İLİŞKİLİ VE İLİŞKİSİZ ÇEŞİTLİLİĞİN AR-GE FAALİYETLERİ ÜZERİNE ETKİSİ: TÜRKİYE DÜZEY-1 BÖLGELERİNDEN KANITLAR

Yıl 2025, Cilt: 12 Sayı: 27, 312 - 346, 30.04.2025

Yusuf Ünsal

https://doi.org/10.58884/akademik-hassasiyetler.1572389

Öz

Yerel yenilikçi çabaların artışı, bilgi yayılımını hızlandırarak, Ar-Ge yoğun bölgelerdeki firmaların daha karmaşık bilgi akışlarıyla yüksek inovasyon potansiyeli kazanmasını sağlamaktadır. Bu doğrultuda, çalışma 2010-2022 yılları arasında Türkiye’nin Düzey-1 bölgelerinde ilişkili ve ilişkisiz çeşitliliğin Ar-Ge faaliyetleri üzerindeki etkilerini incelemektedir. Öncelikle, Türkiye Düzey-1 bölgeleri için ilişkili ve ilişkisiz çeşitlilik değerleri hesaplanmış, ardından sabit etkiler ve Yarım Panel Jackknife (HPJ) yöntemi kullanılarak bu çeşitlilik ölçütlerinin Ar-Ge harcamaları ve Ar-Ge insan gücü üzerindeki etkileri analiz edilmesi açısından literatüre katkı sağlamaktadır. Ayrıca çalışma, ilişkili ve ilişkisiz çeşitliliğin Türkiye Düzey-1 bölgelerindeki etkilerini araştırmasıyla öne çıkmaktadır. Panel veri analizlerinde elde edilen sonuçlara göre, ilişkili çeşitlilik Ar-Ge insan gücü üzerinde pozitif bir etkiye sahipken, ilişkili ve ilişkisiz çeşitliliğin Ar-Ge harcamaları üzerinde anlamlı bir etkisi bulunmamıştır. Bu bulgular, ilişkili endüstriler arasında bilgi değişimi ve bölgesel iş birliğinin Ar-Ge kapasitesini artırmada kritik bir rol oynadığını, ancak ilişkisiz çeşitliliğin radikal yenilik potansiyelinin henüz tam olarak kullanılamadığını göstermektedir. Bu nedenle, politika yapıcıların Türkiye'de sürdürülebilir inovasyonu ve bölgesel kalkınmayı desteklemek amacıyla Ar-Ge kapasitelerini ve çeşitlilik türlerini güçlendirmeye odaklanmaları önerilmektedir.

Anahtar Kelimeler

Ar-Ge Harcaması , İlişkili Çeşitlilik , İlişkisiz Çeşitlilik , Ar-Ge Personeli

THE IMPACT OF RELATED AND UNRELATED VARIETY ON R&D ACTIVITIES: EVIDENCE FROM TURKEY'S LEVEL-1 REGIONS

Öz

Increased local innovative efforts accelerate knowledge spillovers, enabling firms in Increased local innovative efforts facilitate knowledge spillovers, allowing companies in R&D-focused regions to achieve high innovation potential through more intricate knowledge transfers. This study, therefore, investigates the impact of related and unrelated diversity on R&D activities in Turkey's Level-1 regions from 2010 to 2022. The study first calculates related and unrelated diversity values for these regions and then uses fixed effects and Half Panel Jackknife (HPJ) methods to assess how these diversity measures influence R&D expenditures and R&D human capital. A key feature of the study is its examination of the effects of both types of diversity across Turkey's Level-1 regions. The panel data analysis reveals that while related diversity positively impacts R&D human capital, neither related nor unrelated diversity significantly influences R&D expenditures. These results indicate that knowledge sharing and collaboration among related industries are crucial for boosting R&D capacity, but the disruptive innovation potential of unrelated diversity remains underutilized. Consequently, policymakers are encouraged to enhance R&D capacities and focus on different diversity types to foster sustainable innovation and regional development in Turkey.

