DeterminantsofScience-BasedCooperation: EvidenceinaSampleofSmallandMicroFirms MireiaFernández-Ardèvol JosepLladósMasllorens We study the determining factors of science-based cooperation in the case of small and micro firms. In this research, we propose an analyt- ical framework based on the resource-based view of the firm and we identify a set of organisational characteristics, which we classify as in- ternal, external and structural factors. Each factor can be linked to at least one reason, from the firm’s point of view, to cooperate with uni- versities and public research centres. Each reason can, in turn, be used asanindicatorofafirm’sorganisationalneedsororganisationalcapac- ities. In order to validate the theoretical model, we estimate a logistic regression that models the propensity to participate in science-based cooperationactivities within asample of285 small and microfirms lo- catedinBarcelona.Theresultsshowthekeyroleplayedbytheabsorp- tivecapacityofnewand small companies. Key Words: science-basedcooperation,determinants, absorptive capacity,smallandmicrofirms jel Classification:l26 ,o32 Introduction The goal of this paper is to study the motivations that small and mi- cro firms have to engage in science-based cooperation. To this aim, we willidentifyasetofdeterminantsofcooperationbasedonafirm’sneeds andcapabilitiestonetworkwithscienceinstitutions.Ourtheoreticalap- proachisgroundedintheresource-based view–rbv –ofthefirm(Bar- ney1986 a;1986 b;1991 )andisrelated aswell totheconceptofabsorptive capacitysuggested byCohenandLevinthal(1989 ;1990 ). Therbv theory statesthattheessenceofthefirms’strategyisdefined (orshould be),bythe ownanduniqueset ofresources andcapacitiesof each firm (Rumelt1984 ). So it has been assumed that firms’ strategy is shapedbytwomainelements: DrMireia Fernández-Ardèvol isaResearcherat theInternet Interdisciplinary Institute(in3 ),OpenUniversity ofCatalonia, Spain DrJosepLladósMasllorens isLecturerat theFacultyofEconomics andBusiness Studies, OpenUniversity ofCatalonia, Spain Managing GlobalTransitions9 (4 ):319 –333 320 MireiaFernández-Ardèvol andJosepLladósMasllorens theopportunitiesprovidedbytheenvironment,thatis,marketop- portunities; and therestrictionsimposedbyorganizationalweaknessesandstrengths, thatis,internalassetsandcapacities. Innovativeagentstakepartinmultipleandcomplexnetworkrelation- shipswiththeaimofsharingandacquiringknowledge.Inthissense,in- novation can be described as a collective process (Malecki1991 )thatis increasinglyinterdependentandinteractive. One specific form of networking is cooperation (Vázquez Barquero 1999 ). Inparticular,we focusourinterest onscience-basedcooperation, definedasthose agreementsset byfirmswithuniversities andpublic re- search centres addressed to innovation. The cooperation with universi- tiesandresearchcentresplaysanimportantrolefortheimprovementof business performance, as university research has important and perva- siveeffectsonindustryr &d andinnovation(forasummary,seeZucker etal.2001 ,orKim,LeeandMarschke2005 ).Cooperation,however,isnot a universal practice as only25 % of the innovativeeu firms are engaged incooperationactivities(cis2006 ).Forthisreason,thestrengtheningof cooperation between science and business is a goal for innovation poli- ciesinthe EuropeanUnion(Eurostat2009 ). This paper is structured as follows. The nextsection is devoted to the development of our analytical framework, which is based on the rela- tionship betweenorganizationalresources, cooperationandinnovation. Our analysis follows with an empirical application to validate the iden- tified determinants of science-based cooperation among a specific sam- pleofsmallandmicrofirms.Thesection ondiscussion andconclusions closesthepaper. AnalyticalFramework absorptivecapacity Absorptive capacity is one of the most importantconceptual constructs that have emerged in the research on organization in the last decades (Lane, Koka and Pathak2002 ;2006 ). Its emergence coincided with the developmentof therbv theory and its derivative, the knowledge-based view of the firm. The most common definition of absorptive capacity