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Saudi Electronic University
College of Administrative and Financial Sciences
E-commerce Department
Article Summary
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Answer:
Article name:
Author(s):
Journal:
Year:
Link:
Article Summary:
Main points (~300 words)
How they are related to the local Saudi virtual management styles and procedures (~100 words)
The article reference (APA):
AMETA-ANALYTICREVIEWOFSUPPLYCHAINRISKMANAGEMENT:ASSESSINGBUFFERINGANDBRIDGINGSTRATEGIESANDFIRMPERFORMANCEPAMMANHARTBaylorUniversityJAMESK.SUMMERSIowaStateUniversityJENNIFERBLACKHURSTUniversityofIowaSupplychainriskmanagementhasreceivedconsiderableattentionasÞrmsexperiencemorefrequentandsevereimpactdisruptions.Wemeta-analyti-callytesttheBodeetal.(2011)frameworkofbufferingandbridgingsupplychainriskmanagementstrategiestodeterminetheireffectonsupplychainriskmanagement.WeanalyzethesupplychainriskmanagementliteraturetoÞndthatbothbufferingandbridgingstrategiescontributetosupplychainriskmanagement.WealsoaddressthebeneÞtofsupplychainriskmanagement.ResultsindicatethatsupplychainriskmanagementprovidesastrongcontributiontooverallÞrmperformance.Additionally,weidentifyculturaldifferencesoftheserelationships.Althoughsupplychainriskman-agementstrategiesmaybeapplieduniversally,theirefÞcacyvariesbyculture.Inconclusion,weidentifyandprovideguidanceforfuturework.Keywords:supplychainriskmanagement;meta-analysis;bufferingstrategies;bridg-ingstrategies;ÞrmperformanceINTRODUCTIONSupplychaindisruptionisanyunplannedandunan-ticipatedeventthatinterruptstheßowofmaterialsorservices(Craigheadetal.,2007;Kleindorfer&Saad,2005).ThesedisruptionsresultinsigniÞcantÞnancial,operational,andrelationalcosts(Hendricks&Singhal,2005;Ponomarov&Holcomb,2009;Sodhi,Son,&Tang,2012;Speieretal.,2011;Wagner&Bode,2008).Moreover,thefrequencyandseverityofsupplychaindisruptionshasbeenincreasing(AonRiskSolutions,2017;BusinessContinuityInstitute,2017).Forexam-ple,supplychainvisibilityandcollaborationhaveresultedinmorecyberattacksduetotheinterconnect-ednessoftechnology,networks,andsystems.Recently,ÔWannaCryÕshutdownnumerousoperationsworld-wideresultinginÞnanciallossesaswellashaltedpatientcareinthehealthcaresector(Bossert,2017).Duetotheresultingcostsassociatedwithsupplychaindisruption,organizationshaveturnedtheirattentiontobetterunderstandingandmanagingsup-plychainrisk(Chopra&Sodhi,2014),withmanyÞrmsre-evaluatingtheirsupplychainnetworks.Con-sequently,organizationshavedevelopedsupplychainriskmanagement(SCRM)tomaintainbusinessconti-nuityand,thus,attenuatethesecostlydisruptions(Hohensteinetal.,2015).DespitegrowinginterestinSCRM,however,Þrmsstruggletoeffectivelymanagetheirsupplychainrisk(Melnyketal.,2014).SCRMisdeÞnedasÔtheidentiÞ-cation,assessment,treatment,andmonitoringofsup-plychainrisks,withtheaidoftheinternalimplementationoftools,techniques,andstrategiesandofexternalcoordinationandcollaborationwithsupplychainmemberssoastoreducevulnerabilityandensurecontinuitycoupledwithproÞtability,lead-ingtocompetitiveadvantageÕ(Fan&Stevenson,2018,p.7).EmbeddedinthisdeÞnitionaretwoprimaryreasonsforthisstruggle:internalconstraints(Chang,Volume56,Number366JournalofSupplyChainManagement2020,56(3),66Ð87©2020WileyPeriodicals,Inc.
Ellinger,&Blackhurst,2015;J€uttner&Maklan,2011;Knemeyer,Zinn,&Eroglu,2009)andtheexternalenvironment(Slobodow,Abdullah,&Babuschak,2008).Toaddressinternalandexternalfactors,Þrmsemploytwostrategies:bufferingandbridging(Bodeetal.,2011;Fennell&Alexander,1987;Meznar&Nigh,1995).Ontheonehand,bufferingstrategieshaveaninternalfocusandmaintainbusinesscontinu-itybyestablishingsafeguardstominimizetheÞrmÕsexposuretoriskanduncertaintyintheenvironment(Bodeetal.,2011;Fennell&Alexander,1987).Bridg-ingstrategies,ontheotherhand,haveanexternalfocusandmaintainbusinesscontinuitybyattemptingtoinßuencetheenvironmentthroughboundary-span-ningactivities(Bodeetal.,2011;Fennell&Alexander,1987;Meznar&Nigh,1995).ThetwostrategiestakedivergentapproachestoSCRM,sowethereforeinves-tigatethemseparately.Further,supplychainnetworkshavebecomeincreasinglyglobal,yetmanyresearchÞndingsarebaseduponasingleregionoftheglobe(Pagell,Katz,&Sheu,2005).Subsequently,agrowingdebateensuesregardingtheuniversalapplicationofresearchÞnd-ings(Revilla&Saenz,2014).TounderstandSCRMstrategiesmorefully,weneedtounderstandtheeffectofculturaldifferencesacrossnationsoftheworld.Consequently,theprimarypurposeofthispaperistoprovideasystematicandquantitativereviewofSCRMtorevealpatternsunobservableinseparatestudies(Glass,1976).ThesubsequentpurposeistohelpclosethegapinunderstandinghowSCRMenablesÞrmstomoreeffectivelymanagesupplychainrisk.WesynthesizeempiricalSCRMworktoidentifythestrengthofSCRMrelationshipstoguidefutureresearchbyalsoidentifyingrelationshipswithmissingmoderatorsandinconsistentconstructs.Thisresultsinthefollowingresearchquestions:(1)WhatistheimpactofbufferingstrategiesonSCRM?(2)WhatistheimpactofbridgingstrategiesonSCRM?(3)ArethereculturaldifferencesintherelationshipsbetweenbufferingstrategiesandSCRMandbridgingstrategiesandSCRM?(4)WhatistheimpactofSCRMonÞrmperformance?Wecontributetotheliteratureinthefollowingways.First,wemeta-analyticallytesttheBodeetal.(2011)frameworkbyassessingthestrengthofrela-tionshipsbetweenbufferingstrategiesandSCRMandbridgingstrategiesandSCRM.WeÞndindependentsupportforbothstrategies.Second,weexaminebothbufferingstrategiesÕimpactonSCRMandbridgingstrategiesÕimpactonSCRMacrossculturaldifferences.WeÞndthattheimpactofbothbridgingstrategiesandbufferingstrategiesvariesbyculture.Third,weaddresstherelationshipbetweenSCRMandÞrmper-formance.WeÞndthatSCRMcontributestooverallÞrmperformanceandshouldbeconsideredstrategic.Last,weprovidearesearchroadmapoutliningthemostpromisingavenuesfordevelopingandtestingmorecomprehensiveSCRMtheory.Inthefollowingsection,wepresentourtheoreticalfoundationandhypothesisdevelopment.Next,wedescribeourmethodsofdatacollection,codingandanalysis.Third,wereportourresults.Finally,wedis-cusstheoreticalcontributions,managerialimplica-tions,limitations,andfuturework.THEORETICALFOUNDATIONSANDHYPOTHESISDEVELOPMENTTheoreticalFoundationsWeutilizeresourcedependencetheory(RDT;Pfeffer&Salancik,1978)andinformationprocessingtheory(IPT;Tushman&Nadler,1978)asintroducedbyBodeetal.(2011).ThecentralpositionofRDTisthatÞrmsmustacquireandmaintainresourcescreat-ingdependencies(Pfeffer&Salancik,1978).There-fore,Þrmsseekindependencebysafeguardingthemselvesfromtheenvironment(Pfeffer&Salancik,1978).IPTseekstoreduceinformationprocessingneedsand/orimproveinformationprocessing(Huber&Daft,1987;Tushman&Nadler,1978).Firms,therefore,simplifycomplexprocesseswithautoma-tion,reducingthenumberofÞrmsinthesupplybase,narrowingproductlines,anddesigningproductsforßexiblemanufacturing(Flynn&Flynn,1999).Theyalsocreateboundary-spanninglinkagestogather,interpret,andsynthesizeinformationtoreduceenvironmentaluncertainty(Frohlich&West-brook,2001;Tushman&Nadler,1978).Bothlensesarerequiredtoexplainallaspectsofbothbufferingstrategiesandbridgingstrategies,whichdifferentiatetheirfocusandapproachviainternalandexternaldimensions(Fennell&Alexander,1987;Meznar&Nigh,1995).Ontheonehand,bufferinghasaninwardfocus,creatinginternalstructuresthatprotectandinsulatetheÞrmfromtheenvironment(Meznar&Nigh,1995).Ontheotherhand,bridginghasanexternalfocus,creatingboundary-spanninglinkagestotheenvironment.TheselinkagesreducetheÞrmÕsenvironmentaluncertaintybyinvestinginexternalrelationshipstogathermoreinformation(Flynn&Flynn,1999).BufferingStrategiesAccordingtoIPT,bufferingreducesinformation-pro-cessingneeds.Similarly,accordingtoRDT,bufferingreducesresourcedependenceonsupplychainnetworkpartners.Weconceptualizebufferingstrategiesutiliz-ingthemeasurementitemsdevelopedbyBodeetal.(2011).SpeciÞcally,theydevelopthemeasurementJuly2020AMeta-AnalyticReviewofSCRM67
