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Malhotra,Gosain,andElSawy:LeveragingSEBIstoEnableAdaptiveSupplyChainPartnerships270
4.AnalysisandResults
4.1.MeasurementValidation
WeusedPLSGraph3.0fordataanalysis.PLShas
anadvantageoverotherstructuralmodeling(SEM)
methodologiesinthatitdoesnotrequiredistributions
benormalorknown(JoreskogandWold1982).Other
structuralestimationtechniqueslikeLISRELassume
multivariatenormaldistributionorWishartdistribu-
tion,butPLStakesanydistributionthatismani-
festthoughmeasurementandcalculatesthebestset
ofpredictiveweightsthroughaseriesofiterations.
AnotheradvantageofusingPLSisthatithasless
stringentsamplesizerequirements.Techniquessuch
asLISRELusechi-squareestimatesfor“goodness-of-
t”indicators.Unfortunately,chi-squareestimatesare
extremelysensitivetosamplesize.The tindicesin
PLSaredescriptivestatisticsandindicateonlythe
amountofvarianceaccountedforinthemodelbythe
speci edrelationships.
Ournextchoicewaswhethertheconstructswould
bemodeledasre ectiveorformative.Inmakingthis
choice,wefollowedtheguidelineslaidoutbyJarvis
etal.(2003).Constructsshouldbemodeledasfor-
mativeunderthefollowingconditions:(1)indicators
areviewedasthede ningcharacteristicofthecon-
struct,(2)changesintheindicatorscauseachange
intheconstruct(andnotviceversa),(3)indicators
donotneedtonecessarilycovary,(4)indicatorsare
notnecessarilyinterchangeable,and(5)indicatorscan
bedrawnfromdifferentnomologicalnetwork(Jarvis
etal.2003,Patnayakunietal.2006).Basedonthese
criteria,alltheconstructsinthisstudyweremod-
eledasformativeconstructs.Speci cally,weused
indexscoresofassociateditemstoestablishamea-
sureforeachformativeconstruct.Wehadtwochoices
tocomputetheindexscore—factorscoresormean
valueofitems.Although,formativeconstructsare
notrequiredtoexhibitinternalconsistency(Jarvis
etal.2003,Raietal.2006,Petteretal.2007),the
itemswerestronglycorrelated.Therefore,wechose
themeanvaluetocomputetheindex,whichwould
naturallycorrelatehighlywithfactorscoresorother
alternateweightingschemesfortheitems(Rozeboom
1979).Moreover,Hairetal.(1987)recommendthe
useofunitmeanscoresforreplicabilityandeaseof
rmationSystemsResearch18(3),pp.260–279,©2007INFORMSSimilarly,breadthofinformationexchange(CIE1),qualityofinformationexchange(CIE2),andprivi-legedinformationexchange(CIE3)weremodeledasformativeconstructs.CIEwasmodeledasaformativeconstructcomprisedofthreeindicators:CIE1,CIE2,andCIE3.Theindexscoresforthesethreeindicatorswerealsoderivedbasedontheunitmeansofassoci-ateditems(seeAppendixAforitems).Webeganourdataanalysisbyassessingthemea-surementpropertiesofconstructs.Weconductedapseudocon rmatoryfactoranalysis(asPLSdoesnotprovidecrossloadingofitemsonconstructsotherthanthosetheyarehypothesizedtoload)followingtheprocedureoutlinedbyKarahannaetal.(1999)andPatnayakunietal.(2006).Ameanfactorscoreforeachconstructwascomputedfromtheitemsthatwerehypothesizedtore ecttheconstruct.Thenalltheitemswerecorrelatedwitheachoftheconstructs.Anindicator’scorrelationwithitshypothesizedcon-structcanbeconstruedas“loading,”whileitscorre-lationwithotherconstructsis“cross-loading.”Eachoftheitemsexhibitsahighercorrelationwithitsownconstructthanotherconstructsprovidingevidencefordiscriminantvalidity(Table2).Tofurthertestfordis-criminantvalidityofourconstructs,weexaminedtheaveragevarianceextracted(AVE)foreachconstructandcompareditwithcorrelationsbetweenconstructs(FornellandLarcker1981).AscanbeseenfromTable2ItemConstructstoOwnConstructCorrelationvs.CorrelationswithOtherConstructItemAKCMASTDCIECNAdaptivecreationknowledgeAKC1AKC200.220.25AKC30.820.200.210.130.09AKC40.0.68.84780.290.350.190.230.320.030.070.160.050.18MutualadaptationMA1MA20.260.330.180.04MA30.4500.130.0.80.91810.360.370.190.010.100.33UsebusinessofstandardinterfaceselectronicSTD1STD20.160.40STD30.200.200.4100.210.210.280.0.85.93840.340.200.410.37CollaborativeexchangeinformationCIE1 CIE2 0.270.13CIE3 0.060.090.080.250.130.140.0600.360.0.91.69830.020.11CooperativenormCN1CN20.140.16CN30.180.180.100.240.060.210.330.420.1200.200.0.87.8689 Indexcomputedasmeanscoresofassociateditems.
supply chain management
Malhotra,Gosain,andElSawy:LeveragingSEBIstoEnableAdaptiveSupplyChainPartnershipsInformationSystemsResearch18(3),pp.260–279,©2007INFORMSTable3MeasurementPropertiesofConstructs
ConstructMean(SD)12345
1.Adaptivecreationknowledge 40 2798 0.77
2.Mutualadaptation 31 9193 0.330.84
ebusinessofstandardinterfaceselectronic 51 8662 0.210.420.87
4.Collaborativeexchangeinformation 51 0108 0.250.150.310.80
5.Cooperativenorm 41 6512 0.240.170.400.130.87
Note.SquarerootofAVEisshownalongthediagonal.
Table3,theAVEforeachconstructwashigherthantheconstructs’correlationwithotherconstructsasrequiredforvalidatingdiscriminantvalidity(Barclayetal.1995).Table3alsoprovidesthemeanandstan-darddeviationvaluesforallconstructs.