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探索用户对在线虚拟现实展览技术的接受度:以良渚博物院为例

Exploring user acceptance of online virtual reality exhibition technologies: A case study of Liangzhu Museum.

作者信息

Li Jia, Lv Chan

机构信息

Department of Environment Design, College of Design, Jiaxing University, Jiaxing, Zhejiang, China.

Department of Animation and Digital Media, College of Arts, Wuyi University, Wuyishan, Fujian, China.

出版信息

PLoS One. 2024 Aug 1;19(8):e0308267. doi: 10.1371/journal.pone.0308267. eCollection 2024.

DOI:10.1371/journal.pone.0308267
PMID:39088515
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11293688/
Abstract

Museums increasingly rely on cutting-edge digital technologies to attract visitors. Understanding the intricate factors influencing user acceptance of these technologies is, however, crucial for their effective use. This study therefore proposes a model, grounded in the technology acceptance model, to investigate user acceptance of online virtual reality (VR) museum exhibitions. Leveraging the online VR exhibition at Liangzhu Museum as a case study, data were collected from 313 participants and analyzed using partial least squares structural equation modeling (PLS-SEM) with Smart PLS. Semi-structured interviews with 15 individuals were conducted to complement the quantitative findings. The results reveal that factors such as interactivity, immersion, and presence positively influenced users' intrinsic technological beliefs (perceived ease of use, perceived enjoyment, and perceived usefulness), ultimately affecting their willingness to use and intention to visit on-site. Notably, immersion had a direct positive effect on perceived usefulness. There is a pressing need to leverage digital and web technologies to cater to the increasingly complex and diverse needs of online visitors, and emphasizing navigational performance in online VR exhibitions is also paramount for enhancing the overall user experience.

摘要

博物馆越来越依赖前沿数字技术来吸引参观者。然而,了解影响用户对这些技术接受度的复杂因素对于有效利用它们至关重要。因此,本研究提出了一个基于技术接受模型的模型,以调查用户对在线虚拟现实(VR)博物馆展览的接受度。以良渚博物院的在线VR展览为案例研究,收集了313名参与者的数据,并使用Smart PLS通过偏最小二乘结构方程模型(PLS-SEM)进行分析。对15人进行了半结构化访谈,以补充定量研究结果。结果表明,交互性、沉浸感和临场感等因素对用户的内在技术信念(感知易用性、感知趣味性和感知有用性)产生了积极影响,最终影响了他们的使用意愿和实地参观意愿。值得注意的是,沉浸感对感知有用性有直接的积极影响。迫切需要利用数字和网络技术来满足在线参观者日益复杂和多样的需求,并且强调在线VR展览中的导航性能对于提升整体用户体验也至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/54fd/11293688/45cfba6a996f/pone.0308267.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/54fd/11293688/a810c4f20e8a/pone.0308267.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/54fd/11293688/1078283c83a3/pone.0308267.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/54fd/11293688/0e5108c685aa/pone.0308267.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/54fd/11293688/45cfba6a996f/pone.0308267.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/54fd/11293688/a810c4f20e8a/pone.0308267.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/54fd/11293688/1078283c83a3/pone.0308267.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/54fd/11293688/0e5108c685aa/pone.0308267.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/54fd/11293688/45cfba6a996f/pone.0308267.g004.jpg

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Extended TAM based acceptance of AI-Powered ChatGPT for supporting metacognitive self-regulated learning in education: A mixed-methods study.基于扩展技术接受模型的人工智能驱动的ChatGPT在教育中支持元认知自我调节学习的接受度:一项混合方法研究。
Heliyon. 2024 Apr 9;10(8):e29317. doi: 10.1016/j.heliyon.2024.e29317. eCollection 2024 Apr 30.
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"Extending the Technology Acceptance Model (TAM) to Predict University Students' Intentions to Use Metaverse-Based Learning Platforms".
扩展技术接受模型(TAM)以预测大学生使用基于元宇宙的学习平台的意愿
Educ Inf Technol (Dordr). 2023 Apr 28:1-33. doi: 10.1007/s10639-023-11816-3.
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Evaluation of virtual tour in an online museum: Exhibition of Architecture of the Forbidden City.虚拟博物馆导览评估:紫禁城建筑展。
PLoS One. 2022 Jan 6;17(1):e0261607. doi: 10.1371/journal.pone.0261607. eCollection 2022.
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Digital Responses of UK Museum Exhibitions to the COVID-19 Crisis, March - June 2020.英国博物馆展览对2020年3月至6月新冠疫情危机的数字化应对措施
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