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

Stuart Bretschneider, Frederick J. Marc-Aurele, Jiannan Wu

Research output: Contribution to journalArticle

38 Citations (Scopus)

Abstract

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]).

Original languageEnglish (US)
Pages (from-to)307-323
Number of pages17
JournalJournal of Public Administration Research and Theory
Volume15
Issue number2
DOIs
StatePublished - Apr 2005
Externally publishedYes

Fingerprint

best practice
efficiency analysis
examination
public administration
research planning
love
data analysis
Best practice
regression

ASJC Scopus subject areas

  • Sociology and Political Science
  • Public Administration
  • Marketing

Cite this

"Best practices" research : A methodological guide for the perplexed. / Bretschneider, Stuart; Marc-Aurele, Frederick J.; Wu, Jiannan.

In: Journal of Public Administration Research and Theory, Vol. 15, No. 2, 04.2005, p. 307-323.

Research output: Contribution to journalArticle

@article{62e7c254cfd643dca3f0224293eb5f61,
title = "{"}Best practices{"} research: A methodological guide for the perplexed",
abstract = "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]).",
author = "Stuart Bretschneider and Marc-Aurele, {Frederick J.} and Jiannan Wu",
year = "2005",
month = "4",
doi = "10.1093/jopart/mui017",
language = "English (US)",
volume = "15",
pages = "307--323",
journal = "Journal of Public Administration Research and Theory",
issn = "1053-1858",
publisher = "Oxford University Press",
number = "2",

}

TY - JOUR

T1 - "Best practices" research

T2 - A methodological guide for the perplexed

AU - Bretschneider, Stuart

AU - Marc-Aurele, Frederick J.

AU - Wu, Jiannan

PY - 2005/4

Y1 - 2005/4

N2 - 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]).

AB - 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]).

UR - http://www.scopus.com/inward/record.url?scp=25844439322&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=25844439322&partnerID=8YFLogxK

U2 - 10.1093/jopart/mui017

DO - 10.1093/jopart/mui017

M3 - Article

AN - SCOPUS:25844439322

VL - 15

SP - 307

EP - 323

JO - Journal of Public Administration Research and Theory

JF - Journal of Public Administration Research and Theory

SN - 1053-1858

IS - 2

ER -