Method Variance in Organizational Research

TLDR

Common method variance is widely believed to inflate same-method correlations, though some sources argue the problem is overstated. The author contests that CMV automatically inflates same-method correlations, labeling this view an urban legend, and recommends abandoning the term in favor of focusing on measurement bias arising from construct–method interactions. The study proposes a comprehensive approach that identifies and controls potential biases through multiple design strategies to exclude them as explanations for observed relationships. Empirical evidence indicates that the method itself does not generate systematic variance that significantly inflates correlations.

Abstract

It has become widely accepted that correlations between variables measured with the same method, usually self-report surveys, are inflated due to the action of common method variance (CMV), despite a number of sources that suggest the problem is overstated. The author argues that the popular position suggesting CMV automatically affects variables measured with the same method is a distortion and oversimplification of the true state of affairs, reaching the status of urban legend. Empirical evidence is discussed casting doubt that the method itself produces systematic variance in observations that inflates correlations to any significant degree. It is suggested that the term common method variance be abandoned in favor of a focus on measurement bias that is the product of the interplay of constructs and methods by which they are assessed. A complex approach to dealing with potential biases involves their identification and control to rule them out as explanations for observed relationships using a variety of design strategies.