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    DATA-DRIVEN DECISION INTELLIGENCE MODEL TO SUPPORT VALUE-ORIENTED MANAGEMENT IN THE GOVERNMENT INSTITUTES

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    Muna Alfadhli_ OGS Approved Dissertation.pdf (4.992Mb)
    Date
    2024-06
    Author
    ALFADHLI, MUNA SALEM
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    Abstract
    This dissertation focuses on devising a framework to prepare government institutions for implementing Artificial Intelligence towards value-oriented management. It explores the factors influencing AI readiness in government institutions, focusing specifically on two critical areas: digital transformation (and its components) and data management (and its components). The study seeks to uncover the elements essential for preparing government bodies for AI implementation through an in-depth examination of the factors in these two areas. The objective of the study is to determine the requirements of AI Readiness for government institutions, proposing a framework to assess the digital transformation maturity level within these institutions to prepare the IT environment for AI, investigate the importance of data management, and assess the maturity level of data management in government organization to know and monitor progress and achieve an organizational level which is reflected on AI index for country government. The dissertation contributes to the body of research knowledge in several ways. It promotes research efforts to enhance the organizational performance of government institutes, as the focus of most research in this domain has been on corporate and business organizations. Firstly, the dissertation introduces a hybrid model for assessing the digital transformation maturity of government organizations. While existing maturity assessment models primarily cater to corporate organizations and their financial gains, this hybrid model, developed using the Analytic Hierarchy Process (AHP) and evaluated by Subject Matter Experts (SMEs), is tailored to the unique needs of government institutions. It enables them to assess their digital transformation progress and align their efforts with the value embedded in their vision and mission. Secondly, the dissertation provides an empirical study on evaluating a government organization's capabilities in Data management to drive business insights and decision-making. Finally, by addressing the specific requirements of both two areas Digital transformation (DT) and Data management (DM) we found that the AI readiness is strongly affected by both of these areas. Then we deploy decision intelligence modeling for AI readiness in government institutions, this research provides valuable insights for achieving value-oriented management in these organizations.
    DOI/handle
    http://hdl.handle.net/10576/58771
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    • Engineering Management [‎140‎ items ]

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