Loading…

The BCD of response time analysis in experimental economics

For decisions in the wild, time is of the essence. Available decision time is often cut short through natural or artificial constraints, or is impinged upon by the opportunity cost of time. Experimental economists have only recently begun to conduct experiments with time constraints and to analyze r...

Full description

Saved in:
Bibliographic Details
Published in:Experimental economics : a journal of the Economic Science Association 2018-06, Vol.21 (2), p.383-433
Main Authors: Spiliopoulos, Leonidas, Ortmann, Andreas
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c601t-64b818c199bdeee0465a5339b228ac87a0071ff74ebe8e354b7880498966c3713
cites cdi_FETCH-LOGICAL-c601t-64b818c199bdeee0465a5339b228ac87a0071ff74ebe8e354b7880498966c3713
container_end_page 433
container_issue 2
container_start_page 383
container_title Experimental economics : a journal of the Economic Science Association
container_volume 21
creator Spiliopoulos, Leonidas
Ortmann, Andreas
description For decisions in the wild, time is of the essence. Available decision time is often cut short through natural or artificial constraints, or is impinged upon by the opportunity cost of time. Experimental economists have only recently begun to conduct experiments with time constraints and to analyze response time (RT) data, in contrast to experimental psychologists. RT analysis has proven valuable for the identification of individual and strategic decision processes including identification of social preferences in the latter case, model comparison/selection, and the investigation of heuristics that combine speed and performance by exploiting environmental regularities. Here we focus on the benefits, challenges, and desiderata of RT analysis in strategic decision making. We argue that unlocking the potential of RT analysis requires the adoption of process-based models instead of outcome-based models, and discuss how RT in the wild can be captured by time-constrained experiments in the lab. We conclude that RT analysis holds considerable potential for experimental economics, deserves greater attention as a methodological tool, and promises important insights on strategic decision making in naturally occurring environments.
doi_str_mv 10.1007/s10683-017-9528-1
format article
fullrecord <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_5913387</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2034292268</sourcerecordid><originalsourceid>FETCH-LOGICAL-c601t-64b818c199bdeee0465a5339b228ac87a0071ff74ebe8e354b7880498966c3713</originalsourceid><addsrcrecordid>eNp1kUtLAzEUhYMoVqs_wI0MuHEzmsdMHgiC1icU3NR1yKR32ikzkzFpxf57U1rrA1wl3Pvl5Nx7EDoh-IJgLC4DwVyyFBORqpzKlOygA5ILlnLF5G68M8nTLFZ66DCEGcaE5DzbRz2qBMVSqgN0NZpCcju4S1yZeAidawMk86qBxLSmXoYqJFWbwEcHPhbbuakTsK51TWXDEdorTR3geHP20evD_WjwlA5fHp8HN8PUckzmKc8KSaQlShVjAMAZz03OmCoolcZKYeIopCxFBgVIYHlWCClxpqTi3DJBWB9dr3W7RdHA2EYb3tS6i46MX2pnKv2701ZTPXHvOleEMSmiwPlGwLu3BYS5bqpgoa5NC24RNMUso4rSuMw-OvuDztzCx1WsKKqYojlnkSJrynoXgodya4ZgvYpGr6PRMRq9ikavpjj9OcX2xVcWEaBrIMRWOwH__fX_qp9V0JhK</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2029392563</pqid></control><display><type>article</type><title>The BCD of response time analysis in experimental economics</title><source>EconLit s plnými texty</source><source>International Bibliography of the Social Sciences (IBSS)</source><source>ABI/INFORM Global</source><source>Springer Link</source><creator>Spiliopoulos, Leonidas ; Ortmann, Andreas</creator><creatorcontrib>Spiliopoulos, Leonidas ; Ortmann, Andreas</creatorcontrib><description>For decisions in the wild, time is of the essence. Available decision time is often cut short through natural or artificial constraints, or is impinged upon by the opportunity cost of time. Experimental economists have only recently begun to conduct experiments with time constraints and to analyze response time (RT) data, in contrast to experimental psychologists. RT analysis has proven valuable for the identification of individual and strategic decision processes including identification of social preferences in the latter case, model comparison/selection, and the investigation of heuristics that combine speed and performance by exploiting environmental regularities. Here we focus on the benefits, challenges, and desiderata of RT analysis in strategic decision making. We argue that unlocking the potential of RT analysis requires the adoption of process-based models instead of outcome-based models, and discuss how RT in the wild can be captured by time-constrained experiments in the lab. We conclude that RT analysis holds considerable potential for experimental economics, deserves greater attention as a methodological tool, and promises important insights on strategic decision making in naturally occurring environments.