itemsindependence,protection,andalternativestodescribehowÞrmsinsulatethemselvesfromtheirenvironment.Firmsgainindependencefromsupplierswhentheyhavemanufacturingßexibilitytoadapttochangingdemandanddisruptedsupply.Forexample,leansys-temsutilizeßexibleworkcellsofdedicatedmachinery,whichcaneasilyswitchproductionamongavarietyofproducts(Womack,Jones,&Roos,1990).Theapplica-tionofleantoolshasdemonstratedtheimprovedßowofgoodsandreducedthenumberofsupplychaindis-ruptions(Schonberger,2001;Womack&Jones,1997).Manufacturingßexibilityfromdedicatedmachinery,narrowproductlines,andpostponementofÞnalassemblyremovescomplexityandreducessupplychainrisk(Yang&Yang,2010;Zsidisin,2003).Protectionstemsfromslackresources,whichoftenareconsumedduringadisruption.Slackresourcesareanattempttoabsorbinternallytheimpactofexternaldisruptions(Brandon-Jones,Squire,&VanRossen-berg,2015).Safetystockinventory,excesscapacity,andtimecanbuffertheÞrmfromdisruption(Bode,H€ubner,&Wagner,2014;Bourgeois,1981).Protec-tionalsohelpspreventsupplychaindisruption.Inadditiontoslackresources,effortstosecurethesup-plychainnetworkcanhelpprotectagainstdisruptionsduetocontamination,counterfeits(Maruchecketal.,2011),Þre(J€uttner,2005),terrorism(ShefÞ,2001),andtechnologythreats(Smithetal.,2007).Lastly,alternativesarereplacementorsubstituteresourcesthatcanbeusedtoreconÞgurethesupplychainduringadisruption.Alternativessuchascertify-ingbackupsuppliersandaccesstomultiplemodesoftransportationenableÞrmstoreconÞguretheirsupplychainnetworkswithothersupplysourcesortrans-portationroutes(Ambulkar,Blackhurst,&Grawe,2015;Christopher&Lee,2004;Tse&Tan,2012).Thus,takentogether,wehypothesize:H1:BufferingstrategiesarepositivelyassociatedwithSCRM.BridgingStrategiesAccordingtoIPT,bridgingcreateslinkageswiththeenvironment,whichincreasesinformation-processingcapabilities.Similarly,accordingtoRDT,bridgingreducestheenvironmentÕsinßuenceovertheÞrm.Weconceptualizebridgingstrategiesutilizingthemeasure-mentitemsdevelopedbyBodeetal.(2011).TheyÞndÞrmsthatemploybridgingstrategiesdevelopcloserelationships,monitor,cooperate,exchangeinformation,andconductjointactivitieswiththeirsupplychainnetworkpartners.Closerelationshipsrequirehighlevelsoftrustandalong-termcommitmenttodevelopbutresultingreaterinformationsharing(Dyer&Singh,1998).Theinformationsharedincloserelationshipsgoesbeyondtacticalsupplyanddemandtoincludemoreproprietaryknowledge(Spekman,Kamauff,&Myhr,1998).CloserelationshipsalsocaninßuencesupplierstoprioritizeallocationoflimitedresourcestoÞrmswithwhomtheyhavedevelopedlong-termrelation-ships(ShefÞ,2001).Advancednoticeofriskcanbediscoveredthroughmonitoringsupplychainnetworkpartnersforanychangesortrends(Hallikasetal.,2004).OncerisksareidentiÞed,theycanbeassessedbyprobabilityandimpact.ThisallowstheÞrmtoproactivelyaddressrisktohelpavoiddisruptions(Blackhurst,Scheibe,&Johnson,2008).Monitoringalsoenablesdetectionofcurrentproblemsrequiringexpeditingandre-prioritiz-ingtobecorrected(Ambulkaretal.,2015).Developingcooperativerelationshipswithsupplychainnetworkpartnersnotonlyprovidesaccesstoinformationbutalsoprovidesadvancewarningofpotentialissuesaswellasacoordinatedresponsethroughjointlypreparedplans(Revilla&Saenz,2017).CooperationisthebasisforinterdependentÞrmstocoordinateworktoimproveSCRM(Wieland&Wallenburg,2013).Cooperationresultsinfastersupplychaindisruptionresponseandrecovery(Ergunetal.,2010)andinsupplychainnetworkpartnersÕwillingnesstoenduremonitoringandshareinforma-tion(Wieland&Wallenburg,2013).ThesharingofstrategicandtransactionalinformationisrequiredforÞrmstoutilizeinformationtoincreasecontrolofsupplychainrisks(Brandon-Jonesetal.,2014;Fanetal.,2017;Prajogo&Olhager,2012).InaccordancewithIPT,sharingstrategiesreducethecom-plexityoftheenvironment(Flynn&Flynn,1999).Firmscanaccomplishthisthroughseveralavenues.First,communicatingcustomerdemandinformationinmultitiersupplychainnetworksreducesordervarianceatupstreamtiers(Dejonckheereetal.,2004;Lee,Pad-manabhan,&Whang,1997).Second,supplychainnet-workpartnersÕdisclosureofreal-timeinventorypositionshelpsÞrmsimprovedeliveryperformance(Zhou&Benton,2007).Third,informationsharingcandirectlyprovideearlydetectionofsupplychaindis-ruptions.Themorequicklyrelevantinformationisshared,thelowertheseverityofthesupplychaindis-ruption(Craigheadetal.,2007).Lastly,informationsharingalsoenablescooperationtojointlymitigateriskswithsupplychainnetworkpartners(Braunschei-del&Suresh,2009).Infact,evidencehasshownthatthemoreupstreamanddownstreamtiersofsupplychainnetworkpartnersthatareconnectedtogetherthemorecontinuouslythematerialsßowthroughthesup-plychain(Frohlich&Westbrook,2001).InherentintheconceptofsupplychainnetworksistheimplicationthatSCRMshouldbeconductedwithmultipleÞrms(J€uttner,2005).JointactivitiesallowVolume56,Number3JournalofSupplyChainManagement68
supplychainnetworkpartnerstoparticipateindeci-sionsandproblemsolvingandnotsimplycomplywiththedecisionsofothers(Richey,Adams,&Dalela,2012).Forexample,jointplanningimprovesforecast-ingandreplenishment(Barratt,2004)andpreparessupplychainnetworkpartnerstomakequickdeci-sionswhenrespondingtoasupplychaindisruption(J€uttner&Maklan,2011).Further,sharingrisksandrewardswithsupplychainnetworkpartnersalignsincentivesandimprovesSCRM(Lietal.,2015).Thus,wehypothesize:H2:BridgingstrategiesarepositivelyassociatedwithSCRM.CultureGlobalizationhasincreasedtheinclusionofmanymorecountrieswithinthesamesupplychainnet-works,yetwehavelittleinsightintohowculturaldif-ferencesimpactSCRM(Jia&Zsidisin,2014;Revilla&Saenz,2014).Managerialpracticesandstrategyreßectthecollectivevaluesandpracticesofaculture(Hofst-ede,1991;Mettersetal.,2010).Managementandleadership,therefore,varybyculture.Thisprovidesinsightintothestructureandfunctioningofinstitu-tionswithinvariouscultures.Althoughmorenuancedstudieshavebeenconducted(e.g.,Hofstede,1991;Houseetal.,2004),therearethreeoverarchingwaysculturesdifferregardingsocietiesÕinßuenceonman-agement:(1)inequalityandrelationtoauthority,(2)conceptionofself,and(3)waysofdealingwithcon-ßict,uncertainty,andambiguity(Inkeles&Levinson,1954).Variationindealingwithconßict,uncertainty,andambiguitywillmostcertainlyaffectSCRM.AgoodexampleisJiaandRutherford(2010)whodescribeorientation,governance,andrelationshipbuildingdifferencesbetweenChineseandWesterncultures.Theysuggestthesedifferencescontributerisktobuyer–supplierrelationships.Consequently,theyoffersuggestionsforculturaladaptationthatwillimprovesupplychainnetworkpartnershipperfor-mance.Thus,wehypothesizebufferingstrategiesandbridgingstrategieslikelywilldifferacrosscultures.H3a:TherelationshipbetweenbufferingstrategiesandSCRMvariesbyculture.H3b:TherelationshipbetweenbridgingstrategiesandSCRMvariesbyculture.FirmPerformanceAswithRDTandIPT,thegoalofSCRMistoreducevulnerabilityandensurecontinuity(J€uttner,2005;Wieland&Wallenburg,2012).Withoutcontinuity,Þrmsincuramultitudeofcosts.NotonlydoÞrmsincurÞnancialcostsofsupplychaindisruption,whichincludebackorders,lostsales,andreducedshare-holdervalue(Hendricks&Singhal,2003;Hendricks&Singhal,2005),buttheyalsoincuroperationalcosts,whichincludeidleresourcesandexpeditecosts(Hohensteinetal.,2015;Ponomarov&Holcomb,2009;Sodhietal.,2012).Further,relationalcostsassociatedwithbranddamageandlossofreputationwithsuppliersandemployeesalsoresult(Kleindorfer&Saad,2005;Speieretal.,2011).NotallÞrms,however,strategicallypursueSCRM.SCRMisexpensivetoimplement,andthebeneÞtsofapreventedorminimizeddisruptionaredifÞculttoquantify.Disruptioncostsareincurredonlywhenadisruptionoccurs(Gr€otsch,Blome,&Schleper,2013),soaccuratelymeasuringthedisruptionisdifÞcult(Ganguly,Chatterjee,&Rao,2018).Further,reward-ingemployeesforpreventingproblemsisanuncom-monpracticefororganizations(Repenning&Sterman,2001).Thus,toincentivizeÞrmstomoreeffectivelymanagesupplychainrisk,wemustdemon-strateanoverallvaluetotheÞrm.Infact,NarasimhanandTalluri(2009)arguethatsuccessfulriskidentiÞca-tionandassessmentmustÞrstbeginwiththeidentiÞ-cationofoverallÞrmobjectivesandgoals.Wethereforehypothesize:H4:SCRMispositivelyassociatedwithÞrmperfor-mance.METHODLiteraturereviewsareubiquitousontopicsrelatedtoSCRM(e.g.,Datta,2017;Fan&Stevenson,2018;Fridayetal.,2018;Kamalahmadi&Parast,2016;Kochan&Nowicki,2018;Tukamuhabwaetal.,2015),indicatinganeedforconsensusandtheoreticaladvancement.However,lackingisameta-analyticreviewtoassessthenatureoftheserelationships.WetacklethisimportantdeÞciencytoquantitativelyandsystematicallysynthe-sizethegrowingbodyofSCRMresearch.Systematicliteraturereviewsdifferfromtraditionalliteraturereviewsinthattheyaremoreinclusive,reducingthechanceofbias(Glass,1976;Leuschner,Rogers,&Charvet,2013).Onlybysynthesizingthefullyaccumulatedbodyofworkcanthequalityofthatworkbemeasured(Rousseau,Manning,&Denyer,2008).Meta-analysisisamethodofsystem-aticliteraturereview,whichsynthesizestheresultsofprimarystudiestoprovidemoregeneralizableandaccurateresults(Hunter&Schmidt,2004).Mostpri-marystudieslacksufÞcientpowertopreciselyestimateeffectsizes(Lipsey&Wilson,2001).Thus,meta-anal-ysisenablesgreatergeneralizabilityduetolargersam-plesizes,whileimprovingprecisionbycorrectingforsamplingandmeasurementerrorandcomputingthemeancorrelationsweightedbysamplesizes(Hunter&Schmidt,2004).July2020AMeta-AnalyticReviewofSCRM69
SampleSelectionSampleselectionconsistedoffourdistinctsteps:broadsearches,closerexaminationforcontent,datarequirements,andredundancies(e.g.,Field&Gillett,2010;Kong,Dirks,&Ferrin,2014).First,wecon-ductedadatabasesearchinThomsonReuterÕsWebofScience,collectingarticlespublishedthroughJune2018.TheprimarycriterionforinclusionwasthateachstudymustmeasureSCRMaseitheranindepen-dentvariableordependentvariable.Therefore,weusedthefollowingsearchterms:Ôsupplychainagility,ÕÔsupplychaindisruption,ÕÔsupplychainßexibility,ÕÔsupplychainglitch,ÕÔsupplychaindisruptionmitiga-tion,ÕÔsupplychainrecovery,ÕÔsupplychainresilience,ÕÔsupplychainresiliency,ÕÔsupplychainrisk,ÕÔsupplychainrobustness,ÕandÔsupplychainvulnerability.ÕDuetotheaimofbeinginclusiveandbecauseofinconsistenciesindeterminingjournalquality,alljournalsfromtheABSAcademicJournalGuidewereincluded,inadditiontotheupperechelonjournals(Lipsey&Wilson,2001).Thisisinaccordancewithrecommendationsbymethodologicalexperts(Field&Gillett,2010;Glass,1976;Lipsey&Wilson,2001)andis,therefore,commoninmeta-analysis(e.g.,Cao&Lumineau,2015;Chen,Damanpour,&Reilly,2010;Golicic&Smith,2013;Leuschneretal.,2014;Leuschneretal.,2013;Munyonetal.,2015).Inaddi-tiontothetopjournallistscompiledbyMackelprangandNair(2010)andMackelprangetal.(2014),weincludedarticlesfromInternationalJournalofLogisticsResearchandApplication;SupplyChainManagement:anInternationalJournal;InternationalJournalofBusinessPerformanceManagement;InternationalJournalofOpera-tionsandProductionManagement;JournalofBusinessandIndustrialMarketing;andManagementDecisionandTechnologyAnalysisandStrategicManagement.Second,weconductedadissertationsearchinABIInformtoaddresspotentialÞledrawerbias(Mackel-prangetal.,2014).Becausetheyareunpublished,wescrutinizedeachdissertationintwoways.Allaccepteddissertationswereapprovedby(1)committeememberswhohavepublishedonthetopjournallists(Mackel-prang&Nair,2010;Mackelprangetal.,2014)and(2)programsrankedontheempiricalSupplyChainMan-agementlist(2019).ThisaddeddissertationsfromClemsonUniversity,MichiganStateUniversity,theUniversityofMinnesota,andtheUniversityofToledo.Third,amanualsearchwasconducted.JournalarticlesreferencedbyliteraturereviewsrelevanttothetopicofSCRMwereexaminedforpotentialadditionalstudies.Thecompiledsearchreturnedaninitialsamplesizeof1,274studies.Everyeffortwasmadetocaptureallrele-vant,qualiÞedpapers.Anyomissionisunintentional.Thenextstepsoftheselectionprocessreviewedpapersforcontent.WeexcludedpapersthathadnoempiricaldataonstatisticalrelationshipswithSCRM.Thiseliminatedsimulations,meta-analyses,concep-tualframeworks,andliteraturereviews.ThisalsoincludedremovingstudiesexploringantecedentsofSCRMrelateddirectlytoÞrmperformance,withoutrelationshipstoSCRM.Thisprocessremoved1,220papersleaving54possiblestudies.Therequirementofaneffectsizestatisticeliminatedadditionalstudies.Itisthestandardizationfromusingconsistentstatistics,whichallowsforthemeta-analy-sis,becausesuchstatisticsareinterpretableinaconsis-tentfashion(Borensteinetal.,2011).Thepooledestimatethenprovidesgreaterstatisticalpowerthantheindividualstudies.Therefore,datawerescrutinizedforcorrelationaldataormultivariatedataconvertibletor.Studieswererequiredtoreportasamplesizesothateffectsizescouldbeweighted.Thiseliminatedanadditional17papers.Lastly,redundantstudiesalsowererejected.Whendissertationsorconferenceproceedingswerelaterpublishedinapeer-reviewedjournal,thejournalpaperwasretained,andtheearlierworkeliminated.Thisresultedintheeliminationoffouradditionalpapers,resultinginasampleof33qualiÞedstudiestocode.Althoughameta-analysiscanbecalculatedontwostudies,aminimumofthreestudiesperrelation-shipisgenerallyacceptedpractice(Kongetal.,2014).Afterthecodingprocess,somerelationshipshadinsufÞcientreplicationtobeanalyzed.Thisreducedthenumberofpapersusedto26.Totestculturaldifferences,wecodecountriesbyGLOBEcluster.GLOBEgroups62nationalculturesinto10clustersbaseduponcorrelationsofculturaldimensionsandinßuenceonleadershipbehaviorandeffectiveness(Houseetal.,2004).Thisisimportant,becauseGLOBEisnotbasedongeographicalbound-ariesorsubjectiveevaluationsofanEastversusWestclassiÞcation(Pagelletal.,2005).WedonotinvestigateGLOBEdimensionsbutonlyutilizetheframeworkofclusterstoinvestigatetheeffectivenessofbufferingstrategiesÕandbridgingstrategiesÕimpactonSCRMacrossculturaldifferences.WethereforeclusterstudiestogetherforConfucianAsia(China,SouthKorea,andTaiwan),Anglo(theUnitedStatesandtheUnitedKing-dom),andGermanicEurope(Germany,Austria,andSwitzerland)todeterminewhetherbufferingandbridg-ingstrategiesÕeffectonSCRMdiffersacrosscultures.PapersutilizedinouranalysesaredescribedinAppendixA,includingpublicationtype,samplesize,method,levelofanalysis,theory,andGLOBEcluster.CodingProcessThesecondmeta-analyticstepwastoextracttherelevantconstructspertainingtotheresearchques-tionandthatpossessedthenecessarydata.TheVolume56,Number3JournalofSupplyChainManagement70
