| Titre : | Data value creation in agriculture: a review (2024) |
| Auteurs : | H. Uyar ; I. Karvelas ; S. Rizou ; S. Fountas |
| Type de document : | Article |
| Dans : | Computers and Electronics in Agriculture (vol. 227, part. II, December 2024) |
| Article en page(s) : | p. 109602 |
| Langues : | Anglais |
| Langues du résumé : | Anglais |
| Catégories : |
Catégories principales 06 - AGRICULTURE. FORÊTS. PÊCHES ; 6.1 - Généralités. Situation AgricoleThésaurus IAMM AGRICULTURE ; DONNEE STATISTIQUE ; ANALYSE DE DONNEES ; CREATION DE VALEUR ; AIDE A LA DECISION |
| Résumé : | Agricultural data have great potential to improve decision-making, enhance operational efficiency, and drive innovation. Despite the growing acknowledgment of their value, there remains a gap in understanding how data value creation is perceived and implemented in agriculture. This study addresses this gap by investigating data value creation mechanisms, targets, and impacts through a structured literature review of 80 articles, including 13 core articles retrieved via targeted database searches and 67 additional articles identified through cross-reference snowballing. Key ?value creation mechanisms? are categorized as transparency and access, discovery and experimentation, prediction and optimization, customization and targeting, learning and crowdsourcing, and monitoring and adaptation. The value creation mechanisms aim to enhance key ?targets?, namely organizational performance, business process improvement, product and service innovation, and consumer and market experience. Organization performance was the most frequently addressed value target, appearing in approximately 85% of the core articles, followed by business process improvement, highlighted in approximately 77% of the articles. Together, the mechanisms and targets create ?impact?, constructing the value of data. The findings reveal that all core articles (100%) emphasize the functional value of agricultural data, while 54% also explore their symbolic value, which enhances reputation and market positioning. A key takeaway is that, unlike many other assets, the value of agricultural data increases with reuse, which calls for a shift in focus from data ownership to ownership of the value derived from them. This study highlights the need for robust frameworks to fully realize the potential of agricultural data and calls for future research to further characterize and assess this value. These insights are essential for developing tools and methodologies that enhance productivity, sustainability, and profitability in agriculture. |
| Cote : | En ligne |
| URL / DOI : | https://doi.org/10.1016/j.compag.2024.109602 |
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