Investigating the Spatial-Temporal Variation of Pre-Trip Searching in an Urban Agglomeration

Jianxin Zhang, Yuting Yan, Jinyue Zhang, Peixue Liu () and Li Ma
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Jianxin Zhang: School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
Yuting Yan: School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
Jinyue Zhang: School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
Peixue Liu: School of Business Administration, Nanjing University of Finance and Economic, Nanjing 210023, China
Li Ma: School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China

Sustainability, 2023, vol. 15, issue 14, 1-17

Abstract: Search engines have been the primary tool for online information search before traveling. Timely detection and the control of peak tourist flows in scenic areas prevent safety hazards and the overconsumption of tourism resources due to excessive tourist clustering. This study focuses on the spatial-temporal interactions between the pre-trip stage and the after-arrival stage to investigate online information search behavior. Big data obtained from mobile roaming and search engines provide precise data on daytime and city scales, which enabled this paper to examine the relationship between daily tourist arrivals and their pre-trip searching from 40 cities within the Yangtze River Delta urban agglomeration. This study had several original results. First, tourists generally search for tourist information 2–8 days before arriving at destinations, while tourist volume and SVI from source cities show distance attenuation. Second, SVI is a precursor to changes in tourist volume. The precursory time rises with the increase of traffic time spatially. Third, we validated a VAR model and improved its accuracy by constructing it based on the spatial-temporal differentiation of search features. These findings would enhance the management and preservation of tourism resources and promote the sustainable development of tourism destinations.

Keywords: tourism information search; search engine; mobile roaming data; tourism forecasting; Webometrics (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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