Home-regionorientationininternationalexpansionstrategiesElitsaRBanalieva1andCharlesDhanaraj21InternationalBusiness&StrategyGroup,DAmore-McKimSchoolofBusiness,NortheasternUniversity,Boston,USA;2KelleySchoolofBusiness,IndianaUniversity,Indianapolis,USACorrespondence:CDhanaraj,KelleySchoolofBusiness,BS4033,IndianaUniversity,801WestMichiganStreet,Indianapolis,IN46202-5151,USA.Tel: 1317-274-5694;Fax: 1317-274-3312;email:dhanaraj@iupui.eduReceived: 31December2011Revised: 30September2012Accepted:7October2012Onlinepublicationdate:10January2013AbstractDespitetheemergingconsensusthat most multinational enterprises(MNEs)are regional, systematic theory explaining regionalization is conspicuouslyabsent, and empirical findings on its implications for MNE performance remainmixed. Drawing on internalization theory, we suggest that technologicaladvantage and institutional diversity determine firms home-region orientation(HRO), andweposit asimultaneous relationshipbetweenHROandperfor-mance. We apply insights from the firm heterogeneity literature of internationaltradetoexplaintheinfluenceof technologyonHRO. Wepredictanegativeand nonlinear impact of technological advantage on HRO driven by increasingreturns logic, and a negative impact of institutional diversity on HRO driven bysearchanddeliberationcosts.Wefindempirical supportforourmodel usingsimultaneous equations methodology on longitudinal data on Triad-basedMNEs. Performance significantly reduces HRO, but HROdoes not have asignificanteffectonperformance.Journal ofInternational BusinessStudies(2013),44,89116.doi:10.1057/jibs.2012.33Keywords: internalizationtheory;geographicscope;home-regionorientation;technologicaladvantage;regionalizationdebate;institutionaldiversityINTRODUCTIONInternal inducements to growth are not by themselves profitable opportunitiesfor expansion nor are external inducementsbythemselves.Penrose (1995: 87)Howdomultinational enterprises (MNEs) determine their geo-graphic scope?1This is a central concern for international business(IB)research.Yetironicallytheliteraturehaslongremainedsilentregarding the nuances of locationininternational expansion.2Simplyput, shouldMNEs focus onmarkets closetotheir homecountry(i.e., regional), orfarfromhome(i.e., global)?Therehasbeenanimplicit assumptionthat firmsexpandglobally, acceler-atedbygrowing technology,transportation,andtradelinksacrosstheworld(Ghoshal, 1987; Levitt, 1983; Yip, 1992), andpopularbooks have reinforcedthis notion(Cairncross, 2001; Friedman,1999, 2005). RugmanandVerbeke (2004), intheir iconoclasticstudyoftheFortuneGlobal 500firms, arguedthatmostfirmsarenotglobal,butregional;thatis,theylimittheirgeographicscopetotheir homeregion. Ghemawat (2007) independentlyreportedcorroborating findings that the exorbitant cost of operating atadistance (cultural, administrative, geographic, or economic) betweenthe home and host countries had led to a state of semi-globalization.JournalofInternationalBusinessStudies(2013)44,89116& 2013AcademyofInternational Business Allrightsreserved0047-2506www.jibs.netPropelledbythis provocative insight, anumber ofrecent studies explore the nuances of geographicscope,andaconsensusisemergingthatmostMNEsareregional. Yetsystematictheoryexplainingregio-nalization is conspicuously absent, and empiricalfindings onits implications for MNE performanceremain mixed.Wefocusourresearchontworelatedquestions.Why do MNEs limit their geographic scope to theirhome region? Howdoes this affect MNE perfor-mance? Our research interest is driven by thepressing need to explore the conceptual logicunderpinning the limits of firms geographic scope.AsOsegowitschandSammartino(2007: 46) note,[t]he IBcommunityneeds tourgentlyconfrontthe question why, in an age of purported globaliza-tion, manyof theworlds largest firms appear tohavebarelyventuredbeyondtheconfinesoftheirhomeregion. Inundertakingsuchanendeavor,we recognize the endemic constraints posed by thelimitedavailabilityofpubliclyavailabledata,sinceexistingregulationsdonot mandatedisclosureoffine-graineddata suchas sales across geographicsegments (Herrmann & Thomas, 1996). Even whenfirmsreportsegmentsales, theydefinegeographicsegments in an idiosyncratic manner, making com-parisonacross firms difficult (Rugman&Verbeke,2007). Our goal in this paper is to advance the fieldsunderstandingoftheregionalizationphenomenon.We make the best use of available data by adopting aparsimoniousnear/farbimodal approachtogeo-graphicscope.Werecognizethatsuchanapproachdoesnotexplaineverything. However, simplifyingtheframecanleadtoconceptuallyinterestingandempirically tractablequestions.Indevelopingourconceptualframework,weusethe termhome-region orientation (HRO) (Delios &Beamish,2005;Rugman&Verbeke,2008).Broadly,HROisthepropensityof afirmtoexpandwithinthehomeregionas opposedtooutsidethehomeregion, allowing us to theorize systematically on thestrategicchoicesfacedbythefirm, anditsmotiva-tions for these locationchoices. Over time, HROdrivestheexpansionstrategiesof afirm, andthusdictates a firms geographic scope. Although theinternational finance (French & Poterba, 1991; Tesar&Werner, 1998)andinternational tradeliteratures(Hejazi,2005;McCallum,1995)haveusedthetermhomebiastodescribethegeographicconcentra-tion of portfolio and trade activities of investors andcountries, respectively, we refrainfromusing theterm bias, as it signals an a priori negative connota-tionofthe phenomenon.3Technologicaladvantageandinstitutionalenvir-onment are the twodominant explanatory con-structs intheIBliteratureingeneral, andintheinternalization theory in particular (Buckley &Casson, 1976; Rugman, 1981). In this study, we buildoninternalizationtheorytoinvestigatehowthesetwoconstructsdetermineafirmsgeographicscope.We integrate the increasing returns mechanismcentral tothe technologyliterature (Arthur, 1989;Ciuriak,Lapham,Wolfe,Collins-Williams,&Curtis,2011; Helpman, 2006; Helpman, Melitz, &Yeaple,2004; Krugman, 1979; Melitz, 2003; Nocke & Yeaple,2007) with the notion of firm-specific advantage(FSA)centraltotheIBliterature(Buckley&Casson,1976; Rugman, 1981) to propose a negative andnonlinear relationship between technological advan-tage and HRO. We analyze howinstitutional diversitywithin the home region can influence the search anddeliberationcosts for anMNE, andthus affect itsHRO(Goerzen &Beamish, 2003; Rangan, 2000).While most of the extant work has attemptedtodetecttheimpactofHROonfirmperformance(seeQian, Khoury, Peng, & Qian, 2010, for an overview),webuildasimultaneousequations model focusingonhowperformanceandHROjointlyaffect eachother.Ourresearchdesignuseslongitudinaldataon625Triad-based(USA, WesternEurope, andJapan)public MNEs between 1997 and 2006 and controls fora widerange ofalternative explanations.WecontributetotheIBliteratureinthreeways.First, we provide a parsimonious model of howtechnology and environment shape firms geo-graphicscope. Whiletechnological advantagehasbeenwell-recognizedasacritical factordetermin-ing firms overall internationalization and the entrymodes(seeKircaetal., 2011, foranoverview), itsrelevance to HRO is less apparent. In particular, ournegative nonlinear hypothesis of the effect oftechnological advantage on HROis novel, andbuildsonthefirmheterogeneityliterature(Melitz,2003; Nocke &Yeaple, 2007). Also, the varianceapproachthat we adopt inour regional institu-tional diversity hypothesissheds new lighton whysomefirmswouldavoidtheirhomeregiondespitethe proximity. Second, our comprehensive databaseallowsustotestthegeneralizabilityofregionaliza-tion patterns that Rugman and Verbeke (2004,2008) observedusingtheFortune500Global data.Ourlongitudinaldataaredrawnfromalargedata-base of firms fromtheUnitedStates, Japan, andWesternEurope. Finally, our simultaneous equa-tionsmodel providesaninsightintothecomplexHROperformance relationship, and can explainHome-regionorientation ElitsaRBanalievaandCharlesDhanaraj90Journal ofInternational BusinessStudiestheinconsistentempirical findingsontheimpactofregionalizationonperformance.We first synthesize three debates within theregionalization literature. We then present our con-ceptual framework, followed by our research design.Finally,wediscusstheimplicationsofourfindings,andconcludewithasummaryofourcontributionsandideasforfutureresearch.GEOGRAPHICSCOPEINIBRESEARCHTwo complementary streams of literature have beeninvoked in explaining firms geographic scope:the Uppsala internationalization process model(Johanson & Vahlne, 1977) and the Penrosian capa-bilitymodel(Penrose,1995).Theprocessmodelofinternationalizationposits that MNEs internatio-nalizeincrementallyfromfamiliar andproximateto new and distant locations, increasing their com-mitmenttoforeignlocationsinsmallstepsastheylearn about these newmarkets. Thisminimizestheuncertainty inherent inunfamiliar markets, andthecomplexityof engagingwithpartnersembed-dedinlocal networks(Barkema, Bell, &Pennings,1996; Benito & Gripsrud, 1992; Johanson & Vahlne,1977,2009).HenceMNEsstartashome-regionallyorientedandgradually adjust their internationalexpansiontoward more distant global locations.ThePenrosianperspective(Penrose,1995)comple-ments this learning model by emphasizing thegrowing constraint in managerial resources asMNEs expand internationally. Managerial attentionthatcanbedevotedtocomplexitiesofinternatio-nalization is scarce and, accordingly, MNEs arelikely todeploy their attentiontoproximal andfamiliar opportunities to minimize the cost ofdynamic adjustment, thus favoring a regionalstrategy(Hutzschenreuter, Voll, &Verbeke, 2011;Meyer,2006;Tan&Mahoney,2005).Rugman (2000) formalized the regionalizationhypothesis inhis book, provocatively titled Theendofglobalization: Whyglobal strategyisamyth&howto profit fromthe realities of regional markets.Rugmans(2000)ingenuitywastopresentacorus-catinginsight fromsimple, hand-coded data on thegeographic distribution of sales, overlooked by mostscholars (for exceptions, see