Wolvaardt, FrancoisFourie, Alicia2025-10-222025-09Wolvaardt, F. & Fourie, A. 2025, 'Leveraging big data analytics capabilities and data-driven decision-making to enhance farm-level performance in agriculture', African Journal of Innovation and Entrepreneurship, vol. 4, no. 3, pp. 211-234, doi : 10.31920/2753-314X/2025/v4n3a10.2753-3131 (print)2753-314X (online)10.31920/2753-314X/2025/v4n3a10http://hdl.handle.net/2263/104810Big data analytics offers actionable insights that enhance data-driven decision-making and improve firm performance by optimising production and reducing costs. While its application in agriculture is growing, research on its impact at the farm level is limited. This study aims to bridge this gap by exploring how data analytics capabilities can enhance decision-making and organisational performance in agriculture. Utilising a resource-based view and dynamic capabilities perspective, the study develops a research model connecting big data analytics capabilities, data-driven decision-making, and farm performance. An exploratory factor analysis and multiple regression analysis were conducted on data from 145 farming organisations in South Africa. The results indicate that big data analytics capabilities and data-driven decision-making positively affect farm performance. This research contributes to the data analytics literature by identifying key capabilities that enhance performance, offering practical insights for farmers and agricultural service providers seeking to leverage data analytics effectively.en© Adonis & Abbey Publishers.Big data analytics capabilitiesData-driven decision-makingFirm performanceAgricultureSmart farmingArticle