Marketing Research Text and Cases

Cover
Contents
PART 1: FUNDAMENTALS OF MARKETING RESEARCH
	I. Introduction, Evolution, and Emerging Issues
		Role of Marketing Research in a Marketing Plan
		Marketing Intelligence versus Marketing Research
			Who Does the Marketing Research?
		Typical Applications of Marketing Research
			Concept Research
			Product Research
			Pricing Research
			Distribution Research
			Advertising Research
		When To Do Marketing Research? II Limitations of Marketing Research
			Differences in Methodology
			Complementary Inputs for Decision-making
		Secondary and Primary Research
		Ethical Considerations in Marketing Research
		Consumer's Right to Privacy
		Emerging Issues
			Marketing Research in the Internet Era
			Online Research
			Data Warehousing and Data Mining
		Summary
		Assignment Questions
	2. The Marketing Research Process-An Overview
		Information Need
		Defining the Research Objective
		Research Designs: Exploratory, Descriptive, and Causal
			Exploratory Research
			Descriptive Research
			Causal Research Designs
		Designing the Research Methodology
			Survey
			Observation
			Experimentation
			Qualitative Techniques
			Specialised Techniques
		Plan for Sampling, Field Work, and Analysis
			Sampling Plan
			Field Work Plan
			Briefing
			Debriefing
		Analysis Plan and Expected Outcome
			Expected Outcome
			Budget and Cost Estimation
		Presentation, Report, and Marketing Action
		Case Study 1
		Summary
		Assignment Questions
	3. Research Methods and Design-Additional Inputs
		Sources of Secondary Data .
		Disadvantages of Secondary Data
		Exploratory and Conclusive Research
		Major Qualitative Research Techniques
			Depth Interview
			Focus Group
			Projective Techniques
		Validity of Research
		Experiments
			Test Marketing
		Case Study: Consumer Perception of High-end IT Education
		Summary
		Assignment Questions
	4. Questionnaire Design: A Customer-centric Approach
		Designing Questionnaires for Market Research
			Language
			Difficulty Level
			Fatigue
			Cooperation with Researcher
			Social Desirability Bias
			Ease of Recording
			Coding
			Purpose of a Questionnaire
			Sequencing of Questions
			Biased and Leading Questions
			Monotony
			Analysis Required
		Scales of Measurement Used in Marketing Research
			Nominal Scale
			Ordinal Scale
			Interval Scale
			Ratio Scale
		Structured and Unstructured Questionnaires
			Structured Questions
			Structured Answers
			Open-ended and Closed-ended Questions
			Disguised Versus Undisguised Questions
		Types of Questions
			Open-ended Question
			Dichotomous Questions
			Multiple-choice Questions
			Ratings or Rankings
			Paired Comparisons
			Semantic Differential
			How to Choose a Scale and Question Type
		Transfonning Information Needs into a Questionnaire
			Example ofInformation Needs
			Double-barrelled Questions
			Good Questionnaires and Bad Questionnaires
		Reliability and Validity of a Questionnaire
		Reliability and Validity
			What is a Construct?
			Content Validity
			Criterion Validity or Predictive Validity
			Construct Validity
			Reliability of a Scale
		Summary
		Case Study 1: Tamarind Menswear
		Case Study 2: Casual Clothing References of Youth
		Case Study 3: Parryware-A Survey on Consumers Perception of Bathroom and Sanitaryware
		Assignment Questions
	5. Sampling Methods-Theory and Practice
		Basic Terminology in Sampling
			Sampling Element
			Population
			Sampling Frame
			Sampling Unit
		The Sample Size Calculation
			Formula for Sample Size Calculation when Estimating Means (for Continuous or Interval-scaled Variables)
