Management Research Methodology: Integration of Principles, Methods and Techniques

Management Research Methodology: Integration of Principles, Methods and Techniques

by K. N. Krishnaswamy, Appa Iyer Sivakumar, M. Mathirajan
Released July 2006
Publisher(s): Pearson India
ISBN: 9788177585636

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Book description

The subject of management research methodology is enthralling and complex. A student or a practitioner of management research is beguiled by uncertainties in the search and identification of the research problem, intrigued by the ramifications of research design, and confounded by obstacles in obtaining accurate data and complexities of data analysis. Management Research Methodology: Integration of Principles, Methods and Techniques seeks a balanced treatment of all these aspects and blends problem-solving techniques, creativity aspects, mathematical modelling and qualitative approaches in order to present the subject of Management Research Methodology in a lucid and easily understandable way.

Table of contents

  1. Cover
  2. Title Page
  3. Contents
  4. Dedication
  5. About the Authors
  6. Preface
  7. Part A Scientific Method in Management Research
    1. 1. Scientific Method
      1. Introduction
        1. Defining Research
        2. Scientific Enquiry
      2. Scientific Method
        1. Formal Science and Empirical Science
        2. Logic of Scientific Method
        3. Hypothetico deductive Method
        4. Models
        5. Scientific Attitude
      3. Issues of Management Research
        1. Use of Scientific Method
        2. Alternative Perspectives of Management Research
      4. Summary
      5. Suggested Readings
      6. Questions and Exercises
    2. 2. Overview of Research in Management
      1. Scientific Research in Management
      2. Research Problem Identification
      3. Research Problem Definition
        1. Generation of Hypotheses
        2. Formulation of Research Problems
      4. Research Design
        1. Classification of Designs
        2. Issues of Research Design
      5. Research Design Process
        1. Selection of the Type of Research
        2. Measurement and Measurement Techniques
        3. Selection of Sample
        4. Selection of Data Collection Procedures
        5. Selection of Methods of Analysis
      6. Decisional Research with Mathematical Models
      7. Some Philosphic Issues of Management Research
        1. Paradigms
        2. Consultative Approach to Management Research
      8. Errors in Research
      9. Summary
      10. Annexure 2.1
      11. Suggested Readings
      12. Questions and Exercises
  8. Part B Research Problem
    1. 3. Problem Solving
      1. General Problem Solving
        1. What is a Problem?
        2. Types of Problems
        3. Problem Solving Process
      2. Logical Approach
      3. Soft System Approach
      4. Creative Approach
        1. Thinking Process
        2. Creative Thinking
        3. Creative Efforts in Research
        4. Barriers to Creativity
        5. Creative Problem Solving Process
      5. Development of Creativity
      6. Group Problem Solving Techniques for Idea Generation
        1. Introduction
        2. Brainstorming
        3. Delphi Method
      7. Summary
      8. Annexure 3.1—An Illustration of a Case of Application of SSM
      9. Suggested Readings
      10. Questions and Exercises
    2. 4. Formulation of Research Problems
      1. Introduction
      2. Approaches to Management Research Problem
        1. Management Problem is Posed to the Researcher
        2. Investigation of an Idea by an Experienced Researcher
        3. Pilot Study
        4. Initiatiation of a Novice/Student to Research
      3. Exploration for Problem Identification
        1. Literature Survey
        2. System Study
        3. Errors of Problem Identification in Research
      4. Hypothesis Generation
        1. Introduction
        2. Variables
        3. Characteristics of a Good Hypothesis
        4. Origins of a Hypothesis
        5. Process of Hypothesis Generation
        6. Hypothesis Generation Using Qualitative Methods
      5. Formulation of The Problem
        1. Model Building Context
        2. Decision Maker and His Objectives
        3. Environment
        4. Alternative Courses of Action
        5. Scenarios and Structural Modelling
        6. Interpretive Structural Modelling (ISM)
        7. Formulation of Effectiveness Function
      6. Summary
      7. Annexure 4.1—An Example of Taxonomy
      8. Annexure 4.2—An Example for Meta Analysis
