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Manipulating Common Method Variance Via Experimental Conditions, Alison Wall, Marcia Simmering, Christie Fuller, Brian Waterwall

IT and Supply Chain Management Faculty Publications and Presentations

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 is that CMV can inflate substantive relationships, such that they appear statistically significant when they are not. Thus, understanding the nature of CMV is critical, especially when one considers the popularity—and sometimes necessity—of using self-report data. Research examining CMV has found conflicting evidence about the impact of CMV. Researchers who believe CMV influences findings have proposed solutions to combat any real or perceived potential bias, including changing survey instructions and using marker variables, but …