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MARKETING
RESEARCH
AN APPLIED APPROACH
FIFTH EDITION
NARESH K. MALHOTRA
DANIEL NUNAN
DAVID F. BIRKS
Harlow, England • London • New York • Boston • San Francisco • Toronto • Sydney • Dubai • Singapore • Hong Kong
Tokyo • Seoul • Taipei • New Delhi • Cape Town • São Paulo • Mexico City • Madrid • Amsterdam • Munich • Paris • Milan
Brief contents
Preface
Publisher’s acknowledgements
About the authors
xiii
xv
xvii
1.
Introduction to marketing research
2.
Defining the marketing research problem and developing
a research approach
29
3.
Research design
59
4.
Secondary data collection and analysis
90
5.
Internal secondary data and analytics
121
6.
Qualitative research: its nature and approaches
147
7.
Qualitative research: focus group discussions
179
8.
Qualitative research: in-depth interviewing and projective
techniques
207
Qualitative research: data analysis
233
10.
Survey and quantitative observation techniques
267
11.
Causal research design: experimentation
302
12.
Measurement and scaling: fundamentals, comparative
and non-comparative scaling
333
13.
Questionnaire design
371
14.
Sampling: design and procedures
409
15.
Sampling: determining sample size
442
16.
Survey fieldwork
471
17.
Social media research
491
18.
Mobile research
513
19.
Data integrity
528
20.
Frequency distribution, cross-tabulation and hypothesis testing
556
21.
Analysis of variance and covariance
601
9.
1
vi
Marketing Research
22.
Correlation and regression
632
23.
Discriminant and logit analysis
673
24.
Factor analysis
707
25.
Cluster analysis
735
26.
Multidimensional scaling and conjoint analysis
762
27.
Structural equation modelling and path analysis
795
28.
Communicating research findings
831
29.
Business-to-business (b2b) marketing research
854
30.
Research ethics
881
Glossary
908
Subject index
926
Name index
952
Company index
954
Contents
Preface
Publisher’s acknowledgements
About the authors
1 Introduction to marketing research
Objectives
Overview
What does ‘marketing research’ mean?
A brief history of marketing research
Definition of marketing research
The marketing research process
A classification of marketing research
The global marketing research industry
Justifying the investment in marketing research
The future – addressing the marketing research
skills gap
Summary
Questions
Exercises
Notes
2 Defining the marketing
research problem and developing
a research approach
Objectives
Overview
Importance of defining the problem
The marketing research brief
Components of the marketing research brief
The marketing research proposal
The process of defining the problem and
developing a research approach
Environmental context of the problem
Discussions with decision makers
Interviews with industry experts
Initial secondary data analyses
Marketing decision problem and marketing
research problem
Defining the marketing research problem
Components of the research approach
Objective/theoretical framework
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xv
xvii
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15
19
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51
Analytical model
Research questions
Hypothesis
Summary
Questions
Exercises
Notes
52
53
54
54
55
56
57
3 Research design
59
Objectives
Overview
Research design definition
Research design from the decision makers’
perspective
Research design from the participants’ perspective
Research design classification
Descriptive research
Causal research
Relationships between exploratory, descriptive
and causal research
Potential sources of error in research designs
Summary
Questions
Exercises
Notes
4 Secondary data collection
and analysis
Objectives
Overview
Defining primary data, secondary data
and marketing intelligence
Advantages and uses of secondary data
Disadvantages of secondary data
Criteria for evaluating secondary data
Classification of secondary data
Published external secondary sources
Databases
Classification of online databases
Syndicated sources of secondary data
Syndicated data from households
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Marketing Research
Syndicated data from institutions
Summary
Questions
Exercises
Notes
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117
118
119
119
5 Internal secondary data and
analytics
121
Objectives
Overview
Internal secondary data
Geodemographic data analyses
Customer relationship management
Big data
Web analytics
Linking different types of data
Summary
Questions
Exercises
Notes
122
122
125
128
132
134
136
139
144
144
145
146
6 Qualitative research:
its nature and approaches
147
Objectives
Overview
Primary data: qualitative versus
quantitative research
Rationale for using qualitative research
Philosophy and qualitative research
Ethnographic research
Grounded theory
Action research
Summary
Questions
Exercises
Notes
7 Qualitative research:
focus group discussions
Objectives
Overview
Classifying qualitative research techniques
Focus group discussion
