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Management Accounting Research
j o u r n a l h o m e p a g e :w w w . e l s e v i e r . c o m / l o c a t e / m a r
Formal controls and alliance performance: The effects of alliance motivation and informal controls
Kristof Stouthuysen
a,∗, Hendrik Slabbinck
b, Filip Roodhooft
caVlerickBusinessSchool&KULeuven,Vlamingenstraat83,BE-3000Leuven,Belgium
bGhentUniversity&HOGent,Tweekerkenstraat2,9000Ghent,Belgium
cKULeuven&VlerickBusinessSchool,Naamsestraat69,3000Leuven,Belgium
a r t i c l e i n f o
Articlehistory:
Received13November2015 Receivedinrevisedform9March2017 Accepted14March2017
Availableonlinexxx
Keywords:
Exploitation/explorationalliances Formalcontrols
Informalcontrols Allianceperformance
a b s t r a c t
Inthisresearch,westudytheuseofformalcontroltypes(outcome,behavior)acrossdifferentalliance motivations(exploitation,exploration,ambidextrous)andtheeffectsonallianceperformance.Thisstudy furtherexamineswhetherthisrelationshipismoderatedbytheuseofinformalcontrols.Surveydatafrom 236organizationspursuingstrategicalliancesindicatethatwhenfirmsoptforoneprimarystrategic alliancemotivation,firms’emphasisoneitheroutcomecontrols(inexploitationalliances)orbehavior controls(inexplorationalliances)increasesallianceperformance.Resultsalsosupportacomplementary relationshipbetweenoutcomeandbehaviorcontrolsinexplainingallianceperformanceinambidextrous alliances.Furthermore,ourfindingsrevealthatwhileinformalcontrolsenhancetheeffectivenessof behaviorcontrolsinexplorationalliances,thebenefitsofinformalcontrolsdisappearinthecontextof outcomecontrolsandexploitationalliances.Inambidextrousalliances,firmsneedtocarefullyproportion theinformalcontrollevelbecausebeyondamoderatelevel,informalcontrolsseemtonegativelyaffecta controlconfigurationusingoutcomeandbehaviorcontrols.Ouranalysisprovidesamorenuancedview onhoworganizationsmaysuccessfullycontrolallianceswithdifferentmotivations.
©2017ElsevierLtd.Allrightsreserved.
1. Introduction
Astechnologyadvancesandcompetitionintensifies,firmsform alliances to share and exchange resources. Such alliances per- mitfirmstoexploittheirexistingknowledgeand/orexplorenew opportunities (e.g., Koza and Lewin, 1998; Kristal et al., 2010;
LevinthalandMarch,1993;March,1991).Whilerecentresearch hasexaminedwhetherfirmsarebetteroffpursuingasinglestrat- egy(exploitationorexploration)orsimultaneouslypursuingtwo strategies (exploitation and exploration), commonly known as ambidextrousalliances(Lavieetal.,2011),muchmoreremainstobe understoodabouthowfirmseffectivelycontrolallianceswithdif- ferentmotivations.Thisstudyexaminestheuseofcontrolsacross differentalliancemotivationsandtheeffects onallianceperfor- mance.
Inparticular,littleconsensusexistsontheeffectivenessoffor- malcontrolstoshapealliances.Forexample,innovationliterature
∗Correspondingauthor.
E-mailaddresses:[email protected](K.Stouthuysen), [email protected](H.Slabbinck),fi[email protected] (F.Roodhooft).
featuresapredominantlypessimisticattitudetowardformalcon- trols.Extensiveresearchemphasizestheadverseeffectsofformal controlsoncreativityinexplorationalliancesandhighlightsthe importance of intrinsic motivation and freedom (e.g., Amabile, 1998;Carson,2007;LeeandCavusgil,2006).Aparallelliterature inmanagement hassimultaneouslyarguedthat formalcontrols have a role in new technologyalliances, for example, by pre- ventingpotentialopportunism,facilitatingjointproblemsolving, andimplementingradicalinnovative(i.e.,exploration)ideas(e.g., Argyresetal.,2007;MayerandArgyres,2004).Athirdstreamof literaturefindsthatformalcontrolsmaybeusefultodevelopboth explorationandexploitationobjectives(e.g.,Jansenetal.,2006).
Thus,althoughformalcontrolsareubiquitousinalliances,research ontheiractualeffectshasshownaninconsistentpattern.
We aimto address this gapin two ways. First, we deviate frompreviousstudiesanddifferentiatetypesofformalcontrols.
Thatis,whileallianceresearchhastypicallyapproachedformal controls in terms of the degree towhich firms rely on hierar- chical elements (e.g.,detailed contracts, theuse of equity as a
“hostage”,andjointventurestructures),wefocusontheconcrete formalmechanismsafirmcanusetocontrolitspartner.Wealso describein moredetail howtherequiredbehavior willbecome motivated.Therefore,followingorganizationalcontroltheory(e.g., http://dx.doi.org/10.1016/j.mar.2017.03.002
1044-5005/©2017ElsevierLtd.Allrightsreserved.
Cardinaletal.,2004;DasandTeng,1998;Eisenhardt,1985;Kirsch, 1996;Kirsch,2004;Ouchi,1979)andpreviousempiricalaccount- ingresearch (e.g.,Dekker, 2004; Dekker and Van den Abbeele, 2010;EmsleyandKidon,2007;Langfield-Smith,2008;Mahama, 2006),wedistinguishbetweenoutcomeandbehaviorcontrols.His- torically,organizationalcontrolresearchhasgenerallyadvocated oneor theothertype of formalcontrol (e.g.,Eisenhardt, 1985;
GovindarajanandFisher,1990;Ouchi,1979),butmorerecentwork hassuggestedthecomplementaryuseofthedifferenttypes(e.g., Cardinaletal.,2004;ChoudhuryandSabherwal,2003;Dekkerand Vanden Abbeele, 2010;Langfield-Smith, 2008).We investigate boththeindividualandinteractiveeffectsofoutcomeandbehavior controlsonallianceperformanceacrossdifferentalliancemotiva- tions.Ourrationale isthat(mis)alignment betweenthealliance motivationand themechanismsof formalcontrol is associated withsubsequentincreased(decreased)allianceperformance.We adoptamultifacetedapproachtoallianceperformance(i.e.,finan- cial,operational,satisfaction)thatdescribesaglobalperceptionof itbasedononefirm’sexperiences(i.e.,thefirmexercisingcontrol) (see,also,Krishnanetal.,2006).
Second,wenotethepotentiallycriticalrelationshipbetween formalandinformalcontrols.Somestudiessuggestthatinformal controlsmayhelpshapeformalcontrolperformanceeffects(e.g., Cardinal,2001;DekkerandVandenAbbeele,2010;Fryxelletal., 2002;GulatiandNickerson,2008;Heideetal.,2007;Poppoand Zenger,2002).Informalcontrolsarebasedonsocialorpeoplestrate- gies(DasandTeng,2001;Eisenhardt,1985).Unlikeformalcontrol situations, explicitincentives are not needed to align partners’
goals.Firmsbecomemorecommittedtothealliancethroughsocial- izationandconsensus-making.Informal controlsmaypositively moderatetherelationshipbetweenformalcontrolsandalliance outcomesbecausetheymaybuffertheadaptivelimitsofformal controls.Onesuchlimitisthatformalcontrolsmayhavearestricted capacitytocontrolalliancepartneractivitiesbecauseforeseeing allpossiblecontingenciesis difficult(Poppoand Zenger, 2002).
Anotherpotentiallimitisthatformalcontrolsmayoffendapart- ner’ssenseofautonomy(Christetal.,2008;DeciandRyan,1987;
Heideetal.,2007;Stouthuysenetal.,2012).However,informal controlsalsocarrypotentialcostsanddisadvantages,andcomple- mentaryeffectsofformalandinformalcontrolscannotbeassumed (e.g.,DasandTeng,1998;HoetkerandMellewigt,2009).Sofar,little empiricalevidenceindicatesexactlyhowinformalcontrolsmod- eratetheeffectivenessofformalcontrolsmatchedwithdifferent alliancemotivations.
