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MARK5811 AMR2
Research Design: Quantitative,
Qualitative, and Mixed Methods
T3-2023
Lecture structure for this week
• Course issues and questions
• Last topic: AMR1: Overview & Marketing Research Process
• Research design
• Design of quantitative studies
• Design of qualitative studies
• Designing and collecting qualitative data
• Mixed methods: Design, benefits, and types
• Next topic: AMR3: Secondary data analysis
• Lecture summary
Overview
• Generally speaking, research methods are split broadly into
quantitative and qualitative methods.
• Quantitative research is explaining phenomena by collecting
numerical data that are analysed using mathematically based
methods (in particular statistics).
• Qualitative research seeks to answer questions about why and
how people behave in the way that they do. It provides in-depth
information about human behaviour.
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Design of quantitative studies
Marketing research goal/objective
To decide whether Burger King should focus on
providing efficient customer service or friendly
customer service.
Efficient Customer
Service
Friendly Customer
Service
Customer Satisfaction
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Operationally define variables
Gives meaning to a construct or a variable by setting out the
activities or ‘operations’ that are necessary to measure it.
Define and operationalise variables
• Efficient Customer Service: Related to easy, simple, fast, error free,
reducing the amount of wasted inputs
➢ How long does it take for you to complete the order?
➢ How long does it take for you to receive the order?
• Friendly Customer Service: Kind and pleasant
➢ Are customer service staff taking time to understand your need?
➢ Are customer service staff helpful when you have questions or require
special service?
• Customer Satisfaction: Actual performance of the product > Expectation of
the product performance
➢ Does the actual performance of Burger King meet your expectation?
Student/Customer Loyalty
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Independent, Dependent, Mediating, and
Moderating Variables
• A variable is a property that can take different values.
• To identify why events occur. These causes are called
independent variables (IV) and the resulting effects, dependent
variables (DV).
• Mediating variable: Variable that causes mediation in the
dependent and the independent variables. It explains the
relationship between the dependent variable and the
independent variable.
• Moderating variable: Variable that affects the strength of the
relationship between a dependent and independent variable.
Customer Satisfaction
Customer satisfaction value: 1-5: e.g.
Very Dissatisfied (1) to Very Satisfied (5)
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Service Quality Customer Loyalty
Independent Variable
(IV)
Service Quality Customer Loyalty
Dependent Variable
(DV)
Customer
Satisfaction
Customer
Loyalty
Mediator/Mediating
variable
Service Quality
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Competitive
offering
Customer Satisfaction Customer Loyalty
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A hypothesis
• It is a speculative statement of the relation between two or
more variables.
• Describes a research question in a testable format which
predicts the nature of the answer.
H1. Job demands have significant positive impacts on burnout.
H2. Job resources have significant negative impacts on burnout.
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Validity
• In discussing validity, McBurney and White (2009) pose the
interesting analogy of using a measurement of hat size to
determine intelligence. You could measure someone’s hat size,
say, every hour and always come up with the same result. The
test, then, is reliable. However, it is not valid, because hat size
has nothing to do with what is being measured.
• To ensure validity, a research instrument must measure what it
was intended to measure, i.e. the research instrument subject
area and operationally defined subject areas must exactly
match.
Reliability
Reliability is the overall consistency or stability of a measure. A
measure is said to have a high reliability if it produces similar
results under consistent conditions.
Reliability - Internal Reliability
• It seeks to measure the extent to which the items on the
instrument ‘hang together’. Are the individual scale items
measuring the same construct?
• Internal reliability is measured by Cronbach’s alpha test which
calculates the average of all split-half reliability coefficients.
An alpha coefficient varies between 1 (perfect internal
reliability) to 0 (no internal reliability). As a rule of thumb a
figure of .7 or above is deemed acceptable.
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Service climate describes the shared process of collective
sensemaking about the quality of service delivery. It
encourages staff to provide quality service and satisfy
customers
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Design of qualitative studies
Qualitative Research
• The role of the qualitative researcher is to gain a deep, intense
and ‘holistic’ overview of the context under study.
• The types of data gathering tools and resources used by
qualitative researchers, including the use of semi-structured
interviews, observation, focus groups and the analysis of
materials such as documents, photographs, video recordings
and other media.
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Characteristics of qualitative research
Most qualitative research involves a number of characteristics:
• It is conducted through intense contact within a ‘field’ or real
life setting. Qualitative research has advantages over
quantitative research in that researchers are closer to the fields
or settings they are trying to research.
• Themes that emerge from the data are often reviewed with
informants for verification.
Collecting Qualitative Data (1)
• Interviews can be used as either the main instrument of data
collection, or in conjunction with observation, document
analysis or some other type of data gathering technique.
• Observations: Observational data is primarily descriptive of
settings, people, events and the meanings that participants
assign to them.
Collecting Qualitative Data (2)
• Photographs and other visual data: Photographs or other
visual data such as video or film recordings are also sources of
qualitative data. They can be used to stimulate an interview or
encourage a participant to produce a narrative to accompany
and expand upon the photographic evidence.
