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      Assessing the reactions of tourist markets to reinstated travel restrictions in the destination during the post-COVID-19 phase

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          Abstract

          This study, leveraging search engine data, investigates the dynamics of China's domestic tourism markets in response to the August 2022 epidemic outbreak in Xinjiang. It focuses on understanding the reaction mechanisms of tourist-origin markets during destination crises in the post-pandemic phase. Notably, the research identifies a continuous rise in the potential tourism demand from tourist origin cities, despite the challenges posed by the epidemic. Further analysis uncovers a regional disparity in the growth of tourism demand, primarily influenced by the economic stratification of origin markets. Additionally, the study examines key tourism attractions such as Duku Road, highlighting its resilient competitive system, which consists of distinctive tourism experiences, economically robust tourist origins, diverse tourist markets, and spatial pattern stability driven by economic factors in source cities, illustrating an adaptive response to external challenges such as crises. The findings provide new insights into the dynamics of tourism demand, offering a foundation for developing strategies to bolster destination resilience and competitiveness in times of health crises.

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          Pandemics, tourism and global change: a rapid assessment of COVID-19

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            Spatial Econometrics: Methods and Models

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              Predicting the Present with Google Trends

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                Author and article information

                Contributors
                yangzp@ms.xjb.ac.cn
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                5 July 2024
                5 July 2024
                2024
                : 14
                : 15495
                Affiliations
                [1 ]Urumqi Urban Institute of Geotechnical Investigation Surveying and Mapping, Urumqi, 830000 China
                [2 ]GRID grid.9227.e, ISNI 0000000119573309, State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, , Chinese Academy of Sciences, ; Urumqi, 830011 China
                [3 ]GRID grid.9227.e, ISNI 0000000119573309, Institute of Geographic Sciences and Natural Resources Research, , Chinese Academy of Sciences, Beijing, ; No. 818, Beijing South Road, Urumqi, 100101 Xinjiang China
                [4 ]University of Chinese Academy of Sciences, ( https://ror.org/05qbk4x57) Beijing, 100049 China
                [5 ]College of Geography and Remote Sensing Sciences, Xinjiang University, ( https://ror.org/059gw8r13) Urumqi, 800046 China
                [6 ]School of Artificial Intelligence, Shenzhen Polytechnic University, ( https://ror.org/00d2w9g53) Shenzhen, 518055 China
                Article
                66459
                10.1038/s41598-024-66459-2
                11226617
                38969709
                a1cd74f7-36b5-47eb-80ac-2bfb242fd4fa
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 7 November 2023
                : 1 July 2024
                Funding
                Funded by: Guangdong Basic and Applied Basic Research Foundation
                Award ID: 2023A1515011273
                Award Recipient :
                Funded by: Basic Research Program of Shenzhen
                Award ID: 20220811173316001
                Award Recipient :
                Funded by: Specific Innovation Program of the department of Education of Guangdong Province
                Award ID: 2023KTSCX315
                Award Recipient :
                Funded by: Xinjiang Major Science & Technology Projects
                Award ID: No. 2022A03002
                Funded by: Xinjiang Social Science Foundation Projects
                Award ID: No. 2022VZJ028
                Categories
                Article
                Custom metadata
                © Springer Nature Limited 2024

                Uncategorized
                tourism demand,post-covid-19,tourism crisis management,search engine data analysis,tourism resilience,socioeconomic scenarios,sustainability

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