提出人工智能成熟度模型,说明清洁动物养殖管理的路线图

IF 6.9 2区 管理学 Q1 MANAGEMENT Operations Management Research Pub Date : 2024-06-22 DOI:10.1007/s12063-024-00502-3
Erfan Shakeripour, Mohammad Hossein Ronaghi
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引用次数: 0

摘要

由于自然资源有限,传统农业危害了国家资源。另一方面,人工智能(AI)提高了资源利用效率。如今,在人工智能的帮助下,畜牧业更具可持续性。此外,人工智能在畜牧业中的成熟度为优化人工智能与畜牧业的融合提供了路线图,这也是企业管理者和政策制定者非常关注的问题。根据文献资料,目前在畜牧业领域还没有人工智能成熟度模型来评估后者。本研究分四个阶段进行。首先,文献阐明了人工智能的各个维度及其在畜牧业中的应用。其次,畜牧业专家使用最佳-最差法(BWM)对人工智能的各个维度进行了排序。第三阶段,开发了一个模型,用于评估人工智能技术和人工智能在畜牧业中应用的所有方面的人工智能成熟度。最后,公司成熟度评估通过问卷调查对所提出的模型进行了测试。研究结果表明,健康监测是畜牧业中最重要的人工智能应用。同时,所研究的公司在个体识别方面也表现出了很高的成熟度。这项研究具有独创性,它确定了人工智能在畜牧业中的重要性,并在畜牧业中引入了人工智能成熟度模型。
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Proposing an artificial intelligence maturity model to illustrate a road map for cleaner animal farming management

Traditional agriculture has jeopardized national resources given the limited availability of natural resources. On the other hand, artificial intelligence (AI) has resulted in more efficient resource utilization. Nowadays, animal agriculture is much more sustainable with the help of artificial intelligence. Furthermore, the rate of AI maturity in animal agriculture provides a roadmap for optimizing its integration into it, which is of great concern to enterprise managers and policymakers. According to the literature, there is no AI maturity model in the animal agriculture sector to assess the latter. The current study was carried out in four phases. First, the literature shed light on the dimensions of AI and its applications in animal agriculture. Second, animal agricultural experts ranked the AI dimensions using the Best-Worst Method (BWM). In the third phase, a model was developed to assess AI maturity across all dimensions of AI technology and AI applications in animal agriculture. Finally, a company maturity assessment tested the proposed model by questionnaire. The research findings show that health monitoring is the most important AI application in animal agriculture. Also, the company under study showed great individual identification maturity. The research is original in that it determines the importance of AI in animal agriculture and introduces an AI maturity model in the animal agriculture sector.

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来源期刊
CiteScore
6.20
自引率
23.30%
发文量
104
期刊介绍: Operations Management Research is a peer-reviewed journal that focuses on rapidly publishing high-quality research in the field of operations management. It aims to advance both the theory and practice of operations management across a wide range of topics and research paradigms. The journal covers all aspects of operations management, including manufacturing, supply chain, health care, and service operations. It welcomes various research methodologies, such as case studies, action research, surveys, mathematical modeling, and simulation. The goal of Operations Management Research is to promote research that enhances both the theory and practice of operations management, as it is an applied discipline. The journal also publishes Academic Notes, which are special papers that address research methodologies, the direction of the operations management field, and other topics of interest to academicians. Additionally, there is a demand for shorter and more focused research articles in operations management, which this journal aims to fulfill.
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