Management Research Methodology: Integration of Principles, Methods and Techniques (For VTU)

Cover
About the Authors
Preface
Brief Contents
Contents
Part A: Scientific Method in Management Research
	Chapter 1: Scientific Method
		Introduction
			Defining Research
			Scientific Enquiry
		Scientific Method
			Formal Science and Empirical Science
			Logic of Scientific Method
			Hypothetico deductive Method
			Models
			Scientific Attitude
		Issues of Management Research
			Use of Scientific Method
			Alternative Perspectives of Management Research
		Summary
		Suggested Readings
		Questions and Exercises
	Chapter 2: Overview of Research in Management
		Scientific Research in Management
		Research Problem Identification
		Research Problem Definition
			Generation of Hypotheses
			Formulation of Research Problems
		Research Design
			Classification of Designs
			Issues of Research Design
		Research Design Process
			Selection of the Type of Research
			Measurement and Measurement Techniques
			Selection of Sample
			Selection of Data Collection Procedures
			Selection of Methods of Analysis
		Decisional Research with Mathematical Models
		Some Philosphic Issues of Management Research
			Paradigms
			Consultative Approach to Management Research
		Errors in Research
		Summary
		Annexure 2.1
		Suggested Readings
		Questions and Exercises
Part B: Research Problem
	Chapter 3: Problem Solving
		General Problem Solving
			What is a Problem?
			Types of Problems
			Problem Solving Process
		Logical Approach
		Soft System Approach
		Creative Approach
			Thinking Process
			Creative Thinking
			Creative Efforts in Research
			Barriers to Creativity
			Creative Problem Solving Process
		Development of Creativity
		Group Problem Solving Techniques for Idea Generation
			Introduction
			Brainstorming
			Delphi Method
		Summary
		Annexure 3.1—An Illustration of a Case of Application of SSM
		Suggested Readings
		Questions and Exercises
	Chapter 4: Formulation of Research Problems
		Introduction
		Approaches to Management Research Problem
			Management Problem is Posed to the Researcher
			Investigation of an Idea by an Experienced Researcher
			Pilot Study
			Initiatiation of a Novice/Student to Research
		Exploration for Problem Identification
			Literature Survey
			System Study
			Errors of Problem Identification in Research
		Hypothesis Generation
			Introduction
			Variables
			Characteristics of a Good Hypothesis
			Origins of a Hypothesis
			Process of Hypothesis Generation
			Hypothesis Generation Using Qualitative Methods
		Formulation of The Problem
			Model Building Context
			Decision Maker and His Objectives
			Environment
			Alternative Courses of Action
			Scenarios and Structural Modelling
			Interpretive Structural Modelling (ISM)
			Formulation of Effectiveness Function
		Summary
		Annexure 4.1—An Example of Taxonomy
		Annexure 4.2—An Example for Meta Analysis
		Annexure 4.3—An Illustrative Example of Theoretical Framework
		Annexure 4.4—Examples of Hypothesis Generation
		Annexure 4.5—System Study and Problem Formulation–Allocation of Assembly Manpower (Karthikeyan 1986)
		Annexure 4.6
		Suggested Readings
		Questions and Exercises
	Chapter 5: Research Proposal
		Research Proposal
		Purpose of a Research Proposal
		Types of Research Proposals
		Development of the Proposals
			Formatting the Research Proposal
			Contents of the Research Proposal
		Requirements of the Sponsoring Agent
		Evaluation of Research Proposals
		Some Implicit Considerations
		Summary
		Annexure 5.1—Sample (Real) Research Proposal (Krishnaswamy et al, 1997)
		Suggested Readings
		Questions and Exercises
Part C: Research Design—Types of Research
	Chapter 6: Experimental Research
		Experimental Research
		Principles of Experiment
		Laboratory Experiments
			Difficulties of Performing Laboratory Experiments
			Design of Laboratory Experiments
			Execution of Laboratory Experiments
			Strength and Weakness of Experiments
			Errors in Experiments
		Experimental Designs
			Basis of Experimental Design
			Basic Designs
			Statistical Designs
			Field Experiments
		Quasi-Experimental Designs
			Quasi-Experimental Designs
			A Comparison of The Two Quasi-Experimental Designs
			Use of Quasi-Experimental Designs
		Action Research
			Defining Action Research
			Process of Action Research
			Comparison of Action Research with Experiments
			Scientific Merits of Action Research
		Validity and Reliability of Experiments and Quasi-Experiments