Ourfindingsfrommoderatedhierarchicalregressionanalyses onsurveydatafrom236organizationspursuingstrategicalliances show that when the alliance specializes in either exploitation or exploration, firms’ useof outcome controls (in exploitation alliances)orbehaviorcontrols(inexplorationalliances)increases allianceperformance. However, in ambidextrousalliances, out- comeand behaviorcontrolsareshown tohavecomplementary effectsonperformance.Further,ourresultsrevealnuancesinthe effectivenessofinformalcontrolsdependentonthealliancemoti- vation and the formal controlswith which they are paired. In particular,while informal controlsincrease theeffectiveness of behaviorcontrolsinexplorationalliances,thebenefitsofinformal controlsdisappearwhenalliancesarecharacterizedbyoutcome controlsandexploitation.Inambidextrousalliances,ourfindings suggestthatfirmsshouldcarefullyconsiderthelevelofinformal controlstogettheintendedeffectonallianceperformancewhena firmalreadyreliesonoutcomeandbehaviorcontrols.
Overall, our findings elucidate how organizations may suc- cessfully pursuealliancesthrough theeffective useofcontrols.
FollowingAndersonandDekker (2014)and Vélezet al.(2008), wearguethatamorenuancedapproachencompassingthediffer- enttypesofformalcontrolandalliancemotivationsmayprovidea
morecompleteassessmentoftheeffectivenessofformalcontrols andtheirinterrelationshipwithinformalcontrols.
2. Literaturereviewandhypotheses 2.1. Strategicalliancemotivations
March(1991)distinguishesbetweenexplorationandexploita- tionasmotivesfororganizationaladaptation.Exploitationrefersto theintensificationofexistingcapabilitiesandimprovementsineffi- ciencies.Explorationreferstoexperimentingwithorestablishing newassetsandcapabilities.
BuildingonMarch(1991),KozaandLewin(1998)advancea coevolutiontheorythathighlightstwobasicmotivationsforenter- ingstrategicalliancesandexplainsthreetypesofalliances.Thefirst typelinksfirmswithstrongexploitationmotivations,butlittleto noexplorationintent.Theoverridingobjectiveofanexploitation allianceistosecurenewincrementalrevenuesbycombiningspe- cificassetsuniquetoeachpartner(KozaandLewin,2000).Value isadded,forexample,byleveragingeconomiesofscaleortechnol- ogyaccesstocutcostsanddeliverenhanced,well-managedservice levels(LavieandRosenkopf,2006).
In the second alliance type, firms share strong exploration motivations,withlimited or noexploitation intent.Firmstypi- callyengageinexplorationalliancestooffernewdesigns,create new markets, and develop new distribution channels (Kristal etal.,2010).LavieandRosenkopf(2006)suggestthatexploration alliancesenhanceanorganization’sadaptationtoenvironmental changesbyallowingittoattainknowledgeoutsideitsdomain.In explorationalliances,partneringfirmssharerisksandgainsasthey collaborateontransformingkeybusinessprocessesintocompeti- tivetools(Youngdahletal.,2008).
Thethirdalliancetype,ambidextrousalliances,linksfirmswith strategicmotivationsthatincludestrongexplorationandexploita- tionintents.Thefirmsseektosimultaneouslycapturevaluefrom leveragingexistingcapabilities,assets,andsoforthandcreatenew valuethroughjointlearningactivities(e.g.,seeLavieetal.,2011;
Yangetal.,2014).Weultimatelyregardexplorationandexploita- tionastwodistinctdimensionsofalliancemotivation,ratherthan twoendsofaunidimensionalscale.1
2.2. Formalcontrolsandallianceperformance
We rely on organizational control research and empiri- cal accounting research to differentiate two types of formal control—outcome and behavior controls (e.g., Cardinal, 2001;
Cardinaletal.,2004;Choudhuryand Sabherwal,2003;Dasand Teng,2001;Dekker, 2004;Dekker andVan den Abbeele,2010;
Eisenhardt, 1985; Emsley and Kidon,2007; Kirsch etal., 2002;
Langfield-Smith,2008;Mahama,2006;Ouchi,1979).Thesecon- trols are often equated with the conceptions of market and hierarchytypesofformalgovernance(e.g.,Dekker,2004;Ouchi, 1979).Afirmthatreliesonoutcomecontrolsdefinesoutcomestobe realizedbutthenallowsalliancepartnerstodecidehowtoachieve them,suchthatits“Performanceevaluationthenfocusesuponthe
1Inunidimensionalmodels,alliancemotivationhasbeenconceptualizedasacon- tinuumboundedbythediametricpolesofexploitationandexploration.Incontrast, thebidimensionalviewpositsthatthereispotentialvalueinviewingexploitation andexplorationasseparatebutrelatedconstructsinwhichthelackofexploita- tiondoesnotnecessarilysignifyexploration.Bidimensionalmodelsofalliance motivationarefoundedonexplorationandexploitationmotivationscontaining fundamentallydifferentlogicsthatrequireverydifferentstrategiesandstructures (TushmanandO’Reilly,1996)aswellasresearchonconditionsofambidexterity (e.g.,HeandWong,2004;Jansenetal.,2006;Kristaletal.,2010;Parketal.,2002;
Rothaermel,2001;RothaermelandDeeds,2004).
extenttowhichtargetsweremetandnotontheprocessesusedto achievethetargets”(Kirschetal.,2002,p.486).Outcomecontrols featuremechanismstospecifyoutcometargets(e.g.,salesvolume, functionalspecifications,productsdeliverytimes,cost-reduction targets),as wellastoolstomonitora partner’sperformance in relationtothespecifiedoutputtargets(e.g.,producttesting by thecontrollingfirm)andrewardgoalattainment(Dekker,2004;
ChoudhuryandSabherwal, 2003).In contrast,afirms thatuses behaviorcontrolsseekstoinfluencetheactualproductionprocess andmeanstoachievetherelationshipsgoals.Thatistosay,with behaviorcontrols,orcontroloveractivitiesthattransforminputs intooutputs,firmsexplicitlyevaluateormodifytheprocesses,pro- cedures,andmethodologiestofollowandmonitortheirpartner’s compliance(Cardinaletal.,2004;Dekker,2004;MerchantandVan derStede,2007).In thecontextofstrategic alliances,suchcon- trolsmaybeenactedthroughnotonly(ex-ante)reviewswhere thecontrollingfirmcan(dis)approveorco-modifytheprocedures andmethodologiesapartnersuggeststofollow(MerchantandVan derStede,2007),butalsomonitoringofapartner’sbehavior(e.g., throughdirectobservation,regularprocessreports,qualitycontrol, lawsuitprovisions)andprovisionoffeedbackontheactivitiesthat wereexpectedtoproducethefocaloutcomes(Cardinaletal.,2004;
Dekker,2004).
While both types of controls include mechanisms for moti- vatingpartnerstowardattainingallianceobjectives,theyoperate differentially.Giventhesedifferencesinmodusoperandi,organi- zationalcontrolresearchhasgenerallyadvocatedoneortheother typeofformalcontrol(e.g.,Eisenhardt,1985;Govindarajanand Fisher,1990;Ouchi,1979).Contrarytoclassiccontroltheory,how- ever,afewstudieshavefoundthatfirmsoftenusebehaviorand outcomecontrolsincombinationtocontroltheiralliances(e.g., Cardinal et al.,2004; Choudhury and Sabherwal, 2003; Dekker andVandenAbbeele,2010;Langfield-Smith,2008).Thereislittle research,however,onhowexactlyformalcontroltypesinteractin explainingallianceperformance.Thecurrentstudydescribesthe specificalliancemotivationsinfluencinga firm’suseof controls andhowdifferentchoicesaffectallianceperformance.Thebene- fitsofindividualorcomplementaryuseofformalcontrolswillthus dependonthealliancemotivation.Assuch,wearguethatfirms’
useofformalcontroltypesiscontingentonthealliancemotiva- tion,therebyenhancing(reducing)allianceperformanceincaseof (mis)alignment.
