Common methods variance detection in business research

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...

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Veröffentlicht in:Journal of business research 2016-08, Vol.69 (8), p.3192-3198
Hauptverfasser: Fuller, Christie M., Simmering, Marcia J., Atinc, Guclu, Atinc, Yasemin, Babin, Barry J.
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container_end_page 3198
container_issue 8
container_start_page 3192
container_title Journal of business research
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creator Fuller, Christie M.
Simmering, Marcia J.
Atinc, Guclu
Atinc, Yasemin
Babin, Barry J.
description 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.
doi_str_mv 10.1016/j.jbusres.2015.12.008
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subjects CMB
CMV
Error
Harman's one-factor test
Measurement
Scale models
Studies
Surveys
Variances
title Common methods variance detection in business research
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