McGraw-Hill/Irwin?2003TheMcGraw-HillCompanies,Inc.,AllRightsReserved.PartOne

INTRODUCTIONTO

BUSINESSRESEARCHChapterOne

RESEARCHINBUSINESSWhatisBusinessResearch?AsystematicInquirywhoseobjectiveistoprovideinformationtosolvemanagerialproblems.WhyStudyResearch?Researchprovidesyouwiththeknowledgeandskillsneededforthefast-paceddecision-makingenvironmentWhyManagersneedBetterInformationGlobalanddomesticcompetitionismorevigorousOrganizationsareincreasinglypracticingdatamining

anddatawarehousingTheValueofAcquiringResearchSkillsTogathermoreinformationbeforeselectingacourseofactionTodoahigh-levelresearchstudyTounderstandresearchdesignToevaluateandresolveacurrentmanagementdilemmaToestablishacareerasaresearchspecialistTypesofStudiesUsedtodoResearchReportingDescriptiveExplanatoryPredictiveDifferentStylesofResearchAppliedResearchPureResearch/BasicResearchWhatisGoodResearch?FollowingthestandardsofthescientificmethodPurposeclearlydefinedResearchprocessdetailedResearchdesignthoroughlyplannedLimitationsfranklyrevealedHighethicalstandardsappliedWhatisGoodResearch?(cont.)Followingthestandardsofthescientificmethod(cont.)Adequateanalysisfordecision-maker’sneedsFindingspresentedunambiguouslyConclusionsjustifiedResearcher’sexperiencereflectedTheManager-ResearcherRelationshipManager’sobligationsSpecifyproblemsProvideadequatebackgroundinformationAccesstocompanyinformationgatekeepersResearcher’sobligationsDevelopacreativeresearchdesignProvideanswerstoimportantbusinessquestionsManager-ResearcherConflictsManagement’slimitedexposuretoresearchManagerseesresearcherasthreattopersonalstatusResearcherhastoconsidercorporatecultureandpoliticalsituationsResearcher’sisolationfrommanagersWhenResearchShouldbeAvoidedWheninformationcannotbeappliedtoacriticalmanagerialdecisionWhenmanagerialdecisioninvolveslittleriskWhenmanagementhasinsufficientresourcestoconductastudyWhenthecostofthestudyoutweighsthelevelofriskofthedecisionMcGraw-Hill/Irwin?2003TheMcGraw-HillCompanies,Inc.,AllRightsReserved.PartOne

INTRODUCTIONTO

BUSINESSRESEARCHChapterTwo

APPLYINGSCIENTIFICTHINKINGTO

MANAGEMENTPROBLEMSSourcesofKnowledgeEmpiricistsattempttodescribe,explain,andmakepredictionsthroughobservationRationalistsbelieveallknowledgecanbededucedfromknownlawsorbasictruthsofnatureAuthoritiesserveasimportantsourcesofknowledge,butshouldbejudgedonintegrityandwillingnesstopresentabalancedcaseTheEssentialTenetsofScienceDirectobservationofphenomenaClearlydefinedvariables,methods,andproceduresEmpiricallytestablehypothesesAbilitytoruleoutrivalhypothesesStatisticaljustificationofconclusionsSelf-correctingprocessWaystoCommunicateExpositiondescriptivestatementsthatmerelystateanddonotgivereasonArgumentallowsustoexplain,interpret,defend,challenge,andexploremeaningImportantArgumentsinResearchDeductionisaformofinferencethatpurportstobeconclusiveInductiondrawsconclusionsfromoneormoreparticularfacts TheBuildingBlocksofTheoryConceptsConstructsDefinitionsVariablesPropositionsandHypothesesTheoriesModelsUnderstandingConceptsAconceptisabundleofmeaningsorcharacteristicsassociatedwithcertainevents,objects,conditions,situations,andbehaviorsConceptshavebeendevelopedovertimethroughsharedusageUnderstandingConceptsThesuccessofresearchhingeson:howclearlyweconceptualizehowwellothersunderstandtheconceptsweuseWhatisaConstruct?Aconstructisanimageorideaspecificallyinventedforagivenresearchand/ortheory-buildingpurpose.TypesofVariablesIndependentDependentModeratingExtraneousInterveningTheRoleoftheHypothesisGuidesthedirectionofthestudyIdentifiesfactsthatarerelevantSuggestswhichformofresearchdesignisappropriateProvidesaframeworkfororganizingtheconclusionsthatresultWhatisaGoodHypothesis?Agoodhypothesisshouldfulfillthreeconditions:MustbeadequateforitspurposeMustbetestableMustbebetterthanitsrivalsTheValueofaTheoryNarrowstherangeoffactsweneedtostudySuggestswhichresearchapproacheswillyieldthegreatestmeaningSuggestsadataclassificationsystemSummarizeswhatisknownaboutanobjectofstudyPredictsfurtherfactsthatshouldbefoundMcGraw-Hill/Irwin?2003TheMcGraw-HillCompanies,Inc.,AllRightsReserved.PartOne

