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A Systematic Review of the Use of Artificial Intelligence in Managing Innovation in E-Government Organizations Worldwide

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  • Mayid Alshaer

Abstract

Purpose: This paper delivers a methodical literature review that focuses on the application of artificial intelligence (AI) to handle innovation within e-government organizations globally. Methodology: Showcasing meticulousness, the review utilized a structured method to scrutinize 11 academic studies obtained from established, globally renowned databases, such as Scopus and Web of Science. Findings: The findings underscore an expansive array of AI applications within e-government's innovation management, incorporating data-led decision processes, chatbots for effective consumer service, sentiment inspection for useful citizen critique, and predictive analysis for service refinement. Conversely, incorporating AI within e-government establishments encounters considerable hurdles regarding data presence and integrity, transparency and interoperability concerns, ethical considerations, as well as sustainability and expansion challenges. The review strongly underlines the necessity for calculated investments towards resource augmentation and technological infrastructure. Unique Contribution to Theory, Practice and Policy: The integration of artificial intelligence (AI) into e-government innovation may shape the direction of ensuing research in digital governance and public administration. Beneficiaries of the comprehensive insights this scholarly study offers include e-government experts, scholars, and tech innovators hailing from manifold geographical spaces. The findings of this study could be resourceful for top-tier decision-makers in national and local e-government organizations, allowing them to refine their strategies for AI amalgamation and enhance service provision.

Suggested Citation

  • Mayid Alshaer, 2023. "A Systematic Review of the Use of Artificial Intelligence in Managing Innovation in E-Government Organizations Worldwide," International Journal of Technology and Systems, IPRJB, vol. 8(2), pages 65-81.
    • Handle: RePEc:bdu:ojijts:v:8:y:2023:i:2:p:65-81:id:2164
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    References listed on IDEAS

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    3. Ioannis Kosmas & Theofanis Papadopoulos & Georgia Dede & Christos Michalakelis, 2023. "The Use of Artificial Neural Networks in the Public Sector," FinTech, MDPI, vol. 2(1), pages 1-15, March.
    4. Catalin Vrabie, 2023. "E-Government 3.0: An AI Model to Use for Enhanced Local Democracies," Sustainability, MDPI, vol. 15(12), pages 1-19, June.
    5. Mariani, Marcello M. & Machado, Isa & Magrelli, Vittoria & Dwivedi, Yogesh K., 2023. "Artificial intelligence in innovation research: A systematic review, conceptual framework, and future research directions," Technovation, Elsevier, vol. 122(C).
    6. Amine Belhadi & Sachin Kamble & Samuel Fosso Wamba & Maciel M. Queiroz, 2022. "Building supply-chain resilience: an artificial intelligence-based technique and decision-making framework," International Journal of Production Research, Taylor & Francis Journals, vol. 60(14), pages 4487-4507, July.
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