Efficiency of the research and development activities of technical universities in Poland

Authors

  • Irena Łącka West Pomeranian University of Technology in Szczecin
  • Łukasz Brzezicki University of Gdańsk

DOI:

https://doi.org/10.15584/nsawg.2020.3.13

Keywords:

R&D, efficiency, universities, DEA

Abstract

In the 21st century knowledge-based economy, long-term economic growth and development depend on the ability to use the knowledge and technology so as to create product, process, organisational, marketing and even social innovations. The knowledge and technology, human resources and social capital (facilitating the transfer of technology from the world of science to the economy), comprise the most important production factors today. Research and development (R&D) activities are among the diverse determinants affecting the economy’s ability to innovate. They are carried out by public technical universities. One of the tasks that these entities face is to conduct basic, industrial (applied) research and development works. Their results can then be transferred to industrial and service enterprises as novel solutions. Research and development activities of universities are financed mainly from public sources, which suggests the need to assess the efficiency of this task. This can be done with the use of various methods, e.g. the non-parametric DEA method. The purpose of the paper is to measure the efficiency of research and development activities of public technical universities in Poland with the aid of the DEA method. The fourteen universities which in the years 2015–2017 reported to the Ministry of Science and Higher Education (MNiSW) were included in the study. The efficiency of the universities in filing new patent solutions and being granted patents was analysed. The results acquired indicate very low and low efficiency of most Polish technical universities. This is due both to a small number of patent applications and a small number of patents granted. In the examined period, the group of most efficient technical universities in both aspects comprised 4 to 5 universities.

References

Aghion, Ph., Howitt, P. (1992). A Model of Growth through Creative Destruction. Econo-metrica, 60/2, 323–351. DOI:10.2307/2951599.

Aghion, Ph., Howitt, P. (1999). Endogenous Growth Theory. London: MIT Press.

Anderson, T. R., Daim, T. U., Lavoie, F. F. (2007). Measuring the efficiency of university technology transfer. Technovation, 27, 306–318. DOI: 10.1016/j.technovation.2006.10.003.

Berbegal-Mirabent, J. (2018). The influence of regulatory frameworks on research and knowledge transfer outputs: An efficiency analysis of Spanish public universities. Journal of Engineering and Technology Management, 47, 68–80. DOI: 10.1016/j. jengtecman.2018.01.003.

Chuanyi, W., Xiaohong, L., Shikui, Z. (2016). The Relative Efficiencies of Research Universities of Science and Technology in China: Based on the Data Envelopment Analysis and Stochastic Frontier Analysis. Eurasia Journal of Mathematics, Science and Technology Education, 12(10), 2753–2770. DOI: 10.12973/eurasia.2016.02302a.

Cioacă, S., Nedelcu, A. C. (2015). R&D activities’ impact on economic growth: case study on Romania. International Journal of Education and Research, 3(3), 569–578.

Cooper, W. W., Seiford, L. M., Tone, K. (2007). Data Envelopment Analysis. A Comprehensive Text with Models, Applications, References and DEA-Solver Software. New York: Springer. DOI: 10.1007/978-0-387-45283-8.

Czerniak, J. (2013). Polityka innowacyjna w Polsce. Analiza i proponowane kierunki zmian. Warszawa: Difin.

De Witte, K., López-Torres, L. (2017). Efficiency in education: a review of literature and a way forward. Journal of the Operational Research Society, 68(4), 339–363. DOI: 10.1057/jors.2015.92.

Eicher, T. S., Turnovsky, S. J. (1999). Non-scale models of economic growth. Economic Journal, 109, 349–415. DOI: 10.1111/1468-0297.00454.

European Innovation Scoreboard (2019). Luxembourg: European Commission. Retrieved from: https://ec.europa.eu/docsroom/documents/38781 (2020.11.04).

Flegg, A. T., Allen, D. O., Field, K., Thurlow, T. W. (2004). Measuring the efficiency of British universities: a multi-period data envelopment analysis. Education Economics, 12, 231–249. DOI: 10.1080/0904529042000258590.

Florczak, W. (2009). Koncepcja wzrostu endogenicznego i gospodarki opartej na wiedzy w naukach ekonomicznych. Studia Prawno-Ekonomiczne, LXXX, 215–239.

Florczak, W. (2013). Modelowanie zrównoważonego rozwoju w makroekonomicznych modelach gospodarki Polski. Acta Universitatis Lodzienzis Folia Oeconomica, 294, 319–369.

Jones, C. (1995). R&D Based Models of Economic Growth. Journal of Political Economy, 103(4), 759–784. DOI: 10.1086/262002.

Khalozadeh, F., Kazemi, S. A., Movahedi, M., Jandaghi, G. (2011). Reengineering University – Industry Interactions: Knowledge–based Technology Transfer Model. Euro-pean Journal of Economics, Finance and Administrative Sciences, 40, 47–58.

Kodama, T. (2008). The role of intermediation and absorptive capacity in facilitating University-industry linkages an empirical study of TAMA in Japan. Research Policy, 37(8), 1224–1240. DOI: 10.1016/j.respol.2008.04.014.