Anahtar Kelimeler

R&D Expenditure , R&D Personnel , Related Variety , Unrelated Variety

Kaynakça

• Aarstad, J., Kvitastein, O. A., & Jakobsen, S. E. (2016). Related and unrelated variety as regional drivers of enterprise productivity and innovation: A multilevel study. Research Policy, 45(4), 844 856.
• Abolhassani, M. (2024). Productivity spillovers of superior firms through worker mobility. De Economist, 172(1), 1-23.
• Adner, R., & Zemsky, P. (2016). Diversification and performance: Linking relatedness, market structure, and the decision to diversify. Strategy Science, 1(1), 32-55.
• Aghion, P., Akcigit U., & Howitt, P. (2014). Handbook of economic growth. P. Aghion & S. Durlauf (Ed). in What do we learn from schumpeterian growth theory? (p. 515-563). Oxford: North Holland.
• Ahamed, M. M., Luintel, K. B., & Mallick, S. K. (2023). Does local knowledge spillover matter for firm productivity? The role of financial access and corporate governance. Research Policy, 52(8), 104837.
• Akgüngör, S., Kuştepeli, Y. & Gülcan, Y. (2013). An overview on industry clusters and the impact of related variety on regional performance in Turkey. European Review of Industrial Economics and Policy, 5, Erişim adresi: http://revel.unice.fr/eriep/index.html?id=3533.
• Antonelli, C. (2002). Microdynamics of technological change. London: Routledge.
• Antonietti, R., & Cainelli, G. (2011). The role of spatial agglomeration in a structural model of innovation, productivity and export: a firm-level analysis. The Annals of Regional Science, 46, 577-600.
• Antonietti, R., & Gambarotto, F. (2020). The role of industry variety in the creation of innovative start-ups in Italy. Small Business Economics, 54, 561-573.
• Arrow, K. J. (1962). The economic implications of learning by doing. The Review of Economic Studies, 29(3), 155-173.
• Asteriou, D., & Hall, S. G. (2021). Applied econometrics (Fourth edition). London: Macmillan Education Limited.
• Audretsch, D. B., & Belitski, M. (2020). The role of R&D and knowledge spillovers in innovation and productivity. European Economic Review, 123, 103391.
• Balassa, B. (1965). Trade liberalisation and “revealed” comparative advantage. The Manchester School, 33, 99–123
• Baltagi, B. H. (2021). Econometric Analysis of Panel Data (Sixth edition), Switzerland: Springer Texts in Business and Economics.
• Barboza, G., Capocchi, A., & Trejos, S. (2023). Knowledge Spillover Effects and Employment Productivity in the Innovative Startups: Evidence from Italy. The Review of Regional Studies, 53(2), 156-181.
• Bishop, P., & Gripaios, P. (2010). Spatial externalities, relatedness and sector employment growth in Great Britain. Regional Studies, 44(4), 443–454.
• Blomquist, J. and J. Westerlund. 2013. Testing slope homogeneity in large panels with serial correlation. Economics Letters, 121, 374-378.
• Boschma R, & Iammarino, S. (2009). Related variety, trade linkages, and regional growth in Italy. Economic Geography, 85, 289–311.
• Boschma, R., Minondo, A., & Navarro, M. (2012). Related variety and regional growth in Spain: Related variety and regional growth. Papers in Regional Science, 91, 241–256
• Boschma, R., Minondo, A., & Navarro, M. (2013). The emergence of new industries at the regional level in s pain: A proximity approach based on product relatedness. Economic Geography, 89(1), 29-51.
• Boschma, R. (2017). Relatedness as driver of regional diversification: A research agenda. Regional Studies, 51(3), 351-364.
• Boschma, R., Miguelez, E., Moreno, R., & Ocampo-Corrales, D. B. (2023). The role of relatedness and unrelatedness for the geography of technological breakthroughs in Europe. Economic Geography, 99(2), 117-139.
• Castaldi, C., Frenken, K., & Los, B. (2015). Related variety, unrelated variety and technological breakthroughs: An analysis of US state-level patenting. Regional Studies, 49(5), 767-781.
