WU Doris Chenguang

Professor

Phone：020-84112645

Email：wucheng@mail.sysu.edu.cn

Research Areas：Big data analytics and forecasting; Tourism forecasting and impact analysis; Smart medical management

Brief Introduction

 

Doris Chenguang Wu is professor, assistant dean, director of MBA center, director of tourism and healthcare management department in the School of Business at the Sun Yat-sen University, China. 

Her research interests include big data analytics and forecasting, tourism forecasting and impact analysis, and smart healthcare management. She obtained her bachelor and master degrees in economics from School of Statistics, Dongbei University of Finance and Economics in China, and PhD degree in tourism management from School of Hotel and Tourism School at The Hong Kong Polytechnic University in 2010.

She is the founding chair of Tourism and Hospitality Section (THS) of International Institute of Forecasters (IIF), board director of International Institute of Forecasters (IIF, 2020-2024), and Fellow and Outstanding Young Scholar of International Association for China Tourism Studies (IACTS). She serves as editorial board member for the journals of Annals of Tourism Research, Journal of Travel Research, Tourism Economics, Asia Pacific Journal of Tourism Research, Journal of China Tourism Research, and Journal of Hospitality and Tourism Insights.

She has co-edited a special issue on “Tourism forecasting – New trends and issues” for Tourism Economics in 2019, and a special issue on “Big data analytics and forecasting in hospitality and tourism” for International Journal of Contemporary Hospitality Management in 2021. In addition, she has been involved in a number of research grants and consultation projects in the areas of tourism forecasting and tourism economics funded by the governments in China.

 

Dr Wu supervises PhD and master students and postgraduate fellows.

Contact information: wucheng@mail.sysu.edu.cn

Research Areas

Big data analytics and forecasting, Tourism demand forecasting and decision; Tourism impact analysis; Smart medical management

Educational Background

PhD               The Hong Kong Polytechnic University, Hong Kong, China,  2010

MSc              Dongbei University of Finance and Economics, Dalian, China, 2005

BA                Dongbei University of Finance and Economics, Dalian, China, 2002

Professional Experiences

2020-present       Professor, School of Business, Sun Yat-sen University, China

2014-2020           Associate Professor, School of Business, Sun Yat-sen University, China

2017-2018           Visiting Scholar, School of Hotel and Tourism Management, University of Surrey, UK

2010-2014           Assistant Professor, School of Business, Sun Yat-sen University, China

Publications

Books

  1. Wu, D. C., Li, G., & Song, H. (2023). (Eds.) Econometric Modelling and Forecasting of Tourism Demand: Methods and Applications. London, UK: Routledge

     

