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    Disruptive Technologies in Agricultural Operations: A Systematic Review of AI-driven AgriTech Research

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    Publication date
    2021-01
    End of Embargo
    2022
    Author
    Spanaki, K.
    Sivarajah, Uthayasankar
    Fakhimi, M.
    Despoudi, S.
    Irani, Zahir
    Keyword
    Disruptive technologies
    Agricultural operations
    AgriTech
    Agricultural technology
    Artificial Intelligence
    AI
    Systematic literature review
    Rights
    (c) 2021 SpringerNature. Full-text reproduced in accordance with the publisher's self-archiving policy.
    Peer-Reviewed
    Yes
    
    Metadata
    Show full item record
    Abstract
    The evolving field of disruptive technologies has recently gained significant interest in various industries, including agriculture. The fourth industrial revolution has reshaped the context of Agricultural Technology (AgriTech) with applications of Artificial Intelligence (AI) and a strong focus on data-driven analytical techniques. Motivated by the advances in AgriTech for agrarian operations, the study presents a state-of-the-art review of the research advances which are, evolving in a fast pace over the last decades (due to the disruptive potential of the technological context). Following a systematic literature approach, we develop a categorisation of the various types of AgriTech, as well as the associated AI-driven techniques which form the continuously shifting definition of AgriTech. The contribution primarily draws on the conceptualisation and awareness about AI-driven AgriTech context relevant to the agricultural operations for smart, efficient, and sustainable farming. The study provides a single normative reference for the definition, context and future directions of the field for further research towards the operational context of AgriTech. Our findings indicate that AgriTech research and the disruptive potential of AI in the agricultural sector are still in infancy in Operations Research. Through the systematic review, we also intend to inform a wide range of agricultural stakeholders (farmers, agripreneurs, scholars and practitioners) and to provide research agenda for a growing field with multiple potentialities for the future of the agricultural operations.
    URI
    http://hdl.handle.net/10454/18287
    Version
    Accepted manuscript
    Citation
    Spanaki K, Sivarajah U, Fakhimi M et al (2021) Disruptive Technologies in Agricultural Operations: A Systematic Review of AI-driven AgriTech Research. Annals of Operations Research. Accepted for publication.
    Link to publisher’s version
    http://doi.org/10.1007/s10479-020-03922-z
    Type
    Article
    Notes
    The full-text will be released for public view at the end of the publisher embargo, 12 months from first publication.
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    Management and Law Publications

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