面向智慧农业的区块链技术模型:一个建议模型

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引用次数: 0

摘要

本研究的目的是研究区块链技术给农业利益相关者带来的挑战。除此之外,值得注意的是,有两个重要的理论是实现智能农业发展区块链技术目标的整合的基础,它们是扎根理论,并将技术-组织-环境(TOE)理论概念化。本研究采用定性方法,因为它可以提取区块链技术对涉及各种农业部门利益相关者的智能农业的复杂描述。半结构化深度访谈将在六个州进行:玻里斯、吉打州、雪兰莪州、内森美兰州、彭杭州和沙捞越州,作为研究的一部分,以更深入地了解概况,并更好地了解区块链技术给农业利益相关者带来的挑战。利用智慧农业的高价值原则,本研究协调了一个全面的区块链技术模型,并与各利益相关者面临的挑战建立了联系。本研究通过研究区块链技术在可追溯性、可见性、安全性和可访问性方面的属性,以及区块链技术给农业利益相关者带来的挑战,扩展了区块链技术在支持智能农业方面的知识。这项研究成果将促进农业部门的现代化进程,管理国家粮食和农业供应的需求和供应。从技术的角度来看,农业研究的潜在趋势主要体现在科学研究中。智能农业的研究至关重要,但由于供应链不同层面面临的挑战,研究仍然很少。因此,符合这种研究模式的新颖性对于研究人员的最佳知识来说是不可用的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Blockchain Technology Model Towards Smart Agriculture: A Proposed Model
The objective of this study is to examine the challenges created by blockchain technology to the agriculture stakeholders. Besides that, it is also noteworthy to understand that two important theories underlie the integration towards achieving the objectives of developing the blockchain technology for smart agriculture are the Grounded Theory and will conceptualise the Technology-Organisation-Environment (TOE) Theory. This study employs a qualitative approach because it can extract the complex description of the blockchain technology towards smart agriculture that involves various agriculture sector stakeholders. Semi-structured in-depth interviews will be conducted in six states: Perlis, Kedah, Selangor, Negeri Sembilan, Pahang and Sarawak as part of the research to get a more in-depth understanding of the profiles and better understanding on the challenges created by blockchain technology to the agriculture stakeholders. Drawing on the high value of smart agriculture principles, this study reconciles a comprehensive blockchain technology model and draw connections with the challenges faced by various stakeholders. This study expands knowledge on blockchain technology in supporting smart agriculture by looking into the blockchain technology attributes in terms of traceability, visibility, security and accessibility, as well as the challenges created by blockchain technology to the agriculture stakeholders. This study output will boost the modernisation process in the agriculture sector, managing the demand and supply of national food and agriculture supply. The underlying trend of agricultural research is discovered to be primarily embedded in scientific investigations from technologies’ perspectives. Researching in smart agriculture is crucial but remains scanty due to the challenges facing at the different levels in the supply chain. As such, the novelty fits within this research model are unavailable to the researchers’ best knowledge.
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