Hitt, Hoskisson, & Kim,1997). Researchers inother disciplines havemadesimilar observations. For instance, portfolio researchinfinancehas observedthat USinvestors tendtoholdmorethan90%of their equitywealthinUSassets,andJapaneseinvestorstendtoholdroughly98% of their assets at home (French & Poterba, 1991;Tesar & Werner, 1998). The international trade litera-ture has observedthat intra-regional trade is sub-stantially larger than inter-regional trade (Hejazi,2005; McCallum, 1995). In the strategic managementliterature, studies foundthat diverseindustrystan-dards, demand for local differentiation, and thecomplexityofglobaloperationsdrovebusinessestofocusregionally(Douglas&Wind, 1987; Morrison,Ricks, & Roth, 1991; Roth & Morrison, 1992).Regionalism rules (Ethier, 1998: 1214), but popularmediaandevenscholarlyresearchhaveperpetuatedtheassumptionofanintegratedglobalmarketplace,leading Ghemawat (2007: 1) to question why if atall firms should globalize in a world where distancestillmatters.A decade of research on regionalization hasamassedsignificant empirical evidencefor it, andhas refinedthe methodology andsharpenedthefocus ofinquiry. Figure1 synthesizes the evolutionofthisresearch.Inessence,thisstreampositsthatthere are limits to geographic scope, contrary to theimplicit premise in global strategy research and theubiquitous global claims of CEOs (Bartlett &Ghoshal, 1989; Levitt, 1983; Rugman, 2000). Thedevelopment in regionalization research is bestcaptured by three debates that have invigoratedthestreamfor adecade, namely, howtodefinearegion, how to measure regionalization, and howHROmatterstofirmperformance.DefinitionofRegionWhileregionalizationhasbeendocumentedasanimportant emergingthemefor futureIBresearch(Griffith,Cavusgil,&Xu,2008),thereislittlecon-sensus on how to operationalize a region (seeFigure1). Rugmanandassociates original concep-tualizationof the Triad followed Ohmaes (1985)work. Flores andAguilera(2007) show, throughalongitudinalstudy,thatthegrowingrecentnumberof investments outside the core Triad marketsdemandsamorefine-grainedregionalspecification.Dunning, Fujita, andYakova (2007), using macrodata on foreign direct investment (FDI), confirm thebroad regional patterns, with regions defined bycultureclusters. Sensitivitystudies(Aguilera, Flores,&Vaaler, 2007; Vaaler, Aguilera, &Flores, 2007)suggest that differing approaches using cultural,political, economic, or geographic distances togroup countries canaffect the conclusions abouttheregionalizationpatterns. Arregle, Beamish, andHebert (2009) definedregions ingeographictermsas a grouping of countries with physical continuityand proximity, building on the premise thatHome-regionorientation ElitsaRBanalievaandCharlesDhanaraj91Journal ofInternational BusinessStudiesphysical immediacy is a precondition for a sense ofunity or shared properties(Aguilera et al., 2007: 8).Wefollowthisgeographicdefinitionofaregionforseveral reasons. First, geographic proximity is centraltohowMNEs organizetheir international strategy(Buckley & Ghauri, 2004), because it leads to greatertrade andinvestment linkages (Ghemawat, 2007).Second,thegeographicproximityapproachistime-invariant,whichmightprovideanadvantageoverother regional schemes (Aguileraet al., 2007: 9).Third, while sophisticated regional classificationsbased on culture or other considerations are valuable,they are less useful when the focus of the research ison international corporate strategy, because they areanacademic artifact, intellectually appealing butrelativelyfarremovedfromthepracticeofinterna-tional corporate strategy andgeo-political reality(Rugman&Verbeke,2007:203).MeasuresofRegionalizationIntheirearlystudies,Rugmanandassociatesadvoca-tedtheuseofratioofhome-regionsalesdividedbytotalsales, withthehome-regionsalesincludingthedomesticsales,asausefulmeasureoffirmsregiona-lization(Rugman, 2000, 2005; Rugman&Verbeke,2004). Theauthorsusedthresholds toclassifyfirmsinto regional, bi-regional, and global (Rugman &Verbeke, 2004). Recent research, however, criticizedthe thresholds as arbitrary and suggested that theregionalization hypothesis also needs to be tested lon-gitudinally(Osegowitsch&Sammartino, 2008). Stu-dies also noted that including domestic sales inmeasuring regionalization overstates the degree ofregionalization(Delios &Beamish, 2005; Li, 2005).Two alternative measures of regionalization that haveemergedtake intoaccount domestic market sales,while also isolating the effect of the international restof home region: first, the ratio of rest of home-regionsalestoforeignsales(Banalieva&Eddleston, 2011;Delios & Beamish, 2005; Li, 2005; Rugman &Verbeke, 2008), andsecond, the rationof rest ofhome-region sales to total sales (Elango, 2004;Rugman & Verbeke, 2008). Asmussen (2009) suggestsa measure normalizing the ratios using GDP data, butthemeasurehaslittlepractical appeal. WeusetwoalternativemeasuresforHRO. Thefirstmeasurer1,usestheratioofrestofhome-regionsalestoforeignsales(Delios&Beamish, 2005; Rugman&Verbeke,2008).Thesecondmeasurer2,istheratioofrestofhome-regionsales tototal sales minus theratioofglobal salestototal sales(Asmussen, 2009; Elango,2004; Rugman& Verbeke,2008)4.RegionalizationandPerformanceAlthoughRugman(2000, 2005) andRugmanandVerbekes(2004)original workdidnotassumetheDistance mattersGhemawat (2003)Regionalization perspective(Global 500) Rugman & Verbeke (2004) Challenging regionalizationsmeasure and generalizabilityOsegowitsch & Sammartino (2008)Relevance of the TriadRugman & Verbeke (2007)Macro data using culture clustersDunning et al.(2007) Region options and sensitivityAguilera et al. (2007) 2010 2009 2008 2007 2006 2005 2004 2003 2001 2000Rethinking global strategyGhemawat (2007)Real world managersthink regionalMorrison et al. (1991)Transnationalstrategy for aflat worldLevitt (1983)Prahalad & Doz (1987)Bartlett & Ghoshal (1989)Porter (1990)Yip (1992)Cairncross (1998)Friedman (1999)End of globalizationRugman (2000)TCE theory of regionalizationRugman & Verbeke (2005)RegionalizationJapanese dataCollinson & Rugman (2008)Modify regionalization measureto exclude domestic salesRugman & Verbeke (2008) Normalized measure ofregionalizationAsmussen (2009) RegionalizationItalian dataCerrato (2009) Japanese datalongitudinal FDIArregle et al. (2009):EMPIRICAL EVIDENCEDEFINING REGIONREGIONALIZATION MEASURES2011Figure1 Keymilestonesintheevolutionoftheregionalizationperspective.Home-regionorientation ElitsaRBanalievaandCharlesDhanaraj92Journal ofInternational BusinessStudiesimplications of regionalizationonperformance,several follow-up studies have explored thisquestion, yielding mixed results. While somestudies have founda positive effect of HROonperformance (Qianet al., 2010; Rugmanet al.,2007), otherstudieshavefoundanegativeeffect(Delios & Beamish, 2005; Elango, 2004), andmorerecent studies haveadvancedcontingencyperspectives (Banalieva & Eddleston, 2011; Li,2005). DeliosandBeamish(2005), inanexplora-tory study, found that home-region-orientedJapaneseMNEsweretheworstperformersinthesample.Similarly,Elango(2004)theorizedaposi-tive HROperformance relationship, but insteadfoundthat a greater HROreduces performance,althoughnot significantlyso, for aset of world-wideMNEs. Theseresultshaveraisedaninterest-ing but underexplored question: Why is thehome-oriented multinational firm yso prevalentoverall when its performance is the lowest inthesample?(Delios&Beamish,2005:30).Noneof these studies has explored the simultaneouseffect of performanceonHRO. Afirms strategyandits risk-taking behavior canbe constrainedby its performance. It is possible that under-performing firms lack the financial resourcesto expand beyond the home region, so theyare home-region oriented. Thus we explore thesimultaneous relationship between HRO andperformancetoget abetter understandingof thedirection of causality between performance andHRO.THEORYDEVELOPMENTInternalizationtheory (Buckley &Casson, 1976;Rugman, 1981) suggests that market imperfections structural or transaction-specificraisethetrans-actioncosts across national borders, andleadtointernalization of markets and the creation ofMNEs (Hennart, 2007: 428). Internalizationelim-inates buyer uncertainty and haggling costs,bypasses government intervention through transferpricing, andallows for the use of discriminatorypricingbasedonmarketconditions;thesebenefitscanoutweightheadministrativeandcoordinationcosts of internalization(Rugman, 1981). This hasemerged as a general theory to explain MNEsforeignexpansion(Buckley&Casson, 1976, 2009;Rugman, 1981), andprovides significant insightsintofirmsgeographicscope.Thetheorybuildsontwo core constructs: non-location-bound FSAs,whichcreate anedge for the MNE ina foreigncountry; and the institutional environment, whichdetermines the costs of exploiting the FSAs (Rugman& Verbeke, 2008). We theorize a negative, nonlineareffect of technological advantage and a negativeeffect of institutional diversity within the homeregiononHRO,andargueforasimultaneousrela-tionshipbetweenHROandperformance. Figure2synthesizes our conceptualframework.PerformanceNon-location-boundFSATechnologicalAdvantage InstitutionalenvironmentRegional InstitutionalDiversity H1: (negativenonlinear)H4a: (+)H4b: ()H3: ()Home RegionOrientation H2: ()Control and identifying variablesLocation-Bound FSA (Marketing Advantage)MultinationalityRegional Market AttractivenessFirm AgeInstitutional DistanceFirm SizeIndustry DiversificationIndustry Home Region OrientationLeverage*Currency Zone^Domestic Market Size^RTA Trade^*identifying variable in performance eq.