IDEAS home Printed from https://ideas.repec.org/p/mde/wpaper/180.html
   My bibliography  Save this paper

Artificial Intelligence in Agriculture: Revolutionizing Methods and Practices in Portugal

Author

Listed:
  • Maria José Sousa

    (ISCTE Instituto Universitário de Lisboa)

Abstract

Artificial Intelligence (AI) has emerged as a focal point for researchers and industry experts, continuously redefined by technological advancements. AI encompasses the development of machines impersonating human cognitive processes, such as learning, reasoning, and self-correction. Its wide-ranging applications across industries have showcased its increasing precision and efficiency, and Agriculture has also embraced AI to increase income and efficiency. In this regard a literature review to comprehensively understand the concept, existing research, and projects related to AI in agriculture was performed. Moreover, this paper approaches the potential of AI in agriculture practically, addressing the emergence of new methods and practices, using a case study approach, and analyzing the perceptions of impacts of AI in agriculture, from experts, academics, and agriculture professionals regarding the application of AI. It contributes to real application development, offering insights that resonate within academic and practical dimensions.

Suggested Citation

  • Maria José Sousa, "undated". "Artificial Intelligence in Agriculture: Revolutionizing Methods and Practices in Portugal," GEE Papers 180, Gabinete de Estratégia e Estudos, Ministério da Economia.
    • Handle: RePEc:mde:wpaper:180
    as

    Download full text from publisher

    File URL: https://www.gee.gov.pt//RePEc/WorkingPapers/GEE_PAPERS_180.pdf
    File Function: First version, 2024
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Carlo Bagnoli & Francesca Dal Mas & Maurizio Massaro, 2019. "The 4th Industrial Revolution: Business Models and Evidence From the Field," International Journal of E-Services and Mobile Applications (IJESMA), IGI Global, vol. 11(3), pages 34-47, July.
    2. Carlo Bagnoli & Maurizio Massaro & Francesca Dal Mas & Matteo Demartini, 2018. "Defining The Concept Of Business Model: Searching For A Business Model Framework," International Journal of Knowledge and Systems Science (IJKSS), IGI Global, vol. 9(3), pages 48-64, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Maurizio Massaro & Francesca Dal Mas & Charbel Jose Chiappetta Jabbour & Carlo Bagnoli, 2020. "Crypto‐economy and new sustainable business models: Reflections and projections using a case study analysis," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 27(5), pages 2150-2160, September.
    2. Maurizio Massaro & Silvana Secinaro & Francesca Dal Mas & Valerio Brescia & Davide Calandra, 2021. "Industry 4.0 and circular economy: An exploratory analysis of academic and practitioners' perspectives," Business Strategy and the Environment, Wiley Blackwell, vol. 30(2), pages 1213-1231, February.
    3. Dal Mas, F. & Massaro, M. & Ndou, V. & Raguseo, E., 2023. "Blockchain technologies for sustainability in the agrifood sector: A literature review of academic research and business perspectives," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
    4. Zhang Zhen & Zahid Yousaf & Magdalena Radulescu & Muhammad Yasir, 2021. "Nexus of Digital Organizational Culture, Capabilities, Organizational Readiness, and Innovation: Investigation of SMEs Operating in the Digital Economy," Sustainability, MDPI, vol. 13(2), pages 1-15, January.
    5. Nicoletta Fadda & Gianfranco Pischedda & Ludovico Marin? & katia Corsi, 2021. "Sustainable-oriented management come fattore di resilienza organizzativa. Un caso di studio," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2021(2), pages 39-60.
    6. Essen, Anna & Frishammar, Johan & Cenamor, Javier, 2023. "Entering non-platformized sectors: The Co-evolution of legitimacy debates and platform business models in digital health care," Technovation, Elsevier, vol. 121(C).

    More about this item

    Keywords

    Artificial Intelligence; Agriculture; Efficiency; Quantitative analysis;
    All these keywords.

    JEL classification:

    • D20 - Microeconomics - - Production and Organizations - - - General
    • Q16 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - R&D; Agricultural Technology; Biofuels; Agricultural Extension Services

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:mde:wpaper:180. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joana Almodovar (email available below). General contact details of provider: https://edirc.repec.org/data/geegvpt.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.