wassetbyCohenandLevinthalin1990 .Theauthorsstatethat: Absorptivecapacityisthefirmabilitytorecognize the valueofnew externalinformation;toassimilateit;andtoapplyitwithcommer- cialpurposes. ManagingGlobalTransitions Determinants ofScience-Based Cooperation 321 Cohen andLevinthalpointoutthatfirms’absorptivecapacityconsti- tutesacriticalelementthatshapestheirabilitytodevelopinnovations,as an organization needs some previous related knowledge in order to as- similateandusenewlyacquiredexternalknowledge.Aslearningisacu- mulativeanddynamicprocess,learningproductivity increaseswhenthe objectoftheprocessoflearningispreviouslyknown.Forthatreason,di- versityof knowledgewithin the firm plays avery importantrole regard- ing absorptive capacity. As a result, absorptive capacity is firm-specific and is path-dependent. It is shaped as well by the individual absorption capacitiesofthemembersoftheorganizationindividuallyconsidered.In sum,absorptivecapacityisnotagoalbutameans–aninstrument–that determinesandmodulatestheresultsafirmcanachieve.Infact,vanden Bosch, van Wijk and Volverda2003 state that it is a multidimensional, multilevelandtrans-disciplinaryconstruct. The historical approach to innovation suggests that the benefits of scale and scope for internalr &d encourage a vertical integration in- novation model, where large companies internalize their firm-specific r &d activitiesandcommercializethembymeansofdevelopment,man- ufacturing and distribution processes (Chesbrough2006 ).In fact, firms develop innovations in a less hierarchical way. If companies cannot de- velop sufficient absorptive capacity themselves, they utilize strategic al- liancesinordertoobtainnewknowledgeorusecomplementaryexternal resourcestoexploitthatknowledge(Nooteboom1999 ). Many models have been developed to explain how firms can exploit external knowledge. A common way to overcome the first-mover strat- egy from a rival company is imitation (Lieberman and Montgomery 1998 ) or, alternatively, consulting with the lead customers or suppliers can provide useful ideas about how to improve the quality and perfor- manceoffirms’productsandservices. Moreover, in many economies, public sources of knowledge (such as governmentr &d spending) are an importantstimulus for privater &d (David, Hall and Tool2000 ). But, as Powell, Koput and Smith-Doerr (1996 ) state, the construction of alliances and the development of net- works by firms and institutions is an active way to incorporate exter- nalknowledgeintothe innovationsprocess offirms.Atpresent, univer- sityresearchisoftenexplicitlyfundedbycompaniestogenerateexternal spillovers(Colyvaset al.2002 ).In fact, spatiallocation results in knowl- edgespilloversbetweenfirmsandfromuniversityresearchinmanyeco- nomicactivities,especiallythehigh-techindustries(Porter1990 ;Baptista andSwann1998 ). Volume 9 · Number 4 · Winter 2011 322 MireiaFernández-Ardèvol andJosepLladósMasllorens Therefore, organizational strategy is related, among others, to the adoption and diffusion of innovations, the cooperation agreements in r &d orthedevelopmentofbasicresearch.Absorptivecapacityaffectsall these activities (Cohen and Levinthal1990 ). Specifically, it shapes coop- eration forinnovationwith universities andresearch centers:firmshave different absorptive capacities which, in turn, determine the propen- sity of the organization to establish cooperation agreements (Hernán, MarinandSiotis2003 ).Absorptivecapacityevenplaysa relevantrolein the relationship among weak links with other economic agents and the achievement of innovation results, as it encourages a higher profit from the exploitation of these links with external agents (Julien, Andriambe- losonandRamangalahy2004 ). Indeed,awidenumberofempiricalanalysesstudyhowabsorptiveca- pacity shapes cooperationactivities (see, amongothers, Bönte andKeil- bach2005 ; Cassiman and Veugelers2002 ; Frenz, Michie and Oughton 2003 ;Hernán,MarinandSiotis2003 ;LaursenandSalter2004 ;orMiotti andSachwald2003 ).Andparticularly,formaleducationofthestaffpos- itivelyaffectscooperationactivities (Belderbosetal.2004 ). In order to engage in cooperation activities a