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Topic Modeling for Hiking Trail Online Reviews: Analysis of the Mutianyu Great Wall. SUSTAINABILITY 2022. [DOI: 10.3390/su14063246] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Hiking is now one of the most popular activities amongst adventure travelers. Although recent studies have highlighted the differences between Chinese adventure tourists and their international counterparts, few studies have comprehensively explored the differences in hikers’ interests and concerns for experience elements between these two groups. Topic modeling is adopted for an analysis of the online reviews of the Mutianyu Great Wall to identify attributes influencing hikers’ experiences and behavior. Using a large-scale review dataset, the latent Dirichlet allocation (LDA) technique was applied to construct a comprehensive list of the topics posted by hikers. The findings revealed that Chinese and non-Chinese hikers have common concerns regarding the degree of challenges, scenery, tour services and crowding during hiking. Nevertheless, their perceptions of cultural resources are presented in a different way. These findings are beneficial for understanding the similarities and differences between Chinese and non-Chinese hikers’ perceptions, in addition to improving domestic and international markets’ management and marketing strategies.
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Assessing Present and Future Climate Conditions for Beach Tourism in Jardines del Rey (Cuba). ATMOSPHERE 2020. [DOI: 10.3390/atmos11121295] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
This study assesses, adapting the weather types method, the suitability of the climate in Jardines del Rey (Cuba) for the practice of sun and beach tourism over the period 1991–2014, and the potential future impacts of climate change on this form of tourism on the basis of outputs from the PRECIS-Caribbean Regional Climate Model for the period 2021–2050. The methodology applied makes a classification of daily situations according to the most frequent combinations of climatological variables in tropical areas while focusing on a very specific segment of the tourism market (sun and beach tourism) and taking into account the behaviour of beach users and bioclimatic criteria. The results indicate that the distribution of weather types at the destination during the period 1991–2014 was highly consistent with the monthly distribution of tourists in Cuba, highlighting the existence of a low season from May to October and a high season between November and April. The future scenarios project an improvement in climate conditions for the practice of sun and beach tourism. This improvement is not based on a spectacular increase in favourable weather types compared to unfavourable ones, but rather on a better distribution of both.
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Abstract
In sun-and-beach destinations, weather has a decisive influence on the variability of the daily flow of tourists. Uncertainty in demand flows directly affects businesses and employment. This work aims to improve understanding of the behaviour of tourists in response to changes in weather conditions. The analysis is carried out in the Rías Baixas, a sun-and-beach destination in north-west Spain. The paper analyses the relationship of weather conditions with daily flows during the high season at the main tourist beaches in the area, also considering two beach typologies. The density of beach use is measured three times a day through the analysis of webcam images in combination with real-time weather, and an online survey is conducted among tourists who have visited these beaches. The results show that the hours of sunshine are the most influential weather factor. Weather forecast greatly or totally influenced the decision to go to the beach for almost 70% of respondents and about 80% of the respondents checked on the weather before visiting a beach.
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