Google Trends and Baidu index data in tourism demand forecasting: A critical assessment of recent applications

IF 12.4 1区 管理学 Q1 ENVIRONMENTAL STUDIES Tourism Management Pub Date : 2025-10-01 Epub Date: 2025-02-25 DOI:10.1016/j.tourman.2025.105164
Josip Mikulić , Regina M. Baumgärtner
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引用次数: 0

Abstract

The application of search query (SQ) data in tourism demand forecasting is an intriguing area of ongoing research. The present research note aims to (i) critically examine recent studies from leading tourism journals using SQ data for demand forecasting, (ii) synthesize the prevailing key problems, limitations and challenges in the studies, and (iii) provide recommendations emerging from the critical assessment of literature to help improve the quality of future SQ-data-based tourism forecasting research.
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旅游需求预测中的趋势和百度指数数据:对最近应用的关键评估
搜索查询(SQ)数据在旅游需求预测中的应用是当前研究的热点。本研究报告旨在(i)批判性地审查最近来自主要旅游期刊使用SQ数据进行需求预测的研究,(ii)综合研究中普遍存在的关键问题,限制和挑战,以及(iii)从文献的批判性评估中提出建议,以帮助提高未来基于SQ数据的旅游预测研究的质量。
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来源期刊
Tourism Management
Tourism Management Multiple-
CiteScore
24.10
自引率
7.90%
发文量
190
审稿时长
45 days
期刊介绍: Tourism Management, the preeminent scholarly journal, concentrates on the comprehensive management aspects, encompassing planning and policy, within the realm of travel and tourism. Adopting an interdisciplinary perspective, the journal delves into international, national, and regional tourism, addressing various management challenges. Its content mirrors this integrative approach, featuring primary research articles, progress in tourism research, case studies, research notes, discussions on current issues, and book reviews. Emphasizing scholarly rigor, all published papers are expected to contribute to theoretical and/or methodological advancements while offering specific insights relevant to tourism management and policy.
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