Tracing the Evolution of Tourist Perception of Destination Image: A Multi-Method Analysis of a Cultural Heritage Tourist Site
Year: 2025
Type: article
Abstract: In the face of an unprecedented public health crisis (COVID-19), despite tourist perceptions toward cultural heritage tourism having undergone significant transformation, such transitions are increasingly viewed as opportunities to enhance sustainability practices in cultural heritage tourism worldwide. This study traces the evolution of tourist perceptions at Lijiang Old Town, a UNESCO World Heritage Site, across three stages from 2017 to 2024—before the pandemic, during the pandemic, and after the pandemic. Data were collected from major tourism platforms, yielding a comprehensive dataset of 50,022 user-generated reviews. We adopt a mixed-method framework integrating TF-IDF, Social Network Analysis (SNA), and Latent Dirichlet Allocation (LDA) to identify salient terms, semantic structures, and latent themes from large-scale unstructured textual data across time. The findings indicate that cultural heritage tourism demonstrates adaptability and resilience through significant perceptual transitions. After the pandemic, visitors increasingly prioritized cultural depth and high-quality service experiences, whereas before the pandemic, tourists focused more on cultural heritage attractions and commercial experiences. Moreover, during the pandemic period, visitor narratives reflected adaptations toward quieter, safer, and more personalized experiences, highlighting the impact of safety measures on tourism patterns. These findings demonstrate the methodological potential for dynamically monitoring perception shifts and offer empirical grounding for future perception-oriented research and sustainable cultural heritage destination management practices in cultural heritage tourism toward sustainable tourism.
Source: Sustainability
DOI: 10.3390/su17125476
Authors: Yundi Wei, Maowei Chen
Institutions: Xihua University, Kangwon National University
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $2,896
OpenAlex ID: W4411278868