      9. Annexure 4.3—An Illustrative Example of Theoretical Framework
      10. Annexure 4.4—Examples of Hypothesis Generation
      11. Annexure 4.5—System Study and Problem Formulation–Allocation of Assembly Manpower (Karthikeyan 1986)
      12. Annexure 4.6
      13. Suggested Readings
      14. Questions and Exercises
    3. 5. Research Proposal
      1. Research Proposal
      2. Purpose of a Research Proposal
      3. Types of Research Proposals
      4. Development of the Proposals
        1. Formatting the Research Proposal
        2. Contents of the Research Proposal
      5. Requirements of the Sponsoring Agent
      6. Evaluation of Research Proposals
      7. Some Implicit Considerations
      8. Summary
      9. Annexure 5.1—Sample (Real) Research Proposal (Krishnaswamy et al, 1997)
      10. Suggested Readings
      11. Questions and Exercises
  9. Part C Research Design—Types of Research
    1. 6. Experimental Research
      1. Experimental Research
      2. Principles of Experiment
      3. Laboratory Experiments
        1. Difficulties of Performing Laboratory Experiments
        2. Design of Laboratory Experiments
        3. Execution of Laboratory Experiments
        4. Strength and Weakness of Experiments
        5. Errors in Experiments
      4. Experimental Designs
        1. Basis of Experimental Design
        2. Basic Designs
        3. Statistical Designs
        4. Field Experiments
      5. Quasi-Experimental Designs
        1. Quasi-Experimental Designs
        2. A Comparison of The Two Quasi-Experimental Designs
        3. Use of Quasi-Experimental Designs
      6. Action Research
        1. Defining Action Research
        2. Process of Action Research
        3. Comparison of Action Research with Experiments
        4. Scientific Merits of Action Research
      7. Validity and Reliability of Experiments and Quasi-Experiments
        1. Concept of Validity and Reliability
        2. Validity in Experimentation and Quasi-Experimentation
        3. Validity of Quasi-Experimentation
      8. Sources of Invalidity of Experiments and Quasi-experiments
      9. Choice of Experimental Design
      10. Analysis Procedures Used in Experimental Design
      11. Summary
      12. Annexure 6.1—A Laboratory Experiment
      13. Annexure 6.2—A Randomised Two-Group Experiment
      14. Annexure 6.3—Solomon Four-Group Design
      15. Annexure 6.4—Factorial Design
      16. Annexure 6.5—Randomised Block Design
      17. Annexure 6.6—An Action Research Case
      18. Suggested Readings
      19. Questions and Exercises
    2. 7. Ex Post Facto Research
      1. Introduction
      2. Ex Post Facto Research by Objective
        1. Exploratory Research
        2. Historical Research
        3. Descriptive Research
      3. Ex Post Facto Research by Nature of Study
        1. Field Studies
        2. Survey Research
      4. Qualitative Research Methods
        1. Case Study Research
        2. Participant Observation
        3. Ethnographic Methods
        4. Critical Incident Technique
        5. Repertory Grid Technique (RGT)
        6. Some Additional Qualitative Research Methods
        7. Triangulation
        8. Analysis Procedures for Qualitative Data
      5. Evaluation Research
        1. Outcome Evaluation
        2. Formative Evaluation Research
      6. Summary
      7. Annexure 7.1—An Example of Explorative Research
      8. Annexure 7.2—An Example of Descriptive Research
      9. Annexure 7.3—An Example of Field Research
      10. Annexure 7.4—An Example for Survey Research
      11. Annexure 7.5—An Example for Case Study Research
      12. Annexure 7.6—Example of Cognitive Mapping
      13. Suggested Readings
      14. Questions and Exercises
    3. 8. Modelling Research I—Mathematical Modelling
      1. Introduction
      2. Mathematical Models
        1. What is a Model?
        2. Development of Models
        3. Principles of Modeling
        4. Patterns of Model Building
        5. Use of Analogy in Modelling
        6. Models as Approximations
        7. Data Consideration in Modelling
        8. Models as Heuristic Instruments
        9. Solutions of Models
        10. Testing of Models
      3. Composite Modelling Methods
      4. Summary
      5. Annexure 8.1(a)—Illustration of Modelling A
      6. Annexure 8.1(b)—Illustration of Modelling B
      7. Annexure 8.2(a)—Illustration for Composite Methodology A
      8. Annexure 8.2(b)—Illustration of Composite Methodology B
      9. Suggested Readings
      10. Questions and Exercises
    4. 9. Modelling Research II—Heuristics and Simulation
