Tourism demand forecasting and tourists’ search behavior: evidence from segmented Baidu search volume
Given the importance of web search volume for reflecting tourists' preferences for certain tourism services and destinations, incorporating these data into forecasting models can significantly improve forecasting performance. This study enriches the literature on tourism demand forecasting and...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co. Ltd.
2021-12-01
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| Series: | Data Science and Management |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S266676492100028X |
| _version_ | 1797976432893231104 |
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| author | Yifan Yang Ju'e Guo Shaolong Sun |
| author_facet | Yifan Yang Ju'e Guo Shaolong Sun |
| author_sort | Yifan Yang |
| collection | DOAJ |
| description | Given the importance of web search volume for reflecting tourists' preferences for certain tourism services and destinations, incorporating these data into forecasting models can significantly improve forecasting performance. This study enriches the literature on tourism demand forecasting and tourists' search behavior through segmented Baidu search volume data. First, this study divides Baidu search volume data based on volume sources and periods. Then, by analyzing the most relevant keywords in tourism demand in different segments, this study captures the dynamic characteristics of tourist search behavior. Finally, this study adopts a series of econometric and machine learning models to further improve the performance of tourism demand and forecasting. The findings indicate that tourists’ search behavior has changed significantly with the prevalence and popularization of 4G technology and suggest that search volume improves forecasting performance, especially search volume on mobile terminals, from 2014M1–2019M12. |
| first_indexed | 2024-04-11T04:50:50Z |
| format | Article |
| id | doaj.art-3fa7173a3d584ecfb21a0207b7ffa812 |
| institution | Directory Open Access Journal |
| issn | 2666-7649 |
| language | English |
| last_indexed | 2024-04-11T04:50:50Z |
| publishDate | 2021-12-01 |
| publisher | KeAi Communications Co. Ltd. |
| record_format | Article |
| series | Data Science and Management |
| spelling | doaj.art-3fa7173a3d584ecfb21a0207b7ffa8122022-12-27T04:38:27ZengKeAi Communications Co. Ltd.Data Science and Management2666-76492021-12-01419Tourism demand forecasting and tourists’ search behavior: evidence from segmented Baidu search volumeYifan Yang0Ju'e Guo1Shaolong Sun2School of Management, Xi'an Jiaotong University, Xi'an, 710049, ChinaSchool of Management, Xi'an Jiaotong University, Xi'an, 710049, ChinaCorresponding author.; School of Management, Xi'an Jiaotong University, Xi'an, 710049, ChinaGiven the importance of web search volume for reflecting tourists' preferences for certain tourism services and destinations, incorporating these data into forecasting models can significantly improve forecasting performance. This study enriches the literature on tourism demand forecasting and tourists' search behavior through segmented Baidu search volume data. First, this study divides Baidu search volume data based on volume sources and periods. Then, by analyzing the most relevant keywords in tourism demand in different segments, this study captures the dynamic characteristics of tourist search behavior. Finally, this study adopts a series of econometric and machine learning models to further improve the performance of tourism demand and forecasting. The findings indicate that tourists’ search behavior has changed significantly with the prevalence and popularization of 4G technology and suggest that search volume improves forecasting performance, especially search volume on mobile terminals, from 2014M1–2019M12.http://www.sciencedirect.com/science/article/pii/S266676492100028XBaidu search volumeTourist search behaviorTourism demand forecastingEvent studySelection of keywords |
| spellingShingle | Yifan Yang Ju'e Guo Shaolong Sun Tourism demand forecasting and tourists’ search behavior: evidence from segmented Baidu search volume Data Science and Management Baidu search volume Tourist search behavior Tourism demand forecasting Event study Selection of keywords |
| title | Tourism demand forecasting and tourists’ search behavior: evidence from segmented Baidu search volume |
| title_full | Tourism demand forecasting and tourists’ search behavior: evidence from segmented Baidu search volume |
| title_fullStr | Tourism demand forecasting and tourists’ search behavior: evidence from segmented Baidu search volume |
| title_full_unstemmed | Tourism demand forecasting and tourists’ search behavior: evidence from segmented Baidu search volume |
| title_short | Tourism demand forecasting and tourists’ search behavior: evidence from segmented Baidu search volume |
| title_sort | tourism demand forecasting and tourists search behavior evidence from segmented baidu search volume |
| topic | Baidu search volume Tourist search behavior Tourism demand forecasting Event study Selection of keywords |
| url | http://www.sciencedirect.com/science/article/pii/S266676492100028X |
| work_keys_str_mv | AT yifanyang tourismdemandforecastingandtouristssearchbehaviorevidencefromsegmentedbaidusearchvolume AT jueguo tourismdemandforecastingandtouristssearchbehaviorevidencefromsegmentedbaidusearchvolume AT shaolongsun tourismdemandforecastingandtouristssearchbehaviorevidencefromsegmentedbaidusearchvolume |