Revista
de
Administração
http://rausp.usp.br/ RevistadeAdministração52(2017)176–188
Technology
Management
Determinants
of
reverse
knowledge
transfer
for
emerging
market
multinationals:
the
role
of
complexity,
autonomy
and
embeddedness
Determinantes
da
transferência
reversa
de
conhecimento
em
multinacionais
de
mercados
emergentes:
o
papel
da
complexidade,
da
autonomia
e
da
integra¸cão
Factores
determinantes
de
la
transferencia
inversa
de
conocimiento
en
multinacionales
de
mercados
emergentes:
el
papel
de
la
complejidad,
la
autonomía
y
la
integración
Franciane
Freitas
Silveira
a,∗,
Roberto
Sbragia
b,
Henry
Lopez-Vega
c,
Fredrik
Tell
daUniversidadeFederaldoABC,SãoBernardodoCampo,SP,Brazil bUniversidadedeSãoPaulo,SãoPaulo,SP,Brazil
cJönköpingUniversity,JönköpingInternationalBusinessSchool,Jönköping,Sweden dUppsalaUniversity,Uppsala,Sweden
Received29June2016;accepted19August2016 Availableonline2January2017 ScientificEditor:MariaSylviaMacchioneSaes
Abstract
Subsidiariesconductinnovationactivitiesinforeignmarketseithertocapturevaluableknowledgethatisnecessarytoadapttheirproductstolocal marketsortocreatevaluableknowledgeforheadquarters.Foremergingmarketmultinationals,moststudieshaveoverlookedthedeterminantsof successfulreverseknowledgetransferfromsubsidiarieslocatedinemerginganddevelopedmarkets.Thispaperanalyzedtheresponsesofasurvey administeredto78Brazilianmultinationalsthatownsubsidiariesindevelopedandemergingmarkets.Wefoundthatknowledgecomplexity devel-opedatthesubsidiary,itsautonomyandembeddednessintheforeignmarketdeterminethesuccessfulreverseknowledgetransfertoheadquarters ofemergingmarketmultinationals.Thispapercontributestopreviousstudiesofreverseknowledgetransferbyunderlyingthemaindriversfor emergingmarketmultinationals.
©2016DepartamentodeAdministrac¸˜ao,FaculdadedeEconomia,Administrac¸˜aoeContabilidadedaUniversidadedeS˜aoPaulo–FEA/USP. PublishedbyElsevierEditoraLtda.ThisisanopenaccessarticleundertheCCBYlicense(http://creativecommons.org/licenses/by/4.0/).
Keywords: Reverseknowledgetransfer;Emergingmultinationals;Brazilianmultinationals
Resumo
Subsidiáriasrealizamatividadesdeinovac¸ãoemmercadosestrangeiros,querparacapturaroconhecimentovaliosoqueénecessárioparaadaptar seusprodutosaosmercadoslocaisouparacriarconhecimentodealtovalorparaasede.Nocontextodemultinacionaisdemercadosemergentes, amaioriadosestudostêmnegligenciadoosdeterminantesdatransferênciadeconhecimetnoprovenientesdesubsidiárias(transferênciareversa). Foramanalisadasasrespostasdeumapesquisarealizadacom78multinacionaisbrasileirasquepossuemsubsidiáriasemmercadosdesenvolvidos
∗Correspondingauthorat:AlamedadaUniversidade,s/n◦–CEP09606-045,SãoBernardodoCampo,SP,Brazil.
E-mail:[email protected](F.F.Silveira).
PeerReviewundertheresponsibilityofDepartamentodeAdministrac¸ão,FaculdadedeEconomia,Administrac¸ãoeContabilidadedaUniversidadedeSãoPaulo –FEA/USP.
http://dx.doi.org/10.1016/j.rausp.2016.12.007
eemergentes.Verificou-sequeacomplexidadedoconhecimentodesenvolvidonasubsidiária,bemcomoasuaautonomiaeinserc¸ãonomercado externodeterminamofluxodetransferênciareversa deconhecimentonaempresamultinacionalemergente. Estetrabalhoenriqueceestudos anterioressobretransferênciareversadeconhecimentodestacandoosprincipaisdriversparaasmultinacionaisdosmercadosemergentes. ©2016DepartamentodeAdministrac¸˜ao,FaculdadedeEconomia,Administrac¸˜aoeContabilidadedaUniversidadedeS˜aoPaulo–FEA/USP. PublicadoporElsevierEditoraLtda.Este ´eumartigoOpenAccesssobumalicenc¸aCCBY(http://creativecommons.org/licenses/by/4.0/).
Palavras-chave:Trasnferênciareversadeconhecimento;Multinacionaisemergentes;Multinacionaisbrasileiras
Resumen
Filialesrealizanactividadesdeinnovaciónenlosmercadosextranjeros,yaseaparacapturarelconocimientovaliosoqueesnecesarioparaadaptar susproductosalosmercadoslocales,oconelfindecrearconocimientodealtovalorparasusede.Respectoalasmultinacionalesdemercados emergentes,enlamayorpartedelosestudiosnosehadadoladebidaatenciónalosfactoresdeterminantesdelatransferenciadeconocimientoa partirdefiliales(transferenciainversa).Enesteestudioseanalizanlasrespuestasdeunaencuestarealizadaa78multinacionalesbrasile˜nasque poseenfilialesenmercadosdesarrolladosyemergentes.Losresultadosindicanquelacomplejidaddelconocimientodesarrolladoenlafilial,así comosuautonomíaeinserciónenelmercadoexternodeterminanelflujodetransferenciainversadeconocimientoenlaempresamultinacional emergente.Conestetrabajo,secolaboraaldesarrollodelosestudiosacerca delatransferenciainversa deconocimiento,conénfasisenlos principalesdriversparalasmultinacionalesdemercadosemergentes.
©2016DepartamentodeAdministrac¸˜ao,FaculdadedeEconomia,Administrac¸˜aoeContabilidadedaUniversidadedeS˜aoPaulo–FEA/USP. PublicadoporElsevierEditoraLtda.Esteesunart´ıculoOpenAccessbajolalicenciaCCBY(http://creativecommons.org/licenses/by/4.0/).
Palabrasclave: Transferenciainversadeconocimiento;Multinacionalesemergentes;Multinacionalesbrasile˜nas
Introduction
Themultinationalenterprise(MNE)isadifferentiated net-workinwhichitscontrolledsubsidiariesvarywidelyinterms of dutiesand responsibilities(Nohria &Ghoshal,1994). For example,whilesomesubsidiariesevolvethroughthe headquar-ters’mandatesothersfocusontheirowninitiatives(Mudambi, Piscitello,&Rabbiosi,2014).Sincethelate1990s,the recog-nitionthat headquarters operate as knowledgereceivers from their internationallydispersed subsidiarieshas gained signifi-cance ininternational business research (Ambos, 2015). The strategicimportanceoftheMNE’subsidiarieshascontinuedto grow,inthat itisanaccesspathway toknowledgeandtothe technologysituated atthesubsidiaries’localmarkets(Borini, Oliveira,Silveira,&Concer,2012;Criscuolo&Narula,2007; Frost& Zhou, 2005),which canactively contribute tovalue creationandsubsequentgainofcompetitiveadvantageforthe entireMNE(Bartlett&Ghoshal,1989;Cantwell&Mudambi, 2005;Yang,Mudambi,&Meyer,2008).
