Table Of Content

i IBM SPSS Conjoint 21 Note: Beforeusingthisinformationandtheproductitsupports,readthegeneralinformation under Notices on p. 39. ThiseditionappliestoIBM®SPSS®Statistics21andtoallsubsequentreleasesandmodifications untilotherwise indicatedinneweditions. Adobeproductscreenshot(s)reprintedwithpermissionfromAdobeSystemsIncorporated. Microsoftproductscreenshot(s)reprintedwithpermissionfromMicrosoftCorporation. LicensedMaterials-PropertyofIBM ©CopyrightIBMCorporation1989,2012. U.S.GovernmentUsersRestrictedRights-Use,duplicationordisclosurerestrictedbyGSAADP Schedule Contract with IBMCorp. Preface IBM®SPSS®Statisticsisacomprehensivesystemforanalyzingdata. TheConjointoptional add-onmoduleprovidestheadditionalanalytictechniquesdescribedinthismanual. TheConjoint add-onmodulemustbeusedwiththeSPSSStatisticsCoresystemandiscompletelyintegrated into that system. About IBM Business Analytics IBMBusinessAnalyticssoftwaredeliverscomplete,consistentandaccurateinformationthat decision-makerstrusttoimprovebusinessperformance. Acomprehensiveportfolioofbusiness intelligence,predictiveanalytics,financialperformanceandstrategymanagement,andanalytic applicationsprovidesclear,immediateandactionableinsightsintocurrentperformanceandthe abilitytopredictfutureoutcomes. Combinedwithrichindustrysolutions,provenpracticesand professionalservices,organizationsofeverysizecandrivethehighestproductivity,confidently automatedecisionsanddeliverbetterresults. Aspartofthisportfolio,IBMSPSSPredictiveAnalyticssoftwarehelpsorganizationspredict futureeventsandproactivelyactuponthatinsighttodrivebetterbusinessoutcomes. Commercial, governmentandacademiccustomersworldwiderelyonIBMSPSStechnologyasacompetitive advantageinattracting,retainingandgrowingcustomers,whilereducingfraudandmitigating risk. ByincorporatingIBMSPSSsoftwareintotheirdailyoperations,organizationsbecome predictiveenterprises–abletodirectandautomatedecisionstomeetbusinessgoalsandachieve measurablecompetitiveadvantage. Forfurtherinformationortoreacharepresentativevisit http://www.ibm.com/spss. Technical support Technicalsupportisavailabletomaintenancecustomers. CustomersmaycontactTechnical Support for assistance in using IBM Corp. products or for installation help for one of the supportedhardwareenvironments. ToreachTechnicalSupport,seetheIBMCorp. website athttp://www.ibm.com/support. Bepreparedtoidentifyyourself,yourorganization,andyour supportagreementwhenrequestingassistance. Technical Support for Students If you’re a student using a student, academic or grad pack version of any IBM SPSS software product, please see our special online Solutions for Education (http://www.ibm.com/spss/rd/students/) pages for students. If you’re a student using a university-suppliedcopyoftheIBMSPSSsoftware, please contact theIBMSPSSproduct coordinator at your university. Customer Service Ifyouhaveanyquestionsconcerningyourshipmentoraccount,contactyourlocaloffice. Please haveyourserialnumberreadyforidentification. ©CopyrightIBMCorporation1989,2012. iii Training Seminars IBMCorp. providesbothpublicandonsitetrainingseminars. Allseminarsfeaturehands-on workshops. Seminarswillbeofferedinmajorcitiesonaregularbasis. Formoreinformationon theseseminars,gotohttp://www.ibm.com/software/analytics/spss/training. iv Contents 1 Introduction to Conjoint Analysis 1 TheFull-ProfileApproach. ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... 2 AnOrthogonalArray . ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... 2 TheExperimentalStimuli. ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... 2 CollectingandAnalyzingtheData ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... 2 Part I: User's Guide 2 Generating an Orthogonal Design 5 DefiningValuesforanOrthogonalDesign. ... ... ... ... ... ... ... ... ... ... ... ... ... ... 6 OrthogonalDesignOptions... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... 7 ORTHOPLANCommandAdditionalFeatures.. ... ... ... ... ... ... ... ... ... ... ... ... ... 8 3 Displaying a Design 9 DisplayDesignTitles.. ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... 