将数字流程创新应用于农场管理对农民福利的影响:多案例研究

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Watanyoo Suksa-ngiam, Tamir Bechor
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引用次数: 0

摘要

泰国的农业部门是收入最低的部门。泰国需要对数字流程创新进行研究,其具体背景对填补文献空白至关重要。本研究探讨了数字流程创新如何提高农民福利。研究方法是对三个案例进行多案例研究。多案例研究可以回答 "如何 "和 "为什么 "的问题,并提供分析概括。案例 1 是地理信息系统决策支持系统。案例 2 和 3 是基于物联网的农业系统。泰国政府为所有案例提供了支持。这些案例利用信息技术促进数字流程创新,作为农业管理概念,如农业安全、作物适宜性、需求驱动型农业、农民网络、多作物种植、智能农业和精准农业。对这些案例进行了独立调查,然后整合成一个综合数据模型。研究收集了 32 位参与者的数据,包括发明案例的开发人员、促进案例使用的中层员工和地方政府官员、使用案例的用户农民,以及种植相同作物但未使用案例的非用户农民,他们作为每个案例的对照组。数据模型展示了数字流程创新的进步如何影响农民的福利。此外,本研究还提出了理论和实践建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The impact of applying digital process innovation to farm management on farmer welfare: A multiple case study
Thailand's agricultural sector is the lowest-paying sector. Research on digital process innovation is needed in Thailand, where specific contexts are critical in filling the literature gap. This study investigates how digital process innovations can enhance farmers’ welfare. The research method is a multiple-case study with three cases. A multiple-case study can answer how and why questions and provide analytic generalizations. Case 1 was a GIS decision support system. Cases 2 and 3 were IoT-based farming systems. The Thai government supported all the cases. These cases utilized IT to facilitate digital process innovations as farm management concepts, such as agricultural safety, crop suitability, demand-driven agriculture, farmer networks, multi-cropping, smart farming, and precision agriculture. These cases were investigated independently and then integrated into a synthesized data model. The study collected data from 32 participants, including developers who invented the cases, mid-tier employees and local government officers who facilitated the use of the cases, user farmers who used the cases, and non-user farmers who grew the same crop but did not use the cases and served as the control group for each case. The data model demonstrates how advancements in digital process innovations impact farmers’ welfare. Additionally, this study makes theoretical and practical recommendations.
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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