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    <journal-meta>
      <journal-id journal-id-type="nlm-ta">REA Press</journal-id>
      <journal-id journal-id-type="publisher-id">Null</journal-id>
      <journal-title>REA Press</journal-title><issn pub-type="ppub">3042-0180</issn><issn pub-type="epub">3042-0180</issn><publisher>
      	<publisher-name>REA Press</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">https://doi.org/10.22105/scfa.v1i1.17</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
        <subj-group><subject>Artificial intelligence</subject><subject>Cloud systems</subject><subject>Information technology industry</subject><subject>Barriers</subject><subject>Multi-criteria decision making</subject><subject>Strategy</subject></subj-group>
      </article-categories>
      <title-group>
        <article-title>Multi-Criteria Decision-Making Model for Rank Strategy to Overcome Barriers to Integrating the AI and Cloud Systems in the IT Industry</article-title><subtitle>Multi-Criteria Decision-Making Model for Rank Strategy to Overcome Barriers to Integrating the AI and Cloud Systems in the IT Industry</subtitle></title-group>
      <contrib-group><contrib contrib-type="author">
	<name name-style="western">
	<surname>Abdelhafeez</surname>
		<given-names>Ahmed</given-names>
	</name>
	<aff>Faculty of Information Systems and Computer Science, October 6th University, Cairo, Egypt.</aff>
	</contrib><contrib contrib-type="author">
	<name name-style="western">
	<surname>Shawky Aziz</surname>
		<given-names>Alber</given-names>
	</name>
	<aff>Faculty of Information Systems and Computer Science, October 6th University, Cairo, Egypt.</aff>
	</contrib></contrib-group>		
      <pub-date pub-type="ppub">
        <month>01</month>
        <year>2023</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>16</day>
        <month>01</month>
        <year>2023</year>
      </pub-date>
      <volume>1</volume>
      <issue>1</issue>
      <permissions>
        <copyright-statement>© 2023 REA Press</copyright-statement>
        <copyright-year>2023</copyright-year>
        <license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/2.5/"><p>This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p></license>
      </permissions>
      <related-article related-article-type="companion" vol="2" page="e235" id="RA1" ext-link-type="pmc">
			<article-title>Multi-Criteria Decision-Making Model for Rank Strategy to Overcome Barriers to Integrating the AI and Cloud Systems in the IT Industry</article-title>
      </related-article>
	  <abstract abstract-type="toc">
		<p>
			This study proposed a decision-making framework for identifying key barriers when implementing Artificial Intelligence (AI) and cloud systems in the Information Technology (IT) industry. Then, it proposed a set of strategies to overcome these barriers. We proposed a Multi-Criteria Decision-Making (MCDM) methodology  for various criteria. Multiple barriers, such as cost, technology, environment, and digitization, should be analyzed. The Evaluation-based on Distance from Average Solution (EDAS) method is an MCDM method logy used to rank the alternatives. The criteria weights are computed by the average method. This study used ten barriers and ten strategies. The results show that technological barriers have the highest importance in this study. The sensitivity analysis is conducted to show the stability rank of alternatives. There are eleven cases in which criteria weights are proposed. Then, the EDAS method is used to rank the other options. The results show the stability of the rank under different cases.
		</p>
		</abstract>
    </article-meta>
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