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Analysis of the use of artificial intelligence and machine learning in commodity markets

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23510%2F24%3A43974322" target="_blank" >RIV/49777513:23510/24:43974322 - isvavai.cz</a>

  • Result on the web

    <a href="https://drive.google.com/file/d/10ufGZtWvb5rX9EMVbkMBC4wVKNq80q8_/view" target="_blank" >https://drive.google.com/file/d/10ufGZtWvb5rX9EMVbkMBC4wVKNq80q8_/view</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Analysis of the use of artificial intelligence and machine learning in commodity markets

  • Original language description

    This bibliometric study provides a literature review analyzing the use of artificial intelligence (AI) and machine learning (ML) in commodity markets. We identify the development of the number of publications as a function of time and types of publications, authors and institutions, interconnectedness of citations, literature production in individual countries, and areas of research topics. Using co-occurrence method, the study offers an overview of the current development trends using AI and ML to analyze commodity markets. Furthermore, the study points to possible directions for further research by defining research gaps and formulating an overview of calls for further research.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    50202 - Applied Economics, Econometrics

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2024

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Conference Proceedings – Business Trends 2024

  • ISBN

    978-80-261-1270-9

  • ISSN

  • e-ISSN

  • Number of pages

    24

  • Pages from-to

    111-134

  • Publisher name

    Západočeská univerzita v Plzni

  • Place of publication

    Plzeň

  • Event location

    Plzeň

  • Event date

    Nov 21, 2024

  • Type of event by nationality

    EUR - Evropská akce

  • UT code for WoS article