Google Trends and Baidu index data in tourism demand forecasting: a critical assessment of recent applications
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,...
| Үндсэн зохиолчид: | , |
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| Формат: | Өгүүллэг |
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Elsevier
2025
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| Нөхцлүүд: |
| _version_ | 1825625969481744384 |
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| author | Mikulić, Josip Baumgärtner, Regina M. |
| author_facet | Mikulić, Josip Baumgärtner, Regina M. |
| author_sort | Mikulić, Josip |
| collection | LMU |
| description | 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. |
| first_indexed | 2025-03-04T01:43:18Z |
| format | Article |
| id | oai:repository.londonmet.ac.uk:10132 |
| institution | London Metropolitan University |
| last_indexed | 2025-03-04T01:43:18Z |
| publishDate | 2025 |
| publisher | Elsevier |
| record_format | eprints |
| spelling | oai:repository.londonmet.ac.uk:101322025-02-28T11:54:06Z https://repository.londonmet.ac.uk/10132/ Google Trends and Baidu index data in tourism demand forecasting: a critical assessment of recent applications Mikulić, Josip Baumgärtner, Regina M. 330 Economics 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. Elsevier 2025-10 Article PeerReviewed Mikulić, Josip and Baumgärtner, Regina M. (2025) Google Trends and Baidu index data in tourism demand forecasting: a critical assessment of recent applications. Tourism Management, 110 (105164). pp. 1-5. ISSN 0261-5177 https://doi.org/10.1016/j.tourman.2025.105164 10.1016/j.tourman.2025.105164 10.1016/j.tourman.2025.105164 |
| spellingShingle | 330 Economics Mikulić, Josip Baumgärtner, Regina M. Google Trends and Baidu index data in tourism demand forecasting: a critical assessment of recent applications |
| title | Google Trends and Baidu index data in tourism demand forecasting: a critical assessment of recent applications |
| title_full | Google Trends and Baidu index data in tourism demand forecasting: a critical assessment of recent applications |
| title_fullStr | Google Trends and Baidu index data in tourism demand forecasting: a critical assessment of recent applications |
| title_full_unstemmed | Google Trends and Baidu index data in tourism demand forecasting: a critical assessment of recent applications |
| title_short | Google Trends and Baidu index data in tourism demand forecasting: a critical assessment of recent applications |
| title_sort | google trends and baidu index data in tourism demand forecasting a critical assessment of recent applications |
| topic | 330 Economics |
| work_keys_str_mv | AT mikulicjosip googletrendsandbaiduindexdataintourismdemandforecastingacriticalassessmentofrecentapplications AT baumgartnerreginam googletrendsandbaiduindexdataintourismdemandforecastingacriticalassessmentofrecentapplications |