A New Perspective on Method Variance: A Measure-Centric Approach

• Published in: Journal of management Vol. 45; no. 3; pp. 855 - 880
• Main Authors: Spector, Paul E., Rosen, Christopher C., Richardson, Hettie A., Williams, Larry J., Johnson, Russell E.
• Format: Journal Article
• Language: English
• Published: Los Angeles, CA SAGE Publications 01-03-2019; Sage Publications Ltd
• Subjects: Bias; Intelligence tests; Simulation; psychometrics; construct validity; common-method variance; uncommon-method variance; method bias
• ISSN: 0149-2063; 1557-1211
• DOI: 10.1177/0149206316687295

A widespread methodological concern in the organizational literature is the possibility that observed results are due to the influence of common-method variance or mono-method bias. This concern is based on a conception of method variance as being produced by the nature of the method itself, and therefore, variables assessed with the same method would share common-method variance that inflates observed correlations. In this paper, we argue for a more complex view of method variance that consists of multiple sources that affect each measured variable in a potentially unique way. Shared sources among measures (common-method variance) act to inflate correlations, whereas unshared sources (uncommon-method variance) act to attenuate correlations. Two empirical examples, one from a simulation study and the other from a single-source survey, are presented to illustrate the complex action of multiple sources of method variance. A five-step approach is suggested whereby a theory of the measure is generated for each measured variable that would inform strategies to control for method variance by assessing and modeling the actions of identified method variance sources.