Enhancing tourism demand forecasting with a transformer-based framework
Bibliographic Data
| ID | 11235993 |
|---|---|
| Authors | Xin Li (0000-0002-3425-8566, University of Science and Technology Beijing, corresponding author), Yechi Xu (0009-0001-3525-6554, University of Science and Technology Beijing), Robin Law (0000-0001-7199-3757, University of Macau), Rob Law, Shouyang Wang (0000-0001-5773-998X, University of Chinese Academy of Sciences) |
| Year | 2024 |
| Volume | 107 |
| Pages | 103791 |
| Publication date | 2024-07-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Annals of Tourism Research (JOURNAL) |
| Journal identifiers | ISSN: 0160-7383 • E-ISSN: 1873-7722 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.annals.2024.103791 |
| OpenAlex | W4399060724 |
| Language | EN |
| Citations received | 13 |
| References cited | 58 |
Business · Demand forecasting · Economics · Geography · Tourism · Forecasting Techniques and Applications · Stock Market Forecasting Methods · Time Series Analysis and Forecasting · Marketing
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A Systematic Review of Operations Research in Tourism
Navigating Data Limitations
Multimodal deep learning for tourism demand forecasting
Generation of ensemble forecasts using functional-link net for decomposition ensemble learning to forecast tourist arrivals
Enhancing tourism demand forecasting with two-stage feature selection and attention-augmented deep learning models
Data-driven analysis of cultural tourism experience
Imputation recovery tourism demand forecasting
Rethinking Covid-19 tourism recovery
Post-pandemic tourism forecasting with ensemble RNN
Forecasting tourism recovery with multifactor insights – A case of post-pandemic Chinese outbound tourism
Tourism combination forecasting with swarm intelligence
Tourism demand forecasting using social media data
Econometric Modelling and Forecasting of Tourism Demand
New developments in tourism and hotel demand modeling and forecasting
Recent Developments in Econometric Modeling and Forecasting
Random Forests
Tourism demand forecasting
A review of research on tourism demand forecasting
Tourism forecasts after Covid-19
Tourism demand modelling and forecasting—A review of recent research
Tourism demand forecasting using tourist-generated online review data
Seasonality in tourist flows
Forecasting tourist arrivals with machine learning and internet search index
Progress in tourism demand research
Impact of decomposition on time series bagging forecasting performance
Can multi-source heterogeneous data improve the forecasting performance of tourist arrivals amid Covid-19? Mixed-data sampling approach
Forecasting tourism demand with composite search index
Forecasting Chinese cruise tourism demand with big data
Covid-era forecasting
Bayesian BILSTM approach for tourism demand forecasting
The good, the bad and the ugly on Covid-19 tourism recovery
Forecasting tourist arrivals using denoising and potential factors
Tourism demand forecasting with spatiotemporal features
Spatial-temporal forecasting of tourism demand
The combination of interval forecasts in tourism
Forecasting tourism demand with multisource big data
Forecasting air passenger numbers with a GVAR model
Tourism forecasting with granular sentiment analysis
Daily tourism volume forecasting for tourist attractions
Tourism demand forecasting with time series imaging
A decomposition-ensemble approach for tourism forecasting
Multi-attraction, hourly tourism demand forecasting
Tourism demand forecasting with online news data mining
Group pooling for deep tourism demand forecasting
Forecasting tourism demand
Evaluating tourism's economic effects
| Unique citing works | 13 |
|---|---|
| Citations per year | 13 |
| Citation span | 2025 - 2026 (2) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 13 |