1. Exploratory Research Design
Secondary Data
Qualitative Research
Survey & Observation
Experiments
Företagsakademin, Henriksgatan 7 FIN Åbo

2. Primary vs. Secondary data
CollectionPurpose
For the purpose at hand
For other problems
CollectionProcess
Very involved
Rapid and easy
Collection
Cost
High
Relatively low
Time
Long
Short
Primary data: originated by the researcher for the specific purpose addressing the research problem
Secondary data: data collected for some other purpose than the problm at hand
Företagsakademin, Henriksgatan 7 FIN Åbo

3. Advantages and uses of SD
Identifying the problem
Better define the problem
Develop and approach to the problem
Formulate an appropriate research design
Answering certain research Qs and test some hypotheses
Interpret primary data more insightfully
Rule:
Examination of available SD is a prerequisite to the collection of primary data. Start with SD; collect PD only after the SD source yield marginal returns
Företagsakademin, Henriksgatan 7 FIN Åbo

4. Criteria for evaluating SD
Specifications/Methodology
Data collection method
Response rate
Quality of data
Sampling technique
Sample size
Questionnaire design
Field work
Data analysis
Data should be systematic, valid, and generalizable to the problem at hand.
Error/Accuracy
Examine errors in: Approach, Research design, Sampling, Data collection, Data analysis and Reporting
Assess accuracy by comparing data from different sources.
Currency
Time lag between collection and publication. Frequency of updates
Census data is periodically updated by syndicated firms
Företagsakademin, Henriksgatan 7 FIN Åbo

5. Criteria for evaluating SD
Objective: Why were the data collected, i.e. determine the relevance of the data
Nature: Definition of key variables, units of measurement, categories used, relationships examined, i.e. reconfigure the data to increase their usefulness if possible.
Dependability: Expertise, credibility, reputation, and trustworthiness of the source, i.e. Data should be obtained from an original rather than an acquired source
Företagsakademin, Henriksgatan 7 FIN Åbo

6. Företagsakademin, Henriksgatan 7 FIN-20500 Åbo
Classification of SD
Internal
Ready to use
Requires further processing
External
Published materials
guides
directories
indexes
nongov’t statistical data
Census data
Computerized databases
Online/offline, internet DB, bibliograhic DB
Syndicated services
surveys
panels
scanner services
audits
industry services
Företagsakademin, Henriksgatan 7 FIN Åbo

7. A classification of Marketing research data
Företagsakademin, Henriksgatan 7 FIN Åbo

8. Primary Data: Qualitative versus Quantitative Research
Qualitative research
An unstructured, exploratory research methodology based on small samples that provide insights and understanding of the problem setting
Quantitative research
A research methodology that seeks to quantify the data and, typically applies some form of statistical analysis
Qualitative research procedures:
Direct, indirect
Focus group: an interview conducted by a trained moderator, a small group, unstructured
Association technique word associations
Completion techniques
sentence completion
story completion
Construction techniques
picture response
cartoon test
Expressive techniques
Företagsakademin, Henriksgatan 7 FIN Åbo

9. Focus Groups, Depth Interviews, projective techniques
Criteria
Focus Groups
Depth Interviews
Projective techniques
Structure
High
Medium
Low
Probing of respondent
Moderator bias
Low to High
Interpretation bias
Subconscious info
Medium to high
Innovative info
Sensitive info
Unusual behavior No
Some
Yes
Usefulness
Highly useful
Useful
Somewhat
Företagsakademin, Henriksgatan 7 FIN Åbo

10. Qualitative versus Quantitative Research
Qualitative Research
Quantitative Research
Objective
To gain a qualitative understanding of the underlying reasons and motivations
To quantify the data and generalize the results from the sample to the population of interest
Sample
Small number of non-representative cases
Large number of representative cases
Data collection
Unstructured
Structured
Data analysis
Non-statistical
Statistical
Outcome
Develop an initial understanding
Recommend a final course of action
Företagsakademin, Henriksgatan 7 FIN Åbo

11. Descriptive Research Design: Survey & Observation
Survey: A structured questionnaire given to respondents and designed to elicit specific information
Structured data collection: Use of formal questionnaire that presents questions in a prearranged order
Fixed-alternative questions: Respondents are required to choose from a set of predetermined answers
Survey Methods:
Telephone;
traditional, computer-assisted
Personal interviewing;
In-home, Mall Intercept, computer-assisted
Mail Interviewing;
mail, mail panel
Electronic Intrvieweing;
, Internet
Företagsakademin, Henriksgatan 7 FIN Åbo

12. Descriptive Research Design: Survey & Observation
Observation: the recording of behavioral patterna of people, objects, and events in a systematic manner to obtain information about the phenomenon of interest
Structured observation: observation techniques where the researcher defines the behavior to be observed and the methods by which they will be measured
Unstructured observations: A researcher monitors all aspects of the phenomenon without specifying the details in advance
Natural observations: observing behavior as it takes place in the environment
Contrived observation: the behavior is observed in an artificial environment
Disguised vs. undisguised observation
Företagsakademin, Henriksgatan 7 FIN Åbo