An underlying idea is that MNE make use of knowledge
generatedbyforeignsubsidiaries.From thisperspective,
sub-sidiaries upgrade their competence enhancing role such as
marketexpansion, costreduction andsupplieradaptation and begintoplayamoreactiverolethrough knowledge
develop-ment. For example, foreign subsidiaries might develop new
products, new technologies, create new practices, new skills thatwilllatershapetheirowncompetencecreatingpathwaysas wellasaccumulatedifferentdegreesoftechnologicalcapability (Birkinshaw,1997;Borinietal.,2012;Borini,Costa,Bezerra,& Oliveira,2014;Cantwell&Mudambi,2005;Figueiredo&Brito, 2011;Frost,Birkinshaw,&Ensign,2002;Ghoshal&Bartlett, 1988; Govindarajan & Trimble, 2012; Mudambi, Mudambi, &Navarra,2007;Nohria &Ghoshal,1997).Moreover, com-petence creating subsidiaries could enhance their innovation
outcomes which enables them to compete domestically and
internationally (Bell & Pavitt, 1995; Cantwell & Mudambi, 2005;Figueiredo&Brito,2011).Fromasubsidiaryperspective, reverseknowledgetransfer(RKT)givesvisibilitytosubsidiaries thatcouldleveragetheirstrategicpositioninthemultinational network(Borinietal.,2012;Holm&Pedersen,2000).
Thesefactorshavehighlightedthatreverseknowledge trans-ferisakeyvariableinthestudyofcross-borderknowledgeflows inMNEs(Ambos,2015).Asaresult,theknowledgetransferin thereversedirection,thatis,fromsubsidiariestoMNE headquar-ters,hasemergedasaprominentthemeininternationalbusiness studies(Ambos,2015;Ambos,Ambos,&Schlegelmilch,2006; Criscuolo,2005;Frost&Zhou,2005;Gupta&Govindarajan, 2000; Håkanson & Nobel, 2001; Rabiosi, 2008; Rabiosi & Santangelo, 2011;Rabiosi, 2011;Yangetal., 2008).Whilea numberofarticlesexploretheantecedents,successamountand successkey-factorsindifferentfunctionalconFigurationsatthe multinationalcorporation(Ambos,2015),additionalresearchis needed (Michailova&Mustaffa,2012).First,sincethe
trans-ferof knowledge inMNEs hasgrownconsiderably inrecent
years,becomingthereforemorepronetovariousdefinitionsand measurementsofthesameconstructsresultinginconclusions, oftencontradictoryandambiguous.Second,whilerecognizing theimportanceofinvestigatingtherelationshipofthesubsidiary withexternalcompanieslocatedinthehostcountries,the liter-ature oftenfocuses onlyon the research of knowledge flows withinthe MNE.Thisnarrowattention considerssubsidiaries areprimarilyrecipientsofknowledge(Michailova&Mustaffa, 2012).
becombinedwiththeexistingresources (Bartlett&Ghoshal, 2000).Thatissobecause,insteadofinternationalizingtoutilize existingadvantages,emergingmarketmultinationalswill inter-nationalizeaimingatacquiringnewadvantagesandcapabilities (Guillén&García-Canal,2009;Mathews,2006;Ramamurti& Singh,2009)andshouldtodoitquickerthantraditional multi-nationalsdidintheirexpansionpaths(Mathews,2006).
InthecontextofBrazilianmultinationals,recentstudieshave soughttounderstandtheprimaryfactorsthatinfluencetheRKT. ThestudyofBorinietal.(2012)arguesthatthereverse knowl-edge transfer is a function of the strategic guidance of the: (1)subsidiaries’R&D laboratories,(2)integration (communi-cation) between headquarters andsubsidiaries, (3) subsidiary entrepreneurialorientation,(4)subsidiarylifetimeand(5)entry viagreenfieldinvestments.Moreover,thestudyofBezerraand Borini(2015)teststheimpactthatanationdevelopmentexerts onthereverseinnovationtransferinproductsandprocesses.In thisstudy,theysoughttounderstandwhichdeterminantsofRKT arepresentinBrazilianmultinationals.Inourstudy,weshowthat RKTisrelatedtothedegreeof:(1)knowledgecomplexitythat isbeingtransferred,(2) subsidiaryautonomyand(3) external embeddednes.Ashighlightedbynumerousauthors(Minbaeva, 2007;VanWijk,Jansen,&Lyles,2008),suchaspectsare
iden-tified as key ones for understanding the RKT phenomenon.
Althoughtherearemanykindsofknowledgetobetransferred throughconventionaland/orreversedirection,thisstudyfocuses specificallyonthetechnologicaltypeofknowledge(ofproduct andprocess).Ourfindingsarebasedinananalysisofthesurvey responsesadministeredto78Brazilianmultinationalsthatown subsidiariesindevelopedandemergingmarkets.
Asacontribution,itisexpectedthatourstudyadds knowl-edgetotheinternationalbusinessestheory,sincetheknowledge transferhasbeentreatedasakeyfactorofcompetitiveadvantage ofMNEs(Borinietal.,2012,2014;Govindarajan&Ramamurti, 2011)and,specifically,oftheemergingmultinationals compa-nies(Cuervo-Cazurra,2012;Immelt,Govindarajan,&Trimble, 2009;Ramamurti,2008).Sincemostresearchthatexplainsthis phenomenonisbasedonMNEswithsubsidiariesand headquar-tersindevelopedcountries,lessaffectedbyinstitutionaldistance (Rabiosi,2011;Yangetal.,2008),onecannotassumethatthe factorsthatinfluenceRKTfromforMNEsarethesameasthose for EMNEs (Borini,Costa,& Oliveira,2016).A practitioner contributionofthisstudyseekstoinformEMNEmanagersabout thestrategicdriversofRKT.
Thispaperisstructuredasfollows:thenextsection, “Con-ceptualframework”sectionpresentstheproposeddeterminants ofreversetechnologytransfer.“Methodology”sectionoutlines our research strategy and field procedures. “Findings” sec-tionpresentsourresultsanddiscussesthe implicationsof our findingsfor firmsinemergingmarkets.Finally,“Conclusion” sectionpresentsourmainconclusions,somelimitationsofthe study,andavenuesforfurtherresearch.
Conceptualframework
Theliteraturearguesthatknowledgetransfer,whether aris-ingfrominternalorexternalsources,hasanimportantimpact
onorganizationalperformanceandinnovationcapacity(Lyles &Salk,1996;Powell,Koput,&Smith-Doerr,1996;Tsai,2001; VanWijketal.,2008).Theunderlyingideaisthatthetransferred
knowledge contributes to the development of organizational
capabilities that are difficult to imitate and can laterlead to betterperformance(Szulanski,1996).Knowledgetransfer
sti-mulates the combinationof the existing knowledge with the
newly acquired oneandincreasesthe capabilityof aunit for carrying out new combinations (Jansen, Van Den Bisch, & Volberda,2005).