correspondingvariables(i.e.,theoperationalizationoftheconstructsofinterest)aretheuniquemeasure-mentoftheindividualstudies.Thus,eachconstructwascodedaccordingtoitsoperationalization.Con-structdeÞnitionswithrepresentativeoperationaliza-tionsareshowninAppendixB.TheÞrstandsecondauthorscodedallofthe26studiestocalculateinterraterreliability.Throughthecodingprocess,theauthorsdeliberatedambiguousitemstoconÞrmuniformity.Oncethecodingwascompleted,theauthorsexaminedthecodingfordis-crepanciesorerrorsamongthecommoncodedstud-ies.Wethencalculatedinterraterreliabilityestimates.Discrepanciesanderrorswerediscussedandcorrected.Ofthe1397potentialstudyinputscodedbytheÞrsttwoauthors,a94.1percentagreementonstudychar-acteristicsanda98.5percentagreementonstudynumbersweremet,leadingtoanoverallagreementof97.2percentbetweenbothraters.Lower-leveloperationalizationsofconstructswereaggregatedtorepresentbroader,higher-level-relatedconstructs.Thesebroaderconstructsenablegreatergeneralizationthandothecontext-speciÞcindividualstudiesandgenerateconsensusbyÞndingtheoverlapacrossvariousstudies.ThisaggregationisdescribedascombiningÔapplesÕandÔorangesÕtomakeÔfruitsaladÕ(Hunter&Schmidt,2004).Combiningsimilarindi-vidualoperationalizationsresultedin15lower-levelconstructs.Thelower-levelconstructswereaggregatedtofourhigher-levelconstructs:supplychainriskman-agement,bufferingstrategies,bridgingstrategies,andÞrmperformance.WeoutlineconstructaggregationinAppendixB.Meta-AnalyticProcessDatawereÞrstmanuallyanalyzedwithExceltocre-atefamiliaritywiththedetaileddata.Then,scriptsoftheHunterandSchmidt(2004)methoddevelopedbyWilson(2010)wereruninSPSS.Thesearemacrosofwell-establishedSPSSsyntaxÞlesforrunningmeta-analysisprocedures(Field&Gillett,2010).Forastudywithmorethanonereportedcorrelation,wecomputedcompositecorrelationvaluestopreventdoublecounting(Hunter&Schmidt,2004).TheHun-terandSchmidt(2004)methodprogressivelymakescorrectionsforindividualstudyvariances.Thecorrela-tionstatisticrwasusedduetoitswideavailability.Sample-weightedaveragesweremadetoeachindivid-ualstudy.Then,randomvariationduetosamplesizewascorrected.Next,variancesinindependentanddependentvariableswerecorrectedformeasurementerrorbymultiplyinganattenuationfactorcalculatedfromtheconstructreliabilities.Missingreliabilitydatawereimputedwithaveragereliability(Lipsey&Wil-son,2001).Varianceswerecorrectedbysubtractingartifacterrors.Consistencywastherebygainedbycorrectingformeasurementandsamplingerrors.Thecombinedandcorrectedresultsaremoregeneralizabletothetruepopulation.TheHunterandSchmidtmethodutilizesthesemea-surestofocusonthedirectionandmagnitudeofeffects.MoststudiesfocusonsigniÞcancetesting,whichdoesnotdescribethevariance.Thecontribu-tionofameta-analysisisameanstomakesenseofwhathasbeenaccumulatedbyprovidingconÞdenceintervalstoshowtheoverlapofseparatestudies.Also,signiÞcancetestingdoesnotdistinguishbetweenvari-anceduetouncorrectedartifactsormoderators.Meta-analysis,however,cancorrectformeasurementerroranddetectmissingmoderatorsofrelationships.RESULTSHypothesisTestingWeanalyzeddataavailableforeachhypothesisandavailabledimensionsofthehypothesizedconstructs.Foreachmeta-analyticrelationship,wepresentthefollowingresults:thenumberofindependentsamples(k),uncorrectedsample-weightedmeaneffectsize(r),thecombinedtotalsamplesize(n),correctedeffectsize(q),95percentconÞdenceintervalsusingstan-darderror(CI),80percentcredibilityintervalsusingstandarddeviation(CV),andthe%ofartifact-relatedtotalvarianceexplained(%ARTV)bythehypothesizedrelationships(Hunter&Schmidt,2004).Theruleofthumbisthateffectsizes(q)of.1areconsideredsmall,effectsizesofatleast.25areofmediumsigniÞcance,andthosegreaterthanorequalto.4arelargelysigniÞcant(Cohen,1977,1988).Con-Þdenceintervals(CI)reßecttheamountoferrororprecisionofthemeanbyusingthestandarderror(Schmidt&Hunter,2014).Theyareinßuencedbysamplingerrorandindicatetherangeofthemeantruescore.Intervalscontainingzeroareconsideredtopotentiallyhaveatruemeaneffectofzero.Credibilityintervals(CV)expressthedistributionormagnitudeofthepopulationvariancebyusingthestandarddevi-ationofthecorrectedcorrelations(Schmidt&Hunter,2014).WiderCVsarelessreliableandareinßuencedbyrandomeffects(Schmidt&Hunter,2014).WideCVsareabasisfordetectingthepresenceofunidenti-Þedmoderators(Whitener,1990).Moderatorvariablesinthemeta-analysisweredetectedbythe75percentruleofthumb(Schmidt&Hunter,1977).Errorvariancesexplainedbyartifactcorrection(%ARTV)lessthan75percentareconsid-eredtoindicatemissingmoderators.Explainedvari-ancesabove75percentaregenerallyconsideredfreefromlargemoderatoreffects(Hunter&Schmidt,2004).Allbutoneoftherelationships(i.e.,bridgingstrategiesinGermanicEurope)inthisstudyhave%ARTVlessthan75percent,indicatingthatpotentialJuly2020AMeta-AnalyticReviewofSCRM71
moderatorsinßuencemostoftherelationships.Thissuggestsmorecomplexrelationshipsshouldbestud-iedinthefuture,whichreportgreaterdetail.ResultsforallanalysisaresummarizedinTable1Totesthypothesis1,weevaluatedthecorrelationsbetweenbufferingstrategiesandSCRM.Bufferingstrategieshaveamoderate,positiveeffectonSCRM(q=.39),witha95percentconÞdenceintervalthatdoesnotcontainzero(CI=.20to.46).Totesthypothesis2,thecorrelationsbetweenbridgingstrate-giesandSCRMwereevaluated.Bridgingstrategieshaveastrong,positiveeffectonSCRM(q=.47),witha95percentconÞdenceintervalthatdoesnotcontainzero(CI=.29to.50).Theseresultsprovidesupportforhypotheses1and2.Inordertotesthypothesis3aand3b,weexaminedtheeffectsofculturaldifferencesontherelationshipsbetweenbufferingstrategiesandbridgingstrategiesandSCRM.WeanalyzedGLOBEculturaldifferencesbetweenConfucianAsia(China,SouthKorea,andTaiwan),Anglo(theUnitedStatesandtheUnitedKingdom),andGermanicEurope(Germany,Austria,andSwitzerland)todeterminewhetherbufferingandbridgingstrategiesÕeffectonSCRMisdifferentacrosscultures.InConfucianAsia,weÞndstrong,positiveeffectsforbothbufferingstrategies(q=.50;95%CI=.34to.54)andbridgingstrategies(q=.60;95%CI=.42to.61),withneitherconÞdenceintervalscontainingzero.Thesearethestrongesteffectsizesofthethreecultures.InAnglo,weÞndmoderate,positiveeffectsforbuffering(q=.22;95%CI=.05to.32).WeÞndstrong,positiveeffects,however,frombridging(q=.47)withintervalsthatdonotcontainzero(95%CI=.29to.50).Theeffectsizeofbridgingismorethandoublethatofbuffering.Thesearethemostdissimilareffectsizesbetweenbufferingandbridgingstrategiesofthethreecultures.InGermanicEurope,weÞndverysimilareffectsizesofbufferingandbridging(q=.43andq=.43)andintervalsthatdonotcontainzero(95%CI=.21to.49and.25to.48,respectively).Thesearethemostsimilareffectsizesbetweenbufferingstrategiesandbridgingstrate-giesofthethreecultures.Wefurtherconductedarandomeffectsregressionanalysisandchi-squaretestforhomogeneitytoverifyTABLE1DirectEffectsonSupplyChainRiskManagementDirectEffectsonSupplyChainRiskManagementknrqLower95%CIUpper95%CILower80%CVUpper80%CV%ARTVH1aBufferingtoSCRM458,464.33.39.20.46.10.6710.9H1bBridgingtoSCRM5112,448.39.47.29.50.18.767.5H2SCRMtoFirmPerformance102,581.35.40.24.45.04.755.0H3:CountryEffectsBufferingtoSCRM-ConfucianAsia41,027.44.50.34.54.35.6518.3BridgingtoSCRM-ConfucianAsia102,440.52.60.42.61.38.839.0BufferingtoSCRM-Anglo122,524.19.22.05.32.08.529.8BridgingtoSCRM-Anglo133,153.39.47.29.50.11.825.0BufferingtoSCRM-GermanicEurope5793.35.43.21.49.21.6519.0BridgingtoSCRM-GermanicEurope61,296.37.43.25.48.38.4876.2Volume56,Number3JournalofSupplyChainManagement72
