/ANALYSIS Q13brand1r1 Q13brand1r2 Q13brand1r3 Q13brand1r4 Q13brand1r5 Q13brand1r

Question

/ANALYSIS Q13brand1r1 Q13brand1r2 Q13brand1r3 Q13brand1r4 Q13brand1r5 Q13brand1r6 Q13brand1r7     Q13brand1r8 Q13brand1r9 Q13brand1r10 Q13brand1r11 Q13brand1r12 Q13brand1r13 Q13brand1r14 /PRINT INITIAL EXTRACTION ROTATION /FORMAT SORT BLANK(.4) /CRITERIA FACTORS(3) ITERATE(25) /EXTRACTION PC /CRITERIA ITERATE(25) /ROTATION VARIMAX /METHOD=CORRELATION. Total Variance Explained Component Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative % 1 7.115 50.819 50.819 7.115 50.819 50.819 6.833 48.808 48.808 2 2.039 14.563 65.382 2.039 14.563 65.382 1.739 12.42 61.229 3 0.805 5.751 71.133 0.805 5.751 71.133 1.387 9.904 71.133 4 0.684 4.889 76.021 5 0.583 4.162 80.184 6 0.539 3.848 84.032 7 0.466 3.328 87.359 8 0.395 2.82 90.179 9 0.306 2.188 92.367 10 0.273 1.951 94.318 11 0.227 1.625 95.942 12 0.205 1.466 97.408 13 0.188 1.344 98.752 14 0.175 1.248 100 Extraction Method: Principal Component Analysis. Rotated Component Matrixa Component 1 2 3 Q13_13 I love brand 0.892 Q13_1 brand makes me feel valued as a customer 0.865 Q13_14 I am proud to wear/display the brand logo 0.863 Q13_6 I’m willing to pay a bit more to use brand 0.857 Q13_5 I’m willing to go out of my way to use brand 0.856 Q13_4 'I recommend, like, or share brand with friends' 0.849 Q13_2 I am/would be proud to use brand 0.821 Q13_7 I would find it difficult to switch from brand 0.805 Q13_3 brand appreciates my business 0.802 Q13_9 'I would only use brand when it is discounted, on sale, or I have a promotion/coupon' 0.782 Q13_8 I would be happy to use something other than brand if it were available to me 0.691 Q13_11 brand is just one of many companies that is acceptable within the industry 0.502 0.55 Q13_12 I don’t pay a lot of attention to clothing manufacturers 0.913 New Q13_10 I seldom think about brand 0.426 0.56 New Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.a a Rotation converged in 5 iterations. /ANALYSIS Q13brand1r1 Q13brand1r2 Q13brand1r3 Q13brand1r4 Q13brand1r5 Q13brand1r6 Q13brand1r7     Q13brand1r8 Q13brand1r9 Q13brand1r10 Q13brand1r11 Q13brand1r12 Q13brand1r13 Q13brand1r14 /PRINT INITIAL EXTRACTION ROTATION /FORMAT SORT BLANK(.4) /CRITERIA FACTORS(3) ITERATE(25) /EXTRACTION PC /CRITERIA ITERATE(25) /ROTATION VARIMAX /METHOD=CORRELATION. Total Variance Explained Component Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative % 1 7.115 50.819 50.819 7.115 50.819 50.819 6.833 48.808 48.808 2 2.039 14.563 65.382 2.039 14.563 65.382 1.739 12.42 61.229 3 0.805 5.751 71.133 0.805 5.751 71.133 1.387 9.904 71.133 4 0.684 4.889 76.021 5 0.583 4.162 80.184 6 0.539 3.848 84.032 7 0.466 3.328 87.359 8 0.395 2.82 90.179 9 0.306 2.188 92.367 10 0.273 1.951 94.318 11 0.227 1.625 95.942 12 0.205 1.466 97.408 13 0.188 1.344 98.752 14 0.175 1.248 100 Extraction Method: Principal Component Analysis. Rotated Component Matrixa Component 1 2 3 Q13_13 I love brand 0.892 Q13_1 brand makes me feel valued as a customer 0.865 Q13_14 I am proud to wear/display the brand logo 0.863 Q13_6 I’m willing to pay a bit more to use brand 0.857 Q13_5 I’m willing to go out of my way to use brand 0.856 Q13_4 'I recommend, like, or share brand with friends' 0.849 Q13_2 I am/would be proud to use brand 0.821 Q13_7 I would find it difficult to switch from brand 0.805 Q13_3 brand appreciates my business 0.802 Q13_9 'I would only use brand when it is discounted, on sale, or I have a promotion/coupon' 0.782 Q13_8 I would be happy to use something other than brand if it were available to me 0.691 Q13_11 brand is just one of many companies that is acceptable within the industry 0.502 0.55 Q13_12 I don’t pay a lot of attention to clothing manufacturers 0.913 New Q13_10 I seldom think about brand 0.426 0.56 New Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.a a Rotation converged in 5 iterations.

Explanation / Answer

The explanation of the PCA is as follows

Extracting 8 components from the analysis covers about 90% of the information. So instead of choosing all the 14 questions , one can choose only 8 questions and still retain 90% of the information in the questions

Component 1 is related to the following surbey questions

Component 2 is related to the following questions

and component 3 is related to the following survey questions

Q13_13 I love brand Q13_1 brand makes me feel valued as a customer Q13_14 I am proud to wear/display the brand logo Q13_6 I’m willing to pay a bit more to use brand Q13_5 I’m willing to go out of my way to use brand Q13_4 'I recommend, like, or share brand with friends' Q13_2 I am/would be proud to use brand Q13_7 I would find it difficult to switch from brand Q13_3 brand appreciates my business

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