2.3. Formalcontrolsforexploitationalliances
Inexploitationalliances,firms’useofoutcomecontrolsben- efitsallianceperformancefor severalreasons.First,exploitation alliancescomparedtoexplorationalliancesfeaturelessoutcome uncertainty becausetheyrefineand extendexisting competen- cies,technologies,andparadigms,withreturnsthat“arepositive, proximate,andpredictable”(March,1991,p.85).Consequently, exploitationalliancesmayencouragetheuseofoutcomecontrols sincedesiredoutcomescanbeclearlyarticulatedandaccurately measured(Langfield-Smith,2008).Moreover,uncertaintydeclines whentheoutcomesare distinct,which helpspartnersfocus on goalsand ultimately enhances thealliance performance (Joshi, 2009).
In contrast, firms’ reliance on behavior controls may be less effective thanfirms’ relianceonoutcome controlsbecause controllingfirmsmust thoroughlyunderstandtheactions–ends relationshipsofthemonitoredprocesses(Ouchi,1979;Widener, 2007),whichmayentailsubstantialcosts(Eisenhardt,1985).Out- comecontrolsinexploitationalliancesarethena moreefficient formofcontrolbecausetheydonotrequiresuchanunderstanding, whichsparestimeandotherresources(GovindarajanandFisher, 1990).
Furthermore,becauseexploitation alliancesallowthedevel- opment of clear and quantifiable outcome targets, focusing on outcome controls not only provides legitimacy for the control mechanism,butalsopermitsthepartnerlatitudewithrespectto theirbehavior(Heide etal.,2007).Thatis, whileoutcome con- trolsincentivizeandholdthealliancepartneraccountablefortheir performance,thepartnercanchoosetheirownmethods.Incon- trast,behaviorcontrolsareamoredirectformofcontrolbecause theyprovidebothdirectionandguidancetothepartnerthrough- outtheentireprocess(Kreutzeretal.,2014).Aneedfordirection andguidanceariseswhen,inthepursuitofvaluecreation,firms engageinexplorationalliancesinvolvinginterdependenttasksand mutualadaptation(Dekker,2004;KozaandLewin,1998).Behavior controlsinexploitationalliancesarethenlessefficientthanout- comecontrols, astheyarecostlyandproducenovalueforlack ofaneedforcoordinationandadaptationinexploitationalliances and,hence,cannotcontributetoperformance.Inlinewiththese arguments,wepropose
H1. Inexploitationalliances,firms’relianceonoutcomecontrols willcontributemorepositivelytoallianceperformancethanfirms’
relianceonbehaviorcontrols.
2.4. Formalcontrolsforexplorationalliances
Because exploration alliances are motivated by learning unknowntechnologies orattaining newgeographic marketsor productdomains,outcomecontrolsmaybelessviablethanbehav- iorcontrols.Thestrategicambiguitythatcharacterizesexploration allianceshinderssettingreliableandvalidoutcometargets,and alliancememberswhoperceivealackofcontrolovertheirsitua- tionsmayfeelconfusedandexperienceanegativeworkattitude (Joshi,2009).In addition, themarket-based natureof outcome controlsandtheresultinglackofcleardirectionandfeedbackfor improvement(Kreutzeretal.,2014)maycausealliancepartnersto becomeoverlyfocusedonactivitieswithimmediatepayoffstothe detrimentoflong-termobjectives(AndersonandOliver,1987).
Given that the outcome targets of exploration alliancesare generallyambiguous,monitoringprogressandperformanceout- comes is complicated (Koza and Lewin, 2000). Compared with outcomecontrols,behaviorcontrolsmayprovideamoreflexible meansofassessmentbecausetheyfocusonanalliancepartner’s actionsratherthanperformanceoutcomes(Kirsch,1996).More- over, because exploration alliances generally mandate ongoing involvementbybothpartners(RothaermelandDeeds,2004)and coordinationacrossorganizationalboundaries,behaviorcontrols maybeusefulbecausetheycanfosterdialogandenabletimely, correctiveinterventionsintomonitoredprocesses(Dekker,2004).
Herebybehaviorcontrolsnotonlyrefertotheprocessbywhich firmscanarticulateormodifytheproceduresandmethodologies theiralliancepartnerneedstofollow,butalsotheevaluationofthe partner’sactualbehavior(Kirsch,1996).Thelatterrequiresvari- ousinformation-gatheringmechanisms,suchasdirectobservation (e.g.,visitingvendor premises)orweeklyprogress reports,that strengthencoordination. Insodoing, theseinteractiveprocesses enable alliance partners to signal organizational priorities and evengeneratenewexplorationstrategies(AhrensandChapman, 2004; Bisbe and Otley, 2004; Simons, 1995). Not surprisingly then, given their“hands-off” (i.e., market-based) approach, we expect firms’ relianceon outcome controls tobe less effective compared to behavior controls in an exploration alliance con- text.Thisargumentalignswiththeideathathierarchicaltypes ofcontrol,suchasbehaviorcontrols,aremoreeffectiveforman- aging information-processing requirements than market-based type of controls(Galbraith, 1977; Thompson,1967).Narayanan et al. (2011), for example, provide empirical evidence that in
interfirm relationships, when task complexity (leading to task uncertainty) is high, emphasizing coordination between a firm anditspartner(form ofexternalprocess integration)positively affectsperformance.Consequently,inanexplorationalliance,in which tasksare more complex and production processes more interdependent,behavior controlsallow firmstobetter coordi- natetasksandactionsacrossorganizationalboundaries.Incontrast, outcome controls focus more on actual consequences, thereby leaving analliancepartner tochoosein isolation howtoreach the objectives, potentially leading to confusion and demotiva- tion.
Lastly,Noordhoffetal.(2011)notethatexplorationalliances, morethanexploitationalliances,involvetheexchangeofcomplex, sensitive,tacitknowledge,whichincreasestheriskofopportunistic behavior.Inthiscontext,afirmthatsuspectsanalliancepartnerof internalizingitsinformationandperhapsusingitopportunistically maywithholdsensitiveinformation,provokingtheotherpartnerto dothesame.Toaddressthisrisk,behaviorcontrols,suchasexplicit informationexchangeandusageclauses,mayregulatethealliance partners’conductmoreeffectivelythanoutcomecontrols(Argyres andMayer,2007;DasandTeng,2001).Accordingly,wepredict H2. Inexplorationalliances,firms’relianceonbehaviorcontrols willcontributemorepositivelytoallianceperformancethanfirms’
relianceonoutcomecontrols.
2.5. Formalcontrolsforambidextrousalliances
Recentaccountingresearchonmanagingstrategiccontradic- tionsposits that firms will bemore successful when opposing tensions are approached from a both/and rather than from an either/orperspective (e.g., Bedford,2015; Henri, 2006; Mundy, 2010;Widener,2007).Thus, inourcontext,managingandcon- trollingallianceswithcompetingmotivationsofexploitationand explorationrequiresacombinationofcontrolsforsteeringapart- ner’sactionscongruentwiththealliance’sgoalswhilealsogiving the partner sufficient autonomy to make decisions. We argue thatthesimultaneoususeofbehaviorandoutcomecontrolsmay generateadynamictensionthatencouragesalliancepartnersto concurrently address demands for both exploration objectives and predictableexploitation objectives. In particular,while the combined use of outcome and behavior controlshelps to cre- atethis necessary tension, a preference for one formal control type over the othermay disrupt this capabilityand ultimately hinder the performance of ambidextrous alliances. For exam- ple,solerelianceonoutcome controlscanresultin inadequate coordination,anoverfocusonshort-termtargets,andweakpro- tectionofsensitiveknowledge-sharing,whilealackofoutcome controlsmayresultin poorfocus and reducealliance partners’
initiative-related efforts. Meanwhile, sole reliance on behavior controlscanbedestabilizingbygeneratingcontinualdialogand change,preventingactivitiesfrombeingcompleted.Itcanalsobe demotivating(Heideetal.,2007).Failuretostressbehaviorcon- trolsnext tooutcome controls, however, can conceal theneed for changebecause a constructive dialogthat challenges exist- ing assumptions is lacking (Kreutzer et al., 2014). It can also resultin a lackof contractual definition of legitimate behavior forachievingoutcometargetsinanovelcontext(DasandTeng, 2001).
