1. Chapter Three
Research Design

2. Research Design: Definition
A research design is a framework or blueprint for conducting the marketing research project.
It details the procedures necessary for obtaining the information needed to structure or solve marketing research problems.

3. Components of a Research Design
Define the information needed (Chapter 2)
Design the exploratory, descriptive, and/or causal phases of the research (Chapters 3 - 7)
Specify the measurement and scaling procedures (Chapters 8 and 9)
Construct and pretest a questionnaire (interviewing form) or an appropriate form for data collection (Chapter 10)
Specify the sampling process and sample size (Chapters 11 and 12)
Develop a plan of data analysis (Chapter 14)

4. A Classification of Marketing Research Designs
Single Cross-Sectional Design
Multiple Cross-Sectional Design
Fig. 3.1
Research Design
Conclusive Research Design
Exploratory Research Design
Descriptive Research
Causal Research
Cross-Sectional Design
Longitudinal Design

5. Exploratory research design
Exploratory research is used in situations where the problem may have to be defined more precisely, relevant courses of action identified, hypotheses formulated, or additional insights gained before an approach can be developed.

6. Exploratory research design
The owner of The Cupcake King has many, many ideas for improving the bakery's sales, but isn't sure which will work.
They think increasing the flavors of cupcakes the bakery sells will bring in more customers, but know they need more information.
They intend to conduct ER to investigate whether expanding their cupcake selection will lead to an increase in sales, or if there is a better idea.

7. Methods of Exploratory Research
Survey of experts (discussed in Chapter 2)
Pilot surveys (discussed in Chapter 2)
Secondary data analyzed in a qualitative way (discussed in Chapter 4)
Qualitative research (discussed in Chapter 5)
Pilot survey tend to be less structured than large scales survey in that they generally contain more open-ended questions and the sample size is much smaller.

8. Uses of Exploratory Research
Formulate a problem or define a problem more precisely
Identify alternative courses of action
Develop hypotheses
Isolate key variables and relationships for further examination
Gain insights for developing an approach to the problem
Establish priorities for further research

9. Conclusive research designs
Conclusive research would be used to test specific hypotheses, examine specific relationships, or make predictions.
Conclusive research is typically more formal and structured than exploratory research.
It is based on large and representative samples and the data obtained are subjected to quantitative analysis.
Conclusive research may either describe or uncover causal relationships that may be generalised to large populations

10. Descriptive and Causal research
Descriptive research is used to describe something, usually market characteristics or functions.
For example, determining the average age of purchasers of your product.
Causal research is used to obtain evidence regarding cause-and-effect relationships.
For example, determining if increased advertising spending has led to an increase in sales.

11. Six W’s of descriptive research
Descriptive research design requires a clear specification of the six W’s of the research:
1.Who: who should be considered?
2.Where: where should the respondents be contacted to obtain the required information?
3.When: when should the information be obtained from the respondents?
4.What: what information should be obtained from the respondents?
5.Why: why are we obtaining information from the respondents?
6.Way: the way in which we are going to obtain information from the respondents.

12. Use of Descriptive Research
To describe the characteristics of relevant groups, such as consumers, salespeople, organizations, or market areas
To estimate the percentage of units in a specified population exhibiting a certain behavior
To determine the perceptions of product characteristics
To determine the degree to which marketing variables are associated
To make specific predictions

13. Methods of Descriptive Research
Secondary data analysis (discussed in Chapter 4)
Primary data: Surveys, Observations (Chapter 6)

14. Situations where causal research could be used
Causal research is appropriate to use when the purposes are to understand which variables are the cause and which variables are the effect, and to determine the nature of the functional relationship between the causal variables and the effect to be predicted.
understand which variables are the cause (independent variables) and which variables are the effect (dependent variables) of marketing phenomena;
determine the nature of the relationship between the causal variables and the effect to be predicted;
test hypotheses.

15. Exploratory & Conclusive Research Differences
Objective:
Character-istics:
Findings/ Results:
Outcome:
To provide insights and understanding
Information needed is defined only loosely. Research process is flexible and unstructured. Sample is small and non-representative. Analysis of primary data is qualitative
Tentative
Generally followed by further exploratory or conclusive research
To test specific hypotheses and examine relationships
Information needed is clearly defined. Research process is formal and structured. Sample is large and representative. Data analysis is quantitative
Conclusive
Findings used as input into decision making
Exploratory
Table 3.1

16. A Comparison of Basic Research Designs
Objective:
Characteristics:
Methods:
Discovery of ideas and insights
Flexible, versatile
Often the front end of total research design
Expert surveys
Pilot surveys
Case studies
Secondary data:
qualitative analysis
qualitative research
Describe market characteristics or functions
Marked by the prior formulation of specific hypotheses
Preplanned and structured design
quantitative analysis
Surveys
Panels
Observation and other data
Determine cause and effect relationships
Manipulation of independent variables, effect on dependent variables
Control mediating variables
Experiments
Exploratory
Descriptive
Causal
Table 3.2

17. Cross-Sectional Designs
In single cross-sectional designs, there is only one sample of respondents and information is obtained from this sample only once.
In multiple cross-sectional designs, there are two or more samples of respondents, and information from each sample is obtained only once. Often, information from different samples is obtained at different times.
Cohort analysis consists of a series of surveys conducted at appropriate time intervals, where the cohort serves as the basic unit of analysis. A cohort is a group of respondents who experience the same event within the same time interval.

18. Cohort analysis
Cohort analysis is of special interest because it is used to predict changes in consumers' behaviour or attitudes over a period of time. It reveals the shared history and subtle effects of the ageing of consumers upon their behaviour and attitudes.

19. Longitudinal Designs
A fixed sample (or samples) of population elements is measured repeatedly on the same variables
A longitudinal design differs from a cross-sectional design in that the sample or samples remain the same over time

20. Relative Advantages and Disadvantages of Longitudinal and Cross-Sectional Designs
Evaluation Criteria
Cross-Sectional Design
Longitudinal Design
Detecting Change
Large amount of data collection
Accuracy
Representative Sampling
Response bias - +
Note: A “+” indicates a relative advantage over the other design, whereas a “-” indicates a relative disadvantage.
Table 3.4

21. Potential sources of error can affect a research design
The total error is the variation between the true mean value in the population of the variable of interest and the observed mean value obtained in the marketing research project.

22. Potential Sources of Error in Research Designs
Surrogate Information Error
Measurement Error
Population Definition Error
Sampling Frame Error
Data Analysis Error
Respondent Selection Error
Questioning Error
Recording Error
Cheating Error
Inability Error
Unwillingness Error
Fig. 3.2
Total Error
Non-sampling Error
Random Sampling Error
Non-response Error
Response Error
Interviewer Error
Respondent Error
Researcher Error

23. Potential sources of error can affect a research design
The potential sources of error can be broadly categorised into two classes: Random Sampling errors. Sampling error arises when the selected sample is not perfectly representative of the population it represents. In this case the mean value for the sample differs from the actual population mean, because particular types of participant have been over- or under-represented. Non-sampling errors. Non-sampling error can be classified as non-response error and response error. Non-response error occurs when some of the participants do not respond.

24. Potential sources of error can affect a research design
Response errors are those that arise due to errors made by the researchers, interviewers and participants, such as the wrong formulation of the questionnaire, mis-recording of answers, hesitancy or unwillingness to provide answers.