Table Of ContentAdvances in Spatial Science
Jan Stejskal
Petr Hajek
Oto Hudec Editors
Knowledge
Spillovers in
Regional
Innovation
Systems
A Case Study of CEE Regions
Advances in Spatial Science
The Regional Science Series
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ManfredM.Fischer
Jean-ClaudeThill
JoukevanDijk
HansWestlund
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FolkeSnickars
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(cid:129) (cid:129)
Jan Stejskal Petr Hajek Oto Hudec
Editors
Knowledge Spillovers
in Regional Innovation
Systems
A Case Study of CEE Regions
Editors
JanStejskal PetrHajek
UniversityofPardubice UniversityofPardubice
Pardubice,CzechRepublic Pardubice,CzechRepublic
OtoHudec
TechnicalUniversityofKosice
Kosice,Slovakia
ISSN1430-9602 ISSN2197-9375 (electronic)
AdvancesinSpatialScience
ISBN978-3-319-67028-7 ISBN978-3-319-67029-4 (eBook)
https://doi.org/10.1007/978-3-319-67029-4
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Editorial
Technology change is related to knowledge accumulation, which is inevitable to
ensure innovation. A number of studies (e.g., Acemoglu et al. 2012; Wang and
Wang2012;Boonsetal.2013;CamisónandVillar-López2014)haveanalyzedthe
impact of knowledge and innovation on economic growth, company performance,
competitiveness, or sustainable development (Péti 2012). The activation, applica-
tion, or utilization of knowledge has been the subject of extensive research since
1970, when an effort was made to link social research and policy making and to
understand the spatial dimension of knowledge spillover mechanisms and innova-
tive activity. Geographic location and economies of agglomeration are vital for
knowledgegeneration,dissemination,spillover,andapplication(Songetal.2005).
Taking these findings into account, a vast variety of theories have been developed
lookingforthesourcesofknowledgeandinnovationaswellasthemechanismthat
helpsfirmsdrawupontheircorecompetenciesandtransformthemintoperformance
outcomes(DoranandRyan2014).
Capello et al. (2011) have classified studies on innovation, knowledge, and
regional growth into three different approaches. The first approach focuses on the
production of pure knowledge and concentrates more on explaining knowledge
creation, spillovers, and linking knowledge inputs to knowledge outputs using a
classicalproductionfunction(includingthetheoryoftechnologicalspillovers).The
second important approach to the role of knowledge in regional growth includes
theories linking knowledge to regional growth; these take into consideration that
regionaleconomicperformanceincreaseswhenknowledgeisproduced.Thisisthe
fieldrichestinconceptualandappliedanalysesofinnovationandregionalgrowth;it
comprises (i) the innovative milieu theory, (ii) learning regions, and (iii) regional
innovationsystems,forexample.
The third and the most recent approach is concentrated on analyzing a region’s
intangiblecapacityfortranslatinginnovationintoincreasingprofitsfromeconomic
growth. The main benefit of this approach lies in the analysis of territorially
embedded elements, enabling a region to grasp the opportunities provided by
v
vi Editorial
innovationcreation,spillovereffects,andnewknowledgeandtoachieveincreased
profitsfromeconomicgrowthbasedonthesefactors.
Itisclearthatregionsareendowedwithdifferentterritorialcapital(theterritorial
conditionsthatalloweconomicdevelopmenttoaccelerate).Therefore,theavailabil-
ityofpublic,private,material,immaterial,andknowledgeassetsvariessignificantly
between regions and includes infrastructure as well as private, human, and social
capital(FratesiandPerucca2014).
ThecountriesofCentralandEasternEurope(CEE)haveundergonecomparable
historicalchangessinceWorldWarII,markedbythesocialistperiodaftertheWorld
War II, transition to a market economy at the end of twentieth century, and
integration into the European Union. Nationalization or government takeover of
private companies during the socialist era followed by privatization during the
transitionperiod hashad a significant impact ontheirnational and regionalecono-
mies, resulting in increased regional disparities and substantially different trajecto-
ries for development, including those for research, development,and innovation at
the beginning of the twenty-first century. Western European models of innovation
systemshavebeenimplementedwithinthestillcentralizedmodelsofoperationfor
research and development, often resulting in weak, formal, or artificial types of
innovation systems, knowledge transfer, and knowledge exploitation. Even nearly
30 years after reintegration into theEuropean economy, theCEE countries display
lowleveloftrustandcooperationbetweenregionaltriplehelixentities(knowledge
institutions, industry, and the public authorities) as well as poor innovation and
patentperformance.
Moreover,lessdevelopedsocialcapitalandthereluctanceoftheregionalstake-
holderstoworkinpartnershipsresultinmutualmisunderstandinganddifficultiesin
sharing information and strategic planning. As widely accepted, social capital in
innovation networks emerges often as a result of network actors sharing some of
values and norms, and network embeddedness has positive effects on regional
innovation outcomes (Westlund 2006). A mental lock-in has its consequences: the
CEE countries are losing out on the ongoing culture of centralization and central
planning,whichisreflectedincentralmanagementofthesectoralpolicies,distrust
ofcivilsociety,andunderfundingoflowerterritorialself-governments.
