{"title":"Employees' training experience in a metaverse environment? Feedback analysis using structural topic modeling","authors":"","doi":"10.1016/j.techfore.2024.123636","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":null,"pages":null},"PeriodicalIF":12.9000,"publicationDate":"2024-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Technological Forecasting and Social Change","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0040162524004347","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
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.
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.
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