The innovation gap of national innovation systems in the European Union

Dworak, Edyta; Grzelak, Maria Magdalena Article The innovation gap of national innovation systems in the European Union Comparative Economic Research. Central and Eastern Europe Provided in Cooperation with: Institute of Economics, University of Łódź Suggested Citation: Dworak, Edyta; Grzelak, Maria Magdalena (2023) : The innovation gap of national innovation systems in the European Union, Comparative Economic Research. Central and Eastern Europe, ISSN 2082-6737, Lodz University Press, Lodz, Vol. 26, Iss. 1, pp. 7-20, https://doi.org/10.18778/1508-2008.26.01 This Version is available at: https://hdl.handle.net/10419/289724 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by-nc-nd/4.0/ 7 TheInnovationGapofNationalInnovation SystemsintheEuropeanUnion Edyta Dworak https://orcid.org/0000‑0001‑9789‑6752 Ph.D., Assistant Professor, University of Lodz, Department of Institutional Economics and Microeconomics Lodz, Poland, e‑mail: [email protected] Maria Magdalena Grzelak https://orcid.org/0000‑0003‑4353‑9893 Ph.D., Assistant Professor, University of Lodz, Department of Economic and Social Statistics, Lodz, Poland e‑mail: [email protected] Abstract The main aim of the paper is to assess the innovation gap between the national innovation systems (NIS) of the European Union (EU) and the average level of innovation of EU econo‑ mies. The study takes into account NIS identified in the literature, i.e., (a) developed systems and (b) developing systems. In the theoretical part of the paper, the literature in the fields of NIS and the innovation gap is reviewed, the definitions and selected classifications of NIS around the world are presented, and the concept of the innovation gap between countries is defined. In the empirical part, the le‑ vel of innovation in EU economies is assessed using Hellwig’s synthetic development indicator. In order to measure the level of innovation in individual NISs, arithmetic means of national values of the synthetic measure of development (innovation) are used. The innovation gap is calcula‑ ted as the quotient between the level of innovation of individual NISs analyzed in the study and the average level of innovation in EU economies. The study covered 2010 and 2021. The paper formulates the following research hypothesis: the level of innovation in EU economies is determined by the type of NIS. Consequently, developing system countries are less innovati‑ ve and, thus, are characterized by an innovation gap in relation to the EU average. The results of the study confirm the hypothesis. The relationship between the innovation level of the EU economies and the type of NIS, as well as the assessment of the innovation gap between the na‑ tional innovation systems of the EU and the average level of innovation of the EU economies, constitute the value‑added of the paper. Comparative Economic Research. Central and Eastern Europe Volume 26, Number 1, 2023 https://doi.org/10.18778/1508‑2008.26.01 © by the author, licensee University of Lodz – Lodz University Press, Poland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license CC‑BY‑NC‑ND 4.0 (https://creativecommons.org/licenses/by‑nc‑nd/4.0/) Received: 3.02.2022. Verified: 8.08.2022. Accepted: 16.01.2023 8 Edyta Dworak, Maria Magdalena Grzelak innovation gap JEL: O30, O31, O43 Introduction Forseveral decades, innovations have been animportant area ofresearch foreconomists worldwide. Onamicroeconomic scale, theimplementation ofinnovations leads toanin‑ crease inenterprises’ competitiveness through lowering production costs, improving thequality ofproducts andexpanding their range, or better meeting consumers’ needs. These activities increase thecompetitiveness ofenterprises and, consequently, entire economies. Onamacroeconomic scale, innovations are perceived as one ofthemain factors ofeconomic growth anddevelopment. Innovation is always theresult ofthein‑ teraction between people, organizations, andtheir environment. This understanding ofinnovation is inline with thenational innovation system (NIS) concept, which plays animportant role intheinnovation policy ofall developed market economies. Themain aim ofthepaper is toassess theinnovation gap