sufficient capacity is re- quired (Foss1999 ), since ‘firms need resources to get resources’ (Eisen- hardtandSchoonhoven1996 ,137 ).Aspecificandrelevantcaseisscience- based cooperation, in which firm-university relationships can be ex- traordinarily difficult to manage (Pavitt2005 ). Transaction costs can be higher when the interlocutor is a university or a research center, be- cause of their differences with respect to firms concerning commercial andgeneralorganizationalgoalsandaims. However,internalfactorsarenecessarybutnotsufficienttodefinethe absorptive capacity of the firm (Camisón and Forés2007 ). Therefore, thereisaclearneedofanappropriatecombinationofinternalandexter- nalassets,soabsorptivecapacitygets thehighest rateofresultsandfirm performance. Welook at those specific (internalandexternal) assets. In turn, these elements can also be identified with the reasons of firms for engaginginscience-basedcooperation. reasonsforscience -basedcooperationinsmall andmicrofirms Available statistical evidence on innovation shows that larger firms co- operatemost(cis ,2006 ).However,smallandmicrofirmsmaybemore dependentonexternallinksandexternalresources becausecooperation ManagingGlobalTransitions Determinants ofScience-Based Cooperation 323 table1 Reasonsforscience-basedcooperationinsmallandmicrofirms Structuralfactors Size Exploitationofcomplementarities (c ) Lackofresources (n ) Sector Risksharing (n ) Externalfactors Institutionalsupport Risksharing (n ) Turbulent environment Risksharing (n ) Internalfactors Humancapital Exploitationofcomplementarities (c ) Ongoingr &d Exploitationofcomplementarities (c ) notes c –capacitytocooperate,n –need tocooperate. would act as a mechanism to compensate size-inherent competitive dis- advantages(AudretschandFeldman2003 ).Inthis sense,firmsize isone of the elements that must be taken into account when analysingthe de- terminantsofcooperation. Therefore,asorganisationalfactorsaffectthepropensitytocooperate, ourtaxonomyidentifiesthreedifferentcategoriesofelements: structuralfactors, suchasfirmsizeorindustry; external factors, such as the access and use of institutional support forinnovationortheexistenceofmarketturbulences;and internal factors, such as the knowledge embedded in a firm’s staff (identifiedashumancapital)oritscontinuousengagementinr &d activities. We can also identify each one of these factors as an indicator of the mainreasonstoengagein science-based cooperation(seetable1 ).From thepointofviewofasmallfirm,therearethreemainmotivationstoco- operate(HannaandWalsh2002 ;Tether2002 ;JongandVermeulen2004 ): lackofinternalresources, risksharing,and searchofcomplementarities. These three reasons are not incompatibleand they can as well be un- derstoodintermsofthefirm’sneedsorcapacitiestocooperate.Thefirst tworeasonshavetodowithneed,astheirrationaleisthenecessitytoac- cess external resources in order to compensate the organisational weak- nesses.Incontrast,thethirdreasonrelatestoafirm’scooperationcapac- ity,asanyfirmaimingtocreateandtakeadvantageofpotentialcomple- mentaritiesmustbeabletoshareits(own)assetsand/orknowledge. Volume 9 · Number 4 · Winter 2011 324 MireiaFernández-Ardèvol andJosepLladósMasllorens Inthistheoreticalapproach,thesefactorscanbeconsideredindicators of the determinants of science-based cooperation among small and mi- cro firms. Through an empirical application we will try to validate the theoretical framework. EmpiricalApplication Inordertovalidatetheproposedanalyticalframeworkwithanempirical application,weusealogistic regressiontomodelthepropensityofsmall andmicrofirmstoengageinscience-basedcooperation.Welookatself- declared cooperation activities, without distinguishing between formal agreements and weaker ties. This broad definition affords a closer and more realistic picture of these types of firms. A set of indicators is used toproxythefactors(structural,externalandinternal)thatshapescience- basedcooperationactivities. fieldworkandsampledescription The aboveinformationcanonlybegathered throughasurvey.Datacol- lected for our specific application comes from a cross-sectional sample of285 mainly young, small