Planning and conducting focus groups
The moderator
Other variations of focus groups
Other types of qualitative group discussions
Misconceptions about focus groups
Online focus groups
Advantages of online focus groups
Disadvantages of online focus groups
Summary
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Questions
Exercises
Notes
8 Qualitative research: in-depth
interviewing and projective
techniques
Objectives
Overview
In-depth interviews
Projective techniques
Comparison between qualitative techniques
Summary
Questions
Exercises
Notes
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205
207
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227
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230
9 Qualitative research: data analysis 233
Objectives
Overview
The qualitative researcher
The process of qualitative data analysis
Grounded theory
Content analysis
Semiotics
Qualitative data analysis software
Summary
Questions
Exercises
Notes
10 Survey and quantitative
observation techniques
Objectives
Overview
Survey methods
Online surveys
Telephone surveys
Face-to-face surveys
A comparative evaluation of survey methods
Other survey methods
Mixed-mode surveys
Observation techniques
Observation techniques classified by mode
of administration
A comparative evaluation of the
observation techniques
Advantages and disadvantages
of observation techniques
Summary
Questions
Exercises
Notes
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239
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256
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262
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267
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Contents
11 Causal research design:
experimentation
Objectives
Overview
Concept of causality
Conditions for causality
Definitions and concepts
Definition of symbols
Validity in experimentation
Extraneous variables
Controlling extraneous variables
A classification of experimental designs
Pre-experimental designs
True experimental designs
Quasi-experimental designs
Statistical designs
Laboratory versus field experiments
Experimental versus non-experimental designs
Application: test marketing
Summary
Questions
Exercises
Notes
12 Measurement and scaling:
fundamentals, comparative
and non-comparative scaling
Objectives
Overview
Measurement and scaling
Scale characteristics and levels of measurement
Primary scales of measurement
A comparison of scaling techniques
Comparative scaling techniques
Non-comparative scaling techniques
Itemised rating scales
Itemised rating scale decisions
Multi-item scales
Scale evaluation
Choosing a scaling technique
Mathematically derived scales
Summary
Questions
Exercises
Notes
13 Questionnaire design
Objectives
Overview
Questionnaire definition
Questionnaire design process
Specify the information needed
Specify the type of interviewing method
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Determine the content of individual questions
Overcoming the participant’s inability and
unwillingness to answer
Choose question structure
Choose question wording
Arrange the questions in proper order
Identify the form and layout
Reproduce the questionnaire
Eliminate problems by pilot-testing
Summarising the questionnaire design
process
Designing surveys across cultures and countries
Summary
Questions
Exercises
Notes
14 Sampling: design and procedures
Objectives
Overview
Sample or census
The sampling design process
A classification of sampling techniques
Non-probability sampling techniques
Probability sampling techniques
Choosing non-probability versus
probability sampling
Summary of sampling techniques
Issues in sampling across countries and cultures
Summary
Questions
Exercises
Notes
15 Sampling: determining
sample size
Objectives
Overview
Definitions and symbols
The sampling distribution
Statistical approaches to determining
sample size
The confidence interval approach
Multiple characteristics and parameters
Other probability sampling techniques
Adjusting the statistically determined
sample size
Calculation of response rates
Non-response issues in sampling
Summary
Questions
Exercises
Appendix: The normal distribution
Notes
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Marketing Research
16 Survey fieldwork
Objectives
Overview
The nature of survey fieldwork
Survey fieldwork and the data-collection process
Selecting survey fieldworkers
Training survey fieldworkers
Recording the answers
Supervising survey fieldworkers
Evaluating survey fieldworkers
Fieldwork and online research
Fieldwork across countries and cultures
Summary
Questions
Exercises
Notes
17 Social media research
Objectives
Overview
What do we mean by ‘social media’?
The emergence of social media research
Approaches to social media research
Accessing social media data
Social media research methods
Research with image and video data
Limitations of social media research
Summary
Questions
Exercises
Notes
18 Mobile research
Objectives
Overview
What is a mobile device?
