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<journal-meta>
<journal-id journal-id-type="publisher">global-journal-of-management-and-business-research-a-administration-management</journal-id>
<journal-title-group>
<journal-title>Global Journal of Management and Business Research - A: Administration &amp; Management</journal-title>
</journal-title-group>
<issn publication-format="print">0975-5853</issn>
<issn publication-format="electronic">2249-4588</issn>
<publisher><publisher-name>Global Journals Publishing Group Incorporated</publisher-name></publisher>
<self-uri xlink:href="https://globaljournals.org/journal-seo-export/jats/56390.xml" />
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<article-meta>
<article-id pub-id-type="publisher-id">56390</article-id>
<title-group>
<article-title>Using Artificial Intelligence for Quantifying Strategic Business-It Alignment</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author"><name><surname>Diab</surname><given-names>Bassel</given-names></name><xref ref-type="aff" rid="aff1" />
</contrib>
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<aff id="aff1">ROMANIA</aff>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2021-10-15">
<day>15</day>
<month>10</month>
<year>2021</year>
</pub-date>
<volume>21</volume>
<issue>A1</issue>
<fpage>57</fpage>
<lpage>64</lpage>
<abstract><p>This paper aims to test an artificial model and a calculator the author developed based on deep learning, Neural Networks, and machine learning, Random Forest. The “Diab BITA Model” and the “Diab Calculator” are generated to enable organizations of any size and in any industry, of calculating the value of Strategic Business-IT Alignment (BITA) following a scale of 7 degrees. Principally, the same sample of one of his previous papers is addressed in which top Managers subjectively assessed the BITA maturity; the current paper targets to empirically prove the accuracy of managers’ perceptions using both the model and the calculator. Findings show an 89% accuracy rate in estimating those organizations’ BITA levels using the model and 92% using the calculator.</p></abstract>
<kwd-group kwd-group-type="author-generated">
<kwd>deep learning</kwd>
<kwd>machine learning</kwd>
<kwd>diab BITA model</kwd>
<kwd>diab calculator</kwd>
</kwd-group>
<self-uri content-type="pdf" xlink:href="https://globaljournals.org/GJMBR_Volume21/5-Using-Artificial-Intelligence.pdf" />
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<title>Full Text</title>
<p>This paper aims to test an artificial model and a calculator the author developed based on deep learning, Neural Networks, and machine learning, Random Forest. The â€œDiab BITA Modelâ€ and the â€œDiab Calculatorâ€ are generated to enable organizations of any size and in any industry, of calculating the value of Strategic Business-IT Alignment (BITA) following a scale of 7 degrees.</p>
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