and micro firms. These firms are located in Barcelona and are either closely or loosely linked to the local develop- ment agency, an institution created by the City Council (for more de- tails, see Fernández-Ardèvol2009 ; Fernández-Ardèvol and Lladós2009 ; CastellsandVilaseca2007 ). We conducted two online surveys, designed under the same concep- tual framework. Fieldwork was developed between July2005 and April 2006 . Respondents had the choice of answering the survey in Catalan or Spanish, while in order to encourage the response, an institutional e-mail was sent introducing the research. The tool allows multiple con- sistency controls that guarantee the quality of the data and prevent re- spondents from answering more than one questionnaire. The first sur- vey was addressed to entrepreneurs leading a firm who usually interact with the local development agency (256 individuals). With a response rate of52 .4 %,total number of questionnairesequals136 questionnaires. The secondtargeted populationcorrespondsto theusersofaninternet- basedplatformtofosterentrepreneurship.Created bythe localdevelop- ment agency, it had more than11 ,500 registered users. In this case, the response rate was5 .0 %(585 questionnaires). Amongthem, only one set ofindividualswasselectedforthisresearch:entrepreneurswithanactive firm.Thetotalnumberofquestionnairesinthissecondgroupequals164 . ManagingGlobalTransitions Determinants ofScience-Based Cooperation 325 Finally,mergeanddepurationofthetwosurveysledtoauniquesample of285 firms. The studied firms present distinctive features that differentiate them from the Catalan average.Firms are characterized by their youth, as the averageageis3 .3 years,andalmost60 %ofthemstartedtheactivitydur- ingtheprevious36 months.Onethirdofthefirmsinthesamplewerein- cubatedbythelocaldevelopmentagency(27 .7 %).Withanaverageof4 .6 full-timeworkers,morethan80 %havinglessthan5 employees.Inmost cases,theirpersonnel holdauniversitydegree (76 .19 %),whilefirms’ac- tivities lie mainlyin the Informationand Communication Technologies (ict )sector(28 .8 %) and in business services (21 .1%).Firmsareableto pay high salaries, as50 .9 %ofthecompaniespay annualgross wagesper employeeofbetween18 ,000 and24 ,000eur ,while17 %payover24 ,000 eur . In Catalonia, average gross annual wage in2005 was20 ,067eur , while the third quartile equalled22 ,704eur (source: Spanish industrial wagestructure survey, www.ine.es).Surveyed firmsalsoshow good per- formanceindicatorsdespitetheiryouth. modelbuilding :selectionofvariables The selection of variables for the empirical application is based on the literature review. Given the available data gathered through the survey, implementedvariablesareconsideredasfollows. Regarding structural factors, or basic organizational characteristics, the dimensionis measured asthe total numberof employees(expressed in full time equivalent). As size would not be enough to predict the propensity to cooperate, here it is considered as a control variable and we do not present any hypothesis regarding its influencein the endoge- nous variable. Sector of activity is also included by taking into account whether the firm belongs to theict sector or not. Indeed, the survey gathered informationon the next activity sectors:ict ; firm services; in- dustrial production; commercial distribution; personal services and so- cialactivities; andother services. Giventhe distribution andthe charac- teristics of the survey, we selected theict sector as the indicator of the necessity of risk sharing within a sector. As theict sector shows higher levels of innovation activities and a short life-cycle of technologies, we expect that firms in that sector will be more prone to cooperate with scienceagents. Regarding external factors, the first of them is institutional support. Thisisadiscreteandquantitativevariablethatgatherstheintensityofin- Volume 9 · Number 4 · Winter 2011 326 MireiaFernández-Ardèvol andJosepLladósMasllorens table2 Qualitativevariablesinthemodels(dichotomous) Variables Model Yes Roleinthemodel 12 Science-basedcooperationforinnovation × × 16 .1 % Endogenous