10 PLANCARDSCommandAdditionalFeatures.. ... ... ... ... ... ... ... ... ... ... ... ... ... 10 4 Running a Conjoint Analysis 11 Requirements ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... 11 SpecifyingthePlanFileandtheDataFile. ... ... ... ... ... ... ... ... ... ... ... ... ... 12 SpecifyingHowDataWereRecorded ... ... ... ... ... ... ... ... ... ... ... ... ... ... 12 OptionalSubcommands .. ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... 13 Part II: Examples 5 Using Conjoint Analysis to Model Carpet-Cleaner Preference17 GeneratinganOrthogonalDesign. ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... 17 CreatingtheExperimentalStimuli:DisplayingtheDesign . ... ... ... ... ... ... ... ... ... ... 21 ©CopyrightIBMCorporation1989,2012. v RunningtheAnalysis . ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... 23 UtilityScores . ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... 25 Coefficients .. ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... 25 RelativeImportance.. ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... 26 Correlations .. ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... 27 Reversals. ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... 27 RunningSimulations.. ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... 28 PreferenceProbabilitiesofSimulations .. ... ... ... ... ... ... ... ... ... ... ... ... ... ... 28 Appendices A Sample Files 30 B Notices 39 Bibliography 42 Index 43 vi Chapter 1 Introduction to Conjoint Analysis Conjointanalysisisamarketresearchtoolfordevelopingeffectiveproductdesign. Usingconjoint analysis,theresearchercananswerquestionssuchas: Whatproductattributesareimportantor unimportanttotheconsumer? Whatlevelsofproductattributesarethemostorleastdesirablein theconsumer’smind? Whatisthemarketshareofpreferenceforleadingcompetitors’products versusourexistingorproposedproduct? Thevirtueofconjointanalysisisthatitaskstherespondenttomakechoicesinthesamefashion astheconsumerpresumablydoes—bytradingofffeatures,oneagainstanother. Forexample,supposethatyouwanttobookanairlineflight. Youhavethechoiceofsittingina crampedseatoraspaciousseat. Ifthisweretheonlyconsideration,yourchoicewouldbeclear. Youwouldprobablypreferaspaciousseat. Orsupposeyouhaveachoiceofticketprices: $225or $800. Onpricealone,takingnothingelseintoconsideration,thelowerpricewouldbepreferable. Finally,supposeyoucantakeeitheradirectflight,whichtakestwohours,oraflightwithone layover,whichtakesfivehours. Mostpeoplewouldchoosethedirectflight. Thedrawbacktotheaboveapproachisthatchoicealternativesarepresentedonsingleattributes alone,oneatatime. Conjointanalysispresentschoicealternativesbetweenproductsdefinedby setsofattributes. Thisisillustratedbythefollowingchoice: wouldyoupreferaflightthatis cramped,costs$225,andhasonelayover,oraflightthatisspacious,costs$800,andisdirect? If comfort,price,anddurationaretherelevantattributes,therearepotentiallyeightproducts: Product Comfort Price Duration 1 cramped $225 2hours 2 cramped $225 5hours 3 cramped $800 2hours 4 cramped $800 5hours 5 spacious $225 2hours 6 spacious $225 5hours 7 spacious $800 2hours 8 spacious $800 5hours Giventheabovealternatives,product4isprobablytheleastpreferred,whileproduct5isprobably themostpreferred. Thepreferencesofrespondentsfortheotherproductofferingsareimplicitly determinedbywhatisimportanttotherespondent. Usingconjointanalysis,youcandetermineboththerelativeimportanceofeachattributeas wellaswhichlevelsofeachattributearemostpreferred. Ifthemostpreferableproductisnot feasibleforsomereason,suchascost,youwouldknowthenextmostpreferredalternative. If youhaveotherinformationontherespondents,suchasbackgrounddemographics,youmightbe abletoidentifymarketsegmentsforwhichdistinctproductscanbepackaged. Forexample,the businesstravelerandthestudenttravelermighthavedifferentpreferencesthatcouldbemetby distinct product offerings. ©CopyrightIBMCorporation1989,2012. 