Altogether,theseargumentssuggestthatafirm’ssimultaneous useofoutcomeandbehaviorcontrolsinanambidextrousalliance willbenefitallianceperformancemorethanafirm’suseofindivid- ualformalcontroltypes.
H3. In ambidextrousalliances,firms’simultaneousrelianceon outcomecontrolsandbehaviorcontrolswillcontributemoreposi-
tivelytoallianceperformancethanfirms’individualuseofoutcome controlsorbehaviorcontrols.
2.6. Themoderatingimpactofinformalcontrolsonthe effectivenessofformalcontrols
We argue that thematch between alliancemotivations and appropriateformalcontrolsmayaffectperformance.Interestingly, however,previous researchsuggeststhat informalcontrolsmay alsoinfluenceformalcontrolperformance effects(e.g.,Cardinal, 2001; Dekkerand Van den Abbeele, 2010; Fryxell etal., 2002;
Gulati and Nickerson, 2008; Heide et al., 2007; Poppo and Zenger,2002).Asinearlierstudies,informalcontrolsaregener- allyunderstoodtoinclude people- orsocial-basedmechanisms thatenhance opencommunicationand thesharingof informa- tion, trust, dependence, and cooperation(Das and Teng, 2001;
Eisenhardt,1985).Throughasocializationandconsensus-making process, partners becomemore committed to thealliance, and shared views serve to strongly influence the behavior of the partners (Lee and Cavusgil, 2006). In some cases, such shared understanding is the end result of a comprehensive partner selectionprocess(DekkerandVanden Abbeele,2010).Inother cases, it requires ongoing socialization (Kirsch, 1996), includ- ing regularmeetings (Choudhuryand Sabherwal, 2003; Fryxell et al., 2002), workshops, and interfirm visits (Cousins et al., 2006).
It’sclearfromourinformalcontrolconceptualizationthatinfor- malcontrolscanalsobeformallyorganizedasopposedtobeingad hoc(HoetkerandMellewigt,2009).Inthatway,thesamecontrol mechanismcansupportmorethanonecontrolmode.Forexam- ple,conferencecallsatspecifiedintervalsmayallowthecontrolling firmtoassesstasksthatthealliancepartnerhasbeenperforming (behaviorcontrol),butsharedvaluesandbeliefsmayalsoresult overtime fromtheinterpersonalinteractionthattakesplacein theseconferencecalls(informalcontrol)(Kirsch,1997).Wediffer- entiateinformalcontrolsfromformalcontrols,though,basedon two,criticalinterrelateddistinctions.First,theoperationofformal controlsislargelyindependentofspecificpeopleinvolved,while informalcontrols,bycontrast,aretightlyboundtothespecificindi- vidualsandtheirrelationships(cf.‘people’or‘relationalcontrol’) (Eisenhardt,1985;HoetkerandMellewigt,2009).Second,formal controlscanspecifyoutcomes,forexample,‘setatargetdateof 2020forliftingproductsto500,000’,orinvolvespecificactions, forexample,‘checklistsremindsystemdevelopersoftheactions theyneedtotake.’Ontheotherhand,theoutcomeofaninformal controlmechanismreliesontheinteractionofindividualsfrom thealliancepartnersinvolvedand,thus,cannotbepre-specified (DasandTeng,1998).Similarly,thespecificbehaviorofindividu- alsastheyinteractcannotbestipulatedinadvance.Forexample, afirmcannotspecifyinadvancewhatwilloccurduringaface-to- facemeetingofmanagersofbothalliancepartners(Hoetkerand Mellewigt,2009).
Despite the importance of formal controls for the con- trol of alliances, prior studies which examined the effects of informal controls onformal controls frequentlypointed tothe inherent limitationsof formal controlsand generationof resid- ual negative performance effects (e.g., Anderson et al., 2017;
Carey et al., 2011; Fryxell et al., 2002; Liu et al., 2009; Poppo and Zenger, 2002). Complementary use of informal controls mayreducetheseeffects,therebyfurtherstrengtheningalliance performance. Poppo and Zenger (2002), for example, argue that because formal controls are inevitably incomplete, infor- malcontrols maypromote confidence among alliance partners that unexpected contingencies canbe resolvedwithout oppor- tunistic advantage being taken. Fryxell et al. (2002) suggest that informal controls may also foster trust between alliance
partners, which can support the development of more effec- tive formal control (Vosselman and van der Meer-Kooistra, 2009).2
Somestudieshavetakenamorenuancedviewontheinter- relationshipbetweeninformal and formalcontrols.Heide etal.
(2007) and Stouthuysen et al. (2012), for example, find that thesupplementaryeffectofinformalcontrolsonformalcontrols is morepositive withbehavior controlsthanoutcome controls.
Otherstudieshavesuggestedthatinformalcontrolsmaybecoun- terproductive because of high costs and oversocialization (e.g., Bijlsma-FrankemaandCosta,2005;DasandTeng,1998;Krishnan etal.,2006;McEvilyetal.,2003;HoetkerandMellewigt,2009).
Dasand Teng(1998), forexample,argue thatinformal controls consumetime and resourcesbecausetheydependon repeated interactionsbetweenmanagersofthedifferentalliancemembers.
Furthermore,withhighlevelsofinformalcontrolandconsequently substantialtrust,alliancepartnersaremorelikelytoacceptinfor- mationfromtheotherpartneratfacevalue(Krishnanetal.,2006).
Informalcontrolsmayevenincreasethedangerofopportunism (Bijlsma-FrankemaandCosta,2005).Uzzi(1997)notedthatclose socialtiesineconomicexchangesmayrestrictpartnersfromnew informationandopportunitiesandconsequentlyreducealliance performance.Moreover,becauseinformalcontrolsmay“takeon someaspectsofinternalsupplythatdiminishincentives,suchas secondchancesbeinggivenmorefrequently,anexpectationofdue processbeforetermination,andgreaterwillingnesstonegotiate unexpectedcostincreases”(HoetkerandMellewigt,2009,p.1029), theymayevenoffsettheeffectivenessofformalcontrols(McEvily etal.,2003;HoetkerandMellewigt,2009).
Wesuggestthatthepositiveandnegativeeffectsofinformal controlsonformalcontroleffectivenesscouldbebetterunderstood by(1)distinguishingbetweenthemotivationofthealliance,(2)dis- tinguishingbetweenthetypesofformalcontrol,and(3)evaluating theserelationshipsinthecontextofallianceperformance.
2.6.1. Theeffectofinformalcontrolsonoutcomecontrolsin exploitationalliances
Hypothesis1anticipatesthat inexploitation alliances,firms’
relianceonoutcomecontrolswillincreaseallianceperformance more positively than firms’ reliance on behavior controls. We expect, however, that informal controls will weaken this per- formanceeffectofoutcomecontrolsinexploitationalliancesfor severalreasons.
First,recallfromthelogicbehindHypothesis1thattheeffec- tivenessofoutcomecontrolsdependsonreliableandvalidoutcome measures. Because exploitation alliances involve less outcome uncertainty,firmsmayclearlyspecifyandmonitoroutcometar- gets, andtherisk ofmisevaluatingpartner performanceis low.