^ identifying variable in home region orientationeq.Figure2 Conceptualmodelandhypotheses.Home-regionorientation ElitsaRBanalievaandCharlesDhanaraj93Journal ofInternational BusinessStudiesTechnologicalAdvantageTechnological advantagerefers totheproprietaryknowledgedevelopedbyanMNEthroughR&Dorotherwise, andembodiedinthe firms processesandproducts. It is regardedas themost valuableasset MNEs own (Caves, 1996; Dunning, 1980).Technological advantage is the most commonlyusedproxyvariableintheliteraturetodenotetheexistence of internalization advantage, implyingthat highdegrees of R&Dintensity indicate thepresenceofintangibleassetsthatleadtocompeti-tive advantage in international markets (Kircaet al., 2011: 32). It is alsoa non-location-boundFSA that propagates firms globally (Anand & Delios,2002; Meyer, Wright, &Pruthi, 2009; Nocke &Yeaple, 2007; Rugman&Verbeke, 2008). Rugmanand Verbeke (2008: 4060) note that MNEs canpenetrate foreignmarkets onlyif theycanbuildupon non-location-bound FSAs, transferable anddeployableinaprofitablefashioninhostenviron-ments. Whiletherelationshipbetweentechnolo-gical advantageandoverall internationalizationiswell-established (Kirca et al., 2011), fewstudieshave analyzed howtechnological advantage caninfluencethefirms distanceof international expan-sion,thatis,HRO(Cerrato,2009).Firm-specific technological advantage is a keyvariableinthenewnewtradeliteratureaswell(Melitz, 2003; Nocke & Yeaple, 2007). In contrast totheearliernewtradeliterature, whereHeckscherOhlinmodels assumedthat trade gains arose atthecountry-orsector-level ofanalysiswithcoun-triesoperatingunderconstantreturnstoscaleandwiththesameproductiontechnology, thenewnew trade theory adopts a firm level of analysis, andembedsfirm-levelheterogeneitywithinKrugmans(1980) model of trade under monopolistic competi-tion and increasing returns (see Ciuriak et al., 2011;Greenaway & Kneller, 2007, for an overview).Increasingreturns,characterizedbythetendencyforthatwhichisaheadtogetevenfarther ahead5(Arthur, 1996; Helpman&Krugman, 1985; Krug-man, 1980; Romer, 1986), embodies the notion thatas the technological advantage grows, it has anincreasingly larger impact on the competitiveadvantage of the firm. Krugman(1979) invokedtheincreasingreturnsargument tointegratecon-sumers preferences for product diversity andproducers preferencesforeconomiesofscale, andshowedthatcountrieswithalargerdemandforaproduct produced a more-than-proportionate shareof that product. By incorporating firm-level hetero-geneityalongwithincreasingreturns, thenewnewtrade theory aligns well withthe empiricalrealitythatonlyafewfirmsparticipateinforeignmarkets, andthose that do export tend to doso byusing newer technologies that would allow them toovercome the large costs of foreign expansion(Ciuriak et al., 2011; Helpman, 2006; Helpmanetal., 2004; Melitz, 2003; Nocke&Yeaple, 2007).While Melitz (2003) and Helpman et al. (2004) treatfirm-level capabilities as a bundle, Nocke andYeaple(2007)distinguishtechnologicaladvantage,which has mobility across geographic borders, frommarketingadvantage, whichlacks suchmobility.This new new trade theory has integrated exportsandFDIseamlessly,andhasinvokedtechnologicaladvantageasacoredeterminantoffirms interna-tionalactivity. Thisisalsoconfirmedbyempiricalstudies onfirmheterogeneity that have focusedon determinants and effects of exporting (e.g.,Bernard, Eaton, Jensen, &Kortum, 2003; Bernard&Jensen, 1999, 2004; Bernard, Jensen, &Schott,2006).Drawingonthisresearch,wearguethattechnol-ogy confers competitive advantage for a firmtoaccessglobalmarketsandovercome thechallengesof increasing distance fromthe home market,particularlyinthreeareas: diversityoftechnologystandards, demandfor differentiation, andglobalcomplexity of management (Douglas & Wind,1987; Morrison et al., 1991; Roth &Morrison,1992). Wedescribethesethreemechanisms next,incorporatinginsightsfromthefirmheterogeneityliterature.First, with increasing technological advantage,thefungibilityoftheproprietaryassetsofthefirmacross geographic borders andthe marginal pro-ductivityof technologyincreaseat anincreasingrate(Melitz, 2003; Nocke&Yeaple, 2007). Whentechnology sophistication is low, technologicalknowledge tends tobe simpler andgeneric, andfirms imitate each others technologies or evenpurchase technologies from third parties (Hashai &Almor, 2008). This increases the threat of imit-ability, andrenders aninsufficient technologicaladvantage for firms to expand beyond their familiarhome regions (Douglas & Wind, 1987). However, astechnological sophistication increases, the MNEgrows increasingly into a standard-setter ratherthana standard-taker, andthe degree of adapta-tion to newand geographically distant marketsdecreasesatanincreasingrate(Bernard&Jensen,1999; Nocke &Yeaple, 2007). As technologicalsophistication grows, it becomes increasingly man-ageableforthefirmtopenetratefartherintomoreHome-regionorientation ElitsaRBanalievaandCharlesDhanaraj94Journal ofInternational BusinessStudiesdistant global markets anddislodge global rivalsthere,asthefirmslockinglobalconsumerstothefirms own technology standards. For instance,sophisticatedtechnologies caneventuallycornerthe market of potential adopters, withthe othertechnologiesbecominglockedout(Arthur, 1989:116).Second, technologyleaders becometrail blazersas theyset newtrends for other firms tofollow(Arthur, 1989, 1996; Nocke&Yeaple, 2007). Theproprietary knowledge gives the firm the resourcesand competitiveness to expand in all regions and tobenefitfromthescaleeconomiesofaglobalplantconfiguration (Belderbos & Sleuwaegen, 2005:579). Whentechnological advantage is low, theMNEsareforced tofightagainstthe local competi-tionfrombothdomesticincumbents andforeignMNEs. Insuchcases, anMNEs foreignness is aliability, becausetheMNEwithlowtechnologicaladvantage is unable to match the technologyefforts of its rivals, andis likely toface erodingglobal, but acceleratingregional market presence(Autio, Sapienza, & Almeida, 2000). However, risinglevels of technological advantage increasinglyenhance the MNEs ability to combine their knowl-edgeonaglobal scale, findmoreefficient globaldistribution channels, andreducethe highcosts ofnewproductdevelopment(Zahra, Ireland, &Hitt,2000). Thus, astechnological advantageincreases,the MNE becomes less burdened withcost, andinsteadbeginstoenjoyapremiumpricingadvan-tageat anincreasingrate(Helpmanet al., 2004;Melitz, 2003). Additionally, the capacity topen-etrate geographically distant markets increasesdisproportionately, with Levitts global marketbecomingacloserreality.Third,increasingtechnologicaladvantageacceler-ates the productivity of managerial attentionin international expansion at an increasing rate(Bouquet, Morrison, &Birkinshaw, 2009; Bouquet&Birkinshaw, 2011). As technological advantageincreases, productivityof the firms resources alsoincreases more than proportionately (Griliches,1986; Hansen &Wernerfelt, 1989; Henderson &Cockburn, 2000). Penrose (1995) emphasizedthatexecutive management is a key resource that isnecessary, but often limiting for the growth of a firm.Managerial attentionforinternational expansionisthe time and effort that headquarter executivesinvest in activities, communications, and discussionsaimed at improving their understanding of theglobal marketplace(Bouquet &Birkinshaw, 2011:244).Itallowsexecutivestostayabreastofongoinginternational expansionopportunitiesandrespondaccordingly with informed strategic actions. As tech-nological advantage increases, organizational costsof coordinationacross the markets decrease at anincreasingrate, andhencefirms wouldbeabletoreachLevitts worldof globalizedmarkets rapidly.Theincreasingabilityof thefirmtolockinglobalconsumers wouldalsolower the managerial com-plexityat anincreasingrate. Concurrently, as thecapacity of the firmto penetrate distant marketsincreases at an increasing rate, a firms HRO decreasesmorethanproportionately.Acombinationoftheseincreasing returns in technologys fungibility, marketpower,andmanagerialproductivityleadsto:Hypothesis1: Ceterisparibus, foraninternatio-nalizing MNE, as technological advantageincreases,HROdecreasesatanincreasingrate.InstitutionalDiversityMNEs operate in diverse institutional environments(Kostova & Roth, 2002; Rosenzweig & Singh, 1991).In the IB literature, two approaches politicaleconomy andsociocultural have beenusedtostudy institutional environments. The politicaleconomystream emphasizesthe riskand complex-ity of investing in a country arising from its regula-tory policy, and uses variables such as political risk,politicalhazard,formal(regulatory,legal,adminis-trative, economic, and geographic) institutionaldistance, political predictability, and restrictiveness(Abdi & Aulakh, 2012; Boddewyn, 1988; Campbell,Eden, & Miller, 2012; Gomes-Casseres, 1990;Henisz, 2000; Salomon&Wu, 2012). The socio-cultural streamemphasizes thesociological/beha-vioral similarity (or distance) between informalrulesofthehomeandhost-countrycultures,oftencapturedwithpsychicorculturaldistance(Abdi&Aulakh, 2012; Campbell et al., 2012; Hofstede,1980; Johanson&Vahlne, 1977; Kogut &Singh,1988). Recent works have attemptedtointegratethese approaches using institutional distance (Abdi&Aulakh, 2012; Berry, Guillen, &Zhou, 2010;Campbell et al., 2012; Kostova & Roth, 2002;Salomon & Wu, 2012; Slangen & Beugelsdijk,2010;Xu&Shenkar,2002).Berryetal.