However, transferringknowledge betweenunitsof asame
organization isnoteasierthanconductingexternalknowledge transfers(Kogut&Zander,1992).Thisisparticularlythecase whenitcomestoRKT.Thisprocesscanbeevenmore challeng-ing,sincewhile“[...]theconventionaltransferisaprocessof teaching,thereversetransferisaprocessofpersuading(Yang et al.,2008)”. In thiscase,the effortis muchhigher because its effectiveness dependson convincing headquarters. There-fore,thetransferdependsonheadquarter’sassessmentthatthe featuresandrelevanceofthesubsidiary’sknowledgeiscrucial sothat thereversetransferdoesoccur.TheRKTisdefinedas “an intra-organizationalexchange of information, technology or know-how from internationalsubsidiaries (located inhost countries)tocorporateheadquarters(homecountries).Theterm ‘reverse’ is used todistinguishthesetransfers from themore conventional form of‘forward’ transfers –from headquarters tosubsidiaries–,and‘lateral’transfers betweensubsidiaries” (Ambos,2015).
Somestudieshavehighlightedthatsubsidiariescreate
com-petitive advantages for MNEs when valuable knowledge is
transferred to the headquarters (e.g. Gupta & Govindarajan, 2000; Håkanson & Nobel, 2001; Rabiosi, 2011; Yang et al.,
2008).ForMNEs, someof thedeterminants of RKTinclude
the:(1)knowledgefeaturesbeingtransferred(Minbaeva,2007), (2) organizational characteristics(size, age,autonomy)(Frost et al., 2002; Gupta& Govindarajan,2000),(3) role of orga-nizational mechanisms (Håkanson & Nobel, 2001; Rabiosi, 2011),(4)thesubsidiaries’roles(Ambosetal.,2006;Rabiosi,
2011; Yang et al., 2008), (5) the host country economic
development(Cantwell&Mudambi,2005;Frostetal.,2002; Gupta & Govindarajan, 2000), (6) the absorptive capacity (Ambosetal.,2006),(7)theknowledgerelevance(Yangetal., 2008),(8)theinternalembeddedness(subsidiary/headquarters)
and (9) the external embeddedness (subsidiary/partners)
(Figueiredo,2011;Meyer,Mudambi,&Narula,2011). Following, it is explained how knowledge characteristics, suchascomplexity,autonomy,andexternalembeddedness
influ-enceRKTfromsubsidiariestoheadqueartersofEMNEs.
Subsidiary’sautonomy
Subsidiary’s autonomy could be defined as the extent to
which a subsidiary is allowed to make decisions on its key
strategic issues(Mudambi&Navarra,2004),withouta head-quartersdirectintervention(Roth&Morrison,1992).Ahigher level of autonomyisoften relatedtoknowledge creationand
&Govindarajan,1991;Nohria&Ghoshal,1994),since inde-pendentsubsidiaries,(1)havestrategicmandates(Birkinshaw, Hood,&Jonsson,1998),(2) makequick decisions(Cantwell &Piscitello,1999),(3)recognizeandtakeadvantageoflocal opportunities(Frostetal.,2002),(4)developnewknowledgeas oflocalknowledgebases(Andersson,Forsgren,&Holm,2002), (5)generateintrinsicmotivationonindividuals(Mudambietal., 2007),(6)haveinitiativeandwillingnesstosharetheknowledge acquired(Gupta&Govindarajan,2000;Tsai,2002).Onthe con-trary,alowlevelofautonomy,maylimitthesubsidiaryfreedom, hindering its knowledge creation anddevelopmentcapability (Ghoshal & Bartlett, 1988). Foss and Pedersen (2002) also explainthathighlevelsofsubsidiaryautonomy–associatedwith lossofcontrol–couldbeovercomedbytheincreasein
knowl-edge exchange amongst subsidiaries. While opposite results
havealsobeenreported(Frostetal.,2002;Gammelgaard,Holm, &Pedersen,2004),mostresearches havesuggestedmainlya positiverelationshipbetweenknowledge decentralization and transfer(Cantwell&Mudambi,2005;Foss&Pedersen,2002; VanWijketal.,2008).
Recently,Rabiosi(2008)argued thatRKTiscoupled with
subsidiary autonomy, i.e. mechanisms of personal
communi-cation between subsidiary and headquarters. Yet, regarding
subsidiariesof EMNEs, it is argued that, due totheir recent progressintheinternationalmarketand,therefore,duetotheir earlyage, theyare stronglydependent onheadquarters’ deci-sionmakingpower(Dunning,1993).Thismightnotbedifferent inBrazilianMNEs,thattendtobemorecentralizing,limiting therefore their subsidiaries’ knowledge creation possibilities (Chu&Wood,2008).Thisisanunfavorablesituation forthe developmentofexistingandnewknowledgeattheheadquarter. However,inthesamewayastraditionalMNEs,the international-izationprocessofEMNEsrequiresthecapabilitytoacquireand developknowledge(Mathews,2006).Hence,subsidiariesplay acentralroleinthepursuitofnewknowledge(Borini&Fleury, 2011). Different authors state that EMNEs survival depends evenmoreheavilyonresourcesthathavebeendevelopedabroad whencomparedtothemultinationalsfromdevelopedcountries (Guillén&García-Canal,2009;Mathews,2006).Therefore,this studyadvocatesthatsubsidiaryautonomyiscriticalforRKTin EMNEs,whichallowsustohypothesizethat:
H1. The greater the subsidiary autonomy, the greater the
reverseknowledgetransfer.
Knowledgecomplexity
The increasing specialization and sophistication in R&D requires companies to integrate distinct knowledge areas to developnewproducts.Asaresultknwoledgeturnstobehighly complexanddifficulttoconductintra-knowledgetransfers. A paradox emerges:the greater the number of functional areas andscientific disciplines necessary todevelop newproducts, themorecomplexitistotransfertheknowledge(Ciabuschi& Martín,2012).Knowledgecomplexityisassociatedtothe ampli-tudewhichistheextentofspecializationfields(Grant,1996)and theambiguityofthereferencedknowledge(Reed&DeFillippi,
1990). The greater the number of techniques, organizational routines,peopleandresourcesinvolvedthatareconnectedtoa particularknowledge,themorecomplexitbecomes.These con-ditionsmoderatetheinformationamountthatmustbeprocessed fortheunderstandingofcomponentsinvolved(Simonin,1999).
Thus, management scholars tend to agree on the idea that
complexity hinders knowledge transfersinceit decreases the receiver’sabilitytoidentify,understandandintegratethe knowl-edgetobeacquired(Simonin,1999).Yet,oppositeresultshave beenfoundintheliterature(Minbaeva,2007).Since,complex knowledgeisthemostvaluabletothecompany’s competitive-ness.Studieshaveshown,forexample,thatglobalteamsareable
tosharecomplexknowledgethroughrulesandcodescommon
totheexchangingarea(Reddy,2011).
