Forecasting accuracy evaluation of tourist arrivals
Bibliographic Data
| ID | 11236593 |
|---|---|
| Authors | Hamidreza Hassani (0000-0003-0897-8663), Hossein Hassani (0000-0003-3979-9166), Emmanuel Sirimal Silva (0000-0003-3851-9230, University of the Arts London, corresponding author), Nikolaos Antonakakis (0000-0002-0904-3678, University of Portsmouth), George Filis (0000-0002-4912-0973, Bournemouth University), Rangan Gupta (0000-0001-5002-3428, University of Pretoria) |
| Year | 2017 |
| Volume | 63 |
| Pages | 112-127 |
| Publication date | 2017-03-01 |
| 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.2017.01.008 |
| OpenAlex | W2585667993 |
| Language | EN |
| Citations received | 38 |
| References cited | 55 |
Artificial neural network · Autoregressive fractionally integrated moving average · Econometrics · Economics · Geography · Long memory · Nonparametric statistics · Operations research · Parametric statistics · Statistics · Tourism · Computer Science · Grey System Theory Applications · Mathematics · Statistical and numerical algorithms · Artificial Intelligence
Pronóstico postpandemia del turismo receptivo vía aérea mediante la utilización de modelos bayesianos. El caso de Colombia
Forecasting daily visits in Shanghai with Model combination and Telco big data
Monitoring and forecasting Covid-19 impacts on hotel occupancy rates with daily visitor arrivals and search queries
The impact of tree-based machine learning models, length of training data, and quarantine search query on tourist arrival prediction’s accuracy under Covid-19 in Indonesia
Daily tourism demand forecasting
The time–frequency causal effect of Covid-19 outbreaks on the tourism sector
A novel two-step procedure for tourism demand forecasting
Modelling prices and volatilities in the sharing economy
Tourism demand with subtle seasonality
International tourism demand forecasting with machine learning models
Does the combination of models with different explanatory variables improve tourism demand forecasting performance
Tourism and economic growth
Multi‐horizon accommodation demand forecasting
Forecasting tourism demand cycles
Monthly Tourism Demand Forecasting With Covid ‐19 Impact‐Based Hybrid Convolution Neural Network and Gate Recurrent Unit
Analyzing post-pandemic tourism recovery
Camping Tourism in Bulgaria
Hybrid SVR-Sarima model for tourism forecasting using PROMETHEE II as a selection methodology
Longitudinal Analysis of Sustainable Tourism Potential of the Black Sea Riparian States Bulgaria, Romania and Turkey
Forecast without historical data
A review of research on tourism demand forecasting
The good, the bad and the ugly on Covid-19 tourism recovery
Spatial-temporal forecasting of tourism demand
Imputation recovery tourism demand forecasting
Forecasting air passenger numbers with a GVAR model
Forecasting campground demand in US national parks
Forecasting tourism demand with denoised neural networks
Tourism forecasting with granular sentiment analysis
Post-pandemic tourism forecasting with ensemble RNN
Forecasting tourism growth with State-Dependent Models
Predictivity of tourism demand data
Cross country relations in European tourist arrivals
Forecasting occupancy rate with Bayesian compression methods
A decomposition-ensemble approach for tourism forecasting
Modelling’ UK tourism demand using fashion retail sales
Denoising search query improves tourism forecasting
Group pooling for deep tourism demand forecasting
The Impact of the Covid-19 Crisis on Air Travel Demand
Automatic Time Series Forecasting
Computation and analysis of multiple structural change models
Testing the equality of prediction mean squared errors
Tourist arrival forecasting by evolutionary fuzzy systems
A piecewise linear approach to modeling and forecasting demand for Macau tourism
Forecasting international tourist flows to Australia
Forecasting tourism demand with Arma-based methods
A fractionally integrated autoregressive moving average approach to forecasting tourism demand
Forecasting international tourist flows to Macau
Investigating the influence of tourism on economic growth and carbon emissions
Forecasting tourism
Modeling and forecasting tourism demand for arrivals with stochastic nonstationary seasonality and intervention
Designing an artificial neural network for forecasting tourism time series
Forecasting tourism demand
Bayesian models for tourism demand forecasting
Tourism forecasting
A comparison of three different approaches to tourist arrival forecasting
A neural network model to forecast Japanese demand for travel to Hong Kong
Back-propagation learning in improving the accuracy of neural network-based tourism demand forecasting
A practitioners guide to time-series methods for tourism demand forecasting — a case study of Durban, South Africa
Combining volatility and smoothing forecasts of UK demand for international tourism
Forecasting Tourist Arrivals in Greece and the Impact of Macroeconomic Shocks from the Countries of Tourists’ Origin
Aggregate vs. Disaggregate Forecast
Forecasting tourist arrivals
A canonical analysis of international tourism demand
Forecasting tourist arrivals in Barbados
Tourism and growth
| Unique citing works | 38 |
|---|---|
| Citations per year | 4,22 |
| Citation span | 2017 - 2026 (10) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 37 |