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03/17/15 03/17/15 RESEARCH IN RESEARCH IN INFORMATION INFORMATION SYSTEMS SYSTEMS MANAGEMENT MANAGEMENT (IMS 603) (IMS 603)

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  • *RESEARCH IN INFORMATION SYSTEMS MANAGEMENT(IMS 603)

  • *Why Do Research?Research provides you with the knowledge and skills needed for the fast-paced decision-making environment

  • *Types of Research StudiesReportingDescriptiveExplanatoryPredictive

  • *Styles of ResearchApplied Research Pure Research/Basic Research Business Research

  • *What is Good Research?Purpose clearly defined

    Research process detailed

    Research design thoroughly plannedHigh ethical standards appliedLimitations frankly revealed

  • *What is Good Research (cont.)Adequate analysis for decision-makers needs

    Findings presented unambiguously

    Research design thoroughly plannedConclusions justifiedLimitations frankly revealed

  • *The Research ProcessOBSERVATIONBroad Area of Research InterestPROBLEM DEFINITIONResearch problem delineatedPRELIMINARY DATA GATHERINGInterviews & Literature reviewTHEORETICAL FRAMEWORKVariables clearly identifiedGENERATION OF HYPOTHESESDATA COLLECTION, ANALYSIS & INTERPRETATIONDEDUCTIONHypotheses substantiated? Research Questions answered?

  • *The Research StagesFraming your ResearchDesigning your ResearchReporting your Research

  • *Framing your ResearchWhat is your Research Problem?Why is it Important?How is your Research related to the present body of Knowledge?What are your Research Questions?What are various Concepts involved in your Research and how are they interrelated ?What are their Hypothesized Relationships?

  • *Designing your ResearchWhat Research Design to use? What Data to Collect?Where to Collect your Data From?How to Analyze your Data?- Survey vs Experiments- Measurement- Sampling Design- Data Collection Techniques- Data AnalysisHow to Collect your required Data?

  • *Final Steps in Research Data analysis

    Reporting the results - Executive summaryOverview of the researchFindings, Implementation strategies for the recommendationsTechnical appendix

  • *Problem StatementExisting problem that requires solutionSpecific areas in the organisation requiring improvementEg. Complaint of harrassment by senior officersE.g When policy about harassment exist but genuine complaint still occurTheoretical or conceptual issue that needs tightening upEg: What is meant by harrassmentResearch questions that basic researcher needs to answer empiricallyE.g: Impact of harrassment on performance

  • *Literature ReviewPurpose: Gather related information of research areasWhy?Avoid reinventing the wheelWe do not missed out important variablesProblem statement can be stated precisely and accuratelyTestability and replicability of findingsClearer idea of what are the important variables

  • *Research Question HierarchyManagement DilemmaMeasurement QuestionsInvestigative QuestionsResearch QuestionsManagement Questions

  • *Examples of Problem StatementsTo what extent the organizational structure and type of information system implemented explain the effectiveness of managerial decision-making? To what extent the SSB has enhances the motivation level of civil servants? Does leadership style influence the number of turnover?

  • *Theoretical FrameworkA conceptual model that depict how YOU relate all the important variables identified in your study. Helps you generate and test the relationships to enhances your understanding of the dynamics of the problem. Consists of variables and relationships between the variables.

  • *Example of a Theoretical FrameworkIndependent variablesDependent Variable

  • *Example of a Theoretical FrameworkAir traffic violationsCommunication between cockpit crewCommunication between cockpit and air traffic towerDecentralizationCrew trainingIndependent variablesDependent VariableIntervening Variable

  • *Example of a Theoretical FrameworkIndependent variablesDependent VariableModerator Variable

  • *Hypothesis GenerationAn hypothesis is a relationship that is assumed based upon logic, between two or more variables in the form that is testable. Format 1: DifferencesTesting and validating an assumed hypothesis can leads to problem solution. Format 2: If-then

  • *Examples of HypothesesIf communication among crew is good then the number of air traffic violation will be reducedGood training among crew members will reduced nervousness and subsequently reduces the number of air traffic violations. If the communication among crew members is good then the number of air traffic violations will be reduced provided they had sufficient training.

