The determinants of innovation in companies within the framework of BEEPS 2012 - 2014 survey data
Is this your thesis?
This record came from a bulk archive import. If it’s yours, link it to your profile.
Abstract (EN)
Within the framework of innovation concept, this study offers an in-depth investigation of the determinants that invoke the private companies to innovate in the modern day that gains importance each day at both state and company levels. This study is based on the BEEPS Data for 2012-2014 period which covers 15,883 companies from 30 countries of Eastern Europe and Central Asia including Turkey, conducted by the World Bank and European Reconstruction and Development Bank. Within this framework, first, it looks at the theorists of innovation literature and the empirical studies so far. Second, the determinants of innovation are reviewed in light of the current BEEPS Survey Dataset by means of a logistic regression analysis. Albenia, Armenia, Azerbaijan, Belarus, Bosnia and Herzegovina, Bulgaria, Croatia, Czech Republic, Estonia, Macedonia, Georgia, Hungary, Kazakhstan, Kosovo, Kyrgyz Republic, Latvia, Lithuania, Moldova, Mongolia, Montenegro, Poland, Romania, Russia, Serbia, Slovak Republic, Slovenia, Tajikistan, Turkey, Ukraine, and Uzbekistan were chosen as the ethnographic research sites. Results indicate that the determinants of innovation, though vary slightly at different types of innovation, are shown as the size of the establishment, the top manager's experience, international certification, subsidies, consultant, training programmes, loans, licensed technologies obtained from foreign companies, R&D spending to name a few. Keywords: Innovation, The Determinants of Innovation, R&D, Logistic Regression Analysis
Author
Yasemin Şükran Uçar
Institution
How to Cite
Yasemin Şükran Uçar (Master Thesis). The determinants of innovation in companies within the framework of BEEPS 2012 - 2014 survey data, 2015, TOBB Economics and Technology University.
License
Tüm Hakları Saklıdır
This work is shared under the specified license terms.
More theses from TOBB Economics and Technology University
- Extracting the features of drilling foams with image processing techniques and data analysis using artificial neural networks(2007)
- Automatic web services execution engine with qos support(2007)
- Usage of information theory to control the qos and energy consumption for wireless sensor networks(2007)
- Low power techniques for superscalar microprocessors(2007)
- Hardware design for predicting widths of values produced in microprocessors(2007)
- Soft error detection by using tag comperator in microprocessors(2007)
