Best Practice Recommendations for Designing and Implementing Experimental Vignette Methodology Studies

We describe experimental vignette methodology (EVM) as a way to address the dilemma of conducting experimental research that results in high levels of confidence regarding internal validity but is challenged by threats to external validity versus conducting nonexperimental research that usually maxi...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Organizational research methods 2014-10, Vol.17 (4), p.351-371
Hauptverfasser: Aguinis, Herman, Bradley, Kyle J.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 371
container_issue 4
container_start_page 351
container_title Organizational research methods
container_volume 17
creator Aguinis, Herman
Bradley, Kyle J.
description We describe experimental vignette methodology (EVM) as a way to address the dilemma of conducting experimental research that results in high levels of confidence regarding internal validity but is challenged by threats to external validity versus conducting nonexperimental research that usually maximizes external validity but whose conclusions are ambiguous regarding causal relationships. EVM studies consist of presenting participants with carefully constructed and realistic scenarios to assess dependent variables including intentions, attitudes, and behaviors, thereby enhancing experimental realism and also allowing researchers to manipulate and control independent variables. We describe two major types of EVM aimed at assessing explicit (i.e., paper people studies) and implicit (i.e., policy capturing and conjoint analysis) processes and outcomes. We offer best practice recommendations regarding the design and implementation of EVM studies based on a multidisciplinary literature review, discuss substantive domains and topics that can benefit from implementing EVM, address knowledge gaps regarding EVM such as the need to increase realism and the number and diversity of participants, and address ways to overcome some of the negative perceptions about EVM by pointing to exemplary articles that have used EVM successfully.
doi_str_mv 10.1177/1094428114547952
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1686442431</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sage_id>10.1177_1094428114547952</sage_id><sourcerecordid>1686442431</sourcerecordid><originalsourceid>FETCH-LOGICAL-c439t-4af1a0165e68c812cc0607cf98aa971c8d4c5fadf4b98a1f64406b0679c4a9b53</originalsourceid><addsrcrecordid>eNp1kLtPwzAQxi0EEqWwM1piYQnYiR3HI48ClYpAvNbIdc4hVRoH25Hof4-jMqBKTPf6fZ_uDqFTSi4oFeKSEslYWlDKOBOSp3toQjlPE8FSvh_zOE7G-SE68n5FCM1SLifIXIMP-NkpHRoN-AW0Xa-hq1RobOexsQ7fgm_qrulqrLoKz9d9C5EIY2P23YNrxkq1-CNSEALgRwiftrKtrTf4NQxVA_4YHRjVejj5jVP0fjd7u3lIFk_385urRaJZJkPClKGK0JxDXuiCplqTnAhtZKGUFFQXFdPcqMqwZWxRkzNG8iXJhdRMySXPpuh869s7-zXE08p14zW0rerADr6keRE1KctoRM920JUdXBe3ixThBRMpk5EiW0o7670DU_bxYOU2JSXl-Phy9_FRkmwlXtXwx_Q__gfCjYM8</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1605847249</pqid></control><display><type>article</type><title>Best Practice Recommendations for Designing and Implementing Experimental Vignette Methodology Studies</title><source>SAGE Complete</source><creator>Aguinis, Herman ; Bradley, Kyle J.</creator><creatorcontrib>Aguinis, Herman ; Bradley, Kyle J.</creatorcontrib><description>We describe experimental vignette methodology (EVM) as a way to address the dilemma of conducting experimental research that results in high levels of confidence regarding internal validity but is challenged by threats to external validity versus conducting nonexperimental research that usually maximizes external validity but whose conclusions are ambiguous regarding causal relationships. EVM studies consist of presenting participants with carefully constructed and realistic scenarios to assess dependent variables including intentions, attitudes, and behaviors, thereby enhancing experimental realism and also allowing researchers to manipulate and control independent variables. We describe two major types of EVM aimed at assessing explicit (i.e., paper people studies) and implicit (i.e., policy capturing and conjoint analysis) processes and outcomes. We offer best practice recommendations regarding the design and implementation of EVM studies based on a multidisciplinary literature review, discuss substantive domains and topics that can benefit from implementing EVM, address knowledge gaps regarding EVM such as the need to increase realism and the number and diversity of participants, and address ways to overcome some of the negative perceptions about EVM by pointing to exemplary articles that have used EVM successfully.