1. Descriptive and Causal
Chapter 6
Descriptive and Causal
Research Designs

2. Descriptive Research
Research design in which the major emphasis is on determining the frequency with which something occurs or the extent to which two variables covary.

3. Descriptive research rests on one or more specific hyphotheses.
Whereas an exploratory design of marketing research is characterized by its flexibility, descriptive design can be considered rigid.
Descriptive study of marketing research require a clear specification of the who, what, when, where, why, and how of the research.

4. USE OF DESCRIPTIVE RESEARCH
Transparency 6.1
Use of Descriptive Research
USE OF DESCRIPTIVE RESEARCH
To describe the characteristics of certain groups. For example, based on information gathered from known users of our particular product, we might attempt to develop a profile of the “average user” with respect to income, sex, age, educational level, and so on.
2. To estimate the proportion of people in a specified population who behave in a certain way. We might be interested, say, in estimating the proportion of people within a specified radius of a proposed shopping complex who would shop at the center.
3. To make specific predictions. We might be interested in
predicting the level of sales for each of the next five years
so that we could plan for the hiring and training of new
sales representatives.

5. Sample Survey True Panel Longitudinal Omnibus Panel Descriptive
Transparency 6.2
Classification of Descriptive Studies
Descriptive
Studies
Cross Sectional
Sample Survey
Longitudinal
Omnibus Panel
True Panel

6. Longitudinal study
Investigation involving a fixed sample of elements that is measured repeatedly through time.
Cross-sectional study
Investigation involving a sample of elements selected from the population of interest which are measured at a single point in time.

7. There are two types of panels;
True panels: A fixed sample of respondents who are measured repeatedly over time with respect to the same variables.
Omnibus panel; fixed sample of respondents who are measured repeatedly over time but on variables that change from measurement to measurement.

8. (Cross-sectional study)
Transparency 6.8
Sample Survey
SAMPLE SURVEY
(Cross-sectional study)
Cross-sectional study in which the sample is selected to be representative of the target population and in which the emphasis is on the generation of summary statistics such as averages and percentages.
Surveys can be designed to capture a vide variety of information on many diverse topics and subjects.
Disadvantages of the sample survey; Superficial analysis of the subject, High Cost and Technical sophistication

9. Blue collar and use the product Blue collar and don’t use the product
Example: Management thinks that occupation is an important factor determining the consumption of its product.
Proposition: “ White collar workers are more apt to use the product then the blue collar workers.”
White collar and use the product
White collar and don’t use the product
Blue collar and use the product
Blue collar and don’t use the product

10. Causal research
Sometime to be able to explain some events / problems cause –and- effect hypotheses may be required.
For example, if a price change is planned, marketing manager may want to test the hypothesis :
“A 5 percent increase in the price of the product will have no significant effect on the amount of the product that customers will buy” Or
If a new package design is planned:
“A redesign of the package will improve consumer attidues toward the product”.
This situation represents a problem for causal analysis.
For testing cause –and – effect relationships between two variables, causal research is arranged.

11. Concept of Causality The concept of causality is complex.
X- is the cause of another thing (Y) suggests that there is a single cause of an event.
If a change in X, causes Y to change in the hypothesized way, then we are tempted to say X causes Y.

12. Experiments are defined as studies in which conditions are controlled so that one or more independent variable(s) can be manipulated to test a hypothesis about a dependent variable.
In other words, in experimental research, the researcher manipulates the independent variable and then measures the effect of this manipulation on the dependent variable.

13. The key principle of experimental work is manipulation of a treatment variable ( say X), followed by observation of response variable (say Y).
If a change in X, causes Y to change in the hypothesized way, then we are tempted to say X causes Y.

14. What are causal relationships?
A concern with causality appears throughout marketing decision making. For example,
What effect have recent price increases had on product class sales?
Does the number of sales calls per month affect the size of the order placed?
Underlying the research questions given is the need to understand a causal relationship between an action and a probable outcome. These could be actions taken in the past or predictions about future actions.

15. Given the causation concept, that a change in one variable will produce a change in another, it is reasonable to conclude that, if two variables causally linked, they should be associated. Thus, an association between attitude (A) and behavior(B) is evidence of a causal relationship.
Attitude behavior
If a causal link between two variables is thought to exist , a reasonable question is :
Which variable is the causal (independent) variable and which is the “caused” (dependent) variable?

16. One approach to determining the direction of causation is to draw on logic and previous theory. In this context it is useful to observe whether one of the variables is relatively fixed and unalterable.
Variables like sex, age, and income are relatively permanent. If, for example, an association is found between age and attendance at rock concert, it would be unrealistic to claim that attendance at rock concerts causes people to be young. In this case age could not be a “caused” variable because it is fixed in this context.
Asecond approach is to consider the fact that there is usually a time lag between cause and effect. (ıf such a time lag can be postulated , the causal variable should have a positive association with the effect variable lagged in time.)

17. Copyright © 2001 by Harcourt, Inc.
Transparency 6.9
Types of Evidence That Supports a Causal Inference
Concomitant variation--evidence of the extent to which X and Y occur together or vary together in the way predicted by the hypothesis
Time order of occurrence of variables--evidence that shows X occurs before Y
Elimination of other possible causal factors—evidence that allows the elimination of factors other than X as the cause of Y
X -- the presumed cause
Y -- the presumed effect
Copyright © 2001 by Harcourt, Inc.
All Rights Reserved

18. Laboratory Experiment
Transparency 6.10
Types of Experiments
Laboratory Experiment
Research investigation in which investigator
creates a situation with exact conditions so as
to control some, and manipulate other,
variables
Experiment
Scientific investigation in which an
investigator manipulates and controls
one or more independent variables and
observes the dependent variable for
variation concomitant to the manipulation
of the independent variables
Field Experiment
Research study in a realistic situation in
which one or more independent variables
are manipulated by the experimenter under
as carefully controlled conditions as the
situation will permit

19. Transparency 6.11
Internal Validity
INTERNAL VALIDITY
One criterion by which an experiment is evaluated; the criterion focuses on obtaining evidence demonstrating that the variation in the criterion variable was the result of exposure to the treatment, or experimental, variable.

20. Transparency 6.12
External Validity
EXTERNAL VALIDITY
One criterion by which an experiment is evaluated; the extent, to what populations and settings, to which the observed experimental effect can be generalized.

21. MARKET TEST (test-marketing)
Transparency 6.13
Market test (test-marketing)
MARKET TEST (test-marketing)
A controlled experiment done in a limited but carefully selected sector of the marketplace; its aim is to predict the sales or profit consequences, either in absolute or relative terms, of one or more proposed marketing actions.

22. CRITICAL PROBLEMS OF TEST MARKETING
Transparency 6.14
Critical Problems of Test Marketing
CRITICAL PROBLEMS OF TEST MARKETING
COST
TIME
CONTROL

23. Transparency 6.15
Relationship Among the Various Types of Test Markets
Simulated
Test Market
Promising
Not Promising
Abort
Controlled
Test Market
Promising
Not Promising
Abort
Standard
Test Market
Not Promising
Abort
Promising
National
Rollout