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Drivers and barriers to precision agriculture technology and digitalisation adoption: Meta-analysis of decision choice models

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41110%2F24%3A100842" target="_blank" >RIV/60460709:41110/24:100842 - isvavai.cz</a>

  • Result on the web

    <a href="https://link.springer.com/article/10.1007/s11119-024-10213-1" target="_blank" >https://link.springer.com/article/10.1007/s11119-024-10213-1</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/s11119-024-10213-1" target="_blank" >10.1007/s11119-024-10213-1</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Drivers and barriers to precision agriculture technology and digitalisation adoption: Meta-analysis of decision choice models

  • Original language description

    The article defines the key determinants of adopting precision agriculture technologies and digitalisation. The research objectives are fulfilled by the systematic review and meta-analysis of relevant studies, identified and selected in accordance with the PRISMA protocol in the Web of Science and Scopus databases. The findings emphasize the importance of socio-economic factors, such as education, age, and farm size. High technical literacy and adequate information about new technologies—including their expected profitability—are crucial for assessing the benefits of precision agriculture and digitalisation, on which a more considerable expansion of these technologies into the practice of agricultural entities depends. Large and capital-intensive enterprises are more likely to implement new technologies in production practices, especially if they are led by younger and more educated managers who are more open to modern technologies and are more willing to take risks.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    40100 - Agriculture, Forestry, and Fisheries

Result continuities

  • Project

    <a href="/en/project/QK23020058" target="_blank" >QK23020058: Precision agriculture and digitization in the Czech Republic</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Precision Agriculture

  • ISSN

    1385-2256

  • e-ISSN

    1385-2256

  • Volume of the periodical

    26

  • Issue of the periodical within the volume

    1

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    30

  • Pages from-to

    1-30

  • UT code for WoS article

    001385850700002

  • EID of the result in the Scopus database