      1. Heuristic Optimisation
        1. Definition of Heuristics
        2. Why Use Heuristics?
        3. Heuristic Methods
        4. Heuristics Problem-Solving Approaches
        5. Meta-Heuristics
        6. Choice of Heuristic Methods
        7. Evaluation of Heuristics
        8. Evaluation of Heuristics in Empirical Analysis
        9. Sources of Problem Instances
        10. Performance Measures/Measure of Effectiveness
        11. Examples of Heuristic Optimisation
        12. Advantages and Limitations of Heuristic Methods
      2. Simulation Modelling
        1. Meaning of Simulation
        2. What is Simulation?
        3. Classification of Simulation Models
        4. The Process of Simulation
        5. Key Steps in Simulation Experiments
        6. Validation of Simulation Models/Experiments
      3. Summary
      4. Annexure 9.1—Demonstration of Constructive Heuristics and SA (Simulated Annealing)
      5. Annexure 9.2—Illustration of Heuristics
      6. Annexure 9.3—Illustration for Empirical Evaluation of Greedy Heuristics
      7. Annexure 9.4—Illustration for Monte Carlo Simulation
      8. Annexure 9.5—Illustration for Simulation from Actual Research
      9. Suggested Readings
      10. Questions and Exercises
  10. Part D Research Design for Data Acquisition
    1. 10. Measurement Design
      1. Introduction
      2. Primary Types of Measurement Scales
        1. Nominal Scales
        2. Ordinal Scales
        3. Interval Scales
        4. Ratio Scales
      3. Errors in Measurement
      4. Validity and Reliability in Measurement
        1. Validity of Measurement
        2. Reliability in Measurement
      5. Types of Scaling (Scale Classification)
        1. Response Methods
        2. Quantitative Judgment Methods
      6. Scale Construction Techniques
        1. Judgment Methods
        2. Factor Scales
      7. Summary
      8. Annexure 10.1—Illustrative Example: Content Validity
      9. Annexure 10.2—Illustrative Example: Concurrent and External Validity
      10. Annexure 10.3—Illustrative Example: Construct Validity
      11. Annexure 10.4—Illustrative Example: Reliability in Measurement
      12. Suggested Readings
      13. Questions and Exercises
    2. 11. Sample Design
      1. Introduction
        1. Sampling Process
      2. Non-Probability Sampling
      3. Probability Sampling
        1. Simple Random Sampling
        2. Stratified Random Sampling
        3. Cluster Sampling
        4. Systematic Random Sampling
        5. Area Sampling
      4. Determination of Sample Size
        1. Required Size/Cell
        2. Use of Statistical Models
        3. Bayesian Method for Determination of Sample Size
      5. Illustrative Examples of Sample Size Determination
      6. Summary
      7. Suggested Readings
      8. Questions and Exercises
  11. Part E Acquisition and Preparation of Research Data
    1. 12. Data Collection Procedures
      1. Introduction
      2. Sources of Secondary Data
        1. Internal Sources
        2. External Sources
        3. Computer Search for Secondary Data
      3. Primary Data Collection Methods
        1. Observation
        2. Evaluation of Observations as Data Collection Procedures
        3. Questionnaires
        4. Interviews
        5. Projective Techniques
      4. Non-Sampling Errors
        1. Non-Observation Errors
        2. Observation errors
      5. Validity and Reliability of Data Collection Procedures
        1. Validity and Reliability of Interviews
        2. Validity and Reliability of Observation
        3. Validity and Reliability of Questionnaires
      6. Summary
      7. Suggested Readings
      8. Questions and Exercises
    2. 13. Data Preparation and Preliminary Data Analysis
      1. Introduction
      2. Data Preparation
        1. Editing Data
        2. Coding Data
        3. Transcription of Data (Transcribing)
        4. New Variable/Functional Combination/Splitting Form
        5. Data Description
        6. Summarising Statistics
      3. Exploratory Data Analysis
        1. Stem and Leaf Display
        2. Box Plots
        3. Data Mining
      4. Statistical Estimation
      5. Content Analysis
        1. Some Recent Developments
        2. Example of Content Analysis
      6. Summary
      7. Suggested Readings
      8. Questions and Exercises
  12. Part F Data Analysis and Reporting
    1. 14. Hypothesis Testing—Univariate Analysis
      1. Introduction
      2. Logic of Hypothesis Testing
        1. Null Hypothesis
        2. Research Hypothesis
        3. Errors in Hypothesis Testing