INTRODUCTIONTO

BUSINESSRESEARCHChapterThree

THERESEARCHPROCESSTheManagement-Research

QuestionHierarchyManagementDilemmaMeasurementQuestionsInvestigativeQuestionsResearchQuestionsManagementQuestionsManagementDecision123456WorkingwiththeHierarchy

ManagementDilemmaThesymptomofanactualproblemNotdifficulttoidentifyadilemma,howeverchoosingonetofocusonmaybedifficult

WorkingwiththeHierarchy

ManagementQuestionCategoriesChoiceofpurposesorobjectiveGenerationandevaluationofsolutionsTroubleshootingorcontrolsituationWorkingwiththeHierarchy

FinetunetheresearchquestionExamineconceptsandconstructsBreakresearchquestionsintospecificsecond-and-third-levelquestionsVerifyhypotheseswithqualitytestsDeterminewhatevidenceanswersthevariousquestionsandhypothesisSetthescopeofyourstudyWorkingwiththeHierarchy

InvestigativeQuestionsQuestionstheresearchermustanswertosatisfactorilyarriveataconclusionabouttheresearchquestionWorkingwiththeHierarchyMeasurementQuestionsThequestionsweactuallyaskorextractfromrespondentsOtherProcessesintheHierarchyExplorationRecentdevelopmentsPredictionsbyinformedfiguresabouttheprospectsofthetechnologyIdentificationofthoseinvolvedintheareaAccountsofsuccessfulventuresandfailuresbyothersinthefieldResearchProcessProblemsTheFavoredTechniqueSyndromeCompanyDatabaseStrip-MiningUnresearchableQuestionsIll-DefinedManagementProblemsPoliticallyMotivatedResearchDesigningtheStudySelectaresearchdesignfromthelargevarietyofmethods,techniques,procedures,protocols,andsamplingplansResourceAllocation&BudgetsGuidestoplanabudgetProjectplanningDatagatheringAnalysis,interpretation,andreportingTypesofbudgetingRule-of-thumbDepartmentalorfunctionalareaTaskEvaluationMethodsExPostFactoEvaluationPriorEvaluationOptionAnalysisDecisionTheoryContentsofaResearchProposalStatementoftheresearchquestionBriefdescriptionofresearchmethodologyPilotTestingDatacollectionDatapreparationDataanalysisandinterpretationResearchreportingDataCollectionCharacterizedbyabstractnessverifiabilityelusivenessclosenesstothephenomenonTypesSecondarydataPrimarydataFinalStepsinResearchDataanalysisReportingtheresultsExecutivesummaryOverviewoftheresearchImplementationstrategiesfortherecommendationsTechnicalappendixMcGraw-Hill/Irwin?2003TheMcGraw-HillCompanies,Inc.,AllRightsReserved.PartOne

