Manipulating Common Method Variance via Experimental Conditions

Research data collected from single respondents may raise concerns regarding common method variance (CMV), which is believed to threaten the validity of findings. The primary concern that CMV can inflate substantive relationships, such they appear statistically significant when are not. Thus, understanding nature critical, especially one considers popularity—and sometimes necessity—of using self-report data. examining has found conflicting evidence about impact CMV. Researchers who believe influences findings have proposed solutions combat any real or perceived potential bias, including changing survey instructions and marker variables, but few studies examined efficacy these approaches. purpose this study examine techniques an experimental design. To conduct experiment, multiple versions a survey, vary in their use remedial approaches, utilized collect data, resulted 1,069 usable responses. design was based on faking literature included intended induce reduce levels Further, two different variables used determine degree create psychological separation variables. Correlation analysis measurement invariance analyze This posits that, if substantial for approaches effective, then will differ surveys incorporate do Results indicate differences conditions, meaning regardless variable, item correlations remained similar. results likely due minimal CMV, given methods correction did not significantly influence research These implications researchers support at least its remedies, alter However, null conclusions, spite appropriate statistical power, warrant future