Common methods variance detection in business research

Published on Aug 1, 2016in Journal of Business Research
· DOI :10.1016/j.jbusres.2015.12.008
Christie M. Fuller9
Estimated H-index: 9
(La. Tech: Louisiana Tech University),
Marcia J. Simmering11
Estimated H-index: 11
(La. Tech: Louisiana Tech University)
+ 2 AuthorsBarry J. Babin38
Estimated H-index: 38
(La. Tech: Louisiana Tech University)
The issue of common method variance (CMV) has become almost legendary among today's business researchers. In this manuscript, a literature review shows many business researchers take steps to assess potential problems with CMV, or common method bias (CMB), but almost no one reports problematic findings. One widely-criticized procedure assessing CMV levels involves a one-factor test that examines how much common variance might exist in a single dimension. This paper presents a data simulation demonstrating that a relatively high level of CMV must be present to bias true relationships among substantive variables at typically reported reliability levels. The simulation data overall suggests that at levels of CMV typical of multiple item measures with typical reliabilities reporting typical effect sizes, CMV does not represent a grave threat to the validity of research findings.
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