  • *Research DesignPROBLEM STATEMENTTime Horizon

    Cross-sectionalLongitudinalDATA ANALYSISFeel for dataGoodness of dataTesting

  • *What data to collect? Issue of measurement: Measurement must be valid and reliable Source:LiteratureSelf-develop

  • *Measurement

    Development of science is nothing but the development of measurement Whenever you can, count Everything that countsshould be counted

  • *MeasurementsEmpirical research often implies measurementsQuality of information depends on the measurement processMeasurement Defined: The mapping of some propertiesRules for assigning numbers to empirical propertiesRules: specify the procedure according to which numbers are to be assigned to objects

  • *Working DefinitionsMeasurement is a process through which the kind or intensity of something is determined: i.e. measurement is the process of linking abstract concepts to empirical indicants.Dimensionality refers to the number of different qualities inherent in a theoretical concept.A concept is a general idea referring to a characteristic of an individual, group, or a nation.

  • *Working DefinitionsExample: The Theoretical Concept: Social StatusDimensions: Occupational Prestige, Ethnicity, Popularity, Educational Prestige, Financial Resources, and so on.

  • *How are Variables Measured?Objective precise measurementSubjective nebulous & abstract; e.g. attitude, beliefs, involvement, satisfactionConcept of ThirstProcess of reducing abstract concept to measurable items is called Operationalization

  • *OperationalizationConceptOperational DefinitionDimensionsA generalized idea about a class of objects, attributes, occurrences, or processes e.g. sex, loyaltyGives meaning to a concept by specifying the activities or operations necessary to measure itElementsBroad characteristics to ensure coverage or scope of the conceptSpecific items about the identified measurement, which are easily measured

  • *Operationalizing: LearningLearningUnderstandingRetentionApplicationAnswer questions correctlyGive appropriate examplesRecall material after some lapseSolve problems applying concepts understood and recalledIntegrate with other relevant materialeeeeeddd

  • *Operationalizing: Motivation

  • *Operational definition is NOTCorrelate Antecedents ConsequencesReasons of the concept

  • *ScalesA tool or mechanism by which individuals are distinguished on how they differ from one anotherE.g. how do we distinguish individual A from B in terms of learning?Also refers to level of measurement

  • *Levels Of Measurements

    Empirical

    Scale

    Basic

    Operations

    Measures of

    Typical use

    Averages

    Nominal

    Determination of equality

    Classification

    Male-Female

    Occupations

    Mode

    Ordinal

    Determination of greater or less

    Ranking

    Preference

    Attitude

    Median

    Interval

    Determination of equality of intervals

    Index numbers

    Temperature

    Mean

    Ratio

    Determination of equality of ratios

    Sales

    Unit produced

    No. of customers

    Mean

    Geometric

  • *Nominal ScaleClassificatory or Categoricale.g. Sex Male/Female Colour Mutually exclusive & collectively exhaustive

  • *Ordinal ScaleCategorize and ranke.g. Preference in job attributes Please rank from 1 most important to 5 least important the following attributes:

    Interacting with othersUsing multiple skillsCompleting a task from beginning to endServing othersWork independently

  • *Interval ScaleAllows for measurement of distance between two points on the scalee.g. Preference in job attributes Using a scale of 1 (strongly disagree), 2 (disagree), 3 (neither agree nor disagree), 4 (agree) and 5 (strongly agree), please indicate the extent of your agreement by circling the appropriate number.

    The following are very important to meInteracting with others12345Using multiple skills12345Complete a task from beginning to end12345Serving others12345Working independently12345

  • *Ratio ScaleHas absolute zero; thus allowing for not only differences but also proportions in the differencese.g. Number of years in the organization

  • *Properties of the 4 Scales

  • *Scaling MethodsRating ScalesDichotomous ScaleCategory ScaleLikert scaleNumerical ScaleSemantic Differential ScaleItemized rating scaleGraphic rating scaleRanking ScalesPaired ComparisonForced ChoiceComparative Scale

  • *Examples: Rating ScaleLikert

    My work is very interestingStrongly agreeAgreeNeither agree nor disagreeDisagreeStrongly disagree

  • *Examples: Rating Scale

  • *Examples: Rating Scale

  • *Examples: Ranking ScaleForced Choice Rank your preferences among the following magazines, which you would like to subscribe to, 1 being the most preferred choice and 4 being the least preferred:Asiaweek__Economist__Fortune __Newsweek__

  • *Examples: Ranking ScaleComparative Scale In a volatile financial environment, compared to stocks, how wise or useful is it to invest in bonds? Please circle the appropriate response.