</description><identifier>ISSN: 1386-4157</identifier><identifier>EISSN: 1573-6938</identifier><identifier>DOI: 10.1007/s10683-017-9528-1</identifier><identifier>PMID: 29720889</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Analysis ; Behavioral/Experimental Economics ; Decision making ; Economic theory ; Economic Theory/Quantitative Economics/Mathematical Methods ; Economics ; Economics and Finance ; Economists ; Experimental economics ; Game Theory ; Heuristic ; Microeconomics ; Operations Research/Decision Theory ; Original Paper ; Psychologists ; Reaction time ; Social and Behav. Sciences</subject><ispartof>Experimental economics : a journal of the Economic Science Association, 2018-06, Vol.21 (2), p.383-433</ispartof><rights>The Author(s) 2017</rights><rights>Experimental Economics is a copyright of Springer, (2017). All Rights Reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c601t-64b818c199bdeee0465a5339b228ac87a0071ff74ebe8e354b7880498966c3713</citedby><cites>FETCH-LOGICAL-c601t-64b818c199bdeee0465a5339b228ac87a0071ff74ebe8e354b7880498966c3713</cites><orcidid>0000-0001-9154-2160</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2029392563/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$H</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2029392563?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>230,314,780,784,885,11688,12847,27924,27925,33223,36060,36061,44363,74895</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/29720889$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Spiliopoulos, Leonidas</creatorcontrib><creatorcontrib>Ortmann, Andreas</creatorcontrib><title>The BCD of response time analysis in experimental economics</title><title>Experimental economics : a journal of the Economic Science Association</title><addtitle>Exp Econ</addtitle><addtitle>Exp Econ</addtitle><description>For decisions in the wild, time is of the essence. Available decision time is often cut short through natural or artificial constraints, or is impinged upon by the opportunity cost of time. Experimental economists have only recently begun to conduct experiments with time constraints and to analyze response time (RT) data, in contrast to experimental psychologists. RT analysis has proven valuable for the identification of individual and strategic decision processes including identification of social preferences in the latter case, model comparison/selection, and the investigation of heuristics that combine speed and performance by exploiting environmental regularities. Here we focus on the benefits, challenges, and desiderata of RT analysis in strategic decision making. We argue that unlocking the potential of RT analysis requires the adoption of process-based models instead of outcome-based models, and discuss how RT in the wild can be captured by time-constrained experiments in the lab. We conclude that RT analysis holds considerable potential for experimental economics, deserves greater attention as a methodological tool, and promises important insights on strategic decision making in naturally occurring environments.</description><subject>Analysis</subject><subject>Behavioral/Experimental Economics</subject><subject>Decision making</subject><subject>Economic theory</subject><subject>Economic Theory/Quantitative Economics/Mathematical Methods</subject><subject>Economics</subject><subject>Economics and Finance</subject><subject>Economists</subject><subject>Experimental economics</subject><subject>Game Theory</subject><subject>Heuristic</subject><subject>Microeconomics</subject><subject>Operations Research/Decision Theory</subject><subject>Original Paper</subject><subject>Psychologists</subject><subject>Reaction time</subject><subject>Social and Behav. Sciences</subject><issn>1386-4157</issn><issn>1573-6938</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>8BJ</sourceid><sourceid>M0C</sourceid><recordid>eNp1kUtLAzEUhYMoVqs_wI0MuHEzmsdMHgiC1icU3NR1yKR32ikzkzFpxf57U1rrA1wl3Pvl5Nx7EDoh-IJgLC4DwVyyFBORqpzKlOygA5ILlnLF5G68M8nTLFZ66DCEGcaE5DzbRz2qBMVSqgN0NZpCcju4S1yZeAidawMk86qBxLSmXoYqJFWbwEcHPhbbuakTsK51TWXDEdorTR3geHP20evD_WjwlA5fHp8HN8PUckzmKc8KSaQlShVjAMAZz03OmCoolcZKYeIopCxFBgVIYHlWCClxpqTi3DJBWB9dr3W7RdHA2EYb3tS6i46MX2pnKv2701ZTPXHvOleEMSmiwPlGwLu3BYS5bqpgoa5NC24RNMUso4rSuMw-OvuDztzCx1WsKKqYojlnkSJrynoXgodya4ZgvYpGr6PRMRq9ikavpjj9OcX2xVcWEaBrIMRWOwH__fX_qp9V0JhK</recordid><startdate>20180601</startdate><enddate>20180601</enddate><creator>Spiliopoulos, Leonidas</creator><creator>Ortmann, Andreas</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>C6C</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>8AO</scope><scope>8BJ</scope><scope>8FK</scope><scope>8FL</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FQK</scope><scope>FRNLG</scope><scope>F~G</scope><scope>JBE</scope><scope>K60</scope><scope>K6~</scope><scope>L.