1 2 Chapter 1 The Full-Profile Approach Conjointusesthefull-profile(alsoknownasfull-concept)approach,whererespondentsrank, order, orscore a set ofprofiles, orcards, accordingtopreference. Eachprofile describesa completeproductorserviceandconsistsofadifferentcombinationoffactorlevelsforallfactors (attributes) of interest. An Orthogonal Array Apotentialproblemwiththefull-profileapproachsoonbecomesobviousifmorethanafew factorsareinvolvedandeachfactorhasmorethanacoupleoflevels. Thetotalnumberofprofiles resultingfromallpossiblecombinationsofthelevelsbecomestoogreatforrespondentstorankor scoreinameaningfulway. Tosolvethisproblem,thefull-profileapproachuseswhatistermeda fractionalfactorialdesign,whichpresentsasuitablefractionofallpossiblecombinationsof thefactorlevels. Theresultingset,calledanorthogonalarray,isdesignedtocapturethemain effectsforeachfactorlevel. Interactionsbetweenlevelsofonefactorwithlevelsofanother factor are assumed to be negligible. TheGenerateOrthogonalDesignprocedureisusedtogenerateanorthogonalarrayandis typicallythestartingpointofaconjointanalysis. Italsoallowsyoutogeneratefactor-level combinations,knownasholdoutcases,whichareratedbythesubjectsbutarenotusedtobuild thepreferencemodel. Instead,theyareusedasacheckonthevalidityofthemodel. The Experimental Stimuli Eachsetoffactorlevelsinanorthogonaldesignrepresentsadifferentversionoftheproductunder studyandshouldbepresentedtothesubjectsintheformofanindividualproductprofile. This helpstherespondenttofocusononlytheoneproductcurrentlyunderevaluation. Thestimuli shouldbestandardizedbymakingsurethattheprofilesareallsimilarinphysicalappearance exceptforthedifferentcombinationsoffeatures. CreationoftheproductprofilesisfacilitatedwiththeDisplayDesignprocedure. Ittakesa designgeneratedbytheGenerateOrthogonalDesignprocedure, orenteredbytheuser, and producesasetofproductprofilesinaready-to-useformat. Collecting and Analyzing the Data Sincethereistypicallyagreatdealofbetween-subjectvariationinpreferences,muchofconjoint analysisfocusesonthesinglesubject. Togeneralizetheresults,arandomsampleofsubjectsfrom thetargetpopulationisselectedsothatgroupresultscanbeexamined. Thesizeofthesampleinconjointstudiesvariesgreatly. Inonereport(CattinandWittink, 1982),theauthorsstatethatthesamplesizeincommercialconjointstudiesusuallyrangesfrom 100to1,000,with300to550themosttypicalrange. Inanotherstudy(AkaahandKorgaonkar, 1988),itisfoundthatsmallersamplesizes(lessthan100)aretypical. Asalways,thesamplesize shouldbelargeenoughtoensurereliability. 3 IntroductiontoConjointAnalysis Oncethesampleischosen,theresearcheradministersthesetofprofiles,orcards,toeach respondent. TheConjointprocedureallowsforthreemethodsofdatarecording. Inthefirst method,subjectsareaskedtoassignapreferencescoretoeachprofile. Thistypeofmethodis typicalwhenaLikertscaleisusedorwhenthesubjectsareaskedtoassignanumberfrom1to 100toindicatepreference. Inthesecondmethod,subjectsareaskedtoassignaranktoeach profilerangingfrom1tothetotalnumberofprofiles. Inthethirdmethod,subjectsareaskedto sorttheprofilesintermsofpreference. Withthislastmethod,theresearcherrecordstheprofile numbersintheordergivenbyeachsubject. AnalysisofthedataisdonewiththeConjointprocedure(availableonlythroughcommand syntax)andresultsinautilityscore,calledapart-worth,foreachfactorlevel. Theseutility scores,analogoustoregressioncoefficients,provideaquantitativemeasureofthepreference foreachfactorlevel, withlargervaluescorrespondingtogreaterpreference. Part-worthsare expressedinacommonunit,allowingthemtobeaddedtogethertogivethetotalutility,oroverall preference,foranycombinationoffactorlevels. Thepart-worthsthenconstituteamodelfor predictingthepreferenceofanyproductprofile, includingprofiles,referredtoassimulation cases,thatwerenotactuallypresentedintheexperiment. Theinformationobtainedfromaconjointanalysiscanbeappliedtoawidevarietyofmarket researchquestions. Itcanbeusedtoinvestigateareassuchasproductdesign, marketshare, strategicadvertising,cost-benefitanalysis,andmarketsegmentation. Althoughthefocusofthismanualisonmarketresearchapplications,conjointanalysiscan beusefulinalmostanyscientificorbusinessfieldinwhichmeasuringpeople’sperceptions or judgments is important. Part I: User's Guide