thegroupdifferences(Table2).WeÞndapoormodelÞtforbothbufferingstrategies(p=.417)andbridg-ingstrategies(p=.401);therefore,thenullhypothesisofhomogeneityisrejected.ThisindicatesstatisticallysigniÞcantgroupdifferencesbetweencultures(DeVeaux,Velleman,&Bock,2011).Thisprovidesfurthersupportforhypothesis3aand3b.Hypothesis4predictsapositiveeffectofSCRMonÞrmperformance.SCRMhasalarge,positiveeffectonÞrmperformance(q=.40)withintervalsthatdonotcontainzero(95%CI=.24to.45).Therefore,hypothesis4issupported.DISCUSSIONOurgoalwastoprovideasystematicandquantita-tivereviewtoenablegreaterunderstandingofthestrengthofSCRMrelationshipsandguidefuturework.Meta-analysisallowsforrelateditemstobeexaminedtodeterminemoreaccurateandgeneralizablerelation-ships(Borensteinetal.,2011).WeidentiÞedtheeffectofbufferingstrategiesandbridgingstrategiestohelpÞrmsmoreeffectivelymanagesupplychainrisk.WealsoÞndthatculturedifferencesshapetheimpactofSCRMstrategiesofbufferingandbridging.Thisisimportantinestablishingconclusiveevidencethatcul-turaldifferencesarerelevantfactorspriortoinvestigat-ingtheirimpact(Pagelletal.,2005).Further,weaddresstheissueofSCRMimpactontheÞrm.Previ-ousworkhasshownthatsupplychaindisruptionsareassociatedwithÞnancial,operational,andrelationalcosts.WeÞndthatSCRMcanbeasourceofoverallÞrmperformance.AlthoughSCRMisexpensiveanddifÞculttoimplement,itcanprovidebeneÞtsthatsur-passtheinvestmentinsafeguardsandinformationprocessing.Overall,ourresultssuggestthatÞrmscanimproveSCRMandÞrmperformancebyemployingbothbufferingandbridgingstrategies.Therefore,SCRMshouldbeconsideredstrategic.TheoreticalContributionsThisstudyprovidesgeneralsupportfortheBodeetal.(2011)frameworkaswellasbothRDTandIPTastheoriestohelpexplainhowÞrmsutilizebufferingstrategiesandbridgingstrategiestomanagesupplychainrisk.ConsistentwithRDT,weÞndthatÞrmsseektoreducesupplychaindependenceandinßuencefromtheenvironment.AlsoconsistentwithIPT,weÞndthatÞrmsseektoengageandinßuencetheirenvironment.Table1outlinesdifferencesacrosscultures.First,theeffectsofbufferingstrategiesandbridgingstrategieswithinConfucianAsiaarestrongerthanwithinothercultures.Second,theeffectsofbufferingstrategiesandbridgingstrategiesinAngloÞrmsaremoredissimilarthaninothercultures(i.e.,bufferingstrategiesinAngloÞrmsareweaker).Third,wefoundstrongeffectsizesfoundfrombridgingstrategiesinGermanicEuropeanÞrms.TheeffectsofbufferingstrategiesandbridgingstrategieswithinGermanicEuropeanÞrmsaremoresimilarthaninothercultures.Infact,theeffectsizesarethesame,andtheconÞdenceintervalsareverycomparable.ManagerialImplicationsThisstudyalsohasimplicationsformanagement.First,weidentifydistinctbufferingstrategiesandbridgingstrategiesthatcontributetoSCRM.Firmshavelimitedresourcesandfaceanoverwhelmingamountofinformation.Thisstudybeginstohelpthemselectthestrategiestheyshouldemploytoeffec-tivelymanagetheirsupplychainrisks.WeenableselectionbyanalyzingthemostfrequentlystudiedSCRMrelationshipswithinasinglepaper.Theeffectofbridgingstrategiesishigherthanthatofbuffering.Infact,theeffectsizeofbridgingstrategiesisoutsideoftheconÞdenceintervalforbufferingstrategies.Thisdoesnotimplythatbridgingstrategiesshouldbeuni-formlymaximized.Theremustbeastrategicreasonfortheinvestmentofresourcesandhigh-levelman-agerialeffortrequiredforbridgingstrategies.Bufferingstrategiesshouldbepursuedinadditiontobridgingstrategies.Second,weestablishthecontribution,whichSCRMcanmaketotheÞrmÕsbottomline.AsopposedtothinkingofSCRMasaliability,SCRMmaybeseentocontributetoimprovedoverallÞrmperformancebyTABLE2RandomEffectsRegressionAnalysisandChi-SquareTestforHomogeneityRandomEffectsRegressionAnalysisandChiSquareTestforHomogeneityModelw/outPredictorspContinuousPredictorCategoricalPredictorFullModelbdfpv2dfpv2dfpBufferingStrategiestoSCRMwithCultureDifferences.000.26517.0006.7082.03518.59418.417BridgingStrategiestoSCRMwithCultureDifferences.000.52525.0001.2072.54727.16226.401July2020AMeta-AnalyticReviewofSCRM73
maintainingbusinesscontinuity.SCRMcanbeasourceofcompetitiveadvantage.ThisisimportantbecausewhenÞrmsviewSCRMasacosttobejusti-Þed,SCRMbecomesaburden(VanDerVegtetal.,2015)asopposedtoabeneÞt.Thestrategiesofbridgingandbufferingmaynotapplyuniversallytoothercultures.ThissuggestsÞrmsshouldtailorSCRMbylocation.Failuretorecognizeculturaldifferencescouldhindertheimplementationofbuffer-ingstrategiesandbridgingstrategies.Firmswithinterna-tionalsupplychainnetworksmusttrainemployeeshowtoadapttoexpectationsoflegalobligations(i.e.,Anglo),Þnancialincentives(i.e.,GermanicEurope),andreciprocity(i.e.,ConfucianAsia)toemploymoreeffec-tivebridgingstrategies.Theyalsomaywanttoexploitbridgingstrategiestobetterunderstandculturaldiffer-ences(e.g.,risksources,markets)andemploymoreeffectivebufferingstrategies.Firmsmustevaluatetheirglobalfootprinttodeterminethecorrectmixofalterna-tives,independence,andprotection.LimitationsAsisthecaseforallresearchefforts,afewlimita-tionsarepresent.First,wearelimitedbytheavailabil-ityofprimarystudies.Althoughweutilizedrigorousprocedurestoincludeeveryrelevantstudy,wecannotguaranteethatsomeevidencewasnotmissed.WeareconÞdent,however,thatitisunlikelytheresultswouldchange.Further,somemeasurementslackedthereplicationnecessarytobeincludedintheanaly-sis.Thishelpsidentifyareasfornewresearch.Second,wearelimitedbytheavailabilityofreporteddata.Somestudiesdidnotreportreliabilityinformation.Inthesecases,wesubstitutedtheaveragereliability.Inaddition,unidentiÞedpotentialmodera-torsarepresentwhichhavenotbeencaptured.Reportingthesedetailscouldexplainrelationshipsmoreprecisely.Forexample,manystudiesreportcombinedresultsformixedindustriesandmultiplecountries.Thishelpsguidefutureworktoinvestigateandreportcontextualdifferences.RecommendationsforFutureWorkManydirectionsforfutureworkcanbeidentiÞedfromthisstudy,whichwillfurtherourunderstandingofSCRM.WemustfullydevelopresearchtoadvanceSCRMtheoryandgenerateimpact(Knemeyer&Faw-cett,2015).WedothisÞrstbyaddressingpotentialmissingmoderators,whichwereidentiÞedbytherela-tionshipswithARTVlessthan75percent.Inaddition,weaddressmissingconstructs,relationshipinterde-pendencies,andcausalrelationshipsandconcludewithstudydesigns.MissingModerators.Futureworkshouldcompare,contrast,andreportmoreindustry-speciÞcdetails.Allbuttwostudiesaggregatedindustriestogetheraseithermanufacturingormixed.Thisisanimportantareaforfutureresearch,becausedifferentindustrieshavedif-ferentlevelsofindustrydynamism,tierlevel,competi-tiveintensity,marketconcentration,andproductcomplexity.Thus,industrydifferencescouldleadtoeitherbufferingstrategiesorbridgingstrategiesbeingmoreeffective.Animportantpotentialmoderatorimpactingbuffer-ingstrategiescouldbeindustrydynamism.Asthepaceofindustrychangeincreases,alternativesandprotectioncouldquicklybecomeobsolete.Alternativesuppliers,modesoftransportation,androutesmaynolongerbecertiÞedorviablefornewcomponentrequirements.Similarly,slackresourcessuchassafetystocksandpart-speciÞctoolingcouldbecomeobso-lete.WedidnotÞndstudiesmeasuringorcontrollingforindustrydynamism,butwedidÞndsinglestudiesmeasuringenvironmentaldynamism,marketshare,HerÞndahl–HirschmanIndex(marketcompetitive-ness),andcompetitiveintensity.Industrydynamismcouldhindertheeffectivenessofbufferingstrategies,becauseslackresourcesareathigherriskofobsoles-cence.Thehigherriskwouldmakeimplementationunderthoseconditionsmoreexpensive.Anotherimportantpotentialmoderatorimpactingbufferingstrategiesandbridgingstrategiescouldbesup-plychaintierlevel.UpstreamtiersofthesupplychainsuchasrawmaterialsorcomponentsaremoredistantfromtheendcustomerthantheÞnishedgoodtierofthesupplychain.Thisdistancefromtheendcustomerresultsinlessinformationregardingactualdemandandleadstogreatervarianceinorders(Lee,1997).Informa-tionexchangeinupstreamtiersmaybedependentupontheabilityoftheirdownstreamÞnishedgoodssupplychainnetworkpartnerstohavecloserelationships,coop-erate,andconductjointactivitieswithdownstreamcus-tomerstoobtainend-customerinformation.Arebridgingstrategieslesseffectiveforupstreamsupplychaintiers?Doessupplychaintierlevelmoderatetheeffectivenessofdifferentaspectsofbridgingstrategies?Similarly,supplychainnetworkcomplexityisanimportantpotentialmoderator.Firmsthatfrequentlyoutsourcemayincreaseexposuretomoresourcesofrisk(Revilla&Saenz,2014).Themoredirectsuppliersandtiersofsupplychainpartnersinthenetwork,thegreaterthefrequencyofdisruptions(Bode&Wagner,2015).Thisisduetoaninabilitytoidentifyeverysupplychainnetworkpartner,sosomeriskscouldnotbeidentiÞedand,thus,bufferedagainst.Addition-ally,supplychainnetworkcomplexitycanamplifytheseverityofsupplychaindisruptionsastheymovedownstream,creatingmajordisruptions.SafetystockmaybeinsufÞcienttoabsorbamajorsupplychaindisruptioninacomplexsupplychainnetwork.Doessupplychainnetworkcomplexitymoderatetheeffec-tivenessofbufferingstrategies?AthoroughandVolume56,Number3JournalofSupplyChainManagement74