(2010)pro-videacomprehensiveanalysisof varioustypesofinstitutionaldistanceandtheirinfluenceonfirmsforeign entry decisions. Broadly, this literaturesuggeststhatMNEsprefertolocateforeignopera-tions inhost countries that aremoreproximate/similartotheirhomecountry(Flores&Aguilera,2007:7).Home-regionorientation ElitsaRBanalievaandCharlesDhanaraj95Journal ofInternational BusinessStudiesDistance measures are helpful for dyadic (i.e.,homehost country) analysis. However, givenourfocus is on a regional level of analysis, that is, HRO,aregional institutional diversityconstruct becomesmore appropriate (Goerzen & Beamish, 2003),because [f]irms international strategy is set notonly on a country-by-country basis yregional con-siderationsplayanimportantroleaswell(Arregleet al., 2009: 104). Institutional diversity at theregional level is the variationinthe institutionalenvironments across the countries within the homeregion. Unfortunately, IB research has devotedsurprisinglylittleattentiontocomparingthetopo-graphyofinstitutionallandscapesandunderstand-ingtheirdiversity(Jackson&Deeg,2008).Institutional context isacritical factor ininter-nalizationcosts,as institutionsdirectly determinewhat arrows a firm has in its quiver as it struggles toformulate andimplement strategy andto createcompetitive advantage(Ingram&Silverman, 2002:20). Institutionaldiversityincreasestheriskforthedecision-making process, and raises transaction costs(Kostova &Zaheer, 1999). Newcontexts demandhigher information-processing and coordinationcosts, andincreasethecomplexityoflearninghowtomaneuver throughthesediversecountries (Hittetal.,1997;Kostova &Zaheer,1999).Furthermore, MNEs, inpursuingneweconomicopportunities inforeign countries, engage inaprocessofsearchanddeliberation(Rangan,2000:206). Firms incur search costs during the identifica-tionof potential exchangepartners, anddelibera-tioncostsduringtheirassessmentofthecapabilityand reliability of these partners (Rangan, 2000).Incorporatingthesearchanddeliberationcosts intheanalysisallowsustomakeanimportantexten-siontoprior institutional research: namely, whilespatial proximitycanreduce the searchcosts, theinstitutional commonality across the partners withinthe home region can minimize the deliberation costs.As Rangan (2000: 207) notes, search and deliberationareadditivetothepurchaseprice.Internalizationtheory suggeststhatfirmsminimizeboth.Institutional diversityis important not onlyatentry, but all throughthe life of the MNE. Forinstance, governance hazards such as expropriationriskof assets at less thanfull market value, con-straints onthe pursuit of business opportunitiesbecause of weak enforcement of contracts, liquidityrisk caused by local customers delaying or avoidingpayments, etc. cancreatehavocnot onlyinoneparticular country operationbut at the regionalnetwork level as well (Zhou & Poppo, 2010). As thevariance across the institutional environmentswithin the home region decreases, firms can exploitvaluable knowledge created or learned in onecountry within the home region to another countrywithin the home region what Bartlett and Ghoshalrefertoasworldwidelearningtocreatecompe-titive advantage (Chan, Isobe, &Makino, 2008).Whileexplicitcontractswithsuppliers,distributors,and partners can work in some countries within thehomeregion, owingtotheir market-basedinstitu-tions(Zhou&Poppo, 2010), theymaybefutileincountrieswithinthehomeregionwithlessmarket-basedinstitutional frameworks, whichtendtobecharacterized by a greater degree of asymmetricinformationand, hence, riskforahome-regionallyorientedcompany(Chanetal., 2008). Theseargu-ments suggest that spatial proximity is a naturaldriver for firms toconsider home-regionmarkets.However, as regional institutional diversity increases,firms will find alternative global markets moreattractive to avoid the growing regional institutionalcomplexity:Hypothesis2: Ceterisparibus, foraninternatio-nalizingMNE,thegreatertheinstitutionaldiver-sity of its home region, the lower the firms HRO.TheHROPerformanceRelationshipAsdiscussedearlier,weadvanceamodelincorpor-ating a simultaneous relationship between HROandperformance. We first advance the effect ofperformanceonHROinHypothesis3,followedbythe effectof HROon performancein Hypothesis 4.TheimpactofperformanceonHROAs an MNEs resources and slack are conditioned byitsperformance,itswillingnesstotakeriskinnewmarkets will be influencedbyfirmperformance.First, greater firm profitability suggests that the firmhas access toincreasedwealthor slackresourcesthatcanhelpthefirmgrowandallowittopene-trate new, less familiar markets (Fiegenbaum, Shaver,&Yeung, 1997; Nohria &Gulati, 1996; Penrose,1959).Organizationaltheoristshavesuggestedthatsuchresidual resourcesarenecessaryfor flexibilityandgrowth, as theyprovide acushiontoabsorbunexpectedshocks,andallowfirmstotakerisksinmarketexpansion(Bromiley,1991;Nohria&Gulati,1996). Thus increasedfirmprofitability provides abuffer tostoreresourcesanddeploytheminsitua-tions of temporary downturns or difficult competitivecircumstances. Whenafirmperformswell, it canaffordtoexperiment more withnewandriskierHome-regionorientation ElitsaRBanalievaandCharlesDhanaraj96Journal ofInternational BusinessStudiesstrategiesthatcangenerategreaterreturns(Tseng,Tansuhaj, Hallagan, &McCullough, 2007). Globalstrategy has been associated with higher riskcomparedwithregionalstrategy(Elango,2004;Li,2005). Thus a better performance could lead togreaterglobalscopeandalowerHRO.Second, agreateravailabilityofwealthobtainedfromhigher performance would also render themanagers of the organization more inclined to takestrategic risks insearchof newgrowthopportu-nities (Bromiley, 1991). Researchers have longassociatedhigherlevelsofafirmsfinancialwealthwith a greater degree of innovation (Leonard-Barton, 1992). Consistent withthetheoryof thegrowthof thefirm(Penrose, 1959), this suggeststhat managers inwell-performingfirms aremorelikelytochooseglobalmarketsasregionalmarketsassociatedwithanarrowersearchthatcanleadtoincreasingly rigid cognitive maps and highlyspecialized competencies that may become corerigidities(Raisch&Birkinshaw, 2008: 393). Goodperformancealsocreatesabufferthatallowsfirmstowithstandthepossibledangersfromtheriskierglobal segment, andtoestablishadominantposi-tionthereinthelongrun. Thisisconsistentwiththe firmheterogeneity literature, whichsuggeststhat onlythefirms withsufficientlyhighprofitswill be able toovercome the highsunkcosts ofexporting, andthat theforeigngeographicscopeincreases with the productivity of the firm (Bernardetal.,2006;Greenaway&Kneller,2007;Helpman,2006, Helpmanetal.,2004;Melitz,2003). Ciuriaket al. (2011: 5) note, high productivity at thefirmlevel oftenprecedes entryintointernationalmarkets, suggesting the presence of significantfirm-level sunk costs that raise the productivitythreshold that firms must clear to be able toprofitablyenterforeignmarkets.Thus:Hypothesis3: Ceterisparibus, foraninternatio-nalizing MNE, the greater its performance, theloweritsHRO.TheimpactofHROonperformanceAs reviewed earlier, empirical results are mixedregardingtheeffectofHROonperformance(e.g.,Delios &Beamish, 2005; Elango, 2004; Li, 2005;Qianet al., 2010; Rugman, Kudina, &Yip, 2007).Internalization theory would cast regionalization asanoutcomeof thecombinationof resourceposi-tion of the firm and the institutional environment,and does not have specific predictions on theimplications of regionalization for performance.Hennart (2011) convincingly argued that firms canperformwellatdifferentlevelsofmultinationality.While the theoretical argument that regionaliza-tiondoes not influence performance is convinc-ing, itisanarduoustasktotheorizesuchaclaim.Following Hennart (2007, 2011), we set up twocompeting hypotheses, arguing for positive andnegative effects, and use the empirical data toidentifythenatureoftherelationship.HRO can improve firmperformance, becausefirmsattempttominimizesearchanddeliberationcosts (Rangan, 2000) andmaximizethefinancialgains fromeconomies of regional agglomeration(Krugman, 1991; Stigler, 1951). Firms that clusterclosetooneanother benefit fromtheconcentra-tion of their operations as efficiency gains areobtained fromco-located suppliers (e.g., sharedinputs), consumers (e.g., larger markets) (Krugman,1991; Stigler, 1951), and skilled labor marketpooling(Marshall, 1920). Suchco-locationallowsfor easier access to a variety of suppliers, morecompetitive input prices, and greater specializationofproducts(Stigler,1951).MNEscanbenefitfrombothupstreamanddownstreamagglomeration, assuppliers are more likely to cluster when MNEoperations concentrate ina region. Additionally,MNEs can benefit from appealing to similar marketswithinthehomeregion, andhenceenjoyknowl-edge spillover effects due to frequent interactions ofcommonbuyers andsuppliers (Alcacer &Chung,2007). Adams andJaffe (1996) foundthat firmsplantsthat areco-locatedwiththefirms innova-tion activities are more efficient in their productionthan their out-of-state plants. These argumentssuggest that a highHROenables more effectiveinteractions (Rosenthal &Strange, 2003), whichcanenhancefirmperformance.Ontheotherhand,ahighHROcanreducefirmperformanceasitpreventsfirmsfromdiversifyingriskacrossgeographicmarkets(Agmon&Lessard,1977; Dhanaraj &Beamish, 2004; Rugman, 1976;1980).Globaldiversificationisassociatedwithriskreductionasdistant global marketsareless corre-lated with one another than proximate ones(Agmon&Lessard, 1977; Speidell &Sappenfield,1992). The more MNEs are involved in globalmarkets, the more MNEs are able toshare theircostsofproductionacrossgeographicmarketsandincrease their performance (Capar & Kotabe, 2003).GlobalizingMNEs are alsoable toreacha largernumber of global consumers withtheir products,andhenceincreasetheir global market sharevis-a`-visrivals. IncreasingglobaldiversificationisalsoHome-regionorientation ElitsaRBanalievaandCharlesDhanaraj97Journal ofInternational BusinessStudiesassociated with increasing risk reduction from inter-national diversification (e.g., Agmon &Lessard,1977; Dhanaraj &Beamish, 2004; Rugman, 1976,1980). Distant global markets are less correlatedwithoneanotherthanproximateregionalmarkets(Speidell & Sappenfield, 1992), so an MNE pursuingalow-HROstrategyislikelytobelessaffectedbyaregional economic crisis, as it canreadilyshiftexpansioneffortsintoanother,lessaffectedglobalregion, enhancingitsoverallprofitability.IfMNEsconfine their geographic scope to the home region,theymiss out onexploringnewmarket opportu-nities globally, potentiallyexhaustingthemarketopportunities within the home region, and limitingthefirmsmarketshareandprofitability.Addition-ally, inalimitedgeographicspacelikethehomeregion,congestioncostsintheformofincreasedcompetitionfor valuablelabor andcapital inputsor increased risk