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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)
Sources
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.
  • References (31)
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References31
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This article investigates in two ways the use and reporting of marker variables to detect common method variance (CMV) in organizational research. First, a review of 398 empirical articles and 41 unpublished dissertations that employ marker variables indicates that authors are not reporting adequate information regarding marker variable choice and use, are choosing inappropriate marker variables, and are possibly making errors in their assessment of CMV effects. Second, two data sets are present...
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