Hernández-Cruz X., Villalobos J.R., Runger G., Neal G. (2023). Building an intelligent system to identify trends in agricultural markets. Journal of Cleaner Production, 01/11/2023, vol. 425, p. 138956.
https://doi.org/10.1016/j.jclepro.2023.138956
https://doi.org/10.1016/j.jclepro.2023.138956
Titre : | Building an intelligent system to identify trends in agricultural markets (2023) |
Auteurs : | X. Hernández-Cruz ; J.R. Villalobos ; G. Runger ; G. Neal |
Type de document : | Article |
Dans : | Journal of Cleaner Production (vol. 425, November 2023) |
Article en page(s) : | p. 138956 |
Langues : | Anglais |
Langues du résumé : | Anglais |
Catégories : |
Catégories principales 11 - COMMERCE ; 11.1 - Commerce (général ou théorique)Thésaurus IAMM MARCHE DES PRODUITS DE BASE ; MARCHE ; SYSTEME D'INFORMATION ; TENDANCE ; TECHNIQUE DE PREVISION ; CHAINE D'APPROVISIONNEMENT ; AIDE A LA DECISION |
Résumé : | In recent years, scholars and practitioners have discussed several challenges related to the fresh-food supply chains (SCs). One of these challenges is the lack of availability of curated, clean, and processed market information for the SC participants to use to aid in their decision-making process. For example, small growers often feel uncertain because they have little insight into which crops to plant so they will have a market to sell them to. Consequently, some growers are only able to sell parts of their harvest or decide not to harvest at all which causes food waste. This work aims to create a centralized market intelligence platform to acquire market information, curate it, analyze it, and connect this platform to the rest of an emerging intelligent supply chain. It is essential to take into consideration market intelligence to reduce losses related to market prices and demands, avoid scarcity events in which food availability and affordability decrease, and aid small growers by alerting them of future market opportunities A market intelligence layered system framework is developed in this work to collect relevant market indicator data including non-traditional data sources, monitor them, diagnose the market's state, and provide recommendations to the SC participants such as which crops and markets will be most promising in the future. A case study based on the 2019 market event in which celery prices increased across the United States terminal markets is provided. Through the case study, the proposed market intelligence framework is illustrated with focus on the first three layers: data collection, processing, and monitoring. Furthermore, the case study illustrates the usefulness of monitoring non-traditional data to identify market events with greater anticipation. Results indicate that the monitoring of non-traditional data was able to capture the anomalous event with greater time of anticipation than another traditional data source. |
Cote : | Réservé lecteur CIHEAM |
URL / DOI : | https://doi.org/10.1016/j.jclepro.2023.138956 |