of knowledge expropriationbygeographically proximate rivals are likely toincreaseandleadtoshortages(Almeida&Kogut,1997; Pouder &St John, 1996; Shaver &Flyer,2000). Thesearguments wouldsuggest anegativerelationshipbetweenHROandfirmperformance.Thus we have two competing hypotheses stated as:Hypothesis 4a: Ceteris paribus, for aninterna-tionalizingMNE,thegreateritsHRO,thegreateritsperformance.Hypothesis 4b: Ceteris paribus, for aninterna-tionalizingMNE, thegreateritsHRO, theloweritsperformance.RESEARCHDESIGNResearchContextWe tested our conceptual framework using datafromtheTriad(i.e., theUS, WesternEurope, andJapan; Ohmae, 1985; Rugman, 2000, 2005; Rugman&Verbeke, 2004). TheTriadisanimportant geo-graphic space, for several key reasons. First, theTriadcountries sharesimilar macroeconomicfea-tures: for example, loweconomic growth, eco-nomic and financial infrastructures, governmentregulations, relatively homogeneous consumerdemand, high purchasing power ability of con-sumers, high urbanization, etc. (Ohmae, 1985;Rugman, 2000, 2005). Second, [t]he Triad is hometomostinnovationsinindustry, andincludesthethree largest markets inthe worldfor most newproducts (Rugman &Verbeke, 2004: 4). Third,Rugman (2000) documented that 86% of theFortune 500 Global MNEs are headquartered in thesecore Triad regions. This high Triad concentration isauseful indicator of theTriadsenduringimpor-tance(Rugman, 2005: 59). Thus, bydrawingonMNEs fromall these markets simultaneously, wehope to enhance the externalvalidity and compar-abilityofourresults.DataSourcesWeusedtheOSIRISdatabasetoextracttheTriad-based firms. OSIRIS is a commercially availablefinancial database provided by Bureau Van Dijkthat includes closeto70,000companies (subsidi-aries and parent firms) from around the world. Thefinancial datainOSIRIScomefromfirms annualreports, and are provided by WorldVest Base(WVB), Korea InformationService (KIS), TeikokuDatabank, Huaxia International Business CreditConsulting Company, Reuters, andEdgar Online(OSIRIS Data Guide, 2007). OSIRIS is seen as one ofthemost comprehensivedatabases of listedcom-panies (Shao, Kwok, & Guedhami, 2010: 1397), andis increasingly being used for international re-search (e.g., Chakrabarti, Singh, & Mahmood, 2007;Chakrabarti, Vidal, & Mitchell, 2011; Rugman, 2007;Rugmanet al., 2007; Rugman, Oh, &Lim, 2012).However, comprehensivecoveragestartsonlyafter1996, whichconstrainedour observationwindow.Furthermore, if acompanydelists, it stays inthedatabase, but its account is no longer updatedannuallybytheOSIRIStechnicalstaff.Noneofthefirms inour samplehaddelistedover thesampleperiod. OSIRIS geographic segment datacoveragealsodepends onthewayfirms report thedataintheirreports.Asmentionedearlier,segmentdisclo-surerequirements arenot systematicacross coun-tries, and limit the data availability by country(Herrmann&Thomas, 1996). Werandomlycross-checked the financial data reported in OSIRIS and inthefirms annual reports, andfoundthat thetwosources are consistent. Adjusting for these datalimitations, our final sample consisted of firms basedin12Triadcountries(i.e.,theUS,Japan,Denmark,Finland, France, Germany, Ireland, the Netherlands,Norway, Sweden, Switzerland, and the UK). Over the19972006 period, these countries collectively repre-sented 62.11% in average GDP share as a percentageoftheworldsGDP,6areasonable coverage.We used the Bloomberg Terminal, a computersystemprovidedbyBloombergL.P., that providesHome-regionorientation ElitsaRBanalievaandCharlesDhanaraj98Journal ofInternational BusinessStudiesreal time andhistorical financial data onpubliccompaniesworldwide, toextractthestockmarketcapitalization for the firms in our sample. Themacroeconomic data in our analysis came from theWorldBankandtheUnitedNations UniversityComparative Regional IntegrationStudies (UNU-CRIS, 2008). The Regional Institutional Diversitydata came fromthe Business Environment RiskIntelligence (BERI) (e.g., Ali, 2003; Chong &Zanforlin, 2000; Knack &Keefer, 1995) and theFraser Indexof Economic Freedomof the Worldco-published by the CATOInstitute, the FraserInstitute, and more than 70 think-tanks around theworld7(e.g., DiRienzo, Das, Cort, &Burbridge,2007; Gwartney, Lawson, Park, Edward, de Rugy,& Wagh, 2002; Nachum & Song, 2011). AppendicesAandBdescribethetwoindexes.We thenproceededbyselecting the sample offirms based in the Triad nations. To ensure the firmswere sufficiently independent todetermine theirownstrategy, weexcludedfirmsinwhichanotherentity held more than 25%ownership, as providedby OSIRIS (Bartram, Brown, How, &Verhoeven,2007; Chen, 2007). We also excluded firms that aresubsidiaries of the sampled firms, because theirfinancial statementdataarealreadyaccountedforin their parent firms consolidated statements.Additionally, toensurethat thefirmsweremulti-national, we focusedonfirms withat least 10%foreign sales (e.g., Nachum, 2004; Sambharya,1995). Wedroppedfirmswithlessthantwoyearsof availabledata,owing tothe panel datastructurerequirements of our model. We also excludedthe financial firms, as they have very differentcapital structures, oftenaffectedbybankingregu-lations for minimumcapital requirements (Rajan& Zingales, 1995). Our approach is consistentwith prior international finance research (e.g.,Fama&French, 1992; LaPorta, Lopez-De-Silanes,Shleifer, &Vishny, 2002; Mehran&Stulz, 2007),whichhasnotedthat financial ratios andvalua-tionmetricsforbanksarenotdirectlycomparabletofinancial ratiosandvaluationmetricsforotherfirms(Mehran&Stulz,2007).IBresearch hasalsofollowedthis practice (e.g., Reeb, Kwok, &Baek,1998). These steps resulted in 625 MNEs from1997 to 2006, or 3061 firm-year observations(33.09% from the US, 28.91% from Western Europe,and37.99%fromJapan). This ten-year period issufficiently long to capture the evolutionary natureofinternationalization(Lu&Beamish, 2004), andistwiceaslongastheaveragetimeframeinpriorstudies(e.g.,Li,2005;Rugman&Verbeke,2008).MeasuresHome-regionorientationFollowingpriorresearch,wemeasuredfirms HROwith the ratio of regional sales (excluding domesticsales)toforeignsales(e.g.,Banalieva&Eddleston,2011; Delios & Beamish, 2005; Li, 2005; Rugman &Verbeke, 2008). The higher the ratio, the higher thefirms HRO. WealsoadoptedanalternativeHROmeasureas arobustness check, whichwediscusslater.TechnologicaladvantageWe capturedfirms technological advantage withthe ratio of R&D expenditures to total sales, a widelyused measure of firms innovation input (e.g., Anand& Delios, 2002; Kirca et al., 2011; Meyer et al., 2009).WeaddedthesquaretermofR&Dexpenditurestototal sales to test our theoretical arguments that tech-nologicaladvantagedecreasesHROatanincreasingrate.We also attempted to measure technologicaladvantage withanother time-varying firm-levelmeasure firmpatents, an output measure ofinnovation (Hall,Thoma, & Torrisi, 2007) but weencounteredseveraldatachallenges.First, becausefirms file for patents with patent offices around theworld, ensuringthatthepatentportfolioforeachfirmovertimeiscompletebecomesachallengingtask(foranoverview,seeThoma,Torrisi, Gambar-della,Guellec,Hall,&Harhoff,2010).Commercialpatent data providers typically do not supplyunique firm-identifying numbers by which toassignpatents tothesamefocal firm, leadingtoover-orunder-countingafirmspatentportfolioifcompanypatent matching is performed basedsolely oncompany names (Thoma et al., 2010).Second, whileThomaetal. (2010)andHall, Jaffe,and Trajtenberg (2001) have collected firms patentdata and provided unique company identifyingnumbers toovercomethecompanyname-match-ingproblem, their database covers onlyapproxi-mately 58.8% of all EPO applications grantedbetween1979and2008. WeattemptedtousetheThomaet al. (2010) andHall et al. (2001) patentdatasets tomatchwiththe firms inour sample.However, thisresultedinasparsepatentportfoliomatrix for each focal firm, owing to the many zerosobtained when firms did not file for patents,leading todifficulties ininterpreting the results.These data-related challenges prevented us fromusing patents asan alternative firm-leveland time-varyingmeasureoffirms technologicaladvantage.Home-regionorientation ElitsaRBanalievaandCharlesDhanaraj99Journal ofInternational BusinessStudiesRegionalinstitutionaldiversityWefollowedtwostepstomeasureRegional Institu-tional Diversity. First, we assigned the countries fromthe BERI indexintohome region andglobalsegments based on the United Nations (UN) countryclassifications (Appendix C), following prior researchthatalsousestheseUNcountrymappings(Arregleetal.,2009;Flores&Aguilera,2007).Sincethegeo-graphic-based approach to country groupings istime-invariant(Aguileraetal.,2007),itallowsustodisentangle the effect ofregional institutional diver-sity from a possible change in region definition overtime.Second,wemeasuredtheRegionalInstitutionalDiversity with the coefficient of variation of the BERIIndexacross thehomeregion, excludingthefocalfirmshomecountry. Thecoefficientofvariationisthe standard deviation of the distribution divided byitsmean.Ahighercoefficientofvariationindicatesgreater regional institutional diversity (Pfeffer &Langton,1993).PerformanceWemeasuredfirms performancewithreturnonassets (ROA); that is, earnings before tax/totalassets (e.g., Bashir, 2003; Charumilind, Kali, &Wiwattanakantang, 2006; Manos, Murinde, &Green,2007).ROAcapturestheabilityofmanagerstoreapprofitsfromtheirinvestedassets. Wealsousedthenatural logarithm of Tobins Q as an alternative per-formancemeasure,whichwediscusslater.ControlvariablesWe controlled for a range of additional factorssummarizedinTable1.MethodologyThe conceptual framework in Figure 2 can bemodeledempiricallywiththefollowingsystemofequations for firm i, home region r, identifying andcontrolvariablej,andyeart:Performancei;t1 a0 a1 HROi;t1 aj Identifying& Control Variablesj;t e1i;t1HROi;t1 b0 b1 Performancei;t1 b2 Technological Advantagei;t b3 Technological Advantage sq:i;t b4 