INTRODUCTIONTO

BUSINESSRESEARCHChapterFour

THERESEARCHPROPOSALPurposeoftheResearchProposalTopresentthequestiontoberesearchedanditsimportanceTodiscusstheresearcheffortsofotherswhohaveworkedonrelatedquestionsTosuggestthedatanecessaryforsolvingthequestionTheResearchSponsorAllresearchhasasponsorinoneformoranother:Inacorporatesetting,managementsponsorsresearchInanacademicenvironment,thestudentisresponsibletotheclassinstructorWhataretheBenefitsoftheProposaltoaResearcher?Allowstheresearchertoplanandreviewtheproject’sstepsServesasaguidethroughouttheinvestigationForcestimeandbudgetestimatesTypesofResearchProposalsInternalExternal

ProposalComplexity3levelsofcomplexity:Theexploratorystudy

isusedforthemostsimpleproposalsThesmall-scalestudy

ismorecomplexandcommoninbusinessThelarge-scaleprofessionalstudy

isthemostcomplex,costingmillionsofdollarsHowtoStructuretheResearchProposal?CreateproposalmodulesPuttogethervariousmodulestotailoryourproposaltotheintendedaudienceModulesinaResearchProposalExecutiveSummaryProblemStatementResearchObjectivesLiteratureReviewImportanceoftheStudyResearchDesignDataAnalysisNatureandFormofResultsQualificationsofResearcherBudgetScheduleFacilitiesandSpecialResourcesProjectManagementBibliographyAppendicesWhattoincludeintheAppendices?Aglossaryofconcepts,constructs,anddefinitionsSamplesofthemeasurementinstrumentOthermaterialsthatreinforcethebodyoftheproposalEvaluatingtheResearchProposalProposalmustbeneatlywritteninappropriatewritingstyleMajortopicsshouldbeeasilyfoundandlogicallyorganizedProposalmustmeetspecificguidelinessetbythesponsorTechnicalwritingstylemustbeclearlyunderstoodandexplainedMcGraw-Hill/Irwin?2003TheMcGraw-HillCompanies,Inc.,AllRightsReserved.PartOne

INTRODUCTIONTO

BUSINESSRESEARCHChapterFive

ETHICSIN

BUSINESSRESEARCHWhatareResearchEthics?EthicsarenormsorstandardsofbehaviorthatguidemoralchoicesaboutourbehaviorandourrelationshipswithothersThegoalistoensurethatnooneisharmedorsuffersadverseconsequencesfromresearchactivitiesEthicalTreatmentofParticipantsBegindatacollectionbyexplainingtotheparticipantthebenefitsexpectedfromtheresearchExplaintotheparticipantsthattheirrightsandwell-beingwillbeadequatelyprotected,andsayhowthiswillbedoneBecertainthatinterviewersobtaintheinformedconsentoftheparticipantDeceptionTheparticipantistoldonlypartofthetruthorwhenthetruthisfullycompromisedTopreventbiasingtheparticipantsbeforethesurveyorexperimentToprotecttheconfidentialityofathirdpartyIssuesRelatedtoProtectingParticipantsInformedconsentDebriefingRighttoPrivacy/ConfidentialityDataCollectioninCyberspaceEthicalIssuesrelatedtotheClientSponsornon-disclosurePurposenon-disclosureFindingsnon-disclosureRighttoqualityresearchEthicsRelatedtoSponsorSometimesresearcherswillbeaskedbysponsorstoparticipateinunethicalbehavior.Toavoidcoercionbysponsortheresearchershould:EducatesponsortothepurposeofresearchExplainresearcher’sroleExplainhowdistortionofthetruthleadstofutureproblemsIfnecessary,terminaterelationshipwithsponsorEthicalIssuesrelatedto

ResearchersandTeamMembersSafetyEthicalbehaviorofassistantsProtectionofanonymityTheDesignofResearchPart2DonaldCooperPamelaSchindlerChapter6BusinessResearchMethodsChapter6DesignStrategiesWhatisResearchDesign?AplanforselectingthesourcesandtypesofinformationusedtoanswerresearchquestionsAframeworkforspecifyingtherelationshipsamongthestudyvariablesAblueprintthatoutlineseachprocedurefromthehypothesistotheanalysisSlide6-1ClassificationsofDesignsExploratorystudyisusuallytodevelophypothesesorquestionsforfurtherresearchFormalstudyistotestthehypothesesoranswertheresearchquestionsposedSlide6-2MethodsofDataCollectionMonitoring,whichincludesobservational

studiesInterrogation/communicationstudySlide6-3PowertoProduceEffects

Slide6-4Inanexperiment,theresearcherattemptstocontroland/ormanipulatethevariablesinthestudyInanexpostfactodesign,theresearcherhasnocontroloverthevariables;theycanonlyreportwhathashappenedPurposeoftheStudyDescriptivetriestoexplainrelationshipsamongvariables

