Capturing Real-Time Data in Disaster Response Logistics
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | JOSCM. Journal of Operations and Supply Chain Management |
Texto Completo: | https://periodicos.fgv.br/joscm/article/view/56542 |
Resumo: | The volume, accuracy, accessibility and level of detail of near real-time data emerging from disaster-affected regions continue to significantly improve. Integration of dynamically evolving in-field data is an important, yet often overlooked, component of the humanitarian logistics models. In this paper, we present a framework for real-time humanitarian logistics data focused on use in mathematical modeling along with modeling implications of this framework. We also discuss how one might measure the attributes of the framework and describe the application of the presented framework to a case study of near real-time data collection in the days following the landfall of Typhoon Haiyan. We detail our first-hand experience of capturing data as the post-disaster response unfolds starting on November 10, 2013 until March 31, 2014 and assess the characteristics and evolution of data pertaining to humanitarian logistics modeling using the proposed framework. The presented logistical content analysis examines the availability of data and informs modelers about the current state of near real-time data. This analysis illustrates what data is available, how early it is available, and how data changes after the disaster. The study describes how our humanitarian logistics team approached the emergence of dynamic online data after the disaster and the challenges faced during the collection process, as well as recommendations to address these challenges in the future (when possible) from an academic humanitarian logistics perspective. |
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JOSCM. Journal of Operations and Supply Chain Management |
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Capturing Real-Time Data in Disaster Response LogisticsHumanitarian logisticsreal-time dataclassificationlogistical modelingTyphoon Haiyan.The volume, accuracy, accessibility and level of detail of near real-time data emerging from disaster-affected regions continue to significantly improve. Integration of dynamically evolving in-field data is an important, yet often overlooked, component of the humanitarian logistics models. In this paper, we present a framework for real-time humanitarian logistics data focused on use in mathematical modeling along with modeling implications of this framework. We also discuss how one might measure the attributes of the framework and describe the application of the presented framework to a case study of near real-time data collection in the days following the landfall of Typhoon Haiyan. We detail our first-hand experience of capturing data as the post-disaster response unfolds starting on November 10, 2013 until March 31, 2014 and assess the characteristics and evolution of data pertaining to humanitarian logistics modeling using the proposed framework. The presented logistical content analysis examines the availability of data and informs modelers about the current state of near real-time data. This analysis illustrates what data is available, how early it is available, and how data changes after the disaster. The study describes how our humanitarian logistics team approached the emergence of dynamic online data after the disaster and the challenges faced during the collection process, as well as recommendations to address these challenges in the future (when possible) from an academic humanitarian logistics perspective.FGV EAESP2016-07-18info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.fgv.br/joscm/article/view/5654210.12660/joscmv9n1p23-54Journal of Operations and Supply Chain Management; Vol. 9 No. 1 (2016): January - June; 23-54Journal of Operations and Supply Chain Management; v. 9 n. 1 (2016): January - June; 23-541984-3046reponame:JOSCM. Journal of Operations and Supply Chain Managementinstname:Fundação Getulio Vargas (FGV)instacron:FGVenghttps://periodicos.fgv.br/joscm/article/view/56542/pdf_11Copyright (c) 2016 Journal of Operations and Supply Chain Managementinfo:eu-repo/semantics/openAccessYagci Sokat, KezbanZhou, RuiDolinskaya, Irina S.Smilowitz, KarenChan, Jennifer2017-08-04T19:31:57Zoai:ojs.periodicos.fgv.br:article/56542Revistahttp://bibliotecadigital.fgv.br/ojs/index.php/joscmPRIhttp://bibliotecadigital.fgv.br/ojs/index.php/joscm/oai||joscm@fgv.br1984-30461984-3046opendoar:2017-08-04T19:31:57JOSCM. Journal of Operations and Supply Chain Management - Fundação Getulio Vargas (FGV)false |
