Common methods variance detection in business research

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

Research output: Contribution to journalArticlepeer-review

1994 Scopus citations

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.

Original languageEnglish
Pages (from-to)3192-3198
Number of pages7
JournalJournal of Business Research
Volume69
Issue number8
DOIs
StatePublished - 1 Aug 2016

Keywords

  • CMB
  • CMV
  • Error
  • Harman's one-factor test
  • Measurement
  • Surveys

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