Research and development inputs and innovation performance of European Union economies

Authors

  • Iwona Skrodzka Uniwersytet w Białymstoku

DOI:

https://doi.org/10.15584/nsawg.2024.1.3

Keywords:

R&D inputs, innovativeness of economy, innovation performance, structural equation modelling, PLS-SEM

Abstract

The paper discusses the issue of the innovativeness of European Union countries. The innovativeness of an economy is defined as the ability to create and implement innovations. The purpose of the research is to examine the strength and direction of the influence of R&D inputs on the innovation performance of EU economies. Innovation performance is one of two categories describing the innovativeness of the economy. It expresses the outcome stemming from a combination of society’s creativity and the financial assets of a given economic and institutional environment. In turn, R&D inputs are an important factor determining the innovation capacity, i.e. the extent to which an economy is capable of creating and commercialise new ideas. In the paper, R&D inputs are considered in two categories: financial capital and human capital. The main hypothesis to be verified is that R&D inputs have a positive, statistically significant impact on the innovation performance of the economy. PLS-SEM (partial least squares structural equation modelling) was used to achieve the research goal and verify the formulated hypothesis. PLS-SEM models were estimated based on cross-sectional data from 27 EU countries. The data related to three years: 2017, 2019 and 2021. The modelling results indicated that, in the analysed period, R&D inputs had a strong, positive, statistically significant impact on the innovation performance of the economies in EU countries. Both financial and human capital had a significant, positive impact on the innovation performance of the analysed economies, with financial capital being more important. The paper also ranks EU countries according to R&D inputs, financial and human capital, and the innovation performance of the economy.

References

Baum, Ch.F., Lööf, H., Nabavi, P., Stephan, A. (2017). A new approach to estimation of the R&D – innovation – productivity relationship. Economics of Innovation and New Technology, 26(1–2), 121–133. DOI: 10.1080/10438599.2016.1202515.

Becker, J.-M., Klein, K., Wetzels, M. (2012). Hierarchical latent variable models in PLS-SEM: guidelines for using reflective-formative type models. Long Range Planning, 45(5), 359–394. DOI: 10.1016/j.lrp.2012.10.001.

Borowiecki, R., Siuta-Tokarska, B. (2017). Problemy innowacyjności gospodarki Polski, ze szczególnym uwzględnieniem działalności badawczo-rozwojowej. Nierówności Społeczne a Wzrost Gospodarczy, 50(2), 163–176. DOI: 10.15584/nsawg.2017.2.10.

Crépon, B., Duguet, E., Mairesse, J. (1998). Research and development, innovation and productivity: an econometric analysis at the firm level. Economics of Innovation and New Technology, 7(2), 115–158. DOI: 10.1080/10438599800000031.

Ciborowski, R.W. (2016). Międzynarodowy transfer technologii a innowacyjność krajów Europy Środkowo-Wschodniej. Białystok: Wydawnictwo PTE.

Ciborowski, R.W., Skrodzka, I. (2020). International technology transfer and innovative changes adjustment in EU. Empirical Economics, 59(3), 1351–1371. DOI: 10.1007/ s00181-019-01683-8.

Danguy, J., de Rassenfosse, G., van Pottelsberghe de la Potterie, B. (2009). The R&D-patent relationship: An industry perspective. European Investment Bank Papers, 14(1), 170–195.

European Commission. (2023). European Innovation Scoreboard 2023. Luxembourg: Publications Office of the European Union. DOI: 10.2777/119961.

Fagerberg, J., Srholec, M., Verspagen, B. (2010). Innovation and Economic Development. W: B.H. Hall, N. Rosenberg (red.), Handbook of the Economics of Innovation, t. 2 (s. 833–872). Amsterdam: North-Holland. DOI: 10.1016/S0169-7218(10)02004-6.

Freeman, C. (2002). Continental, national and sub-national innovation systems – complementarity and economic growth. Research Policy, 31(2), 191–211. DOI: 10.1016/ S0048-7333(01)00136-6.

