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Bilgi Alanı, İlişkililik ve Karmaşıklık: Türkiye İçin Bölgesel Bir Analiz

Year 2021, Volume: 7 Issue: 2, 123 - 136, 30.11.2021
https://doi.org/10.51803/yssr.869824

Abstract

Bölgelerin güçlü yönlerine dayalı bölgesel kalkınma politikaları, yenilikçi ve rekabetçi büyüme için anahtar niteliğindedir. Sürdürülebilir büyüme için her bölge kendi öz bilgi havuzu ve kabiliyeti üzerinde temellendirilmiş büyüme yollarını keşfetmelidir. Türkiye’deki ekonomik faaliyetin bölgesel kümelenmesi ve sektörlerin teknolojik dağılımları konularına odaklanan çalışmalar bulunmasına rağmen, bölgelerin güçlü yönlerine dayalı yeni teknolojileri çekme potansiyelleri konusunda kısıtlı bilgi bulunmaktadır. Bu makalenin üç hedefi vardır: İlk hedef Türkiye’nin 2010 ve 2017 yıllarına ait bilgi alanının (teknolojiler arasındaki ilişkililik) haritasını çizmektir. Makalenin ikinci hedefi, Türkiye’nin 2010 ve 2017 yıllarındaki ilişkiliik (dallanma fırsatları) ve bilgi karmaşıklığını anlamaktır. Üçüncü hedef, Türkiye’nin NUTS3 bölgeleri düzeyinde patent başvuruları ile ölçülen bölgesel yenilikçilik ile ilişkililik ve bilgi karmaşıklığı arasındaki ilişkiyi göstermektir. Çalışmada, Avrupa Patent Ofisi (EPO) REGPAT Veritabanı’ndan Ocak 2020 tarihinde erişilmiş veriler kullanılmaktadır. Türkiye’nin bilgi alanının haritasını çizebilmek için, patent sınıfları arasındaki teknolojik ilişkililik kullanılmıştır. Bilgi alanı, boğumların teknolojik kategorileri, çizgilerin ise her bir çift teknoloji arasındaki bağı temsil ettiği bir ağdır. Bölgelerin ilişkililikleri, ilişkililik yoğunluğu değişkeni ile ölçülmektedir. Bilgi karmaşıklığı ise bilgi karmaşıklığı endeksi ile ölçülmüştür. Patent başvurularının bölgelerin ilişkililik yoğunluğu ve bilgi karmaşıklığı ile korelasyonunu anlamak için regresyon analizi kullanılmıştır. Kontrol değişkeni olarak regresyon modeli, her şehrin göreceli teknolojik üstünlüğe sahip olduğu teknoloji sınıflarının sayısını ölçen çeşitlenme değişkenini kullanmaktadır. Analizler, Türkiye’deki bilgi alanının 2010 ve 2017 arasında daha yoğun bir hale geldiğini ve dallanma fırsatları ve bilgi karmaşıklığı bakımından bölgeler arasında farklılıklar olduğunu göstermektedir. Çeşitlenme ve ilişkililik yoğunluğu patent başvurularını ile pozitif yönde bir korelasyona sahipken, karmaşıklığın bölgesel yenilikçilikle ilişkili olmadığı görülmüştür.

