Method Variance in Organizational Research
质疑共同方法变异（CMV）自动膨胀同方法测量变量间相关性的普遍观点，认为这是对事实的扭曲和过度简化，并建议用更复杂的测量偏差视角取代CMV概念。
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.