Measurement error in research on human resources and firm performance: How much error is there and how does it influence effect size estimates?

Studies of the relationship between human resource (HR) practices and firm performance typically use a single respondent to assess firm level HR practices or HR effectiveness. However, previous research in other substantive areas suggests that rater differences are a potentially important source of measurement error. We demonstrate analytically the potential consequences of both random and systematic measurement error in research on HR and firm performance. However, our main focus is on random error and we show how generalizability theory can be applied to obtain better estimates of reliability by simultaneously recognizing multiple sources (e.g., items, raters) of random measurement error. These more inclusive reliability estimates, in turn, offer the possibility of more precisely quantifying substantive relationships in the KR and firm performance literature. In our sample, reliabilities (as estimated by generalizability coefficients) for single-rater assessments of HR variables were generally below .50. This degree of measurement error, if present in substantive studies on HR and firm performance, could lead to considerable bias, given that an unstandardized regression coefficient is corrected for measurement error in the independent variable by dividing by its reliability coefficient (not its square root). We also found only limited convergent validity between HR and line managers ratings of a second type of HR measure, HR effectiveness. In general, our findings suggest that future researchers need to devote greater attention to measurement error and construct validity issues. Our study provides an example of how generalizability theory can be useful in this pursuit.