虚拟现实之旅:通过谱聚类识别在旅游中使用虚拟现实的行为意向

Q1 Economics, Econometrics and Finance Journal of Open Innovation: Technology, Market, and Complexity Pub Date : 2025-03-01 Epub Date: 2024-11-28 DOI:10.1016/j.joitmc.2024.100442
Attasit Wiangkham , Komsit Kieanwatana , Rattawut Vongvit
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引用次数: 0

摘要

虚拟现实(VR)通过改变目的地的营销和体验方式,具有彻底改变旅游业的巨大潜力。研究一直强调VR增强和丰富游客体验的能力,提供新的参与维度。然而,尽管前景看好,但人们对虚拟现实景点互动动机降低的担忧可能会阻碍虚拟现实的广泛采用。本研究通过探索性因子分析和实证调查数据的谱聚类,旨在基于扩展的技术接受模型(TAM)识别旅游中使用虚拟现实的行为意图聚类。这些集群分别是A群(“谨慎的旅行者”)、B群(“幻灭的旅行者”)、C群(“追求品质的旅行者”)和D群(“信息驱动的旅行者”),它们突出了全面的目的地知识和信息获取在增强VR旅游体验中的重要性。通过了解这些群体的行为和偏好,企业和开发人员可以创建量身定制的VR内容和体验,通过关注易用性和内容质量来提高用户满意度。
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Journey into virtual reality: Identifying behavioral intentions to use virtual reality in tourism through spectral clustering
Virtual Reality (VR) holds immense potential to revolutionize the tourism industry by transforming how destinations are marketed and experienced. Research consistently emphasizes VR’s ability to enhance and enrich tourist experiences, offering new dimensions of engagement. However, despite its promise, concerns about diminished motivation to interact with VR-enabled attractions may hinder widespread adoption. This study, through the application of Exploratory Factor Analysis and spectral clustering of empirical survey data, aims to identify clusters of behavioral intentions for using VR in tourism based on an extended Technology Acceptance Model (TAM). These clusters, namely Cluster A ("Cautious Travelers"), Cluster B ("Disenchanted Travelers"), Cluster C ("Quality-Seeking Travelers"), and Cluster D ("Information-Driven Travelers"), highlight the critical role of comprehensive destination knowledge and the importance of information access in enhancing the VR tourism experience. By understanding the behaviors and preferences of these groups, businesses and developers can create tailored VR content and experiences that improve user satisfaction with a focus on ease of use and content quality.
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来源期刊
Journal of Open Innovation: Technology, Market, and Complexity
Journal of Open Innovation: Technology, Market, and Complexity Economics, Econometrics and Finance-Economics, Econometrics and Finance (all)
CiteScore
11.00
自引率
0.00%
发文量
196
审稿时长
1 day
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