It is necessary to emphasize that individual CEE countries are to a large extent
export economies, primarily depending on the performance of the economy of
GermanyandotherWesterncountries.Thereisonlyatentativeregionalknowledge
spillover mechanism existing in parallel with the organized external knowledge
spillovers.EffortsofCEEcountriestobuildeconomicdevelopmentontheterritorial
assets are still under way and, instead, reliant on external exogenous knowledge
transfers, and foreign capital prevails to stimulate growth. Domestic companies
(with some exceptions) are less competitive because of their lower innovative
potential. Technology and equipment are mostly imported. The impact of foreign
capital inflow and knowledge acquisition on innovation performance is limited by
theinsufficientabsorptivecapacitytoassimilateandintegrateexternalknowledge.A
similar problem exists in the utilization of knowledge transfer acquired from the
massiveEUfunds.
Editorial vii
The results of many studies show that external resources bring positive effects
only to advanced economic systems, which embody focused public structural
policies, effective law enforcement institutions, trust between cooperating entities,
andincreasing workers’knowledge potential(including creativity and thecapacity
toinnovate).Moreover,ineffectivetake-upandredistributionofEUfundshaveled
to crowding out of foreign investment in several CEE countries. The flow of
European funds often causes the low-hanging fruit effect, which adversely affects
businessenvironment,corporateculture,andthewillingnessofcompaniestocoop-
erateoncreatinginnovativeoutputs.
On the other hand, it is worth pointing out that the CEE countries have shown
distinct progress over the last 20 years. Two decades of economic growth and
catching up with western EU countries were based on lower wage costs. The
progressivegrowthmodelshouldbechangedtobedrivenbyinnovationtoconfirm
theglobalcompetitiveness.Theindividualcountriesenactvariouspublicpolicieson
innovation support resulting in implementing innovation system policies and
supporting a positive innovation environment. The public resources of the CEE
countriesandtheEUhavebeenusedtobuildindustrialinnovationzones,innovation
andcompetencecenters,technologyandresearchparks,etc.Likewise,considerable
attention has been given to soft infrastructure in the area of supporting science,
research,andeducation.
As Radosevic demonstrated in his studies (1999b, 2002), the complicated tran-
sition period significantly influences the long-term economic growth of the CEE
countries. He pointed out that long-term growth depends on the sustainability of
economic recovery in the economies of Central and Eastern Europe and on the
reconstructionofinnovationsystems(intercompany,sectoral,regional,national,or
global).Well-tailoredinnovationssystemsshouldemergethroughtheinteractionof
factorsthatarespecifictomicroeconomicsorthegivensector,nation,orregion.This
is not an easy task, as the ineffectiveness and inefficiencies of current innovation
systemsarecausedbythepathdependenceoftheoldcentrallyplannedandsectoral
model.
CEEcountrieshaveapplieddifferent kindsofstrategies torebuild theirinnova-
tion systems. A variety of policy combinations have strongly focused on
(i)increasingin-housecompanyR&D,(ii)attractingforeigncompaniesandprovid-
ing them with incentives to innovate, (iii) enhancing public institutions’ R&D
capacities—tocooperatewith(partner)privatecompanies,and(iv)creatinginstitu-
tions that support and enable knowledge creation and transfer (Edler 2009).
Krammer (2009) analyzed the drivers of innovative activities in transition econo-
mies. Countries of Eastern Europe and the former Soviet Union (EECs) have been
experiencingapainfultransitionsincetheearly1990s,andthisdifficultconversion
has also impeded their innovative capacities. Even though, there is still a lack of
studies analyzing and evaluating innovative activities and the application of tools
supportingknowledgecapitalwithinCentralandEasternEuropeancountries.
Radosevic has focused extensively on patterns of innovative activities in CEE
countries between the years 1999 and 2002 and has pointed to some significant
findings (Radosevic and Auriol 1999; Radosevic 1999a, b, 2002). The systemic
viii Editorial
changes in transition economies in the early 1990s have not brought about funda-
mentalshiftintheperceptionofpolicymakers.Theycontinuetoimplementmostly
linear models of innovation processes (Varblane et al. 2007). Drivers of regional
growthcertainlyrequiretheinvolvementofseveralsectors,whichishardlypossible
inexistingverticalandsectoralsystemoforganizationandgiveninternalobjectives.
Communication and coordination are inefficient without breaking out the policy
silos.
Thedetailedlookatthestateofinnovationsystemsandtheirperformanceatthe
turnofthecenturyshowthatthepositionoftheCEEcountriesisatthebottomofthe
EU countries, reflecting the limited scale of their innovative activities. The initial
situation in the CEE innovation system can be characterized by several R&D and
innovationdifferences:
(cid:129) ThepercentageofenterpriseswithR&Dactivitieswassignificantlylowerinthe
CEEthanintheEUcountries.
(cid:129) ExtramuralR&Dorganizationsplayedastrongerroleintheinnovationsystems
thanintramuralones.
(cid:129) The innovation expenditures were relatively higher on more embodied technol-
ogy,patents,andlicenses.
