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

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Listed:
  • Shuai Ma
  • Hengyun Li
  • Mingming Hu
  • Haifeng Yang
  • Ruogu Gan

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.

Suggested Citation

  • Shuai Ma & Hengyun Li & Mingming Hu & Haifeng Yang & Ruogu Gan, 2024. "Tourism demand forecasting based on user-generated images on OTA platforms," Current Issues in Tourism, Taylor & Francis Journals, vol. 27(11), pages 1814-1833, June.
    • Handle: RePEc:taf:rcitxx:v:27:y:2024:i:11:p:1814-1833
    DOI: 10.1080/13683500.2023.2216882
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