The Legitimacy, Accountability, and Ownership of an Impact-Based Forecasting Model in Disaster Governance

Author:

Bierens Sterre,Boersma Kees,Van den Homberg Marc J. C.ORCID

Abstract

The global shift within disaster governance from disaster response to preparedness and risk reduction includes the emergency of novel Early Warning Systems such as impact based forecasting and forecast-based financing. In this new paradigm, funds usually reserved for response can be released before a disaster happens when an impact-based forecast—i.e., the expected humanitarian impact as a result of the forecasted weather—reaches a predefined danger level. The development of these impact-based forecasting models are promising, but they also come with significant implementation challenges. This article presents the data-driven impact-based forecasting model as developed by 510, an initiative of the Netherlands Red Cross. It elaborates on how questions on legitimacy, accountability and ownership influenced the implementation of the model within the Philippines with the Philippine Red Cross and the local government as the main stakeholders. The findings imply that the exchange of knowledge between the designer and manufacturer of impact-based models and the end users of those models fall short if novel Early Warnign Systems are seen as just a matter of technology transfer. Instead the development and implementation of impact based models should be based on mutual understanding of the users’ needs and the developers of such models.

Publisher

Cogitatio

Subject

Public Administration,Sociology and Political Science

Reference62 articles.

1. Aitsi-Selmi, A., Sasaki, H., Wannous, C., Murray, V., & Egawa, S. (2015). The Sendai Framework for Disaster Risk Reduction: Renewing the global commitment to people’s resilience, health, and well-being. International Journal of Disaster Risk Science, 6(2), 164–176.

2. Alcayna, T., Bollettino, V., Dy, P., & Vinck, P. (2016). Resilience and disaster trends in the Philippines: Opportunities for national and local capacity building. PLoS Currents. https://doi.org/10.1371/currents.dis.4a0bc960866e53bd6357ac135d740846

3. Baharmand, H., Boersma, F. K., Meesters, K., Mulder, F., & Wolbers, J. J. (2016). A multidisciplinary perspective on supporting community disaster resilience in Nepal. In A. Tapia, P. Antunes, V. A. Bañuls, K. Moore, & J. Porto (Eds.), Proceedings of the ISCRAM 2016 conference (pp. 2–12). Rio de Janeiro: Federal University of Rio de Janeiro.

4. Balcik, B., Beamon, B. M., & Smilowitz, K. (2008). Last mile distribution in humanitarian relief. Journal of Intelligent Transportation Systems, 12(2), 51–63.

5. Bankoff, G., Frerks, G., & Hilhorst, T. (2004). Mapping vulnerability: Disasters, development and people. London and New York, NY: Earthscan.

Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3