MARKETING RESEARCH ASSIGNMENT Harvard Case Solution & Analysis

MARKETING RESEARCH ASSIGNMENT Case Solution

Question 1

a).The Bartlett’s Test of Sphericity has been performed on the nine attitude variables and this has been performed as the variable reduction method to reduce the nine variables into a smaller set of the artificial variables, which have the highest variance on the original values. This is basically a factor analysis which is used to ensure that whether the questions that have been asked relate to the construct which is intended to be measured or not. If we interpret the output of this test, then first of all we need to have sampling adequacy for all the nine variables which is 0.784 which is higher and this means that factor analysis should now be able to yield reliable and distinct factors.

            The p value of this test is 0.000 therefore, it could be concluded that there is some relationship in the variables which we intent to include in our analysis. Overall, Bartlett’s test is highly significant and factor analysis is appropriate. Next the eigenvalues give us the variance, which is explained by each of the linear component and the percentage of variance has also been shown. It could be seen that the percentage of variance for the first few factors is higher as compared to the others.

b)   This output table presents the factor loading's for each of the nine attitude variables and how these variables are weighted for each actor. This also shows us the correlation between the factor and the variables.For instance, the higher the value of the load, the more it is relevant in describing the dimensionality of the factor. Here three factors have been retained since they have eigen values over 1. In this table, enjoy Buy, buy Healthy, buy Fresh and store Conv define factor 1. hardly Cook, good store Far and buy want define factor 2 whereas, eat out and comp Price define factor 3. Finally, uniqueness shows the variance of the variable which is unique to that variable and not shared with the other variables. For instance, most of those respondents that prefer to eat out rather than cooking have a higher unique variance and this is not shared with the other variables. On the other hand, the lower unique variance could be seen for the food in grocery stores with all the other variables.

c).d).  t he first table in this output shows the total number of the N variables and the number of the N values corresponding to each of the three clusters. Cluster 2 and Cluster 3 have higher values, which are highly relevant to our marketing concept. Table 2 in this output shows the weight age of each of the variable with regard to each of the factor and also the correlations between the variables and the factors. This information would now be used to perform the multiple regression analysis on our model by determining the impact of these factors on the dependent variable which is ‘liking’.

e).            The test which has been conducted in this part is the Multiple Regression Analysis where the independent variables are the three factors generated in STATA and the dependent variable is the GSS store concept labeled as liking.  Moreover, it could also be seen that the impact of factor 2 and factor 3 variables in liking is significant and negative which could be seen by their coefficients’ value and the significant value of 0.000. ...........................

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