IntheEMNEperspective,additionaleffortstosharethiskind of knowledgecanbeadvantageous since,as itsimitationand substitution ishampered, it maybe useful tothe buildingof strategic capabilities (Nair,Demirbag, &Mellahi, 2015) due to the prevailing need to use the available foreign resources (Mathews, 2006). A study conducted in Indian
multination-als, for example, found that RKT happens regardless of the
knowledgecomplexity.InBrazilianMNEs,itissuspectedthat onlylesscomplexknowledgefromsubsidiariesistransferredin reversedirection,consideringthattheforeignsubsidiariesrole isdeterminedbytheBrazilianheadquarters(Galina&Moura, 2013)whichstill holdsgreater centralization inthedecisions andinnovations.Accordinglyitwasformulatedthefollowing hypothesis:
H2. Thelowerthecomplexityofthesubsidiary’sR&D knowl-edge,thegreaterthedegreeofreverseknowledgetransfer.
Localembeddedness
EmbeddednesisrelatedtothenotionthatMNE’scompetitive performancecanbefacilitatedthroughthesocialrelationships they create withseveral business players such as customers, universities and local research institutions (Grabher, 1993; Granovetter, 1985; Uzzi, 1996). More specifically, embed-dedness refers tothe mutual adaptation of activitiesbetween
two companies as much as a common understanding of the
collective targets and appropriate ways to work in a social system (Tsai & Ghoshal, 1998). Therefore, it is considered as astrategic resourcefor MNEs.It provides easyaccess to the resources and capabilities that are outside the company (Anderssonetal.,2002;Uzzi&Gillespie,2002)thatareable
to generate a large knowledge transfer among the partners
(Figueiredo,2011;Uzzi&Gillespie,2002).
Indirectly,localsubsidiaryembeddednesscanfosterknowledge transfertootherMNE’sunits(Powelletal.,1996;Yamin&Otto, 2004),constructing,inturn,thesubsidiary’spowerrelationships withintheMNE(Andersson,Forsgren,&Holm,2007).
Higher levels of subsidiary embeddedness are related to
an understanding of the context in which the local
knowl-edge resides. Frequently,subsidiariesinteractwithits closest networkof local companiesandinstitutions inorder tolearn aboutcustomersandtechnologiesand, therefore‘capture’the localknowledge(Figueiredo,2011).Subsequently,itmustuse theconnectivityalreadyestablished withintheMNE network for transferring the knowledge in reverse direction (Meyer et al., 2011; Najafi-Tavani, Giroud, & Andersson, 2013).
Regarding MNEsof emerging markets,Child andRodriguez
(2005),Mathews(2006)andLuoandTung(2007)emphasize the importance of relationships andknowledge opportunities availableatsubsidiarieshostingmarkets.Forexample,
provid-ing easy access to technologies found in developed markets
(Figueiredo,2005).RamamurtiandSingh(2009,pp.126–127)
showthatEMNEscanpursueseveraldifferentstrategies,such as“low-costpartners”,“globalconsolidators”and“globalfirst movers”.Basedonthesearguments,thefollowinghypothesisis suggested:
H3. Thegreatertheembeddednessofaforeignsubsidiary,the higherthereverseknowledgetransfer.
Methodology
Sampleanddatacollection
Thesample ofthisstudy consistsof BrazilianMNEswith manufacturing,salesorR&Dsubsidiariesabroad.Weexpected thatsubsidiarieswithmorestrategicactivitieswouldhavemore opportunitiesof transferringknowledgetotheheadquartersin reversedirection.Thedatawascollectedusinganeletronic sur-veywithBrazilianMNEssubsidiariesestablishedabroad(see
Appendix1).Duetothenon-existenceofanofficialnumberof Brazilianmultinationalsowning subsidiarieswitheither man-ufacturingorR&Dcentersinstalledabroad.Thefirststepwas toidentifyBrazilianmultinationalspresentingthese character-isticsfromsecondarydatasources,suchasGINEBRAProject (ManagementSystemfor theInternationalizationofBrazilian Enterprises) that resulted in the publication ‘Business Man-agementfor the Internationalization of BrazilianCompanies’ (coordinatedbyFleury,2010),anannualsurveyoftheFundac¸ão DomCabral(DomCabralFoundation),ValorEconômico( Eco-nomicValue),andSOBEET(BrazilianSocietyofTransnational Corporations)surveysaswellasdatafromtheBrazilian Multi-nationalsObservatory (CenterofBrazilian Multinationals)of theESPM(SchoolofHigherEducationinAdvertisingand Mar-keting).
In this secondary sources, 63 multinational companies
were listed, being possible to identify 240 subsidiaries with foreign manufacturing operations and/or R&D centers. Of thispopulation,39Brazilianmultinationalsparticipatedinthe survey(61.9%),with78responses,correspondingto32.5%of
allsubsidiaries.Thismeansthatinsomecasesresponseswere receivedfrommorethanonesubsidiaryperheadquarter.
Intheattempttoidentifypossibleshortcomingsor misunder-standingsinthesurvey,apre-testwasconductedtogetherwith specialists from academia andindustry(Cooper &Schindler, 2003)whichhelptogeneratenewinsightsandadjustmentsin thequestionnaire.Following,theelectronicsurveywassentto participants,withafollow-upphone-calltoclarifyanyquestions fromrespondents.Thetotalperiodof datacollectionwasfive
months, fromOctober 2013 uptoFebruary 2014.Responses
were collectedfromR&Doffices andtherespondentsranged fromsubsidiarydirector,internationalbusinessandR&D direc-tor,andengineeringmanagers.
Measures
Dependentvariable
Thedependentvariable(reverseknowledgetransfer–RKT) represents, overthe lastthreeyears,therate of RKTof tech-nology andmarket knowledge that the subsidiary transferred back totheheadquarters. Inordertodetailthe typesof tech-nologicalcontent,itwasappliedtheIammarino,Padilla-Pérez, andVonTunzelmann(2008)scale,whichwasvalidated previ-ouslybyotherauthors(Lall,1992;Bell&Pavitt,1995;Ariffin andFigueiredo(2003)),whorankthetechnologicalknowledge transferintermsofproductandprocess.Onafive-pointscale (rangingfrom1“notatall”to5“toaverygreatextent”).For ensuring therobustnessresults,it wasalsoinserted adummy variablewhichallowedtherespondenttoindicatethecasesin
whichthe subsidiary hadneverdone or haddonethe reverse
transferofaspecificproductorprocessknowledge(0or1).
Independentvariables
The knowledge complexity construct measures the
num-ber of interdependent technologies, routines,individuals,and resources linkedtoaparticularknowledge orasset (Simonin, 1999).Moreover,thecomplexityconstructwasmeasuredusing a six-item Likert scale based on responses (1=strongly dis-agree;5=stronglyagree)(adaptedfromSimonin,2004;Zander &Kogut,1995).Thesubsidiaryautonomymeasureindicatesthe extenttowhichasubsidiaryisallowedtomakedecisionsabout its key strategic issues (Rabiosi, 2011).The measureof sub-sidiaryautonomywasbasedonascaleoriginallydevelopedby
GhoshalandNohria(1989)andlaterusedbyBirkinshawetal. (1998)andRabiosi(2011).Afive-itemLikertscaleassessedit. Thesubsidiaryembeddednessindicatesthecollaborationdegree withthelocalnetworks.Inparticular,thisstudyfocusesonthe subsidiary embeddedness withlocalcustomersandsuppliers. ThisconstructwasdevelopedbasedonAnderssonetal.(2002, 2005).Afive-itemLikertscaleassessedit.