CausalstudyishowonevariableproduceschangesinanotherSlide6-5TheTimeDimensionCross-sectionalstudiesarecarriedoutonceandrepresentasnapshotofonepointintimeLongitudinalstudiesarerepeatedoveranextendedperiodSlide6-6TheTopicalScopeStatisticalstudiesattempttocaptureapopulation’scharacteristicsbymakinginferencesfromasample’scharacteristicsCasestudiesplacemoreemphasisonafullcontextualanalysisoffewereventsorconditionsandtheirinterrelationsSlide6-7TheResearchEnvironmentFieldconditionsLaboratoryconditionsSimulationsSlide6-8ASubjects’PerceptionsUsefulnessofadesignmaybereducedwhenpeopleinthestudyperceivethatresearchisbeingconductedSubjects’perceptionsinfluencetheoutcomesoftheresearchSlide6-9WhydoExploratoryStudies?ExplorationisparticularlyusefulwhenresearcherslackaclearideaoftheproblemsSlide6-10DataCollectionTechniquesQualitativetechniquesSecondarydataFocusgroups

Two-stagedesignSlide6-11Causation

TheessentialelementofcausationisA“produces〞B orA“forces〞BtooccurSlide6-12CausalStudyRelationshipsSymmetricalReciprocalAsymmetricalSlide6-13AsymmetricalRelationshipsStimulus-ResponseProperty-DispositionDisposition-BehaviorProperty-BehaviorSlide6-14AchievingtheIdealExperimentalDesign

Control RandomAssignment Matching Randomization ManipulationandcontrolofvariablesSlide6-15DonaldCooperPamelaSchindlerChapter7BusinessResearchMethodsChapter7SamplingDesignSelectionofElements

Population PopulationElementSampling

CensusSlide7-1WhatisaGoodSample?Accurate:absenceofbiasPreciseestimate:samplingerrorSlide7-2TypesofSamplingDesigns

ProbabilityNonprobabilitySlide7-3StepsinSamplingDesignWhatistherelevantpopulation?Whataretheparametersofinterest?Whatisthesamplingframe?Whatisthetypeofsample?Whatsizesampleisneeded?Howmuchwillitcost?Slide7-4ConceptstohelpunderstandProbabilitySampling

Standarderror ConfidenceintervalCentrallimittheoremSlide7-5ProbabilitySamplingDesigns

SimplerandomSystematicStratifiedProportionateDisproportionateClusterDoubleSlide7-6DesigningClusterSamplesHowhomogeneousaretheclusters?Shallweseekequalorunequalclusters?Howlargeaclustershallwetake?Shallweuseasingle-stageormultistagecluster?Howlargeasampleisneeded?Slide7-7Slide7-8NonprobabilitySamplingReasonstouseProceduresatisfactorilymeetsthesamplingobjectivesLowerCostLimitedTimeNotasmuchhumanerrorasselectingacompletelyrandomsampleTotallistpopulationnotavailableNonprobabilitySampling

ConvenienceSamplingPurposiveSamplingJudgmentSamplingQuotaSamplingSnowballSamplingSlide7-9DonaldCooperPamelaSchindlerChapter8BusinessResearchMethodsChapter8MeasurementMeasurementSelectingobservableempiricaleventsUsingnumbersorsymbolstorepresentaspectsoftheeventsApplyingamappingruletoconnecttheobservationtothesymbolSlide8-1WhatisMeasured?

