The global food system is characterized by market concentration and oligopoly. In our article, we focus on the most powerful input supply and machinery companies and analyze how these firms create value, both economic and otherwise, from big data. In digital capitalism, data is valorized across sectors; personal data is aggregated into large-scale datasets, a practice that feeds economic concentration and monopolization. Big data also has become central to the business model for agricultural companies; it is a claim made by the companies themselves. Yet, little is known about their specific strategies to do so. We aim to fill this gap, asking how is agricultural data transformed into value by the most powerful agribusinesses and ag-tech firms?Through the lens of assetization, we examine corporate strategies for transforming agricultural data into value. We draw on literature from food studies, specifically political economic analyses of the historical practices of agricultural corporations, as well as literature from critical data studies that investigates data as an asset. For our analysis, we rely on a variety of gray literature and public-facing documents: financial documents, sustainability and shareholder reports, terms of use, license agreements, and news articles. Our results contribute to the critical data studies literature on agricultural big data by identifying three main strategies of assetization: securing relationships and dependence, price-setting and data sharing, and product development and targeted marketing.The strategies have socio-ecological implications; our results indicate the reproduction of asymmetrical power relations in the agri-food system favoring corporations and the continuation of long-standing dynamics of inequalities.

中文翻译：

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收获价值：农业数据资产化的企业战略及其社会生态影响

全球粮食体系的特点是市场集中和寡头垄断。在我们的文章中，我们关注最强大的投入供应和机械公司，并分析这些公司如何通过大数据创造经济和其他价值。在数字资本主义中，数据在各个部门都具有价值。个人数据被汇总成大规模数据集，这种做法助长了经济集中和垄断。大数据也已成为农业公司商业模式的核心；这是公司自己提出的主张。然而，人们对他们这样做的具体策略知之甚少。我们的目标是填补这一空白，询问最强大的农业企业和农业科技公司如何将农业数据转化为价值？通过资产化的视角，我们研究了将农业数据转化为价值的企业策略。我们借鉴食品研究文献，特别是对农业公司历史实践的政治经济分析，以及将数据作为资产进行调查的关键数据研究文献。在我们的分析中，我们依赖于各种灰色文献和面向公众的文件：财务文件、可持续发展和股东报告、使用条款、许可协议和新闻文章。我们的研究结果通过确定资产化的三种主要策略，为农业大数据的关键数据研究文献做出贡献：确保关系和依赖、定价和数据共享、产品开发和有针对性的营销。这些策略具有社会生态影响；我们的研究结果表明，农业食品体系中不对称权力关系的再现有利于企业，并且不平等的长期动态仍在继续。