			Concept of Validity and Reliability
			Validity in Experimentation and Quasi-Experimentation
			Validity of Quasi-Experimentation
		Sources of Invalidity of Experiments and Quasi-experiments
		Choice of Experimental Design
		Analysis Procedures Used in Experimental Design
		Summary
		Annexure 6.1—A Laboratory Experiment
		Annexure 6.2—A Randomised Two-Group Experiment
		Annexure 6.3—Solomon Four-Group Design
		Annexure 6.4—Factorial Design
		Annexure 6.5—Randomised Block Design
		Annexure 6.6—An Action Research Case
		Suggested Readings
		Questions and Exercises
	Chapter 7: Ex Post Facto Research
		Introduction
		Ex Post Facto Research by Objective
			Exploratory Research
			Historical Research
			Descriptive Research
		Ex Post Facto Research by Nature of Study
			Field Studies
			Survey Research
		Qualitative Research Methods
			Case Study Research
			Participant Observation
			Ethnographic Methods
			Critical Incident Technique
			Repertory Grid Technique (RGT)
			Some Additional Qualitative Research Methods
			Triangulation
			Analysis Procedures for Qualitative Data
		Evaluation Research
			Outcome Evaluation
			Formative Evaluation Research
		Summary
		Annexure 7.1—An Example of Explorative Research
		Annexure 7.2—An Example of Descriptive Research
		Annexure 7.3—An Example of Field Research
		Annexure 7.4—An Example for Survey Research
		Annexure 7.5—An Example for Case Study Research
		Annexure 7.6—Example of Cognitive Mapping
		Suggested Readings
		Questions and Exercises
	Chapter 8: Modelling Research I—Mathematical Modelling
		Introduction
		Mathematical Models
			What is a Model?
			Development of Models
			Principles of Modeling
			Patterns of Model Building
			Use of Analogy in Modelling
			Models as Approximations
			Data Consideration in Modelling
			Models as Heuristic Instruments
			Solutions of Models
			Testing of Models
		Composite Modelling Methods
		Summary
		Annexure 8.1(a)—Illustration of Modelling A
		Annexure 8.1(b)—Illustration of Modelling B
		Annexure 8.2(a)—Illustration for Composite Methodology A
		Annexure 8.2(b)—Illustration of Composite Methodology B
		Suggested Readings
		Questions and Exercises
	Chapter 9: Modelling Research II—Heuristics and Simulation
		Heuristic Optimisation
			Definition of Heuristics
			Why Use Heuristics?
			Heuristic Methods
			Heuristics Problem-Solving Approaches
			Meta-Heuristics
			Choice of Heuristic Methods
			Evaluation of Heuristics
			Evaluation of Heuristics in Empirical Analysis
			Sources of Problem Instances
			Performance Measures/Measure of Effectiveness
			Examples of Heuristic Optimisation
			Advantages and Limitations of Heuristic Methods
		Simulation Modelling
			Meaning of Simulation
			What is Simulation?
			Classification of Simulation Models
			The Process of Simulation
			Key Steps in Simulation Experiments
			Validation of Simulation Models/Experiments
		Summary
		Annexure 9.1—Demonstration of Constructive Heuristics and SA (Simulated Annealing)
		Annexure 9.2—Illustration of Heuristics
		Annexure 9.3—Illustration for Empirical Evaluation of Greedy Heuristics
		Annexure 9.4—Illustration for Monte Carlo Simulation
		Annexure 9.5—Illustration for Simulation from Actual Research
		Suggested Readings
		Questions and Exercises
Part D: Research Design for Data Acquisition
	Chapter 10: Measurement Design
		Introduction
		Primary Types of Measurement Scales
			Nominal Scales
			Ordinal Scales
			Interval Scales
			Ratio Scales
		Errors in Measurement
		Validity and Reliability in Measurement
			Validity of Measurement
			Reliability in Measurement
		Types of Scaling (Scale Classification)
			Response Methods
			Quantitative Judgment Methods
		Scale Construction Techniques
			Judgment Methods
			Factor Scales
		Summary
		Annexure 10.1—Illustrative Example: Content Validity
		Annexure 10.2—Illustrative Example: Concurrent and External Validity
		Annexure 10.3—Illustrative Example: Construct Validity
		Annexure 10.4—Illustrative Example: Reliability in Measurement
		Suggested Readings
		Questions and Exercises
	Chapter 11: Sample Design
		Introduction
			Sampling Process
		Non-Probability Sampling
		Probability Sampling
			Simple Random Sampling
			Stratified Random Sampling
			Cluster Sampling
			Systematic Random Sampling
			Area Sampling
		Determination of Sample Size
			Required Size/Cell
			Use of Statistical Models
			Bayesian Method for Determination of Sample Size
		Illustrative Examples of Sample Size Determination
		Summary