Regional Institutional Diversityi;r;t b5 Identifying& Control Variablesj;t e2i;t2Since Performance and HRO are determined simul-taneously,theyarecorrelatedwiththeerrortermse1 and e2, which makes OLS inappropriate (Greene,2003; Wooldridge, 2009). The proper estimationmethodologyissimultaneousequations models,asitexplicitlymodelsthesimultaneitybetweenHROandperformance(Greene, 2003). Indoingso, themodelconsiderstheexogenousvariablestojointlydetermineeachendogenous variableandtocon-struct theset of instruments for theendogenousvariables (Kennedy, 2001; Wooldridge, 2009). Usingsuch simultaneous equations methodology isanimportantempiricaladvancementtotheregio-nal/global strategies literature, as prior studies havenotexplicitlytakenthissimultaneityintoaccount(e.g., Delios &Beamish, 2005; Elango, 2004; Li,2005; Rugman&Verbeke, 2004). [T]hefailuretostatistically correct for endogeneity canleadnotonly to biased coefficient estimates but, moreimportantly to faulty conclusions about theoreticalpropositions(Hamilton&Nickerson,2003:52).After the Hausman test revealed that fixed effectsarebetterthanrandom, wefollowedpriorresearchandtookadvantageof thepanel structureof ourdatabyde-meaningthevariables withthe within(fixed effects) transformation (e.g., Clougherty, 2006;Wooldridge, 2009). This procedure is identical toadding dummy variables for eachfirminthe re-gression, but de-meaning the data instead pre-serves degrees of freedom(e.g., Clougherty, 2006;Wooldridge, 2009). Thus firm heterogeneity that canarise fromtime-invariant variables (e.g., industry,country, region, geographic distance, language, colo-nial ties, common border, etc.) is accounted forthrough the firm fixed effects (Wooldridge, 2009). Astime-invariantvariableswouldbeperfectlycollinearwith the fixed effects, their inclusion is not necessary(Wooldridge, 2009). Welaggedtheexogenousvari-ables one year with respect to the dependentvariablestofacilitatethedirectionofcausality(e.g.,Elango & Pattnaik, 2007), and standardized theregressioncoefficients sotheycanbereadilycom-pared(e.g.,Ait-Sahalia &Brandt,2001).Wenextemployedtwo-stageleastsquares(2SLS)and three-stage least squares (3SLS) to test thesimultaneousequationsmodel.Boththe2SLSand3SLS estimators use instrumental variables. 2SLSestimates each equation separately, so it keepspossiblemis-specificationtooneequation, but italso ignores the information contained in thecorrelationbetweentheerror terms (Wooldridge,2009). 3SLS estimates all equations jointly, so it usesthefull informationinthemodel, butalsorunsaHome-regionorientation ElitsaRBanalievaandCharlesDhanaraj100Journal ofInternational BusinessStudieshigher mis-specification risk (Wooldridge, 2009).However, whenthe 2SLS and3SLS models yieldsimilarresults, theyincreasetherobustnessofthefindings(Kumar,2009).In simultaneous equations models, identificationof eachequationneedstobeachievedfor properestimation by ensuring that the number of exogen-ous variables excluded fromeachequationis atleast as great as thenumber of endogenous vari-ables in the system minus one(a necessary butnotsufficient condition) (Johnston, 1972). Thus eachequation needs to include at least one variable thatis not in the other equation for identificationpurposes. To identify Eq. (1), we used Leverage (totalliabilities tototal assets), as higher leverage mayimpede firmperformance as firms borrowmoredebt that theyhave torepaylater (Li, 2005). Toidentify Eq. (2), we usedCurrency Zone, as firmsbased in currency zones are more likely to beregionallyoriented; RTATrade, as firms basedinRTAsaremorelikelytotakeadvantageofregionalintegration; and Domestic Market Size, as firms basedinlarger domestic markets maybe more region-allyoriented, giventheir familiaritywithgreaterTable1 ControlvariablesMeasure Operationalization RationaleMarketingAdvantage Selling,general,administrativeexpenses/total sales Control forlocation-boundFSAs(Anand&Delios,2002)Multinationality Foreignsales/total sales Control for international expansion (Li,2005;Rugman&Verbeke,2008)IndustryDiversification1 Xsi2wheresiistheshareofsalesfrombusinesssegmentiControl forindustrydiversification(Tallman&Li,1996)RegionalMarketAttractiveness Restofhome-regionGDPgrowth Control formarketattractiveness(Goerzen&Beamish,2003)FirmAge ln(numberofyearssinceincorporation+1) Control forexperienceeffectsInstitutional DistanceAverageGlobaltoHomeCountryDistanceAverageResttoHomeCountryDistance2whereAverageGlobaltoHomeCountryDistance AverageGlobal BERIScore HomeCountryBERI ScoreAverageResttoHome CountryDistance AverageRestof Home Region BERIScore HomeCountryBERI ScoreControl forinstitutional distancebetweenhomecountry,restofhomeregion,andglobalsegmentFirmSize lntotal sales(thousandsofUSdollars) Control foreconomiesofscaleIndustryHRO AverageHROforfocalfirmscompetitorsineachindustry(sic2)andyear,excludingfocalfirmsHROControl forindustryisomorphismeffectsFirmEffects Fixedeffectswithin-transformationofthevariables Control forfirmfixedeffects(Clougherty,2006;Wooldridge,2009)YearEffects 01dummyvariablesforeachyear,1997baseyear Control forbusinesscycleeffects(Li,2005)Home-regionorientation ElitsaRBanalievaandCharlesDhanaraj101Journal ofInternational BusinessStudiesconsumer demand locally. Currency Zone is equal to1 for countries withno commoncurrency (i.e.,19972006:US,Japan,Denmark,Norway,Sweden,Switzerland, and the UK; 19971998: Germany,Finland, France, Ireland, and the Netherlands); andequal to 2 otherwise. RTA Trade is equal to (HITIi,tHETIi,t)/(HITIi,tHETIi,t), where HITIi,tstands forhomogeneous intra-regional trade intensityindexandHETI stands for homogeneous extra-regional trade intensity index (Iapadre, 2006).BothHETI andHITI arefunctions of theregionsshare of outsiders total trade (Iapadre, 2006;Plummer,Cheong,&Hamanaka,2010).RTA Traderises if theintensityof intra-regional tradegrowsfaster thanthat of extra-regional trade. We alsocapturedDomesticMarketSizewiththenatural logofGDP(inUSdollars).We checked that the equations are properlyidentifiedinthreeways.First,weensuredthattheidentifyingvariablesforEq.(2)arecorrelatedwithHRO but not with Performance, and that theidentifyingvariable for Eq. (1) is correlatedwithPerformancebutnotwithHRO. ThecorrelationsinTable 2 support this criterion, as Leverage issignificantly(po0.05) correlatedonlywithPerfor-mancebut not withHRO, andCurrencyZone, RTATrade, and Domestic Market Size are significantly(po0.05) correlatedonlywithHRObut not withPerformance.Second, weperformedtheSargantestof over-identifying restrictions (Greene, 2003; Sargan,1958; Wooldridge, 2009) to confirm that theidentifyingvariablesareproperlyincludedintheirrespectiveequationandexcludedfromtheotherequation. A statistically insignificant p-value oftheSargantest suggests that thesystemof equa-tionsisproperlyidentified:theSargantestp-valuewas 0.5790, confirmingthat theidentifyingvari-ables areindeedexogenous. Third, weperformedtherankconditiontest(anecessaryandsufficientconditionfor identification) toensurethemodelcouldbeproperlyestimated(Johnston,1972).Thesystemofequationspassedtherankconditiontestaswell.RESULTSThe 2SLS and 3SLS regression analyses yieldedsimilar results, so we present the 3SLS findingsthroughoutourpaper,astheyaremoreconsistentand asymptotically efficient than 2SLS (Kumar,2009). The results followin Table 3. We testedHypotheses13oncolumn1andHypothesis4oncolumn2. Table2DescriptivestatisticsandcorrelationsmatrixVariableMeanS.D.1234567891011121314151ROA0.050.091.002Home-regionorientation0.370.310.001.003Technologicaladvantage0.050.060.180.231.004Marketingadvantage0.230.150.110.260.551.005Multinationality0.430.240.040.060.220.071.006Regionalinstitutionaldiversity0.210.020.140.160.150.090.271.007Industryhome-regionorientation0.380.120.010.220.170.130.070.141.008Institutionaldistance17.265.150.070.010.110.070.400.160.041.009Firmage3.581.030.060.120.280.240.100.330.150.201.0010Firmsize13.282.040.170.060.170.320.080.080.140.110.371.0011Regionalmarketattractiveness4.431.590.040.210.130.110.150.360.230.120.230.031.0012Industrydiversification0.400.250.030.050.070.090.010.040.050.050.130.380.031.0013Leverage0.510.240.160.030.210.270.050.010.040.070.110.310.030.201.0014Domesticmarketsize28.971.100.010.350.070.190.430.070.080.360.060.030.060.120.081.0015Currencyzone1.110.320.000.150.050.170.370.100.020.290.020.130.060.050.090.451.0016RTAtrade0.710.210.000.050.020.040.240.240.030.350.040.030.060.050.000.290.12Note:Boldindicatessignificanceat5%.N3061.Home-regionorientation ElitsaRBanalievaandCharlesDhanaraj102Journal ofInternational BusinessStudiesHypothesis1predictedthatTechnological Advan-tage will haveanegativecoefficient for boththelinear and the squared terms. Column 1 shows that,while we find that the signs of TechnologicalAdvantage areas expected, thelinear termis notsignificant. However, the squaredtermis signifi-cant (po0.05), and thus provides partial support forHypothesis 1. Hypothesis 2 is fully supported,becausecolumn1showsthatRegional InstitutionalDiversityhadanegativeandsignificant(po0.001)effect onfirms HRO. Hypothesis 3 is also fullysupported, because column1 shows that perfor-mancesignificantly(po0.05) decreasedHRO. Thecompeting Hypotheses 4a and4bwere not sup-ported, because column 2 showed that HRO had nosignificant effect on firm performance. This findingsuggeststhatthecausalityrunsfromperformancetoHRO, suchthatwhentheinternalandexternalinducements to growth are properly accounted for,theybalance out anypossible performancegainsfromagreater HROpreference. It ispossiblethatprior researchfinds significant effects of HROonperformancebecauseithasnotcontrolledfortheeffects of its antecedents. When the errors arecorrelatedinasimultaneous equations model, astatistical relationship between M [HRO in our case]andY[performanceinourcase] couldbedrivenby an actual relationship between the two variablesor by any other factor that affects both M and Y yetis not