Management Research Methodology

for ANNA Univeristy and VTU

Management Research Methodology

Author(s): K. N. Krishnaswamy, Appa Iyer Sivakumar, M. Mathirajan

Publisher: Pearson Education, Year: 2012

ISBN: 9788131767771

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


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

Management Research Methodology Table Of Contents

About the Authors
Brief Contents
Part A: Scientific Method in Management Research
Chapter 1: Scientific Method
Defining Research
Scientific Enquiry
Scientific Method
Formal Science and Empirical Science
Logic of Scientific Method
Hypothetico deductive Method
Scientific Attitude
Issues of Management Research
Use of Scientific Method
Alternative Perspectives of Management Research
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
Consultative Approach to Management Research
Errors in Research
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
Delphi Method
Annexure 3.1 An Illustration of a Case of Application of SSM (Krishnaswamy 1998)
Suggested Readings
Questions and Exercises
Chapter 4: Formulation of Research Problems
Approaches to Management Research Problem
Management Problem is Posed to the Researcher
Investigation of an Idea by an Experienced Researcher
Initiation of a Novice/Student to Research
Pilot Study
Exploration for Problem Identification
Literature Survey
System Study
Errors of Problem Identification in Research
Hypothesis Generation
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
Alternative Courses of Action
Scenarios and Structural Modelling
Interpretive Structural Modelling (ISM)
Formulation of Effectiveness Function
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
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
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
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
Analysis Procedures for Qualitative Data
Evaluation Research
Outcome Evaluation
Formative Evaluation Research
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
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
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
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
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
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
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
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
Suggested Readings
Questions and Exercises
Part E: Acquisition and Preparation of Research Data
Chapter 12: Data Collection Procedures
Sources of Secondary Data
Internal Sources
External Sources
Computer Search for Secondary Data
Primary Data Collection Methods
Evaluation of Observations as Data Collection Procedures
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
Suggested Readings
Questions and Exercises
Chapter 13: Data Preparation and Preliminary Data Analysis
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
Suggested Readings
Questions and Exercises
Part F: Data Analysis and Reporting
Chapter 14: Hypothesis Testing—Univariate Analysis
Logic of Hypothesis Testing
Null Hypothesis
Research Hypothesis
Errors in Hypothesis Testing
Identification of an Appropriate Test for Hypothesis Testing
Parametric Tests
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)
Suggested Readings
Questions and Exercises
Chapter 15: Bivariate Analysis and Hypothesis Testing
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
Suggested Readings
Questions and Exercises
Chapter 16: Analysis of Experimental Data
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
Suggested Readings
Questions and Exercises
Chapter 17: Multivariate Analysis of Data—Dependence Analysis
Multiple Regression
Assumptions and the Procedure
Problems Encountered While Using Multiple Regression
Overcoming Multicolinearity
Variable Selection and Model Building
An Overview of Multiple Regression Analysis Procedure
Variants of Regression Analysis
Discriminant Analysis
The Method
Testing Statistical Significance of Discriminant Functions
Canonical Correlation Analysis
The Model
The Method
Significance Test
Path Analysis
Other Methods
Conjoint Analysis
Automatic Interaction Detection Analysis
Suggested Readings
Questions and Exercises
Chapter 18: Multivariate Analysis of Data II—Interdependence Analysis
Factor Analysis
Geometric Representation of Factor Analysis
The Model
Methods of Factor Analysis
Multidimensional Scaling (MDS)
Fundamentals of MDS
Process of MDS
Factor Analysis versus Multidimensional Scaling
Cluster Analysis
Methods of Clustering
Annexure 18.1—Confirmatory Factor Analysis to Test Research Hypothesis
Suggested Readings
Questions and Exercises
Chapter 19: Report Writing
Pre-writing Considerations
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
Rules for Typing or Word Processing
Suggested Readings
Questions and Exercises
Appendix—Selected Statistical
Model Question Papers
Model Questions Paper-II
Model Question Paper-III
Model Question Paper-IV
Solution to Model Question Paper-I
Solution to Model Question Paper-II



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