TABLE3CulturalDescriptionsCultureRelationshipOrientationRegulatoryForcesOutsourcingOutcomesConfucianAsia:China,SouthKorea,andTaiwanResult-driven,encourageCollective:groupworkingtogetheroverindividualgoals.Reciprocityoffavors(guanxi)includinggovernmentandcompetitorswithlessexpectedfromweakerparties.Longterm.Investsinteamworkskills(Caietal.,2010;Park&Luo,2001;Poweretal.,2010)Relational,negationandcompromise(Caietal.,2010;Handley&Angst,2015)Lowlevels(Ribbink&Grimm,2014)Veryhighbuffering(.50)andbridging(.60)Anglo:UnitedStatesandUnitedKingdomCompetitiveandresultsoriented.Lowcollectivism.Legalandself-interestexertedfrompower.Shortterm.Investsininnovation(Caietal.,2010;Jia&Rutherford,2010;Poweretal.,2010)Contractuallawsandprocedures(Caietal.,2010;Jia&Rutherford,2010)HighlevelsandreliantonChineseÞrms(Jia&Zsidisin,2014;Ribbink&Grimm,2014)Unbalancedeffects.Moderatebuffering(.22)andsometimesnoeffect.Highbridging(.47)GermanicEurope:Germany,Austria,andSwitzerlandValuecompetitionandaggressivenessandaremoreresult-oriented.Lowcollectivism.Financialincentivesandworkerparticipation.Importancefromtrainingandeducation.Weakpartiessupportedbyregulation.(Lane,1997;Millingetal.,2001)Standardizationthroughtradeassociations(Lane,1997;Millingetal.,2001)Commonunderstandingfromstandardsandtechnicaltrainingenablesoutsourcingwithlesscommunicationandmisunderstanding(Lane,1997;Skipperetal.,2008)Highandbalancedbuffering(.43)andbridging(.43)July2020AMeta-AnalyticReviewofSCRM75
parsimoniousframeworkformeasuringsupplychainnetworkcomplexityinfutureresearchishorizontal,vertical,andspatialcomplexitybyBodeandWagner(2015).MissingConstructs.Thisstudyhighlightsopportuni-tiesforfutureworkbyidentifyingconstructswheretherewerenotenoughstudiestoconductameta-anal-ysis.ExamplesofmissingorunderstudiedconstructsTABLE4RecommendationsforFutureResearchInßuentialFactorResearchQuestionCausationIstherecausationbetweenbridgingandbufferingstrategies?Whichrisksourcesofsupplychaindisruptionsarebestmitigatedbybufferingorbridgingstrategies?Isbufferingmoreeffectivefornaturaldisastersandsocio-economicchangewhilebridgingismoreeffectiveforsupplyanddemandsources?WhataspectsofsupplychainnetworkcomplexityarethegreatesthindrancetoSCRM?Whichaspectscanbebridged,andwhichshouldbebuffered?DoesidentiÞcationofuncertaintiesaffectemploymentofeitherbufferingstrategiesorbridgingstrategies?CountriesFutureworkshouldcompare,contrast,andreportmorecountry-speciÞcworkconsideringfactorssuchasinfrastructure,ruleoflaw,regulations,intellectualpropertyprotections,andculture.Whichfactorsarethemostimportantinexplainingcountrydifferences?Howareperceptions,motivation,anddecisionmakingimpactedbyinternationalsupplychainnetworks?Cansomecountry-levelaffectsbeattributedtothetierinthesupplychainnetwork?IndustriesFutureworkshouldcompare,contrast,andreportmoreindustry-speciÞcwork,consideringfactorssuchascompetitiveintensity,HHI,tierlevel,productcomplexity,andindustrydynamism.WhichfactorsandlevelsaremostimportanttoSCRM?InterdependenciesUnderwhatconditionsmightbufferingandbridgingstrategiesbeeffectiveornot?WhataretheinterdependenciesbetweenspeciÞcbridingstrategiessuchassocialcapital,collaboration,informationsharing,andintegration?Whatistheoverlaportensionbetweenalternatives,independenceandprotection?IstheimpactofnetworkcomplexityonSCRMmoderatedbyeffectivebridgingstrategies?OperationalizationsThesupplychainÞeldlacksconsensusofterms,andauthorsutilizevariousmeasures.Operationalizationsshouldconvergetoenablecomparison.Measuresofresponsetimeshouldmoveawayfromsubjectiveself-reports(i.e.,slowtofast)tomoreobjectivemeasures(i.e.,hours,days,weeks).PerformanceWhichspeciÞcstrategiesordimensionshavethegreatesteffectonoverallÞrmperformance?Howisstrategyselectionimpactedbyattributionsofsupplychaindisruptionorperformanceaspirations?ReplicationLackofreplicationremovedstudiesfromtheanalysis.ReplicationofstudiesisneedednotonlytosynthesizeÞndingsforamoreaccurateassessmentofeffectsize,butalsotoidentifyunknownmoderatorsofrelationships.Theorydevelopmentrequiresreplicationandnotjustnovelty.TemporalWhatarethecostbeneÞttradeoffsofvarioussupplychaindisruptionresponsetimesunderdifferentconditions?Howdocapabilitiesevolveovertime?HowisSCRMcreated,changed,orpreserved?HowdobufferingandbridgingstrategiesrelatetotheSCRMprocess?Howdointeractionsbetweensocietalfactorsevolveovertime?Doeconomicpressuresprovideinfrastructure,whichthenchangesculturalandregulatorysupport?Volume56,Number3JournalofSupplyChainManagement76
includepostponement(Yang&Yang,2010),productcomplexity(Novak&Eppinger,2001),andorganiza-tionalculture(Braunscheidel&Suresh,2009).Weneedtounderstandtheeffectofthesepotentialcon-structstounderstandmorecomplexcause-and-effectrelationshipsandinterdependencies.WedidnotÞndpapersmeasuringtheeffectofpost-ponementonsupplychainriskmanagement.Post-ponementisabufferingstrategytomanagehigh-demanduncertaintybydelayingthecommitmentofresources(Manuj&Mentzer,2008a,2008b).Whendemandisuncertain,Þrmscanapplysafetystockstocomponentassemblies,whicharecheaperthanÞn-ishedgoods,andthenemployßexiblemanufacturingtoquicklyassembleÞnishedgoodsasdeterminedbyactualsales.Isbufferingmoreeffectivewhenitincludespostponement?Whataretheinterdependen-ciesofpostponement,buffering,andbridging?Ispostponementmoreeffectivewhenbridgingstrategiesareineffectiveatdeterminingdemand?Orispost-ponementmoreeffectivewhenbridgingstrategieseffectivelyconveycustomerpreferencesindeterminingcommoncomponents?NovakandEppinger(2001)foundthatÞrmswithcomplexproductsseekindependencefromsuppliers(i.e.,bufferingstrategy)andproducein-house,becauseitisassumedthatinternalcoordinationismoreefÞcientthanexternalcoordination(i.e.,bridg-ingstrategy).Wefoundtwostudiesmeasuringtherelationshipofproductcomplexitytosupplychainriskmanagement.Productcomplexityincreasestherisk(Merschmann&Thonemann,2011)andimpactofdisruption(Bode&Macdonald,2017).IstheassumptionthatinternalcoordinationismoreefÞ-cientthanexternalcoordinationcorrectunderallcon-ditions?AretherespeciÞcbridgingstrategieswithagreatereffectonsupplychainriskmanagementthanbufferingstrategies?Itisimportanttostudytheeffectofthesemissingorunderstudiedconstructsonbuffer-ingstrategiesandbridgingstrategiesinfutureresearch.Inadditiontoculturalinßuences,stemmingfromnationaldifferencesisÞrm-leveldifferences.Weneeddescriptionsoforganizationalcultureandtheireffectsonbufferingstrategiesandbridgingstrategies.AlthoughwedidnotÞndstudiesmeasuringorganiza-tionalculture,wedidÞndafewstudiesthatmeasuredtheenablingeffectofspeciÞclearning(Ellingeretal.,2015)anddisruption