• Choi, W., & Lee, H. (2021). Identifying disease-gene associations using a convolutional neural network-based model by embedding a biological knowledge graph with entity descriptions. Plos One, 16(10), e0258626.
• Content, J. & Frenken, K. (2016). Related variety and economic development: a literature review. European Planning Studies, 24(12), 2097–2112.
• Content, J., Frenken, K., & Jordaan, J. A. (2019). Does related variety foster regional entrepreneurship? Evidence from European regions. Regional Studies, 53(11), 1531–1543.
• Cooper, D. (2001). Innovation and reciprocal externalities: Information transmission via job mobility?. Journal of Economic Behavior and Organization, 45, 403–425.
• Cortinovis, N., & Van Oort, F. (2015). Variety, economic growth and knowledge intensity of European regions: a spatial panel analysis. The Annals of Regional Science, 55(1), 7-32.
• Crescenzi, R., & Jaax, A. (2016). Innovation in Russia: The territorial dimension. Economic Geography, 93(1), 1–23.
• Çınar, T. (2017). Spatial dimensions of sectoral labor productivity convergence in Turkey: A spatial panel data approach. Review of Middle East Economics and Finance, 13(1), 20170006.
• Çınar, İ. T. (2023). İlişkili–ilişkisiz çeşitlilik ve gelir dağılımı: Türkiye’de düzey-2 bölgeleri için bir analiz. İzmir İktisat Dergisi, 38(1), 233-252.
• Çınar, İ. T. (2023). Regional development trap in Turkey: Can relatedness find a way out?. Papers in Regional Science, 102(4), 817-851.
• Çınar, İ. T., Korkmaz, İ., & Şişman, M. Y. (2023). Green complexity, economic fitness, and environmental degradation: evidence from US state-level data. Environmental Science and Pollution Research, 30(15), 43013-43023.
• Çınar, İ. T. (2024). Influence of product relatedness on provincial growth: comparative analysis of east–west discrepancies in Turkey. Asia-Pacific Journal of Regional Science, 8(1), 267-290.
• Dasgupta, P., & Stiglitz, J. (1988). Learning-by-doing, market structure and industrial and trade policies. Oxford Economic Papers, 40(2), 246-268.
• Dettmann, E., Dominguez Lacasa, I., Günther, J., & Jindra, B. (2016). The importance of localized related variety for international diversification of corporate technology. Regional Studies, 50(10), 1648-1662.
• Dhaene, G., & Jochmans, K. (2015). Split-panel jackknife estimation of fixed-effect models. The Review of Economic Studies, 82(3), 991-1030.
• Duan, Y., Liu, S., Cheng, H., Chin, T., & Luo, X. (2021). The moderating effect of absorptive capacity on transnational knowledge spillover and the innovation quality of high-tech industries in host countries: evidence from the Chinese manufacturing industry. International Journal of Production Economics, 233, 108019.
• Ejdemo, T., & Örtqvist, D. (2020). Related variety as a driver of regional innovation and entrepreneurship: A moderated and mediated model with non-linear effects. Research Policy, 49(7), 104073.
• Elekes, Z., Boschma, R., & Lengyel, B. (2019). Foreign-owned firms as agents of structural change in regions. Regional Studies, 53(11), 1603–1613.
• Falcıoğlu, P. (2011). Location and determinants of productivity: The case of the manufacturing industry Turkey. Emerging Markets Finance and Trade, 47(5), 86–96.
• Ferreira, J. J., Ratten, V., & Dana, L. P. (2017). Knowledge spillover-based strategic entrepreneurship. International Entrepreneurship and Management Journal, 13, 161-167.
• Frenken K., Van Oort F., Verburg T. (2007). Related variety, unrelated variety and regional economic growth. Regional Studies, 41(5), 685–697.
• Fritsch M, & Kublina, S. (2018). Related variety, unrelated variety and regional growth: the role of absorptive capacity and entrepreneurship. Regional Studies, 52(10), 1360–1371.
• Gaulier, G. & Zignago, S. (2010) BACI: International Trade Database at the Product-Level. The 1995-2022 Version. CEPII Working Paper, N0: 2010-23.
• Grillitsch, M., Asheim, B., & Trippl, M. (2018). Unrelated knowledge combinations: the unexplored potential for regional industrial path development. Cambridge Journal of Regions, Economy and Society, 11(2), 257-274.