Objects: Thingsofordinaryexperience Somethingsnotconcrete Properties:characteristicsofobjectsSlide8-2CharacteristicsofDataClassificationOrderDistance(intervalbetweennumbers)Originofnumberseries7-4Slide8-3DataTypes

Order Interval OriginNominal none

none noneOrdinal yes unequal noneInterval yes equalor none unequalRatio yes equal zeroSlide8-4SourcesofMeasurementDifferencesRespondentSituationalfactorsMeasurerorresearcherDatacollectioninstrumentSlide8-5Validity

ContentValidityCriterion-RelatedValidityPredictiveConcurrentConstructValiditySlide8-6Reliability

StabilityTest-retestEquivalenceParallelformsInternalConsistencySplit-halfKR20Cronbach’salphaSlide8-7PracticalityEconomyConvenienceInterpretability7-9Slide8-8DonaldCooperPamelaSchindlerChapter9BusinessResearchMethodsChapter9MeasurementScalesWhatisScaling?AssigningnumberstoindicantsofthepropertiesofobjectsSlide9-1TypesofResponseScalesSlide9-2RatingScalesRankingScalesCategorizationTypesofRatingScalesSimplecategoryMultiplechoice,singleresponseMultiplechoice,multipleresponseLikertscaleSemanticdifferentialNumericalMultipleratingFixedsumStapelGraphicratingSlide9-3RatingScaleErrorstoAvoidLeniency NegativeLeniency PositiveLeniencyCentralTendencyHaloEffectSlide9-4TypesofRankingScalesPaired-comparisonForcedRankingComparativeSlide9-5DimensionsofaScaleUnidimensionalMultidimensionalSlide9-6ScaleDesignTechniquesArbitraryConsensusItemAnalysisCumulativeFactorSlide9-7DonaldCooperPamelaSchindlerChapter10BusinessResearchMethodsChapter10SourcesandCollectionofDataExploratoryResearchSlide10-1ExpandunderstandingofmanagementdilemmaExpandunderstandingofresearchquestionIdentifyplausibleinvestigativequestionsLevelsofInformationSlide10-2PrimarysourcesSecondarysourcesTertiarysourcesTypesofInformationSourcesIndexesandBibliographiesDictionariesEncyclopediasHandbooksDirectoriesSlide10-3SecondarySourcesbyTypeIndexesandBibliographiestofindorlocatebooksorarticlestofindauthors,topicstouseinonlinesearchesSlide10-4Dictionariestoidentifyjargonofanindustry--usedforonlinesearchestoidentifybell-weathereventsinanindustrytoidentifyknowledgeablepeopletointerviewtoidentifyorganizationsofinfluenceSecondarySourcesbyTypeSlide10-5EncyclopediasToidentifyhistoricalorbackgroundinformationTofindcriticaldateswithinanindustryTofindeventsofsignificancetotheindustry,companySecondarySourcesbyTypeSlide10-6HandbooksTofindfactsrelevanttotopicToidentifyinfluentialindividualsthroughsourcecitationsSecondarySourcesbyTypeSlide10-7DirectoriesToidentifyinfluentialpeopleandorganizationstofindaddresses,e-mail,othercontactinfoonthesepeopleandorganizationsSecondarySourcesbyTypeSlide10-8EvaluatingInformationSourcesPurposeScopeAuthorityAudienceFormatSlide10-9EvaluatingSourcesPurposewhattheauthorisattemptingtoaccomplishidentifyhiddenagenda(s)identifydirectionofbiasSeekbothbiasedandunbiasedsourcesSlide10-10EvaluatingSourcesScopeIdentifydatesofinclusionandexclusionIdentifysubjectsofinclusionandexclusionSlide10-11EvaluatingSourcesAuthorityIdentifybackgroundofauthorCredentials:educational,professionalExperience:duration,setting,levelIdentifythelevelofscholarshipincontentfootnotes,endnotesSlide10-12EvaluatingSourcesAudienceIdentifyknowledgelevelandbackgroundIdentifyorientationandbiasSeekbiasedandunbiasedsourcesSlide10-13EvaluatingSourcesFormatOrderofcontentVersatilityofuseIndexed?Searchable?Downloadable?Slide10-14SearchingDatabasesSelectanappropriatedatabaseABI/InformBusinessInfoSuiteBusinessSourceDowJonesInteractiveNexis-LexisUniverseSlide10-15SearchingDatabasesSelectanappropriatedatabaseConstructasearchquerySlide10-16SearchingDatabasesConstructasearchqueryBooleanOperatorsOR-forplurals,synonymsspellingvariationswomanORwomenAND-narrowsyoursearchadvertisingANDbibliographyNOT/ANDNOT-eliminatestermsawardNOTtrophyADJ-orderkeytermswithinyoursearchassistedADJlivingSlide10-17SearchingDatabasesConstructasearchqueryBooleanOperators?or*-totruncateatermnur*fornurse,nursing“X〞forphrasesearching“advertisingcampaigns〞LimitersdatessourcetypelanguageSlide10-18SearchingDatabasesSelectanappropriatedatabaseConstructasearchqueryReviewandevaluatesearchresultsRelevancyQuantityTimelinessSlide10-19SearchingDatabasesModifythesearchqueryCheckbibliographynewkeywords,otherauthorsLinkdirectlyAdaptoriginalsearchqueryCreatenewsearchquerywithnewkeywordsSearchforotherworksbysameauthor(s)Slide10-20SearchingDatabasesModifythesearchqueryDocumentfindingsPrintordownloadsearchfindingsDownloadfull-textsourcePrintfull-textsourceSlide10-21SearchingDatabasesModifythesearchqueryDocumentfindingsRetrieveorrequestarticlesSearchonlinecatalogInterlibraryloanInterlibrarydeliverySlide10-22WebSearchesDefineyourquestionSelectSearchEngineorDirectoryDannySullivan’sSearchEngineWatchGregNotess〞SearchEngineShowdownSlide10-23WebSearchesDetermineSearchOptionsandProtocolConstructsearchqueryReviewsearchresultsSlide10-24WebSearchesModifysearchqueryandsearchagainSearchusingadifferentsearchengineDocumentyourfindingssearchfindingsfulltextsourcesSupplementwebresultsfromothersourcesSlide10-25SpecificWebSearchesKnown-ItemWhoWhereWhatSlide10-26GovernmentSourcesGovernmentorganizationsLaws,regulations,courtdecisionsGovernmentstatisticsSlide10-27MiningInternalSourcesDatawarehouseDatamartDataminingPatterndiscoveryPredictingtrendsandbehaviorsSlide10-28DataMiningTechniques

