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Yongjing Wang

Biographic Data

ID3914717
NAMEYongjing Wang
GIVEN NAMESYongjing
FAMILY NAMEWang
SIGNATUREWANG Y
AFFILIATIONSSchool of Professional Education and Executive Development The Hong Kong Polytechnic University Hong Kong SAR China
ORCID0000-0002-0494-5998
VERIFIEDYes
TOTAL WORKS5
TOTAL CITATIONS0
AUTHOR COUNT5
EDITOR COUNT0
FIRST PUBLICATION YEAR2021
LATEST PUBLICATION YEAR2026
H-INDEX0
  • Tourism Recovery Nowcasting Based on Combined Survey‐Based and Search Engine Data: A Forward‐Looking Micro–Macro Approach

    Open Access•Xinyan Zhang, Haiyan Song et al.•ARTICLE•International Journal of Tourism…•2026

    The uncertainty of tourism demand in the aftermath of a crisis makes high‐frequency nowcasts valuable for fast decision‐making in destination management. Through the lens of modern macroeconomic theories, this study proposes an innovative macro–micro tourism demand nowcasting approach using forward‐looking survey‐based and search engine data to capture the post‐COVID‐19 recovery trajectory. The empirical results show that combining survey‐based c…

  • International country risk and tourism demand: A multidimensional analysis using a mixed-frequency global vector autoregressive model in the Asia-Pacific Region

    Open Access•Yongjing Wang, Han Liu et al.•ARTICLE•Tourism Management•2026•References: 49

  • Digitization and Multidimensional Relative Poverty in Rural Regions: A Theoretical Examination and China Practice

    Open Access•Yongjing Wang, Yangyang Ji•ARTICLE•Journal of International…•2025

    This study investigates the impact of digitization on multidimensional relative poverty in rural areas using provincial panel data from China. The findings reveal that digitization significantly reduces rural multidimensional relative poverty, with indirect effects through farmers' income structures, rural industrial revitalization and urban–rural integration. Moreover, digitization demonstrates a positive spatial spillover effect, reducing multi…

  • Measuring tourism demand nowcasting performance using a monotonicity test

    Open Access•Han Liu, Yongjing Wang et al.•ARTICLE•Tourism Economics•2023

    Tourism demand nowcasting is generally carried out using econometric models that incorporate either macroeconomic variables or search query data as explanatory variables. Nowcasting model accuracy is normally evaluated by traditional loss functions. This study proposes a novel statistical method, the monotonicity test, to assess whether the nowcasting errors obtained from the ordinary least squares, generalised dynamic factor model and generalise…

  • The Robust Causal Relationships Among Domestic Tourism Demand, Carbon Emissions, and Economic Growth in China

    Open Access•Yonglian Wang, Lijun Wang et al.•ARTICLE•SAGE Open•2021•References: 63

    Green and low-carbon development has become a compelling trend of our time. To formulate policies for development and also reduction of carbon emissions, quantifying the trend of tourism in green sustainable development is an essential issue for China, which is undergoing an economic transformation. This study first measured China's domestic tourism carbon emissions through a bottom-up approach and then used the robust Granger causality test on a…

No prominent works on this page.

  • The Robust Causal Relationships Among Domestic Tourism Demand, Carbon Emissions, and Economic Growth in China

    Open Access•Yonglian Wang, Lijun Wang et al.•ARTICLE•SAGE Open•2021•References: 63

    Green and low-carbon development has become a compelling trend of our time. To formulate policies for development and also reduction of carbon emissions, quantifying the trend of tourism in green sustainable development is an essential issue for China, which is undergoing an economic transformation. This study first measured China's domestic tourism carbon emissions through a bottom-up approach and then used the robust Granger causality test on a…

  • Measuring tourism demand nowcasting performance using a monotonicity test

    Open Access•Han Liu, Yongjing Wang et al.•ARTICLE•Tourism Economics•2023

    Tourism demand nowcasting is generally carried out using econometric models that incorporate either macroeconomic variables or search query data as explanatory variables. Nowcasting model accuracy is normally evaluated by traditional loss functions. This study proposes a novel statistical method, the monotonicity test, to assess whether the nowcasting errors obtained from the ordinary least squares, generalised dynamic factor model and generalise…

  • Digitization and Multidimensional Relative Poverty in Rural Regions: A Theoretical Examination and China Practice

    Open Access•Yongjing Wang, Yangyang Ji•ARTICLE•Journal of International…•2025

    This study investigates the impact of digitization on multidimensional relative poverty in rural areas using provincial panel data from China. The findings reveal that digitization significantly reduces rural multidimensional relative poverty, with indirect effects through farmers' income structures, rural industrial revitalization and urban–rural integration. Moreover, digitization demonstrates a positive spatial spillover effect, reducing multi…

  • Tourism Recovery Nowcasting Based on Combined Survey‐Based and Search Engine Data: A Forward‐Looking Micro–Macro Approach

    Open Access•Xinyan Zhang, Haiyan Song et al.•ARTICLE•International Journal of Tourism…•2026

    The uncertainty of tourism demand in the aftermath of a crisis makes high‐frequency nowcasts valuable for fast decision‐making in destination management. Through the lens of modern macroeconomic theories, this study proposes an innovative macro–micro tourism demand nowcasting approach using forward‐looking survey‐based and search engine data to capture the post‐COVID‐19 recovery trajectory. The empirical results show that combining survey‐based c…

  • International country risk and tourism demand: A multidimensional analysis using a mixed-frequency global vector autoregressive model in the Asia-Pacific Region

    Open Access•Yongjing Wang, Han Liu et al.•ARTICLE•Tourism Management•2026•References: 49

Diverse Aspects of Tourism Research (4 works) · Econometrics (3 works) · Economics (3 works) · Geography (3 works) · Tourism (3 works) · China (2 works) · Computer Science (2 works) · Nowcasting (2 works) · Spillover effect (2 works) · Big data (1 works)

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