Topic modelling for wildlife tourism online reviews
Analysis of quality factors
Bibliographic Data
| ID | 21699554 |
|---|---|
| Authors | Ziye Shang (0000-0002-7949-1089, City University of Macau, corresponding author), J M Luo (0000-0002-5779-1152, City University of Macau, corresponding author) |
| Year | 2023 |
| Volume | 26 |
| Issue | 14 |
| Pages | 2317-2331 |
| Publication date | 2023-07-18 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Current Issues in Tourism (JOURNAL) |
| Journal identifiers | ISSN: 1368-3500 • E-ISSN: 1747-7603 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/13683500.2022.2086107 |
| OpenAlex | W4286631588 |
| Language | EN |
| Citations received | 12 |
| References cited | 78 |
Improving the wildlife tourism experience of travellers is critical to achieving environmental sustainability. Therefore, it’s critical to investigate quality factors to raise experience quality. This study aims to identify the most salient quality factors and their relative importance to the wildlife tourism experience of travellers. In order to take advantage of big data and unprompted textual data, a machine learning method, namely, supervised latent Dirichlet allocation, was used in analysing online reviews of wildlife tourism. A total of 18 quality factors are extracted from data and cross-validated by comparing a prior theoretical framework. Results reveal that travellers’ perception of intensity, authenticity, species popularity, and operators’ rule management are crucial for enhancing traveller’s experience. In addition, the negative influences of wildlife attack and disease highlight the importance of control of encounter. These findings suggest some future research directions and provide practical implications
Business · Data science · Economics · Ecotourism · Environmental planning · Environmental resource management · Geography · Tourism · Wildlife · Wildlife tourism · Computational and Text Analysis Methods · Computer Science · Digital Marketing and Social Media · Diverse Aspects of Tourism Research · Ecology · Marketing
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| Unique citing works | 12 |
|---|---|
| Citations per year | 6 |
| Citation span | 2024 - 2026 (3) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 11 |