Outcomecontrolswillthenmotivatealliancepartnersbysignal- ingthatimprovedperformancegarnersincreasedpaymentsand preferredstatusfor future business(Joshi,2009).Informal con- trolsmaythenbelessnecessarybecausethelevelofcommitment andengagementisalreadyhigh, andtherelative costsof infor-
2Ourconceptualizationofinformalcontrolsdoesnotequaltrust.Inparticular, firmscandecidetoimplementinformalcontrolsbypromulgatingcommonvalues, beliefs,andphilosophy.Theoutcomeofthissocializationprocessmaythenleadto increasedlevelsoftrust(e.g.,Dekker,2004).Dekker(2004),forexample,elaborates howtrustandinformalcontrolsareinterconnected,yetdistinct:“Althoughrela- tionaltrustisanemergentcharacteristicandcannotsimplybeimplemented,over timeitcanbebuilt.Mechanismstobuildtrustaredeliberaterisktakingandincreas- inginteraction,forinstancebyjointgoalsetting,problemsolving,decisionmaking andpartnerdevelopmentactivities”(Dekker,2004:33).Insummary,westudythe moderatingimpactofinformalcontrols,whicharepeople-orsocial-basedmecha- nismsmanagerscandeploy,asopposedtotrust,whichisasetofbeliefsthatcannot bedeployedbymanagers.
malcontrolsmayoutweightheirrelativebenefits.Second,when outcomesaremeasurable,firmsrelyonoutcomecontrolsregard- less of their knowledge of the alliance process activities (e.g., Kirsch,1996;Ouchi,1979).Ongoingbehavioralsurveillanceisnot required,whichmakesoutcomecontrolsaveryefficienttypeof control(AndersonandOliver,1987;Kreutzeretal.,2014).Infor- malcontrolsmayharmoutcomecontrols’effectivenessbecausethe additionaltimeandresourcesareunnecessarycosts.Third,Hoetker andMellewigt(2009)andMalhotraandLumineau(2011)suggest thatlessuncertainallianceenvironments,suchaswithexploitation alliances,mayfacilitatethenegotiationofmutuallyacceptablecon- trolssuchasperformancemeasures.Suchmeasuresshouldlimit partnerdisputes and promotea willingness toresolveany dis- putesthatdoemerge.Notsurprisinglythen,investinginadditional informalcontrolsislessworthwhile.
Overall, we expect that informal controls in exploitation alliancesmayweakenthepositiveeffectofoutcomecontrolson allianceperformance.Astrongerpredictionwouldbethatinformal controlschangethedirectionoftheoverallpositiveperformance effectofoutcomecontrolsinexploitationalliances.However,we donotbelievetheorysupportssuchastrongprediction.
H4. Informal controls negatively moderate the relationship betweenoutcomecontrolsandallianceperformanceinexploita- tionalliances.
2.6.2. Theeffectofinformalcontrolsonbehaviorcontrolsin explorationalliances
ThemainpremiseofHypothesis2isthatfirms’greaterreliance onbehaviorcontrolsinexplorationalliancesmorepositivelyaffects alliance performancecompared withtheirrelianceonoutcome controls.Weexpectthatinformalcontrolsfurtherstrengthenthis positiveperformanceeffect.
First,theeffectivenessofbehaviorcontrolsvariesdirectlywith afirm’sunderstandingoftheallianceprocessesandmemberactiv- ities(Kirsch,1996;Kirschetal.,2002).Complementingbehavior controlswithinformalcontrolsmaythenimprovefirms’under- standing by establishing a climate that encourages trust and information sharing.Second, thedynamic natureofexploration alliancesgreatlycomplicatesthedesignandmonitoringofprogress and,hence,increasesthecontractingandmonitoringcostsrelated toanexclusiverelianceonbehaviorcontrols(Cardinaletal.,2004).
Informalcontrolsmaymitigatethesecostsbyallowingthealliance partners to assume that agreements will hold and contingen- cieswill beaddressed ingood faith (Poppoand Zenger, 2002).
Moreover,whenunanticipatedchangesdooccur,formalrenego- tiationwill not benecessary,increasing thestrategic flexibility oftherelationship(HoetkerandMellewigt,2009).Third,in the eventofanalliance-endingdispute,theliteratureonincomplete contractingemphasizesthatallianceactivities,evenifobservable throughbehaviorcontrols,maynotbeverifiableinacourtoflaw (LumineauandOxley,2012).Thefocusonadvancing(intangible) learninganddevelopingnewadvancedknowledgeinexploration alliances,in particular, willhinderany external arbitrator (e.g., courts)fromascertainingwhethereachpartnerisperformingas agreed(HoetkerandMellewigt,2009).Moreover,highrelianceon behaviorcontrolsinsuchacontextmayevenescalatethealliance disputeanditscost.Becausebehaviorcontrolstypically contain explicitprovisions,e.g.,thespecificationofpartners’roles,orthe allocationofassetdecisionrights,orthedefinitionofsanctionsthat canbeimposedontheoffendingparty,theymaycreateincen- tivesforeach sidetodefenditsown behaviorandquestionthe other’sactions(LumineauandMalhotra,2011).This,again,high- lightstheneed forcomplementing behavior controlswithhigh levelsofinformalcontrolbecausethelattermay“reduceinforma- tionasymmetriesbetweentheparties,decreaseuncertaintyover
litigationoutcomes,andfacilitatenegotiationandprivatedispute resolution”(LumineauandOxley,2012,p.824).
Lastly,because behavior controlsdictate how toperform or coordinate activities,theycouldstiflecreativity and innovation (Anderson and Oliver, 1987; Carson, 2007).Moreover, because scrutinyisinherentinbehaviorcontrols,trustisoftenalsocompro- mised.Inanexperimentalanalysisofmanagingstrategicalliances, Christetal.(2008),forexample,foundbehaviorcontrolscompro- misedbothtrustintheorganizationandcooperationbythealliance partner.Informalcontrolsmaythenimprovetheoveralleffective- nessofbehaviorcontrolsinexplorationalliancesbecausepartners mayperceivethebehaviorcontrolsasbeingmorefairandreason- able(Heideetal.,2007).Informalcontrolsmaybeimplementedby promulgatingcommonvalues,beliefs,andphilosophy.Thissocial- izationprocessmayinturnenhancetrust(DasandTeng,1998;
Fryxelletal.,2002),whichmayreducetheresidualnegativereac- tion(i.e.,psychologicalcost)ofalliancepartnersfeelingrestricted bythecontrollingfirm’suseofbehaviorcontrols.Insummary,the costsofinformalcontrolsmaybemeritedingoverningexploration alliancesbecausetheyempowerbehaviorcontrols.Accordingly,
H5. Informal controls positively moderate the relationship betweenbehaviorcontrolsandallianceperformanceinexploration alliances.
2.6.3. Theeffectofinformalcontrolsonformalcontrolsin ambidextrousalliances
Hypothesis3reflectsthatacontrolconfigurationcharacterized byoutcomeandbehaviorcontrolsencouragesalliancepartnersto expandexploration search whilerecognizing therisksto avoid in orderto preventdisruptionto exploitation routines,leading toincreasedallianceperformanceinambidextrousalliances.We expectthatafirm’scomplementaryrelianceoninformalcontrols mayincreasetheeffectivenessofaformalcontrolconfiguration by creating opportunities for further socialization and increas- ingtrust and thusthe chancesto combineexisting knowledge (underlyingexploitation)anddevelopnewknowledge(underlying exploration).Asarguedearlier,informalcontrolsmayalsoassistin establishinglegitimacyforrelyingonformalcontrols, especially behaviorcontrols,andenableflexibilityinthecaseofunexpected contingencies.
However, a firm’s supplementary reliance on informal con- trolsmaylimitaccesstodivergentperspectivesand alternative methods, consequently reducing the effectiveness of a control configuration characterizedby the use of outcome and behav- iorcontrolsinambidextrousalliances.Inparticular,becausehigh levelsof informalcontrol maydiffusestrongnorms andestab- lishsharedbehavioralexpectations,theyreducedeviantbehavior, limitsearchscope, andincreaseselectiveperceptionofalterna- tives(Krishnanetal.,2006;Uzzi,1997).Complementaryreliance oninformalcontrolswillthereforeeventuallyconstrainthetension provokedbyafirm’ssimultaneoususeofoutcomeandbehavior controlstocontinuallyassesswhentobreachexistingboundaries toadaptto(exploitation)ortakeadvantageofshiftingenvironmen- talconditions(exploration).
Wemakenohypothesisaboutwhetherinformalcontrolspos- itively or negatively impact firms’ increased reliance on both outcomeandbehaviorcontrolsinexplainingallianceperformance inambidextrousalliances;however,wemodeltherelationsamong thevariouscontroltypestopermiteitherrelation.Weproposea model(Fig.1)thatrelatesspecificalliancemotivationswithappro- priateformalcontrols,leadingtoincreasedallianceperformance.
