概念化
计算机科学
沉浸式(数学)
斯科普斯
旅游
社会学
知识管理
数据科学
文化遗产
主题(计算)
虚拟现实
心理学
共同创造
概念框架
工程伦理学
感知
系统回顾
管理科学
网络志
人机交互
作者
Chuhan Wang,Chaozhi Zhang,Ding Xu
标识
DOI:10.1108/ijchm-05-2025-0686
摘要
Purpose In the tourism, hospitality, events and leisure (THEL) domain, the concept of immersion lacks a consistent definition and a unified theoretical foundation. This study is designed to address this gap, aiming to comprehensively understand the immersion concept, its contextualization, creation mechanisms and impacts. Design/methodology/approach A GenAI-assisted review approach was adopted, with 419 publications retrieved systematically from WoS and Scopus databases. The authors developed and exemplified a six-step procedure for using GenAI in literature analysis, in which GenAI was deployed as a textual analysis tool for theme retraction, classification and summarization. Findings Six immersion-facilitating contexts were identified, with digital and virtual engagement and cultural and heritage visitation being the most prominent. An in-depth examination of conceptualization suggested a new definition of immersion as a graded experience of progressively heightened engagement. Immersion was theorized into eight dimensions adhering to two distinct research paradigms, and the mechanisms of its creation and post hoc impacts were further delineated. Practical implications For industry practitioners in the THEL sector, these findings can enhance the design and delivery of immersion. By leveraging different categories of antecedents, businesses can create more engaging and immersive products. Originality/value The review provides a unified conceptual basis for understanding immersion. It also highlights future directions to examine the socio-cultural instead of micro-social-level antecedents, and the standalone instead of amplifier impacts on experience subjects and societies. Methodologically, the present investigation developed and exemplified six-step structural procedures to effectively deploy GenAI for review studies.
科研通智能强力驱动
Strongly Powered by AbleSci AI