• Gonçalves, E., de Matos, C. M., & de Araújo, I. F. (2019). Path dependent dynamics and technological spillovers in the Brazilian regions. Applied Spatial Analysis and Policy, 12(3), 605–629.
• Gültekin, L., Yavan, N., & Kurul, Z. (2023). Evrimsel ekonomik coğrafya perspektifinden Türkiye’de bölgelerin ilişkili çeşitlilik dinamiklerine yönelik ampirik bir analiz. Coğrafi Bilimler Dergisi, 21(2), 616-659.
• Hausman, J. A. (1978). Specification tests in econometrics. Econometrica: Journal of the Econometric Society, 46(6), 1251-1271.
• Hesse, K., & Fornahl, D. (2020). Essential ingredients for radical innovations? The role of (un‐) related variety and external linkages in Germany. Papers in Regional Science, 99(5), 1165-1184.
• Hidalgo, C. A., Klinger, B., Barabási, A. L., & Hausmann, R. (2007). The product space conditions the development of nations. Science, 317, 482–487.
• Hidalgo, C. A. (2021). Economic complexity theory and applications. Nature Reviews Physics, 3(2), 92-113.
• Hartog, M., Boschma, R., & Sotarauta, M. (2012). The impact of related variety on regional employment growth in Finland 1993–2006: high-tech versus medium/low-tech. Industry and Innovation, 19(6), 459-476.
• Hassink, R., Klaerding, C., & Marques, P. (2014). Advancing evolutionary economic geography by engaged pluralism. Regional Studies, 48(7), 1295-1307.
• Hu, G. G. (2021). Is knowledge spillover from human capital investment a catalyst for technological innovation? The curious case of fourth industrial revolution in BRICS economies. Technological Forecasting and Social Change, 162, 120327.
• Hu, F., Xi, X., & Zhang, Y. (2021). Influencing mechanism of reverse knowledge spillover on investment enterprises’ technological progress: an empirical examination of Chinese firms. Technological Forecasting and Social Change, 169, 120797.
• Huang, Y., Fang, Y., & Gu, G. (2022). Innovation effect and regional difference of related variety: An empirical study based on prefecture-level city data of China. Applied Spatial Analysis and Policy, 15(2), 441-454.
• Ishaq, A., Ali, M., & Naveed, S. (2024). Related or unrelated variety and economic growth of South Asian countries. Journal of Asian and African Studies, 59(2), 603-622.
• Juodis, A., Karavias, Y., & Sarafidis, V. (2021). A homogeneous approach to testing for Granger non-causality in heterogeneous panels. Empirical Economics, 60, 93–112.
• Kublina, S., & Schiller, F. V. (2015). Related variety, unrelated variety and regional growth: Development patterns and role of absorptive capacity. Regional Studies, 20(1), 2-5.
• Le, N. L., & Bayrak, M. M. (2024). Highly-skilled migration, knowledge mobility, and knowledge mobility barriers: empirical evidence from Vietnamese migrants in the Lao construction sector. GeoJournal, 89(3), 1-15.
• Lin, T. X., Gozgor, G., Rather, K. N., Mahalik, M. K., & Lau, C. K. M. (2024). How do natural resource rents and productive capacity affect carbon emissions? Evidence from developed and developing countries. Resources Policy, 93, 105095.
• Mahn, D., & Poblete, C. (2023). Contextualizing the knowledge spillover theory of entrepreneurship: the Chilean paradox. Entrepreneurship and Regional Development, 35(1-2), 209-239.
• Mascarini, S., Garcia, R., Costa, A. R., dos Santos, E. G., & Araujo, V. (2021). Shaping the effects of related and unrelated variety on innovation. Blucher Engineering Proceedings, 2307-2322.
• Mascarini, S., Garcia, R., & Quatraro, F. (2023). Local knowledge spillovers and the effects of related and unrelated variety on the novelty of innovation. Regional Studies, 57(9), 1666-1680.
• Miguelez, E., & Moreno, R. (2018). Relatedness, external linkages and regional innovation in Europe. Regional Studies, 52(5), 688-701.
• Neffke, F., & Henning, M. (2013). Skill relatedness and firm diversification. Strategic Management Journal, 34(3), 297–316.
• Pan, Z. Z., & Liu, Y. H. (2014). Knowledge Spillover, Absorptive Ability and Performance of Firms in High-Tech Clusters. Advanced Materials Research, 845, 499-504.
