{"title":"人工智能在商业决策中的人类判断:实证研究","authors":"ARUN KUMAR CHANDA","doi":"10.1142/s136391962450004x","DOIUrl":null,"url":null,"abstract":"<p>The deployment of AI systems has increased across several industries as they exhibit progressively stronger predictive performance. Due to safety, moral, and legal considerations, full automation is frequently undesirable. However, fully manual methods might be erroneous and time-consuming. The idea of using AI to support human decision-making is therefore gaining popularity in the scientific community. The flourishing subject of AI decision-making needs to embrace empirical methodologies in addition to building AI technologies for that purpose to establish a solid understanding of how people interact and collaborate with AI to make decisions. This research intends to analyse how artificial intelligence uses human judgment for decision-making in business. Researchers gathered survey results from high-tech employees in India via email, media, and other means. The sample size was 196, and the sampling strategy most likely employed was convenience sampling. With the data collected measurement and structural model are performed and found that artificial intelligence-based decision-making impacts the organizations’ business value and artificial intelligence capability impacts the organization created with the moderating effect of business intelligence. Also, it is concluded that AI-based decision-making impacts knowledge management.</p>","PeriodicalId":47711,"journal":{"name":"International Journal of Innovation Management","volume":"43 1","pages":""},"PeriodicalIF":1.3000,"publicationDate":"2024-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"HUMAN JUDGMENT IN ARTIFICIAL INTELLIGENCE FOR BUSINESS DECISION-MAKING: AN EMPIRICAL STUDY\",\"authors\":\"ARUN KUMAR CHANDA\",\"doi\":\"10.1142/s136391962450004x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The deployment of AI systems has increased across several industries as they exhibit progressively stronger predictive performance. Due to safety, moral, and legal considerations, full automation is frequently undesirable. However, fully manual methods might be erroneous and time-consuming. The idea of using AI to support human decision-making is therefore gaining popularity in the scientific community. The flourishing subject of AI decision-making needs to embrace empirical methodologies in addition to building AI technologies for that purpose to establish a solid understanding of how people interact and collaborate with AI to make decisions. This research intends to analyse how artificial intelligence uses human judgment for decision-making in business. Researchers gathered survey results from high-tech employees in India via email, media, and other means. The sample size was 196, and the sampling strategy most likely employed was convenience sampling. With the data collected measurement and structural model are performed and found that artificial intelligence-based decision-making impacts the organizations’ business value and artificial intelligence capability impacts the organization created with the moderating effect of business intelligence. Also, it is concluded that AI-based decision-making impacts knowledge management.</p>\",\"PeriodicalId\":47711,\"journal\":{\"name\":\"International Journal of Innovation Management\",\"volume\":\"43 1\",\"pages\":\"\"},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2024-05-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Innovation Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1142/s136391962450004x\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MANAGEMENT\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Innovation Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/s136391962450004x","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MANAGEMENT","Score":null,"Total":0}
HUMAN JUDGMENT IN ARTIFICIAL INTELLIGENCE FOR BUSINESS DECISION-MAKING: AN EMPIRICAL STUDY
The deployment of AI systems has increased across several industries as they exhibit progressively stronger predictive performance. Due to safety, moral, and legal considerations, full automation is frequently undesirable. However, fully manual methods might be erroneous and time-consuming. The idea of using AI to support human decision-making is therefore gaining popularity in the scientific community. The flourishing subject of AI decision-making needs to embrace empirical methodologies in addition to building AI technologies for that purpose to establish a solid understanding of how people interact and collaborate with AI to make decisions. This research intends to analyse how artificial intelligence uses human judgment for decision-making in business. Researchers gathered survey results from high-tech employees in India via email, media, and other means. The sample size was 196, and the sampling strategy most likely employed was convenience sampling. With the data collected measurement and structural model are performed and found that artificial intelligence-based decision-making impacts the organizations’ business value and artificial intelligence capability impacts the organization created with the moderating effect of business intelligence. Also, it is concluded that AI-based decision-making impacts knowledge management.
期刊介绍:
The International Journal of Innovation (IJIM) is the official journal of the International Society of Professional Innovation Management (ISPIM). Both the IJIM and ISPIM adopt a multi-disciplinary approach to addressing the many challenges of managing innovation, rather than a narrow focus on a single aspect such as technology, R&D or new product development. Both are also international, inclusive & practical, and encourage active interaction between academics, managers and consultants.