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Which search queries are more powerful in tourism demand forecasting: searches via mobile device or PC?

Mingming Hu (Business School, Guangxi University, Nanning, China and School of Hotel and Tourism Management, The Hong Kong Polytechnic University, Hong Kong SAR, China)
Mengqing Xiao (Business School, Guangxi University, Nanning, China and Guangxi Development Strategy Research Institute, Guangxi University, Nanning, China)
Hengyun Li (Hospitality and Tourism Research Centre (HTRC), School of Hotel and Tourism Management, The Hong Kong Polytechnic University, Hong Kong SAR, China)

International Journal of Contemporary Hospitality Management

ISSN: 0959-6119

Article publication date: 31 May 2021

Issue publication date: 9 August 2021

845

Abstract

Purpose

While relevant research has considered aggregated data from mobile devices and personal computers (PCs), tourists’ search patterns on mobile devices and PCs differ significantly. This study aims to explore whether decomposing aggregated search queries based on the terminals from which these queries are generated can enhance tourism demand forecasting.

Design/methodology/approach

Mount Siguniang, a national geopark in China, is taken as a case study in this paper; another case, Kulangsu in China, is used as the robustness check. The authors decomposed the total Baidu search volume into searches from mobile devices and PCs. Weekly rolling forecasts were used to test the roles of decomposed and aggregated search queries in tourism demand forecasting.

Findings

Search queries generated from PCs can greatly improve forecasting performance compared to those from mobile devices and to aggregate search volumes from both terminals. Models incorporating search queries generated via multiple terminals did not necessarily outperform those incorporating search queries generated via a single type of terminal.

Practical implications

Major players in the tourism industry, including hotels, tourist attractions and airlines, can benefit from identifying effective search terminals to forecast tourism demand. Industry managers can also leverage search indices generated through effective terminals for more accurate demand forecasting, which can in turn inform strategic decision-making and operations management.

Originality/value

This study represents one of the earliest attempts to apply decomposed search query data generated via different terminals in tourism demand forecasting. It also enriches the literature on tourism demand forecasting using search engine data.

Keywords

Acknowledgements

This study is supported by the National Natural Science Foundation of China (71761001), Early Career Scheme from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. 25500520) and the Guangxi Key Research and Development Plan (Guike-AB20297040).

Authors’ note: All three authors contributed equally to the paper.

Citation

Hu, M., Xiao, M. and Li, H. (2021), "Which search queries are more powerful in tourism demand forecasting: searches via mobile device or PC?", International Journal of Contemporary Hospitality Management, Vol. 33 No. 6, pp. 2022-2043. https://doi.org/10.1108/IJCHM-06-2020-0559

Publisher

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Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

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