			Formulafor Sample Size Calculation when Estimating Proportions
		Other Issues that Affect Sample Size Decisions
			1. Number of Centres
			2. Multiple Questions
			3. Cell Size in Analysis
			4. Time and Budget Constraints
			5. The Role of Experience in Determination of Sample Size
		Sampling Techniques
			Probability Sampling Techniques
			Non-probability Sampling Techniques
			Census ""rsus Sample
		Types of Errors in Marketing Research
			Sampling Error
			Non-sampling Error
			Total Error
		Summary
		Assignment Questions
	6. Field Procedures.
		Design of Field Work
		Selection'ofCities/Centres
		Organising Field Work
		Quotas
		Selection of Respondents
		Control Procedures on the Field
		Briefing
		Debriefing
		Summary
		Assignment Questions
	7. Planning the Data Analysis
		Processing of Data with Computer Packages
		Statistical and Data Processing Packages
			Types of Analysis
			Data Processing
		Data Input Format
			Coding
		Variables and Variable Labels
			Variable Format
		'Value Labels
			Record Number/Case Number
			Missing Data
		Statistical Analysis
		Hypothesis Testing and Probability Values (p-values)
		Approaches to Analysis
			Three Types of Analysis
		Hypothesis Testing
		Summary
		Assignment Questions
		SPSS Data Input and t-test Commands
		Integrated Case Studies for Part I
			Case Study 1: Crocin
			Case Study 2: Detergents
			Case Study 3: BPL
PART 2: DATA ANALYSIS
	8. Simple Tabulation and Cross-tabulation
		Univariate and Bivariate Analysis
			Dependent and Independent Variables
			Demographic Variables
		First Stage Analysis-Simple Tabulation
			Computer Tabulation
			Percentages
		Simple Tabulation for Ranking Type Questions
			Tabulating Ratings
		Second Stage Analysis--Cross-Tabulation
			Calculating Percentages in a Cross-tabulation
			Cross-tabulation of More Than Two Variables
			Lack of Causal Inference in Cross-tabulations
			The Chi-squared Test for Cross-tabulations
			Chi-squared Test: An Illustration
			Measures of the Strength of Association Between Variables
		Doing More with Data (Transformation of Variables and Use of Part-samples)
		Summary
		Assignment Questions
		SPSS Commands for Frequency Tables, and Cross-tabs with Chi-squared Test
		Case Study 1: Chi-square Test for Cross-tabs
		Case Study 2: Chi-square Test for Cross-tabs
		Case Study 3: Chi-square Test
	9. ANOVA and the Design of Experiments
		Introduction
		Applications
		Methods
		Variables
		Experimental Designs
			Completely Randomised Design in a One-way ANOVA
			Randomised Block Design
			Latin Square Design
			Factorial Design with Two or More Factors
		Additional Comments
		Pairwise Tests
		Summary
		Assignment Questions
		SPSS Commands Jar ANOVA
		Case Study 1: ANOVA
		Case Study 2: ANOVA
		Case Study 3: ANOVA
	10. Correlation and Regression: Explaining Association and Causation
		Application Areas
		Methods
		Recommended Usage
		Worked Example
			Problem
			Input Data
			Correlation
			Regression
			Regression Output
			Predictions
		Forward Stepwise Regression
		Backward Stepwise Regression
			Additional Comments
		Summary
		Assignment Questions
		SPSS Commands Jar Correlation and Regression
		Case Study 1: Correlation and Regression
		Case Study 2: Correlation and Regression
		Case Study 3: Correlation and Regression
	11. Discriminant Analysis for Classification and Prediction
		Application Areas
			Methods
		Variables and Data
		Predicting the Group Membership for a New Data Point
		Accuracy of Classification
			StepwisefFixed Model
			Relative Importance of Independent Variables
			Apriori Probability of Classification into Groups
		Worked Example
			Problem
			Input Data
		Interpretation of Computer Output
			Additional Comments
		Summary
		Assignment Questions
		SPSS Commands for Discriminant Analysis
		Case Study 1: Discriminant Analysis
		Case Study 2: Discriminant Analysis
		Case Study 3: Discriminant Analysis
	12. Logistic Regression for Classification and Prediction
		Application Areas
		Methods
			The Algorithm
			Logistic Regression Versus Linear Discriminant Analysis
		Numerical Example with SPSS