between theNISs oftheEuro‑ pean Union (EU) andtheaverage level ofinnovation ofEU economies. Thestudy takes intoaccount theNISs identified intheliterature (Godinho, Mendonca, andPereira 2003), i.e., (a)developed systems, which include dynamic, stable, andunevenly developed systems, and(b) developing systems, comprising catching up andunbalanced systems. Thepaper formulates thefollowing research hypothesis: thelevel ofinnovation inEU economies is determined by thetype ofNIS. Consequently, developing sys‑ tem countries are less innovative andare thus characterized by aninnovation gap inrelation totheEU average. Theresults ofthestudy confirm thehypothesis. Therelationship between theinnovation level oftheEU economies andthetype ofNIS, as well as theassessment oftheinnovation gap between thenational inno‑ vation systems oftheEU andtheaverage level ofinnovation oftheEU economies, constitute thevalue‑added ofthepaper. Inthetheoretical part ofthepaper, theliterature inthefields ofNISs andtheinnova‑ tion gap is reviewed, thedefinitions andselected classifications ofNISs around theworld are presented, andtheconcept oftheinnovation gap between countries is defined. Intheempirical part, thelevel ofinnovation inEU economies is assessed using Hellwig’s synthetic development indicator, called thesynthetic measure ofdevelopment (SMD) (Panek 2009). Inorder tomeasure thelevel ofinnovation inindividual NISs, arithme‑ tic means ofnational values ofthesynthetic measure ofdevelopment (innovation) are used. Theinnovation gap is calculated as thequotient between thelevel ofinnovation oftheindividual NISs andtheaverage level ofinnovation inEU economies. Keywords: innovation, innovativeness of an economy, national innovation system, 9 The Innovation Gap of National Innovation Systems in the European Union Thestudy covered 2010and2021. Forseveral variables, themost recent data come from 2020. Thechoice ofyears was dictated by theavailability ofthemost recent statistical data andthedesire toshow theinnovation gap ofNIS over anextended time horizon. Thedata used inthestudy were obtained from Eurostat andOECD databases. Theconceptandclassificationsofthenationalinnovation system.Thedefinitionoftheinnovationgap TheNIS concept was created inthelate 1980s andhas become thefocus ofthefollow‑ ing economists: Freeman (1992), Lundvall (1992), Nelson andRosenberg (1993), Patel andPavitt (1994) andEdquist (1997). Research onNIS continues inthe21 st century. Thedefinitions formulated by contemporary authors are presented inTable1. Table 1. Definitions of the national innovation system Anetworkofeconomicagents,togetherwiththeinstitutionsandpoliciesthatinfluence theirinnovativebehaviorandperformance. Mytelka (2003) An evolutionary system in which enterprises in interaction with each other and supported by institutions and organizations such as industry associations, R&D, innovation and productiv‑ ity centers, standard setting bodies, universities and vocational training centers, information gathering and analysis services, and banking and other financing mechanisms play a key role in bringing new products, new processes and new forms of organization into economic use. Wangwe (2003) Creating an efficient innovation system and business environment that encourages inno‑ vation and entrepreneurship, comprising firms, science and research centers, universities, think tanks, and other organizations that can tap into and contribute to the growing stock of global knowledge, which can adapt it to local needs, and that can use it to create new products, services, and ways of doing business. Goel et al. (2004) A network of interacting policies, institutions and organizations whose holistic functionali‑ ty depends on the quality of cooperation between the various component parts. Manzini (2012) A unity of enterprises of various patterns of ownership that individually or through interac‑ tion with each other provide the formation and dispersion of innovation technologies within a definite state; […] it encourages the implementation of the derived technologies into pro‑ duction and development of new products saleable in the world market; among such organi‑ zations there are scientific institutions (R&D institutes, institutes of higher