Author/Authors
pabuçcu, hakan bayburt üniversitesi - iktisadi idari bilimler fakültesi - işletme bölümü öğretim üyesi, Turkey , imamoğlu, ilyas kays bayburt üniversitesi - dış ticaret bölümü, turkey
Title Of Article
Determinants Of Innovation: A Cross-Country Data Analysis
شماره ركورد
36437
Abstract
In this study investigates, whether competitiveness, gross domestic product (GDP), labor market efficiency, patent applications and technology readiness level are the determinants of innovation by using regression analysis and the data belong to the countries examined in the global competitiveness report. In addition to regression analysis, by using the variables, that have a statistically significant relationship between innovation, it is constructed a neural network (NN) model. In both models, the results are consistent each other and NN model determined as the best to explain the ability of relationship between variables for innovation estimates. The relationship between innovation and other explanatory variable is statistically significant except patent application. The patent applications variable doesn’t provide an assumptions related with statistical methods. It excluded from the analysis for this reason. The relationship between variables found positive as expected. But the coefficient of GDP is very low near zero, so the effect is very weak as surprisingly.
From Page
110
NaturalLanguageKeyword
Innovation , regression analysis , artificial neural network
JournalTitle
Journal Of Economics and Administrative Sciences
To Page
129
JournalTitle
Journal Of Economics and Administrative Sciences
Link To Document