Tourism demand forecasting from the perspective of mobility: a brand-new predictive variable generated from intercity population mobility big data

ABSTRACT

Few studies have investigated tourism demand forecasting from a mobility perspective. We explore whether population mobility data improve the ability to forecast tourist volumes in scenic spots. We selected Jiuzhaigou and Mount Siguniang in China as study cases and ensured the robustness of the results using single- and multistep rolling evaluation techniques. The findings reveal a significant correlation, long-term cointegration, and two-way Granger causality between intercity population flow and tourist flow. The comparison model with population flow as a variable outperforms the benchmark model. We prove the feasibility of leveraging population flow in tourism demand forecasting and suggest further research.

KEYWORDS:

• Population mobility
• tourism mobility
• tourism demand forecasting
• rolling origin
• tourist volume
• mobility theory

Acknowledgments

The authors would like to express appreciation to anonymous eviewers for their very helpful comments on ways to improve the paper.

Disclosure statement

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

Additional information

Funding

This research is partially supported by Beijing Natural Science Foundation [Grant number No. 9222005].