      3. Identification of an Appropriate Test for Hypothesis Testing
      4. Parametric Tests
        1. Z-Test
        2. t-Test
        3. F-Test for Analysis of Variance
      5. Non-Parametric Tests
        1. Chi-Square Test
        2. McNemar Test
        3. Kolmogorov-Smirnov Test
        4. Kruskal-Wallis Test (For Ranked Data)
        5. Friedman’s Two-Way ANOVA
        6. Kendal’s Coefficient of Concordance (W)
      6. Summary
      7. Suggested Readings
      8. Questions and Exercises
    2. 15. Bivariate Analysis and Hypothesis Testing
      1. Introduction
      2. Correlation
      3. Simple Linear Regression Model
        1. Fitting of a Simple Linear Regression Model
      4. Non-parametric Methods of Association
        1. Spearman’s Rank Correlation Coefficient (rs)
        2. Kendall’s Tau
        3. Contingency Coefficient
      5. Summary
      6. Suggested Readings
      7. Questions and Exercises
    3. 16. Analysis of Experimental Data
      1. Introduction
      2. Analysis of Single Factor Experiments
      3. Single Factor Randomised Blocks Design
        1. RBD Model
      4. Latin Square Design
        1. Latin Square Design Model
      5. Completely Randomised 2 × 2 Factorial Design
        1. 2 × 2 Factorial Design Model
      6. Summary
      7. Suggested Readings
      8. Questions and Exercises
    4. 17. Multivariate Analysis of Data—Dependence Analysis
      1. Multiple Regression
        1. Introduction
        2. Assumptions and the Procedure
        3. Verification
        4. Problems Encountered While Using Multiple Regression
        5. Overcoming Multicolinearity
        6. Variable Selection and Model Building
        7. An Overview of Multiple Regression Analysis Procedure
        8. Variants of Regression Analysis
        9. Applications
      2. Discriminant Analysis
        1. Introduction
        2. Assumptions
        3. The Method
        4. Testing Statistical Significance of Discriminant Functions
      3. Canonical Correlation Analysis
        1. Introduction
        2. The Model
        3. Assumptions
        4. The Method
        5. Significance Test
        6. Interpretation
      4. Path Analysis
      5. Other Methods
        1. Conjoint Analysis
        2. Automatic Interaction Detection Analysis
      6. Summary
      7. Suggested Readings
      8. Questions and Exercises
    5. 18. Multivariate Analysis of Data II—Interdependence Analysis
      1. Introduction
      2. Factor Analysis
        1. Introduction
        2. Geometric Representation of Factor Analysis
        3. The Model
        4. Assumptions
        5. Methods of Factor Analysis
      3. Multidimensional Scaling (MDS)
        1. Introduction
        2. Fundamentals of MDS
        3. Process of MDS
        4. Factor Analysis versus Multidimensional Scaling
      4. Cluster Analysis
        1. Introduction
        2. Extraction
        3. Methods of Clustering
        4. Reliability
      5. Summary
      6. Annexure 18.1—Confirmatory Factor Analysis to Test Research Hypothesis
      7. Suggested Readings
      8. Questions and Exercises
    6. 19. Report Writing
      1. Introduction
      2. Pre-writing Considerations
        1. Dissertations/Theses
        2. Style and Composition of the Report
        3. Principles of Thesis Writing
      3. Format of Reporting
        1. Format of Dissertations
        2. Format of Research Reports
        3. Format of Publication in a Research Journal
        4. Reporting of Qualitative Research
      4. Briefing
      5. Rules for Typing or Word Processing
      6. Summary
      7. Suggested Readings
      8. Questions and Exercises
  13. Appendix A1—System Concept
  14. Appendix A2—Analysis of Covariance (ANCOVS)
  15. Appendix A3—Some Research Findings on Creativity
  16. Appendix A4—Some Further Group Problem-Solving Techniques
  17. Appendix B—Sources of Information of Management and Social Sciences
  18. Appendix C—Formulae for Hypothesis Testing
  19. Appendix D—Selected Statistical Tables
  20. Bibliography
  21. Glossary
  22. Notes
    1. Chapter 2
    2. Chapter 4
    3. Chapter 6
    4. Chapter 7
    5. Chapter 8
    6. Chapter 9
    7. Chapter 10
    8. Chapter 12
    9. Chapter 13
    10. Chapter 17
    11. Appendix C
  23. Acknowledgements
  24. Copyright

Product information

  • Title: Management Research Methodology: Integration of Principles, Methods and Techniques
  • Author(s): K. N. Krishnaswamy, Appa Iyer Sivakumar, M. Mathirajan
  • Release date: July 2006
  • Publisher(s): Pearson India
  • ISBN: 9788177585636