DataVisualizationDimensionsMeasurementsHierarchiesClusteringNeuralNetworksTreeModelsClassificationSlide10-29DataMiningTechniques(cont.)

Estimation Association Market-BasketAnalysisSequenceBasedAnalysisFuzzyLogicGeneticAlgorithmsFractal-BasedTransformationSlide10-30DataMiningProcessSampleExploreModifyModelAssessSlide10-31DonaldCooperPamelaSchindlerChapter11BusinessResearchMethodsChapter11SurveyMethods:CommunicatingwithRespondentsCommunicationApproachImpactstheResearchProcessCreationandselectionofmeasurementquestionsSamplingissues,drivecontactandcallbackproceduresInstrumentdesign,whichincorporatesattemptstoreduceerrorandcreaterespondent-screeningproceduresDatacollectionprocesses,whichcreatetheneedforfollow-upproceduresandpossibleinterviewertrainingSlide11-1PersonalInterviewRequirementsforsuccessAvailabilityoftheneededinformationfromtherespondentAnunderstandingbytherespondentofhisorherroleAdequatemotivationbytherespondenttocooperateSlide11-2PersonalInterviewToIncreaseRespondent’sReceptivenesstheymustbelievetheexperiencewillbepleasantandsatisfyingthinkansweringthesurveyisanimportantandworthwhileuseoftheirtimehaveanymentalreservationssatisfiedSlide11-3TheInterviewIntroductionEstablishagoodrelationshipGatherthedataProbingRecordtheinterviewSlide11-4ProbingStylesAbriefassertionofunderstandingandinterestAnexpectantpauseRepeatingthequestionRepeatingtherespondent’sreplyAneutralquestionorcommentQuestionclarificationSlide11-5InterviewProblems

