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 …
ABSTRACT The novel coronavirus (COVID-19), which is one of its kind of humanitarian disasters, has affected people and businesses worldwide, triggering a global economic …
H Lv, S Shi, D Gursoy - Journal of Hospitality Marketing & …, 2022 - Taylor & Francis
In reaction to the growing attention paid to big data and artificial intelligence in hospitality and tourism research, we systematically reviewed 270 relevant studies to identify topical …
R Law, G Li, DKC Fong, X Han - Annals of tourism research, 2019 - Elsevier
Traditional tourism demand forecasting models may face challenges when massive amounts of search intensity indices are adopted as tourism demand indicators. Using a …
X Li, R Law, G Xie, S Wang - Tourism Management, 2021 - Elsevier
Internet techniques significantly influence the tourism industry and Internet data have been used widely used in tourism and hospitality research. However, reviews on the recent …
S Sun, Y Wei, KL Tsui, S Wang - Tourism Management, 2019 - Elsevier
Previous studies have shown that online data, such as search engine queries, is a new source of data that can be used to forecast tourism demand. In this study, we propose a …
Big data generated across social media sites have created numerous opportunities for bringing more insights to decision-makers. Few studies on big data analytics, however, have …
M Hu, H Li, H Song, X Li, R Law - Tourism management, 2022 - Elsevier
This study aims to forecast international tourist arrivals to Hong Kong from seven English- speaking countries. A new direction in tourism demand modeling and forecasting is …
G Xie, Y Qian, S Wang - Tourism Management, 2021 - Elsevier
After more than ten years of exponential development, the growth rate of cruise tourist in China is slowing down. There is increasingly financial risk of investing in homeports, cruise …