Majorityofemployees holdingauniv.degree × × 76 .1 % Internalfactor r &d &i owndepartment × × 27 .0 % Internalfactor High competitive pressure (perception) × 82 .8%E x t e r n a l f a c t o r ict sector × 28 .8 % Structural factor notes Valid observations =285 . table3 Quantitativevariablesinthemodels Variables Modelms d Role in the model 12 Dimension:Totalnumber ofemployees (fulltimeequivalent) ××4 .58 6 .32 Structural factor Control variable Institutionalsupportintensity(1 –7)× 1 .86 0 .99 Externalfactor notes Valid observations =285 . stitutionalsupport.Itisboundedbetween1 and7.Thelowervaluecorre- spondstothosefirmsthatareonlysupportedbyBarcelonaActiva,while thehighervaluecorrespondstothosethataresupportedbyalltheseven different institutions considered in the survey. Institutions range from universities and business schools to the chamber of commerce, among others. The second external factor shows the competitive pressure perceived bythemanagerofthefirm,thatiswhetherthemarketsinwhichthefirm acts doordonot placerelevantpressure onthe businessactivity. This is a dichotomous variable that takes value one when competitive pressure isstatedtobe‘high’ or‘veryhigh’ andzero otherwise. Finally, we include two other dichotomous variables or internal fac- tors, that could be understood as indicators of the firm’s absorptive ca- pacity: 1 . humancapital:whetherthemajorityofemployeeshavehighdegree qualifications,and 2 . the existenceinthefirmofaspecificr &d department. Two models are specified. Model1 , the baseline model, has three ex- planatory variables: the two internal factors usually identified as indi- ManagingGlobalTransitions Determinants ofScience-Based Cooperation 327 cators of absorptive capacity, and firm dimension, the control variable. Model2 , on the other hand, is an enlarged model which includes the industry and the external factor variables listed in tables2 and3 . Both modelsincludeaconstantterm. GoodnessoffitGstatisticshowsthatbothmodelsaresignificantlydif- ferent from a model in which the only predictor was the constant term (see table4 ). Besides, covariances among explanatory variables stay at very low levels (values not showen in the table). Complementary statis- tics confirm that Model2 is preferable to Model1 : predictive capacity is similar (76 .1%vs.76 .5 %) but in Model2 there is a higher balance in correct predictions forthe positive category of the endogenousvariable. Apartfromthat,AkaikeandBayesInformationCriterion(aic andbic ) are lower in Model2 , and the deviance statistics show that the contri- bution of the variables added to Model1 to build Model2 really plays a significant role. Therefore, in the next paragraphs we will set our atten- tiononresultsforModel2 . It can be seen that the dimension of the firm positively influencesthe probabilityof engaging in science-based cooperation. In light of this re- sult we can consider that the number of employees is an indicator of absorptivecapacityinthecontextofasampleofsmallcompanies,asthe average firm size is below five employees. It confirms that, in order to assume the transaction cost inherent to science-based cooperation, the firmneedsasufficientamountofinternalresources. A higher dimension, in this context, would mean the availability of more complex and diverse knowledge and skills (Lee, Lee and Pennings 2001 ; Kogut and Zander1996 ). So, a larger knowledge base would in- crease the firm’s capability to engage in cooperation with science insti- tutionsbecausefirm’sperception ofrisk would belowerregarding these relationships. On the other hand,the two internal factors (human capitalandr &d department)positivelyaffecttheendogenousvariableaswell.Highered- ucation seems to be a key determinant factor, as can be seen from the magnitude of the estimated parameter (2 .132 ). As76 .1%ofthecompa- niesinthesamplehaveamajorityofemployeesholdingauniversityde- gree, this result is especially outstanding as it signals the importance of internalcapacitiestoengage inscience-based cooperation. Inviewofthese results, we canconsiderthatthe three first exogenous variables(numberofworkers;humancapitalandr &d department)act