可持续农业融资：信任在农民采用金融科技中的作用

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change Pub Date : 2025-08-01 DOI:10.1016/j.techfore.2025.124302

Maximilian Antonius Köster , William Hurst , Caspar Krampe

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引用次数: 0

摘要

向可持续农业生产实践的（数字化）转型需要大量资金，农民可以利用这些资金实施制度变革。利用人工智能驱动的大数据分析的金融科技解决方案可以通过数据驱动的贷款标准来增强资本获取，为标准化的传统银行方法提供了另一种选择。然而，尽管有这些优势，由于对这些技术的信任有限，采用率仍然很低。基于初始信任模型，本研究考察了农民对农业金融科技初始信任的五个前因：战略合作伙伴关系、数据处理和存储的结构性保证、农民的信任倾向和感知的相对利益。从农业贸易展览会收集的101名德国农场经理的定量数据，使用偏最小二乘结构方程模型（PLS-SEM）进行分析。结果表明，结构保证和感知附加价值显著增加信任，但个体信任倾向存在差异。研究结果为有针对性的营销策略提供信息，并有助于开发特定的应用功能，以确保金融科技解决方案在农业领域的成功实施。研究结果进一步强调了提供有关数据流程和效益的明确信息的重要性，这有助于建立信任并支持农民采用金融科技，最终有助于建立更具弹性和可持续性的农业系统。

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Financing sustainable farming: The role of trust in the adoption of fintech by farmers

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.

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来源期刊

Technological Forecasting and Social Change Multiple-

CiteScore

21.30

自引率

10.80%

发文量

813

期刊介绍： Technological Forecasting and Social Change is a prominent platform for individuals engaged in the methodology and application of technological forecasting and future studies as planning tools, exploring the interconnectedness of social, environmental, and technological factors. In addition to serving as a key forum for these discussions, we offer numerous benefits for authors, including complimentary PDFs, a generous copyright policy, exclusive discounts on Elsevier publications, and more.