</description><identifier>ISSN: 1094-4281</identifier><identifier>EISSN: 1552-7425</identifier><identifier>DOI: 10.1177/1094428114547952</identifier><language>eng</language><publisher>Los Angeles, CA: SAGE Publications</publisher><subject>Best practice ; Causality ; Conduction ; Confidence ; Conjoint analysis ; Dependent variables ; Design engineering ; Literature reviews ; Methodology ; Perception ; Realism ; Research methodology ; Studies ; Validation studies ; Validity</subject><ispartof>Organizational research methods, 2014-10, Vol.17 (4), p.351-371</ispartof><rights>The Author(s) 2014</rights><rights>Copyright SAGE PUBLICATIONS, INC. Oct 2014</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c439t-4af1a0165e68c812cc0607cf98aa971c8d4c5fadf4b98a1f64406b0679c4a9b53</citedby><cites>FETCH-LOGICAL-c439t-4af1a0165e68c812cc0607cf98aa971c8d4c5fadf4b98a1f64406b0679c4a9b53</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://journals.sagepub.com/doi/pdf/10.1177/1094428114547952$$EPDF$$P50$$Gsage$$H</linktopdf><linktohtml>$$Uhttps://journals.sagepub.com/doi/10.1177/1094428114547952$$EHTML$$P50$$Gsage$$H</linktohtml><link.rule.ids>314,776,780,21798,27901,27902,43597,43598</link.rule.ids></links><search><creatorcontrib>Aguinis, Herman</creatorcontrib><creatorcontrib>Bradley, Kyle J.</creatorcontrib><title>Best Practice Recommendations for Designing and Implementing Experimental Vignette Methodology Studies</title><title>Organizational research methods</title><description>We describe experimental vignette methodology (EVM) as a way to address the dilemma of conducting experimental research that results in high levels of confidence regarding internal validity but is challenged by threats to external validity versus conducting nonexperimental research that usually maximizes external validity but whose conclusions are ambiguous regarding causal relationships. EVM studies consist of presenting participants with carefully constructed and realistic scenarios to assess dependent variables including intentions, attitudes, and behaviors, thereby enhancing experimental realism and also allowing researchers to manipulate and control independent variables. We describe two major types of EVM aimed at assessing explicit (i.e., paper people studies) and implicit (i.e., policy capturing and conjoint analysis) processes and outcomes. We offer best practice recommendations regarding the design and implementation of EVM studies based on a multidisciplinary literature review, discuss substantive domains and topics that can benefit from implementing EVM, address knowledge gaps regarding EVM such as the need to increase realism and the number and diversity of participants, and address ways to overcome some of the negative perceptions about EVM by pointing to exemplary articles that have used EVM successfully.</description><subject>Best practice</subject><subject>Causality</subject><subject>Conduction</subject><subject>Confidence</subject><subject>Conjoint analysis</subject><subject>Dependent variables</subject><subject>Design engineering</subject><subject>Literature reviews</subject><subject>Methodology</subject><subject>Perception</subject><subject>Realism</subject><subject>Research methodology</subject><subject>Studies</subject><subject>Validation studies</subject><subject>Validity</subject><issn>1094-4281</issn><issn>1552-7425</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><recordid>eNp1kLtPwzAQxi0EEqWwM1piYQnYiR3HI48ClYpAvNbIdc4hVRoH25Hof4-jMqBKTPf6fZ_uDqFTSi4oFeKSEslYWlDKOBOSp3toQjlPE8FSvh_zOE7G-SE68n5FCM1SLifIXIMP-NkpHRoN-AW0Xa-hq1RobOexsQ7fgm_qrulqrLoKz9d9C5EIY2P23YNrxkq1-CNSEALgRwiftrKtrTf4NQxVA_4YHRjVejj5jVP0fjd7u3lIFk_385urRaJZJkPClKGK0JxDXuiCplqTnAhtZKGUFFQXFdPcqMqwZWxRkzNG8iXJhdRMySXPpuh869s7-zXE08p14zW0rerADr6keRE1KctoRM920JUdXBe3ixThBRMpk5EiW0o7670DU_bxYOU2JSXl-Phy9_FRkmwlXtXwx_Q__gfCjYM8</recordid><startdate>20141001</startdate><enddate>20141001</enddate><creator>Aguinis, Herman</creator><creator>Bradley, Kyle J.