Measuring and modeling behavioral decision dynamics in collective evacuation.

Identifying and quantifying factors influencing human decision making remains an outstanding challenge, impacting the performance and predictability of social and technological systems. In many cases, system failures are traced to human factors including congestion, overload, miscommunication, and d...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Jean M Carlson, David L Alderson, Sean P Stromberg, Danielle S Bassett, Emily M Craparo, Francisco Guiterrez-Villarreal, Thomas Otani
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2014
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/37a83ffa80004c6fb3faf96932045d2a
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:37a83ffa80004c6fb3faf96932045d2a
record_format	dspace
spelling	oai:doaj.org-article:37a83ffa80004c6fb3faf96932045d2a2021-11-18T08:33:13ZMeasuring and modeling behavioral decision dynamics in collective evacuation.1932-620310.1371/journal.pone.0087380https://doaj.org/article/37a83ffa80004c6fb3faf96932045d2a2014-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24520331/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203Identifying and quantifying factors influencing human decision making remains an outstanding challenge, impacting the performance and predictability of social and technological systems. In many cases, system failures are traced to human factors including congestion, overload, miscommunication, and delays. Here we report results of a behavioral network science experiment, targeting decision making in a natural disaster. In a controlled laboratory setting, our results quantify several key factors influencing individual evacuation decision making in a controlled laboratory setting. The experiment includes tensions between broadcast and peer-to-peer information, and contrasts the effects of temporal urgency associated with the imminence of the disaster and the effects of limited shelter capacity for evacuees. Based on empirical measurements of the cumulative rate of evacuations as a function of the instantaneous disaster likelihood, we develop a quantitative model for decision making that captures remarkably well the main features of observed collective behavior across many different scenarios. Moreover, this model captures the sensitivity of individual- and population-level decision behaviors to external pressures, and systematic deviations from the model provide meaningful estimates of variability in the collective response. Identification of robust methods for quantifying human decisions in the face of risk has implications for policy in disasters and other threat scenarios, specifically the development and testing of robust strategies for training and control of evacuations that account for human behavior and network topologies.Jean M CarlsonDavid L AldersonSean P StrombergDanielle S BassettEmily M CraparoFrancisco Guiterrez-VillarrealThomas OtaniPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 9, Iss 2, p e87380 (2014)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Jean M Carlson David L Alderson Sean P Stromberg Danielle S Bassett Emily M Craparo Francisco Guiterrez-Villarreal Thomas Otani Measuring and modeling behavioral decision dynamics in collective evacuation.
description	Identifying and quantifying factors influencing human decision making remains an outstanding challenge, impacting the performance and predictability of social and technological systems. In many cases, system failures are traced to human factors including congestion, overload, miscommunication, and delays. Here we report results of a behavioral network science experiment, targeting decision making in a natural disaster. In a controlled laboratory setting, our results quantify several key factors influencing individual evacuation decision making in a controlled laboratory setting. The experiment includes tensions between broadcast and peer-to-peer information, and contrasts the effects of temporal urgency associated with the imminence of the disaster and the effects of limited shelter capacity for evacuees. Based on empirical measurements of the cumulative rate of evacuations as a function of the instantaneous disaster likelihood, we develop a quantitative model for decision making that captures remarkably well the main features of observed collective behavior across many different scenarios. Moreover, this model captures the sensitivity of individual- and population-level decision behaviors to external pressures, and systematic deviations from the model provide meaningful estimates of variability in the collective response. Identification of robust methods for quantifying human decisions in the face of risk has implications for policy in disasters and other threat scenarios, specifically the development and testing of robust strategies for training and control of evacuations that account for human behavior and network topologies.
format	article
author	Jean M Carlson David L Alderson Sean P Stromberg Danielle S Bassett Emily M Craparo Francisco Guiterrez-Villarreal Thomas Otani
author_facet	Jean M Carlson David L Alderson Sean P Stromberg Danielle S Bassett Emily M Craparo Francisco Guiterrez-Villarreal Thomas Otani
author_sort	Jean M Carlson
title	Measuring and modeling behavioral decision dynamics in collective evacuation.
title_short	Measuring and modeling behavioral decision dynamics in collective evacuation.
title_full	Measuring and modeling behavioral decision dynamics in collective evacuation.
title_fullStr	Measuring and modeling behavioral decision dynamics in collective evacuation.
title_full_unstemmed	Measuring and modeling behavioral decision dynamics in collective evacuation.
title_sort	measuring and modeling behavioral decision dynamics in collective evacuation.
publisher	Public Library of Science (PLoS)
publishDate	2014
url	https://doaj.org/article/37a83ffa80004c6fb3faf96932045d2a
work_keys_str_mv	AT jeanmcarlson measuringandmodelingbehavioraldecisiondynamicsincollectiveevacuation AT davidlalderson measuringandmodelingbehavioraldecisiondynamicsincollectiveevacuation AT seanpstromberg measuringandmodelingbehavioraldecisiondynamicsincollectiveevacuation AT daniellesbassett measuringandmodelingbehavioraldecisiondynamicsincollectiveevacuation AT emilymcraparo measuringandmodelingbehavioraldecisiondynamicsincollectiveevacuation AT franciscoguiterrezvillarreal measuringandmodelingbehavioraldecisiondynamicsincollectiveevacuation AT thomasotani measuringandmodelingbehavioraldecisiondynamicsincollectiveevacuation
_version_	1718421614489501696

Measuring and modeling behavioral decision dynamics in collective evacuation.

Ejemplares similares