causal research design and...
TRANSCRIPT
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PART TWO
Chapter 6
Causal Research Design
and Experimentation
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Chapter Objectives
After reading this chapter, you should be able to:
Explain the concept of causality as defined in marketing research.
Define and differentiate the to types of validity: internal and external.
Discuss the various extraneous variables that can affect the validity of results obtained through experimentation and explain how the researcher can control extraneous variables.
Compare and contrast the use of laboratory vs field experimentation and experimental vs non-experimental designs in marketing research.
Describe test marketing and its various forms.
Understand why the internal and external validity of field experiments conducted overseas is generally lower in Australia.
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Concept of Causality
Causality may be thought of as understanding a
phenomenon in terms of conditional statements of
the form "if x, then y"
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Some simple examples
If: We increase the
temperature on the
thermostat
We increase advertising
expenditure
We reduce price
Then: The room will get warmer
Sales may increase
Sales may increase
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Scientific meaning of Causality
Marketing effects are caused by multiple
variables
The relationship between cause and effect tends
to be probabilistic
Causality can never be proved
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Conditions for Causality
Concomitant Variation
Extent to which a cause (x) and an effect (y)
occur together or vary together in the way
predicted by the hypothesis under consideration.
Association or relationship between variables
eg. level of education “causes” people to play
golf??
Watch out for spurious correlation
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Conditions for Causality cont.
Time Order of Occurrence of Variables
Causing events (x) must occur either before or
simultaneously with the effect (y); can not occur
afterwards
eg. If we increase promotional expenditure, sales may
increase (not the other way around)
An event in a relationship could be both a cause
and effect
eg. Which is the cause?
Store loyalty or owning a store credit card.
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Conditions for Causality cont.
Absence of other Probabilistic Causal Factors
The variable being investigated should be the only
possible casual explanation
Difficult to rule out all other casual factors
If all the evidence is strong and consistent, it may be
reasonable to conclude that there is a causal
relationship
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Definition
Experiment
manipulating an independent variable to
see how it affects the dependent variable
while also controlling the effect of
additional extraneous variables
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Examples of…
Independent variables
level of advertising expenditure, types of ads,
displays, price changes
Dependent variables
sales, market share, level of customer satisfaction
Extraneous variables
store location, competition, questionnaire used,
respondents
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Validity in Experimentation
Internal Validity
Extent to which the research design accurately
identifies causal relationships
The researcher can rule out rival explanations
[other variables] for the observed results and
conclusions about the relationship
External Validity
Extent to which the cause-and-effect relationships
found in the experiment can be generalised
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Extraneous Variables
History Specific events that are external to the experiment
but occur at the same time as the experiment
These events may affect the dependent variable.
[economic downturn, competitors’ price reductions]
O1 X1 O2
If there is no difference between O1 and O2, we may conclude that X1 (treatment) was ineffective. However, consider if the effects might have been compounded by history.
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Extraneous Variables cont.
Maturation
Changes in the test units over time
[changes in the people who are part of the
experiment, changes to stores (change in layout,
décor, traffic)]
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Extraneous Variables cont.
Test Effects
The effect on the experiment of taking a measure
on the dependent variable before and after the
presentation of the treatment
[The actual act of ‘testing’ may contaminate the
results of the experiment]
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Extraneous Variables cont.
Instrumentation
Changes in the measuring instrument, observers
or scores
[Changing the questionnaire, observers, or
scores during the course of the experiment may
contaminate the results of the experiment]
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Extraneous Variables cont.
Statistical Regression
When test units with extreme scores move closer
to the average during the course of the
experiment
[Respondents’ opinions move to the average
because they are part of the experiment, rather
than as a result to the treatment]
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Extraneous Variables cont.
Selection Bias
Improper assignment of test units to treatment
conditions
[sampling error]
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Extraneous Variables cont.
Mortality
Loss of test units while the experiment is in
progress
[respondents selected no longer wish to
participate]
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Controlling Extraneous Variables
Randomisation
Randomly assigning test units to experimental groups by using random numbers
Matching
Comparing test units on a set of key background variables before assigning them to the treatment
Statistical Control
Measuring the extraneous variables and adjusting for their effects through statistical analysis
Design Control
Use of experiments designed to control specific extraneous variables
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Case: Beauty is in the eye of the beholder
Scientists have found a link between drinking alcohol and perceptions of beauty
80 students were shown colour photographs of 120 male and female students and were asked to rate the aesthetic properties on a 7-point scale from high unattractive to highly attractive
Half the students had drunk up to four units of alcohol, the other half had no alcohol.
The students who had consumed alcohol rated the people in the photographs as more attractive than the student who did not consume alcohol.
Source: http://www.theage.com.au/articles/2002/09/091031115991721.html
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A Classification of
Experimental Design (Figure 6.1)
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Laboratory versus Field Experiments
Laboratory
The independent variable is manipulated and
measures of the dependent variable are taken in
a contrived, artificial setting for the purpose of
controlling the many possible extraneous
variables that may affect the dependent variable
Field
Independent variables are manipulated and
measures of the dependent variable are made on
test units in their natural setting
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Table 6.3 Laboratory versus Field Experiments
Factor Laboratory Field
Environment
Control
Reactive error
Demand artefacts
Internal validity
External validity
Time
Number of units
Ease of implementation
Cost
Artificial
High
High
High
High
Low
Short
Small
High
Low
Realistic
Low
Low
Low
Low
High
Long
Large
Low
High
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Limitations of Experimentation
Time
Cost
Administration
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Test Marketing
An application of a controlled experiment, done
in limited but carefully selected parts of the
marketplace called test markets.
Classifications
Standard market test
Controlled test market
Simulated test market
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Test Marketing cont.
Criteria for the selection of test markets
Be large enough to produce meaningful projections
(ie.at least 2% of the potential actual population).
Be representative:
demographically
with respect to product consumption behavior
with respect to media usage
with respect to competition
Be relatively isolated in terms of media and physical
distribution.
Have normal historical development in the product class
Have marketing research and auditing services available
Not be over-tested