Spatio-temporal Characterization of Potential Demand for Tourist Attractions Based on Internet Search

Xiao-Bing Feng

SAGE Open, 2025, vol. 15, issue 1, 21582440251323550

Abstract: With the development and popularization of Internet information technology, search engines have become an important channel for the majority of Internet users to find and obtain the information they need. Network attention is an important manifestation of users’ potential demand or realistic concern for a certain thing or phenomenon. The article takes Dujiangyan Scenic Area in Sichuan Province, China as a case study, uses the network search data from the Baidu Index platform from 2017 to 2022, applies geographical spatial statistical analysis methods to study the spatiotemporal characteristics of tourist network attention to Dujiangyan Scenic Area, and explores the factors influencing the spatiotemporal characteristics of tourist network attention. The research found that there is a significant correlation between network attention and changes in the actual number of tourists received. The network attention to Dujiangyan Scenic Area is relatively dispersed in terms of time distribution, with differences in the distribution of tourist network attention over time caused by climate comfort, holiday system, and festival activities. The network attention to Dujiangyan Scenic Area exhibits relatively dispersed spatial distribution characteristics, with the population size of tourist source areas, spatial distance, Internet development level, and economic development level being the main factors influencing the spatial distribution characteristics of tourist network attention. Tourist attractions can enhance the effectiveness of tourism network marketing, develop differentiated tourism marketing and promotion strategies by utilizing the spatiotemporal distribution characteristics of network attention.

Keywords: network attention; spatial and temporal characteristics; tourism demand; tourist attractions; Baidu index (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:sae:sagope:v:15:y:2025:i:1:p:21582440251323550

DOI: 10.1177/21582440251323550

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