Flood Risk Reduction Among Malaysian Disaster Management Agencies: Challenges and Recommendations
The result's identifiers
Result code in 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>
Result on the web
<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>
Alternative languages
Result language
angličtina
Original language name
Flood Risk Reduction Among Malaysian Disaster Management Agencies: Challenges and Recommendations
Original language description
Floods are considered one of Malaysia'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.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Frontiers in artificial intelligence and applications
ISBN
978-1-64368-619-6
ISSN
0922-6389
e-ISSN
0922-6389
Number of pages
14
Pages from-to
593-606
Publisher name
IOS press
Place of publication
Amsterdam
Event location
Kitakyushu
Event date
Sep 23, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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