References

  • Asheim, B. T., Boschma, R., & Cooke, P. (2011). Constructing regional advantage: Platform policies based on related variety and differentiated knowledge bases. Regional studies, 45(7), 893-904. doi:10.1080/00343404.2010.543126
  • Balland, P. A. (2017). Economic Geography in R: Introduction to the EconGeo Package. Papers in Evolutionary Economic Geography, 17(09), 1-75.
  • Balland, P. A., & Rigby, D. (2017). The geography of complex knowledge. Economic Geography, 93(1), 1-23. doi:10.1080/00130095.2016.1205947
  • Balland, P. A., Boschma, R., Crespo, J., & Rigby, D. (2019). Smart specialization policy in the European Union: relatedness, knowledge complexity and regional diversification. Regional Studies, 53(9), 1252-1268. doi:10.1080/00343404.2018.1437900
  • Balland, P. A., Rigby, D., & Boschma, R. (2015). The technological resilience of US cities. Cambridge Journal of Regions, Economy and Society, 8(2), 167-184.
  • Boschma, R. (2014). Constructing regional advantage and smart specialisation: Comparison of two European policy concepts. Italian Journal of Regional Science (Scienze Regionali), 13(1), 51-68.
  • Boschma, R. A., & Frenken, K. (2006). Why is economic geography not an evolutionary science? Towards an evolutionary economic geography. Journal of economic geography, 6(3), 273-302.
  • Çelik, N., Akgüngör, S., & Kumral, N. (2019). An assessment of the technology level and knowledge intensity of regions in Turkey. European Planning Studies, 27(5), 952-973. doi:10.1080/09654313.2019.1579301
  • Cooke, P., Uranga, M. G., & Etxebarria, G. (1997). Regional innovation systems: Institutional and organisational dimensions. Research policy, 26(4-5), 475-491. doi:10.1016/S0048-7333(97)00025-5
  • European Commission. (2020). Smart Specialization Platform. Retrieved from https://s3platform.jrc.ec.europa.eu/,
  • Freeman, C. (1995). The ‘national system of innovation’ in historical perspective. Cambridge Journal of Economics, 19(1), 5-24.
  • Frenken, K., & Boschma, R. A. (2007). A theoretical framework for evolutionary economic geography: Industrial dynamics and urban growth as a branching process. Journal of economic geography, 7(5), 635-649.
  • Frenken, K., Van Oort, F., & Verburg, T. (2007). Related variety, unrelated variety and regional economic growth. Regional studies, 41(5), 685-697. doi:10.1080/00343400601120296
  • Gezici, F., Yazgı-Walsh, B., & Kacar, S. (2017). Regional and structural analysis of the manufacturing industry in Turkey. Annals of Regional Science, 1(59), 209–230. doi:10.1007/s00168-017-0827-4
  • Gülcan, Y., Akgüngör, S., & Kuştepeli, Y. (2011). Knowledge generation and innovativeness in Turkish textile industry: Comparison of Istanbul and Denizli. European Planning Studies, 19(7), 1229-1243. doi:10.1080/09654313.2011.573134
  • Hidalgo, C. A., & Hausmann, R. (2009). The building blocks of economic complexity. Proceedings of the National Academy of Sciences, 106(26), 10570-10575.
  • Hidalgo, C., Balland, P. A., Boschma, R., Delgado, M., Feldman, M., Frenken, K., . . . Zho, S. (2018). The principle of relatedness. In A. J. Morales, et al. (EDS), Unifying Themes in Complex Systems IX (pp. 451-457). Cham: Springer Nature.
  • Jacobs, J. (1969). The Economy of Cities. New York: Vintage Books.
  • James, G., Witten, D., Hastie, T., & Tibshirani, R. (2017). An Introduction to Statistical Learning with Applications in R (8 ed.). Springer Texts in Statistics.
  • Kaygalak, İ. (2013). Türkiye sanayi coğrafyasında endüstriyel kümelenme ve bölgesel yoğunlaşma eğilimi. Beşeri Coğrafya Dergisi, 1(1), 67-81.
  • Kaygalak, İ., & Reid, N. (2016). The geographical evolution of manufacturing and industrial policies in Turkey. Applied Geography, 70, 37-48. doi:10.1016/j.apgeog.2016.01.001
  • Kuştepeli, Y., Gülcan, Y., & Akgüngör, S. (2013). The innovativeness of the Turkish textile industry within similar knowledge bases across different regional innovation systems. European Urban and Regional Studies, 20(2), 227-242.
  • Lundvall, B. Ä., & Johnson, B. (1994). The learning economy. Journal of industry Studies, 1(2), 23-42. doi:10.1080/13662719400000002
  • Marshall, A. (1890). Principles of Economics. 1 (First ed.). London: Macmillan.
  • Martin, R., & Sunley, P. (2015). On the notion of regional economic resilience: conceptualization and explanation. Journal of Economic Geography, 15(1), 1-42.
  • Maskell, P., & Malmberg, A. (1999). Localised learning and industrial competitiveness. Cambridge journal of economics, 23(2), 167-185.
  • Morgan, K. (1997). The learning region: institutions, innovation and regional renewal. Regional Studies, 31(5), 491-503.
  • Neffke, F., Henning, M., & Boschma, R. (2011). How do regions diversify over time? Industry relatedness and the development of new growth paths in regions. Economic geography, 87(3), 237-265.
  • Nelson, R. R., & Winter., S. G. (1982). An evolutionary theory of economic change. Cambridge, Mass.: Harvard University Press.
  • Rigby, D. L., Roesler, C., Kogler, D., Boschma, R., & Balland, P. A. (2019). Do EU regions benefit from smart specialization? Utrecht University Papers in Evolutionary Economic Geography, 19.
  • Riveros, J. M. (2020, May 14). Ramsey RESET Test on Panel Data using Stata. Retrieved from M&S Research Hub.
  • Romer, P. M. (1990). Endogenous technological change. Journal of political Economy, 98(5, Part 2), S71-S102.
  • Schmoch, U. (2008). Concept of a technology classification for country comparisons. Final report to the world intellectual property organisation (WIPO). WIPO.
  • Schumpeter, J. A. (1939). Business cycles: A theoretical, historical, and statistical analysis of the capitalist process (Vol. 1). New York and London: McGraw-Hill Book Company Inc.
  • Schumpeter, J. A. (1942). Capitalism, Socialism and Democracy. New York: Harper & Row.
  • Solow, R. M. (1956). A contribution to the theory of economic growth. The quarterly journal of economics, 70(1), 65-94.
  • Whittle, A., & Kogler, D. F. (2019). Related to what? Reviewing the literature on technological relatedness: Where we are now and where can we go? Papers in Regional Science, 99(1), 97-113.

