Common methods variance detection in business research

被引:1820
作者
Fuller, Christie M. [1 ]
Simmering, Marcia J. [2 ]
Atinc, Guclu [3 ]
Atinc, Yasemin [3 ]
Babin, Barry J. [4 ]
机构
[1] Louisiana Tech Univ, Comp Informat Syst, POB 10318, Ruston, LA 71270 USA
[2] Louisiana Tech Univ, Management, POB 10318, Ruston, LA 71270 USA
[3] Texas A&M Univ Commerce, POB 3011, Commerce, TX 75429 USA
[4] Louisiana Tech Univ, Mkt, POB 10318, Ruston, LA 71270 USA
关键词
CMV; CMB; Measurement; Error; Surveys; Harman's one-factor test; ORGANIZATIONAL RESEARCH; ERROR; PERSPECTIVES; REVIEWERS; BEHAVIOR; BIAS;
D O I
10.1016/j.jbusres.2015.12.008
中图分类号
F [经济];
学科分类号
02 ;
摘要
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. (C) 2015 Elsevier Inc. All rights reserved.
引用
收藏
页码:3192 / 3198
页数:7
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