Tourism Demand Modeling and Forecasting: A Review of Literature Related to Greater China

Abstract

Greater China, including Mainland China, Hong Kong, Macau and Taiwan, contributes significantly to both regional and global tourism developments. Empirical research on tourism demand modelling and forecasting has attracted increasing attention of scholars both within and beyond this region. One hundred and eighty articles are identified that were published in both English and Chinese language journals since the beginning of the 1990s. This study presents the largest scale of literature survey on tourism demand studies. Furthermore, this is the first attempt in tourism demand review studies that focuses exclusively on one geographic region and covers bilingual literature. Particular emphasis of this review is placed on research development, geographic focus, data type and frequency, measurement of tourism demand, modelling and forecasting techniques, demand elasticity analysis, forecasting exercises and emerging research trends. Comparisons between the two bodies of literature published in two languages show a number of research gaps, such as the diversity and sophistication of the research methodology, rigour of the modelling and forecasting process and theoretical foundations of demand analysis. Correspondingly, constructive recommendations are made to further advance tourism demand studies related to Greater China.

Modeling and Forecasting Chinese Outbound Tourism: An Econometric Approach

“…This is consistent with most findings in the general literature on tourism demand (Li, 2009). Taking overseas holidays is still a relatively recent phenomenon and is limited to urban populations, especially to the three most economically developed regions of Beijing, Shanghai, and Guangdong Province.…”

“…Li (2009) reviewed 200 studies including 137 articles published in Chinese and concluded that the outbound demand analysis related to the Greater China region (including mainland China, Hong Kong, Macau, and Taiwan) is a new research direction for researchers. This study, therefore, fills this research gap.…”

A Dynamic Panel Data Analysis of Climate and Tourism Demand

“…This finding is consistent with previous studies in the tourism demand literature, in which international tourism demand for Greater China is generally found to be a luxury product (Li 2009). However, the income elasticity of tourism demand in Mainland China among Hong Kong tourists is smaller than the average income elasticity (around 2) of tourism demand in Mainland China among other source markets reported in Li (2009). Although the coefficient is not statistically significant, the relative price negatively affects tourist arrivals (coefficient = −0.1865).…”

“…The geographic conditions of these regions have a particularly strong influence on their climate patterns and natural attributes. As a result, China’s tourism industry, including Hong Kong, exhibits strong seasonality within its regions (Li 2009). Figure 1 shows the seasonal variations in demand for Mainland tourism among Hong Kong residents.…”

The role of disaggregated search data in improving tourism forecasts: Evidence from Sri Lanka

“…Accurate tourism forecasts are key inputs for effective government policy planning to enable tourism development and economic growth (Jiao & Chen, 2019;Li, 2009). Number of tourist arrivals are the most commonly used indicator to measure overall changes in tourism demand (Wu et al, 2017).…”