A review of research on tourism demand forecasting: Launching the Annals of Tourism Research Curated Collection on tourism demand forecasting
This study reviews 211 key papers published between 1968 and 2018, for a better
understanding of how the methods of tourism demand forecasting have evolved over time …
understanding of how the methods of tourism demand forecasting have evolved over time …
Demand forecasting model using hotel clustering findings for hospitality industry
Tourism has become a growing industry day by day with the developing economic
conditions and the increasing communication and social interaction ability of the people …
conditions and the increasing communication and social interaction ability of the people …
Using machine learning and big data for efficient forecasting of hotel booking cancellations
AJ Sánchez-Medina, C Eleazar - International Journal of Hospitality …, 2020 - Elsevier
Cancellations are a key aspect of hotel revenue management because of their impact on
room reservation systems. In fact, very little is known about the reasons that lead customers …
room reservation systems. In fact, very little is known about the reasons that lead customers …
[HTML][HTML] The derived demand for advertising expenses and implications on sustainability: a comparative study using deep learning and traditional machine learning …
In recent years, machine learning models based on big data have been introduced into
marketing in order to transform customer data into meaningful insights and to make strategic …
marketing in order to transform customer data into meaningful insights and to make strategic …
The impact of Google Trends index and encompassing tests on forecast combinations in tourism
YC Hu, G Wu - Tourism Review, 2022 - emerald.com
Purpose Given that the use of Google Trends data is helpful to improve forecasting
performance, this study aims to investigate whether the precision of forecast combination …
performance, this study aims to investigate whether the precision of forecast combination …
A multivariate grey prediction model with grey relational analysis for bankruptcy prediction problems
YC Hu - Soft Computing, 2020 - Springer
Regarding bankruptcy prediction as a kind of grey system problem, this study aims to
develop multivariate grey prediction models based on the most representative GM (1, N) for …
develop multivariate grey prediction models based on the most representative GM (1, N) for …
Understanding cumulative sum operator in grey prediction model with integral matching
Grey prediction models have been widely used in various fields and disciplines. Cumulative
sum operator, also called accumulative generation operator, is an essential step in grey …
sum operator, also called accumulative generation operator, is an essential step in grey …
Predicting resilience in retailing using grey theory and moving probability based Markov models
R Rajesh, AK Agariya, C Rajendran - Journal of Retailing and Consumer …, 2021 - Elsevier
The level of resilience for an urban retail system is referred to as the ability of diverse types
of retailing to adjust to any modifications, crises or shocks, which can adversely influence the …
of retailing to adjust to any modifications, crises or shocks, which can adversely influence the …
Forecast combination using grey prediction with fuzzy integral and time-varying weighting in tourism
YC Hu - Grey Systems: Theory and Application, 2023 - emerald.com
Purpose Tourism demand forecasting is vital for the airline industry and tourism sector.
Combination forecasting has the advantage of fusing several forecasts to reduce the risk of …
Combination forecasting has the advantage of fusing several forecasts to reduce the risk of …
Tourism demand forecasting using nonadditive forecast combinations
YC Hu, G Wu, P Jiang - Journal of Hospitality & Tourism …, 2023 - journals.sagepub.com
Accurately forecasting the demand for tourism can help governments formulate industrial
policies and guide the business sector in investment planning. Combining forecasts can …
policies and guide the business sector in investment planning. Combining forecasts can …