-</scope><scope>M0C</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PYYUZ</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0001-9154-2160</orcidid></search><sort><creationdate>20180601</creationdate><title>The BCD of response time analysis in experimental economics</title><author>Spiliopoulos, Leonidas ; Ortmann, Andreas</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c601t-64b818c199bdeee0465a5339b228ac87a0071ff74ebe8e354b7880498966c3713</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Analysis</topic><topic>Behavioral/Experimental Economics</topic><topic>Decision making</topic><topic>Economic theory</topic><topic>Economic Theory/Quantitative Economics/Mathematical Methods</topic><topic>Economics</topic><topic>Economics and Finance</topic><topic>Economists</topic><topic>Experimental economics</topic><topic>Game Theory</topic><topic>Heuristic</topic><topic>Microeconomics</topic><topic>Operations Research/Decision Theory</topic><topic>Original Paper</topic><topic>Psychologists</topic><topic>Reaction time</topic><topic>Social and Behav. Sciences</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Spiliopoulos, Leonidas</creatorcontrib><creatorcontrib>Ortmann, Andreas</creatorcontrib><collection>Springer Nature OA Free Journals</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central</collection><collection>ProQuest Business Premium Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>International Bibliography of the Social Sciences</collection><collection>Business Premium Collection (Alumni)</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>International Bibliography of the Social Sciences</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ABI/INFORM Global</collection><collection>ProQuest One Business</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ABI/INFORM Collection China</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Experimental economics : a journal of the Economic Science Association</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Spiliopoulos, Leonidas</au><au>Ortmann, Andreas</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The BCD of response time analysis in experimental economics</atitle><jtitle>Experimental economics : a journal of the Economic Science Association</jtitle><stitle>Exp Econ</stitle><addtitle>Exp Econ</addtitle><date>2018-06-01</date><risdate>2018</risdate><volume>21</volume><issue>2</issue><spage>383</spage><epage>433</epage><pages>383-433</pages><issn>1386-4157</issn><eissn>1573-6938</eissn><abstract>For decisions in the wild, time is of the essence. Available decision time is often cut short through natural or artificial constraints, or is impinged upon by the opportunity cost of time. Experimental economists have only recently begun to conduct experiments with time constraints and to analyze response time (RT) data, in contrast to experimental psychologists. RT analysis has proven valuable for the identification of individual and strategic decision processes including identification of social preferences in the latter case, model comparison/selection, and the investigation of heuristics that combine speed and performance by exploiting environmental regularities. Here we focus on the benefits, challenges, and desiderata of RT analysis in strategic decision making. We argue that unlocking the potential of RT analysis requires the adoption of process-based models instead of outcome-based models, and discuss how RT in the wild can be captured by time-constrained experiments in the lab. We conclude that RT analysis holds considerable potential for experimental economics, deserves greater attention as a methodological tool, and promises important insights on strategic decision making in naturally occurring environments.</abstract><cop>New York</cop><pub>Springer US</pub><pmid>29720889</pmid><doi>10.1007/s10683-017-9528-1</doi><tpages>51</tpages><orcidid>https://orcid.org/0000-0001-9154-2160</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1386-4157
ispartof Experimental economics : a journal of the Economic Science Association, 2018-06, Vol.21 (2), p.383-433
issn 1386-4157
1573-6938
language eng
recordid cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_5913387
source EconLit s plnými texty; International Bibliography of the Social Sciences (IBSS); ABI/INFORM Global; Springer Link
subjects Analysis
Behavioral/Experimental Economics
Decision making
Economic theory
Economic Theory/Quantitative Economics/Mathematical Methods
Economics
Economics and Finance
Economists
Experimental economics
Game Theory
Heuristic
Microeconomics
Operations Research/Decision Theory
Original Paper
Psychologists
Reaction time
Social and Behav. Sciences
title The BCD of response time analysis in experimental economics
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-28T02%3A57%3A07IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=The%20BCD%20of%20response%20time%20analysis%20in%20experimental%20economics&rft.jtitle=Experimental%20economics%20:%20a%20journal%20of%20the%20Economic%20Science%20Association&rft.au=Spiliopoulos,%20Leonidas&rft.date=2018-06-01&rft.volume=21&rft.issue=2&rft.spage=383&rft.epage=433&rft.pages=383-433&rft.issn=1386-4157&rft.eissn=1573-6938&rft_id=info:doi/10.1007/s10683-017-9528-1&rft_dat=%3Cproquest_pubme%3E2034292268%3C/proquest_pubme%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c601t-64b818c199bdeee0465a5339b228ac87a0071ff74ebe8e354b7880498966c3713%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2029392563&rft_id=info:pmid/29720889&rfr_iscdi=true