CONTEXT

Adoption and diffusion of digital farming technologies are expected to help transform current agricultural systems towards sustainability. To enable and steer transformation we need to understand the mechanisms of adoption and diffusion holistically. Our current understanding is mainly informed by empirical farm-level adoption studies and by agent-based models simulating systemic diffusion mechanisms. These two approaches are weakly integrated.

OBJECTIVE

Our objective is to build an empirically grounded conceptual framework for adoption and diffusion of digital farming technologies by synthesizing literature on these alternative approaches.

METHODS

We review 32 empirical farm-level studies on the adoption of precision and digital farming technologies and 27 agent-based models on the diffusion of agricultural innovations. Empirical findings are synthesized in terms of significance and partially standardized coefficients, and diffusion studies are categorized by their approaches and theoretical frameworks.

RESULTS AND CONCLUSIONS

We show that farm-level studies focus on farm and operator characteristics but pay less attention to attributes of technology, interactions, institutional and psychological factors. Agent-based models, despite their usefulness for representing system interaction, only loosely connect with empirical farm-level findings. Based on the identified gaps, we develop a conceptual framework integrating farm-level evidence on adoption with a systemic perspective on technology diffusion.

SIGNIFICANCE

Our empirically grounded conceptual framework is the first holistic approach to connect the dots between the wealth of empirical research on technology adoption with more model-driven investigation of innovation diffusion in agent-based studies. Focusing on digital farming technologies, it may serve as a reference for those studying the adoption and diffusion of such technologies beyond farm scale. Furthermore, this framework can be the basis for contextual applications to inform policy-makers trying to foster the diffusion of suitable digital technologies through interventions as it highlights where policy can impact important aspects of adoption via relevant processes of diffusion.

中文翻译：

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数字化农业技术的采用和传播-整合农场级证据和系统交互

语境

预计数字农业技术的采用和传播将有助于将当前的农业系统转变为可持续性。为了实现和引导转型，我们需要全面了解采用和传播的机制。我们当前的理解主要是基于经验性农场级收养研究以及基于代理的模型，该模型模拟系统扩散机制。这两种方法是弱集成的。

客观的

我们的目标是通过综合有关这些替代方法的文献，为数字农业技术的采用和传播建立以经验为基础的概念框架。

方法

我们回顾了32项关于采用精确和数字化农业技术的经验性农场级研究，以及27项基于农业创新传播的基于主体的模型。根据意义和部分标准化的系数对经验发现进行综合，对扩散研究按其方法和理论框架进行分类。

结果与结论

我们表明，农场一级的研究集中于农场和经营者的特征，但较少关注技术的属性，相互作用，制度和心理因素。尽管基于代理的模型对于表示系统交互非常有用，但只能与农场级的经验发现紧密地联系在一起。基于发现的差距，我们开发了一个概念框架，将农场采用的证据与技术传播的系统性观点相结合。

意义

我们以经验为基础的概念框架是第一个整体方法，将技术采用的大量经验研究与基于代理的研究中更多的模型驱动的创新扩散研究联系起来。着重于数字农业技术，它可以为那些研究在农场规模之外采用和传播这种技术的人们提供参考。此外，该框架可以作为情境应用程序的基础，以告知政策制定者试图通过干预来促进适当的数字技术的传播，因为它强调了政策可以通过相关的传播过程影响采用的重要方面的地方。