Business ResearchBusiness ResearchGerald L. BlakelyGerald L. Blakely

INTRODUCTIONINTRODUCTION

• Why do research?Why do research?

• Purposes of researchPurposes of research

• Ethics in researchEthics in research

• Ways of knowingWays of knowing

RESEARCH DESIGNSRESEARCH DESIGNS

• CorrelationalCorrelational

• QualitativeQualitative

• ExperimentalExperimental

• Quasi-experimentalQuasi-experimental

EXPERIMENTAL DESIGNSEXPERIMENTAL DESIGNS

• Pre-experimental designsPre-experimental designs

1. X O1. X O

2. O X O2. O X O

3. X O3. X O

OO

EXPERIMENTAL DESIGNS (cont.)EXPERIMENTAL DESIGNS (cont.)

• True experimental designsTrue experimental designs4. R O X O4. R O X O R O OR O O

5. R X O5. R X O R OR O

6. R O X O6. R O X O R R O O R X OR X O R O OR O O

EXPERIMENTAL DESIGNS (cont.)EXPERIMENTAL DESIGNS (cont.)

• Quasi-experimental designsQuasi-experimental designs

7. O O O X O O O Time series7. O O O X O O O Time series

8. O X O Non-equivalent control 8. O X O Non-equivalent control groupgroup

O OO O

9. O O O X O O O (X) O O O 9. O O O X O O O (X) O O O Withdrawal Withdrawal

CAUSAL INFERENCECAUSAL INFERENCE

• Temporal antecedenceTemporal antecedence

• CovariationCovariation

• Plausible alternatives ruled outPlausible alternatives ruled out– Reverse causationReverse causation– Reciprocal causationReciprocal causation– Spurious relationshipsSpurious relationships– ModeratorsModerators– MediatorsMediators

STUDY VALIDITY (Internal)STUDY VALIDITY (Internal)

• Selection of participantsSelection of participants• TestingTesting• Regression to the meanRegression to the mean• HistoryHistory• MaturationMaturation• MortalityMortality• Compensatory rivalryCompensatory rivalry• Resentful demoralizationResentful demoralization

PSYCHOMETRIC PROPERTIES PSYCHOMETRIC PROPERTIES OF MEASURES (RELIABILITY)OF MEASURES (RELIABILITY)

• Test re-testTest re-test

• Parallel formsParallel forms

• Inter-raterInter-rater

• Internal consistencyInternal consistency

PSYCHOMETRIC PROPERTIES PSYCHOMETRIC PROPERTIES OF MEASURES (VALIDITY)OF MEASURES (VALIDITY)

• FaceFace

• ContentContent

• ConstructConstruct

• Criterion relatedCriterion related– predictivepredictive– concurrentconcurrent

SCALE CONSTRUCTIONSCALE CONSTRUCTION

• Determine clearly what you want to Determine clearly what you want to measuremeasure

• Generate an item poolGenerate an item pool– RedundancyRedundancy– NumberNumber– Item characteristicsItem characteristics

ITEM CHARACTERISTICS ITEM CHARACTERISTICS (cont.)(cont.)

• item lengthitem length• reading levelreading level•double-barreleddouble-barreled• reverse scoredreverse scored• leading questionsleading questions•delicate/sensitivedelicate/sensitive• social desirabilitysocial desirability

SCALE FORMATSCALE FORMAT

• ThurstoneThurstone

• Semantic differentialSemantic differential

• Summated rating (Likert type)Summated rating (Likert type)

• GuttmanGuttman

• Rank orderRank order

QUESTIONNAIRE QUESTIONNAIRE CONSTRUCTIONCONSTRUCTION

• White spaceWhite space

• IDID

• Physical formPhysical form

• LanguageLanguage

• LengthLength

QUESTIONNAIRE QUESTIONNAIRE CONSTRUCTION (cont.)CONSTRUCTION (cont.)

• SimplicitySimplicity

• VariationVariation

• Page formatPage format

OPTIMIZING RESPONSE OPTIMIZING RESPONSE RATESRATES

• No junk mailNo junk mail

• Return envelopeReturn envelope

• Follow upFollow up

• RelevanceRelevance

• Cover letterCover letter

SAMPLING: BASIC SAMPLING: BASIC DEFINITIONSDEFINITIONS

• A good sample is one where every member A good sample is one where every member of the population has an equal probability of the population has an equal probability of being selected for the sampleof being selected for the sample

• Sampling error - difference between Sampling error - difference between sample and entire populationsample and entire population

• Sampling biases - non-random errors due Sampling biases - non-random errors due to inadequate data or clerical mistakesto inadequate data or clerical mistakes

• Non-sampling biases - errors that occur Non-sampling biases - errors that occur even if we sampled the entire populationeven if we sampled the entire population

SAMPLING: SAMPLE DESIGNSAMPLING: SAMPLE DESIGN

• Probability samplesProbability samples

– Simple random samplesSimple random samples

– Systematic random samplesSystematic random samples

– Stratified samplesStratified samples

– Cluster samplesCluster samples

SAMPLING: SAMPLE DESIGN SAMPLING: SAMPLE DESIGN (cont.)(cont.)

• Nonprobability samplesNonprobability samples

– PurposivePurposive

– QuotaQuota

– ChunkChunk

– VolunteerVolunteer

– ConvenienceConvenience