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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&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.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

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

Result continuities

  • Project

  • 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