开启雇主洞察力:在工业 5.0 背景下使用大型语言模型探索以人为本的方面

IF 12.9 1区 管理学 Q1 BUSINESS
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引用次数: 0

摘要

本文旨在通过引入一种基于人工智能的创新方法,利用招聘信息熟练映射与幸福感相关的雇主表达方式,从而加深对工业 5.0 的理解。这一过程包括创建一个全面的幸福感表达词典,然后将其与现有的学术文献进行比较。这种方法有助于从雇主的角度对幸福感进行实证分析。在理论和实践领域之间架起一座桥梁,我们为学术界和工业界提供了有关雇主对幸福感(以人为本)解释的宝贵见解。研究结果凸显了英国雇主优先考虑自我实现和积极的工作氛围,以吸引求职者。然而,许多职位空缺并没有明确强调幸福感来吸引潜在的员工。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Unlocking employer insights: Using large language models to explore human-centric aspects in the context of industry 5.0

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.

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来源期刊
CiteScore
21.30
自引率
10.80%
发文量
813
期刊介绍: Technological Forecasting and Social Change is a prominent platform for individuals engaged in the methodology and application of technological forecasting and future studies as planning tools, exploring the interconnectedness of social, environmental, and technological factors. In addition to serving as a key forum for these discussions, we offer numerous benefits for authors, including complimentary PDFs, a generous copyright policy, exclusive discounts on Elsevier publications, and more.
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