Author
Listed:
- Bin Jiang
- Chunxiang Zhang
- Yingyin Cui
- JiuLian Zhu
- Zhennan Liu
Abstract
In recent years, the ice and snow tourism industry has exhibited a concurrent state of vigorous expansion and intense rivalry. Strengthening competitiveness is of paramount significance for attaining a dominant position in the market. Thus, this study endeavors to dissect the multi-dimensional determinants of the competitiveness of ice and snow tourism destinations from the demand perspective and establish an evaluation framework. Leveraging 48,420 tourist reviews sourced from ten highly reputed ice and snow tourist attractions in Harbin, text features were extracted via the application of Term Frequency - Inverse Document Frequency (TF-IDF). Subsequently, the Latent Dirichlet Allocation (LDA) topic model was deployed to precisely extract key themes. The sentiment inclination was gauged by SnowNLP. Eventually, the Importance - Performance (IPA) model was utilized to analyze the strengths and weaknesses of the ice and snow tourism competitiveness. The outcomes are as follows: (1) Seven prominent themes, namely tourist activities, environment, resources, historical and cultural aspects, cost - performance, service, and experience, were recognized as potent driving forces. (2) Tourists manifested positive emotions and a high degree of approval. (3) The competitiveness score of the Harbin ice and snow tourism destination was determined to be 0.64, with tourist activities constituting the advantage, whereas resources and environment necessitating enhancement. This study transcends the constraints of traditional supply-side-centered research. Innovatively, tourist sentiment was integrated into the evaluation system, thereby augmenting the connotations of the competitiveness evaluation model. Based on the LDA topic clustering results, sentiment analysis was conducted, enhancing the accuracy of portraying tourists’ inner experiences. Concrete and forward-looking strategic recommendations were proffered for augmenting the competitiveness of ice and snow tourism destinations, thereby furnishing theoretical and practical guidance for the high-quality progression of ice and snow tourism.
Suggested Citation
Bin Jiang & Chunxiang Zhang & Yingyin Cui & JiuLian Zhu & Zhennan Liu, 2025.
"Enhancement of Harbin ice and snow tourism destination competitiveness: A large-scale data study based on sentiment analysis and Latent Dirichlet Allocation,"
PLOS ONE, Public Library of Science, vol. 20(3), pages 1-25, March.
Handle:
RePEc:plo:pone00:0319435
DOI: 10.1371/journal.pone.0319435
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