Recreation comforting degree identification and assessment in national parks by integrating text mining technology and fuzzy DEMATEL-based ANP method

To enhance tourists' perceived transformative experience in national parks, a comprehensive model of recreation comforting degree was constructed using a mixed-methods that integrated text mining (TM) technology with the fuzzy DEMATEL-based analytic network process (FDANP). The developed model systematically incorporated physiological, psychological, spiritual, and social comforting degree dimensions, encapsulating 16 indicators into a coherent index system. The FDANP method was subsequently applied to establish a cause-and-effect diagram for the recreation comforting degree model in Wuyishan national park. This integrated approach provides a more comprehensive and systematic assessment compared to traditional single-method assessments, particularly advantageous in addressing the inherent variability and complexity associated with assessing recreation comforting degree of national parks. The results indicated that physiological comforting degree emerged as the most significant dimension influencing recreation comforting degree. Additionally, factors such as attaining positive emotions, sharing online, evoking tourism memories, undergoing a spiritual cleansing, and appreciate local culture exhibited positive influences on the sub-criteria of recreation comforting degree. This study provides practitioners with a practical and informed decision-making tool to enhance tourists' perceived transformative experience in national parks.

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Publication Details

Journal
Scientific Reports
Published
2025-08-22
DOI
https://doi.org/10.1038/s41598-025-14107-8
Citations
1
Primary Topic
Diverse Aspects of Tourism Research
Type
article
Field-Weighted Citation Impact
4.20

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article

Recreation comforting degree identification and assessment in national parks by integrating text mining technology and fuzzy DEMATEL-based ANP method

Y. S. Lin, Chaoling Wu, Yuahn‐Sieh Huang, Kaimiao Lin et al.
1 citations
Scientific Reports
Diverse Aspects of Tourism Research
4.20
article

Recreation comforting degree identification and assessment in national parks by integrating text mining technology and fuzzy DEMATEL-based ANP method

Y. S. Lin, Chaoling Wu, Yuahn‐Sieh Huang, Kaimiao Lin, Bingkai Huang, Xuejiao Wang, Xiaoxia Wu
article en
1 citations

Abstract

To enhance tourists' perceived transformative experience in national parks, a comprehensive model of recreation comforting degree was constructed using a mixed-methods that integrated text mining (TM) technology with the fuzzy DEMATEL-based analytic network process (FDANP). The developed model systematically incorporated physiological, psychological, spiritual, and social comforting degree dimensions, encapsulating 16 indicators into a coherent index system. The FDANP method was subsequently applied to establish a cause-and-effect diagram for the recreation comforting degree model in Wuyishan national park. This integrated approach provides a more comprehensive and systematic assessment compared to traditional single-method assessments, particularly advantageous in addressing the inherent variability and complexity associated with assessing recreation comforting degree of national parks. The results indicated that physiological comforting degree emerged as the most significant dimension influencing recreation comforting degree. Additionally, factors such as attaining positive emotions, sharing online, evoking tourism memories, undergoing a spiritual cleansing, and appreciate local culture exhibited positive influences on the sub-criteria of recreation comforting degree. This study provides practitioners with a practical and informed decision-making tool to enhance tourists' perceived transformative experience in national parks.

Scientific ReportsVol. 15(1)
Wuyi University (CN), Wuyi University (CN)
Department of Education, Fujian Province, Wuyi University, National Office for Philosophy and Social Sciences
Openalex Percentile: Top 6%
Diverse Aspects of Tourism Research
4.20
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