Araştırma Makalesi
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Türkiye'nin İhracata Dayalı Öncü Endüstrilerinde Ar-Ge ve İnovasyon Faaliyetleri: Gelecek Görüşleri İçin Bir Analiz

Yıl 2024, PRODUCTIVITY FOR INNOVATION, 57 - 76, 15.01.2024
https://doi.org/10.51551/verimlilik.1326253

Öz

Amaç: Araştırma ve Geliştirme (Ar-Ge) ve inovasyon faaliyetleri, organizasyonun gelişimi ve rekabet avantajı üzerinde kritik etkilere sahiptir. Tüm sektörlerin Ar-Ge ve inovasyon faaliyetleri olmasına rağmen, sektörel uygulamalar; hazırlık düzeyi, yatırım fırsatları ve organizasyonel stratejilere göre farklılık göstermektedir. Bu çalışma, Türkiye'nin en yüksek ihracat oranlarına sahip otomotiv, tekstil ve ana metal sektörlerine odaklanmaktadır. Bu çalışma, seçilen endüstriler için Ar-Ge ve yenilik faaliyetlerini analiz etmeyi ve uygulayıcılara geleceğe yönelik öngörüler sağlamayı amaçlamaktadır.
Yöntem: Bu çalışma için cari harcamalar, personel harcamaları, ticari yatırımlar, patent başvuru sayısı ve Ar-Ge personeli sayısı olmak üzere altı farklı Ar-Ge ve yenilik göstergesi dikkate alınmış ve 2022-2030 tahmininde GM (1, 1) tahmin modeli kullanılmıştır.
Bulgular: Sonuç olarak, özellikle her gösterge için otomotiv sanayinde Ar-Ge ve inovasyon faaliyetlerinde artış beklenmesine rağmen, tekstil ve ana metal için bu değerler sınırlıdır. Özellikle bu iki sektörün daha fazla desteğe ihtiyacı olduğu anlaşılmaktadır.
Özgünlük: Bu çalışma kapsamında, sektörel farklılıklar göz önüne alınarak dijitalleşme ve teknolojinin benimsenmesi, çalışanların lisansüstü eğitimlerinin ve yükseköğretim-sanayi işbirliklerinin teşvik edilmesi, Ar-Ge ve inovasyonun kurum kültürünün bir parçası olarak benimsenmesi, Ar-Ge ve inovasyon teşviklerinin yaygınlaştırılması, Ar-Ge ve yenilik faaliyetlerinde KOBİ'lerin desteklenmesi gibi başlıkları altında geleceğe yönelik öngörü ve öneriler verilerek sektörel açıdan katkı sağlamak amaçlanmaktadır.

Kaynakça

  • Afriana, F.M. and Khoirunurrofik, K. (2023). “Measuring Research Efficiency and Its Determining Factors for Indonesian R&D Institutions: Does Scientific Publication Make a Difference?”, Journal of Science and Technology Policy Management, DOI: 10.1108/JSTPM-04-2022-0076.
  • Ahmad, M. and Zheng, J. (2023). “The Cyclical and Nonlinear Impact of R&D and Innovation Activities on Economic Growth in OECD Economies: A New Perspective”, Journal of the Knowledge Economy, 14(1), 544-593.
  • Akçomak, I.S. and Bürken, S. (2021). “Middle-Technology Trap: The Case of Automotive Industry in Turkey”, Technological Innovation and International Competitiveness for Business Growth. Palgrave Studies in Democracy, Innovation, and Entrepreneurship for Growth, (Editors: Ferreira, J.J.M., Teixeira, S.J., Rammal, H.G.), 263-306 Palgrave Macmillan, Cham.
  • Alpkan, L. and Gemici, E. (2023). “The Relation Between High-Performance Work Systems and Product Innovativeness: The Mediating Role of Technological Capabilities and the Moderating Role of University-Industry Collaboration”, Journal of Engineering and Technology Management, 67, 101735.
  • Anisah, A., Irwansyah, I., Agustan, A., Santosa, B.H., Bintoro, O.B., Paramita, C.H., ... and Emillia, D. (2023, May). Application of grey model to predict Covid-19 in Indonesia. In AIP Conference Proceedings (Vol. 2683, No. 1). AIP Publishing.
  • Aydin, M., Degirmenci, T., Gurdal, T. and Yavuz, H. (2023). “The Role of Green Innovation in Achieving Environmental Sustainability in European Union Countries: Testing the Environmental Kuznets Curve Hypothesis”, Gondwana Research, 118, 105-116.
  • Barazza, S. (2023). “The Automotive Sector: A Crystal Ball for the Future of IP?”, Journal of Intellectual Property Law & Practice.
  • Bate, A.F., Wachira, E.W. and Danka, S. (2023). “The Determinants of Innovation Performance: An Income-Based Cross-Country Comparative Analysis Using the Global Innovation Index (GII)”, Journal of Innovation and Entrepreneurship, 12(1), 1-27.
  • Belgin, Ö. and Balkan, D. (2019). “Ar-Ge ve Yeni̇li̇k Destekleri̇ne İli̇şki̇n Etki̇ Değerlendi̇rme Çalışmalari Üzeri̇ne Bi̇r Li̇teratür Taramasi”, Verimlilik Dergisi, 4, 233-258.
  • Berrar D. (2018). “Cross-Validation”, Encyclopedia of Bioinformatics and Computational Biology, Volume 1, Elsevier, pp. 542–545, DOI: 10.1016/B978-0-12-809633-8.20349-X.
  • Börü, M.K. and Çelik, D. (2019). “Türkiye’de Ar-Ge Harcamaları, İnovasyon ve Ekonomik Büyüme İlişkisi”, R&S-Research Studies Anatolia Journal, 2(5), 196-206.
  • Bozkurt, C. (2015). “R&D Expenditures and Economic Growth Relationship in Turkey”, International Journal of Economics and Financial Issues, 5(1), 188-198.
  • BTK (2022). “Türkiye’de Dijital Dönüşüm ve Dijital Okuryazarlık”, https://www.btk.gov.tr/uploads/pages/arastirma-raporlari/tu-rkiyede-dijital-do-nu-s-u-m-ve-dijital-okuryazarlik.pdf, (Access Date: 10.03.2023).
  • Çalık E. (2021). “Türkiye’deki İmalat İşletmelerinin Sürdürülebilir İnovasyon Faaliyetleri”, Verimlilik Dergisi, (3), 185-201.
  • Cao, X.Y., Wu, X.L. and Wang, L.M. (2023). “Innovation Network Structure, Government R&D Investment and Regional Innovation Efficiency: Evidence from China”, Plos one, 18(5), e0286096.
  • Çelik, A. (2020). “Seçilmiş OECD Ülkelerinde Ar-Ge Harcamalarının Makroekonomik Göstergeler Üzerindeki Etkisi”, Verimlilik Dergisi, (3), 59-90.
  • Cipek, M., Pavković, D. and Kljaić, Z. (2023). “Optimized Energy Management Control of a Hybrid Electric Locomotive”, Machines, 11(6), 589.
  • Comert, G., Begashaw, N. and Huynh, N. (2021). “Improved Grey System Models for Predicting Traffic Parameters”, Expert Systems with Applications, 177, 114972.
  • Costantiello, A. and Leogrande, A. (2023). “The Impact of Research and Development Expenditures on ESG Model in the Global Economy”, Available at SSRN: https://ssrn.com/abstract=4414232 ,
  • Çubuk, M. (2023). “R&D and Innovation Map of Turkey: Hybrid Model Approach”, Turkish Journal of Science and Technology, 18(2), 487-502.
  • Davis, P.D., Amankwah, G. and Fang, Q. (2019). “Predicting the Rainfall of Ghana Using the Grey Prediction Model GM (1, 1) and the Grey Verhulst Model”, International Research Journal of Engineering and Technology (IRJET), 6(8), 1362-1372.
  • Demir, M. and Geyik, O. (2014). “Türkiye’de Ar-Ge & İnovasyon Harcamalarının Gelişim Süreci ve Ekonomik Etkileri”, Journal of Life Economics, 1(2), 171-190.
  • Dhar, B.K., Shaturaev, J., Kurbonov, K. and Nazirjon, R. (2023). “The Causal Nexus Between Innovation and Economic Growth: An OECD Study”, Social Science Quarterly.
  • Dong, G., Kokko, A. and Zhou, H. (2022). “Innovation and Export Performance of Emerging Market Enterprises: The Roles of State and Foreign Ownership in China”, International Business Review, 31(6), 102025.
  • Jiyamuratov, R. (2023). “Ways to Develop Goods-Market Marketing Strategies in Free Economic Zones”, Science and Innovation, 2(A1), 63-69.
  • Kantur, Ç. and Türkekul, B. (2023). “Comparative Advantage of Yarn and Weaving Industries: Evidence for Türkiye and Top Exporters”, Fibres & Textiles in Eastern Europe.
  • Kazancoglu, Y., Ozbiltekin-Pala, M. and Ozkan-Ozen, Y.D. (2021). “Prediction and Evaluation of Greenhouse Gas Emissions for Sustainable Road Transport within Europe”, Sustainable Cities and Society, 70, 102924.
  • Khan, A.M. and Osińska, M. (2023). “Comparing Forecasting Accuracy of Selected Grey and Time Series Models Based on Energy Consumption in Brazil and India”, Expert Systems with Applications, 212, 118840.
  • Kose, B. and Atasever, M. (2023). “Covid-19 Pandemic and Sustainable Green Product Strategies: The Case Study for Textile Recycle Sector”, International Journal of Scientific Multidisciplinary Research, 1(1), 1-16.
  • Li, X. and Zhang, X. (2023). “A Comparative Study of Statistical and Machine Learning Models on Carbon Dioxide Emissions Prediction of China”, Environmental Science and Pollution Research, DOI: 10.21203/rs.3.rs-3070359/v1.
  • Li, X., Xu, C., Wang, K., Yang, X. and Li, Y. (2023). “Data-Driven Adaptive GM (1, 1) Time series Prediction Model for Thermal Comfort”, International Journal of Biometeorology, 1-10.
  • Liu, C., Xu, Z., Zhao, K. and Xie, W. (2023). “Forecasting Education Expenditure with a Generalized Conformable Fractional-Order Nonlinear Grey System Model”, Heliyon, 9(6).
  • Madaleno, M. and Nogueira, M.C. (2023). “How Renewable Energy and CO2 Emissions Contribute to Economic Growth, and Sustainability-An Extensive Analysis”, Sustainability, 15(5), 4089.
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  • Ministry of Industry and Technology (2021b). “Tekstil, Hazır Giyim ve Deri Ürünleri Sektörleri Raporu”, https://www.sanayi.gov.tr/, (Access Date: 21.06.2023).
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  • Murrieta-Oquendo, M.E. and De la Vega, I.M. (2023). “State and Dynamics of the Innovative Performance of Medium and Large Firms in the Manufacturing Sector in Emerging Economies: The Cases of Peru and Ecuador”, Sustainability, 15(1), 670.
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R&D and Innovation Activities in Leading Export-Based Industries in Türkiye: An Analysis for Future Insights

Yıl 2024, PRODUCTIVITY FOR INNOVATION, 57 - 76, 15.01.2024
https://doi.org/10.51551/verimlilik.1326253

Öz

Purpose: Research and Development (R&D) and innovation activities critically impact an organization's development and competitive advantage. Although all industries have R&D and innovation activities, sectoral applications vary depending on readiness, investment opportunities, and organizational strategies. This study focuses on the automotive, textile, and main metal industries, with the highest export rates in Türkiye. This study aims to analyze R&D and innovation activities for the selected industries and provide practitioners with future insights.
Methodology: Six different R&D and innovation indicators, i.e., current expenditure, personnel expenditures, trade investments, number of patent applications and number of R&D personnel, are considered for this study, and the GM (1,1) forecasting model is used to predict 2022-2030.
Findings: As a result, although an increase in R&D and innovation activities in the automotive industry is expected, especially for each indicator, these values are limited for textile and main metal. It is realized that especially these two industries need more support.
Originality: Within the scope of this study, future insights and suggestions are given under digitalization and technology adoption, encouraging postgraduate studies of employees and higher education - industry collaborations, adopting R&D and innovation as a part of corporate culture, extending R&D and innovation incentives, supporting SMEs in R&D and innovation activities according to sectoral comparisons.

Kaynakça

  • Afriana, F.M. and Khoirunurrofik, K. (2023). “Measuring Research Efficiency and Its Determining Factors for Indonesian R&D Institutions: Does Scientific Publication Make a Difference?”, Journal of Science and Technology Policy Management, DOI: 10.1108/JSTPM-04-2022-0076.
  • Ahmad, M. and Zheng, J. (2023). “The Cyclical and Nonlinear Impact of R&D and Innovation Activities on Economic Growth in OECD Economies: A New Perspective”, Journal of the Knowledge Economy, 14(1), 544-593.
  • Akçomak, I.S. and Bürken, S. (2021). “Middle-Technology Trap: The Case of Automotive Industry in Turkey”, Technological Innovation and International Competitiveness for Business Growth. Palgrave Studies in Democracy, Innovation, and Entrepreneurship for Growth, (Editors: Ferreira, J.J.M., Teixeira, S.J., Rammal, H.G.), 263-306 Palgrave Macmillan, Cham.
  • Alpkan, L. and Gemici, E. (2023). “The Relation Between High-Performance Work Systems and Product Innovativeness: The Mediating Role of Technological Capabilities and the Moderating Role of University-Industry Collaboration”, Journal of Engineering and Technology Management, 67, 101735.
  • Anisah, A., Irwansyah, I., Agustan, A., Santosa, B.H., Bintoro, O.B., Paramita, C.H., ... and Emillia, D. (2023, May). Application of grey model to predict Covid-19 in Indonesia. In AIP Conference Proceedings (Vol. 2683, No. 1). AIP Publishing.
  • Aydin, M., Degirmenci, T., Gurdal, T. and Yavuz, H. (2023). “The Role of Green Innovation in Achieving Environmental Sustainability in European Union Countries: Testing the Environmental Kuznets Curve Hypothesis”, Gondwana Research, 118, 105-116.
  • Barazza, S. (2023). “The Automotive Sector: A Crystal Ball for the Future of IP?”, Journal of Intellectual Property Law & Practice.
  • Bate, A.F., Wachira, E.W. and Danka, S. (2023). “The Determinants of Innovation Performance: An Income-Based Cross-Country Comparative Analysis Using the Global Innovation Index (GII)”, Journal of Innovation and Entrepreneurship, 12(1), 1-27.
  • Belgin, Ö. and Balkan, D. (2019). “Ar-Ge ve Yeni̇li̇k Destekleri̇ne İli̇şki̇n Etki̇ Değerlendi̇rme Çalışmalari Üzeri̇ne Bi̇r Li̇teratür Taramasi”, Verimlilik Dergisi, 4, 233-258.
  • Berrar D. (2018). “Cross-Validation”, Encyclopedia of Bioinformatics and Computational Biology, Volume 1, Elsevier, pp. 542–545, DOI: 10.1016/B978-0-12-809633-8.20349-X.
  • Börü, M.K. and Çelik, D. (2019). “Türkiye’de Ar-Ge Harcamaları, İnovasyon ve Ekonomik Büyüme İlişkisi”, R&S-Research Studies Anatolia Journal, 2(5), 196-206.
  • Bozkurt, C. (2015). “R&D Expenditures and Economic Growth Relationship in Turkey”, International Journal of Economics and Financial Issues, 5(1), 188-198.
  • BTK (2022). “Türkiye’de Dijital Dönüşüm ve Dijital Okuryazarlık”, https://www.btk.gov.tr/uploads/pages/arastirma-raporlari/tu-rkiyede-dijital-do-nu-s-u-m-ve-dijital-okuryazarlik.pdf, (Access Date: 10.03.2023).
  • Çalık E. (2021). “Türkiye’deki İmalat İşletmelerinin Sürdürülebilir İnovasyon Faaliyetleri”, Verimlilik Dergisi, (3), 185-201.
  • Cao, X.Y., Wu, X.L. and Wang, L.M. (2023). “Innovation Network Structure, Government R&D Investment and Regional Innovation Efficiency: Evidence from China”, Plos one, 18(5), e0286096.
  • Çelik, A. (2020). “Seçilmiş OECD Ülkelerinde Ar-Ge Harcamalarının Makroekonomik Göstergeler Üzerindeki Etkisi”, Verimlilik Dergisi, (3), 59-90.
  • Cipek, M., Pavković, D. and Kljaić, Z. (2023). “Optimized Energy Management Control of a Hybrid Electric Locomotive”, Machines, 11(6), 589.
  • Comert, G., Begashaw, N. and Huynh, N. (2021). “Improved Grey System Models for Predicting Traffic Parameters”, Expert Systems with Applications, 177, 114972.
  • Costantiello, A. and Leogrande, A. (2023). “The Impact of Research and Development Expenditures on ESG Model in the Global Economy”, Available at SSRN: https://ssrn.com/abstract=4414232 ,
  • Çubuk, M. (2023). “R&D and Innovation Map of Turkey: Hybrid Model Approach”, Turkish Journal of Science and Technology, 18(2), 487-502.
  • Davis, P.D., Amankwah, G. and Fang, Q. (2019). “Predicting the Rainfall of Ghana Using the Grey Prediction Model GM (1, 1) and the Grey Verhulst Model”, International Research Journal of Engineering and Technology (IRJET), 6(8), 1362-1372.
  • Demir, M. and Geyik, O. (2014). “Türkiye’de Ar-Ge & İnovasyon Harcamalarının Gelişim Süreci ve Ekonomik Etkileri”, Journal of Life Economics, 1(2), 171-190.
  • Dhar, B.K., Shaturaev, J., Kurbonov, K. and Nazirjon, R. (2023). “The Causal Nexus Between Innovation and Economic Growth: An OECD Study”, Social Science Quarterly.
  • Dong, G., Kokko, A. and Zhou, H. (2022). “Innovation and Export Performance of Emerging Market Enterprises: The Roles of State and Foreign Ownership in China”, International Business Review, 31(6), 102025.
  • Jiyamuratov, R. (2023). “Ways to Develop Goods-Market Marketing Strategies in Free Economic Zones”, Science and Innovation, 2(A1), 63-69.
  • Kantur, Ç. and Türkekul, B. (2023). “Comparative Advantage of Yarn and Weaving Industries: Evidence for Türkiye and Top Exporters”, Fibres & Textiles in Eastern Europe.
  • Kazancoglu, Y., Ozbiltekin-Pala, M. and Ozkan-Ozen, Y.D. (2021). “Prediction and Evaluation of Greenhouse Gas Emissions for Sustainable Road Transport within Europe”, Sustainable Cities and Society, 70, 102924.
  • Khan, A.M. and Osińska, M. (2023). “Comparing Forecasting Accuracy of Selected Grey and Time Series Models Based on Energy Consumption in Brazil and India”, Expert Systems with Applications, 212, 118840.
  • Kose, B. and Atasever, M. (2023). “Covid-19 Pandemic and Sustainable Green Product Strategies: The Case Study for Textile Recycle Sector”, International Journal of Scientific Multidisciplinary Research, 1(1), 1-16.
  • Li, X. and Zhang, X. (2023). “A Comparative Study of Statistical and Machine Learning Models on Carbon Dioxide Emissions Prediction of China”, Environmental Science and Pollution Research, DOI: 10.21203/rs.3.rs-3070359/v1.
  • Li, X., Xu, C., Wang, K., Yang, X. and Li, Y. (2023). “Data-Driven Adaptive GM (1, 1) Time series Prediction Model for Thermal Comfort”, International Journal of Biometeorology, 1-10.
  • Liu, C., Xu, Z., Zhao, K. and Xie, W. (2023). “Forecasting Education Expenditure with a Generalized Conformable Fractional-Order Nonlinear Grey System Model”, Heliyon, 9(6).
  • Madaleno, M. and Nogueira, M.C. (2023). “How Renewable Energy and CO2 Emissions Contribute to Economic Growth, and Sustainability-An Extensive Analysis”, Sustainability, 15(5), 4089.
  • Ministry of Industry and Technology (2021a). “Otomotiv Sektör Raporu”, Accessed Date: 21.05.2023 Retrieved from: https://www.sanayi.gov.tr/
  • Ministry of Industry and Technology (2021b). “Tekstil, Hazır Giyim ve Deri Ürünleri Sektörleri Raporu”, https://www.sanayi.gov.tr/, (Access Date: 21.06.2023).
  • Ministry of Industry and Technology (2021c). “Demir-Çelik Sektör Raporu”, https://www.sanayi.gov.tr/, (Access Date: 21.05.2023).
  • Murrieta-Oquendo, M.E. and De la Vega, I.M. (2023). “State and Dynamics of the Innovative Performance of Medium and Large Firms in the Manufacturing Sector in Emerging Economies: The Cases of Peru and Ecuador”, Sustainability, 15(1), 670.
  • Nguyen, N.T., Phan, V.T. and Malara, Z. (2019). “Nonlinear Grey Bernoulli Model Based on Fourier Transformation and its Application in Forecasting the Electricity Consumption in Vietnam”, Journal of Intelligent & Fuzzy Systems, 37(6), 7631-7641.
  • Pelikánová, R.M. (2019). “R&D Expenditure and Innovation in the EU and Selected Member States”, Journal of Entrepreneurship, Management and Innovation, 15(1), 13-34.
  • Podrecca, M., and Sartor, M. (2023). “Forecasting the Diffusion of ISO/IEC 27001: A Grey Model Approach”, The TQM Journal, 35(9), 123-151.
  • Pudcha, T., Phongphiphat, A., Wangyao, K. and Towprayoon, S. (2023). “Forecasting Municipal Solid Waste Generation in Thailand with Grey Modelling”, Environment and Natural Resources Journal, 21(1), 35-46.
  • Ralphs, G. and Mustapha, N. (2023). “Indicators of R&D, Innovation in South African SOEs”. HSRC Review. 20(1):34-39.
  • Su, X. and Huang, S. (2023). An improved machine learning model Shapley value-based to forecast demand for aquatic product supply chain. Frontiers in Ecology and Evolution, 11, 1160684.
  • Sungur, O., AYDIN, H. and Mehmet, E. (2016). “Türkiye’de Ar-Ge, İnovasyon, İhracat Ve Ekonomik Büyüme Arasindaki İlişki: Asimetrik Nedensellik Analizi”, Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 21(1), 173-192.
  • Temel, S., Mention, A.L. and Yurtseven, A.E. (2023). “Cooperation for Innovation: More is not Necessarily Merrier”, European Journal of Innovation Management, 26(2), 446-474.
  • TÜBİSAD (2022), “Türkiye Dijital Dönüşüm Endeksi 2022”, ", https://www.tubisad.org.tr/tr/images/pdf/DDE-2022-Raporu-Final.pdf, (Access Date: 19.04.2023).
  • TÜBİTAK (2023). “1507 TÜBITAK SME R&D Start-up Support Programme ", https://www.tubitak.gov.tr/en/funds/industry/national-support-programmes/content-1507-tubitak-sme-rd- start-up-support-programme, (Access Date: 10.04.2023).
  • Türkiye Exporters Assembly (2022). “Export 2022 Report”, https://tim.org.tr/en/export-export-figures, (Access Date: 17.03.2023).
  • Türkiye Exporters Assembly (2023).” Export 2023 Report”, https://tim.org.tr/en/export-export-figures, (Access Date: 17.03.2023).
  • TurkStat (Turkish Statistical Institute) (2022). “Foreign Trade Statistics", https://biruni.tuik.gov.tr/disticaretapp/menu.zul, (Access Date: 19.04.2023).
  • TÜSİAD (2023). “Türkiye’nin 2. Yüzyılında Yüksek Teknoloji için Eylem Çağrısı”, https://tusiad.org/tr/yayinlar/raporlar/item/11278-turkiye-nin-2-yuzyilinda-yuksek-teknoloji-icin-eylem-cagrisi, (Access Date: 10.02.2023).
  • Wang, Y., Zhang, L., He, X., Ma, X., Wu, W., Nie, R., Chi, P. and Zhang, Y. (2023). “A Novel Exponential Time Delayed Fractional Grey Model and its Application in Forecasting Oil Production and Consumption of China”, Cybernetics and Systems, 54(2), 168-196.
  • Wei, W., Wang, G., Tao, X., Luo, Q., Chen, L., Bao, X., Liu, Y, Jiang, J., Liang, H. and Ye, L. (2023). “Time Series Prediction for the Epidemic Trends of Monkeypox Using the ARIMA, Exponential Smoothing, GM (1, 1) and LSTM Deep Learning Methods”, Journal of General Virology, 104(4), 001839.
  • Xie, D., Chen, S., Duan, H., Li, X., Luo, C., Ji, Y. and Duan, H. (2023). A Novel Grey Prediction Model Based on Tensor Higher-Order Singular Value Decomposition and its Application in Short-Term Traffic Flow. Engineering Applications of Artificial Intelligence, 126, 107068.
  • Xu, X., Cui, X., Zhang, Y., Chen, X. and Li, W. (2023). “Carbon Neutrality and Green Technology Innovation Efficiency in Chinese Textile Industry, “Journal of Cleaner Production”, 395, 136453.
  • Yanmaz Arpacı, Ö. and Gülel, F.E. (2023). “Scale Adaptation of Innovation-Outsourcing in Companies”, İstanbul Business Research, 52(1), 31-45.
  • Yontar, E. and Ersoy Duran, F. (2023, February). “Evaluation of Understandability of the Concept of Sustainability by Companies: Automotive Sector Spare Parts Industry”, In Industrial Engineering in the Covid-19 Era: Selected Papers from the Hybrid Global Joint Conference on Industrial Engineering and Its Application Areas, GJCIE 2022, October 29-30, 2022 (pp. 213-223), Cham: Springer Nature Switzerland.
  • Zeng, B., He, C., Mao, C. and Wu, Y. (2023). “Forecasting China's Hydropower Generation Capacity Using a Novel Grey Combination Optimization Model”, Energy, 262, 125341.
  • Zhang, R., Mao, S. and Kang, Y. (2023). “A Novel Traffic Flow Prediction Model: Variable Order Fractional Grey Model Based on an Improved Grey Evolution Algorithm”, Expert Systems with Applications, 224, 119943.
  • Zhou, J. and Wang, M. (2023). “The Role of Government-Industry-Academia Partnership in Business Incubation: Evidence from New R&D Institutions in China”, Technology in Society, 72, 102194.
Toplam 60 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular İşletme
Bölüm Makaleler
Yazarlar

Melisa Özbiltekin-pala 0000-0002-1356-3203

Yesım Denız Ozkan Ozen 0000-0003-4520-6590

Yayımlanma Tarihi 15 Ocak 2024
Gönderilme Tarihi 12 Temmuz 2023
Yayımlandığı Sayı Yıl 2024 PRODUCTIVITY FOR INNOVATION

Kaynak Göster

APA Özbiltekin-pala, M., & Ozkan Ozen, Y. D. (2024). R&D and Innovation Activities in Leading Export-Based Industries in Türkiye: An Analysis for Future Insights. Verimlilik Dergisi57-76. https://doi.org/10.51551/verimlilik.1326253

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