Measuring regional innovation performance in turkey
Measuring regional innovation performance in turkey
dc.contributor.advisor | Baycan, Tüzin | |
dc.contributor.author | Özen, Berna Sezen | |
dc.contributor.authorID | 502122803 | |
dc.contributor.department | Urban and Regional Planning | |
dc.date.accessioned | 2024-02-05T08:59:55Z | |
dc.date.available | 2024-02-05T08:59:55Z | |
dc.date.issued | 2022-12-23 | |
dc.description | Thesis(Ph.D.) -- Istanbul Technical University, Graduate School, 2022 | |
dc.description.abstract | Innovation Systems is an effective tool for examining the national and regional economies and policy-making. Although there are some studies on regional innovation measurement for Turkey, there has not been any study found focusing on the transitions through different time periods at the NUTS-3 level. The purpose of the thesis is (i) to evaluate the general status of the innovation performance of Turkey in international and national scales, (ii) to focus mainly on measuring and mapping regional innovation performances in Turkey by providing a temporal dynamic analysis of transitions of the regions (at NUTS-3 level) from one state of innovative performance to another over time from 2000 to 2017 based on the EU-defined performance grouping as innovation leaders, strong innovators, moderate innovators and modest innovators, (iii) to demonstrate in which issues the similarities and/or differences of the innovation performances occur within the regions and at interregional levels, (iv) to determine the factors related to these innovation performances and (v) to create related policies and strategies for establishing and managing an effective innovation system. Focusing on the intellectual assets, Markov Chains and Shorrocks Trace indices have revealed that there are regional disparities (between (i) regions located in the east and west of the country, (ii) metropolitan and non-metropolitan regions, (iii) high-developed and relatively less-developed regions). Five different panel data models were performed to identify the determinants of the innovation performances of the innovation leaders. These econometric models revealed that different innovation indicators may differently affect the different types of intellectual assets. | |
dc.description.degree | Ph. D. | |
dc.identifier.uri | http://hdl.handle.net/11527/24490 | |
dc.language.iso | en_US | |
dc.publisher | Graduate School | |
dc.sdg.type | Goal 9: Industry, Innovation and Infrastructure | |
dc.subject | regional innovation systems | |
dc.subject | bölgesel yenilik sistemleri | |
dc.subject | Markov chain | |
dc.subject | Markov zinciri | |
dc.title | Measuring regional innovation performance in turkey | |
dc.title.alternative | Türkiye'nin bölgesel inovasyon performansinin ölçülmesi | |
dc.type | Doctoral Thesis |