Financing sustainable farming: The role of trust in the adoption of fintech by farmers
基于初始信任模型，研究德国农民对农业金融科技的信任影响因素，发现数据安全保障和感知价值能显著提升信任，为推广金融科技、促进可持续农业提供策略参考。
The (digital) transition to sustainable agricultural production practices requires substantial capital that is accessible to farmers implementing system changes. FinTech solutions leveraging AI-driven big data analytics can enhance capital access through data-driven loan criteria, offering an alternative to standardised, traditional banking approaches. Yet, despite these advantages, adoption remains low due to limited trust in these technologies. Based on the initial trust model, this study investigates five antecedents of farmers' initial trust in agricultural FinTech: strategic partnerships, structural assurances in data processing and storage, farmers' propensity to trust, and perceived relative benefits. Quantitative data from 101 German farm managers, collected at agricultural trade fairs, were analysed using partial least squares structural equation modelling (PLS-SEM). Results reveal that structural assurances and perceived added value significantly increase trust, while individual trust propensity varies. The findings inform targeted marketing strategies and help to develop specific application features to ensure the successful implementation of FinTech solutions in agriculture. The results further highlight the importance of providing clear information about data processes and benefits to build trust and support FinTech adoption among farmers, ultimately contributing to more resilient and sustainable agricultural systems.