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Exploring the drivers of responsible scaling of Agriculture 4.0 technologies for transformative impact in the modern agri-food ecosystem: An ISM-based analysis

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Autor(es):
da Silveira, Franco ; Smania, Guilherme Sales ; Landaverde, Rafael ; Osiro, Lauro ; Bolfe, Edson Luis ; Romani, Luciana Alvim Santos ; Barbedo, Jayme Garcia Arnal
Número total de Autores: 7
Tipo de documento: Artigo Científico
Fonte: AGRICULTURAL SYSTEMS; v. 231, p. 17-pg., 2026-01-01.
Resumo

CONTEXT: The emergence of Agriculture 4.0 has revolutionized the agri-food system, introducing technologies like AI, IoT, drones, and digital twins that reshape traditional practices and offer new opportunities to address food crises driven by climate change, population growth, and resource scarcity. The adoption of these technologies has gained global interest, and concepts like "drivers" have been used to explain the forces behind this transformation. However, studies on these drivers and their interrelationships remain scarce, highlighting a gap in understanding the factors influencing the adoption of Agriculture 4.0. OBJECTIVE: This research, therefore, explores this context by identifying the key drivers for the adoption of Agriculture 4.0 technologies in the modern agri-food ecosystem. Additionally, it identifies the interrelationships and hierarchical structures among these drivers, providing insights to tackle the challenges of complex agri-food systems and prioritize key issues for their modernization. METHODS: A total of eighteen drivers were identified through a Systematic Literature Review (SLR) and classified into three clusters: Technological Drivers (TD), Political Drivers (PD), and Social Drivers (SD). Subsequently, ten experts established contextual relationships among all these drivers. The Interpretive Structural Modeling (ISM) method was applied, along with the fuzzy Matrix Impact of Cross Multiplication Applied to Classification (MICMAC) analysis, which enabled the identification of Agriculture 4.0 drivers with high driving power and those that are dependent. RESULTS AND CONCLUSIONS: The study's findings reveal that the most influential drivers- rural connectivity, rural youth, governmental pressure, information disclosure mechanisms, and ecosystem representativeness- hold the greatest driving power in shaping the adoption dynamics of Agriculture 4.0 technologies. These elements act as core levers that not only directly influence adoption but also amplify the effect of other drivers within the agri-food system. When these primary drivers are overlooked, they can generate structural and social bottlenecks that hinder- or even block- the effective integration of Agriculture 4.0, especially in small rural and resource-limited contexts. From a strategic perspective, enhancing rural connectivity and fostering the active participation of rural youth emerge as foundational actions to strengthen long-term adoption capacity. In parallel, policymakers should reinforce governance frameworks that ensure transparency, facilitate the free flow of reliable information, and integrate ecosystem diversity and representativeness into agricultural innovation policies. By addressing these interconnected drivers in synergy with other enabling drivers across their respective clusters, it becomes possible to accelerate the transition toward more equitable, productive, and sustainable agrifood ecosystems in both developing and developed regions. SIGNIFICANCE: This research's results contribute to a more meaningful adoption of Agriculture 4.0 technologies across different regions and countries, paving the way for a fairer and more equitable implementation while supporting the development of more productive, resilient, and sustainable agri-food systems. Although the evidence is drawn from the Brazilian context, the insights and recommendations are also relevant for other regions seeking to modernize their agri-food ecosystems. (AU)

Processo FAPESP: 23/12215-3 - Proposição de Estratégias para Superar as Barreiras que Dificultam a Implementação das Tecnologias da Agricultura 4.0: um estudo de caso nos Distritos Agro-Tecnológicos (DATs)
Beneficiário:Franco da Silveira
Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado
Processo FAPESP: 22/09319-9 - Centro de Ciência para o Desenvolvimento em Agricultura Digital - CCD-AD/SemeAr
Beneficiário:Silvia Maria Fonseca Silveira Massruhá
Modalidade de apoio: Auxílio à Pesquisa - Centros de Ciência para o Desenvolvimento