education, private laboratories, scientific departments of corporations – all of them can be summarized under the term „creators of innovation”); then, „infrastructural” enterprises–technoparks, innovative technology centers, venture funds; agencies conditioning the innovation climate and govern‑ mental bodies: ministries and specialized departments; the small, medium and big businesses as the first and the final consumer and as one of the primary initiators of innovation. Garifullin, Ablaev (2015) A multilevel concept where national, regional and sectoral innovation systems can coexist and co‑evolve together in the same country. Carayannis, Grigoroudis, Goletsis (2016) 10 Edyta Dworak, Maria Magdalena Grzelak Anetworkofeconomicagents,togetherwiththeinstitutionsandpoliciesthatinfluence theirinnovativebehaviorandperformance. Mytelka (2003) The institutions, human capital and interactions among them that facilitate the creation and diffusion of knowledge. Maloney (2017) An innovation system encompasses all the organizations and institutions involved in the innovation process and the na onal innovation system gives special attention to those institutions and organizations which are located in or rooted in a nation state. The system is open and one crucial characteristic of the national innovation system is its capacity to absorb and use knowledge developed abroad. Chaminade, Lundvall, Haneef (2018) Source: the authors’ own compilation. Theliterature onthesubject also includes many typologies ofnational innovation sys‑ tems, distinguished based onvarious criteria (Schmoch, Rammer, andLegler 2006; We‑ resa 2014, pp.66–70), e.g., from thepoint ofview ofthetype ofinnovation that dom‑ inates inagiven system, andtheareas that determine thedevelopment ofthesystem (Patel andPavitt 1991, pp.35–58; Schmoch, Rammer, andLegler 2006). Thecriteria also include institutional factors (e.g., educational, scientific, technological, andinnova‑ tion regulations) (Amable, Barre, andBoyer 2008; Kotlebova, Arendas, andChovancova 2020, pp.717–734) andhow science andtheeconomy interact (OECD 2000, pp.168–172; Bal‑Domańska, Sobczak, andStańczyk 2020; Gorączkowska 2020). Anattempt atamulti‑level NIS typology is auniversal approach using hierarchical clus‑ ter analysis based onthefollowing classification criteria (developed by Godinho, Men‑ donça, andPereira, andis hereinafter referred toas theGMP classification) (Weresa 2012; Dworak, Grzelak, andRoszko‑Wójtowicz 2022): • theinternal market, described by thefollowing indicators: GDP inabsolute terms, GDP per capita, andpopulation density; • institutional conditions, measured by income inequality, life expectancy, demograph‑ ic structure, andcorruption index; • tangible andintangible investments, as shown by expenditure onR&D andeducation per capita andas a%ofGDP; • theoretical andapplied knowledge, described interms ofthepercentage ofthepopula‑ tion with secondary andtertiary education, thepercentage ofstudents ofexact scienc‑ es, thenumber ofresearch workers inrelation tototal employment, andthenumber ofpublications per capita; • thestructure oftheeconomy, presented by theshare ofhigh‑tech industries inex‑ ports andGDP, andtheturnover ofdomestic R&D companies onaglobal scale inre‑ lation toGDP; 11 The Innovation Gap of National Innovation Systems in the European Union • connections between theeconomy andtheenvironment, measured by thebalance offor‑ eign trade anddirect investment inrelation toGDP, broadband Internet connections; •knowledge diffusion, described by thefollowing indicators: Internet access, cellular network density, number ofISO 9000 andISO 1400 certificates per capita; • innovation, measured by thenumber ofpatents andtrademarks per capita. Based ontheabove‑mentioned measures, two main types ofNIS were distinguished: (1) developed innovative systems, (2) developing innovative systems. Within these NIS types, three sub‑types are distinguished ineach group, some ofwhich have their types listed.1 This typology is presented inTable2. Table 2. Typology of national innovation systems according to Godinho, Mendonça, and Pereira (the GMP classification) NIS Type NIS Subtype NIS Kind CountriesbelongingtoagivenNISType T.0 Hongkong T.1. Developed innovation