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Measurement of the average innovativeness change over time in the EU member states

Abstract

In the age of globalisation, implementation and commercialisation of new technologies are perceived as key elements determining competitiveness of particular countries, therefore, the growth of innovativeness is seen as the predominant direction of European Union society’s transformation into information society. The aim of the paper is to propose a procedure of measurement of innovativeness growth over time, with the Summary Innovation Index (SII) methodology as a starting point. The considered issue can be expressed by the following main question: how to measure the innovation performance dynamics for a selected group of countries (such as the EU-28, EU-15 or EU-13 countries) and for time intervals (not only for two moments of observations). This is an important inquiry since well-known innovativeness indices (SII, GII, or IOI) concentrate mainly on the provision of information about countries’ innovation performance for a specific year of observations. Due to this fact, changes occurring over longer time periods are rather neglected. The main result of the paper is a proposition of average innovativeness growth index. The index uses weights describing the employment share of a selected group of specialists (e.g.: scientists and engineers, research and development personnel) in relation to the economically active population.

Keyword : innovativeness measurement, Summary Innovation Index, innovativeness growth, index theory, European Union

How to Cite
Roszko-Wójtowicz, E., & Białek, J. (2019). Measurement of the average innovativeness change over time in the EU member states. Journal of Business Economics and Management, 20(2), 268-293. https://doi.org/10.3846/jbem.2019.8337
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Mar 14, 2019
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References

Acs, Z., Audretsch, D. B., Braunerhjelm, P., & Carlsson, B. (2009). The knowledge spillover theory of entrepreneurship. Small Business Economics, 32(1), 15-30. https://doi.org/10.1007/s11187-008-9157-3

Andersson, Å. E., & Beckmann, M. J. (2009). Economics of knowledge: theory, models and measurements. Cheltenham: Edward Elgar Publishing.

Andersson, M., & Ejermo, O. (2004). Sectoral knowledge production in Swedish regions 1993-1999. In Knowledge spillovers and knowledge management (pp. 143-170). Northampton, UK.

Balk, M. (1995). Axiomatic price index theory: a survey. International Statistical Review, 63, 69-95. https://doi.org/10.2307/1403778

Balk, B. M. (2016a). A review of index number theory. In Wiley StatsRef: statistics reference online. John Wiley & Sons, Ltd. https://doi.org/10.1002/9781118445112.stat07880

Balk, B. M. (2016b). Various approaches to the aggregation of economic productivity indices. Pacific Economic Review, 21(4), 445-463. https://doi.org/10.1111/1468-0106.12192

Białek, J. (2007). Agregatowy indeks przeciętnej wydajności pracy. Wiadomości Statystyczne, 8, 1-13.

Białek, J., & Czajkowski, A. (2008). A proposition of the system of weights for aggregative indexes on the example of the index of work efficiency. Acta Universitatis Lodziensis, Folia Oeconomica, 216, 333-341.

Bogliacino, F., Piva, M., & Vivarelli, M. (2012). R&D and employment: An application of the LSDVC estimator using European data. Economics Letters, 116, 56-59. https://doi.org/10.1016/j.econlet.2012.01.010

Bogliacino, F., & Vivarelli, M. (2012). The job creation effect of R&D expenditures. Australian Economic Papers, 51, 96-113. https://doi.org/10.1111/j.1467-8454.2012.00425.x

Chatzkel, J. L. (2004). Human capital: The rules of engagement are changing. Lifelong Learning Journal in Europe, 9(3), 139-145.

Clements, K. W., & Selvanathan, E. A. (2007). More on stochastic index numbers. Applied Economics, 39(5), 605-611. https://doi.org/10.1080/00036840500439093

Dobni, C. B. (2010). Achieving synergy between strategy and innovation: The key to value creation. International Journal of Business Science and Applied Management, 5(1), 48-58.

Drucker, P. F. (1992). The age of discontinuity: guidelines to changing our society. USA: Transaction Pubs.

European Commission. (2018). European Innovation Scoreboard 2018. Luxembourg: Publications Office of the European Union.

