加利福尼亚精准除草商业化生态系统利益相关者图谱

IF 6.1 1区 农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY Agricultural Systems Pub Date : 2024-10-25 DOI:10.1016/j.agsy.2024.104152
Christiana Wong , Ali Moghimi
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引用次数: 0

摘要

摘要精准除草是农业技术的一个领域,无人机和/或自动除草机使用化学、机械或热力手段来铲除杂草。由于劳动力短缺的压力、获得竞争优势的动力以及过量化学投入对环境的影响,许多加利福尼亚种植者都有兴趣在其作业中采用精准除草技术:加利福尼亚种植者、精准除草初创企业和农业技术风险投资公司。在大型农业公司及其企业风险投资部门和政府机构观点的补充下,本研究试图了解利益相关者之间的兼容动机、利益相关者之间的现有合作模式及其局限性,以及种植者采用精准除草技术的用户历程。方法我们对精准除草领域的不同利益相关者进行了 17 次半结构式定性访谈,以收集文本数据并获得高数据饱和度。数据收集兼顾了严格的参与者选择标准和适应性访谈问题,以确保深度和相关性。分析程序包括编码和主题框架开发,辅以基础理论进行迭代数据检查,并创建利益相关者地图以提炼跨组织见解和利益相关者动态。较少被提及但仍受欢迎的动机包括:有更多的除草选择、满足特定的田间需求以及环境的可持续发展。个人和利益相关者群体的认知图显示,初创企业的寿命、精确除草机械的高昂费用以及一些初创企业缺乏与种植者的直接联系等问题普遍限制了种植者对精确除草技术的采用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Stakeholder mapping of precision weeding commercialization ecosystem in California

CONTEXT

Precision weeding, a sector of agricultural technology in which drones and/or automated weeders use chemical, mechanical, or thermal means to eradicate weeds, has moved from academic research settings to commercialization. Because of labor shortage pressures, the push to gain competitive advantages, and the environmental impacts of excessive chemical inputs, many California growers have been interested in adopting precision weeding technologies in their operations.

OBJECTIVE

Using semi-structured qualitative interviews, this study investigated the viewpoints of three key stakeholder groups involved in the diffusion and adoption of precision weeding technologies: California growers, precision weeding startups, and agricultural technology venture capital firms. With the supplemental viewpoints of large agricultural firms and their corporate venture capital arms and government agencies, this study seeks to understand the compatible motivations between stakeholders, current collaborative models between stakeholders and their limitations, and the user journey for growers adopting precision weeding technology.

METHODS

We conducted 17 semi-structured qualitative interviews with diverse stakeholders in the precision weeding sector to gather textual data and gain high data saturation. Data collection balanced rigorous criteria for participant selection with adaptive interview questions to ensure depth and relevance. The analysis procedure involved coding and thematic framework development, complemented by grounded theory for iterative data examination and stakeholder map creation for distilling cross-organizational insights and stakeholder dynamics.

RESULTS AND CONCLUSIONS

The results indicated that compatible motivations include addressing current labor issues, reducing costs, and the potential of precision weeding to transform agriculture. Less cited but still popular motivations included having more weeding options, meeting specific field needs, and environmental sustainability. The individual and stakeholder group cognitive maps demonstrated that concerns such as startup longevity, the high expenses of precision weeding machinery, and some startups lacking a direct connection to growers commonly limit the growers' adoption of precision weeding technologies.

SIGNIFICANCE

The procedure and cognitive mapping presented in this study can be applied to other emerging agtech technologies and ecosystems.
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来源期刊
Agricultural Systems
Agricultural Systems 农林科学-农业综合
CiteScore
13.30
自引率
7.60%
发文量
174
审稿时长
30 days
期刊介绍: Agricultural Systems is an international journal that deals with interactions - among the components of agricultural systems, among hierarchical levels of agricultural systems, between agricultural and other land use systems, and between agricultural systems and their natural, social and economic environments. The scope includes the development and application of systems analysis methodologies in the following areas: Systems approaches in the sustainable intensification of agriculture; pathways for sustainable intensification; crop-livestock integration; farm-level resource allocation; quantification of benefits and trade-offs at farm to landscape levels; integrative, participatory and dynamic modelling approaches for qualitative and quantitative assessments of agricultural systems and decision making; The interactions between agricultural and non-agricultural landscapes; the multiple services of agricultural systems; food security and the environment; Global change and adaptation science; transformational adaptations as driven by changes in climate, policy, values and attitudes influencing the design of farming systems; Development and application of farming systems design tools and methods for impact, scenario and case study analysis; managing the complexities of dynamic agricultural systems; innovation systems and multi stakeholder arrangements that support or promote change and (or) inform policy decisions.
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