dc.title.none.fl_str_mv |
Capturing Real-Time Data in Disaster Response Logistics |
title |
Capturing Real-Time Data in Disaster Response Logistics |
spellingShingle |
Capturing Real-Time Data in Disaster Response Logistics Yagci Sokat, Kezban Humanitarian logistics real-time data classification logistical modeling Typhoon Haiyan. |
title_short |
Capturing Real-Time Data in Disaster Response Logistics |
title_full |
Capturing Real-Time Data in Disaster Response Logistics |
title_fullStr |
Capturing Real-Time Data in Disaster Response Logistics |
title_full_unstemmed |
Capturing Real-Time Data in Disaster Response Logistics |
title_sort |
Capturing Real-Time Data in Disaster Response Logistics |
author |
Yagci Sokat, Kezban |
author_facet |
Yagci Sokat, Kezban Zhou, Rui Dolinskaya, Irina S. Smilowitz, Karen Chan, Jennifer |
author_role |
author |
author2 |
Zhou, Rui Dolinskaya, Irina S. Smilowitz, Karen Chan, Jennifer |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Yagci Sokat, Kezban Zhou, Rui Dolinskaya, Irina S. Smilowitz, Karen Chan, Jennifer |
dc.subject.por.fl_str_mv |
Humanitarian logistics real-time data classification logistical modeling Typhoon Haiyan. |
topic |
Humanitarian logistics real-time data classification logistical modeling Typhoon Haiyan. |
description |
The volume, accuracy, accessibility and level of detail of near real-time data emerging from disaster-affected regions continue to significantly improve. Integration of dynamically evolving in-field data is an important, yet often overlooked, component of the humanitarian logistics models. In this paper, we present a framework for real-time humanitarian logistics data focused on use in mathematical modeling along with modeling implications of this framework. We also discuss how one might measure the attributes of the framework and describe the application of the presented framework to a case study of near real-time data collection in the days following the landfall of Typhoon Haiyan. We detail our first-hand experience of capturing data as the post-disaster response unfolds starting on November 10, 2013 until March 31, 2014 and assess the characteristics and evolution of data pertaining to humanitarian logistics modeling using the proposed framework. The presented logistical content analysis examines the availability of data and informs modelers about the current state of near real-time data. This analysis illustrates what data is available, how early it is available, and how data changes after the disaster. The study describes how our humanitarian logistics team approached the emergence of dynamic online data after the disaster and the challenges faced during the collection process, as well as recommendations to address these challenges in the future (when possible) from an academic humanitarian logistics perspective. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-07-18 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://periodicos.fgv.br/joscm/article/view/56542 10.12660/joscmv9n1p23-54 |
url |
https://periodicos.fgv.br/joscm/article/view/56542 |
identifier_str_mv |
10.12660/joscmv9n1p23-54 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://periodicos.fgv.br/joscm/article/view/56542/pdf_11 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2016 Journal of Operations and Supply Chain Management info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2016 Journal of Operations and Supply Chain Management |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
FGV EAESP |
publisher.none.fl_str_mv |
FGV EAESP |
dc.source.none.fl_str_mv |
Journal of Operations and Supply Chain Management; Vol. 9 No. 1 (2016): January - June; 23-54 Journal of Operations and Supply Chain Management; v. 9 n. 1 (2016): January - June; 23-54 1984-3046 reponame:JOSCM. Journal of Operations and Supply Chain Management instname:Fundação Getulio Vargas (FGV) instacron:FGV |
instname_str |
Fundação Getulio Vargas (FGV) |
instacron_str |
FGV |
institution |
FGV |
reponame_str |
JOSCM. Journal of Operations and Supply Chain Management |
collection |
JOSCM. Journal of Operations and Supply Chain Management |
repository.name.fl_str_mv |
JOSCM. Journal of Operations and Supply Chain Management - Fundação Getulio Vargas (FGV) |
repository.mail.fl_str_mv |
||joscm@fgv.br |
_version_ |
1798943730642714624 |