Feldmann, H. (2013). Technological unemployment in industrial countries. Journal of Evolutionary Economics, 23, 1099-1126. https://doi.org/10.1007/s00191-013-0308-6

Firszt, D. (2012). Uwarunkowania dyfuzji innowacji w polskiej gospodarce. Warszawa: CeDeWu.

Fisher, I. (1922). The making of index numbers. Boston: Houghton Mifflin.

Geng, X., & Huang, K. G. (2016). Informal institutions and the geography of innovation: An integrative perspective. In Global innovation and entrepreneurship: challenges and experiences from East and West (pp. 61-78). Singapore: Research Collection Lee Kong Chian School of Business. Retrieved from http://ink.library.smu.edu.sg/lkcsb_research/5124

Hall, B. H., Griuches, Z., & Hausman, I. (1986). Patents and R&D: is there a lag? International Economic Review, 27, 265-283. https://doi.org/10.2307/2526504

Horth, D. M., & Vehar, J. (2014). Becoming a leader who fosters innovation. Greensboro, NC: Center for Creative Leadership.

Huarng, K., & Mas-Tur, A. (2016). New knowledge impacts in designing implementable innovative realities. Journal of Business Research, 69(5), 1529-1533. https://doi.org/10.1080/10496491.2016.1190219

Johansson, B. (2014). Generation and diffusion of innovation. In Handbook of regional science. Berlin: Springer. https://doi.org/10.1007/978-3-642-23430-9_23

Jones, C. I. (2016). The facts of economic growth. In J. B. Taylor & H. Uhlig (Eds.), Handbook of macroeconomics (Vol. 2, pp. 3-69). https://doi.org/10.1016/bs.hesmac.2016.03.002

Karlsson, Ch., Johansson, B., & Norman, T. (2011). Innovation, technology and knowledge (CESIS Electronic Working Paper No. 247). The Royal Institute of technology Centre of Excellence for Science and Innovation Studies (CESIS).

Lu, Y., Tsang, W. K., & Peng, M. W. (2008). Knowledge management and innovation strategy in the Asia Pacific: toward an institution-based view. Asia Pacific Journal of Management, 25, 361-374. https://doi.org/10.1007/s10490-008-9100-9

Machin, S. (2001). The changing nature of labor demand in the new economy and skill-biased technology change. Oxford Bulletin of Economics and Statistics, 63, 753-776. https://doi.org/10.1111/1468-0084.63.spe1.8

Mačiulytė-Šniukienė, A., & Matuzevičiūtė, K. (2018). Impact of human capital development on productivity growth in EU Member States. Business. Management and Education, 16(1), 1-12. https://doi.org/10.3846/bme.2018.66

Madsen, J. B. (2008). Innovations and manufacturing export performance in the OECD countries. Oxford Economic Papers, 60, 143-167. https://doi.org/10.1093/oep/gpm014

Martini, M. (1992). A general function of axiomatic index numbers. Journal of the Italian Statistics Society, 1(3), 359-376. https://doi.org/10.1007/bf02589086

Niklewicz-Pijaczyńska M., & Wachowska, M. (2012). Wiedza – kapitał ludzki – innowacje. Wrocław: Prawnicza i Ekonomiczna Biblioteka Cyfrowa.

Olt, B. (1996). Axiom und Struktur in der statistischen Preisindextheorie. Frankfurt: Peter Lang.Peng, M. W. (2006). Global strategy. Cincinnati: South-Western Thomson.

Piva, M., & Vivarelli, M. (2009). The role of skills as a major driver of corporate R&D. International Journal of Manpower, 30, 835‐852. https://doi.org/10.1108/01437720911004452

Rao, D. S. P., & Hajargasht, G. (2015). Stochastic approach to computation of purchasing power parities in the International Comparison Program (ICP). Journal of Econometrics, 191(2), 414-425. https://doi.org/10.1016/j.jeconom.2015.12.012

Raymond, W., Mairesse, J., Mohnen, P., & Palm, F. (2015). Dynamic models of R&D, innovation and productivity: panel data evidence for dutch and french manufacturing. European Economic Review, 78, 285-306. https://doi.org/10.1016/j.euroecorev.2015.06.002

Roberts, M., & Vuong, V. A. (2013). Empirical modeling of R&D demand in a dynamic framework. Applied Economic Perspectives and Policy, 35(2), 185-205. https://doi.org/10.1093/aepp/ppt011

Roszko-Wójtowicz, E., & Białek, J. (2017). Evaluation of the EU countries innovative potential – multivariate approach. Statistics in Transition New Series, 18(1), 167-180. https://doi.org/10.21307/stattrans-2016-064

Roszko-Wójtowicz, E., & Białek, J. (2018). The size of the substitution bias of inflation measurement in relation to the level of innovativeness of the European Union’s economies. Econometrics. Advances in Applied Data Analysis, 22(4), 79-97.

