{"title":"对印度管理机构采用人工智能的因素进行建模","authors":"Samant Shant Priya, V. Jain, Meenu Shant Priya, Sushil Kumar Dixit, Gaurav Joshi","doi":"10.1108/fs-09-2021-0181","DOIUrl":null,"url":null,"abstract":"\nPurpose\nThis study aims to examine which organisational and other factors can facilitate the adoption of artificial intelligence (AI) in Indian management institutes and their interrelationship.\n\n\nDesign/methodology/approach\nTo determine the factors influencing AI adoption, a synthesis-based examination of the literature was used. The interpretative structural modelling (ISM) method is used to determine the most effective factors among the identified ones and the inter-relationship among the factors, while the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method is used to analyse the cause-and-effect relationships among the factors in a quantitative manner. The approaches used in the analysis aid in understanding the relationship among the factors affecting AI adoption in management institutes of India.\n\n\nFindings\nThis study concludes that leadership support plays the most significant role in the adoption of AI in Indian management institutes. The results from the DEMATEL analysis also confirmed the findings from the ISM and Matrice d’ Impacts croises- multiplication applique and classment (MICMAC) analyses. Remarkably, no linkage factor (unstable one) was reported in the research. Leadership support, technological context, financial consideration, organizational context and human resource readiness are reported as independent factors.\n\n\nPractical implications\nThis study provides a listing of the important factors affecting the adoption of AI in Indian management institutes with their structural relationships. The findings provide a deeper insight about AI adoption. The study's societal implications include the delivery of better outcomes by Indian management institutes.\n\n\nOriginality/value\nAccording to the authors, this study is a one-of-a-kind effort that involves the synthesis of several validated models and frameworks and uncovers the key elements and their connections in the adoption of AI in Indian management institutes.\n","PeriodicalId":51620,"journal":{"name":"Foresight","volume":" ","pages":""},"PeriodicalIF":2.3000,"publicationDate":"2022-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Modelling the factors in the adoption of artificial intelligence in Indian management institutes\",\"authors\":\"Samant Shant Priya, V. 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引用次数: 2
摘要
本研究旨在研究哪些组织和其他因素可以促进印度管理机构采用人工智能(AI)及其相互关系。设计/方法/方法为了确定影响人工智能采用的因素,采用了基于综合的文献检查。采用解释结构建模(ISM)方法确定识别的因素中最有效的因素以及因素之间的相互关系,采用决策试验与评价实验室(DEMATEL)方法定量分析因素之间的因果关系。分析中使用的方法有助于理解影响印度管理机构采用人工智能的因素之间的关系。本研究得出结论,领导支持在印度管理机构采用人工智能方面发挥了最重要的作用。DEMATEL分析的结果也证实了ISM和matrix d ' Impacts croises-乘法贴花和分类(MICMAC)分析的结果。值得注意的是,研究中未发现任何连锁因子(不稳定因子)。领导支持、技术背景、财务考虑、组织背景和人力资源准备被报告为独立因素。本研究列出了影响印度管理机构采用人工智能的重要因素及其结构关系。这些发现为人工智能的采用提供了更深入的见解。该研究的社会影响包括印度管理学院提供了更好的结果。原创性/价值根据作者的说法,这项研究是一项独一无二的努力,涉及几个经过验证的模型和框架的综合,并揭示了印度管理机构采用人工智能的关键因素及其联系。
Modelling the factors in the adoption of artificial intelligence in Indian management institutes
Purpose
This study aims to examine which organisational and other factors can facilitate the adoption of artificial intelligence (AI) in Indian management institutes and their interrelationship.
Design/methodology/approach
To determine the factors influencing AI adoption, a synthesis-based examination of the literature was used. The interpretative structural modelling (ISM) method is used to determine the most effective factors among the identified ones and the inter-relationship among the factors, while the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method is used to analyse the cause-and-effect relationships among the factors in a quantitative manner. The approaches used in the analysis aid in understanding the relationship among the factors affecting AI adoption in management institutes of India.
Findings
This study concludes that leadership support plays the most significant role in the adoption of AI in Indian management institutes. The results from the DEMATEL analysis also confirmed the findings from the ISM and Matrice d’ Impacts croises- multiplication applique and classment (MICMAC) analyses. Remarkably, no linkage factor (unstable one) was reported in the research. Leadership support, technological context, financial consideration, organizational context and human resource readiness are reported as independent factors.
Practical implications
This study provides a listing of the important factors affecting the adoption of AI in Indian management institutes with their structural relationships. The findings provide a deeper insight about AI adoption. The study's societal implications include the delivery of better outcomes by Indian management institutes.
Originality/value
According to the authors, this study is a one-of-a-kind effort that involves the synthesis of several validated models and frameworks and uncovers the key elements and their connections in the adoption of AI in Indian management institutes.
期刊介绍:
■Social, political and economic science ■Sustainable development ■Horizon scanning ■Scientific and Technological Change and its implications for society and policy ■Management of Uncertainty, Complexity and Risk ■Foresight methodology, tools and techniques