explicitly included in the two regressionequations(Shaver,2005:337).ThecoefficientsofthecontrolvariablesonHROincolumn1 reveal some interesting findings aswell. Forinstance,largerfirmsize, largerdomesticmarket size, and faster RTAtrade decrease HROsignificantly. Conversely, industry diversification,regional market attractiveness, andcurrencyzoneincreaseHROsignificantly.Similarly,incolumn2,agreater industrydiversification, regional marketattractiveness,andleveragesignificantlyimprovedfirmperformance.We proceedbygraphingthe sample HROagainstthesampleTechnological Advantage (Figure3) andthe average HRO against the three categories(low, medium, or high) of Technological Advantage(Figure4). ForFigure4, wesplittheMNEsbyfirstfindingthe sample averageforTechnological Advan-tage(0.05),andthenfindingtheaverageTechnolo-gicalAdvantagefortheabove-sampleaveragegroup(0.12) andtheaverageTechnological Advantageforthebelow-sample averagegroup(0.02). Thus thelow-technology MNEs (1766 firm-year observa-tions) hadTechnological Advantage less than0.02and an average HRO of 0.40. The medium-technology Triad MNEs (976 firm-year observa-tions) hadTechnological Advantage between0.02and0.12andanaverageHROof 0.39. Thehigh-technology Triad MNEs (319 firm-year observa-tions)hadTechnologicalAdvantageabove0.12andanaverageHROof0.19. Theseresultsareconsis-tent withthe previouslydocumentedpyramidalstructureofMNEs,accordingtowhichmostfirmsare regional and very few expand globally.Theyarealsoinlinewiththefirmheterogeneityliteratureininternational economics, whereonlyTable3 Three-stageleastsquaresregressionresultsDependentvariable HRO ROATechnological advantage 0.021 0.010(1.001) (0.472)Technological advantagesq. 0.007* 0.007*(2.485) (2.280)Regional institutional diversity 0.145*** 0.001(6.078) (0.028)Performance 0.240*(1.999)Home-regionorientation 0.216(0.954)Marketingadvantage 0.021 0.016(0.988) (0.774)Multinationality 0.001 0.019(0.061) (0.946)Firmsize 0.085** 0.161***(2.845) (6.014)Firmage 0.081** 0.016(3.206) (0.628)Industrydiversification 0.043* 0.046*(2.082) (2.318)Regional marketattractiveness 0.066w0.091*(1.850) (2.447)Institutional distance 0.013 0.026(0.435) (0.911)IndustryHRO 0.023 0.024(1.090) (1.140)Domesticmarketsize 0.141***(3.944)Currencyzone 0.058**(2.668)RTAtrade 0.073**(2.598)Leverage 0.170***(8.036)Constant 0.212*** 0.244***(3.696) (4.909)Chi-sq. 155.68*** 339.86***wpo0.10;*po0.05;**po0.01;***po0.001.Note:t-statisticsinparentheses.N2436.Home-regionorientation ElitsaRBanalievaandCharlesDhanaraj103Journal ofInternational BusinessStudiesafewfirmsserveforeignmarkets, andmostservetheir home market (e.g., Bernard et al., 2006;Helpmanetal., 2004; Melitz, 2003). Ourfindingssuggest tworeasons for this pyramidal structure.First, theresultsshowthat most (89.58%) of theTriadMNEs arelow-to-medium-technologyfirmsthat lackthe necessarytechnologycapabilitytoventure globally, in line with Rugman and Verbeke(2004, 2008). Second, the results showthat theaverage HROdeclines at an increasing rate asTechnologicalAdvantageincreases.Forexample,theaverage HRO declines by 0.1 point between the low-andmedium-technologyfirms,butitdeclinesbyamuchlarger amount 0.20points betweenthemedium- and high-technology firms, illustrating theincreasingreturnsmechanism.RobustnessTestsWe performedadditional robustness tests toruleout possible alternative explanations for ourresults.8Becauseof spaceconsiderations, wepre-sentsomeoftheseadditionaltestsinTable4,withfull results available from the authors upon request.First, we retested the models with a market-basedperformance measure: Tobins Q(natural log ofmarketcapitalizationplusbookvalueofliabilitiesdivided by book value of assets; Cummins, Lewis, &Wei, 2006) and present the results in Model 1.Similarlytothemodel withROA, wefindpartialsupport for Hypothesis 1 and full support forHypothesis2.We didnotfindsupport for Hypoth-esis 3, suggesting that our argument of performancebeing indicative of internal perception of slackresources may be more consistent with accounting-based measures suchas ROAthanwithmarket-based measures such as Tobins Qthat includeinvestors forward expectations about the company.WealsodidnotfindsupportforHypotheses4aor4b, suggestingthat HROdoes not affect market-basedperformancesignificantly.Second, we replaced the BERI composite measurewith each of its three sub-components (Appendix A)and present the results in Models 24 in Table 4. Theresults wereconsistent withour previous analysis.We next replaced the BERI measure with thealternative Fraser index (DiRienzo et al., 2007;Gwartneyetal., 2002; Nachum&Song, 2011)andreport the results in Model 5. The results wereconsistent. We next usedeachof the Fraser sub-components(AppendixB). TheresultsforHypoth-eses 1 and 3 were consistent. Hypothesis 2 was fullysupported only with the Government and LegalFraser sub-components. Neither of the competingHypotheses4aor4bwassupported, exceptforthemodelwiththeGovernmentsub-index,whichwastheonlymodelwhereHROincreasedperformancesignificantly (po0.05). Among other factors, thegovernment sub-component capturesmarginal taxrates and government expenditure, which areessential forMNEsandlikelydriversfor thesigni-ficanteffect.Third, wetestedthemodelswithanalternativeHRO measure: rest of home-regional sales/totalsalesglobal sales/total sales adapted frompriorresearch (Asmussen, 2009; Elango, 2004; Rugman &Verbeke, 2008). This alternative measure is 85%correlated with our main measure of regional sales/foreign sales. As before, we found partial support forHypothesis 1 andfull support for Hypothesis 2.PerformancedecreasedHRO, butnotsignificantly00.20.40.60.81Home Region Orientation0 0.2 0.4 0.6 0.8Technological AdvantageFigure 3 Sample home-region orientation vs technologicaladvantage.0.190.390.400.000.100.200.300.400.50Low Medium HighTechnological AdvantageAverage Home Region OrientationFigure 4 Average home regionorientationvs technologicaladvantage.Note:HROisrestofhomeregionsales/foreignsales.Home-regionorientation ElitsaRBanalievaandCharlesDhanaraj104Journal ofInternational BusinessStudiesso, thus findingnosupport for Hypothesis 3. Asbefore, wedidnot findsupport for either of thecompetingHypotheses4aor4b.DISCUSSIONOurresultspresentacompellingtheoreticalexpla-nationfor the regionalizationphenomenonthathasbeengaininggrowingscholarlyattention.Ourempiricallysupported,theoreticalpropositionthatnonlinear behavior of firms technological advan-tage dictates their geographic scope and theirdistanceininternationalexpansionopensamajoravenueforfurtherresearch. Specifically, wefoundthat HROdecreases rapidlyas aresult of increas-ing technological advantage, suggesting that MNEsgeographic scope increases globally, and morethanproportionately, as technological advantageincreases(i.e., theincreasingreturnsmechanism).ThispresentsaplausibleexplanationofRugmans(2005) observationof the pyramidal structure offirms geographic scope whereby most firms areregional, somearebi-regional, andonlyafewareglobal. This finding is also consistent with the firmheterogeneity literature in international economics,whereonlyafewfirmsserveforeignmarketsandmost serve their domestic market (e.g., Bernardetal.,2006;Helpmanetal.,2004;Melitz,2003).ItalsoextendsCerratos(2009)findingthatinnova-tionintheItalianmanufacturingindustrypropor-tionatelyenablesafirmtoovercometheliabilitiesof global foreignness. Our integration of the increa-singreturnsconceptwithinternalizationtheoryfitswell withthebroadempirical observations withinthegeographicscopestreaminexplainingboththeinternationalizationintensityandthenuancedgra-dationof firms locational strategies. Eventhoughtechnology has received major attentionfromIBscholars, verylittleattentionhasbeengiventothedynamics of technology indetermining firm-levelphenomena suchas HRO. Prior studies that haveusedtheincreasingreturns notionhavetendedtofocus onindustry- andcountry-level analyses. Forinstance, NachumandZaheer (2005) incorporatedthe increasing returns notion in their analysis of thetelecommunicationsindustry.Krugman(2010),too,invoked the increasing returns notion, and inte-gratedit withcountries comparativeadvantagetoexplainhowfocusedlocationswithincountriesareTable4 Three-stageleastsquaresrobustnesstestsIndependentvariable Model 1 Model 2 Model 3 Model4 Model 5(a)HROasthedependentvariablePerformance 1.019 0.238* 0.283* 0.235* 0.234w(1.499) (1.987) (2.297) (1.965) (1.900)Technological advantage 0.073 0.020 0.019 0.020 0.022(1.577) (0.963) (0.923) (0.982) (1.076)Technological advantagesq. 