st: Common method bias

["Foong, Awie (RIC)" <Awie.Foong@watsonwyatt.com>]

This is more a statistical and methodological issue rather than STATA. I am hoping to hear the advice from quantitative research experts. 

I am working on an old dataset collected through questionnaire survey. The survey asked the respondents about their perception of their job and company practices. I ran a Harman's one-factor test to check for common method bias according to Podsakoff and Organ (1986). The results of the unrotated factor analysis show six factors with Eigenvalue more than 1. However, the first unrotated factor has an Eigenvalue of 25.1 and accounted for 67+ACU- of the variance. The pattern matrix of the factor loadings show that all items (variables) load higher on the first factor than on the other factors. This, according to Podsakoff, is the evidence of common method bias.
 
I would like to ask:
1. If there is any known criteria to access what is the amount of variance explained by the first factor before the measurement model is considered as a single-factor model?
2. More importantly, what can we do to remedy the situation, AFTER the data collection phrase is over? Is there any post-hoc methods that I can use (even at the expense of dropping some variables)?
 
Many thanks,
Awie Foong

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