Tourism demand forecasting based on user-generated images on OTA platforms

ABSTRACT

Tourists’ images of destinations posted on online travel agency (OTA) platforms are important information sources for potential tourists to perceive and construct destination images. These perceptions can then inform travel decisions. We investigated the roles of the aesthetics of user-generated images on OTA platforms in tourism demand forecasting. Specifically, the aesthetics of images of three popular scenic spots in Hong Kong were used to predict tourism demand from the region’s two largest short-haul markets and largest long-haul market using a seasonal autoregressive moving average with exogenous factors (SARIMAX) model. Seasonal naïve, SARIMA, and SARIMAX models involving search query data were taken as benchmarks. Results showed that (1) image aesthetics could help make more accurate tourism demand forecasting; and (2) as an additional variable, image aesthetics could supplement search query-based volume variables to enhance tourism demand forecasting.

KEYWORDS:

• Tourism demand
• forecast
• online travel agency
• user-generated images
• image aesthetics

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

This work was supported by the Innovation Project of Guangxi Graduate Education [grant number YCSW2022024], The Guangxi Key Research and Development Plan [grant number Guike-AB20297040], Guangxi Natural Science Foundation [grant number 2022JJA180046], The National Social Science Fund of China [grant number 21BJY193], and the The National Natural Science Foundation of China [grant number 71964012].