Gardocka-Jałowiec, A. (2012). Nakłady na działalność badawczo-rozwojową a innowacyjność polskiej gospodarki. Ekonomista, 1, 79–99.

GUS. (2022). Zeszyt metodologiczny. Działalność badawcza i rozwojowa. Szczecin/Warszawa: Urząd Statystyczny w Szczecinie.

Hair, J.F., Hult, G.T.M., Ringle, C.M., Sarstedt, M. (2022). A primer on partial least squares structural equation modelling (PLS-SEM). Thousand Oaks: Sage.

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. DOI: 10.1108/ EBR-11-2018-0203.

Henseler, J., Ringle, C.M., Sarstedt, M. (2012). Using partial least squares path mode-ling in international advertising research: basic concepts and recent issues. W: S. Okazaki (red.), Handbook of research in international advertising (s. 252–276). Cheltenham: Edward Elgar. DOI: 10.4337/9781781001042.00023.

Krawczyk, M. (2014). Wydatki przedsiębiorstw na działalność badawczo-rozwojową a pomiar innowacyjności. Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu, 326, 115–122.

Mairesse, J., Mohnen, P. (2004). The Importance of R&D for Innovation: A Reassessment Using French Survey Data. The Journal of Technology Transfer, 30, 183–197. DOI: 10.1007/s10961-004-4365-8.

OECD. (2006). Podręcznik Oslo. Zasady gromadzenia i interpretacji danych dotyczących innowacji, wyd. 3. Warszawa: Ministerstwo Nauki i Szkolnictwa Wyższego.

OECD. (2015). Frascati manual 2015: guidelines for collecting and reporting data on research and experimental development, The measurement of scientific, technological and innovation activities. Paris: OECD Publishing. DOI: 10.1787/9789264239012-en.

OECD. (2017). OECD Science, Technology, and Industry Scoreboard 2017: The digital transformation. Paris: OECD Publishing. DOI: 10.1787/9789264268821-en.

OECD/Eurostat. (2018). Oslo Manual 2018: guidelines for collecting, reporting and using data on innovation, 4th edition, The measurement of scientific, technological and innovation activities. Paris: OECD Publishing/Luxembourg: Eurostat. DOI: 10.1787/9789264304604-en.

Pangsy-Kania, S. (2007). Polityka innowacyjna państwa a narodowa strategia konkurencyjnego rozwoju. Gdańsk: Wydawnictwo Uniwersytetu Gdańskiego.

Penc, J. (1999). Innowacje i zmiany w firmie. Warszawa: Placet.

Poznańska, K. (2018). Działalność badawczo-rozwojowa determinantą innowacyjności przedsiębiorstw przemysłowych w Polsce. Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu, 538, 347–358.

Rogowski, J. (1990). Modele miękkie. Teoria i ich zastosowanie w badaniach ekonomicznych. Białystok: Wydawnictwo Filii UW w Białymstoku.

Sarstedt, M., Hair, J.F., Cheah, J.-H., Becker, J.-M., Ringle, C.M. (2019). How to specify, estimate, and validate higher-order constructs in PLS-SEM. Australian Marketing Journal, 27(3), 197–211. DOI: 10.1016/j.ausmj.2019.05.003.

Weresa, M.A. (2012). Systemy innowacyjne we współczesnej gospodarce światowej. Warszawa: PWN.

Weresa, M.A. (2014). Polityka innowacyjna. Warszawa: PWN.

WIPO. (2023). Global Innovation Index 2023.Innovation in the face of uncertainty. Geneva: WIPO. DOI:10.34667/tind.48220.

Wold, H. (1982). Soft modeling: the basic design and some extensions. W: K.G. Jöreskog, H. Wold (red.), Systems under indirect observations: causality, structure, prediction, t. 2 (s. 1–54). Amsterdam: North-Holland.

Published

2024-03-31

How to Cite

Skrodzka, I. (2024). Research and development inputs and innovation performance of European Union economies. Social Inequalities and Economic Growth, (77), 56–74. https://doi.org/10.15584/nsawg.2024.1.3

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Articles