Forthcoming Articles

International Journal of Intelligent Systems Design and Computing

International Journal of Intelligent Systems Design and Computing (IJISDC)

Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

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International Journal of Intelligent Systems Design and Computing (One paper in press)

Regular Issues

  • The conceptual frameworks for global acceptance of artificial intelligence in the post-pandemic era   Order a copy of this article
    by Efosa Carroll Idemudia 
    Abstract: In 2024, the generative AI market was valued at $128 billion. To date, numerous firms, organisations, governments, and institutions have invested millions and billions of dollars in artificial intelligence to make informed decisions and gain a competitive advantage. To provide a holistic view and insights on how companies and institutions can utilise artificial intelligence to solve complex real-world problems, make informed decisions, and gain a competitive advantage in the post-pandemic era, we conducted our study. The theoretical background for our models and frameworks is the stakeholder theory. Our models and frameworks provide insights and understanding into how firms, companies, organisations, governments, and institutions can adapt to and adopt a wide range of artificial intelligence platforms. Our frameworks identify the key variables that influence the acceptance and usage of artificial intelligence. Our study has many managerial and research implications.
    Keywords: stakeholder theory; post-pandemic era; data; artificial intelligence; diverse team; algorithm design; public perception; environmental factors.
    DOI: 10.1504/IJISDC.2026.10077585
     

 

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