Santos, J., Doz, Y., & Williamson, P. (2004). Is your innovation process global? Sloan Management Review, 45(4), 31-37.

Savrul, M., & Incekara, A. (2015). The effect of R&D intensity on innovation performance: a country level evaluation. Procedia – Social and Behavioral Sciences, 210, 388-396. https://doi.org/10.1016/j.sbspro.2015.11.386

Selvanathan, E. A., & Rao, D. S. P. (1994). Index numbers: a stochastic approach. Ann Arbor: The University of Michigan Press. https://doi.org/10.3998/mpub.13784

Selvanathan, E. A. (1989). A note on the stochastic approach to index numbers. Journal of Business and Economic Statistics, 7(4), 471-474. https://doi.org/10.1080/07350015.1989.10509759

Shanhong, T. (2002). Knowledge management in libraries in the twenty-first century. Journal of Science Relationship, 3, 72-77. https://doi.org/10.1515/9783110956238.88

Steinmueller, W. E. (2010). Economics of technology policy. In Handbook of the economics of innovation (pp. 1192-1214). Amsterdam: Elsevier. https://doi.org/10.1016/S0169-7218(10)02012-5

ter Haar, P. (2018). Measuring innovation: A state of the science review of existing approaches. Intangible Capital, 14(3), 409-428. https://doi.org/10.3926/ic.1254

Toffler, A., & Toffler, H. (1980). The third wave. New York: William Morrow. Retrieved from http://www.swo.ae.katowice.pl/_pdf/226.pdf

Vancauteren, M., Melenberg, B., Plasmans, J., & Bongard, R. (2017). Innovation and productivity of dutch firms: a panel data analysis. Retrieved from https://www.cbs.nl/nl-nl/achtergrond/2017/44/innovation-and-productivity-of-dutch-firms

Veugelers, R. (2010). Towards a multipolar science world: trends and impact. Scientometrics, 82, 439-456. https://doi.org/10.1007/s11192-009-0045-7

Vila, L. E., Cabrer, B., & Pavía, J. M. (2015). On the relationship between knowledge creation and economic performance. Technological and Economic Development of Economy, 21(4), 539-556. http://doi.org/10.3846/20294913.2013.876687

von der Lippe, P. (2001). Chain indices: a study in index theory. Wiesbaden: Federal Statistical Office Germany.

von der Lippe, P. (2007). Index theory and price statistics. Frankfurt: Peter Lang. https://doi.org/10.3726/978-3-653-01120-3

Węgrzyn, G. (2015). Wykształcenie i kwalifikacje pracowników jako determinant zmian w poziomie innowacyjności gospodarek. Ekonomia XXI wieku, 1(5), 10-18.

Wiig, H., & Wood, M. (1995). What comprises a regional innovation system? – an empirical study (STEP Working Paper No. 01). Retrieved from https://www.researchgate.net/publication/275614827_Innowacyjnosc_Input-Output_regionow_grupy_wyszehradzkiej

Williams, R., Slack, R., & Stewart, J. (2000). Social learning in multimedia: final report. EC targeted socio-economic research project: 4141 PL 951003. Edinburgh, Scotland: Research Centre for Social Sciences, The University of Edinburgh.

Witkowski, B., & Weresa, M. A. (2006). Wpływ innowacji na konkurencyjność branż polskiego prze-mysłu. In Polska. Raport o konkurencyjności 2006. Rola innowacji w kształtowaniu przewag konkurencyjnych (pp. 202-214). Szkoła Głowna Handlowa w Warszawie, Warszawa.