Common methods variance detection in business research

Christie M. Fuller, Marcia J. Simmering, Guclu Atinc, Yasemin Atinc and Barry J. Babin

Journal of Business Research, 2016, vol. 69, issue 8, 3192-3198

Abstract: 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.

Keywords: CMV; CMB; Measurement; Error; Surveys; Harman's one-factor test (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (288)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:69:y:2016:i:8:p:3192-3198

DOI: 10.1016/j.jbusres.2015.12.008

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