{"title":"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","authors":"Erfan Shakeripour, Mohammad Hossein Ronaghi","doi":"10.1007/s12063-024-00502-3","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":46120,"journal":{"name":"Operations Management Research","volume":null,"pages":null},"PeriodicalIF":6.9000,"publicationDate":"2024-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Proposing an artificial intelligence maturity model to illustrate a road map for cleaner animal farming management\",\"authors\":\"Erfan Shakeripour, Mohammad Hossein Ronaghi\",\"doi\":\"10.1007/s12063-024-00502-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>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.</p>\",\"PeriodicalId\":46120,\"journal\":{\"name\":\"Operations Management Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":6.9000,\"publicationDate\":\"2024-06-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Operations Management Research\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.1007/s12063-024-00502-3\",\"RegionNum\":2,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MANAGEMENT\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Operations Management Research","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1007/s12063-024-00502-3","RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MANAGEMENT","Score":null,"Total":0}
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.
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.