Attempt Only Four Case Study
CASE – 1 Consumer Perception of High-end IT Education
This case study of recent origin (2001), illustrates the use of free-response questions which permit respondents to give unstructured answers. The responses are given in the form of excerpted quotes from the study at the end of the case. The entire study was bigger in scope and results. These reported results are only for the purpose of illustration and do not constitute the complete analysis.
BACKGROUND
SSI, a computer education centre, has added Internet to its portfolio. Now SSI plans to re-launch its course called Internet in its updated form. The course includes ASP, XML, WAP, .NET and BLUETOOTH, the last one being offered only by SSI’s Internet.
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• Student (SSI)
Question
1. Write don a brief summary of all the answers given above. How does this differ from the analysis of structured-response questions?
CASE – 2 Chi-square Test
Methodology
1. A fictitious data set consisting of thirty respondents was created. The data was mainly constructed to find the relationship between the dependent and independent variable. Age was taken as the independent variable and choice of a drink as dependent variable. Six brands of soft drinks were considered as the different choices for the respondents.
2. The age group coded into six categories as 1 to 6 and the brands of soft drinks were coded into six categories and the codings are as follows:
(
3. Chi-square test has been used to cross-tabulate and to understand the relationship between the independent and the dependent variable.
4. Calculation of contingency coefficient and the lambda asymmetric coefficient is done to find the strength of the association between the two variables.
5. Sample size is taken as thirty.
6. Analysis of cross-tabulation.
7. SPSS software package for the cross tabulation analysis.
Problem
This is a bivariate problem. The basic intention of the problem is to understand the relationship between AGE and BRAND PREFERENCE of different brands of soft drinks.
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In a Chi-square test, for a 90 per cent confidence level, if the significance level is greater than or equal to 0.1, it signifies that there is no association between the two variables in the cross-tabulation and if significance level is less than 0.1, then it signifies that there is a significance relationship between the selected variables.
The result of the cross-tabulation
From the output tables, the Chi-square test read a significance level of 0.08325 at 90 percent confidence level. For 90 per cent, significance level is 0.1, that is (1-0.9), so the above result shows that at 0.08 (which is less than 0.1), there is a significant relationship between the two variables. At 95 per cent confidence level, significance level being 0.05, and the above output giving a significance level of 0.08 which is greater than 0.05, there is no relationship between the variables:
If contingency coefficient value is greater than +0.5 then the variables are strongly associated. In the above case the contingency coefficient value being 0.6 which is greater than 0.5, hence the variables are strongly associated.
The asymmetric lambda value (with DRINKCODE dependent) 0.21739 means that 21.7% of error is reduced in predicting brand preference when age is known.
From the above result we can conclude that there is a significant relationship between AGE (independent variable) and BRAND PREFERENCE (dependent variable), of the respondents.
Thus we can conclude that the age of the respondent plays an important role in the purchasing intention of a particular brand of soft drink.
Question
Case 2: Conduct Chi-square test to cross-tabulate and to understand the relationship between the independent and the dependent variable. Also calculate contingency coefficient and the lambda asymmetric coefficient to find the strength of the association between the two variables. Take Sample size as thirty. Analysis of cross-tabulation using SPSS software package would be required.
CASE – 3 Tamarind Menswear
Given below is a preliminary questionnaire for retailers and consumers of a recently launched menswear brand. Can you list down the research objectives for both questionnaire? Can you modify the given questionnaires to a final draft?
TAMARIND QUESTIONNAIRE FOR RETAILERS
1. Do you have Tamarind? Yes/No
2. What do you think about it?
3. Is there place in the market for one more readymade garment company?
4. What kind of products does Tamarind have? Are they good?
5. Is it a threat to any existing brand? If yes, which one?
6. If it is not a available, what is your view about advertising so heavily before the product is launched?
7. Are people coming and asking for Tamarind?
8. The range of clothes with the retailer.
9. Price range.
10. Name of the shop and so on.
TAMARIND QUESTIONNAIRE FOR CONSUMERS
1. Which ads do you recall?
2. Which garment ads do you recall?
3. Have you seen the Tamarind ad?
4. What do you remember from the ads?
5. Do you like the ad? Why?
6. What is the main message?
7. What kind of clothes are Tamarind?
8. What do you think will be the price range?
9. Will you buy it? Why?
CASE – 4 Logistics Regression
A pharmaceutical firm that developed particular drug for women wants to understand the characteristics that cause some of them to have an adverse reaction to a particular drug. They collect data on 15 women who had such a reaction and 15 who did not. The variables measured are:
1. Systolic Blood Pressure
2. Cholesterol Level
3. Age of the person
4. Whether or not the woman was pregnant (1 = yes)
The dependent variable indicates if there was an adverse reaction (1 = yes)
TABLE 1
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Question:
Case 4: Using logistic regression proof that particular drug for women has characteristics that cause some of them an adverse reaction to a particular drug.
CASE – 5 Conjoint Analysis
Problem
XYZ paint company identified the attributes which are important to their customers and also classified each of the attributes into their levels. Based on this, they want to use the technique of conjoint analysis to determine from a potential customer’s point of view, how important each attribute is to him. They also want to know how much utility the customer derives from a given combination of these levels of attributes. It also helps to understand the feasible offerings from the marketer’s point of view. The three important attributes identified for the paint are:
1. Life—this is the number of years the paint coat lasts.
2. Price—the price of one litre of paint.
3. Colour—the colour of paint.
The levels of the above mentioned attributes are as follows:
• Life—3 years, 4 years, 5 years
• Price—Rs. 50 per litre, Rs. 60 per litre, Rs. 70 per litre
• Colour—Green, Blue, Cream
.....
Individual Attributes
The difference in utility with the change of one level in one attribute can also be checked. For the life of 3 years to 4 years, there is increase in utility value of 7.22 units, but the next level, that is, 4 years to 5 years has an increase in utility of 6.89.
Similarly, increase in price from Rs. 50/litre to Rs. 60/litre induces a utility drop of 5.55, whereas from Rs. 60/litre to Rs. 70/litre there is an increase in utility of 5.44.
Finally, colour green to colour blue induces 3.99 drop in utility. Next, from colour blue to colour cream there is an increase in utility of 3.11.
Question:
Case 5: Use conjoint analysis to determine from a potential customer’s point of view, how important each attribute is to him. Also determine how much utility the customer derives from a given combination of these levels of attributes. The attributes are life, price and colour.
CASE 6
A recent case study for a cellular phone service provider in Chennai listed its research objectives and methodology (including sampling plan) for a marketing research study as follows:
SKCELL, A CELLULAR OPERATOR/STUDY ON VALUE ADDED SERVICES LIKE SMS (SHORT MESSAGING SERVICE), VOICE MAIL, AND SO ON
Research Objectives
To find out
• whether people actually use the mobile phone just for talking
• to what extent the mobile phone is used for its VAS (Value Added Services)
• factors influencing choice of service provider
• awareness of Skycell’s improved coverage
Locations Covered
Chennai city and the suburbs
Methodology
Primary data:
Through questionnaires
Sample Composition
• Mobile phone users
• Business pesons
• Executives
• Youth
Sample size: 75
Age group: 18 – 45 years
Questions:
1. Can you add to methodology section?
2. Distribute the sample of 75 among the different categories of respondents mentioned under “Sample Composition”.
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