<?xml version="1.0" encoding="UTF-8"?>
<article article-type="Research Article">
  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher">journal-of-information-and-optimization-sciences</journal-id>
      <journal-title-group>
        <journal-title>Journal of Information and Optimization Sciences</journal-title>
      </journal-title-group>
      <issn publication-format="electronic">2169-0103</issn>
      <issn publication-format="print">0252-2667</issn>
      <publisher>
        <publisher-name>Taru Publications</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.47974/JIOS-1979</article-id>
      <title-group>
        <article-title>Sustainable evaluation of 3PL service for medical waste handling providers in Saudi healthcare using a hybrid fuzzy TOPSIS and clustering method</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes">
          <name>
            <surname>Aouadni</surname>
            <given-names>Sourour</given-names>
          </name>
          <aff>Department of Business Administration, College of Business, University of Bisha, Bisha, 61922, Saudi Arabia</aff>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Messaoudi</surname>
            <given-names>Laila</given-names>
          </name>
          <aff>Department of Quantitatives Methods, Research Unit 3E, Higher Institute of Management, University of Gabes, Gabes, Tunisia</aff>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Euchi</surname>
            <given-names>Jalel</given-names>
          </name>
          <aff>Department of Quantitatives Methods, Institut Supérieur de Gestion, University of Sousse, Sousse, Rue Abdlaaziz El Behi Bp, 763-4000, Tunisia</aff>
          <aff>Optimization Logistique et Informatique Décisionnelle Laboratory, Higher Institute of Industrial Management, Sfax-Route de Tunis km 10.5, University of Sfax, Technopole de Sfax, 3021 - BP 1164, Tunisia</aff>
        </contrib>
      </contrib-group>
      <fpage>1</fpage>
      <lpage>36</lpage>
      <pub-date date-type="pub">
        <day>01</day>
        <month>04</month>
        <year>2026</year>
      </pub-date>
      <abstract>
        <p>The process of selecting eco-friendly medical waste disposal services offered by 3PL presents a significant challenge in the healthcare sector, particularly in Saudi Arabia. This study suggests an integrated decision-making model that integrates fuzzy TOPSIS and clustering techniques to address this complex problem. The methodology evaluates 3PL providers using a multidimensional sustainability assessment encompassing social, economic, and environmental criteria. Fuzzy TOPSIS ranks the providers based on their performance across these criteria, and fuzzy clustering is then applied to group providers with similar performance characteristics. This clustering process enhances the decision-making framework by enabling the identification of patterns and trends among the alternatives, thus allowing for more informed decision-making. The evaluation framework involves the input of three experts and considers ten sustainability criteria across ten 3PL service providers within the Saudi healthcare system. Findings from this study support better decision-making in selecting 3PL partners for environmentally responsible medical waste handling.</p>
      </abstract>
      <kwd-group>
        <kwd>Sustainable logistics</kwd>
        <kwd>3PL provider selection</kwd>
        <kwd>Medical waste management</kwd>
        <kwd>Fuzzy TOPSIS</kwd>
        <kwd>Saudi healthcare system</kwd>
        <kwd>Environmental management</kwd>
        <kwd>Supply chain optimization</kwd>
      </kwd-group>
      <custom-meta-group>
        <custom-meta>
          <meta-name>access</meta-name>
          <meta-value>open</meta-value>
        </custom-meta>
        <custom-meta>
          <meta-name>retracted</meta-name>
          <meta-value>no</meta-value>
        </custom-meta>
      </custom-meta-group>
    </article-meta>
  </front>
</article>