asindicators of the absorptive capacity of the sampled firms. This set of Volume 9 · Number 4 · Winter 2011 328 MireiaFernández-Ardèvol andJosepLladósMasllorens table4 Determinantsofscience-basedcooperationforinnovation Logitregressionmodels Model1 Model2 Endogenous:Science-basedcooperationforinnovation(yes= 16 .11 %) Totalnumber ofemployees(fulltimeequivalent) 0 .079 (0 .001 ) 0 .073 (0 .006 ) Majorityofemployees holdingauniversitydegree 2 .365 (0 .003 ) 2 .132 (0 .013 ) r &d &i owndepartment 1 .146 (0 .001 ) 0 .834 (0 .032 ) Institutionalsupportintensity(1 –7)— 0 .765 (0 .000 ) High competitive pressure (perception) — 0 .562 (0 .331 ) ict sector — 0 .398 (0 .331 ) Constantterm –4 .575 (0 .000 ) –6 .482 (0 .000 ) Goodnessoffitclassification table(percentageofcorrect predictions,cut= 16 %) Yes 63 .0 % 73 .9 % No 79 .1 % 76 .6 % Total 76 .5 % 76 .1 % Numberofobservations 285 285 Degrees offreedom 36 Ji-squaredtestofglobalsignificance:G 41 .755 (0 .000 ) 64 .363 (0 .000 ) Devianceofvariablesadded to themodel — 22 .608 (0 .000 ) −2 lnlikelihood 210 .179 187 .571 AkaikeInformationCriterion(aic ) 216 .179 199 .571 BayesInformationCriterion(bic ) 227 .137 221 .486 NagelkerkePseudoR 2 0 .232 0 .344 Hosmer-Lemeshowtest 5 .364 (0 .616 ) 6 .746 (0 .564 ) notes In bracketsp-values. minimal internal capabilities seems to favour the ability of the firms to considerscienceinstitutionsforcooperation,astrategythat,asDuysters and Lokshin (2007 ) point out, would make more complex the portfolio ofexternalalliances. ManagingGlobalTransitions Determinants ofScience-Based Cooperation 329 A third group of variables corresponds to external factors. It is con- firmed that institutional support has a significant and positive influ- enceonthepropensitytowardsscience-basedcooperation.However,al- though competitiveness pressure shows a positive influence as well, its parameter is not statistically significant. As entrepreneurs’ perception is highly extreme (with82 .8 % declaring that their business faces a high competitive pressure), this variable maybe is not the optimum instru- menttomeasurethecompetitivenesssituationinthosemarketsinwhich thesurveyedfirmsdeveloptheiractivity. Belonging to theict sector, which has been considered as an indica- tor of market dynamism, shows a positive parameter. However,it is not statistically significant either. As a consequence, the multivariate model showsthatthe activity sector isnotsignificantwhen absorptivecapacity indicatorsaretakenintoaccount. Finally, as already stated in previous works (see, for instance, Fritsch andLukas2001 ),the predictive capacityof themodel probablycouldbe improvedwiththeinclusionofvariablesregardingtheinternalizationof spilloversgeneratedbytheinnovativeactivityortheeffectivecostsaving dueto the cooperative activity. Unfortunately, that informationwasnot available. DiscussionandConclusion The results show the key role played by absorptive capacity as a deter- minant of science-based cooperation activities among small and micro firms. More specifically, itis possible to identify twodifferent sources of absorptivecapacity:aset ofinternalfactors andaset ofexternalfactors. Bothofthem improvethepropensity to engageinthat kindofcoopera- tionforinnovation. From aninternal perspective, the most importantfactor is the labour qualification,thatis, theeducationaldegree ofemployees.Itisalsocon- firmed that the existence of an r &d department is also very signifi- cant.Bothelementsarekeycomponentsthathelporganizationstobetter dealwithuniversitiesandresearchcentresforcooperation.Ontheother hand, firm size is relevant as well. In the studied milieu of very young firms,thecompaniesareclearlyshapedbythenumberofemployees,be- cause the marginal contribution of a new employee would have more significancethaninthecaseofalargercompany. From an external perspective, institutional support appears to be a crucial element for improving the absorptive capacity of small compa- Volume 9 · Number 4 · Winter 2011 330 MireiaFernández-Ardèvol andJosepLladósMasllorens nies, as it can help these firms to strengthen their organizational knowl- edge and to