Cargando…
Resilience in emergency management: Learning from COVID-19 in oil and gas platforms
Emergency management, both in civilian and military context, is regarded as a complex socio-technical system, whose dynamic nature and complexity require a holistic approach. Over time, scholars developed diverse strategies and methods to capture such complexity and effectively design emergency plan...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9068239/ https://www.ncbi.nlm.nih.gov/pubmed/35535139 http://dx.doi.org/10.1016/j.ijdrr.2022.103026 |
_version_ | 1784700183919984640 |
---|---|
author | Cantelmi, R. Steen, R. Di Gravio, G. Patriarca, R. |
author_facet | Cantelmi, R. Steen, R. Di Gravio, G. Patriarca, R. |
author_sort | Cantelmi, R. |
collection | PubMed |
description | Emergency management, both in civilian and military context, is regarded as a complex socio-technical system, whose dynamic nature and complexity require a holistic approach. Over time, scholars developed diverse strategies and methods to capture such complexity and effectively design emergency plans for more or less severe disasters scenarios. Nonetheless, planning is not always an omni-comprehensive task, pushing organizations to stretch their adaptive capacities in dynamic and challenging settings. This manuscript explores such adaptive capacity as put in place by a leading Norwegian organization in providing emergency management solutions, facing unexpected challenges (at the time of the event): handling of Covid-19 infection episodes on offshore oil platforms. The study, conducted through the Functional Resonance Analysis Method (FRAM) highlights the relevance of organizational learning which allows to handle emergencies by adapting plans to the specific context and by renewing new emergency management procedures derived from lessons learned. The study focuses on three different Covid-19 infection management cases to understand the nuances of actions and emerging adaptations that led to the development of a revised emergency plan, seen again through the lens of FRAM. While the methodological approach refers to Covid-19 infection management, we believe it can be extended into larger crisis management, providing a use case for the applicability of FRAM into emergency management scenarios. |
format | Online Article Text |
id | pubmed-9068239 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-90682392022-05-05 Resilience in emergency management: Learning from COVID-19 in oil and gas platforms Cantelmi, R. Steen, R. Di Gravio, G. Patriarca, R. Int J Disaster Risk Reduct Article Emergency management, both in civilian and military context, is regarded as a complex socio-technical system, whose dynamic nature and complexity require a holistic approach. Over time, scholars developed diverse strategies and methods to capture such complexity and effectively design emergency plans for more or less severe disasters scenarios. Nonetheless, planning is not always an omni-comprehensive task, pushing organizations to stretch their adaptive capacities in dynamic and challenging settings. This manuscript explores such adaptive capacity as put in place by a leading Norwegian organization in providing emergency management solutions, facing unexpected challenges (at the time of the event): handling of Covid-19 infection episodes on offshore oil platforms. The study, conducted through the Functional Resonance Analysis Method (FRAM) highlights the relevance of organizational learning which allows to handle emergencies by adapting plans to the specific context and by renewing new emergency management procedures derived from lessons learned. The study focuses on three different Covid-19 infection management cases to understand the nuances of actions and emerging adaptations that led to the development of a revised emergency plan, seen again through the lens of FRAM. While the methodological approach refers to Covid-19 infection management, we believe it can be extended into larger crisis management, providing a use case for the applicability of FRAM into emergency management scenarios. Elsevier Ltd. 2022-06-15 2022-05-05 /pmc/articles/PMC9068239/ /pubmed/35535139 http://dx.doi.org/10.1016/j.ijdrr.2022.103026 Text en © 2022 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Cantelmi, R. Steen, R. Di Gravio, G. Patriarca, R. Resilience in emergency management: Learning from COVID-19 in oil and gas platforms |
title | Resilience in emergency management: Learning from COVID-19 in oil and gas platforms |
title_full | Resilience in emergency management: Learning from COVID-19 in oil and gas platforms |
title_fullStr | Resilience in emergency management: Learning from COVID-19 in oil and gas platforms |
title_full_unstemmed | Resilience in emergency management: Learning from COVID-19 in oil and gas platforms |
title_short | Resilience in emergency management: Learning from COVID-19 in oil and gas platforms |
title_sort | resilience in emergency management: learning from covid-19 in oil and gas platforms |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9068239/ https://www.ncbi.nlm.nih.gov/pubmed/35535139 http://dx.doi.org/10.1016/j.ijdrr.2022.103026 |
work_keys_str_mv | AT cantelmir resilienceinemergencymanagementlearningfromcovid19inoilandgasplatforms AT steenr resilienceinemergencymanagementlearningfromcovid19inoilandgasplatforms AT digraviog resilienceinemergencymanagementlearningfromcovid19inoilandgasplatforms AT patriarcar resilienceinemergencymanagementlearningfromcovid19inoilandgasplatforms |