Flood Risk Reduction Among Malaysian Disaster Management Agencies: Challenges and Recommendations

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F25%3A50022816" target="_blank" >RIV/62690094:18450/25:50022816 - isvavai.cz</a>

Výsledek na webu

<a href="https://ebooks.iospress.nl/doi/10.3233/FAIA250557" target="_blank" >https://ebooks.iospress.nl/doi/10.3233/FAIA250557</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3233/FAIA250557" target="_blank" >10.3233/FAIA250557</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Flood Risk Reduction Among Malaysian Disaster Management Agencies: Challenges and Recommendations

Popis výsledku v původním jazyce

Floods are considered one of Malaysia&apos;s most detrimental natural hazards in terms of frequency, extent, duration, damage, and population affected. Consequently, flood risk reduction has become a popular research topic in recent years. Despite various efforts made, flood mitigation strategies within the Malaysian government sectors remain ineffective in alleviating the negative impacts of flooding. As a result, this paper aims to examine the current challenges faced by Malaysian disaster management agencies and their recommendations for reducing the disastrous effects of floods. To achieve this, a qualitative approach was employed through nine focus group discussions comprising a total of 48 participants. Inductive thematic analysis was used to categorize these challenges into several groups under different phases of the disaster management cycle. The obtained results revealed that most challenges faced by Malaysian government agencies were from the pre-disaster phase. Several recommendations were suggested to overcome these challenges and to obtain an effective disaster management capability. In addition, the findings also indicated that although Artificial Intelligence (AI) has great potential in flood risk reduction, AI integration into flood disaster management is still at an early stage in Malaysia. Outcomes from this study are expected to provide valuable insights to support decision-makers in handling flood events more effectively, ultimately saving lives and reducing the damaging impacts of floods in Malaysia. © 2025 The Authors.

Název v anglickém jazyce

Flood Risk Reduction Among Malaysian Disaster Management Agencies: Challenges and Recommendations

Popis výsledku anglicky

Floods are considered one of Malaysia&apos;s most detrimental natural hazards in terms of frequency, extent, duration, damage, and population affected. Consequently, flood risk reduction has become a popular research topic in recent years. Despite various efforts made, flood mitigation strategies within the Malaysian government sectors remain ineffective in alleviating the negative impacts of flooding. As a result, this paper aims to examine the current challenges faced by Malaysian disaster management agencies and their recommendations for reducing the disastrous effects of floods. To achieve this, a qualitative approach was employed through nine focus group discussions comprising a total of 48 participants. Inductive thematic analysis was used to categorize these challenges into several groups under different phases of the disaster management cycle. The obtained results revealed that most challenges faced by Malaysian government agencies were from the pre-disaster phase. Several recommendations were suggested to overcome these challenges and to obtain an effective disaster management capability. In addition, the findings also indicated that although Artificial Intelligence (AI) has great potential in flood risk reduction, AI integration into flood disaster management is still at an early stage in Malaysia. Outcomes from this study are expected to provide valuable insights to support decision-makers in handling flood events more effectively, ultimately saving lives and reducing the damaging impacts of floods in Malaysia. © 2025 The Authors.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Frontiers in artificial intelligence and applications

ISBN

978-1-64368-619-6

ISSN

0922-6389

e-ISSN

0922-6389

Počet stran výsledku

14

Strana od-do

593-606

Název nakladatele

IOS press

Místo vydání

Amsterdam

Místo konání akce

Kitakyushu

Datum konání akce

23. 9. 2025

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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