Analysis and Strategy formulation (Retail case)

Permap-Attribute based- Session 11-12

Amrita Bazray

14005

Today we used the attribute based perceptual mapping for the Retail case in class. For the above exercise we first chose an Objective and the attributes.

What is an attribute?  An attribute is some aspect of an object.  It may be called a factor, characteristic, trait, property, component, quantity, variable, dimension (not a good choice in

MDS work, but occasionally seen), parameter, and so forth.  The attributes should be presented in a form where each is normalized  (standardized) to some kind of range or standard deviation, but  Permap can do the normalizing internally if so desired.  An attribute in one study may be an object in another study.  It is all a matter of perspective and interest.

Parking Active Attributes Control

If your data file contains attribute information, just below the functional shortcut buttons

will be a box that shows the "active attributes."  These attributes are used to calculate the

dissimilarities by using any of several built-in attribute-to-dissimilarity functions. 

Double clicking on an attribute moves it to the attribute parking lot and the dissimilarities

are recalculated using only the remaining active attributes.  A parked (inactive) attribute can be

brought back into the active set by double clicking on it in the attribute parking lot.

For the retail case we chose Store as the objective and converted into Nominal variable for using in SPSS. Then we identified 6 attributes which are scale variables to get a custom table like below:

		Price satisfaction	Variety satisfaction	Organization satisfaction	Service satisfaction	Item quality satisfaction	Overall satisfaction
		Mean	Mean	Mean	Mean	Mean	Mean
Store	Store 1	3	3	3	3	3	3
	Store 2	3	3	3	3	3	3
	Store 3	3	3	3	3	3	3
	Store 4	3	3	3	3	3	3

The various as you can see are

1.      Price

2.     Variety

3.     Organization satisfaction

4.     Service satisfaction

5.     Item quality

6.     Overall satisfaction

Once we copy the custom table on excel we get data mean to 2 decimal points and move ahead to get the PERMAP.

Title=store satisfaction

NObjects=4

nattributes=6

attributelist

Store1  3.01     3.08     3.25     3.18     3.17     2.99

Store2  3.21     3.10     2.94     2.88     3.31     3.00

Store3  3.16     3.09     3.23     3.30     3.08     3.31

Store4  2.97     3.04     3.31     3.01     3.08     3.07

After getting the data in this format we tried to analyze the objective and the attributes in the given way:

We see the arrow heads once we do MAP EVALUATION and click “All Archive Vectors” which represents the 6 attributes as arrows and the store which lies towards the head of the arrow reflects that it is affected the most by that attribute.

Here although it isn’t clear store 3 is affected the most by attribute 6 i.e. overall satisfactions from the store that the people get. We can park some attributes also to have a clear picture of what all factors affect the store.

Thus we see using PERMAP we can analyze a given variable, the objective variable and see what all factors affect that objective.