Approaches to mobile research
Guidelines specific to mobile marketing research
Key challenges in mobile research
Summary
Questions
Exercises
Notes
19 Data integrity
Objectives
Overview
The data integrity process
Checking the questionnaire
Editing
Coding
Transcribing
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Cleaning the data
Statistically adjusting the data
Selecting a data analysis strategy
Data integrity across countries and cultures
Practise data analysis with SPSS
Summary
Questions
Exercises
Notes
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545
548
549
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554
20 Frequency distribution, crosstabulation and hypothesis testing
556
Objectives
Overview
Frequency distribution
Statistics associated with frequency distribution
A general procedure for hypothesis testing
Cross-tabulations
Statistics associated with cross-tabulation
Hypothesis testing related to differences
Parametric tests
Non-parametric tests
Practise data analysis with SPSS
Summary
Questions
Exercises
Notes
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598
21 Analysis of variance and covariance 601
Objectives
Overview
Relationship among techniques
One-way ANOVA
Statistics associated with one-way ANOVA
Conducting one-way ANOVA
Illustrative applications of one-way ANOVA
n-way ANOVA
Analysis of covariance (ANCOVA)
Issues in interpretation
Repeated measures ANOVA
Non-metric ANOVA
Multivariate ANOVA
Practise data analysis with SPSS
Summary
Questions
Exercises
Notes
22 Correlation and regression
Objectives
Overview
Product moment correlation
Partial correlation
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614
619
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Contents
Non-metric correlation
Regression analysis
Bivariate regression
Statistics associated with bivariate regression
analysis
Conducting bivariate regression analysis
Multiple regression
Statistics associated with multiple regression
Conducting multiple regression analysis
Multicollinearity
Relative importance of predictors
Cross-validation
Regression with dummy variables
Analysis of variance and covariance
with regression
Practise data analysis with SPSS
Summary
Questions
Exercises
Notes
23 Discriminant and logit analysis
Objectives
Overview
Basic concept of discriminant analysis
Relationship of discriminant and logit analysis
to ANOVA and regression
Discriminant analysis model
Statistics associated with discriminant
analysis
Conducting discriminant analysis
Conducting multiple discriminant analysis
Stepwise discriminant analysis
The logit model
Conducting binary logit analysis
Practise data analysis with SPSS
Summary
Questions
Exercises
Notes
24 Factor analysis
Objectives
Overview
Basic concept
Factor analysis model
Statistics associated with factor analysis
Conducting factor analysis
Applications of common factor analysis
Practise data analysis with SPSS
Summary
Questions
Exercises
Notes
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25 Cluster analysis
Objectives
Overview
Basic concept
Statistics associated with cluster analysis
Conducting cluster analysis
Applications of non-hierarchical clustering
Applications of TwoStep clustering
Clustering variables
Practise data analysis with SPSS
Summary
Questions
Exercises
Notes
26 Multidimensional scaling
and conjoint analysis
Objectives
Overview
Basic concepts in MDS
Statistics and terms associated with MDS
Conducting MDS
Assumptions and limitations of MDS
Scaling preference data
Correspondence analysis
Relationship among MDS, factor analysis
and discriminant analysis
Basic concepts in conjoint analysis
Statistics and terms associated with
conjoint analysis
Conducting conjoint analysis
Assumptions and limitations of conjoint analysis
Hybrid conjoint analysis
Practise data analysis with SPSS
Summary
Questions
Exercises
Notes
27 Structural equation modelling
and path analysis
Objectives
Overview
Basic concepts in SEM
Statistics and terms associated with SEM
Foundations of SEM
Conducting SEM
Higher-order CFA
Relationship of SEM to other multivariate
techniques
Application of SEM: first-order factor model
Application of SEM: second-order factor model
Path analysis
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Marketing Research
Software to support SEM
Summary
Questions
Exercises
Notes
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28 Communicating research findings
831
Objectives
Overview
Why does communication of research
findings matter?
Importance of the report and presentation
Preparation and presentation process
Report preparation
Guidelines for graphs
Report distribution
Digital dashboards
Infographics
Oral presentation
Research follow-up
Summary
Questions
Exercises
Notes
832
832
29 Business-to-business (b2b)
marketing research
Objectives
Overview
What is b2b marketing and why is it important?
The distinction between b2b and consumer
marketing
Concepts underlying b2b marketing research
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Implications of the differences between business
and consumer purchases for researchers
The growth of competitive intelligence
The future of b2b marketing research
Summary
Questions
Exercises
Notes
30 Research ethics
Objectives
Overview
Ethics in marketing research
Professional ethics codes
Ethics in the research process
Ethics in data collection
Data analysis
Ethical communication of research findings
Key issues in research ethics: informed consent
Key issues in research ethics: maintaining
respondent trust
Key issues in research ethics: anonymity
and privacy
Key issues in research ethics: sugging
and frugging
Summary
Questions
Exercises
Notes
Glossary
Subject index
Name index
Company index
Supporting resources
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