Employees' training experience in a metaverse environment? Feedback analysis using structural topic modeling

IF 12.9 1区 管理学 Q1 BUSINESS
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Abstract

The metaverse has been heralded as the next frontier for fueling strategic business opportunities. A recent surge in business investments in digital technologies-based training applications is witnessed. Metaverse is a technology in training and development landscape that intends to materialize a highly immersive experience by combining the virtual and the real world. Organizations are moving towards a metaverse environment to enhance the interactivity and flexibility of training while maintaining a high quality of their educational content and training plans. However, the existing scholarly work on metaverse tends to be more focused on employees' recruitment and retention functions of human resource, while the training and development function, particularly, the employees' training experience of the metaverse, is largely overlooked. Understanding employees' experiences is critical for businesses to achieve the desired training outcomes. Our study aims to fill this research gap by adopting a novel structural topic model text analysis method to analyze 889 employees' reviews about various training applications in metaverse environment. Specifically, we explored the employees' reviews of leading training platforms STRIVR, Spatial Computing, Mursion, Program ACE, Rewo, Gather, and ARKit. Our initial results reveal 9 topics, of which 5 relate to positive aspects and 4 are potential concerns. In particular, real-time collaboration, enhanced practicality, alignment with technology training, real-time feedback analytics, and customizable learning environments are positive, whereas accessibility and inclusivity, ethical considerations, privacy and security concerns, and cultural resistance are negative aspects. This study highlights the promising potential of the metaverse in improving the training and development functions within human resource management. By leveraging the novel efficiencies that the metaverse confers, firms can use these advancements to gain a competitive advantage.

元环境中的员工培训体验?利用结构主题模型进行反馈分析
元网络被誉为促进战略商机的下一个前沿领域。最近,企业对基于数字技术的培训应用的投资激增。元世界是培训与开发领域的一项技术,旨在通过将虚拟世界与现实世界相结合,实现高度身临其境的体验。各组织都在向元宇宙环境发展,以增强培训的互动性和灵活性,同时保持教育内容和培训计划的高质量。然而,现有学者对元海外的研究往往更关注人力资源中的员工招聘和保留职能,而培训和发展职能,尤其是员工在元海外的培训体验,则在很大程度上被忽视了。了解员工的培训体验对于企业实现预期培训效果至关重要。我们的研究采用一种新颖的结构主题模型文本分析方法,分析了 889 名员工对元数据环境下各种培训应用的评论,旨在填补这一研究空白。具体而言,我们探讨了员工对领先培训平台 STRIVR、Spatial Computing、Mursion、Program ACE、Rewo、Gather 和 ARKit 的评论。我们的初步结果揭示了 9 个主题,其中 5 个涉及积极方面,4 个是潜在问题。其中,实时协作、增强实用性、与技术培训保持一致、实时反馈分析和可定制的学习环境是积极方面,而可访问性和包容性、伦理考虑、隐私和安全问题以及文化阻力则是消极方面。本研究强调了元世界在改进人力资源管理中的培训和发展职能方面的巨大潜力。通过利用元网络带来的新效率,企业可以利用这些进步获得竞争优势。
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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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