give access to networks configured by more diverse mem- bers. We do understand, therefore, that support institutions act as an effective interface between small and micro firms and universities and research centres. Summing up, absorptive capacity positively increases the propensity to establish cooperation with universities and research centres, evenamongfirmslocated ina non-universityinnovativemilieu whichismanagedbythelocaldevelopmentagencyinBarcelona.Inturn, theabsorptivecapacitycanbeeffectivelyimprovedbothfrominsideand outsidethesenewandsmallcompanies. References Audretsch, D. B., and M. P. Feldman.2003 . ‘Small-Firm Strategic Re- search Partnerships: The Case of Biotechnology.’ Technology Analysis andStrategicManagement15 (2 ):273 –88 . Baptista, R., and P. Swann.1998 . ‘Do Firms in Clusters Innovate More?’ ResearchPolicy27 (5 ):525 –40 . BarneyJ.B.1986 a.‘StrategicFactorMarkets:Expectations,LuckandBusi- ness Strategy.’ManagementScience32 (10 ):1231 –41 . ———.1986 b.‘OrganizationalCulture:CanitBeaSourceofCompetitive Advantage?’ AcademyofManagementReview11 (3 ):656 –65 . ———. 1991 . ‘Firm Resources and Sustained Competitive Advantage.’ JournalofManagement17 (1 ):99 –120 . Belderbos, R., M. Carree, B. Diederen, B. Lokshin, and R. Veugelers R. 2004 .‘ H et er ogen eityinr &d cooperation strategies.’ International JournalofIndustrial Organization22 (8 –9 ):1237 –63 . Bönte, W., and M. Keilbach.2005 . ‘Concubinage or Marriage? Informal and Formal Cooperation for Innovation.’ International Journal of In- dustrial Organization23 :278 –302 . Bosch,vandenF.A.J.,R.vanWijk,andH.W.Volverda.2003 .‘Absorptive Capacity:Antecedents,ModelsandOutcomes.’InBlackwellHandbook of Organizational Learning and Knowledge Management, edited by M. Smith,andM.A.Lyles,273 –302 .Malden,ma :Blackwell. Camisón, C., and B. Forés.2007 . ‘Factores antecedentes de la capacidad deabsorción deconocimiento:unestudio teórico.’In Empresa Global y Mercados Locales:xxi Congreso Anualaedem . Comunicaciones, 6 .– 8 .Junio2007 ,Madrid,edited by C. Mercado Idoeta,48 –65 .Madrid: UniversidadReyJuanCarlosI. Cassiman, B., and R. Veugelers.2002 .‘r &d Cooperation and Spillovers: Some Empirical Evidence from Belgium.’ American Economic Review 92 (4 ):1169 –84 . ManagingGlobalTransitions Determinants ofScience-Based Cooperation 331 Castells, M., and J. Vilaseca, ed.2007 . Entorno innovador, iniciativa em- prendedoraydesarrollo local.Barcelona:Octaedro. Chesbrough, H.2006 . ‘Open Innovation: A New Paradigm for Under- standing Industrial Innovation.’ In Open Innovation: Researching a NewParadigm,editedbyH.Chesbrogh,W.Vanhaverbeke,andJ.West, 1 –12 .Oxford:OxfordUniversityPress. cis .2006 . ‘Community Innovation Survey2006 .’ http://epp.eurostat.ec .europa.eu/portal/page/portal/science_technology_innovation/data/ database Cohen, W. M., and D. A. Levinthal.1989 . ‘Innovation and Learning: The Two Faces ofr &d .’ TheEconomicJournal99 (397 ):569 –96 . ———.1990 . ‘Absorptive Capacity: A New Perspective on Learning and Innovation.’Administrative ScienceQuarterly35 (1 ):128 –52 . Colyvas,J.,M.Crow,A.Gelijns,R.Mazzoleni,R.R.Nelson,N.Rosen- berg,andB.N.Sampat.2002 .‘HowDoUniversityInventionsGetinto Pratice?’ ManagementScience48 (1 ):61 –72 . David, P., B. H. Hall and A. A. Tool.2000 ‘Is Publicr &d a Complement orSubstituteofPrivater &d ?AReviewoftheEconometricEvidence.’ ResearchPolicy29 (4 –5 ):497 –529 . Duysters, G., and B. Lokshin.2007 . ‘Determinants of alliance portfolio complexity and its effect on innovative performance of companies.’ unu -merit Working Paper Series 033 , United Nations University, Maastricht Economic and Social Research and Training centre on In- novationand Technology,Maastricht. Eisenhardt, K., and C. Schoonhoven. 1996 . ‘Resource-Based View of StrategicAllianceFormation:StrategicandSocialEffectsinEntrepre- neurialFirms.’Organization Science7 (2 ):136 –50 . Eurostat.2009 .Science,TechnologyandInnovationinEurope.EurostatSta- tistical Books. Brussels: European Communities. http://epp.eurostat .ec.europa.eu/cache/ity _offpub /ks -em -09 -001 /en /ks -em -09 -001 -en .pdf . Fernández-Ardèvol,M.2009 .