Knowledge Space, Relatedness and Complexity: A Regional Analysis in Turkey

Year 2021, Volume: 7 Issue: 2, 123 - 136, 30.11.2021
https://doi.org/10.51803/yssr.869824

Abstract

Regional development policies based on regions’ core strengths is key for innovative and competitive growth. For sustainable growth, each region would discover their own growth paths grounded on their core knowledge base and capabilities. Although there are studies that focus on regional clustering of economic activity and technological dispersion of sectors in Turkey, little is known related to the regions’ potential to attract new technologies based on their core strenghts. There are three objectives of the paper: The first objective is to map knowledge space (relatedness between technologies) in Turkey for 2010 and 2017. The second objective of the paper is to understand relatedness (branching opportunities) and knowledge complexity in Turkey’s regions for 2010 and 2017. The third objective is to demonstrate the relationship of regional innovativeness as measured by patent applications with relatedness and knowledge complexity across Turkey’s NUTS3 regions. The study uses data from the European Patent Office (EPO) REGPAT Database (downloaded in January 2020). In order to map Turkey’s knowledge space, we use technological relatedness between patent classes. The knowledge space is a network where nodes represent technological categories and lines represent links between each pair of technology. Relatedness of the regions is operationalized by relatedness density. Knowledge complexity is operationalized by knowledge complexity index. We use regression analysis to understand the correlation of patent applications with regions’ relatedness density and knowledge complexity. As a control variable, the regression model uses diversity variable that is operationalized by the number of technological classes in which each city has relative technological advantage. The analysis demonstrates that knowledge space in Turkey became denser between 2010 and 2017 and there are variations across regions with respect to branching opportunities and knowledge complexity. Diversity and relatedness density are positively correlated with patent applications while complexity does not have a correlation with regional innovativeness.