    More usefulAbout the sameLess useful12345

  • *Goodness of Measures

  • *Goodness of MeasuresGOODNESS OF DATAReliability (Accuracy)Validity (Actuality)StabilityConsistency Test-retestParallel formInteritem consistencySplit-halfLogical (content)Criterion related Congruent (construct)FacePredictiveConcurrent Convergent Discriminant

  • *Reliability and Validity

  • *ReliabilityObserved scores may reflect true scores, but it may reflect other factors as well:stable characteristics: two people having the same opinion may circle different responsestransients personal factors such as moodsituational factors, time pressure, time variations in administration and mechanical factorsReliability: Stability and consistencyStability over time, conditions, state of respondentsConsistency Homogeneity of times; items can measure the construct independently

  • *Reliability of Measures

  • *ValidityMultiple indicators: - often used to capture a given construct e.g. attitude; to cover the domain of the constructrobust - reduce random errorCronbach alpha - measures intercorrelation between indicators - they should be positively correlated but not perfectly correlatedConstruct ValidityFace validityConvergent validity (Correlation to assess it)Divergent validity

  • *Validity

  • *Data Source: Sampling Two Central Questions Do we sample or census? If sample:How to identify Who/what to include in the sample? - sampling designHow many to include in the sample? - sample size

  • *What is a Good Sample?Representative of the PopulationEstimates from sample are accurateEstimates from sample are precise

  • *Steps in Sampling DesignWhat is the relevant population?

    What are the parameters of interest?

    What is the sampling frame? What size sample is needed? What is the type of sample? How much will it cost?

  • *Types of Sampling Design

  • *Choosing a Sampling DesignIs REPRESENTATIVENESS critical?Area samples

  • *Sample Size: FactorsHomogeneity of sampling unitsConfidence levelPrecisionAnalytical ProcedureCost, Time and Personnel

  • *Roscoes Rule of ThumbLarger than 30 and less than 500 appropriate for most research

    A minimum of 30 for each sub samplesMultivariate research: At least 10 times the number of variablesSimple Experiments with tight controls - samples as small as 10 to 20

  • *Types of Primary Data Collection Method

  • *Personal InterviewMajor concerns:Non-responseResponse errorsNon-responseCall-back, prior introduction, specific timesResponse BiasInterview variations (situations, interviewer)Question structuring & sequence (protocol)Method of administration (socially accepted)Respondent error (intentional and unintentional)

  • *The InterviewIntroductionEstablishes rapportGather DataProbing (brief assertion of understanding, expectant pause, repeating the question, repeating the answer, neutral comment, question clarification)Recording the Interview

  • *Self-Administered SurveyTypeIntercept StudyMail surveyDisadvantagesLarge non-response errorSuperficial dataImproving Response RateReduced length; survey sponsorship, return envelope, return postage, personalization, anonymity, size color and reproduction, deadline dates, cover letters

  • *Data Analysis The StagesInterpretationPreanalyticalData EditingVariable DevelopmentData CodingError CheckData AnalysisFeel for DataGoodness of MeasuresInferential: Testing & Relationships

  • *Data Analysis - Types

    Purpose of StudyExploratory; Test of Differences; Establishing Relationships

  • *The Right Technique?

    Research QuestionConcern for Central Tendency; Comparing groups; Relationships

  • *The Right Technique?What is the purpose of the analysis?What is the level of measurement?How many variables are involved?

  • *Descriptive AnalysisPurpose: To describe the distribution of the variables of interest

  • *Test of DifferencesPurpose: To evaluate the differences between 2 or more groups with respect to a variable of interest

  • *Test of DifferencesMore than 2 group?Are they independent?Are they independent?Nominal: McNemarOrdinal: Wilcoxon Signed RankContinuous:-Paired t-testNoNoYesNominal: 2 testOrdinal: Kruskal-Wallis ANOVAContinuous: 1-way ANOVANominal: 2 - testOrdinal: Friedman 2-way ANOVAContinuous: Factorial 2-way ANOVA

  • *RelationshipPurpose: To establish relationship between variables

  • *Dependence RelationshipsHow many dependent variables?Scale of DependentCanonical CorrelationScale of IndependentScale of DependentScale of IndependentMultivariate ANOVA

  • *Contents of a Research ProposalA statement of the research problem

  • *Final WordsGood Luck in Your Research and Remember the Good Research begins with an Inquisitive Mind