Ourmodelfurtherinvestigatesthemoderatingrelationshiparis- ingfromtheuseofinformalandformalcontrolsmatchedwithan alliance’smotivation.
3. Method
3.1. Sampleanddatacollection
Totestourhypotheses,weusedasurveyandcollecteddataon controls,alliancemotivation,andallianceperformance.Thealumni databaseofa large,westernEuropeanbusinessschoolprovided theprimarydata.Thedatabasecontainsinformationonthestudy programsofthealumniandtheircurrentjobpositions.Wefirst selectedexecutivesinfunctionssuchasvice-presidentsofalliances, vice-presidentofstrategy,alliancedirectorsor,inabsenceofthese functions,managersinchargeofalliancemanagementorexternal relationsmanagers(Heimeriksetal.,2015).Intotal,weidentified 946executiveswhodeemedtobeappropriateforthisstudy.We usedathree-partsurveytooffsetpotentialproblemsassociated withsingle-respondentbiasandcommon-methodbias.According toDoty andGlick(1998)andfollowingJansenetal.(2006)and LevinandCross(2004)temporalseparationofthemeasurement ofindependentanddependentvariablesreducescommonmethod bias.
The first part of the survey assessed alliance motivation (exploitation,exploration)andwassentto946alliancemanagers andvice-presidentsresponsibleformanagingandoverseeingfirms’
alliances.Weallowedrespondentstoidentifytheirmostimportant alliance(Kaleetal.,2002;HoetkerandMellewigt,2009)andasked themto describetheunderlyingmotivation.FollowingHoetker andMellewigt(2009,p.1032),wedefinedanallianceas“avol- untaryarrangementbetweenfirmsinordertogainacompetitive advantage,involvingexchanging,sharing,orco-developmentof products,technologiesorservices.”Mergersandacquisitionswere excluded.Intotal,372allianceresponsiblesreturnedtheirques- tionnaire(39.3percentresponserate).
Withintwo weeks aftercompletingthefirst part,these 372 allianceresponsibles receivedthesecondpartofthesurvey.To ensurethatrespondentsansweredquestionswithrespecttothe samealliance,wereiteratedthenameofthealliancepartnerand thetaskdescription.Weassessedthealliance’srelianceonoutcome controls,behaviorcontrols,andinformalcontrols.Wereceived339 questionnaires(35.8percentresponserate).
Finally,twotothreeweeksafterreceiptofthesecondsurvey, a third survey was mailed to the same 339 alliance responsi- blestoassesstheirmainalliance’sperformanceandtheirgeneral appraisalofthesurvey.Tomaximizeresponserates,wefollowed YuandCooper(1983)andcombinedamail surveywitha tele- phoneoption (chosen byseven respondents). We received267 surveys,representing a 28.2percentfinal responserate, which wascomparabletorecentsurveyswithtopexecutivesonalliances (Dekker et al., 2013; Heimeriks et al., 2015; Kaleet al., 2002).
Afterdeleting31casesmainlybecauseofmissingvalues,wehada usablesampleof236matchedquestionnaires.We tookprecau- tionarymeasures tominimizecommonmethods bias,although recentresearchshowsthatsuchbiasislessofaconcernforstud- ies(likeours)withinteractioneffects (Siemsenetal.,2010).In addition,Schalleretal.(2014)providestrongconfirmatoryevi- dencethattheeffectsofcommonmethodsvariancedonotalter thesubstantiveinferencesofstudyresults.Wealsoperformeda Harman’s(1967)singlefactortest.Inthistest,commonmethod varianceexistsinthedataifanunrotatedexploratoryfactoranaly- sisonallthemeasurement itemsusedinthemodelshowsthat one factor accounts for the majority of the variance. Our fac- toranalysis (principalcomponentsanalysis) revealed six factor witheigenvaluesgreater thanone.The firstfactor oftheunro- tatedsolutiononlyaccountedfor28percentofthevariance.Also a confirmatory factor analysis model in which each item was constrained toloadonly ona singlefactor yielded poormodel
Exploitation alliances
Exploration alliances
Ambidextrous alliances
Outcome controls
Behavior controls
Outcome X behavior controls
Alliance performance
H1: +
H2: +
H3: +
Informal controls H4: -
H5: +
?
Fig.1. Conceptualmodeloftherelationbetweenalliancemotivations,formalcontrols,themoderatingimpactofinformalcontrols,andallianceperformance.
fit (2/df>10, NNFI=.55, CFI=.59, RMSEA=.25).3 These results suggest that commonmethod biasdid not seriouslyaffect our results.
Of the respondents, 63 percent were active in information andcommunicationtechnology(ICT)and servicesectors.Ofthe reported alliances, 71 percent were with a specialist service provider,includingICTservices(22%),transportandstorage(19%), facility services (e.g., catering, cleaning; 18%), business devel- opment(7%);financial administration(4%); R&Dresearch (4%);
corporatebankservices(4%);andlegalservices(3%).Thisdiver- gencetowardallianceswithaservicepartneraccordswithrecent alliance work(e.g.,Lavieet al., 2011) and canbeexplained by modern technological innovations, trends in globalization, and competitiveadvances(TiwanaandKeil,2007).Allianceslasted4.47 yearsonaverage.Finally,oursampleincludes35percentequity alliances(e.g.,jointventures)and65percentnonequityalliances (e.g.,licensingagreements,buyer–supplierrelationships).
We tested for nonresponse bias by comparing respondents withnonrespondentsfromthefinal samplein termsofgender, organizational function, and firm size and foundno significant differences.Wealsocomparedourfinalsampleofallianceresponsi- bles(n=236)withtheinitialsamplingframe(n=946)withrespect tofirmsize.Wefoundnosignificantdifferences.Finally,wecom- paredourfinalsample(participationinallthreesurveys)withthe allianceresponsiblesthatparticipatedonlyinthefirstorsecond waveofdatacollectiontoourfocalvariables.Foreachwave,we alsocomparedearlywithlateresponders.Theset-testswerenot significantata95%confidencelevel.
3.2. Constructsandmeasurement
Wepreparedthequestionnaireusingwell-establishedscales.In apilottest,arandomselectionof11managerswithvarioustenures atdifferentfirms,notincludedinthemainsample,reviewedthe surveyforcontent,clarity,andvalidity.Wemodifiedsomescale itemsbasedontheirfeedback.Thefullversionofthescalesappears inAppendixA;allscalesusedseven-pointLikert-typeitemswith
3Thenormed2(2/df)isanabsolutefitindex(i.e.,noupperboundary).Com- paredtothe2,thisindexislesssensitivetosamplesize.Normed2valueslessthan 2indicateacceptablemodelfit.TheNNFI(non-normedfitindex)isanincremental fitindexandcomparesthefitofthenullmodelwiththefitoftheestimatedmodel.
NNFIvaluesgreaterthan0.90indicatewell-fittingmodels.TheRMSEA(root-mean- squareerrorofapproximation)isanindexofmodelparsimoniousness.RMSEA valuessmallerthan.08areindicativeofagoodmodelfit.SeeHairetal.(2006) foradetaileddiscussionoffitstatistics.
anchorsat1(“stronglydisagree”)and7(“stronglyagree”),unless statedotherwise.Forallscales,wecalculatedindividualscoresas themeanscoresforthecombinedscaleitems.
3.2.1. Dependentvariable
Allianceperformance.ConsistentwithKrishnanetal.(2006),we askedallianceresponsiblestoindicatetheextenttowhichthey agreedthatseveralgoalsandobjectiveswereachievedoverthe pastyear.Thescale(˛=.96)containedfiveitemsonaseven-point Likert-typescale (1=veryunsuccessful; 7=very successful) and coveredmultiplefacetsofallianceperformance,namely,overall satisfaction(twoitems),operationalperformance(twoitems),and financialperformance(oneitem).
3.2.2. Independentandmoderatingvariables
Alliancemotivations.FollowingHeandWong(2004),Kristaletal.
(2010),andRothaermelandDeeds(2004),weregardexploration andexploitationastwodistinctdimensionsofalliancemotivation.
Exploitationwasmeasuredwithafour-itemscale(˛=.89)adapted fromHeandWong(2004),Kristaletal.(2010)andJansenetal.