(Ambulkaretal.,2015;Riley,2013)orientationsandriskpropensity(Park,2011).Thecompetingvalueframework(Cameron&Quinn,2011)isawell-establishedclassiÞcationoforganiza-tionalculture,includingdimensionsofstability,ßexi-bility,andrisktakingthatcouldproveenlightening.Forexample,BraunscheidelandSuresh(2009)Þndthataßexibleapproachandexternalfocusenableexternalintegrationwithsuppliersandcustomers.Docertainorganizationalcultureshaveacausalrelation-shipwithbufferingandbridgingstrategies?ComplexRelationships.ExploringhowbufferingstrategiesandbridgingstrategiesinteractalsocouldimpactSCRM.Forexample,SrinivasanandSwink(2015)foundthatÞrmsinvestinginintegrationcapa-bilities(i.e.,bridging)wouldnotexperienceexpectedbeneÞtsunlesstheyalsoinvestedinthecapabilitytoquicklyandeffectivelyimplement(i.e.,buffering)anyplans,whichweresubsequentlydeveloped.Similarly,SrinivasanandSwink(2018)foundthatifÞrmsdonothavetheßexibilitytoquicklyimplementdeci-sions,thenaccesstomoreinformationiswasted.Theyarguethatßexibility(i.e.,buffering)andvisibil-ity(i.e.,bridging)complementeachother.Further,RevillaandSaenz(2017)foundthatÞrmsengaginginbothinternal(i.e.,buffering)andexternal(i.e.,bridging)strategieshadthebestÞrmperformance.AlthoughweÞndthatSCRMimprovesoverallÞrmperformance,itisabroadmetric.Weneedtounder-standwhichspeciÞcdimensionsofbufferingstrategiesorbridgingstrategiesareassociatedwithspeciÞcdimensionsofperformance.Forexample,bufferingstrategiesÕeffortstogainindependencefromsuppliersthroughmanufacturingßexibilitysuchasqualityimprovement,inventoryreduction,andfastercycletimesandleadtimescanhaveÞnancialbeneÞtssuchascostreductionandshortercashcycles(Gerwin,1993;Hayes&Wheelwright,1984;Skinner,1985).Alternativessuchasexcesscapacity,Þnancialsavings,andtheabilitytore-routeshipmentscanbeenactedwithoutdisruptingmarketingobjectivessuchaspur-suingnewmarkets(Christopher&Holweg,2011;Manuj&Mentzer,2008b;ShefÞ&Rice,2005;Tallurietal.,2013).Similarly,bridgingstrategiesÕcloserela-tionshipsandinformationexchangecouldprovideaccesstonewtechnologies,whichcouldbeusedforinnovationobjectivessuchasnewproductintroduc-tion.Finally,howdoescultureresultinvaryingeffects?Althoughclusteringbyregionsisratherbroad,theresultsilluminateareasformorenuancedresearch.WhyarebridgingstrategiesÕeffectinConfucianAsiaandGermanicEuropegreaterthaninAnglo?Howdoculturaldifferencesinteractwithmissingpotentialmoderatorssuchastierlevel?Forexample,doÞrmsinsomeculturesconductmoreorlessoffshoringofrawmaterialsandcomponentsthatmightmoderatetheeffectivenessofbridgingstrategies?Whatarethewaystoovercomethesedifferences?AretheseÞxedeffectsoraretheychangingovertime?StudyDesigns.Ourmeta-analysisrevealsthecon-foundingstateoftheSCRMÞeldandpointstowardfuturework,whichcanprovideconsensus.Theinsuf-ÞcienttheoreticalexplicationandlackofempiricalJuly2020AMeta-AnalyticReviewofSCRM77
evidencecreateinconsistentuseofconstructs.This,inturn,causesresearcherstoutilizevariousmeasuresduetothelackofconsensussurroundingconstructs.Ambiguityresultsinconfusingandcontradictoryout-comesthatlackthecapabilitytoadvancetheory(Flynn&Flynn,2004).Operationalizationsofcon-structsshould,therefore,convergetoenablecompar-isonandadvancementoftheory.Indeed,thisisoneofthebeneÞtsofmeta-analysis(Hunter&Schmidt,2004).Themostcommonoperationalizationofsupplychaindisruptionistheself-reportedimpactonsixcross-functionalmetrics:prices,operationalefÞciency,quality,responsiveness,reliability,andsales(Bodeetal.,2011).Thisisaparsimoniousandholisticmea-sureofoutcomes,whichshouldcontinuetobeused.Supplychaindisruptionhasbeendescribedwithcon-structssuchasduration,dichotomousseverity,spreadtootherÞrms,andclosecalls.Habermannetal.,2015,whomeasureclosecalls,istheonlystudywefoundthatbeginstomeasureproblemprevention.ItisimportantforfutureworktocontinuetoidentifythesuccessfulpreventionofproblemsinordertoincreaserecognitionofSCRMasstrategic.Thefre-quencyofoccurrencehasbeenmeasuredonascalerangingfromnevertofrequently(Zsidisin&Wagner,2010).Measuresoftimeinfutureworkshouldmoveawayfromsubjectiveself-reports(i.e.,slowtofast)tomoreobjectivemeasures(i.e.,hours,days,weeks).Oneofthekeystobufferingstrategiesissafetystock,whichfrequentlymeasuresperceptionsofutilization.ZsidisinandWagner(2010)includeperceiveddegreeofuseofsafetystockasaniteminascaleforredun-dancypractices.Inhisfour-itemscaleofsafetystock,Park(2011)capturestheperceivedobjectiveforhold-inginventory.Likertscalesofperceptionsofutiliza-tion,however,aresubjective.Futureworkshouldutilizemoreobjectivemeasurestoenablecomparisonacrossstudies.Someworkhasbeguntomeasuremoreobjectiveinventorylevels(Brandon-Jonesetal.,2015;Haber-mannetal.,2015).MoststudiestaketheperspectiveofthefocalÞrm.Brandon-Jonesandcolleagues,how-ever,provideaverynuancedandparsimoniousmea-sureofthesupplychainnetworkperspective.Theymeasureinventorylevelsofplantsandsupplierssepa-rately.Duetotheinterdependenciesinsupplychainnetworks,thisisanimportantoperationalizationthatshouldbeutilizedinfutureresearch.SupplychainresilienceisanimportantSCRMcon-struct,withseveraloverlappingmeanings.Thebroad-estoperationalizationsdeÞnesupplychainresilienceasanoutcomethatincludesboththereadinesstopre-ventaswellasrecoverfromadisruption(Golgeci&Ponomarov,2013;Park,2011;Voss&Williams,2013).Amorenarrowoperationalizationisadynamiccapabilityenactedinthefaceofasupplychaindisruption(Ambulkaretal.,2015;Brusset&Teller,2017;Kwak,Seo,&Mason,2018).Theempha-sisisquicklyreturningtonormaloramoredesirablestate.ThesemorenarrowdeÞnitionsseparatelyattri-butereadinessandpreventiontorobustness(Wieland&Wallenburg,2012).Thesedifferencesarenotminor.Giventhecentralityofthisconstructwithinthecon-textofSCRM,consensusofthedeÞnitionisnecessaryinordertoconsistentlyoperationalizesupplychainresilience.Onlythenwewillbeabletofullyunder-standtheconstructanditsrelationshipwithotherconstructs.WedidnotÞndalongitudinalstudythatmetoursamplecriteria.Thisisanimportantgap,becauseaquickresponsetimeisimportantinreducingtheimpactofasupplychaindisruption(Bode&Macdon-ald,2017;Wagner&Bode,2009).Actualresponsetimewasnotmeasured,butperceptionsofresponsetimeweremeasuredwithaLikertscaleof1(slow)to5(fast)(BodeandMacdonald,2017).Moreobjectivemeasuresoftimewouldenableunbiasedcomparisons.Also,utilizingalongitudinalmethodologytounder-standhowSCRMevolvesovertimemighthelpÞrmsimproveSCRM.WedidnotÞndastudythatcapturedmorethanasnapshotoftime.ResearchhasshownthatÞrmsfrequentlyinitiateSCRMafterexperiencingadisruptiveevent(Bodeetal.,2011),butweknowlittleabouthowthatinitialexperienceimpactsSCRMinthelongterm.FutureworkshouldexaminehowÞrmslearnandadaptSCRMinresponsetosupplychaindisruptions.REFERENCESAmbulkar,S.,Blackhurst,J.,&Grawe,S.(2015).FirmÕsresiliencetosupplychaindisruptions:Scaledevelopmentandempiricalexamination.JournalofOperationsManagement,33,111–122.AonRiskSolutions(2017).Globalriskmanagementsurvey.London,England.Barratt,M.(2004).Unveilingenablersandinhibitorsofcollaborativeplanning.TheInternationalJournalofLogisticsManagement,15,73–90.Blackhurst,J.,Dunn,K.S.,&Craighead,C.W.(2011).Anempiricallyderivedframeworkofglo-balsupplyresiliency.JournalofBusinessLogistics,32,374–391.Blackhurst,J.V.,Scheibe,K.P.,&Johnson,D.J.(2008).Supplierriskassessmentandmonitoringfortheautomotiveindustry.InternationalJournalofPhysicalDistribution&LogisticsManagement,38,143–165.Bode,C.,H€ubner,D.,&Wagner,S.M.(2014).ManagingÞnanciallydistressedsuppliers:Anexploratorystudy.JournalofSupplyChainManage-ment,50,24–43.Volume56,Number3JournalofSupplyChainManagement78