• Park, J. I., & Choi, T. (2022). Related variety, unrelated variety, and R&D investment in the environmental industry. Asian Journal of Technology Innovation, 30(1), 90-105.
• Pata, U. K., Tekin, B., & Özbay, F. (2023). Empirical considerations on the reciprocal relationship between energy efficiency and leading variables: New evidence from OECD countries. Energy and Buildings, 284, 112857.
• Pata, U. K., Tiwari, A. K., & Erdogan, S. (2024). Technological innovation, globalization and ecological quality: A disaggregated ecological footprint approach for BRICS countries. Journal of Environmental Management, 370, 122518.
• Pesaran M. H. (2004). General diagnostic tests for cross section dependence in panels. CESifo Working Paper Series, No: 1229.
• Pesaran, M. H. (2007). A simple panel unit root test in the presence of cross‐section dependence. Journal of Applied Econometrics, 22(2), 265-312.
• Plechero, M., & Chaminade, C. (2016). Spatial distribution of inno vation networks, technological competencies and degree of novelty in emerging economy firms. European Planning Studies, 24(6), 1056–1078.
• Plunket, A., & Starosta de Waldemar, F. (2023). Regional recombinant novelty, related and unrelated technologies: a patent-level approach. Regional Studies, 57(7), 1267-1288.
• Porter, M. (2003). The economic performance of regions. Regional Studies, 37, 549–578.
• Qin, X., Li, S., Xu, W., & Li, X. (2019). Which export variety matters for urban economic growth, related or unrelated variety?. Sustainability, 11(16), 4325.
• Romer, D. (2012). Advanced Macroeconomics (Fourth Edition). New York: McGraw Hill Companies Inc.
• Romer, P. M. (1986). Increasing returns and long-run growth. Journal of Political Economy, 94(5), 1002-1037.
• Saviotti, P. P., & Frenken, K. (2008). Export variety and the economic performance of countries. Journal of Evolutionary Economics, 18, 201-218.
• Sergio, I., Iandolo, S., & Ferragina, A. M. (2023). Inter-sectoral and inter-regional knowledge spillovers: The role of ICT and technological branching on innovation in high-tech sectors. Technological Forecasting and Social Change, 194, 122728.
• Tavassoli, S., & Carbonara, N. (2014). The role of knowledge variety and intensity for regional innovation. Small Business Economics, 43(2), 493-509.
• Tomasz, M., & Paweł, D. (2021). Related and unrelated variety vs. basic labour market variables-regional analysis for Poland. European Planning Studies, 29(2), 221-240.
• TÜİK (2024). Araştırma-Geliştirme faaliyetleri araştırması-2022. 15 Ekim 2024 tarihinde https://data.tuik.gov.tr/Bulten/Index?p=Arastirma-Gelistirme-Faaliyetleri-Arastirmasi-2022-49408 adresinden edinilmiştir.
• TÜİK (2024). Bölgesel istatistikler. 16 Ekim 2024 tarihinde https://biruni.tuik.gov.tr/bolgeselistatistik/sorguSayfa.do?target=degisken adresinden edinilmiştir.
• Wang, Y., Pan, X., Li, J., & Ning, L. (2016). Does technological diversification matter for regional innovation capability? Evidence from China. Technology Analysis and Strategic Management, 28(3), 323-334.
• Xu, Y., Li, X., Tao, C., & Zhou, X. (2022). Connected knowledge spillovers, technological cluster innovation and efficient industrial structure. Journal of Innovation and Knowledge, 7(3), 100195.
• Xu, T., Xuan, Y., Yang, S., & Ding, C. J. (2024). Labour market mobility, knowledge diffusion, and firm innovation: empirical evidence from Chinese industrial enterprise. Technology Analysis and Strategic Management, 1-14, https://doi.org/10.1080/09537325.2024.2311282.
• Yang, N., Liu, Q., & Qi, Y. (2020). Does (un)-related variety promote regional innovation in China? Industry versus services sector. Chinese Management Studies, 14(3), 769-788.
• Zabala-Iturriagagoitia, J. M., Gómez, I. P., & Larracoechea, U. A. (2020). Technological diversification: a matter of related or unrelated varieties?. Technological Forecasting and Social Change, 155, 119997.