(2006).Theseitemsmeasuredtheextenttowhichalliancesbuild onexistingknowledgeandmeettheneedsofexistingcustomers.
Thefour-item measureforexploration motivation(˛=.82)cap- turedtheextenttowhichalliancesdepartfromexistingknowledge andpursueinnovationsforemergingcustomersormarkets.
Formalcontrols.Thescalestomeasureoutcomeandbehavior controlscamefromDekker(2004),Cardinal(2001),Cardinaletal.
(2004),andKirschetal.(2002).Specifically,thethree-itemscale forassessingtheoutcomecontrolconstruct(˛=.84)reflectedthe extenttowhichthefirmspecifiedallianceoutcomesandmoni- toredtheirachievement.Thebehaviorcontrolscale(˛=.89)also consistedofthreeitemsbutreferredtotheextenttowhichthe firmevaluatedandmodifiedallianceproceduresanddevelopment methodologiesandmonitoredpartner’scompliancewiththispre- specifiedbehavior.
Fortheinformalcontrolsconstruct,weusedafive-itemscale (˛=.93)basedonpreviousliterature(Cousinsetal.,2006;Dekker andVandenAbbeele,2010;Fryxelletal.,2002;Kirschetal.,2002).
Theinformalcontrolscaleassessedthedegreetowhichfirmsused differentsocializationmechanisms(e.g.,interactivegoalsetting, regularlyorganizedmeetings,jointworkshops)topromoteshared beliefs,norms,andvaluesamongalliancepartnersortomaximize commongoalsandvaluesfromthestartthroughcarefulpartner selectionandsocialization.
Wetestedthemeasurementmodelindependentlyofandprior toourassessment of thestructuralrelations (i.e.,ourhypothe-
ses)(HancockandMueller,2001).Toverifythegoodnessoffitof themeasurementmodel,wesubjectedallitemsofthedependent, independent,and moderatingconstructs toconfirmatory factor analyses(CFA).Ananalysisinwhicheach itemwasconstrained toloadonlyonthefactorforwhichitwastheproposedindicator yieldeda satisfactorymodelfit(2/df=2.41,NNFI=.94,CFI=.95, RMSEA=.078),anditemloadingswereasproposedandsignificant (p<.05).Tofurtherassessdiscriminantvalidity,wecalculatedthe averagevarianceextracted(AVE)ofeachconstructandcompared thesevalueswiththesharedvariancewithanyotherconstructs.
TheAVEvaluesexceededtherecommended.5thresholdandwere alwaysgreaterthanthehighestvariancethateachconstructshared withanyotherconstruct(FornellandLarcker,1981),whichindi- cateddiscriminantvaliditybetweentheconstructsInsummary,all fitindicesandvaliditytestsindicatethatourmeasurementmodel wasreliableandvalid.
3.2.3. Controlvariables
Becauseofthesignificantvarianceinthesamples,thefirsttwo variableswecontrolledforweretherespondentfirm’sandrespon- dent partner’s industries, withdummy variables distinguishing industriesintheservice(1)and nonservice(0)sectors.Wealso measuredfirm sizeas thelogarithmof thenumberof employ- ees.Wedistinguishequityfromnon-equityalliances.Thus,equity assumesavalueofoneforallianceswithanequitycomponent(e.g., jointventures)andzeroforpurelycontractualalliances(Reuerand Ari ˜no,2002).Wealsoconsideredthedegreeofassetspecificityona seven-pointLikertscale(rangingfrom“negligible”to“substantial”) thatmeasured(1)“Ifwedecidedtostopthisalliance,theexpenses thecompanywouldhaveintransferringitsbusinesstoanother alliancepartnerprovidewouldbe...”and(2)“Ifthisalliancewere todissolve,ournon-recoverableinvestmentsinequipment,peo- ple,etc.wouldbe...”(Dekkeretal.,2013;HoetkerandMellewigt, 2009).Alliancedurationreflectedthenumberofyearstherespon- dentfirmhadbeenusingthealliancepartner’sservices.Weprovide thedescriptiveinformation(scalemeansandstandarddeviations) andacorrelationmatrixofthefocalandcontrolvariablesinTable1.
4. Analysismethods
Beforeweexaminedtherelationbetweenalliancemotivations, formalcontrols,themoderatingimpactofinformalcontrols,and allianceperformance,weusedatwo-stageclusteranalysistocre- atesubgroupsinoursample(KetchenandShook,1996).Inthe firststage,theindividual scoresontheexploitationand explo- rationconstructsweresubjectedtoahierarchicalclusteranalysis usingWard’smethod(Hairetal.,2006).Theagglomerationcoeffi- cientsindicatedappropriatesolutionsoftwo,three,orfourclusters.
Aquick review of theclustercentroids ledtoa 4-cluster solu- tion,which clearly distinguishesbetween explorationalliances, exploitationalliances,ambidextrousalliances,andallianceswith- outclearfocus.Inthesecondstage,weenteredtheclustercentroids ofthe4-clusterasinitialclustercentersofaK-Meansclusteranal- ysis.TheK-Meansclusteralgorithmrepresentsafine-tuningofthe hierarchicalclusteranalysis(Hairetal.,2006).
AspresentedinTable2,PanelA,cluster1joinsallianceswith strongexplorationmotivations(n=75),whilecluster2represents allianceswithstrongexploitationmotivations(n=56).Alliancesin cluster4emphasizedbothexplorationandexploitation motiva- tionsandthusareambidextrousalliances(n=56).Finally,cluster 3 represents alliances that are not motivated by either explo- rationorexploitation(n=49).Becauseourhypothesesonlyinvolve allianceswithstrongmotivations,cluster3 wasnotconsidered further(Bedford,2015).
Table2PanelBreportsthemeanscoresofeachcluster’sreliance onformalandinformalcontrols.Regardingtheuseofformalcon- trols,resultsshowthatexplorationalliancesprimarilymakeuse ofbehavior controls,exploitation alliancesofoutcome controls, andambidextrousalliancesofbothoutcomeandbehaviorcontrols.
Althoughnot hypothesized, thesefindings alignwithKoza and Lewin’s(1998,2000)theoreticalpropositionsthatthegreaterthe exploitation(respectively,explorative)intentofthealliance,the greatertherelianceonoutcome(respectively,behavior)controls.
Eventhoughwedidnothypothesizearelationbetweenalliance motivationsand reliance oninformal controls, Table 2 Panel B showsthateachclusterreliesrelativelyhighlyoninformalcon- trols.Inparticular,ambidextrousand,toalesserextent,exploration alliancesplacegreatemphasisoninformalcontrols.
Becauseourhypothesesdo notrequiretesting simultaneous relationships, moderated hierarchical regression analysis is the besttechniquefortestingourhypotheses(Antonakisetal.,2010).
Independentvariablesweremeancenteredtofacilitatetheinter- pretabilityofourresults(Hayesetal.,2012).4InTable3wereport theparameterestimates,t-values,andlevelsofsignificanceofour models,alongwiththeR-squareandadjustedR-squarevaluesfor thedependent variable,alliance performance. We ran separate modelsforeachcluster.Forexploration(cluster1)andexploita- tion(cluster 2)alliances,we first entered thecontrol variables andthemaineffectsofoutcome,behavior,andinformalcontrols (Model1).Wethenenteredtheinteractionsbetweenoutcomeand informalcontrols, behavior andinformal controls,and behavior andoutcomecontrols(Model2).Addingtheinteractionbetween behaviorandoutcomecontrolswasnotstrictlynecessarytotest ourhypotheses,but we includedthis termtomake theresults comparablewiththoseoftheambidextrousalliances.Weuseda slightlydifferentapproachtotestthehypothesesconcerningthe ambidextrousalliances(cluster4).Thatis,similartoexploitation andexplorationalliances,wefirstenteredthecontrolvariablesand themaineffectsofoutcome,behavior,andinformalcontrols(Model 1).Totesttheeffectoffirms’relianceonbothoutcomeandbehavior controls(Hypothesis3),weenteredtheinteractionbetweenout- comeandbehaviorcontrols(Model2)andincludedtheremaining two-andthree-wayinteractions(Model3).Todeterminethemer- itsofaddingtheinteractiontermstothemodels,wecalculatedthe changeinR-squareandassesseditssignificanceusinganF-test.
