Forecasting tourist arrivals using time-varying parameter structural time series models
By Haiyan Song, Gang Li, Stephen F. Witt, George Athanasopoulos. 2011
167 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Sociology and Political Science, Tourism, Leisure and Hospitality Management
View Paper: https://www.semanticscholar.org/paper/d27e8452b950c6eec2bc48113f6917a4a3c1c7d4
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Citations in the corpus
- Forecasting tourist arrivals with machine learning and internet search index (2017, background): “Around the world, tourism contributes significantly to the economic growth [2].”
- Tourism economics research: A review and assessment (2012, background): “(Adams & Parmenter, 1995), while the latter (e.g., Smeral, 2009b; Song et al., 2011) focus on the impact on tourism demand only.”
- New developments in tourism and hotel demand modeling and forecasting (2017, methodology): “…variables relate to the scale of demand, such as guest arrivals (Guizzardi and Stacchini, 2015), the number of nights stayed (Falk, 2014; Lim et al., 2009), the number of rooms sold (such as Corgel et al., 2013; Song et al., 2011b), and occupancy rates (Koupriouchina et al., 2014; Wu et al., 2010).”