		Suggested Readings
		Questions and Exercises
Part E: Acquisition and Preparation of Research Data
	Chapter 12: Data Collection Procedures
		Introduction
		Sources of Secondary Data
			Internal Sources
			External Sources
			Computer Search for Secondary Data
		Primary Data Collection Methods
			Observation
			Evaluation of Observations as Data Collection
Procedures
			Questionnaires
			Interviews
			Projective Techniques
		Non-Sampling Errors
			Non-Observation Errors
			Observation errors
		Validity and Reliability of Data Collection Procedures
			Validity and Reliability of Interviews
			Validity and Reliability of Observation
			Validity and Reliability of Questionnaires
		Summary
		Suggested Readings
		Questions and Exercises
	Chapter 13: Data Preparation and Preliminary Data Analysis
		Introduction
		Data Preparation
			Editing Data
			Coding Data
			Transcription of Data (Transcribing)
			New Variable/Functional Combination/Splitting Form
			Data Description
			Summarising Statistics
		Exploratory Data Analysis
			Stem and Leaf Display
			Box Plots
			Data Mining
		Statistical Estimation
		Content Analysis
			Some Recent Developments
			Example of Content Analysis
		Summary
		Suggested Readings
		Questions and Exercises
Part F: Data Analysis and Reporting
	Chapter 14: Hypothesis Testing—Univariate Analysis
		Introduction
		Logic of Hypothesis Testing
			Null Hypothesis
			Research Hypothesis
			Errors in Hypothesis Testing
		Identification of an Appropriate Test for Hypothesis Testing
		Parametric Tests
			Z-Test
			t-Test
			F-Test for Analysis of Variance
		Non-Parametric Tests
			Chi-Square Test
			McNemar Test
			Kolmogorov-Smirnov Test
			Kruskal-Wallis Test (For Ranked Data)
			Friedman’s Two-Way ANOVA
			Kendal’s Coefficient of Concordance (W)
		Summary
		Suggested Readings
		Questions and Exercises
	Chapter 15: Bivariate Analysis and Hypothesis Testing
		Introduction
		Correlation
		Simple Linear Regression Model
			Fitting of a Simple Linear Regression Model
		Non-parametric Methods of Association
			Spearman’s Rank Correlation Coefficient (rs )
			Kendall’s Tau
			Contingency Coefficient
		Summary
		Suggested Readings
		Questions and Exercises
	Chapter 16: Analysis of Experimental Data
		Introduction
		Analysis of Single Factor Experiments
		Single Factor Randomised Blocks Design
			RBD Model
		Latin Square Design
			Latin Square Design Model
		Completely Randomised 2 × 2 Factorial Design
			2 × 2 Factorial Design Model
		Summary
		Suggested Readings
		Questions and Exercises
	Chapter 17: Multivariate Analysis of Data—Dependence Analysis
		Multiple Regression
			Introduction
			Assumptions and the Procedure
			Verification
			Problems Encountered While Using Multiple Regression
			Overcoming Multicolinearity
			Variable Selection and Model Building
			An Overview of Multiple Regression Analysis Procedure
			Variants of Regression Analysis
			Applications
		Discriminant Analysis
			Introduction
			Assumptions
			The Method
			Testing Statistical Significance of Discriminant Functions
		Canonical Correlation Analysis
			Introduction
			The Model
			Assumptions
			The Method
			Significance Test
			Interpretation
		Path Analysis
		Other Methods
			Conjoint Analysis
			Automatic Interaction Detection Analysis
		Summary
		Suggested Readings
		Questions and Exercises
	Chapter 18: Multivariate Analysis of Data II—Interdependence Analysis
		Introduction
		Factor Analysis
			Introduction
			Geometric Representation of Factor Analysis
			The Model
			Assumptions
			Methods of Factor Analysis
		Multidimensional Scaling (MDS)
			Introduction
			Fundamentals of MDS
			Process of MDS
			Factor Analysis versus Multidimensional Scaling
		Cluster Analysis
			Introduction
			Extraction
			Methods of Clustering
			Reliability
		Summary
		Annexure 18.1—Confirmatory Factor Analysis to Test Research Hypothesis
		Suggested Readings
		Questions and Exercises
	Chapter 19: Report Writing
		Introduction
		Pre-writing Considerations
			Dissertations/Theses
			Style and Composition of the Report
			Principles of Thesis Writing
		Format of Reporting
			Format of Dissertations
			Format of Research Reports
			Format of Publication in a Research Journal
			Reporting of Qualitative Research
		Briefing
		Rules for Typing or Word Processing
		Summary
		Suggested Readings
		Questions and Exercises
Appendix—Selected Statistical Tables
Model Question Papers
Solution to Model Question Paper-I
Solution to Model Question Paper-II