"Best practices" research: A methodological guide for the perplexed

Like many applied fields, public administration has a long-running love affair with the idea of "best practices" research. Although occasional reviews and critical examinations of approaches to best practices research have appeared in the literature (Overman and Boyd 1994), very little critical examination and reflection have been devoted to core methodological issues surrounding such work. The purpose of this article is twofold. First, we critically examine the underlying assumptions associated with "best practices research" in order to distill an appropriate set of rules to frame research designs for best practice studies. Second, we review several statistical approaches that provide a rigorous empirical basis for identification of "best practices" in public organizations - methods for modeling extreme behavior (i.e., iteratively weighted least squares and quantile regression) and measuring relative technical efficiency (data envelopment analysis [DEA]).