Controlsvariables
Subsidiarylocation. Thehostcountryhasbeenrelatedto fac-tors that impact the subsidiary development and positioning (Birkinshaw & Hood, 1998; Gupta & Govindarajan, 2000; Cantwell&Mudambi,2005;Rabiosi,2011)aswellasthenature ofRKT(Yangetal.,2008).Particularly,thishappensbecausethe subsidiary’scapabilitiesandskillscouldreflectthecountry tech-nologicalandinstitutionalforces,suchaslegalandinstitutional factors(forexamplepatentprotectionandindustrialincentives) that ensure the proliferation of innovation. The assumption, therefore,isthatcompaniesinemergingmarketsgetinvolvedin lessinnovationthancompaniesindevelopedmarkets,duetothe lackofhightechnologyinemergingmarkets(Vernon-Wortzel& Wortzel,1998).Thus,thehighertheeconomicdevelopmentof thesubsidiary’shostcountry,thegreaterthebenefitsearnedby theheadquartersarisingfromthetransferredknowledge(Frost etal.,2002).
Foremerged market MNEs, subsidiarieslocated in
devel-opedor high-incomecountriescanimpactthe rateandspeed ofRKT,sincetheresourcesavailableinthesemarketscanhelp increasetheheadquartersbreadthandnovelty(Mathews,2006).
Onthecontrary,Aulakh(2007)andCuervo-CazurraandGenc
(2008)arguethatemergingmarketMNEshavethesame knowl-edge resources than those operating in developed countries. In the specific case of Brazilian companies,Bezerra, Borini, and Maclennan(2015) have concluded that MNEs’ Brazilian subsidiarieslocatedindevelopedcountriestransfermore knowl-edgeinreversedirectionthansubsidiarieslocatedinemerging countries.Inordertocapturethesubsidiarylocationeffectson
thelevels ofRKT,thedummyvariablelow-income countries
(0)andhigh-incomecountries(1)wereaddedtothemodel.
Subsidiary’sage. More ancientsubsidiariescould havesome advantagesovernewerones dueto(1) theincreased informa-tionandresources,(2)thehigherdevelopmentofR&Dskills, (3)acquiredexperienceandexpertise,and(4)increasedlearning curveeffects.Thereforetheymightbelessdependenton knowl-edge from headquarters (Foss &Pedersen, 2002; Yamin and Otto,2004).Previousstudiesshowbothpositiveandnegative effectsoforganizations’sageregardingthelearningand innova-tionoutcomes(Sørensen&Stuart,2000).Whilepositiveeffects are justified by the knowledge increase, accumulated experi-ence and possessionof stronger relationships with suppliers, andcustomersthatenabletheinnovationprocessimprovement (Cohen&Levinthal,1990).Negativeeffectsareassociatedwith upgrade difficultiesof moremature companies withexternal technologicaladvances,attheriskofbecominginertandlimited forlearningandadaptingtonewcircumstances.Inotherwords, thereisalossofinnovativecapacity(Sørensen&Stuart,2000; Tushman&Anderson,1986).
Inthisregard,intheBrazilianmultinationalscontext,Bezerra etal.(2015) foundthat the younger asubsidiary, the greater its extent of RKT.Thus,despite the inconclusive findings of subsidiaries’age,itisexpectedthatoldersubsidiariesaremore likelytodevelopandtransferbackknowledgetoheadquarters thanrecently establishedsubsidiaries. Particularly, duetothe periodofexistenceofBraziliansubsidiariesismuchlowerwhen comparedtoemergedmarketsubsidiaries.Inordertocapturethe
subsidiaryageeffectsonthelevelsofRKT,thedummyvariable young(0)andoldsubsidiary(1)wereaddedtothemodel.The detailsofeachvariable,includingindicatorsandauthors,used asbackgroundispresentedinAppendix1.
Dataanalysis
Adescriptiveanalysiswascarriedouttoidentifythe frequen-ciesofrespondents’answersforallconstructscomprisedinthe survey.ThePartialLeastSquare–StructuralEquationModeling (PLS-SEM)wasused toassessthedeterminants’influenceof RKT(Hair,Hult,Ringle,&Sarstedt,2014).Thestructuralmodel wasestimatedonSmartPLS3.0(Ringle,Sarstedt,&Schlittgen, 2014)usingthe‘path’weightingscheme.Thedecisiontouse thismethodtookintoaccount anumberof criteria,including (1)thefactthattheindicatorsdonothaveanormaldistribution,
whichisoneofthe assumptionsfor theuseof themaximum
likelihoodmethod(ML);(2)theuseofintervalscales(Joreskog &Wold,1982);(3)itsabilitytodealwithmorecomplexmodels ascomparedtoLISREL(Henseler,Ringle,&Sinkovics,2009); and(4)thesmallsamplesize.
Since the PLSalgorithmformulation(Hui &Wold, 1982; Lohmöller, 1989) is recognized that it is biased and is only “consistent at large”,whichmeans that the biasdecreases as the numberof indicatorsbylatent variableis increased.This issueoccursbecausetherelationshipsamongstlatentvariables (correlationsand pathcoefficients) are estimated as from the factorialscores,whichareobtainedasasumoraweighted aver-ageoftheirindicators,includingthemeasurementerrors.This factistreatedascorrelationattenuationinthemethodological referencesrelatedtopsychometrics,forexample(Nunnally& Bernstein,1994,p.212).However,despitethisbias,Hairetal. (2014,p.79)mentionsomesimulationswhereitisidentified thatthebiasissmallforpracticalpurposes.Forfourandeight indicatorsbylatentvariable,ChinandNewsted(1999,p.333)
foundabiasequalto0.05.Tominimizethisbias(attenuation)the latentvariablesweremeasuredwithfivetosixindicatorseach, reachingreliabilityvalues(compositereliabilityandCronbach’s alpha)higherthan0.8(Table2).
Additionally,toassessthisbiassize,thedisattenuated cor-relations were calculated (or “correction” for attenuation as
explained by Nunnally and Bernstein (1994, p. 241) of the
dependentvariable(RKT)withtheotherindependentvariables (Table1).
Itisobservedthatthehighestbiaswasequalto0.053.Asthis isasmallbiasforpracticalpurposesandisintheconservative direction(underestimatingthepopulationparameter),theresults wereconsideredadequateforpurposesofresultsinterpretation fromthepointofviewofstatistical significanceandpractical importance.
Table1
DisattenuatedcorrelationsofthedependentvariableRKT.
Statistics 1.Age 2.Country 3.Complexity 4.Autonomy 5.Embeddedness 6.RKT
CorrelationwithRKT −0.150 0.350 0.270 0.300 0.410 1000
Compositereliability 1 1 0.890 0.880 0.900 0.870
DisattenuatedcorrelationwithRKT(usingCR) 0.161 0.375 0.307 0.343 0.463
Attenuation −0.011 0.025 0.307 0.343 0.053
Using the population effect formula f2=R2/(1−R2) (Cohen,
1998),itwasconcludedthattheresearchwilldetectaminimum
R2of0.1507.
