<?xml version="1.0" encoding="UTF-8"?>
<doi_batch version="5.3.1" xmlns="http://www.crossref.org/schema/5.3.1" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:jats="http://www.ncbi.nlm.nih.gov/JATS1" xmlns:ai="http://www.crossref.org/AccessIndicators.xsd" xsi:schemaLocation="http://www.crossref.org/schema/5.3.1 http://www.crossref.org/schema/deposit/crossref5.3.1.xsd">
 <head>
  <doi_batch_id>aspg-21-2721-1791475170</doi_batch_id>
  <timestamp>20261008155930</timestamp>
  <depositor>
   <depositor_name>American Scientific Publishing Group</depositor_name>
   <email_address>admin@americaspg.com</email_address>
  </depositor>
  <registrant>American Scientific Publishing Group</registrant>
 </head>
 <body>
  <journal>
   <journal_metadata language="en">
    <full_title>International Journal of Neutrosophic Science</full_title>
    <abbrev_title>IJNS</abbrev_title>
    <issn media_type="print">2692-6148</issn>
    <issn media_type="electronic">2690-6805</issn>
   </journal_metadata>
   <journal_issue>
    <publication_date media_type="online">
     <year>2024</year>
    </publication_date>
    <journal_volume>
     <volume>24</volume>
    </journal_volume>
    <issue>2</issue>
   </journal_issue>
   <journal_article publication_type="full_text">
    <titles>
     <title>Enhancing Decision-Making in Complex Environments: Integrating AHP, Delphi, and Neutrosophic Logic</title>
    </titles>
    <contributors>
     <person_name sequence="first" contributor_role="author">
      <given_name>Marcia Esther E.</given_name>
      <surname>Heredia</surname>
      <affiliations>
       <institution>
        <institution_name>Regional Autonomous University of the Andes Babahoyo, Ecuador</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Jorge Washigton S.</given_name>
      <surname>Andachi</surname>
      <affiliations>
       <institution>
        <institution_name>Regional Autonomous University of the Andes Puyo, Ecuador</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Nemis García</given_name>
      <surname>Arias</surname>
      <affiliations>
       <institution>
        <institution_name>Regional Autonomous University of the Andes Santo Domingo, Ecuador</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Saziye</given_name>
      <surname>Yaman</surname>
      <affiliations>
       <institution>
        <institution_name>Liberal Arts Department, American University of the Middle East, Kuwait</institution_name>
       </institution>
      </affiliations>
     </person_name>
    </contributors>
    <jats:abstract>
     <jats:p>The integration of the Analytic Hierarchy Process (AHP), the Delphi method, and neutrosophic logic provides a powerful framework for complex decision-making, allowing for an enhanced handling of uncertainties and multiple criteria that characterizes many strategic planning and policy formulation scenarios. AHP’s structured approach helps decompose decision-making into manageable sub-problems, while the Delphi method facilitates expert consensus through iterative rounds, enriching the decision-making process with diverse expert insights. The inclusion of neutrosophic logic allows for better representation and processing of uncertainty, offering a flexible way to handle indeterminate and contradictory information. This robust methodology not only improves the precision of decisions but also adapts to the nuanced requirements of multifaceted decision environments. Future research could benefit from integrating these methods with technological advancements like artificial intelligence to automate and optimize the decision-making process further. Applying this integrated approach in various sectors such as healthcare, environmental management, and urban planning could also provide valuable insights into its effectiveness and scalability.</jats:p>
    </jats:abstract>
    <publication_date media_type="online">
     <year>2024</year>
    </publication_date>
    <pages>
     <first_page>58</first_page>
     <last_page>67</last_page>
    </pages>
    <publisher_item>
     <item_number item_number_type="article-number">2721</item_number>
    </publisher_item>
    <ai:program name="AccessIndicators">
     <ai:license_ref applies_to="vor">https://creativecommons.org/licenses/by/4.0/</ai:license_ref>
    </ai:program>
    <doi_data>
     <doi>10.54216/IJNS.240206</doi>
     <resource>https://www.americaspg.com/journal/21/article/2721</resource>
     <collection property="text-mining">
      <item>
       <resource mime_type="application/pdf">https://www.americaspg.com/storage/81737392586.pdf</resource>
      </item>
     </collection>
    </doi_data>
   </journal_article>
  </journal>
 </body>
</doi_batch>