Wecalculatedvarianceinflationfactors(VIFs)toassesstheimpact ofmulticollinearityonparameterestimates.ThemaximumVIFfor modelswithoutinteractiontermswas1.95andformodelsinclud- inginteractionterms,themaximumVIFwas5.09.Yet,becauseall highVIFswerecausedbytheinclusionofinteractiontermsand p-valuesforproducttermsarenotaffectedbymulticollinearity, weconcludedthatmulticollinearityisnotaproblem(Hayesetal., 2012;Shieh,2011).
5. Results
5.1. Theinfluenceofformalcontrolsonallianceperformance
Table3reportstheestimatesoftheeffectsofformalcontrols onalliance performance. Examiningthe effects for exploitation alliancesinTable3,Panel A,weobservethatoutcome controls have a positive and highlysignificanteffect onalliance perfor- mance(b=.60,p<.001),whereasbehaviorcontrolshaveanegative
4Ithasoftenbeenarguedthatmeancenteringreducesmulticollinearity.How- ever,meancenteringinregressionmodelsdoesnotreducemulticollinearityandthe problemsmulticollinearityproduces(foracomprehensivediscussionofthisissue, seeHayesetal.,2012).
Table1
Pearsoncorrelationsanddescriptivestatisticsoffocalstudyvariables.
Construct 1 2 3 4 5 6 7 8 9 10 11 12
1 Allianceperformance (.96)
2 Exploitation 0.14 ** (.89)
3 Exploration 0.24 *** −0.28 *** (.82)
4 Outcomecontrols(OC) 0.09 0.17 *** −0.10 (.84)
5 Behaviorcontrols(BC) 0.08 −0.09 0.37 *** 0.36 *** (.89)
6 Informalcontrols(IC) 0.49 *** 0.10 0.35 *** −0.18 *** 0.15 ** (.93)
7 OC×IC 0.36 *** 0.25 *** 0.12 * 0.75 *** 0.42 *** 0.49 ***
8 BC×IC 0.41 *** 0.02 0.47 *** 0.18 *** 0.80 *** 0.70 *** 0.62 ***
9 OC×BC 0.04 0.09 0.14 ** 0.84 *** 0.77 *** −0.01 0.73 *** 0.54 ***
10 Firmsize 0.13 * 0.20 *** 0.06 −0.08 0.03 0.16 ** 0.05 0.12 * −0.03
11 Assetspecificity 0.13 ** 0.02 0.17 *** −0.07 0.12 * 0.27 *** 0.11 * 0.24 *** 0.05 0.10
12 Allianceduration 0.14 ** −0.10 0.29 *** −0.01 0.29 *** 0.24 *** 0.13 ** 0.34 *** 0.15 ** 0.10 0.20 ***
Mean 4.82 4.27 4.08 4.3 4.8 4.64 20.3 23.2 21.4 4.47 4.9 4.42
SD 1.41 1.21 1.27 1.51 1.41 1.05 8.32 9.49 10.4 3.6 1.29 1.55
Note.n=236.NumbersinparenthesesonthediagonalareCronbach’salphasofthecompositescales.
*p<.10.
**p<.05.
***p<.01.
Table2
Pairwisecomparisonofclustermeansforalliancemotivationsandcontroltypes.
Cluster1: Cluster2: Cluster3: Cluster4: Meandifferences
Exploration Exploitation Moderate Ambidexterity
(n=75) (n=56) (n=49) (n=56)
Panela:Alliancemotivation
Exploitation 5.17 2.63 3.3 4.75 C1>C4>C3>C2
(0.45) (0.69) (1.00) (0.72)
Exploration 3.06 5.25 3.71 5.38 C2=C4>C3>C1
(0.55) (0.47) (0.92) (0.63)
Panelb:Controltype
Outcome 3.72 4.38 4.63 4.69 C3,C4>C1
(1.57) (1.90) (1.19) (0.92)
Behavior 5.26 4.02 4.52 5.22 C1,C4>C2,C3(*)
(1.30) (1.46) (1.44) (1.04)
Informal 4.85 4.35 4.64 5.25 C4>C2,C3
(1.20) (1.08) (1.08) (0.78)
a:Standarddeviationsreportedinparentheses.
b:Tuckeyposthoctestsforclustermeandifferencesreportedatp<0.05.Pairsdenotedbyanasterisk(*)usedTamhane’sT2becauseequalityofvarianceswasnotassumed.
andhighlysignificanteffect(b=−.56,p<.001).Theseresultsthus providesupportforH1.
Adifferentpatternemergesforexplorationalliances.Theresults of Model 1 in Table3,Panel Bindicate that behavior controls havepositiveandhighlysignificanteffectsonallianceperformance (b=.34,p<.001).Thenegativebutinsignificantcoefficientofout- comecontrols(b=−.12,p>.05)indicatesthattheydonotaffectthe performanceofexplorationalliances.Thus,incontrasttoexploita- tionalliances,explorationalliancesseemtobenefitfromincreased relianceonbehaviorcontrols.TheresultssupportH2.
Table3Panel C,Models1 and2 reporttheestimatesofthe performanceeffectsofformalcontrolsinambidextrousalliances.
Notably,theinsignificantcoefficients forbothoutcome controls (b=.14,p>.05)andbehaviorcontrols(b=−.07,p>.05)indicatethat neithertypeofcontroldirectlyaffectsallianceperformance.Inter- estinglyandinlinewithourhypothesis,thesignificantandpositive coefficientoftheinteractiontermbetweenbehaviorandoutcome controlsispositiveandsignificant(b=.22,p<.05).Tointerpretthis interaction,weplotted theresultsinFig.2 andtestedthesim- pleslopesofoutcomecontrolsforhighandlowlevelsofbehavior controls(onestandarddeviationbelowandabovethemean).The simpleslopeforoutcome controlswithhighrelianceonbehav- iorcontrolsispositiveandmarginallysignificant(t=1.67,p=.10), whilethesimpleslopeforlowrelianceonbehaviorcontrolsdoes notdiffersignificantlyfromzero(t=−.44, p>.05).Wealsoper- formedJohnson-Neymanregionsofsignificanceanalyses(Spiller etal.,2013)toinvestigatethelevelofbehaviorcontrolatwhich theeffectofoutcomecontrolsbecomessignificant.Resultsindicate
thatoutcomecontrolshavea(marginally)significantandpositive effectonallianceperformanceforbehaviorcontrollevelsof6.27 andabove.Forlowerbehaviorcontrollevels,thejointeffectsof outcomeand behaviorcontrolsarenonsignificant.Theseresults suggestthatahighrelianceonbothoutcomeandbehaviorcon- trolsisnecessarytopositivelyaffectperformanceofambidextrous alliances.Otherconfigurationsofoutcomeandbehaviorcontrols seemtoyieldsuboptimalallianceperformanceforfirmspursuing ambidextrousalliances.Thus,thesefindingslendsupporttoH3.
5.2. Themoderatingimpactofinformalcontrolsonthe effectivenessofformalcontrols
Toinvestigatehowinformal controlsmayshape thealliance performance effects of formal controlsacross differentalliance motivations, we included the interactions between formal and informalcontrolsinourmodels.Althoughwedidnot hypothe- sizeanydirect effectofinformalcontrols, theresultsinTable3 reportpositiveand(marginally)significantmaineffectsofinformal controlsonallianceperformanceforeachmotivation.
Table3PanelA,Model2reportstheinteractionsbetweenout- comeandinformalcontrolsforexploitationalliances.Theseresults reveala negativeand significantinteractiontermbetweenout- comecontrolsandinformalcontrols(b=−.04,p<.05).Fig.3and simpleslopeanalysesrevealedthatforexploitationalliances,the relationbetweenoutcome controlsand allianceperformance is stronger for firms with low relianceon informal controlsthan forfirmswithhighrelianceoninformalcontrols(lowrelianceon
