I have administered a questionnaire to respondents asking about customers' adoption of technology. I want to do an exploratory principal components factor analysis in Stata to form constructs from a couple of questions (in line with the existing literature).
The variables that I want to construct are perceived usefulness, perceived ease of use, perceived risk with product (PRP), etc. and I am comparing customers from two countries: The Netherlands (n=63) and Bulgaria (n=101).
I designed items based on the research literature. So I expected that there would be no problems with the factor analysis; i.e., all items would have high factor loadings on a single factor. I have obtained cronbach's alpha which is 0.7 for all factors and 0.6 for usefulness for the Dutch customers, which is OK. The factor analysis is fine for most of the factors and most of items load most on one single factor as suggested by literature.
The problem is that for PRP I got 4/5 factors for Bulgarians and 6/7 factors for Dutch which are actually different constructs compared to PRP for Bulgarians (13 factor loadings for PRP). I also have similar problem with Subjective norm (SN).
- When items do not fit into one factor is it possible to just take the means of such items? *
- Or is there something else I should do?
- Can you also provide me with some reference?