**Management Research Methodology**

#### for ANNA Univeristy and VTU

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**

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 (Krishnaswamy 1998)

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

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

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

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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