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Exploring, Categorisation and Usage of Artificial Intelligence Algorithms for Supply Chain Management

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F23%3A43924526" target="_blank" >RIV/62156489:43110/23:43924526 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.doi.org/10.17512/CUT/9788371939563/18" target="_blank" >https://www.doi.org/10.17512/CUT/9788371939563/18</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.17512/CUT/9788371939563/18" target="_blank" >10.17512/CUT/9788371939563/18</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Exploring, Categorisation and Usage of Artificial Intelligence Algorithms for Supply Chain Management

  • Original language description

    This paper explores the categorisation and usage of Artificial intelligence Algorithms (AIA) in Supply Chain Management (SCM) and discusses the potential benefits and challenges of implementing AI in SCM. The study reviews the literature on the application of AI in SCM. It provides a comprehensive list of commonly used algorithms in different SCM applications, such as vendor selection, production planning, resource allocation, quality control, predictive maintenance, visibility, demand forecasting, inventory optimisation, transportation optimisation, and customer segmentation. The paper highlights the versatility and potential for the cross-functional use of many AI algorithms. It identifies challenges and limitations, including data quality and availability, privacy and security concerns, and a lack of understanding and trust in AI systems. The study concludes that AI has the potential to significantly impact SCM by increasing efficiency, accuracy, and flexibility while reducing costs. However, further research is needed to develop best practices for adopting and implementing AI in SCM and to address ethical implications related to AI in SCM.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2023

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    International Conference on Management „Sustainability – Security – Quality“: Book of Proceedings

  • ISBN

    978-83-7193-956-3

  • ISSN

  • e-ISSN

  • Number of pages

    9

  • Pages from-to

    118-126

  • Publisher name

    Czestochowa University of Technology

  • Place of publication

    Częstochowa

  • Event location

    Czestochowa

  • Event date

    Jun 15, 2023

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article