</creator><general>SAGE Publications</general><general>SAGE PUBLICATIONS, INC</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TA</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>JG9</scope></search><sort><creationdate>20141001</creationdate><title>Best Practice Recommendations for Designing and Implementing Experimental Vignette Methodology Studies</title><author>Aguinis, Herman ; Bradley, Kyle J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c439t-4af1a0165e68c812cc0607cf98aa971c8d4c5fadf4b98a1f64406b0679c4a9b53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Best practice</topic><topic>Causality</topic><topic>Conduction</topic><topic>Confidence</topic><topic>Conjoint analysis</topic><topic>Dependent variables</topic><topic>Design engineering</topic><topic>Literature reviews</topic><topic>Methodology</topic><topic>Perception</topic><topic>Realism</topic><topic>Research methodology</topic><topic>Studies</topic><topic>Validation studies</topic><topic>Validity</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Aguinis, Herman</creatorcontrib><creatorcontrib>Bradley, Kyle J.</creatorcontrib><collection>CrossRef</collection><collection>Materials Business File</collection><collection>Mechanical &amp; Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Materials Research Database</collection><jtitle>Organizational research methods</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Aguinis, Herman</au><au>Bradley, Kyle J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Best Practice Recommendations for Designing and Implementing Experimental Vignette Methodology Studies</atitle><jtitle>Organizational research methods</jtitle><date>2014-10-01</date><risdate>2014</risdate><volume>17</volume><issue>4</issue><spage>351</spage><epage>371</epage><pages>351-371</pages><issn>1094-4281</issn><eissn>1552-7425</eissn><abstract>We describe experimental vignette methodology (EVM) as a way to address the dilemma of conducting experimental research that results in high levels of confidence regarding internal validity but is challenged by threats to external validity versus conducting nonexperimental research that usually maximizes external validity but whose conclusions are ambiguous regarding causal relationships. EVM studies consist of presenting participants with carefully constructed and realistic scenarios to assess dependent variables including intentions, attitudes, and behaviors, thereby enhancing experimental realism and also allowing researchers to manipulate and control independent variables. We describe two major types of EVM aimed at assessing explicit (i.e., paper people studies) and implicit (i.e., policy capturing and conjoint analysis) processes and outcomes. We offer best practice recommendations regarding the design and implementation of EVM studies based on a multidisciplinary literature review, discuss substantive domains and topics that can benefit from implementing EVM, address knowledge gaps regarding EVM such as the need to increase realism and the number and diversity of participants, and address ways to overcome some of the negative perceptions about EVM by pointing to exemplary articles that have used EVM successfully.</abstract><cop>Los Angeles, CA</cop><pub>SAGE Publications</pub><doi>10.1177/1094428114547952</doi><tpages>21</tpages></addata></record>
fulltext fulltext
identifier ISSN: 1094-4281
ispartof Organizational research methods, 2014-10, Vol.17 (4), p.351-371
issn 1094-4281
1552-7425
language eng
recordid cdi_proquest_miscellaneous_1686442431
source SAGE Complete
subjects Best practice
Causality
Conduction
Confidence
Conjoint analysis
Dependent variables
Design engineering
Literature reviews
Methodology
Perception
Realism
Research methodology
Studies
Validation studies
Validity
title Best Practice Recommendations for Designing and Implementing Experimental Vignette Methodology Studies
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-21T18%3A07%3A34IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Best%20Practice%20Recommendations%20for%20Designing%20and%20Implementing%20Experimental%20Vignette%20Methodology%20Studies&rft.jtitle=Organizational%20research%20methods&rft.au=Aguinis,%20Herman&rft.date=2014-10-01&rft.volume=17&rft.issue=4&rft.spage=351&rft.epage=371&rft.pages=351-371&rft.issn=1094-4281&rft.eissn=1552-7425&rft_id=info:doi/10.1177/1094428114547952&rft_dat=%3Cproquest_cross%3E1686442431%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1605847249&rft_id=info:pmid/&rft_sage_id=10.1177_1094428114547952&rfr_iscdi=true