NonresponseerrorResponseerrorInterviewererrorCostSlide11-6TelephoneInterviewTypesComputer-assistedtelephoneinterviewingComputer-administeredtelephonesurveyProblemsNoncontactrateRefusalrateSlide11-7Self-AdministeredSurveysTypesMailsurveyComputer-delivered InterceptstudiesDisadvantagesLargenonresponseerrorCannotobtaindetailedorlargeamountsofinformationSlide11-8ConcurrentTechniquestoImproveMailResponseReduceLengthSurveySponsorshipReturnEnvelopesPostagePersonalizationAnonymitySize,Color,andReproductionMoneyIncentivesDeadlineDatesCoverLettersSlide11-9OutsourcingSurveyServicesResearchFirmsProvideCentralized-locationinterviewingFocusgroupfacilitiesTrainedstaffwithexperienceData-processingandstatisticalanalysiscapabilitiesAccesstopoint-of-saledataPanelsSlide11-10DonaldCooperPamelaSchindlerChapter12BusinessResearchMethodsChapter12InstrumentsforRespondentCommunicationInstrumentDesignProcessPhase1:DevelopingtheinstrumentdesignstrategyPhase2:ConstructingandrefiningthemeasurementquestionsPhase3:DraftingandrefiningtheinstrumentSlide12-1DevelopingtheInstrumentDesignStrategyManagement-ResearchQuestionHierarchy:Themanagementproblem/questionResearchquestion(s)InvestigativequestionsMeasurementquestionsSlide12-2StrategicConcernsofInstrumentDesignWhattypeofdataisneededtoanswerthemanagementquestion?Whatcommunicationapproachwillbeused?Shouldthequestionsbestructured,unstructured,orsomecombination?Shouldthequestionsbedisguisedorundisguised?Slide12-3WaystoInteractwiththeRespondentPersonalinterviewTelephoneMailComputerSlide12-4Slide12-5TypesofMeasurementQuestions?TargetClassificationAdministrativeAppropriateQuestionContentShouldthisquestionbeasked?Isthequestionofproperscopeandcoverage?Cantherespondentadequatelyanswerthisquestion,asasked?Willtherespondentwillinglyanswerthisquestion,asasked?Slide12-6HowtoTesta

Respondent’sAppropriatenessFilterquestionsScreenquestionsSlide12-7QuestionWordingCriteriaIsthequestionstatedintermsofasharedvocabulary?Doesthequestioncontainvocabularywithasinglemeaning?Doesthequestioncontainunsupportedassumptions?Isthequestioncorrectlypersonalized?Areadequatealternativespresentedwithinthequestion?Slide12-8WhatDictates

YourResponseStrategy?CharacteristicsofrespondentsNatureofthetopic(s)beingstudiedTypeofdataneededYouranalysisplanSlide12-9TypesofResponseQuestionsFree-responseDichotomousMultiple-choiceChecklistRatingRankingSlide12-10GuidelinestoRefiningtheInstrumentAwakentherespondent'sinterestUsebufferquestionsasaguidetorequestsensitiveinformationUsethefunnelapproachtomovetomorespecificquestionsSlide12-11ImprovingSurveyResultsPretestingisanestablishedpracticefordiscoveringerrorsandusefulfortrainingtheresearchteamSlide12-12DonaldCooperPamelaSchindlerChapter13BusinessResearchMethodsChapter13ObservationalStudiesObservationNonbehavioralobservationBehavioralobservationSlide13-1ObservationNonbehavioralobservationRecordanalysisPhysicalconditionanalysisProcessoractivityanalysisSlide13-2ObservationBehavioralobservationNonverbalanalysisLinguisticanalysisExtralinguisticanalysisSpatialanalysisSlide13-3AdvantagesoftheObservationalMethodCollecttheoriginaldataatthetimeitoccursSecureinformationthatparticipantswouldignorebecauseit’ssocom