• Unobtrusive data: Organizations contain a rich unobtrusive
data in the form of documents such as company reports,
business plans, written statements.
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Criticisms of qualitative research
• ‘Unscientific’: Lacks reproducibility – the research is so based
in or confined to one context that it lacks generalizability.
• Qualitative research is so personal to the researcher that
another researcher might use the same data to come to
radically different conclusions.
Generalisability describes the extent to which
research findings can be applied to settings
other than that in which they were originally
tested.
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Designing qualitative research (1)
• Allow other researchers to inspect the procedures through
which the research has been conducted.
• Use individual cases to build working hypotheses/propositions
that can be tested in subsequent cases through the use of
multiple case studies, e.g., as more similar or contrasting cases
are used, we can justify, through replication, the stability of the
findings. Rather than generalize, we can see if the findings
from Context A can be transferred to Context B.
Designing qualitative research (2)
• For most qualitative approaches, reliability is improved by
triangulation, i.e. gathering information from multiple sources or
by using multiple data gathering tools.
• For interview data, reliability can be increased through the
training of interviewers and through the use of standardized
interview schedules.
• For observations, researchers also need to be trained before they
enter the field. Reliability can also be improved through the use of
pre-designed observation schedules.
• Use thick descriptions to provide evidence for making judgements
about similarities between cases.
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Welté, Jean-Baptiste, Julien Cayla, and Eileen Fischer (2022). “Navigating contradictory
logics in the field of luxury retailing”, Journal of Retailing, Available online,
https://doi.org/10.1016/j.jretai.2021.11.002.
Welté, Jean-Baptiste, Julien Cayla, and Eileen Fischer (2022). “Navigating contradictory logics in the field of
luxury retailing”, Journal of Retailing, Available online, https://doi.org/10.1016/j.jretai.2021.11.002.
Digital Research Methods
• Digital research methods comprise a range of approaches used
for collecting primary data, and include the use of the Internet
for conducting interviews, surveys and observations. For
example: e.g., using discussion forums, instant messages.
• Social media (e.g., Facebook, Twitter, YouTube) offer a varied
but also complex landscape for research.
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Mixed Methods
Mixed methods design
• Mixed method designs are those that include at least one
quantitative method and one qualitative method.
• Mixed methods is the collection or analysis of both
quantitative and qualitative data in a single study in which the
data are collected concurrently or sequentially.
How two, seemingly opposite approaches to
research can in fact support and complement
each other?
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(Finalist for the Journal of Service Research Best Article Award for 2013)
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Benefits of mixed methods designs (1)
• Triangulation
➢Combining methods allows for one method compensating for
the weaknesses or blind spots of the other. Triangulation
which combines quantitative and qualitative methods can
focus on a single case, in which the same people complete a
questionnaire and are also interviewed. The answers from
both data sets are combined and compared.
• Complementarity
➢Quantitative and qualitative methods are combined to
measure overlapping but also different elements of a
phenomenon.
Benefits of mixed methods designs (2)
• Development
➢The results of one method are used to inform the
development of the second.
• Initiation
➢ In contrast to triangulation which seeks to combine
methods towards convergence, initiation uses mixed
methods to uncover new perspectives and contradictions.
• Expansion
➢Expansion uses mixed methods to broaden and widen the
range of a study.
Looking at mixed methods research critically
• Collecting both quantitative and qualitative data can be
expensive and time consuming.
• There is still considerable confusion concerning how mixed
methods findings can be integrated.
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Types of mixed methods design (1)
• Qualitative then quantitative
➢Occurs when the results of a qualitative study are used to
inform the quantitative research phase.
➢This design is used when relatively little or nothing is
known about the research setting or research problems. In
such a situation, it would be unfeasible and impractical to
design a questionnaire, since the constructs being measured
are either unknown or not sufficiently understood. The
qualitative study, then, explores, identifies and can provide
clarity about the kinds of variables requiring further
investigation.
Types of mixed methods design (2)
• Quantitative then qualitative
➢Occurs when the findings of a quantitative study are used
to develop the qualitative stage.
➢A quantitative study could be used to identify important
themes that qualitative fieldwork could then be used to gain
an in-depth understanding of the themes.
Perceived service quality in higher education
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Types of mixed methods design (3)
• Quantitative and qualitative concurrently
➢Mixed designs do not always have to be interdependent.
➢Quantitative and qualitative elements can be conducted
quite independently and not in any particular order, they
could be carried out concurrently.
➢Different methods could be used to address the same
research question or focus on different aspects of the
research.
In Sum
Mixed methods approaches can be based upon different types of
research question, sampling procedures, data collection
methods or approaches to data analysis.
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Next Topic: AMR3 – Secondary Data Analysis
• Secondary data: Advantages and disadvantages
• Different types of secondary data
• Using secondary data
• Ethical considerations