Kuna-Marszałek, A., Lisowska, R. (2013). Działalność badawczo-rozwojowa jednostek naukowych i badawczo-rozwojowych w regionie łódzkim. Studia Prawno-Ekonomiczne, t. LC, 29–46.

Leitner, K.-H., Prikoszovits, J., Schaffhauser-Linzatti, M., Stowasser, R., Wagner, K. (2007). The impact of size and specialisation on universities’ department performance: a DEA anal sis applied to Austrian universities. Higher Education, 53, 517–538. DOI: 10.1007/s10734-006-0002-9.

Liu, J. S., Lu, L. Y. Y., Lu, W-M., Lin, B. J. Y. (2013). A survey of DEA applications. Omega, 41, 893–902. DOI: 10.1016/j.omega.2012.11.004.

Mok, K. H. (2005). Globalization and educational restructuring. University merging and changing governance in China. Higher University, 50, 57–88. DOI: 10.1007/s10734-004-6347-z.

Nowacki, F. (2013). Aktywność przedsiębiorcza uniwersytetu trzeciej generacji – uniwersytet czy przedsiębiorstwo. In: D. Burawski (Ed.), Uniwersytet trzeciej generacji. Stan i perspektywy rozwoju (pp. 25–38). Poznań: Europejskie Centrum Wspierania Przedsiębiorczości.

Obwieszczenie Marszałka Sejmu Rzeczypospolitej Polskiej z dnia 30 października 2017 r. w sprawie ogłoszenia jednolitego tekstu ustawy – Prawo o szkolnictwie wyższym (DzU 2017 poz. 2183).

Obwieszczenie Marszałka Sejmu Rzeczypospolitej Polskiej z dnia 8 grudnia 2017 r. w sprawie ogłoszenia jednolitego tekstu ustawy o zasadach finansowania nauki (DzU 2018 poz. 87).

Podręcznik Frascati 2015. Zalecenia dotyczące pozyskiwania i prezentowania danych z zakresu działalności badawczo-rozwojowej. (2018). Warszawa: GUS.

RAD-on (2020). Projekty naukowe w wybranym roku. Retrieved from: https://radon.nauka.gov.pl/raporty/szkolnictwo-wyzsze-i-nauka (2020.11.04).

Prędki, A. (2012). Geneza zbiorów możliwości produkcyjnych wykorzystywanych w DEA. Zeszyty Naukowe Uniwersytetu Ekonomicznego w Poznaniu, 241, 126–137.

Prodan, I. (2005). Influence of Research and Development Expenditures on Number of

Patent Applications: Selected Case Studies in OECD Countries and Central Europe, 1981–2001. Applied Econometrics and International Development, 5–4, 5–20.

Romer, P. (1990a). Endogenous technological change. Journal of Political Economy, 98(5), 71–102.

Romer, P. M. (1990b). Human capital and growth: theory and evidence. Carnegie Rochester Conference Series on Public Policy, 32, 251–286. DOI: 10.1016/0167-2231(90)90028-J.

Rutkowska, A. (2013), Teoretyczne aspekty efektywności – pojęcie i metody pomiaru. Zarządzanie i Finanse, 11(1, 4), 439–453.

Seppo, M., Lilles, A. (2012). Indicators measuring university-industry cooperation. Discussion on Estonian Policy, 20(1), 204–225. DOI: 10.15157/tpep.v20i1.782.

Spencer, J. W. (2001). How relevant is university-based scientific research to private high-technology firms? A United States – Japan comparison. Academy of Management Journal, 44, 432–440. DOI: 10.2307/3069465.

Szmal, A. (2012). Identyfikacja dóbr intelektualnych podlegających komercjalizacji. Zeszyty Naukowe Politechniki Śląskiej. Seria: Organizacja i Zarządzanie, 60, 321–333.

Tone, K., Tsutsui, M. (2010). Dynamic DEA: A slacks-based measure approach. Omega, 38, 145–156. DOI:10.1016/j.omega.2009.07.003.

Wissema, J. G. (2005). Technostarterzy dlaczego i jak? Warszawa: PARP.

Wolszczak-Derlacz, J. (2013). Efektywność naukowa, dydaktyczna i wdrożeniowa publicznych szkół wyższych w Polsce – analiza nieparametryczna. Gdańsk: Wydawnictwo Politechniki Gdańskiej.

Wunsch-Vincent, S. (2012). Accounting for science–industry collaboration in innovation: existing metrics and related challenges. In: S. Dutta (Ed.), The Global Innovation Index 2012. Stronger innovation linkages for global world (pp. 97–108). Fontaine- bleau: WIPO.

Yang, G.-L., Fukuyama, H., Song, Y.-Y. (2018). Measuring the inefficiency of Chinese research universities based on a two-stage network DEA model. Journal of Informetrics, 12(1), 10–30. DOI: 10.1016/j.joi.2017.11.002.

Downloads

Published

2020-11-13

How to Cite

Łącka, I., & Brzezicki, Łukasz. (2020). Efficiency of the research and development activities of technical universities in Poland. Social Inequalities and Economic Growth, 3(63), 258–274. https://doi.org/10.15584/nsawg.2020.3.13

Issue

Section

Articles