13. Causal Research Design: Experimentation
Causality: Ordinary meaning and scientific meaning:
Ordinary:
X is the only cause of Y
X must always lead to Y
It is possible to prove that X is a cause of Y
Scientific:
X is only one of a number of possible causes of Y
The occurence of X makes the occurence of Y more probable
We can never prove the X is a cause of Y. At best we can infer that X is a cause of Y
Företagsakademin, Henriksgatan 7 FIN Åbo

14. Causal Research Design: Experimentation
Concomitant Variation: The extent to which a cause X and an effect Y occur together is predicted by the hypothesis under consideration
Purchase of Fashion Clothing Y is influenced by education X
The absence of initial evidence of concomitant variation does not imply there is no causation
Företagsakademin, Henriksgatan 7 FIN Åbo

15. Can we prove high education cause high purchase?
Education X
Purchase of Fashion Clothing Y
High
Low
Total
363 (73%)
137 (27%)
500 (100%)
322 (64%)
178 (36%)
Företagsakademin, Henriksgatan 7 FIN Åbo

16. Företagsakademin, Henriksgatan 7 FIN-20500 Åbo
What about Income?
Low Income
High Income
Purchase
Educa-tion
High
Low
Total
122
(61%) 78
(39%)
200
(100%)
241
(80%) 59
(20%)
300
171
(57%)
129
(43%)
151
(76%) 49
(24%)
Företagsakademin, Henriksgatan 7 FIN Åbo

17. Time order of occurence of variables
The causing event must occur either before or simultaneously with the effect. It cannot occur afterwards!
An effect cannot be produced by an event that occur after the effect has taken place!
But: A variable can be both the cause and the effect in a causal relationship!
Customer who shop frequently in a store is likely to have a credit card for that store. Also customers who have the card is likely to shop there more frequently
Företagsakademin, Henriksgatan 7 FIN Åbo

18. Definitions and Concepts
Independent variables (treatments) (iv) are variables that are manipulated by the researcher and whose effects are measured and compared. These can be price levels, package designs, advertising themes, etc.
Test unit are individuals, organizations, or other entities whose response to the independnt variables or treatments is being examined. Test units may include consumers, stores, geographic areas
Företagsakademin, Henriksgatan 7 FIN Åbo

19. Definitions and Concepts
Extraneous or confounding variables are all variables other than the independent variables that affect the response of the test units. These variables can confound the dv. measures in a way that weakens or invalidates the results, e.g. store size, location, competitive effort. These variables have to be controlled for!
Dependent variables (dv) are the variables that measure the effect of the independent variable on the test unit. These variables may include, sales, profits, market share, brand, consumer choice, intentions to buy, etc.
Företagsakademin, Henriksgatan 7 FIN Åbo

20. Definitions and Concepts
Experiment is formed when the researcher manipulates one or more iv. and measures their effect on one or more dv. while controlling for the effect of confounding variables
Experimental design is a set of procedures specifying
the test units and how they are to be divided into homogeneous subsamples
what iv is to be manipulated
what dv are to be measured
how the confounding variabls are to be controlled
Företagsakademin, Henriksgatan 7 FIN Åbo

21. Företagsakademin, Henriksgatan 7 FIN-20500 Åbo
Validity
Internal validity is a measure of accuracy of an experiment. It measures whether an iv actually causes the effects on the dv
External validity determines whether the cause-and-effect found in the experiment can be generalized
Företagsakademin, Henriksgatan 7 FIN Åbo

22. Confounding variables
History: events that are external to the experiment but occur a the same time
Maturation: changes in the test unit due to passage of time
Testing effect:
main testing effect
interactive testing effect
Main testing effect: when a prior observation affects the latter. Affects the internal validity
interactive testing effect: prior measurement affects the test unit’s response to the iv. Affects the external validity
Företagsakademin, Henriksgatan 7 FIN Åbo

23. Confounding variables
Statistical regression: when respondents with extreme scores move closer to the average, i.e. the change in attitude is attributable to statistical regression rather than the treatment
Selection bias: Improper assignment of test units to treatment
Mortality: loss of a test unit while the experiment is in progress
Företagsakademin, Henriksgatan 7 FIN Åbo

24. Controlling confounding variables
Randomization
Matching
Statistical control: measuring the confounding variable and adjusting for their effects
Design control
Företagsakademin, Henriksgatan 7 FIN Åbo

25. Classification of experimental designs
One-shot case
study
One group
pre-posttest
Static group
Pretest-posttest
control group
Posttest-only
Solomon
Four group
Time Series
Multiple
Randomized
Blocks
Latin Square
Factorial
Företagsakademin, Henriksgatan 7 FIN Åbo

26. Classification of experimental designs
Preexperimental design do not control for confounding factors by randomization
True experimental designs the researcher can randomly assign test units to experimental groups and assign treatment randomly to experimental groups
quasi-experimental design is like the true experimental design BUT without full experimental control
Företagsakademin, Henriksgatan 7 FIN Åbo

27. Limitations of experimentation
Time
Cost
Administration
Application: Test marketing
controlled test market
simulated test market
Företagsakademin, Henriksgatan 7 FIN Åbo