Findings
TherespondentsincludedalargevarietyofBrazilian
multi-nationals ranging from natural resources (12%), consumer
goods(21%), basicinputs(32%), manufacturing (19%),
sys-temassembly(10%) andrawmaterialsforconstruction(6%).
The responding subsidiaries locations were: Latin America
(42%),NorthAmerica(24%),Asia(14%),Europe(14%)and
Africa(5%).Atthe countrylevel,the largestnumberof
sub-sidiaries are in the U.S. (15%), Argentina (15%), Colombia
(10%)andMexico(9%).Moreover,China(6%)alreadyappears as an important destination for Brazilian subsidiaries. As to
the size and numberof employees at the subsidiary, 56% of
responding subsidiaries are in the range 100–1000
employ-ees, followed by 14% of subsidiaries employing more than
1000workers.Thisdescriptivestatistics showsthatarelative percentage of subsidiariesconsist of consolidated companies abroad.Asregardtothesubsidiaries’age,themajority(69%)
is under ten years of age, 22% are between ten and
nine-teenyears andonly9%are morethan 20yearsof activities.
The entry mode of Brazilian subsidiaries abroad represents
77% acquisitions and 23% direct investment or greenfield
investment.
Evaluationofthemeasurementmodel
In measuring the constructs, the model wasconducted by
evaluatingtheconvergent,discriminantandreliabilityvalidity. AspresentedinTable1,theconstructs(alsocalledlatent vari-ables)weremeasured using reflectiveindicatorstoverify the adequatereliabilityoftheCronbach’salphavalues.Inaddition, all latent variablesachieved convergent validity, that is, they haveanaveragevarianceextracted(AVE)higherthan0.5,and compositereliabilityhigherthan0.7(Hairetal.,2014;Henseler etal.,2009;Tenenhaus,Vinzi,Chatelin,&Lauro,2005). How-ever,threeitemsofthescaleshadtoberemovedfromthemodel so that theAVE reached thereference value(3.7;4.2; 4.4in
Appendix1).Thediscriminantvalidityisverifiedbythe For-nellLarckercriterionandwasevaluatedthroughthecross-loads analysis. Thisfacilitated todetermine whether a construct is trulydistinctfromotherconstructsthroughempiricalpatterns. Basedonthisresult,itwasnotedthatallcorrelationsamongstthe latentvariablesweresmallerthanthesquarerootoftheaverage
varianceextractedoftheirlatentvariables(Fornell&Larcker, 1981).Thus,itcanbesaidthatthemodelpresentedconvergent, discriminantandreliabilityvalidity.Themeans,standard devi-ations,reliabilityestimatesandfactorcorrelationsarereported inTable2.
Assessmentofthestructuralmodel
Thestructuralmodelisabletospecifytherelationship pat-ternsamongsttheconstructs.Themodelwasassessedusingfive criteria:(i)pathcoefficients(β);(ii)pathsignificant(p-value); (iii) varianceexplain(R2);(iv)effectsize(f2)and(v) predic-tiverelevance(Q2).AccordingtoHairetal.(2014),themain criteria for the structural model evaluationare thecoefficient ofdetermination(R2)andthelevelandsignificanceofthepath coefficients(β).Tocalculatethem,thepathweightingscheme andabootstrappingtechniquewereusedwith78observations and 500 randomsamples to estimatethe t-values inorderto assessthe significance.Forsocial scienceresearches,R2 val-uesof0.26,0.13and0.02areconsideredstrong,moderateand weak,respectively(Cohen,1998).
Continuing Fichman and Kemerer (1997), in addition to
the full model, we have evaluated two nested models
(con-trolmodelandtheoreticalmodel).Intotal,thesethreemodels were accessed toevaluate the true impact andthe additional explanatorypowerofthetheoreticalvariablesafterthevariance explainedbythecontrol.Thefullmodelincludesallthisstudy variables,thecontrolmodelincludesonlythecontrolvariables, and thetheoretical model includesthe hypothesized
relation-ships.Comparisonsamongstthethreemodelsaresummarized
inTable3.
TheR2valueresultsforthefullmodel(includingcontrol vari-ables)indicatethatthevarianceof36%inRKTwasexplained bythemodel.Thisresultisconsideredsubstantialandprovides evidence thatthe model iscapableof explainingthe depend-entvariable(Cohen,1998).Whencomparingtheresultsofthe adjusted R2 (33%) with the sensitivity analysis on statistical power,itisfoundaR2valuewellabovetheminimumdetectable bythemodel,whichis15%.
A comparison between the full model and control model
Table2
Evaluationofthemeasurementmodel.
Variables Mean S.D. AVE C.R. C.A. 1 2 3 4 5 6
1.Age 10.8 11.1 1.00
2.Country – – 0.13 1.00
3.Complexity 3.7 1.1 0.61 0.89 0.86 −0.18 0.19 0.78
4.Autonomy 3.2 1.0 0.55 0.88 0.90 0.07 0.17 0.03 0.74
5.Embeddedness 3.0 1.0 0.53 0.90 0.87 0.08 0.28 0.02 0.07 0.73
6.ReverseTransfer 3.0 1.0 0.54 0.87 0.83 −0.15 0.35 0.27 0.30 0.41 0.73
Note1:Inboldonthediagonal,therearevaluesofthesquarerootoftheaveragevarianceextracted. Note2:AVE,averagevarianceextracted;C.R.,compositereliability;C.A.,Cronbachsalpha. Note3:AVEbenchmarks:0.5;compositereliability:0.7;Cronbach’salpha:0.6.
Table3
Significancetestresultsofthestructuralmodelpathcoefficients.
H Pathfrom To Fullmodel Controlmodel Theoreticalmodel Effectsize(f2)
β p-Values β p-Values β p-Values
Age RKT −0.182 0.01** −0.212 0.00***
Country RKT 0.195 0.04* 0.408 0.00***
H1 Autonomy RKT 0.188 0.04* 0.252 0.01** 0.05
H2 Complexity RKT 0.246 0.01** 0.262 0.00*** 0.08
H3 Embeddednes RKT 0.351 0.00*** 0.395 0.00*** 0.15
ReversetransferR2 0.36 0.19 0.30
R2 0.17 0.06
Valuesoftwerecalculatedthroughbootstrappingwith500resamplesand78casespersample.
* p≤0.05. ** p≤0.01. ***p
≤0.001
Comparing the full model and the theoretical model, the
incrementalvariancederived bythemodelisaround 30%for RKT.Resultsindicatethatthetheoreticalmodelinthisstudyis substantiveenoughtoexplainthevarianceintheresearchmodel. However,controlvariableswereresponsibleforaconsiderable proportionofthevarianceintheR2valueofRKT.Asthe pre-dictedpathsforthestructuralmodel,allthehypothesizedwere statisticallysignificant.Theconfidencelevel inthe prediction modelwasmeasuredbytheindicatorQ2whichmustbehigher thanzero.TheQ2valuetoconstruct‘RKT’is0.171ensuring themodelpredictiverelevance(Hairetal.,2014;Henseleretal., 2009).
