology development
2019
Author:  
Abstract:

Technology development regions are the places where technological knowledge is produced and commercialized by sharing the experiences of university and industry 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 performance 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 shown 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%.

Keywords:

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Hacettepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi

Field :   Sosyal, Beşeri ve İdari Bilimler

Journal Type :   Uluslararası

Metrics
Article : 957
Cite : 5.266
Hacettepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi