KaydedilenlerDerginizi ekleyin

Dergiler / Dokuz Eylül Üniversitesi İşletme Fakültesi Dergisi / 2026 / Cilt: 27 Sayı: 1

AB ÜLKELERİNDE DİJİTALLEŞMENİN AR-GE VE İNOVASYON KAPASİTESİ ÜZERİNDEKİ ETKİSİ: AMPİRİK BİR ANALİZ

THE IMPACT OF DIGITALIZATION ON R&D AND INNOVATION CAPACITY IN EU COUNTRIES: AN EMPIRICAL ANALYSIS

Ayşegül Yıldız(KÜTAHYA DUMLUPINAR ÜNİVERSİTESİ)0000-0002-8036-9910
Sayfa
79–101
Yayın Tarihi
2026-06-29
🏛️Bu makalenin bibliyografik verileri ve tam metin bağlantısı DergiPark üzerinden sağlanmıştır.
DergiPark Kaydı ↗
✨

Yapay Zeka Hızlı Bakış & Çıkarımlar

AI Insight
⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Ampirik bulgular, dijital performansın AB ülkelerinde Ar-Ge ve inovasyon kapasitesini istatistiksel olarak anlamlı ve pozitif yönde etkilediğini göstermektedir (β=0,626 t=6,088 p<0,01).

📌 3 Maddede Bu Makale

🎯
Amaç & Hipotez:Bu çalışma Avrupa Birliği ülkelerinde dijital performansın araştırma-geliştirme (Ar-Ge) ve inovasyon kapasitesi üzerindeki etkisini kısmi en küçük kareler yapısal eşitlik modellemesi ile ortaya koymaktadır.
📊
Temel Bulgular & Veri:Ülkelerin dijital performans düzeyinin değerlendirilmesinde Dijital Ekonomi ve Toplum Endeksi (DESI) çerçevesinde yer alan bağlanabilirlik, beşeri sermaye, dijital kamu hizmetleri ve dijital teknolojinin entegrasyonu boyutları modele dahil edilmiştir.
💡
Sonuç & Katkı:Ampirik bulgular, dijital performansın AB ülkelerinde Ar-Ge ve inovasyon kapasitesini istatistiksel olarak anlamlı ve pozitif yönde etkilediğini göstermektedir (β=0,626 t=6,088 p<0,01).
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:2022 Verileri
⚙️Değişkenler:Dijitalleşme · Ar-Ge ve İnovasyon · PLS-SEM

Özet

Bu çalışma Avrupa Birliği ülkelerinde dijital performansın araştırma-geliştirme (Ar-Ge) ve inovasyon kapasitesi üzerindeki etkisini kısmi en küçük kareler yapısal eşitlik modellemesi ile ortaya koymaktadır. Ülkelerin dijital performans düzeyinin değerlendirilmesinde Dijital Ekonomi ve Toplum Endeksi (DESI) çerçevesinde yer alan bağlanabilirlik, beşeri sermaye, dijital kamu hizmetleri ve dijital teknolojinin entegrasyonu boyutları modele dahil edilmiştir. Yüksek teknoloji ihracatı, Ar-Ge harcamaları (% GSYİH) ve Ar-Ge araştırmacılarından (milyon kişi başına) oluşan üç alt boyut ise, çalışmaya konu olan ülkelerin Ar-Ge ve inovasyon kapasitesini belirlemek için kullanılan göstergelerdir. 2022 yılına ait verilerin ele alındığı modelin analizinde SmartPLS 4 yazılımı aracılığıyla geçerlilik, güvenilirlik ve yol katsayılarına ilişkin testler uygulanmıştır. Ampirik bulgular, dijital performansın AB ülkelerinde Ar-Ge ve inovasyon kapasitesini istatistiksel olarak anlamlı ve pozitif yönde etkilediğini göstermektedir (β=0,626 t=6,088 p<0,01). Çalışmada, dijital becerilerle donatılmış bir işgücünün oluşturulması, dijital teknolojilerin kullanımının yaygınlaştırılması, bağlantı alt yapısının güçlendirilmesi ve kamu hizmetlerinde dijitalleşmenin teşvik edilmesi alanlarında gözlemlenen iyileşmelerin ülkelerin dijital performanslarındaki gelişmeyle birlikte Ar-Ge ve inovasyon kapasitelerini artırmada politika yapıcılar açısından stratejik bir rol oynadığı ortaya konulmaktadır.

Abstract

This study reveals the impact of digital performance on research and development (R&D) and innovation capacity in European Union countries using partial least squares structural equation modeling. To assess the digital performance level of countries, the connectivity, human capital, digital public services, and integration of digital technology dimensions included in the Digital Economy and Society Index (DESI) framework have been incorporated into the model. The three sub-dimensions consisting of high-technology exports, research and development expenditure (% of GDP), and researchers in R&D (per million people)- are indicators used to determine the R&D and innovation capacity of the countries studied. In the analysis of the model, in which 2022 data were employed, tests on validity, reliability, and path coefficients were carried out through SmartPLS 4 software. The empirical findings show that the digital performance affects the R&D and innovation capacity in EU countries statistically significantly and positively (β=0.626, t=6.088, p<0.01). The study reveals that improvements observed in areas such as creating a digitally skilled workforce, expanding the use of digital technologies, strengthening connectivity infrastructure, and encouraging digitalization in public services play a strategic role for policymakers in increasing countries' R&D and innovation capacities, along with improving their digital performance.

🔖

Bu Makaleye Atıf Yap

Yıldız, A. (2026). AB ÜLKELERİNDE DİJİTALLEŞMENİN AR-GE VE İNOVASYON KAPASİTESİ ÜZERİNDEKİ ETKİSİ: AMPİRİK BİR ANALİZ. Dokuz Eylül Üniversitesi İşletme Fakültesi Dergisi, Cilt: 27 Sayı: 1, 79–101. https://doi.org/10.24889/ifede.1865913

📄 Tam Metin PDF Okuyucu

📄

PDF görüntüleyici hazırlanıyor...

Kaynakça (72)

  1. Akinwale, Y. O., Dada, A. D., Oluwadare, A. J., Jesuleye, O. A., & Siyanbola, W. O. (2012). Understanding the nexus of R&D, innovation and economic growth in Nigeria. International Business Research, 5(11), 187-196. https://doi.org/10.5539/ibr.v5n11p187
  2. Apak, S., Sarıdoğan, E., & Uçak, A. (2008). Macroeconomic determinants of innovation. In International Conference Patent and Innovation. (December 19-20), Applied Econometric Association. Tokyo, Japan.
  3. Astrachan, C. B., Patel, V. K., & Wanzenried, G. (2014). A comparative study of CB-SEM and PLS-SEM for theory development in family firm research. Journal of Family Business Strategy, 5(1), 116-128. https://doi.org/10.1016/j.jfbs.2013.12.002
  4. Awang, Z., Afthanorhan, A., & Asri, M. A. M. (2015). Parametric and non-parametric approach in structural equation modeling (SEM): the application of bootstrapping. Modern Applied Science, 9(9), 58-67. https://doi.org/10.5539/mas.v9n9p58
  5. Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of The Academy of Marketing Science, 16(1), 74-94. https://doi.org/10.1007/BF02723327
  6. Barroso, C., Cepeda, G., & Roldan, J.L. (2010). Applying maximum likelihood and PLS on different sample sizes: studies on SERVQUAL model and employee behavior model, Handbook of Partial Least Squares, Springer Handbooks of Computational Statistics, (Ed: Esposito-Vinzi, V., Chin, W., Henseler, J. and Wang, H.), Springer, Berlin.
  7. Başol, O., & Yalçın, E. C. (2021). How does the Digital Economy and Society Index (DESI) affect labor market indicators in EU countries?. Human Systems Management, 40(4), 503-512. https://doi.org/10.3233/HSM-200904
  8. Başol, O., Sevgi, H., & Yalçın, E. C. (2023). The effect of digitalization on youth unemployment for EU countries: Treat or threat?. Sustainability, 15(14), 11080. https://doi.org/ 10.3390/su151411080
  9. Başol, O., & Yalçın, E. C. (2024). Dijital ekonomi ve toplum endeksi’nin yaşam kalitesi endeksi üzerindeki etkisinin değerlendirilmesi. Paradoks Ekonomi Sosyoloji ve Politika Dergisi, 20(2), 224-240. https://izlik.org/JA35WM76MJ
  10. Buchinskaya, O. N., & Dyatel, E. P. (2019). Influence of high-technology exports and foreign charges for the use of intellectual property on economic growth. Journal of New Economy, 20(2), 114-126. https://doi.org/10.29141/2073-1019-2019-20-2-7
  11. Chin, W. W., & Newsted, P. R. (1999). Structural equation modeling analysis with small samples using partial least squares. In R. H. Hoyle (Ed.), Statistical strategies for small sample research (pp. 307–341). Thousand Oaks, CA: Sage Publications.
  12. Chin, W. W. (1998). The partial least squares approach for structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 295–336). Lawrence Erlbaum Associates Publishers.
  13. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates.
  14. Coltman, T., Devinney, T. M., Midgley, D. F., & Venaik, S. (2008). Formative versus reflective measurement models: Two applications of formative measurement. Journal of Business Research, 61(12), 1250-1262. https://doi.org/10.1016/j.jbusres.2008.01.013
  15. Crăciun, A. F., Țăran, A. M., Noja, G. G., Pirtea, M. G., & Răcătăian, R. I. (2023). Advanced modelling of the interplay between public governance and digital transformation: New empirical evidence from structural equation modelling and Gaussian and mixed-Markov graphical models. Mathematics, 11(5), 1168. https://doi.org/10.3390/math11051168
  16. Çeviker, A., & Sarıdoğan, E. (2006). Bilgi ve iletişim teknolojileri ve yenilik üretimi: OECD ülkeleri üzerine ekonometrik bir analiz. Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi, 21(1), 477-496. https://izlik.org/JA47EW49AR
  17. DESI. (2022). Digital Economy and Society Index (DESI) 2022—Thematic Chapters. Retrieved from https://digital-strategy.ec.europa.eu/en/library/digital-economy-and-society-index-desi-2022
  18. Diamantopoulos, A., & Siguaw, J. A. (2006). Formative versus reflective indicators in organizational measure development: A comparison and empirical illustration. British Journal of Management, 17(4), 263-282. https://doi.org/10.1111/j.1467-8551.2006.00500.x
  19. Du, Z. Y., & Wang, Q. (2024). Digital infrastructure and innovation: Digital divide or digital dividend?. Journal of Innovation & Knowledge, 9(3), 100542. https://doi.org/ 10.1016/j.jik.2024.100542
  20. Duarte, M. P., & de Oliveira Carvalho, F. M. P. (2024). How digital transformation shapes European Union countries’ national systems of innovation: A Configurational moderation approach. Journal of Innovation & Knowledge, 9(4), 100578. https://doi.org/ 10.1016/j.jik.2024.100578
  21. Edvardsson, B., Johnson, M. D., Gustafsson, A., & Strandvik, T. (2000). The effects of satisfaction and loyalty on profits and growth: Products versus services. Total Quality Management, 11(7), 917-927. https://doi.org/10.1080/09544120050135461
  22. European Commission. (2025a). 2025 State of the digital decade package. Retrieved from https://digital-strategy.ec.europa.eu/en/policies/2025-state-digital-decade-package
  23. European Commission. (2025b). The Digital Economy and Society Index (DESI). Retrieved from https://digital-strategy.ec.europa.eu/en/policies/desi
  24. Falk, M. (2009). High-tech exports and economic growth in industrialized countries. Applied Economics Letters, 16(10), 1025–1028. https://doi.org/10.1080/13504850701222228
  25. Fornell, C., & Larcker, D. F. (1981). Structure equation models: LISREL and PLS applied to customer exist-voice theory. Journal of Marketing Research, 18(2), 39-50.
  26. Fortea, C., Antohi, V. M., Zlati, M. L., & Meca, A. (2024). The impact of digital transformation and innovation on economic performance in the European Union. Revista de Management Comparat International, 25(5), 908-927. https://doi.org/10.24818/rmci.2024.5.908
  27. Geisser, S. (1974). A predictive approach to the random effect model. Biometrika, 61(1), 101-107. https://doi.org/10.1093/biomet/61.1.101
  28. Hair, J. F., Jr., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). Partial least squares structural equation modeling (PLS-SEM) (2nd ed.). Thousand Oaks, CA: SAGE Publications.
  29. Hair, J. F., Jr., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM) [Kindle Edition]. Thousand Oaks, CA: SAGE Publications.
  30. Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., & Thiele, K. O. (2017). Mirror, mirror on the wall: A comparative evaluation of composite based Structural Equation Modeling methods. Journal of the Academy of Marketing Science, 45(5), 616–632. https://doi.org/ 10.1007/s11747-017-0517-x
  31. Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139-152. https://doi.org/10.2753/MTP1069-6679190202
  32. Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24. https://doi.org/10.1108/EBR-11-2018-0203
  33. Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, H. A. (2009). Multivariate data analysis (7th ed.). Upper Saddle River, NJ: Pearson Prentice-Hall.
  34. Hair, J.F., Hult, G.T, Ringle, & Sarstedt, C. (2014). A primer on partial least squares structural equation modeling (PLS-SEM), London: SAGE
  35. Hair, J.F., Ringle, C.M. & Sarstedt, M. (2013). Editorial-Partial Least Squares Structural Equation Modeling: rigorous applications, better results and higher acceptance. Long Range Planning, 46(1-2), 1-12. https://doi.org/10.1016/j.lrp.2013.01.001
  36. Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial least squares structural equation modeling (PLS-SEM) using R: A workbook. Springer international publishing.
  37. Hock, M., & Ringle, C. M. (2006). Strategic networks in the software industry: An empirical analysis of the value continuum. in Proceedings of the IFSAM VIIIth World Congress. Berlin, Germany, September 28–30.
  38. Hoyle, R. H. (Ed.). (1995). Structural equation modeling: Concepts, issues, and applications. Thousand Oaks, CA: SAGE Publications.
  39. Hulland, J. (1999). Use of Partial Least Squares (PLS) in strategic management research: A review of four recent studies. Strategic Management Journal, 20(2), 195-204. https://doi.org/10.1002/(SICI)1097-0266(199902)20:2 3.0.CO;2-7
  40. Hussain, A., Iqbal, M., Khan, J. A., Khan, M., & Arafat, Q. Y. (2022). Digital transformation, innovation and sustainable growth. Competitive Social Sciences Research Journal (CSSRJ), 3(2), 403-414.
  41. Jovanović, M., Dlačić, J., & Okanović, M. (2018). Digitalization and society’s sustainable development–Measures and implications. Zbornik radova Ekonomskog fakulteta u Rijeci, 36(2), 905-928. https://doi.org/10.18045/zbefri.2018.2.905
  42. Jöreskog, K. G. (1973). A general method for estimating a linear structural equation system. In A. S. Goldberger & O. D. Duncan (Eds.), Structural equation models in the social sciences. New York, NY: Seminar Press.
  43. Kim, S., Choi, B., & Lew, Y. K. (2021). Where is the age of digitalization heading? The meaning, characteristics, and implications of contemporary digital transformation. Sustainability, 13(16), 8909. https://doi.org/10.3390/su13168909
  44. Kock, N., & Hadaya, P. (2018). Minimum sample size estimation in PLS‐SEM: The inverse square root and gamma‐exponential methods. Information Systems Journal, 28(1), 227-261. https://doi.org/10.1111/isj.12131
  45. Li, K., Kim, D. J., Lang, K. R., Kauffman, R. J., & Naldi, M. (2020). How should we understand the digital economy in Asia? Critical assessment and research agenda. Electronic Commerce Research and Applications, 44, 101004. https://doi.org/10.1016/j.elerap.2020.101004
  46. Lohmöller, J.B. (1989). Latent variable path modeling with partial least squares. Physica-Verlag, Heidelberg.
  47. Magoutas, A. I., Chaideftou, M., Skandali, D., & Chountalas, P. T. (2024). Digital progression and economic growth: Analyzing the impact of ICT advancements on the GDP of European Union countries. Economies, 12(3), 63. https://doi.org/10.3390/economies12030063
  48. Nambisan, S., Wright, M., & Feldman, M. (2019). The digital transformation of innovation and entrepreneurship: Progress, challenges and key themes. Research Policy, 48(8), 103773. https://doi.org/10.1016/j.respol.2019.03.018
  49. Nazarov, O., & Kostyuchenko, A. (2024). The bilateral linkages between innovations and digitalization. Evidence from CIS countries. Science and Innovation, 3(A1), 66-72. https://doi.org/ 10.5281/zenodo.10511035
  50. Nigam, J. K. (1986). Structuring of research institutes to promote integration with industry. In M. D. Nengu (Ed.), R&D institutes and local industry interaction: An international perspective. WAITRO.
  51. Nunnally, J. C. (1978). Psychometric theory (2nd ed.). New York, NY: McGraw-Hill.
  52. Oslo Kılavuzu (2005). Yenilik Verilerinin Toplanması ve Yorumlanması için İlkeler, (Çev: TÜBİTAK). Üçüncü Baskı, TÜBİTAK Yayınları, Ankara.
  53. Özkan, O., & Atan, M. (2023). Dijital ekonomi ve toplum indeksinin çok ölçütlü karar verme yöntemleri ile incelenmesi. Üçüncü Sektör Sosyal Ekonomi Dergisi, 58(4), 3113-3134. https://doi.org/10.15659/3.sektor-sosyal-ekonomi.23.11.2182
  54. Özsoy, S., Ergüzel, O. Ş., Ersoy, A. Y., & Saygılı, M. (2022). The impact of digitalization on export of high technology products: A panel data approach. The Journal of International Trade & Economic Development, 31/2, 277-298. https://doi.org/10.1080/09638199.2021.1965645
  55. Pu, T. (2025). How digital transformation shapes corporate R&D expenditure: An exploration of multidimensional perspectives and innovation consequences. SAGE Open, 15(3), https://doi.org/ 10.1177/21582440251349
  56. Ringle, C. M., Wende, S., & Will, A. (2005). SmartPLS 2.0 (Beta). Hamburg: University of Hamburg.
  57. Rîndaşu, S. M., Ionescu-Feleagă, L., Ionescu, B. Ş., & Topor, I. D. (2023). Digitalization and skills adequacy as determinants of innovation for sustainable development in EU countries: a PLS-SEM approach. Amfiteatru Economic, 25, 968-986. https://doi.org/ 10.24818/EA/2023/S17/968
  58. Rouf, M. A., & Akhtaruddin, M. (2018). Factors affecting the voluntary disclosure: a study by using smart PLS-SEM approach. International Journal of Law and Management, 60(6), 1498-1508. https://doi.org/10.1108/IJLMA-01-2018-0011
  59. Singh, A. K., & Jyoti, B. (2023). Impact of digitalization on global sustainable development across countries. Green and Low-carbon Economy, 1-20. https://doi.org/ 10.47852/bonviewGLCE32021482
  60. Sochuľáková, J. (2020). Research and development expenditure and their importance for innovation development. University Review, 14(4), 18-23.
  61. Solis, B. (2017). The Six Stages of Digital Transformation Maturity, San Francisco, CA: Altimeter Group.
  62. Stone, M. (1974). Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society Series B (Methodological), 36(2), 111–133. https://doi.org/10.1111/j.2517-6161.1974.tb00994.x
  63. Şahinoğlu, K. T., & Yakut, S. G. (2019). An evolution on effect of freedoms on economic performance with structural equation modeling. EKOIST Journal of Econometrics and Statistics, 30, 1-20. https://doi.org/10.26650/ekoist.2019.30.0005
  64. Taş, Ç. K., Özel, S. Ö., & Veysikarani, D. (2021). Dijital ekonominin sürdürülebilir kalkınma hedefleri üzerine etkisi: Avrupa birliği ülkeleri için bir inceleme. Abant Sosyal Bilimler Dergisi, 21(2), 55-78. https://doi.org/10.11616/basbed.vi.896953
  65. Tebaldi, E. (2011). The determinants of high-technology exports: A panel data analysis. Atlantic Economic Journal, 39, 343–353. https://doi.org/10.1007/s11293-011-9288-9
  66. Topçu, B. A. (2021). Dijital ekonomi ve göstergelerinin sürdürülebilir kalkınma üzerindeki etkisi: AB ülkeleri örneği. Uluslararası Yönetim Akademisi Dergisi, 4(2), 455-465. https://doi.org/ 10.33712/mana.958754
  67. Urbinati, A., Chiaroni, D., Chiesa, V., & Frattini, F. (2020). The role of digital technologies in open innovation processes: An exploratory multiple case study analysis. R&D Management, 50(1), 136-160. https://doi.org/10.1111/radm.12313
  68. Vărzaru, A. A., & Bocean, C. G. (2024). Digital transformation and innovation: The influence of digital technologies on turnover from innovation activities and types of innovation. Systems, 12(9), 359. https://doi.org/10.3390/systems12090359
  69. Wold, H. (1975). Soft modeling by latent variables: The nonlinear iterative partial least squares approach. In J. Gani (Ed.), Perspectives in probability and statistics (pp. 117–142). London, UK: Academic Press.
  70. Wong, K. K. K. (2013). Partial least squares structural equation modeling (PLS-SEM) techniques using SmartPLS. Marketing Bulletin, 24(1), 1-32.
  71. World Bank Group. (2016). World development report 2016: Digital dividends. World Bank Publications. Retrieved from https://openknowledge.worldbank.org/bitstream/handle/10986/23347/9781464806711.pdf
  72. World Bank. (2025). World Development Indicators. Retrieved from https://databank.worldbank.org/reports.aspx?source=world-development-indicatorsim