{"title":"设计人工智能驱动的人才智能解决方案:探索大数据以扩展TOE框架","authors":"A. Faqihi, S. Miah","doi":"10.48550/arXiv.2207.12052","DOIUrl":null,"url":null,"abstract":"AI has the potential to improve approaches to talent management enabling dynamic provisions through implementing advanced automation. This study aims to identify the new requirements for developing AI-oriented artifacts to address talent management issues. Focusing on enhancing interactions between professional assessment and planning attributes, the design artifact is an intelligent employment automation solution for career guidance that is largely dependent on a talent intelligent module and an individuals growth needs. A design science method is adopted for conducting the experimental study with structured machine learning techniques which is the primary element of a comprehensive AI solution framework informed through a proposed moderation of the technology-organization-environment theory.","PeriodicalId":92346,"journal":{"name":"DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International...","volume":"18 1","pages":"69-82"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Designing an AI-Driven Talent Intelligence Solution: Exploring Big Data to extend the TOE Framework\",\"authors\":\"A. Faqihi, S. Miah\",\"doi\":\"10.48550/arXiv.2207.12052\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"AI has the potential to improve approaches to talent management enabling dynamic provisions through implementing advanced automation. This study aims to identify the new requirements for developing AI-oriented artifacts to address talent management issues. Focusing on enhancing interactions between professional assessment and planning attributes, the design artifact is an intelligent employment automation solution for career guidance that is largely dependent on a talent intelligent module and an individuals growth needs. A design science method is adopted for conducting the experimental study with structured machine learning techniques which is the primary element of a comprehensive AI solution framework informed through a proposed moderation of the technology-organization-environment theory.\",\"PeriodicalId\":92346,\"journal\":{\"name\":\"DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International...\",\"volume\":\"18 1\",\"pages\":\"69-82\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-07-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International...\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.48550/arXiv.2207.12052\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International...","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.48550/arXiv.2207.12052","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Designing an AI-Driven Talent Intelligence Solution: Exploring Big Data to extend the TOE Framework
AI has the potential to improve approaches to talent management enabling dynamic provisions through implementing advanced automation. This study aims to identify the new requirements for developing AI-oriented artifacts to address talent management issues. Focusing on enhancing interactions between professional assessment and planning attributes, the design artifact is an intelligent employment automation solution for career guidance that is largely dependent on a talent intelligent module and an individuals growth needs. A design science method is adopted for conducting the experimental study with structured machine learning techniques which is the primary element of a comprehensive AI solution framework informed through a proposed moderation of the technology-organization-environment theory.
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