EAGER: Pilot Comparative Research on Adoption of Digital Agricultural Technologies

EAGER：数字农业技术采用的试点比较研究

• 批准号: 2025918
• 负责人: Glenn Stone
• 金额: $ 3.32万
• 依托单位: Washington University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2023-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2025918&HistoricalAwards=false
• 关键词: EAGER; Pilot; Comparative; Research; Adoption

This award is made under NSF's EAGER funding mechanism, which supports Early-Concept Grants for Exploratory Research. Some data-intensive digital agriculture technologies have been in use in farms and other food production operations since the 1990s. The range of digital agricultural technologies is now expanding rapidly and some of these technologies are being introduced more widely. Historically most agricultural technologies have brought impacts beyond the obvious realms of yield and farmer profits, including impacts on technical knowledge, on dependencies, and relations among farmers. Given the diversity in emerging digital technologies and in the settings into which they are being introduced, such indirect impacts will be highly diverse and difficult to predict. To date, most research on digital agriculture has focused on a narrow set of issues, with scant attention to indirect impacts and little analysis from a comparative perspective. This EAGER project will conduct exploratory pilot research in diverse settings to collect data to allow investigators to develop a comparative, multi-sited study of this range of impacts. The project is appropriate for EAGER funding because it aims to collect data to test and evaluate questions as a step towards developing a proposal for the larger comparative project.Interviews will be conducted by a team of researchers with local knowledge of agriculture across multiple sites and scales. While the specific digital technologies and farmer characteristics will, by design, vary greatly across sites, researchers will investigate four sets of related questions in each setting. The first concerns identifying the recipients of information about farm operations and farmer behavior. Potential recipients include private companies, government offices, extension agents, CGIAR researchers, and academic analysts. Each of these has distinct expertise and sets of interests. The second concerns the social dynamics of adoption and non-adoption. Farmer decisions on adoption may be driven by various factors other than simple bottom-line profit expectations. The third concerns effects on farmer behavior. The last concerns effects on social relations among farmers.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该奖项是在 NSF 的 EAGER 资助机制下颁发的，该机制支持探索性研究的早期概念资助。自 20 世纪 90 年代以来，一些数据密集型数字农业技术已在农场和其他粮食生产作业中使用。数字农业技术的范围正在迅速扩大，其中一些技术正在得到更广泛的推广。从历史上看，大多数农业技术带来的影响超出了产量和农民利润的明显范围，包括对技术知识、依赖性和农民之间关系的影响。鉴于新兴数字技术及其引入环境的多样性，此类间接影响将高度多样化且难以预测。迄今为止，大多数数字农业研究都集中在狭隘的问题上，很少关注间接影响，也很少从比较角度进行分析。该 EAGER 项目将在不同的环境中进行探索性试点研究，以收集数据，以便研究人员能够针对这一系列影响开展比较性、多地点的研究。该项目适合 EAGER 资助，因为它旨在收集数据来测试和评估问题，作为为更大的比较项目制定提案的一个步骤。访谈将由具有跨多个地点和规模的当地农业知识的研究人员团队进行。虽然具体的数字技术和农民特征在设计上会因地点而异，但研究人员将在每个环境中调查四组相关问题。第一个涉及识别有关农场经营和农民行为信息的接收者。潜在的接收者包括私营公司、政府机关、推广机构、CGIAR 研究人员和学术分析师。他们每个人都有独特的专业知识和兴趣。第二个涉及收养和不收养的社会动态。除了简单的底线利润预期之外，农民的收养决定可能受到多种因素的驱动。第三个涉及对农民行为的影响。最后一个涉及对农民之间社会关系的影响。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。