0.011* 0.008* 0.008** 0.007* 0.007*(2.041) (2.540) (2.640) (2.418) (2.500)Regionalinstitutional Diversity(BERI) 0.105**(2.684)Regionalinstitutional diversity(BERI-ORI) 0.108***(4.836)Regionalinstitutional diversity(BERI-PRI) 0.010(0.395)Regionalinstitutional diversity(BERI-RFactor) 0.158***(6.301)Regionalinstitutional diversity(Fraser) 0.051w(1.855)(b)PerformanceasthedependentvariableDependentvariable TobinsQ ROA ROA ROA ROAIndependentvariable:Home-regionorientation 0.368 0.233 0.231 0.162 0.221(1.064) (1.261) (1.233) (0.635) (1.100)wpo0.10;*po0.05;**po0.01;***po0.001.Note: All control variables were included in models but were omitted here for space consideration. t-statistics in parentheses. BERI-ORI,-PRI, and -RFactorstandfortheOperational,Political,andRemittancessub-componentsoftheBERIindex.N2436.Home-regionorientation ElitsaRBanalievaandCharlesDhanaraj105Journal ofInternational BusinessStudiesdictating countries international trade patterns.Littlehas remainedunderstoodas towhether andhow increasing returns can affect firm-level phenom-enasuchasgeographicscope.Ourpapershedsnewlightintothisarea.Furthermore, our results onthe overwhelmingeffect of regional institutional diversitypresent awindowonwhyfirmswouldgoglobalratherthanstay regional, even considering the liabilities ofworking across the regions (Rugman&Verbeke,2008). Internationalization patterns of firms inmarkets suchas Japan, China, andIndiaarelessregional, andtheinstitutional diversitymaypro-videanexplanation.Unlike priorresearch thathasanalyzedinstitutional effectsintermsof distance,we useda variance measure ona wide range ofinstitutional components and found consistent andsignificantnegative effects ofregionalinstitutionaldiversityonfirmsHRO.Unfortunately,ourmodeldoesnotgofarenoughtoexplainthepresenceofbi-regional firms. Havingspecificregional bound-aries, theTriadinour model, wewereunabletoexplore the possibility of firms selecting specificcountries withinthe home regiontofocus theiractivities. For example, firms in the US and Canadaseemto focus onthe NAFTAregionmore thanoutsideNAFTA. These are interestingpossibilitiesforfutureresearch. Nevertheless, thefundamentalpremise we propose here stands: firms seek tominimize the institutional diversity of the environ-mentsthattheyworkin.We also analyzed the dynamics of HRO evolutionover 19972006. Ourt-test withunequal varianceandWelchs adjustment showedthat theaverageHROhasgrownsignificantly(po0.05)from0.325in1997 to 0.414 in2006. We also graphedthelongitudinal trends between 1997 and 2006 foreachoftheTriadbranchesandpresenttheresultsin Figure 5. European MNEs were the most regionalin the sample. American firms were the leastregional, withanaverageHROdecreasingslightlyover time. Japanese firms became increasinglyregional overthesampleperiod, andreachedandslightly surpassed the Western European firmsHROin2006.Thisevidenceofagrowingregionaltrend among Japanese MNEs is consistent withotherfindings(Collinson&Rugman,2008;Delios&Beamish, 2005), perhaps owingtothegrowingtrade relationship between Japan and China (METI,2004).Additionally, ourpost-hocanalysisonthedyna-micsofHROovertimeconfirmedtheimportanceof regional integration. For instance, EuropeanMNEswerethemostregional,andAmericanfirmswere the least regional. The impact of regionaltrade agreements indiffusingpatterns across theregion and thus reducing institutional diversity hasbeenwell analyzedintheliterature. However, westill find the persistence of firms HRO overtime, withour t-test revealingthat HROactuallyincreasedsignificantly from1997to2006. If wefollow the internationalization models derivedfromthe Uppsala school (Johanson & Vahlne,1977), weshouldlogicallyseeadiminishingHROover time. Eventually, as firms mature, they shouldincreasetheirgeographicscopetoglobal markets.However, itisperplexingtoseethepersistenceofregionalization, even after multiple decades of firmoperations. Suchdynamicanalysisposesaninter-esting question: What drives the persistence ofregional boundaries in international expansion?Arregleet al. (2009) provideauseful first stepinthatdirection.ThesimultaneouseffectofperformanceonHROdepicts averydifferent picturefromprior studiesthat have focused exclusively on analyzing theeffectofHROonperformance.Thesepriorstudieshave treated regionalization as an independentvariable, andinferredpositiveandnegativeeffectson performance. We extended this prior research byarguing for a simultaneous relationship betweenHRO and performance. We showed that whileperformancedrivesHRO, HROdoesnotinfluenceperformance significantly, after accounting forHROsantecedentsandextensivecontrolvariables.Wehadthedifficult taskof provinganull hypo-thesis, whichweovercamebyusingasetofcom-peting hypotheses. In line with Hennart (2007,2011), wefoundthatgeographicscopeisinitself00.10.20.30.40.50.61997199819992000200120022003200420052006YearHome Region OrientationUSA Western Europe JapanFigure 5 Longitudinal trends in the home-region orientation oftheTriad.Home-regionorientation ElitsaRBanalievaandCharlesDhanaraj106Journal ofInternational BusinessStudiesconstrained or driven by other variables, and henceis not a strategic optionby whichperformance canbeenhancedor diminished. Wealsotookaverycareful approach to account properly for HROsantecedents inour model, andperhaps provideabetter predictionof theperformanceimpact thanothermodels,whichdonotcontrolforthem.Our study has several limitations. We focused ouranalysisonfirmsHROintheirsales-basedforeignmarket penetrationstrategies (e.g., Elango, 2004;Li, 2005; Rugman&Verbeke, 2004, 2008). How-ever, analyzing firms HRO in other types of foreignstrategies,suchaspurchasingorsourcing,orusingsubsidiary-level data, could further enhance thegeneralizabilityofourfindings.Unfortunately,ourdata were limitedbythe publiclyavailable data-bases, and thus we do not have specific informationonthe internationalizationmotives of the firm.Ourcontrol fordomesticmarketsizecanmitigatethisprobleminsomeway,asfirmsbasedinlargerdomesticmarketsaremorelikelytointernationa-lizeinsearchofcheaperforeignproduction,whilefirms basedinsmaller domestic markets maybemore likely tointernationalize insearchof newmarket opportunities (Dunning&Lundan, 2008;Moon, 1994). Amajorconstraintwehadwasourtechnologicaladvantagemeasure.EventhoughweusedR&Dintensityas the most commonlyusedmeasure for technology (Kirca et al., 2011), there isanincreasingrealizationthat weneedtoexpandbeyondittocaptureafirmstechnological advan-tage. However, we have not yet, as a field, generateda comparable measure of technology across differentgeographies, as internationally compatible patentmeasures are difficult to compile (Thoma et al.,2010). Giventhecentralityof theinnovationandtechnologyfocus, thisremainsanunresolvedissuefor cross-countryIBresearchlikeours.CONCLUSIONWeusedinternalizationtheorytoinvestigatethegeographic scope of a firm, paying particularattention to the decision to concentrate theiractivities within or outside their home region.Wehavedevelopedatheory-drivenexplanationofgeographicscope, empiricallyvalidatedwithTriad-basedMNE data. We showed howtechnologicaladvantage and regional institutional diversitydetermine HRO, and suggested a simultaneousrelationshipbetweenHROandperformance. Thuswehopeour studyserves as auseful platformtoadvancefuturetheorydevelopmentongeographicscope.A decade of research on regionalization withconverging empirical data demands that the IB fieldtakeafreshlookat howweconstruct geographicscope and theorize on its impact on performance. Itdemandsforamoveawayfromsimplenotionsofdomestic vs international expansion, to take a moreconsciouslookat thelocational aspects. Wehaveattempted to steer the conversation away fromdifferent ontological debates regarding definingregionsormeasuringregionalization, andtowardshowfirmsexpandtheirgeographicscope(Flores&Aguilera, 2007: 16). A longitudinal viewof theinternational expansionprocesses, understandinghowtechnologyenablesthepenetrationofdistantmarkets,andhowinstitutionaldiversityenablesordiffuses home-regional concentration, wouldadduseful insights for both IB theory and practice. Suchanapproachcanintegrateotherformsofinterna-tional activity, such as alliances, which can providea complementary perspective on howfirms usediverse entry modes toexploit their FSAs acrossdiverse geographies.Expandingthe regionalizationresearch to frame international firms as a geo-graphicallydistributednetwork, andtostudythedynamic changes in the network over time,dictatedbytechnologyandenvironment,willalsobe useful ways to extend future research. Suchnetwork-based approaches can capture the elementofrandomnessoridiosyncrasy, whichseemstobeprevalentinmanyearlyinternationalizationdeci-sions.Suchstudiesonthedynamicsofgeographicscope will also uncover some of the viscouselements withininternational strategy that con-strain firms internationalization paths, and lead toapersistentfocusonthehomeregion. Ourmodelfocusingontechnologyandenvironmentprovidesapointofdepartureforsuchresearch.ACKNOWLEDGEMENTSWearegrateful fortheinvaluablefeedbackfromtheeditor, Professor Ulf Andersson, and from threeanonymous reviewers, which has sharpened ourcontributionhere.Wethankourcolleagueswhohavehelped us significantly: Christian Asmussen, PaulBeamish,AllanBird,CyrilBouquet,AnthonyGoerzen,ShyamKumar, Harry Lane, Dan Li, Marjorie Lyles,SimonParker,Ravi Ramamurti,SubramanianRangan,AlanRugman, K. Sivakumar, AlainVerbeke, andtheparticipants at the research workshops at BEPPdepartmentatIndianaUniversity,HaskayneSchool ofBusiness at theUniversityof Calgary, IB&SgroupatNortheasternUniversity, andstrategydepartment atBoston College. The first author acknowledges theHome-regionorientation ElitsaRBanalievaandCharlesDhanaraj107Journal ofInternational BusinessStudiessupport from the Northeastern Universitys GaryGregg Research Fellowship and the second authoracknowledges thesupport fromtheIndianaUniver-sitysSchmenner FacultyFellowshipfor enablingthisresearch.NOTES1Despite the wide use of the termgeographicscope,ithasnotbeenwell definedintheliterature.Geographicscopecanrefertotheextent,dispersion,and diversity of the foreign markets that a firmexpandsinto.Afirmsgeographicscopeisacumula-tiveeffect of its locational choices (Hennart, 2011).Somestudiesuseitsynonymouslywithdegreeofinter-nationalization;othersuseentropymeasurestoincludethe dispersion and diversity dimensions (Goerzen &Beamish,2003;Hittetal.,1997;Lu&Beamish,2004;Tallman & Li, 1996). Until Rugman and associates work,mostof theworkhadnotdifferentiatedbetweennearandfargeographicactivities,astheliteraturesprimaryfocushad beenondomestic vsforeignmarkets.2Dunning (1998) pointed out that locationremained a neglected issue in IB research, and adecadelater,whenDunningsarticlereceived the JIBSDecadeAward,Cantwell(2009)gaveareminderthattheissuestillpersisted.3Wearegrateful toouranonymousreviewers,whogentlynudgedustostayneutral andconsistentwiththe established terminology in the regionalizationliterature.4IfTisthetotal salesofanMNE,Disthedomesticsales, F is the foreign sales, and R is the sales within thehome region, andGis the sales outside the homeregion, then our measures r1 and r2 for regionalizationcan be represented as: r1(RD)/F and r2(RD)/TG/T. 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