‘Determinantsdelacompetitivitatdelespe- titesimicroempresesenunentornd’innovació.’PhDdiss.,University ofBarcelona. Fernández-Ardèvol, M., and J. Lladós.2009 . ‘Science-based cooperation and business success: Transmittal mechanisms in a sample of small and micro firms.’ In Proceedings of the 10 th Management International Conference, Sousse, Tunisia, 25 –28 November,199 –217 .Koper:Faculty ofManagement. Foss, N. J. 1999 . ‘Networks, Capabilities, and Competitive Advantage.’ Scandinavian JournalofManagement15 (1 ):1 –15 . Frenz,M.,J.Michie,andC.Oughton.2003 .‘RegionalDimensionofInno- Volume 9 · Number 4 · Winter 2011 332 MireiaFernández-Ardèvol andJosepLladósMasllorens vation:Resultsfrom theThird CommunityInnovation Survey.’Paper presentedatthesiepi2003 conference,Urbino,1 –2 December. Fritsch,M.,andR.Lukas.2001 .‘WhoCooperatesonr &d ?’ResearchPolicy 30 (2 ):297 –312 . Hanna, V., and K. Walsh.2002 . ‘Small Firm Networks: A Successful Ap- proachtoInnovation?’r &d Management32 (3 ):201 –207 . Hernán, R., P. Marín, and G. Siotis.2003 .‘AnEmpiricalEvaluationofthe DeterminantsofResearchJointVentureFormation.’TheJournalofIn- dustrialEconomics51 (1 ):75 –89 . Jong,J.P .J.de,andP .A.M.Vermeulen.2004 .DeterminantsofProductIn- novation in Small Firms: A Comparison across Industries. Zoetermeer: eim . Julien, P. A., E. Andriambeloson, and C. Ramangalahy.2004 .‘Networks, weaksignalsandTechnologicalInnovationsamongsme sintheLand- Based Transportation Equipment Sector.’ Entrepreneurship and Re- gionalDevelopment16 (4 ):251 –69 . Kim, J., S.J. Lee, and G. Marschke.2005 . ‘The Influence ofUniversity Re- search on Industrial Innovation.’nber Working Paper Series11447 , NationalBureauofEconomicResearch,Cambridge,ma . Kogut, B., and U. Zander.1996 . ‘What Firms do? Coordination, Identity, and Learning.’Organization Science7 (5 ):502 –18 . Lane,P.L.,B.Koka,andS.Pathak.2002 .‘AThematicAnalysisandCritical AssessmentofAbsorptiveCapacityResearch.’AcademyofManagement Proceedings1 :1 –7 . ———.2006 . ‘The Reification of Absorptive Capacity: A Critical Review and Rejuvenation of the Construct.’ Academy of Management Review 31 (4 ):833 –63 . Laursen, K.,andA.Salter.2004 .‘Searching Lowand High:WhatTypesof Firms use Universities as a Source of Innovation?’ Research Policy33 (8 ):1201 –15 . Lee, C., K. Lee, and J. M. Pennings.2001 . ‘Internal Capabilities, External Networks, and Performance: A Studyon Technology Based Ventures.’ StrategicManagementJournal22 (6 –7 ):615 –40 . Lieberman,M.B.andD.B.Montgomery.1998 .‘First-MoverAdvantages.’ StrategicManagementJournal9 :41 –58 . Malecki, E. J.1991 . Technology and Economic Development: The Dynamics ofLocal,RegionalandNationalChange. London:Longman. Miotti, L., and S. Sachwald.2003 .‘Co-Operativer &d :WhyandWith Whom? AnIntegrated Framework ofAnalysis.’ Research Policy32 (8 ): 1481 –99 . Noteboom, B.1999 . Inter-Firm Alliances: Analysis and Design. London: Rutledge. ManagingGlobalTransitions Determinants ofScience-Based Cooperation 333 Pavitt, K.2005 . ‘Innovation Process.’ In The Oxford Handbook of Innova- tion, edited by J. Faberger, D. C. Mowery, and R. R. Nelson,86 –114 . Oxford: Oxford University Press. Porter, M.1990 .TheCompetitiveAdvantageofNations.NewYork:TheFree Press. Powell, W. W., K. W. Koput, and L. Smith-Doerr. 1996 . ‘Interorganisa- tional Collaboration and the Locus of Control of Innovation: Net- works of Learning in the Biotechnology Industry.’ Administrative Sci- enceQuarterly41 :116 –45 . Rumelt, R.1984 . ‘Toward a Strategic Theory of the Firm.’ In Competitive Strategic Management, edited by R. Lamb,556 –70 . Englewood Cliffs, nj :Prentice-Hall. Tether, B. S.2002 . ‘Who Co-Operates for Innovation, and Why: An Em- piricalAnalysis.’ResearchPolicy31 (6 ):947 –67 . Vázquez Barquero, A.1999 . Desarrollo, redes e innovación: Lecciones sobre desarrollo endógeno.Madrid:Pirámide Ediciones. Zucker,L.G.,M.R.Darby,andJ.S.Armstrong.2001 . ‘Commercializing Knowledge:UniversityScience,KnowledgeCapture,andFirmPerfor- mance in Biotechnology.’nber Working Paper Series8499 ,National BureauofEconomicResearch,Cambridge,ma . Volume 9 · Number 4 · Winter 2011