The study aimed to explore the relationship and interaction between humans and nature in specific areas. Latent Dirichlet allocation topic recognition and SnowNLP sentiment analysis were used to extract the topics and analyze the sentiments from visitors’ online reviews of Wuyishan National Park. The conclusions were as follows: (1) The tourists mainly expressed positive emotions toward Wuyishan National Park, and the tourists acknowledged its ecological environment and natural and cultural heritage value. (2) The tourists’ comments focused on four themes: tourism activities and facilities, natural and cultural heritage value, characteristic tourism products, and tourism management and services. Natural experience was the main tourism activity in Wuyishan National Park, while cultural activities were related to the tea culture. (3) The tourist facilities, ticket and reservation mechanism, and management and services of Wuyishan National Park were the main concerns of the tourists. The study suggested that Wuyishan National Park could be transformed from a tourist destination into a comprehensive national park that provides recreational experiences and environmental education. This should be conducted by (1) developing detailed natural and cultural education and experience products and (2) improving public service functions and enhancing the public welfare of the national park.

Tourist payment is one of the effective ways to solve the shortage of environmental protection and development funds in ecotourism areas. Prior research has predominantly examined the factors influencing tourists’ Willingness-To-Pay (WTP) for environmental protection from the tourists’ own perspective, yet there remains a gap in exploring how destinations can effectively motivate tourists’ willingness to contribute financially to environmental conservation efforts. Based on Reasonable Person Model (RPM), with the famous ecotourism site of Hulunbuir Grassland in China as the research site, this study tested the relationship between Perceived destination restorative qualities (PDRQs), Eudaimonic well-being(EWB), Ecotourism destination image(EDI), and WTP for environmental protection, based on questionnaire survey and structural equation model. According to the results, PDRQs did not significantly affect WTP, however, RDRQs made a positive impact on EWB and EDI, Furthermore, EWB and EDI fully mediated the correlation between RDRQs and WTP. These findings confirm that the RPM is applicable to account for the mechanism of RDRQs on WTP for environmental protection, expand its research scope, and help us to comprehend the relationship between human and environment and the inducing mechanism of WTP for environmental protection from the aspect of environmental psychology.

Scientifically mitigating the ecological risks in tourist destinations is an important foundation for the healthy and sustainable development of tourist destinations. In this study, we summarize the progress of ecological risk research in tourist destinations at home and abroad and the internal logic of ecological risk research in tourist destinations. Current research adhered to an internal framework encompassing the following stages: formation and analysis of ecological risks in tourism destinations, exposure characterization, effect exploration, risk assessment, and risk management. Specific research results were summarized in four aspects: the analysis of ecological risk sources, assessment of acceptors and endpoints, ecological risk assessment, perceptions of ecological risk, predictions and management of ecological risks within tourism destinations. Future research should prioritize fostering a harmonious relationship between humanity and natural environment, which necessitates strengthening the foundation of a multidisciplinary theory. Future research should focus on the formation mechanisms of ecological risks in tourist destinations, the mechanisms of interaction among ecological risk sources, receptors, and endpoints, ecological risk assessments of tourist destinations based on multiple risk sources, ecological risk assessments of typical tourism destinations and their key exposures, enhancing the ecological risk assessment index system for tourist destinations by incorporating data from various sources, conducting simulation studies to develop ecological risk warning systems for tourist destinations, exploring the spatiotemporal scale coupling relationships of ecological risks in tourist destinations, examining the perceptions and attitudes of different stakeholders towards ecological risks in tourist destinations, evaluating the cost-benefit of ecological risk adaptation, and performing prevention measures in tourist destinations.

This study examines holiday self-drive tourists' perceptions of expressway congestion and explores the underlying mechanisms through which these perceptions influence their intention to take future holiday self-drive trips. A mixed-methods design was employed. In the qualitative phase, in-depth interviews and grounded theory analysis identified a four-dimensional structure and corresponding measurement items of tourists perceived expressway congestion. In the quantitative phase, data collected from 414 self-drive tourists were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS. The results indicate that while expressway congestion provokes negative emotions and subsequently leads to negative word-of-mouth, it does not diminish the intention for additional holiday self-drive trips. Furthermore, optimism and frequency of self-drive trips serve as moderators between perceived environmental impact and negative emotions, and between negative emotions and negative word-of-mouth, respectively. This study makes the first systematic attempt to develop a measurement scale for perceived expressway congestion, thereby advancing the understanding of intention for holiday self-drive trips from a novel perspective. It also extends the application of Affective Events Theory (AET) and offers actionable insights for managing expressway congestion during peak holiday travel periods.