systems T.1.1. Dynamic NIS Ireland, the Netherlands, Switzerland, Finland, Sweden, Singapore T.1.2. Stable functioning NIS T.1.2.1. Germany, Great Britain, France, Italy, South Korea, Taiwan T.1.2.2. USA, Japan T.1.2.3. Canada, Norway, Australia, Austria, New Zealand, Spain T.1.3. Unevenly developed NIS Denmark, Belgium, Luxembourg T.2. Developing innovation systems T.2.1. Catching up NIS T.2.1.1. Portugal, Greece, Poland, Hungary, the Czech Republic, Slovenia T.2.1.2. Malaysia, Malta T.2.1.3. Latvia, Estonia, Lithuania, Slovakia, Ukraine T.2.2. Unbalanced NIS T.2.2.1. Russia T.2.2.2. China, Brazil, South Africa, Thailand, Argentina, India, Mexico T.2.2.3. Turkey, Colombia, Bulgaria, Indonesia, the Philippines, Peru, Romania T.2.2.4. Egypt, Cyprus, Chile, Venezuela T.2.3. Unshaped NIS T.2.3.1. Algeria, Iran, Vietnam, Morocco, Bangladesh T.2.3.2. Pakistan, Kenya, Ethiopia, Tanzania, Sudan, Nigeria, Congo, Myanmar Source: Weresa 2012, p. 46; Godinho, Mendonca, and Pereira 2003. 1 The classification includes all the countries that currently belong to the EU, with the exception of Croatia. 12 Edyta Dworak, Maria Magdalena Grzelak Thetheoretical background for theinnovation gap is formed by different studies onthetechnological gap intheworld economy (Posner 1961, pp.323–341; Krugman 1979) andrecently inCentral European countries (Kubielas 2013; 2016, pp.7–10; Ko‑ walski 2020, pp.1966–1981). Kubielas (2013, p.137) defines theinnovation gap as thedifferences intechnological advancement between countries. He proposes anumber ofmethods tomeasure its size, e,g, thedistance between thelevel oftechnological activity ofaparticular country andthecountries atthetechnological frontier, calculated either as aratio ofthenumber ofpatents per capita or theshare ofresearch expenditure invalue‑added or national in‑ come. Theliterature review also shows indirect measures such as theshare ofhigh‑tech products inexports inrelation toasimilar indicator forthetechnology frontier (Sałama‑ ga 2020, p.362), therelationship between theperformance (labor productivity) ofagiven branch ofthecountry inrelation tothecountry onthetechnological frontier or inag‑ gregate terms therelation ofGDP per capita tothecorresponding indicator ofthetech‑ nological frontier (Kubielas 2013, p.137). Thelast two approaches identify thetechnological gap with aproductivity or income gap. Theglobal technological frontier is deemed tobe theGDP level that can be achieved using thegiven inputs ofcapital andlabor andthebest possible technologies (Growiec 2012). This level ofGDP is now achieved by theU.S. economy, inwhich thedistribution ofspecialization (between thefour Pavitt sectors) is thestandard foratechnology leader (Kubielas 2016, p.7). Thehighest competitive advantages are demonstrated by thesci‑ ence‑based sector, followed by thespecialized supplier sectors; theconsecutive sectors; thescale‑intensive andtraditional, supplier‑dominated sectors are characterized by neg‑ ative indices oftherevealed comparative advantage, ofwhich thetraditional is thelow‑ est onthescale ofrevealed advantages oftheU.S. economy (Kubielas 2013, p.153). Intheliterature, there is also theconcept oftheinnovation gap, understood as thedistance ofindividual economies tothemodern technological frontier, which is identified with thelast stage ofsocio‑economic development ofeconomies, i.e., theemergence ofaknowl‑ edge‑based economy (Dworak 2012, pp.27–32). Toinvestigate this approach tothein‑ novation gap, there should be apoint ofreference, which involves theinitial conditions ofbuilding aknowledge‑based economy formulated intheliterature (e.g., Kleer 2009). TheUnited Nations defines theinnovation gap generally as thedistance between those who have access totechnologies andknow how touse them effectively andthose who donot (Kraciuk 2006). Theinnovation gap can be considered from theperspective ofcre‑ ating new technology inthehome country, as well as from theperspective ofits transfer from other countries andeffective adaptation totheneeds andnational capabilities. Insummary, measuring theinnovation gap means estimating thedistance between theeconomy andthemost developed economies ofEurope andtheworld, known today 13 The Innovation Gap of National Innovation Systems