1
Return

Sense of presence in metaverse tourism experiences: scale development and validation

delete2025-04-01
delete0
PRE
AI
X
Xiao-Ling Jin
B
Bingxin Wang
Y
Yang Li
Y
Yuting Wang *
周中允 cover
周中允 (Zhongyun Zhou)
DOI:10.1108/IMDS-10-2024-0993delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
Purpose This paper aims to develop and validate a comprehensive scale to measure presence in metaverse tourism, which merges virtual and real environments to offer immersive cultural and sensory experiences. Despite its critical role in shaping immersive experiences, presence in metaverse tourism has been insufficiently studied, and there is currently no well-established tool to measure this fundamental construct. Design/methodology/approach This research is conducted in three studies. In Study 1, a multidimensional scale is developed based on insights from literature and online interactions. Study 2 involves conducting exploratory and confirmatory factor analyses on survey samples to assess the reliability and validity of the scale. Study 3 applies the scale within a nomological network to examine its potential influence on traveler experiences. Findings The findings demonstrate that presence in metaverse tourism is a second-order construct consisting of four dimensions: self-presence, social presence, tourism space presence and cultural presence. Different dimensions of presence significantly contribute to travelers' sense of meaningfulness and willingness to revisit. Ultimately, this research confirms the validity and reliability of the 36-item multidimensional presence scale in metaverse tourism. Originality/value This study addresses a gap in metaverse tourism research by providing a tool to quantify presence. The validated scale not only advances the theoretical understanding of presence in virtual environments but also offers practical applications for enhancing the design and evaluation of immersive tourism experiences.
Keywords:
Sense of presence
Metaverse tourism
Scale development
Inductive analysis
Nomological network analysis

Journal

I
Industrial Management and Data Systems
IF:
4.7
Papers:
2.4K
Citations:
8.8K

Organization

T
tongji university
Scholars:
7.5W
Papers: 5.8W
Citations: 98
S
shanghai university
Scholars:
3.8W
Papers: 2.7W
Citations: 52
Cited Papers

Cited Papers

Citing Papers

Citing Papers