This set of publications may serve as a benchmark or indicative basis for
comparison after 15 years, as presented in this book. The book consists of four
parts, with the ambition to cover a large number of CEE countries and to present
more dimensions,thus creatinga space for deeper understanding ofdevelopments,
changes,andprocessesinthefieldofknowledgeandinnovation.
Today, a long list of literature is already devoted to national and regional
innovation systems, knowledge spillovers, innovation networks, knowledge bases,
absorption capacity, etc. The vast majority of key results are based on the more
developed North American and Western European countries, though their evolu-
tionary basis and institutional framework are very different from the group of
catching-uppostcommunistcountriesofCentralandEasternEurope,withdifferent
historicalexperience anddiscrepantsocioeconomiccharacteristics.Thisiswhythe
introductorypartprovidesanoverviewofkeyconceptsandresultsontheunderlying
topicofthisbook—knowledgespilloversinknowledgeenvironmentaswellasthe
ways of classification and measuring spillover effects. The chapter entitled “The
Effects of Cooperation and Knowledge Spillovers in Knowledge Environment” of
Part1summarizesthecurrentknowledgegainedalmostexclusivelybythestudyof
theregionalinnovationenvironmentinWesternEuropeandUSAandthefactorsof
cooperation and rivalry inrelation tothe creationand exchange of knowledge as a
precondition for economic growth. Hence, the new paradigm has brought the shift
from traditional to knowledge factors of development. Newer theories of regional
developmentarestronglybasedontheknowledgeandinstitutionaleconomicfactors
such as knowledge workers, R&D, innovation, social capital, and spillovers. The
mostsignificanttheoreticalapproachesofcooperationandknowledgespilloversare
explained and classified in the chapter entitled “The Effects of Cooperation and
Knowledge Spillovers in Knowledge Environment.” All the following chapters
Editorial ix
almost exclusively deal with CEE countries, which can always be considered in
termsofconsistencyanddifferenceswiththe“Western-founded”theoreticalframe-
workinthechapterentitled“TheEffectsofCooperationandKnowledgeSpillovers
inKnowledgeEnvironment.”Asanarenafortheknowledgetransferandspillovers,
the concept of regional innovation systems (RIS) is used. RIS is considered in
general to consist of two subsystems of knowledge production and knowledge
exploitation,anditsefficiencycanbeevaluatedintermsofinputsandoutputs.
Part II builds on the theoretical Part I, comprising three chapters dealing with
evaluation and assessment of the regional innovation systems by the authors from
Lithuania, the Czech Republic, Slovakia, and Poland. The assessment of regional
innovation systems is based on several factors (absorption capacity, intellectual
capital, etc.) and is realized using several methods (data envelopment analysis,
fuzzycognitivemaps,andtheweightedsummodel)providingamultifacetedview
ofCEEregionsandenablingbetterunderstandingofthekeystonesoftheirinnova-
tion performance. Absorptive capacity, which refers to the ability to attract and
absorb external innovative ideas, is an essential characteristic of RIS. Absorptive
capacity assessment methodology is applied to the Lithuanian regions, also
highlightingthecontextofsmallcountries.Anotherweightedsummethod(WSM)
isbasedontheprincipleofutilitymaximizationofRISlevelassessment.Thesetof
CzechRIScharacteristics isdividedintofourlayers:companies,supportorganiza-
tions,environmentandinfrastructure,andrelationshipsandlinks.Thelastchapterof
PartIIevaluatestheintellectualcapitalinthePolishandSlovakregions.TheDEA
methodologywasusedfortheevaluationoftheintellectualcapitalefficiency.
PartIIIofthisbookfocusesontheevolutionanddynamicsofregionalinnovation
systems.Knowledgeproductionprocessesduringthetransitionperiodfromauthor-
itarian socialism to market economy experienced the disintegration of the former
inventory networks followed by only a slow recovery over the last 20 years. The
authors deal with the evolutionary development of regional innovation systems in
CEE countries by spatial evaluation of the regional networks of inventors in the
Slovakregions.Theinnovationsystems,whethernationalorregional,areunderde-
veloped and lacking the main substance—social capital and well-functioning link-
ages between the actors. In the following chapter, spatial dynamics of inventor
activity in the Czech Republic, Hungary, Poland, and Slovakia between 1981 and
2010isstudied.Theinternationalanddomesticcollaborationpatentsarecompared
to explain the number of citations and technological profile. The collaboration
betweentheassignee-inventorsisanalyzedatthetownlevel.
Lastly,PartIVrespondstotheexpectedquestionsaboutthelocationfactorsfor
investment in the automotive industry in Central Europe. A qualitative survey
focused on discussing the interaction between MNCs and the local environment
andwhetherforeigndirectinvestmentshaveacapacitytostimulateagrowthbased
on an endogenous innovation pattern. The role of knowledge spillovers on firms’
productivity, demand,and successfulimplementationofproduct andprocessinno-
vationsisstudiedinthefollowingchapter,lookingfordifferencesbetweenthegroup
ofcountries—Czech,Slovakia,Estonia,Lithuania,Romania,Croatia,Slovenia,and
Hungary.Theanalysisisaimedatevaluatingtheinfluenceofselecteddeterminants
