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  <doi_batch_id>aspg-1-2319-1791417761</doi_batch_id>
  <timestamp>20261008000241</timestamp>
  <depositor>
   <depositor_name>American Scientific Publishing Group</depositor_name>
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  <journal>
   <journal_metadata language="en">
    <full_title>American Journal of Business and Operations Research</full_title>
    <abbrev_title>AJBOR</abbrev_title>
    <issn media_type="print">2770-0216</issn>
    <issn media_type="electronic">2692-2967</issn>
   </journal_metadata>
   <journal_issue>
    <publication_date media_type="online">
     <year>2019</year>
    </publication_date>
    <journal_volume>
     <volume>0</volume>
    </journal_volume>
    <issue>2</issue>
   </journal_issue>
   <journal_article publication_type="full_text">
    <titles>
     <title>Strategic Resource Allocation in Project Management: A Data-Driven Framework</title>
    </titles>
    <contributors>
     <person_name sequence="first" contributor_role="author">
      <given_name>Abedallah Z.</given_name>
      <surname>Abualkishik</surname>
      <affiliations>
       <institution>
        <institution_name>American University in the Emirates, Dubai, UAE</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Rasha</given_name>
      <surname>Almajed</surname>
      <affiliations>
       <institution>
        <institution_name>American University in the Emirates, Dubai, UAE</institution_name>
       </institution>
      </affiliations>
     </person_name>
    </contributors>
    <jats:abstract>
     <jats:p>Effective project management relies on smart resource allocation strategies that navigate the complexities, in project dynamics. However, it is important to consider factors when choosing projects for a portfolio and allocating resources to that portfolio. In this paper, we present a data-driven framework for strategic resource allocation in project management. By using the Fuzzy TOPSIS method this framework combines evaluations into a model improving decision-making accuracy. Our study identifies ten factors that contribute to project complexity and transforms opinions into fuzzy numbers to evaluate project performance. When we applied this framework to five projects, we gained insights into how they align with established criteria resulting in nuanced rankings based on calculated closeness coefficients. This research lays the foundation for resource allocation strategies by advocating for the integration of dynamic data sources and advanced analytical techniques. The goal is to enhance adaptability and facilitate implementation, within project management paradigms.</jats:p>
    </jats:abstract>
    <publication_date media_type="online">
     <year>2019</year>
    </publication_date>
    <pages>
     <first_page>97</first_page>
     <last_page>103</last_page>
    </pages>
    <publisher_item>
     <item_number item_number_type="article-number">2319</item_number>
    </publisher_item>
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     <ai:license_ref applies_to="vor">https://creativecommons.org/licenses/by/4.0/</ai:license_ref>
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    <doi_data>
     <doi>10.54216/AJBOR.000204</doi>
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