Theeffectsize(f2)measuresthemagnitudeofan indepen-dent variableon a dependent variable(Tabachnick & Fidell,
2007).The exogenous constructs omission of the model can
beusedtoassessinwhichcasetheseomittedconstructshave substantialimpactontheendogenousconstructs.Cohen(1998)
providedvaluesof0.02,0.15and0.35consideredweak, mod-erateandstrong,respectively.The f2 isalsocalculatedbyR2
included=f2−R2excluded/1−R2included(Hairetal.,2014). Following,Table3showsthesignificanceresultsofeachpath amongstthelatentvariablesandtheeffectsize.
Theresultssupporttwoofthethreehypothesesstatements.
Hypothesis H1 shows that autonomy has a positive and
significant effectonreversetransfer(β=0.19, p≤0.05).The effectsize (f2) of 0.05 indicates that theconstruct subsidiary autonomyhasaweakeffectontheendogenouslatentvariable RKT(Cohen,1998).Hypothesis H2 statesthat the lowerthe
complexityofsubsidiary’sR&Dknowledge,thelargertherate of reverse technology transfer to headquarters. Surprisingly, this study’s results showed that knowledge complexity has a significant, but positive effect on reverse transfer (β=0.25,
p≤0.01).Thisrelationship ischaracterizedby aweakeffect (0.08)ontheendogenouslatentvariable‘RKT’(Cohen,1998). Finally,theresultsshowedthatsubsidiaryembeddednesshasa significantandpositiveeffect(0.15)onRKT,whichconfirms
H3 hypothesis (β=0.35, p≤0.001). This relationship is
characterizedbyamoderatetostrongeffectontheendogenous latentvariable‘RKT’(Cohen,1998).
Withregardtothecontrol variables,thelocalizationeffect waspositiveandsignificant(β=0.19,p=0.05)forRKT, indi-catingthatsubsidiarieslocatedindevelopingcountriesaremore likelytotransferknowledge inreversedirection.Alsofor the subsidiaryagevariablethecoefficientissignificant(β=−0.18, p=0.01)butthenegativesignindicatesthatRKTismorelikely to occur from young subsidiaries, confirmingthe findings of
Bezerraetal.(2015).
Discussion
Despiteambiguous evidenceabout RKTin Brazil(Fleury
& Fleury, 2011), this study found that Brazilian subsidiaries withahighautonomydegreearemorecapableoftransferring knowledgebacktoheadquarters,confirmingourhypothesisH1.
An argument on the positive effect of autonomy for RKT is
greater accesstolocalknowledgedatabases,knowledge from local partners andpossibilities to innovate(Andersson etal., 2002;Ciabuschi&Martín,2012;Gupta&Govindarajan,1991; Cantwell&Mudambi,2005).Hence, subsidiaryautonomy is recognizedasanimportantpredictorofreverseknowledge trans-ferinthecontextofEMNEs.Autonomyempowerssubsidiaries toexploretheirownbusinessandmarketopportunitiessothat
they can make use of external sources to their competitive
advantage. Taking into account that Brazilian multinationals are still at an early stage of internationalization, it is a new phenomenon the fact that their subsidiaries have been
seek-ing for autonomyandindependence fromtheir headquarters’
decisions.
Thispaperidentifiedthatknowledgecharacteristicsand sub-sidiarycharacteristicsdeterminetherateofreverseknowledge transferfromsubsidiariestoemergingmarketMNEs.First,from theknowledgecharacteristicsviewpoint,itwaspossibletoshow thattheknowledgecomplexitylevelhasapositiveimpactonthe extentofRKT.Thisfindingiscontrarytothisstudy’shypothesis (H2),whichsuggestedthatthelowerthesubsidiaryknowledge complexity,thegreatertheRKT.Itissuspectedthatoneofthe reasonsforthisintriguing,butinterestingresult,mayberelated
totheknowledge complexityparadox,because,while
knowl-edgetransferencountershighercostsproblems,itisthe most
compensatory type of knowledge to the headquarters. Thus,
itissuspectedthat theBrazilianmultinationalstrytotransfer the mostcomplex knowledge developedintheir subsidiaries, regardlessofthecomplexitylevelsassociated,whichincludes theinvolvementtoagreaterextent,oftheheadquarterssothat thistype of transfer actually materializes (Nairet al., 2015). Sucharesultisalsoinlinewiththeframeworkoflearningand effective leverage(Mathews, 2006)of theEMNE’s resources andnetworksabroad(LLLchart).Otherpossibleexplanationis theeffectofsubsidiary’srole.Forexample,moreinnovative sub-sidiariesmighttransfermorecomplexR&Dknowledge,which suggeststhatimplementerandcontributorsubsidiariesmaynot transfer(ortransfertoalesserextent)complextypeknowledge. Insummary,althoughtheinitialH2wasnotsupported,thisresult providesanopportunitytosuggestthatinnovativesubsidiaries
mayengageincomplexknowledgetransferandthusbecomea
competitiveplayer.
OurresultsalsosupportthehypothesisH3whichproposes thatlocalembeddednessimpactstherateofRKT.Itwasfound thatembeddednesswithsuppliersandcustomers,inotherwords, localbusinessnetworksincreasethepossibilityofgainingaccess
tonew knowledge,whichcan subsequently be transferredto
EMNEs. This paper confirms that subsidiaries from
emerg-ing market multinationals become internationalized in order toexploreknowledgeandexistingcapabilitiesinforeign
mar-kets as well as to develop new knowledge and capabilities
throughknowledgeavailableinthesubsidiaries’host environ-ment(Narula,2012).Forsubsidiariesisessentialtobeembedded inlocalbusinessnetworkstoobtaindistinctiveknowledge devel-opment.Newconnectionswithlocalnetworksallowsubsidiaries toperforminnovative tasksfor headquarters,instead of tasks limited to adaptation of products and processes to the local market(Borini&Fleury,2011).
Withregardtothefirstcontrolvariable(location),theresults indicatedthat subsidiarieslocatedindevelopedmarkets,such asNorthAmericaandEurope,areprobablytheonesthatmost transferknowledgetotheirheadquarters.Thisresultisinline withseveralcontributionsintheliteraturewhichstatethatthe innovationcapacityofsubsidiarieslargelydependsonthehost countriesadvantages(Gupta&Govindarajan,2000;Cantwell &Mudambi,2005;Yangetal.,2008).
