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<ArticleSet>
  <Article>
    <Journal>
      <PublisherName></PublisherName>
      <JournalTitle>Journal of Resource Management and Decision Engineering</JournalTitle>
      <Issn></Issn>
      <Volume>5</Volume>
      <Issue>Serial Number 17</Issue>
      <PubDate PubStatus="epublish">
        <Year>2026</Year>
        <Month>07</Month>
        <Day>01</Day>
      </PubDate>
    </Journal>
    <ArticleTitle>Explanation and Prioritization of Factors Influencing the Location of Resilient Schools Against Natural Hazards with an Emphasis on Collective Intelligence (Case Study: Nowshahr City)</ArticleTitle>
    <VernacularTitle>Explanation and Prioritization of Factors Influencing the Location of Resilient Schools Against Natural Hazards with an Emphasis on Collective Intelligence (Case Study: Nowshahr City)</VernacularTitle>
    <FirstPage>1</FirstPage>
    <LastPage>14</LastPage>
    <ELocationID EIdType="doi">10.61838/kman.jrmde.283</ELocationID>
    <Language>EN</Language>
    <AuthorList>
      <Author>
        <FirstName></FirstName>
        <LastName></LastName>
        <Affiliation></Affiliation>
      </Author>
      <Author>
        <FirstName></FirstName>
        <LastName></LastName>
        <Affiliation></Affiliation>
      </Author>
      <Author>
        <FirstName></FirstName>
        <LastName></LastName>
        <Affiliation></Affiliation>
      </Author>
    </AuthorList>
    <PublicationType>Journal Article</PublicationType>
    <History>
      <PubDate PubStatus="received">
        <Year>2026</Year>
        <Month>01</Month>
        <Day>05</Day>
      </PubDate>
    </History>
    <Abstract>&lt;p&gt;This study was conducted with the aim of identifying and prioritizing the factors influencing the location of resilient schools in the face of natural hazards. The research adopted a mixed-methods approach, and data were analyzed using the Analytic Network Process (ANP), Delphi method, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and Geographic Information System (GIS). The findings indicated that out of 22 initial items, 14 items were identified as key factors agreed upon by experts, encompassing physical, environmental, safety, accessibility, and socio-managerial dimensions. The results of spatial analysis, combined with collective intelligence algorithms, enabled the identification of safe and high-risk zones, as well as the optimization of evacuation routes and school site allocation. This framework can serve as a practical tool for urban planners, educational administrators, and designers of educational spaces to enhance the resilience and safety of schools.&lt;/p&gt;</Abstract>
    <ObjectList>
      <Object Type="keyword">
        <Param Name="value">resilient school site selection</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">natural hazards</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">multi-criteria analysis</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">green logistics</Param>
      </Object>
    </ObjectList>
    <ArchiveCopySource DocType="pdf">https://www.journalrmde.com/index.php/jrmde/article/download/283/265</ArchiveCopySource>
  </Article>
</ArticleSet>
