The paper by Stewart I. Donaldson and Elisa J. Grant-Vallone addresses the issue of self-report bias and mono-method bias in organizational behavior research, which can undermine the validity of findings and hinder theoretical development. The authors propose a conceptual framework to understand the factors influencing employees' motivation to bias their responses to questions posed by researchers. Using a longitudinal, multitrait-multimethod dataset, they illustrate the problem and argue that traditional methods for controlling self-report bias are insufficient. The results highlight the need for developing a theory of method effects and companion analytic techniques to improve the accuracy of psychological research in business settings. The paper emphasizes the importance of accurate measurement in advancing organizational behavior and psychology, given the reliance on self-reports in such research. It also discusses the challenges posed by response bias and common method variance, and suggests that understanding and addressing these biases is crucial for reliable empirical studies.The paper by Stewart I. Donaldson and Elisa J. Grant-Vallone addresses the issue of self-report bias and mono-method bias in organizational behavior research, which can undermine the validity of findings and hinder theoretical development. The authors propose a conceptual framework to understand the factors influencing employees' motivation to bias their responses to questions posed by researchers. Using a longitudinal, multitrait-multimethod dataset, they illustrate the problem and argue that traditional methods for controlling self-report bias are insufficient. The results highlight the need for developing a theory of method effects and companion analytic techniques to improve the accuracy of psychological research in business settings. The paper emphasizes the importance of accurate measurement in advancing organizational behavior and psychology, given the reliance on self-reports in such research. It also discusses the challenges posed by response bias and common method variance, and suggests that understanding and addressing these biases is crucial for reliable empirical studies.