BasedonpreviousfindingsaboutEMNEs,twoperspectives canbepresented.Thefirstperspective,ledbyCuervo-Cazurra andGenc(2008),Ramamurti(2008),KhannaandPalepu(2011),
Cuervo-Cazurra (2012) and Ramamurti (2012), argues that EMNEs have a newtype of capability,unlike the traditional MNEscapabilities,whichisrelatedtotheabilityofcopingwith the institutional deficiencies towhichtheyare exposed. This
current advocates that emerging MNEs, for having operated
inenvironmentspresentingdifficultconditions,suchas under-developed premises, corrupt bureaucracies, poor educational institutions and unstable governments, have the “advantages of adversity.”The second perspective,led byauthorssuch as
Mathews (2006) andChild andRodriguez (2005),argue that MNEsplacetheirsubsidiariesindevelopedcountriesasaway toleveragetheirproductive,technologicalandmarketing effi-ciency, following an asset-seeking strategy, looking for their competitiveadvantagesincrease.Therefore,thepreferencesof
emerging MNEs for developing markets exemplify their
ten-dency to explore the “institutional voids”. However when it comes to subsidiaries that transferknowledge in the reverse direction, theyare morelikelytobeincountrieswherethere arebetterinfrastructureconditions,businesssupportinstitutions andfavorablelegalenvironment.
Regarding the second control variable (age), the results surprisingly indicatedthat therewas asignificant correlation, thoughnegative,betweenageandRKT.Thus,theyoungerthe subsidiary, the more likelythe existence of RKT. Apossible explanationforthisunexpectedresultisthefactthatexperience leads to efficiency gains, but on the other hand, in environ-mentswherechangesoccurveryrapidly,theadjustmentbetween organizational capabilities and market demands declines, as the subsidiariesgrow older,having inviewthatmore mature companiestakelongertoincorporatethemostcurrent techno-logical developments (Sørensen &Stuart, 2000).It is inthis perspectivethatageandaccumulatedskillscanbecome disad-vantageswhencomparedtoyoungersubsidiaries.Particularly, this occurs withregard tothe company’s ability to adapt or developmajortechnologicalchanges(Sørensen&Stuart,2000; Tushman & Anderson, 1986). With respect to the group of
emerging MNEs,younger subsidiariesmay be more
influen-tial in the headquarters’ knowledge exactly because they are abletobemoreagileanddynamicinrelationtotechnological developments.
Conclusions,limitationsandfurtherresearch
Thispaperexplainedreverseknowledgeflowsinsubsidiaries
of emerging market multinationals and tested the impact of
Ramamurti,2011).Hence,severalcontributionstothe
knowl-edge flow of RKT in Brazilian MNEs are suggested. First,
incomparison with traditional MNEs, BrazilianMNEs have
a higher interest in reverse technology transfer, due to the higherimportanceofsubsidiariesforheadquarters.Second, sub-sidiariesofBrazilianMNEswilltransferproducts’knowledge justwithabasicandintermediateleveloftechnological com-plexity(Ariffin &Figueiredo, 2003;Iammarinoetal., 2008). Third,ontheprocessofRKTinforeignsubsidiariesofBrazilian MNEs,thisworkexploredtheimpactofknowledgecomplexity characteristicsaswellsubsidiarycharacteristics,i.e.autonomy andembeddedness.TheresultsshowedthatRKTispositively
affectedby knowledge complexity,subsidiary autonomy and
embeddednessofforeignsubsidiarieswithcustomersand sup-pliers. Fourth, it was assessed the effect of the subsidiary’s location and age on the RKT.The results indicate that sub-sidiaries located in developed countries are more likely to
transfer knowledge in reverse direction as well as younger
subsidiaries. Thispaper’s empirical implications suggest that subsidiarieswithhigheraccesstolocalknowledgewillbebetter positionedtoacquirenewknowledgeandconsequentlytransfer itback toheadquarters.Theexternal embeddednesshasbeen indicatedasanimportantdeterminantofRKT.Fromthe view-pointofpracticalimplications,itisnecessarythatsubsidiaries investinmechanismsofrelationshipandknowledgeexchange
to establish strong collaborations with local partners. These findings mayalso beusefulfor policy makersin as muchas understandingtheinnovationtransferpatternisakeycomponent ofacountry’sinnovationsystem.
Animportantlimitationofthisstudyisthatthisresearchis limited tothe narrowcontextofBraziliansubsidiaries,which thereforeimposeslimitstotheresultsgeneralization.Second, thesamplesizeandsamplecompositionturnitdifficulttomake far-reaching generalizations of its results. Third, the survey methodprovidesasnapshotthatreducestheinformationsource credibility,theaccesstotherightpeople,theresponsescontrol, andtheutilizationofonlyonerespondentbycompany.Fourth, itschoiceofcontrolvariables,whichcouldhavecoveredother aspects, possibly stakeholdersinthe achievedresult. Finally, it isassumed somerestrictions relatedtothe unit of analysis andtheinformationfromheadquarters.Furtherresearchescould explore the autonomy and integration degree of subsidiaries fromemergingmarketsmultinationals.
Conflictsofinterest
Theauthorsdeclarenoconflictsofinterest.
AppendixA. Operationaldefinitionofmodelvariables
Indicators Authors
Dependentvariables
Reverseknowledge transfer(RKT)
1.1Developmentofnewproductionprocess;1.2Developmentofnewequipmentand/ortools;1.3 Developmentofnewproducts;1.4Know-howandexpertiseintheformofplans,models,instructions, guides,formulas,specifications,designs,plans,technicaldrawings,and/orprototypestodesignnew products;1.5Resultsofresearchintonewmaterialsandspecifications;1.6Resultsofresearchand development(R&D)intonewproductgenerations.
AriffinandFigueiredo (2003);BellandPavitt (1995);Iammarinoetal. (2008);Lall(1992);Yang etal.(2008)
Independentvariables
Complexity 2.1Itsunderstandingrequirespriorlearningfromotherrelatedtechnologicalknowledge;2.2Its understandingrequiresalargeamountofinformation;2.3Itistheproductofmanyinterdependent routines,individualsandresources;2.4Itincludesmanydifferentskillsorcompetencies;2.5Itis technologicallysophisticatedanddifficulttodeploy;2.6Itiscomplex(vs.simple)
Simonin(2004);Zanderand Kogut(1995)
Autonomy 3.1Implementationofchangesinproductsandservices;3.2Developmentofnewproductsand services;3.3Implementationofchangesinproductionprocesses;3.4Entryintonewmarketsinthe country;3.5Procurementandsupplychainmanagement;3.6.ManagementofPurchasingandSupply Chain;3.7Hiringandfiringofthesubsidiaryworkforce.
GhoshalandNohria(1989); Birkinshawetal.(1998); Rabiosi(2011)
External embeddedness (withcustomers, suppliers)
4.1Customers/suppliershasfullyparticipatedinthedevelopmentoftechnologicalknowledgeinthe subsidiary;4.2Customers/suppliersshowedimportantinitiativesforthedevelopmentoftechnological knowledgeinthesubsidiary;4.3Customers/supplierssatisfiedtherequirementsindeveloping technologicalknowledgeinthesubsidiary;4.4Thetechnologicalsubsidiaryknowledgewaspartially developedwithinthisCustomers/suppliers’premises;4.5Thecooperationwithcustomers/suppliers hasbeencharacterizedbyfrequentinteractions.
LaneandLubatkin(1998),
Anderssonetal.(2005)and
Najafi-Tavanietal.(2013)
Moderatingvariables
Subsidiary’slocation 5.1Low-incomecountries(0);5.2High-incomecountries(1) CantwellandMudambi
(2005)
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