Accounting for common method variance in cross-sectional research designs

Cross-sectional studies of attitude-behavior relationships are vulnerable t o the inflation of correlations by common method variance (CMV). Here. a mo del is presented that allows partial correlation analysis to adjust the obs erved correlations for CMV contamination and determine if conclusions about the and practical significance of a predictor have been influenced by the presence of CMV. This method also suggests procedures for designing questio nnaires to increase the precision of this adjustment.