in the European Union as knowledge‑based economies, inmany areas, e.g., innovation, education, andthein‑ stitutional system. Estimating theinnovation gap is possible by comparing synthetic measures ofinnovation (Mielcarek 2013; Weresa 2014, p.64). Assessingtheinnovationgapbetweenthenational innovationsystemsintheEuropeanUnionbased onanoriginalsyntheticindicatorofeconomicinnovation Theinnovation level ofEU economies in2010and2021 was first assessed (forsever‑ al variables mentioned below, i.e., X1, X2, X3, X4, andX5, themost recent data come from 2020). Thecomplexity ofinnovation means that there is no one‑size‑fits‑all indi‑ cator tomeasure it atthemacroeconomic level. Weassessed innovation using Zellwig’s synthetic development indicator, called thesynthetic measure ofdevelopment (SMD). Theselection ofpotential diagnostic variables was based ontheOslo methodology (OECD/Eurostat 2018). Theinput data set included 13 variables –potential diagnostic indicators (Eurostat n.d.): X1 – R&D expenditure ineuro per capita –all sectors, X2 – R&D expenditure ineuro per capita –business enterprise sector, X3 – R&D expenditure ineuro per capita –government sector, X4 – R&D expenditure ineuro per capita –high education sector, X5 – High‑tech patent applications totheEPO (European Patent Office) per million inhabitants, X6 – EU trademark applications per million population, X7 – Students intertiary education by age group as a%ofthecorresponding age pop‑ ulation, X8 – Total high‑tech trade inmillion euros as %oftotal (imports), X9 – R&D personnel as %ofthelabor force, X10 – High‑tech exports as %oftotal exports, X11 – Employment inknowledge‑intensive activities as %oftotal employment, X12 – Product or process innovative enterprises engaged incooperation as %ofinno‑ vative enterprises, X13 – Triadic patent families per million inhabitants. 14 Edyta Dworak, Maria Magdalena Grzelak Theset ofpotential diagnostic variables was verified interms oftheinformation value ofthevariables. This verification was performed using statistical procedures that took intoaccount thediscriminant andinformation capacity ofthevariables (Panek 2009, pp.18–23). Three indicators were removed from theset ofpotential diagnostic indica‑ tors: X11 –due tolow volatility andX2 andX4 –due totoo much correlation with other indicators. Ultimately, theset ofdiagnostic features comprised thefollowing indicators: X1, X3, X5, X6, X7, X8, X9, X10, X12, andX13. As aresult ofapplying Hellwig’s economic development measure, asynthetic measure ofeconomic innovation was determined fortheEU countries in2010and2021. Then, onits basis, thelevel ofinnovation ofthenational innovation systems oftheEuropean Union was assessed. It was assumed that thelevel ofinnovation ofagiven NIS is determined by thearithmetic mean ofthesynthetic measure ofinnovation oftheeconomies ofits con‑ stituent countries. Inorder tocalculate theinnovation gap, it was also necessary todeter‑ mine theaverage EU level ofinnovation in2010and2021, which was, respectively: 0.2250 and0.1642. Theprevious stages ofthestudy allowed us todetermine theinnovation gap between individual NISs andtheaverage level ofinnovation inEU economies. Inthestudy, theinnovation gap index is defined as thequotient between thevalue ofthesynthet‑ ic measure ofinnovation foragiven NIS andtheaverage value ofthesynthetic index ofinnovation oftheEU countries’ economies. Theindicator oftheinnovation gap takes thefollowing form (Weresa 2014, p.64): t pt pt UE SII LSII =, (1) where: Lpt –theinnovation gap index (innovation gap) foragiven NIS inyear t, SIIpt –thevalue ofthesynthetic measure ofinnovation foragiven NIS inyear t, SII UEt –themean value ofthesynthetic measure ofinnovation oftheEU countries’ economies. Avalue oftheinnovation gap index exceeding 1 means that theanalyzed system pre‑ sents ahigher level ofinnovation than theEU average. Incontrast, avalue lower than 1 indicates that aninnovation gap exists between agiven system andtheEU average. Inorder toassess thechanges inthelevel oftheinnovation gap over time, aformula pre‑ senting thedifference between theinnovation gap index (L pt ) inagiven year andtheval‑ ue ofthis index forthebase year should be used. It is written as follows (Weresa 2014, p. 64):