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PamManhart(Ph.D.IowaStateUniversity)Dr.ManhartÕsresearchfocusisunderstandingthegapbetweenstrategyandimplementationofsupplychainriskmanagement,particularlyorganizationalbehavioranddecision-makingimpactonresilience.Dr.Man-hartÕsnextprojectisorganizationallearningfromdis-ruption.JamesK.Summers(Ph.DFloridaStateUniversity)Dr.Summers,interestsincludeteamadaptability,socialinßuence,stigma,andmeta-analysis.JenniferBlackhurst(Ph.D.UniversityofIowa)Dr.BlackhurstÕsresearchinterestsincludesupplychainriskanddisruptionmanagement.APPENDIXAPAPERSUSEDINMETA-ANALYSISAuthorPublicationSampleSizeMethodLevelofAnalysisGlobeClusterTheoryAmbulkaretal.(2015)1199032BodeandMacdonald(2017)1438030,2,36Brandon-Jonesetal.(2015)12640206Brandon-Jonesetal.(2014)12640204BrussetandTeller(2017)11710335Cantoretal.(2014)12171107Chaudhuri,BoerandTaran(2018)13420208ChowdhuryandQuaddus(2017)12960315Ellingeretal.(2015)23260321G€olgeciandPonomarov(2013)21141325Habermannetal.(2015)110803010Kernetal.(2012)1162030Kwaketal.(2018)11740324LeeandRha(2016)23160324LiuandLee(2018)11610314Mandal(2017)22070324MerschmannandThonemann(2011)1850329Park(2011)31630324,9Riley(2013)320603212Shao(2013)2221032Su(2011)31470329Viswanathan(2011)315303213VossandWilliams(2013)13380323WielandandWallenburg(2012)1268030WielandandWallenburg(2013)12700303,4,15ZsidisinandWagner(2010)129602,32Publication:1-TopjournallistoutlinedbyMackelprangandNair(2010);2-ABSAcademicJournalGuidePeer-ReviewedJournal;3-DissertationMethod:0-Field/Survey;1-vignettesurveymixLevelofanalysis:1-individual;2-unit;3-ÞrmGlobe:0-Anglo;1-ConfucianAsia;2-GermanicEurope;3-LatinEuropeTheory:1-Knowledge-BasedView;2-TechnologyAcceptanceModel;3-NormalAccidentTheory;4-ResourceBasedView;5-DynamicCapabilityTheory;6-InformationProcessingTheory;7-RegulatoryFocusTheory;8-AgencyTheory;9-ContingencyTheory;10-ClusterTheory;11-ConvergenceTheory;12-HighReliabilityTheory;13-TheoryofPlannedBehavior;14-StrategicChoiceTheory;15-ResourceDependencyTheoryVolume56,Number3JournalofSupplyChainManagement84
APPENDIXBDEFINITIONSOFCONSTRUCTSANDAGGREGATEDITEMSHigherandLower-levelConstructsDeÞnitionRepresentativeMeasures1.SupplychainriskmanagementÒTheidentiÞcation,assessment,treatment,andmonitoringofsupplychainrisks,withtheaidoftheinternalimplementationoftools,techniquesandstrategiesandofexternalcoordinationandcollaborationwithsupplychainmemberssoastoreducevulnerabilityandensurecontinuitycoupledwithproÞtability,leadingtocompetitiveadvantageÓ(Fan&Stevenson,2018,p.7).Cantoretal.(2014);Ellingeretal.(2015)Disruptionimpact(reversecoded)Immediateandlong-termdetrimentalconsequencestooperationsandperformanceoftheaffectedÞrmduetosupplychaindisruption(Blackhurst,Dunn,&Craighead,2011).Ambulkaretal.(2015);BodeandMacdonald(2017)Disruptionoccurrence(reversecoded)Thefrequencyofsupplychaindisruptions(Zsidisin&Wagner,2010).Brandon-Jonesetal.(2015)ResilienceÒTheadaptivecapabilityofthesupplychaintoprepareforunexpectedevents,respondtodisruptions,andrecoverfromthembymaintainingcontinuityofoperationsatthedesiredlevelofconnectednessandcontroloverstructureandfunctionÓ(Ponomarov&Holcomb,2009,p.131).Ambulkaretal.(2015);ChowdhuryandQuaddus(2017)RobustnessÒTheabilityofthesupplychaintomaintainitsfunctiondespiteinternalorexternaldisruptionsÓ(Brandon-Jonesetal.,2014,p.58).WielandandWallenburg(2012);Brandon-Jonesetal.(2014)2.BufferingStrategiestogainstabilitybyestablishingsafeguardswhichminimizeaÞrmÕsexposuretodisturbances(Bodeetal.,2011;Mishraetal.,2016).AllfromaggregateditemsAlternativesTheabilityofaÞrmtoquicklyandeffectivelyinnovate,reconÞgure,realign,andreorganizethesupplychaininresponsetoexternaluncertainties,therebyallowingtheÞrmtoprovidesolutionsforcustomerneedsandasuperiorcompetitiveposition(Ambulkaretal.,2015;Lee,Lee,&Schniederjans,2011;Swafford,Ghosh,&Murthy,2006).Includesmeasuresofsupplychainagility,supplychainßexibility,andsupplychainreconÞguration.LeeandRha(2016);Kwaketal.(2018)IndependentTheabilitytoadapttouncertaintiesthroughself-sufÞcientproductionsitespossessingdedicatedresourceswhichspecializeinproductsandtechnologiesenablingversatilityofproductionvolumeandmix(Flynn&Flynn,1999;Skipper&Hanna,2009).Includesmeasuresofmanufacturingßexibilityandcustomerresponsiveness.BrussetandTeller(2017);Chaudhurietal.(2018)ProtectiveIncreasedresourcesandinternalstructurestosecureandinsulatetheÞrmfromexternaluncertaintieswhichcannotbeeliminated(Fennell&Alexander,1987;ZsidisinandWagner(2010);Ambulkaretal.(2015)(continued)July2020AMeta-AnalyticReviewofSCRM85
APPENDIXB(continued)HigherandLower-levelConstructsDeÞnitionRepresentativeMeasuresMeznar&Nigh,1995;Voss&Williams,2013).Includesmeasuresofriskmanagementinfrastructure,security,andslackresources.3.BridgingStrategiestomanageuncertaintybycreatinglinkageswithsupplychainnetworkpartnerstoincreaseinßuenceoverthem(Bodeetal.,2011;Mishraetal.,2016).AllfromaggregateditemsCooperationAstrategicsetofmethodsandtoolsusedtoalign,coordinate,andmanageinterdependencebetweenorganizations,people,andprocessesthatinteracttoexecutesupplychainobjectives(Mentzeretal.,2001;Xu&Beamon,2006).Includesmeasuresofcollaborationandsharedvision.Park(2011);WielandandWallenburg(2013)InformationsharingAstrategicsetofactivities,tools,andmethodsfortheexchangeofinformation,coordinationoffunctions,andalignmentofprocessestofacilitatethesynchronizedßowofgoodsandservicesbetweensupplychainnetworkpartnersandsharerisksandrewards(Ellingeretal.,2015;Mackelprangetal.,2014).Includesmeasuresofdemandmanagement,externalcapabilities,internalandexternalintegration,ITconnectivity,knowledgemanagement,andvisibility.WielandandWallenburg(2013);Ellingeretal.(2015)JointactivitiesStrategicallyworkingtogetherwithsupplychainnetworkpartnerstoplan,solveproblems,andmakedecisionsincludingperformanceevaluation,supplierdevelopment,continuousimprovementprojects,newproductdevelopment,andriskmanagementmechanisms(Mentzeretal.,2001;Spekman,Salmond,&Lambe,1997;Stank,Keller,&Daugherty,2001;Taran,Boer,&Lindgren,2015).Cantoretal.(2014);BodeandMacdonald(2017)MonitoringMethodsandmeasuresscanningtheenvironmenttodetectandassessriskandsensechanges,therebyincreasingthelikelihoodofnoticingearlywarningsignalsandformaquickerresponse(Bode&Macdonald,2017).Kernetal.(2012);BodeandMacdonald(2017)4.FirmperformanceThesuccessfulexecutionoraccomplishmentofworkcomprehensivelyoperationalizedwithmarket,operations,andaccountingcriteria(Golicic&Smith,2013).VossandWilliams(2013);LeeandRha(2016)CompetitiveadvantageAuniquepositionachievedrelativetothecompetitioninregardtosuperiorefÞciency,effectiveness,differentiation,andreputation(Hofer&Schendel,1978;Kwaketal.,2018).Kwaketal.(2018)CostperformanceAconditionofmaximumoutputprovidedbyworkerefÞciency,qualitycontrol,andwastereduction(Chowdhury&Quaddus,2017;F€are&Lovell,1978).ChowdhuryandQuaddus(2017)FinancialperformanceProÞtanalyzedthroughtheinternalrateofreturnonassets(ROA)andreturnoninvestment(ROI)(Cantoretal.,2014;Tan,2002).Cantoretal.,(2014)(continued)Volume56,Number3JournalofSupplyChainManagement86
APPENDIXB(continued)HigherandLower-levelConstructsDeÞnitionRepresentativeMeasuresMarketperformanceAnassessmentofaÞrmÕsabilitytocompeteinthemarketplacebytheirproportionofsalesintheindustryserved(Buzzell,Gale,&Sultan,1975).Cantoretal.(2014);ChowdhuryandQuaddus(2017)July2020AMeta-AnalyticReviewofSCRM87
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