{"title":"Unlocking employer insights: Using large language models to explore human-centric aspects in the context of industry 5.0","authors":"","doi":"10.1016/j.techfore.2024.123719","DOIUrl":null,"url":null,"abstract":"<div><p>This paper aims to enhance the understanding of Industry 5.0 by introducing an innovative AI-based methodology that proficiently maps employer expressions related to well-being using job postings. This process involves creating a comprehensive dictionary of well-being expressions, which is then compared with existing academic literature. This approach facilitates empirical well-being analysis from employers’ perspectives. Bridging theoretical and practical realms, we offer valuable insights to academia and industry about well-being (human-centricity) interpretation by employers. The findings highlight UK employers’ prioritisation of self-realisation and a positive work atmosphere to attract job seekers. Nonetheless, many vacancies do not explicitly emphasise well-being to attract potential workers.</p></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":null,"pages":null},"PeriodicalIF":12.9000,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0040162524005171/pdfft?md5=e6a9b0b1c51f1ea12a4f6f6c7b2d7006&pid=1-s2.0-S0040162524005171-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Technological Forecasting and Social Change","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0040162524005171","RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS","Score":null,"Total":0}
引用次数: 0
Abstract
This paper aims to enhance the understanding of Industry 5.0 by introducing an innovative AI-based methodology that proficiently maps employer expressions related to well-being using job postings. This process involves creating a comprehensive dictionary of well-being expressions, which is then compared with existing academic literature. This approach facilitates empirical well-being analysis from employers’ perspectives. Bridging theoretical and practical realms, we offer valuable insights to academia and industry about well-being (human-centricity) interpretation by employers. The findings highlight UK employers’ prioritisation of self-realisation and a positive work atmosphere to attract job seekers. Nonetheless, many vacancies do not explicitly emphasise well-being to attract potential workers.
期刊介绍:
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