References

  • Asheim, B. T., Boschma, R., & Cooke, P. (2011). Constructing regional advantage: Platform policies based on related variety and differentiated knowledge bases. Regional studies, 45(7), 893-904. doi:10.1080/00343404.2010.543126
  • Balland, P. A. (2017). Economic Geography in R: Introduction to the EconGeo Package. Papers in Evolutionary Economic Geography, 17(09), 1-75.
  • Balland, P. A., & Rigby, D. (2017). The geography of complex knowledge. Economic Geography, 93(1), 1-23. doi:10.1080/00130095.2016.1205947
  • Balland, P. A., Boschma, R., Crespo, J., & Rigby, D. (2019). Smart specialization policy in the European Union: relatedness, knowledge complexity and regional diversification. Regional Studies, 53(9), 1252-1268. doi:10.1080/00343404.2018.1437900
  • Balland, P. A., Rigby, D., & Boschma, R. (2015). The technological resilience of US cities. Cambridge Journal of Regions, Economy and Society, 8(2), 167-184.
  • Boschma, R. (2014). Constructing regional advantage and smart specialisation: Comparison of two European policy concepts. Italian Journal of Regional Science (Scienze Regionali), 13(1), 51-68.
  • Boschma, R. A., & Frenken, K. (2006). Why is economic geography not an evolutionary science? Towards an evolutionary economic geography. Journal of economic geography, 6(3), 273-302.
  • Çelik, N., Akgüngör, S., & Kumral, N. (2019). An assessment of the technology level and knowledge intensity of regions in Turkey. European Planning Studies, 27(5), 952-973. doi:10.1080/09654313.2019.1579301
  • Cooke, P., Uranga, M. G., & Etxebarria, G. (1997). Regional innovation systems: Institutional and organisational dimensions. Research policy, 26(4-5), 475-491. doi:10.1016/S0048-7333(97)00025-5
  • European Commission. (2020). Smart Specialization Platform. Retrieved from https://s3platform.jrc.ec.europa.eu/,
  • Freeman, C. (1995). The ‘national system of innovation’ in historical perspective. Cambridge Journal of Economics, 19(1), 5-24.
  • Frenken, K., & Boschma, R. A. (2007). A theoretical framework for evolutionary economic geography: Industrial dynamics and urban growth as a branching process. Journal of economic geography, 7(5), 635-649.
  • Frenken, K., Van Oort, F., & Verburg, T. (2007). Related variety, unrelated variety and regional economic growth. Regional studies, 41(5), 685-697. doi:10.1080/00343400601120296
  • Gezici, F., Yazgı-Walsh, B., & Kacar, S. (2017). Regional and structural analysis of the manufacturing industry in Turkey. Annals of Regional Science, 1(59), 209–230. doi:10.1007/s00168-017-0827-4
  • Gülcan, Y., Akgüngör, S., & Kuştepeli, Y. (2011). Knowledge generation and innovativeness in Turkish textile industry: Comparison of Istanbul and Denizli. European Planning Studies, 19(7), 1229-1243. doi:10.1080/09654313.2011.573134
  • Hidalgo, C. A., & Hausmann, R. (2009). The building blocks of economic complexity. Proceedings of the National Academy of Sciences, 106(26), 10570-10575.
  • Hidalgo, C., Balland, P. A., Boschma, R., Delgado, M., Feldman, M., Frenken, K., . . . Zho, S. (2018). The principle of relatedness. In A. J. Morales, et al. (EDS), Unifying Themes in Complex Systems IX (pp. 451-457). Cham: Springer Nature.
  • Jacobs, J. (1969). The Economy of Cities. New York: Vintage Books.
  • James, G., Witten, D., Hastie, T., & Tibshirani, R. (2017). An Introduction to Statistical Learning with Applications in R (8 ed.). Springer Texts in Statistics.
  • Kaygalak, İ. (2013). Türkiye sanayi coğrafyasında endüstriyel kümelenme ve bölgesel yoğunlaşma eğilimi. Beşeri Coğrafya Dergisi, 1(1), 67-81.
  • Kaygalak, İ., & Reid, N. (2016). The geographical evolution of manufacturing and industrial policies in Turkey. Applied Geography, 70, 37-48. doi:10.1016/j.apgeog.2016.01.001
  • Kuştepeli, Y., Gülcan, Y., & Akgüngör, S. (2013). The innovativeness of the Turkish textile industry within similar knowledge bases across different regional innovation systems. European Urban and Regional Studies, 20(2), 227-242.
  • Lundvall, B. Ä., & Johnson, B. (1994). The learning economy. Journal of industry Studies, 1(2), 23-42. doi:10.1080/13662719400000002
  • Marshall, A. (1890). Principles of Economics. 1 (First ed.). London: Macmillan.
  • Martin, R., & Sunley, P. (2015). On the notion of regional economic resilience: conceptualization and explanation. Journal of Economic Geography, 15(1), 1-42.
  • Maskell, P., & Malmberg, A. (1999). Localised learning and industrial competitiveness. Cambridge journal of economics, 23(2), 167-185.
  • Morgan, K. (1997). The learning region: institutions, innovation and regional renewal. Regional Studies, 31(5), 491-503.
  • Neffke, F., Henning, M., & Boschma, R. (2011). How do regions diversify over time? Industry relatedness and the development of new growth paths in regions. Economic geography, 87(3), 237-265.
  • Nelson, R. R., & Winter., S. G. (1982). An evolutionary theory of economic change. Cambridge, Mass.: Harvard University Press.
  • Rigby, D. L., Roesler, C., Kogler, D., Boschma, R., & Balland, P. A. (2019). Do EU regions benefit from smart specialization? Utrecht University Papers in Evolutionary Economic Geography, 19.
  • Riveros, J. M. (2020, May 14). Ramsey RESET Test on Panel Data using Stata. Retrieved from M&S Research Hub.
  • Romer, P. M. (1990). Endogenous technological change. Journal of political Economy, 98(5, Part 2), S71-S102.
  • Schmoch, U. (2008). Concept of a technology classification for country comparisons. Final report to the world intellectual property organisation (WIPO). WIPO.
  • Schumpeter, J. A. (1939). Business cycles: A theoretical, historical, and statistical analysis of the capitalist process (Vol. 1). New York and London: McGraw-Hill Book Company Inc.
  • Schumpeter, J. A. (1942). Capitalism, Socialism and Democracy. New York: Harper & Row.
  • Solow, R. M. (1956). A contribution to the theory of economic growth. The quarterly journal of economics, 70(1), 65-94.
  • Whittle, A., & Kogler, D. F. (2019). Related to what? Reviewing the literature on technological relatedness: Where we are now and where can we go? Papers in Regional Science, 99(1), 97-113.
There are 37 citations in total.

Details

Primary Language English
Journal Section Makaleler
Authors

Sedef Akgüngör

Mert Abay 0000-0003-3941-3200

Publication Date November 30, 2021
Published in Issue Year 2021 Volume: 7 Issue: 2

Cite

APA Akgüngör, S., & Abay, M. (2021). Knowledge Space, Relatedness and Complexity: A Regional Analysis in Turkey. Yildiz Social Science Review, 7(2), 123-136. https://doi.org/10.51803/yssr.869824