			Interpretation of Output
			Statistical Significance
			Predictors
			Classification of New Customer
		Summary
		Assignment Questions
		SPSS Commands for Logistic Regression
		Case Study 1: Logistic Regression
		Case Study 2: Logistic Regression
		Case Study 3: Logistic Regression
	13. Factor Analysis for Data Reduction
		Application Areas
			Methods
			Recommended Usage
		Worked Example
			Input Data
			Interpretation of Computer Output
		Additional Comments
		Appendix 1
		Summary
		Assignment Questions
		SPSS Commands for Factor Analysis
		Case Study I: Factor Analysis
		Case Study 2: Factor Analysis
		Case Study 3: Factor Analysis
	14. Cluster Analysis for Market Segmentation
		Application Areas
		Methods
			Data/Scales of Variables
		Recommended Usage
		Worked Example
			Input Data
			Output and Its Interpretation
			Stage I
			Stage 2
			Cluster I
			Cluster 2
			Cluster 3
			Cluster 4
			ANOVA
		Additional Comments on Cluster Analysis
			Objects
			Scale
			Statistical Tests
		Summary
		ASSignment Questions
		SPSS Commands for Cluster Analysis
		Case Study 1: Cluster Analysis
		Case Study 2: Cluster Analysis
		Case Study 3: Cluster AnalYSis
	15. Multidimensional Scaling for Brand Positioning
		Application Areas
			Methods
		Recommended Usage
		Worked Example
		Problem
			Input Data
			Interpretation of Computer Output
			3-Dimensional Solution
		Additional Comments
		Summary
		Assignment Questions
		SPSS Commands Jor Multidimensional Scaling
		Case Study 1: Multidimensional Scaling
		Case Study 2: Multidimensional Scaling
		Case Study 3: Multidimensional Scaling
	16. Conjoint Analysis for Product Design
		Application Areas
		Methods
		Recommended Usage
			Number of Attributes and Levels
			Number of Combinations
		Worked Example
			Ranking
		Running Conjoint as a Regression Model
			Output and its Interpretation
			Utilities Table for Conjoint Analysis
			Combination Utilities
			Individual Attributes
		Additional Comments
		Summary
		Assignment Questions
		SPSS Commands Jor Conjoint Analysis
		Case Study 1: Conjoint Analysis
		Case Study 2: Conjoint Analysis
		Case Study 3: Conjoint Analysis
	17. Attribute-based Perceptual Mapping Using Discriminant Analysis
		Application Areas
		Methods
		Worked Example
			Problem
			Discriminant Analysis Output
			Summary of Canonical DiscrirninantFunctions
			Unstandardised Coefficients
			Putting Variables/ Atttibute Vectors on the Above Map
			Brands and their Association with AtttibnteslDimensions
			Atttibute vs. Non-atttibute Based Perceptual Maps: Which are Better?
		Summary
		Assignment Questions
		SPSS Commands for Attribute-based Perceptual Mapping Using Discriminant Analysis
		Case Study 1: Attribute-based Perceptual Mapping Using Discriminant Analysis
		Case Study 2: Attribute-based Perceptual Mapping Using Discriminant Analysis
		Case Study 3: Attribute-based Perceptual Mapping Using Discriminant Analysis
	18. Structural Equation Modeling (SEM) for Complex Models (including Confirmatory Factor Analysis)
		ConfIrmatory Factor Analysis
			Tests Used in CFA and SEM
			Goodness-of-fIt Tests Comparing the Given Model with an Alternative Model
			Chi-square Test in SEM
			ConfIrmatory Factor Analysis
			STATISTICA Commands for CFA
			SEM Commands Using STATISTICA
			Conclusion from SEM Analysis
		Summary
		Appendix
		Assignment Questions	#538,531,-9PART 3: APPENDICES
	Appendix I: Industrial Marketing Research
		Definng the Target Population
		Applications
		Who Does Industrial Marketing Research?
			Internal versus External
			Technical QualifIcation of Researcher
		Questionnaire Design
		Checklists
		Use of Secondary Research
		Use of Industry Experts
		Analysing Government Policy 518. Forecasting Derived Demand
		Assignment
		Marketing Research for Product Redesign: A Case Study of ABC Ltd.
	Appendix 2: Careers in Marketing Research
		Major Companies in Marketing Research
		Jobs in Marketing Research
			Research Executive
			Statistical Analyst
			Field Supervisors
			Field Staff
		Sununary of Job Prospects
		Growth Prospects
		Getting Business
		Summary
		Assignment Questions
References
Index