Comparing the efficacy of policy-capturing weights and direct estimates for predicting job choice

Jerel E Slaughter, Erin M. Richard, James H. Martin

Research output: Contribution to journalArticle

24 Citations (Scopus)

Abstract

When studying applicants' job attribute preferences, researchers have used either direct estimates (DE) of importance or regression-derived statistical weights from policy-capturing (PC) studies. Although each methodology has been criticized, no research has examined the efficacy of weights derived from either method for predicting choices among job offers. In this study, participants were assigned to either a DE or PC condition, and weights for 14 attribute preferences were derived. Three weeks later, the participants made choices among hypothetical job offers. As predicted, PC weights outperformed DE weights when a noncompensatory strategy was assumed, and DE weights outperformed PC weights when a compensatory strategy was assumed. Implications for researchers' choice of methodology when studying attribute preferences are discussed.

Original languageEnglish (US)
Pages (from-to)285-314
Number of pages30
JournalOrganizational Research Methods
Volume9
Issue number3
DOIs
StatePublished - Jul 2006

Fingerprint

Efficacy
Job choice
Policy capturing
Methodology

Keywords

  • Job choice
  • Policy capturing
  • Recruitment
  • Research methods

ASJC Scopus subject areas

  • Management of Technology and Innovation
  • Strategy and Management
  • Decision Sciences(all)

Cite this

Comparing the efficacy of policy-capturing weights and direct estimates for predicting job choice. / Slaughter, Jerel E; Richard, Erin M.; Martin, James H.

In: Organizational Research Methods, Vol. 9, No. 3, 07.2006, p. 285-314.

Research output: Contribution to journalArticle

@article{8fb9ade5d29c477fb549dc4e52f3b4d8,
title = "Comparing the efficacy of policy-capturing weights and direct estimates for predicting job choice",
abstract = "When studying applicants' job attribute preferences, researchers have used either direct estimates (DE) of importance or regression-derived statistical weights from policy-capturing (PC) studies. Although each methodology has been criticized, no research has examined the efficacy of weights derived from either method for predicting choices among job offers. In this study, participants were assigned to either a DE or PC condition, and weights for 14 attribute preferences were derived. Three weeks later, the participants made choices among hypothetical job offers. As predicted, PC weights outperformed DE weights when a noncompensatory strategy was assumed, and DE weights outperformed PC weights when a compensatory strategy was assumed. Implications for researchers' choice of methodology when studying attribute preferences are discussed.",
keywords = "Job choice, Policy capturing, Recruitment, Research methods",
author = "Slaughter, {Jerel E} and Richard, {Erin M.} and Martin, {James H.}",
year = "2006",
month = "7",
doi = "10.1177/1094428105279936",
language = "English (US)",
volume = "9",
pages = "285--314",
journal = "Organizational Research Methods",
issn = "1094-4281",
publisher = "SAGE Publications Inc.",
number = "3",

}

TY - JOUR

T1 - Comparing the efficacy of policy-capturing weights and direct estimates for predicting job choice

AU - Slaughter, Jerel E

AU - Richard, Erin M.

AU - Martin, James H.

PY - 2006/7

Y1 - 2006/7

N2 - When studying applicants' job attribute preferences, researchers have used either direct estimates (DE) of importance or regression-derived statistical weights from policy-capturing (PC) studies. Although each methodology has been criticized, no research has examined the efficacy of weights derived from either method for predicting choices among job offers. In this study, participants were assigned to either a DE or PC condition, and weights for 14 attribute preferences were derived. Three weeks later, the participants made choices among hypothetical job offers. As predicted, PC weights outperformed DE weights when a noncompensatory strategy was assumed, and DE weights outperformed PC weights when a compensatory strategy was assumed. Implications for researchers' choice of methodology when studying attribute preferences are discussed.

AB - When studying applicants' job attribute preferences, researchers have used either direct estimates (DE) of importance or regression-derived statistical weights from policy-capturing (PC) studies. Although each methodology has been criticized, no research has examined the efficacy of weights derived from either method for predicting choices among job offers. In this study, participants were assigned to either a DE or PC condition, and weights for 14 attribute preferences were derived. Three weeks later, the participants made choices among hypothetical job offers. As predicted, PC weights outperformed DE weights when a noncompensatory strategy was assumed, and DE weights outperformed PC weights when a compensatory strategy was assumed. Implications for researchers' choice of methodology when studying attribute preferences are discussed.

KW - Job choice

KW - Policy capturing

KW - Recruitment

KW - Research methods

UR - http://www.scopus.com/inward/record.url?scp=33745036517&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33745036517&partnerID=8YFLogxK

U2 - 10.1177/1094428105279936

DO - 10.1177/1094428105279936

M3 - Article

AN - SCOPUS:33745036517

VL - 9

SP - 285

EP - 314

JO - Organizational Research Methods

JF - Organizational Research Methods

SN - 1094-4281

IS - 3

ER -