That common source bias paper

It’s available on Advance Access. From Ken Meier and Larry O’Toole. Read:

In any design science such as public management, the importance of measurement is central to both scholarship and practice. Research built on measures that are not valid or reliable can generate misleading results and produces little value in the world of practice. This article applies measurement theory to administrators’ self-perceptions of organizational performance, measures commonly used in the literature. Such measures can be prone to common source bias whereby spurious results are highly likely. This article uses measurement theory to show why common source bias can be a problem and then introduces an empirical test for bias based on a data set that includes both perceptual measures of performance and archival measures. The empirical test shows that spurious results are not only common but that they might include as many as 50% of all statistical tests. The article further examines the specific types of questions and measures most likely to generate measurement bias and provides guidelines for scholars conducting research on public organization performance.

This will be part of a special symposium that Ken Meier and I are editing for JPART.