Journal articles

  1. Hu, M., Zhao, X., Ren, J., & Wu*, D. C. (2025). A novel big data-based multicollinearity-eliminating feature extraction method for tourism demand forecasting. Tourism Economics.
    http://doi.org/10.1177/135481662513649982
  2. Hu, M., Liang, W., Qiu, R. T. R., & Wu*, D. C. (2025). Tourism demand forecasting using compound pattern recognition. Tourism Management, 109, 105138.
    https://doi.org/10.1016/j.tourman.2025.1051383
  3. Li, W., Wang, T.,& Wu*, D. C. (2025). User motivation and sustained participation in walking donation as a virtual corporate social responsibility co-creation project. Humanities &Social Sciences Communications, 12, 784.
    https://doi.org/10.1057/s41599-025-05106-14
  4. Wu, D. C., Li, W., Wu*, J., Hu, M., & Shen, S. (2025). How well can ChatGPT forecast tourism demand? Tourism Management, 108, 105119.
    https://doi.org/10.1016/j.tourman.2024.1051195
  5. Wu, J., Song, Y., & Wu*, D. C. (2024). Does ChatGPT show gender bias in behavior detection? Humanities& Social Sciences Communications. 11, 1706. 
    https://doi.org/10.1057/s41599-024-04219-3
  6. Wu, D. C., Zhong, S., Song, H., & Wu*, J. (2024). Do topic and sentiment matter? Predictive power of online reviews for hotel demand forecasting. International Journal of Hospitality Management. 120, 103750.
    https://doi.org/10.1016/j.ijhm.2024.103750
  7. Wu, D. C., Cao, C., Wu, J., & Hu*, M. (2024) Wine tourism experiences of Chinese tourists: A tourist-centric perspective. International Journal of Contemporary Hospitality Management.
    https://doi.org/10.1108/IJCHM-07-2023-1003
  8. Wu, D. C., Zhong, S. T., Wu*, J., & Song, H. (2024) Tourism and hospitality forecasting with big data: A systematic review of the literature. Journal of Hospitality & Tourism Research 1–20
    http://doi.org/10.1177/10963480231223151
  9. Hu, M., Yang, H., Wu*, D. C., & Ma, S. (2024). A novel two-stage combination model for tourism demand forecasting. Tourism Economics 0 0:0
    https://doi.org/10.1177/13548166241237845
  10. Zhang*, X., Cheng, M., & Wu, D. C. (2024). Daily tourism demand forecasting and tourists’ search behavior analysis: A deep learning approach. International Journal of Machine Learning and Cybernetics.
    https://doi.org/10.1007/s13042-024-02157-9
  11. Wu, D. C., Zhao, X., & Wu*, J. (2023). Online physician-patient interaction and patient satisfaction: Empirical study of the internet hospital service. Journal of Medical Internet Research. 25
    https://doi.org/10.2196/39089
  12. Liu, H., Yang, P., Song, H., & Wu*, D. C. (2023). Global and domestic economic policy uncertainties and tourism stock market: Evidence from China. Tourism Economics
    https://doi.org/10.1177/13548166231173171
  13. 宋海岩，吴晨光*. (2022). 新一轮科技革命与旅游需求分析和预测创新：理论探讨与实践前沿[J]. 旅游学刊，37(10),1-3
    https://doi.org/10.19765/j.cnki.1002-5006.2022.10.001
  14. Wu, D. C., Cao, C., Liu, W., & Chen*, J. L. (2022). Impact of domestic tourism on economy under COVID-19: The perspective of tourism satellite accounts. Annals of Tourism Research Empirical Insights, 3(2), 100055.
     https://doi.org/10.1016/j.annale.2022.100055
  15. Wu, D. C., Zhong, S., Qiu, R. T. R., & Wu*, J. (2022). Are customer reviews just reviews? Hotel forecasting using sentiment analysis. Tourism Economics, 28(3), 795-816.
    https://doi.org/10.1177/13548166211049865
  16. Song, H. & Wu*, D. C. (2022). A critique of tourism-led economic growth studies. Journal of Travel Research, 61(4), 719-729. 
    https://doi.org/10.1177/00472875211018514
  17. 吴晨光.(2021).基于大数据的旅游预测与决策[J]. 旅游论坛, 14(3):19-22.
    https://doi.org/10.15962/j.cnki.tourismforum.202103020
  18. Wu, D. C., Wu*, J., & Song, H. (2021). Guest editorial: Big data analytics and forecasting in hospitality and tourism. International Journal of Contemporary Hospitality Management, 33(6), 1917-1921.
    https://doi.org/10.1108/IJCHM-06-2021-035
  19. Qiu*, R.T.R., Wu*, D. C., Dropsy, V., Sylvain, P., Pratt, S., & Ohe, Y. (2021). Visitor arrival forecast amid Covid-19: A perspective from the Asia and Pacific team. Annals of Tourism Research, 88, 103155.
    https://doi.org/10.1016/j.annals.2021.103155
  20. Hu, M., Qiu, R. T. R., Wu*, D. C., & Song, H. (2021). Hierarchical pattern recognition for tourism demand forecasting. Tourism Management, 84, 104263.
    https://doi.org/10.1016/j.tourman.2020.104263
  21. Wu, D. C., Cao, Z., Wen, L., &Song, H. (2021). Scenario forecasting for global tourism. Journal of Hospitality and Tourism Research, 45(1), 28-51. https://doi.org/10.1177/1096348020919990
  22. Liu, A., & Wu*, D. C. (2019). Tourism productivity and economic growth. Annals of Tourism Research, 76, 253-265.
    https://doi.org/10.1016/j.annals.2019.04.005
  23. Li, G., Wu*, D. C., Zhou, M., & Liu, A. (2019). The combination of interval forecasts in tourism. Annals of Tourism Research, 75, 363-378. 
    https://doi.org/10.1016/j.annals.2019.01.010
  24. Li, G. &Wu*, D. C. (2019). Introduction to the special focus: Tourism forecasting – New trends and issue, Tourism Economics, 25(3), 305-308.
    https://doi.org/10.1177/1354816618816809
  25. Chen, J. L., Li, G., Wu*, D. C., & Shen, S. (2019). Forecasting seasonal tourism demand using a multiseries structural time series method, Journal of Travel Research, 58(1), 92-103.
    https://doi.org/10.1177/0047287517737191
  26. Wu, D. C., Liu, J., Song, H., Liu, A., & Fu, H. (2019). Developing a Web-based regional tourism satellite account (TSA) information system, Tourism Economics, 25(1), 67-84.
    https://doi.org/10.1177/1354816618792446
  27. Wu, D. C., Fu, H., & Kang, M. (2018). Why volunteer teaching tourism? Empirical evidence from China, Asia Pacific Journal of Tourism Research, 23(2):109-120.
    https://doi.org/10.1080/10941665.2017.1410191
  28. Wu, D. C., Song, H., & Shen, S. (2017). New developments in tourism and hotel demand modeling and forecasting, International Journal of Contemporary Hospitality Management, 29(1), 507-529.
    https://doi.org/10.1108/IJCHM-05-2015-0249
  29. 吴晨光，刘静艳. 旅游卫星账户的时空观——基于广东省旅游卫星账户数据信息系统建设的研究和再思考[J]. 旅游学刊, 2016, 31(3): 6-7.
  30. Fu, H., Wu*, D. C., Huang, S.S., Song, H., Gong, J. (2015). Monetary or nonmonetary compensation for service failure? A study of customer preferences under various loci of causality. International Journal of Hospitality Management. 46, 55-64.
    https://doi.org/10.1016/j.ijhm.2015.01.006
  31. 傅慧,吴晨光,段艳红. “货币补偿”总是最优策略吗？——高星级酒店不同服务失误归因下的情境研究[J]. 旅游学刊, 2014, 29(1): 101-110.
  32. 颜麒,吴晨光,叶浩彬. (2013) 离岛免税政策对海南省旅游需求影响效应实证研究[J]. 旅游学刊, 2013, 28(10): 47-51.
  33. Li, G., Song, H., Cao Z., & Wu*, D. C. (2013). How competitive is Hong Kong against its competitors? An econometric study. Tourism Management. 36(1), 247-256.
    https://doi.org/10.1016/j.tourman.2012.11.019
  34. Li, G., Song, H., Chen, J., & Wu, D. C. (2012). Comparing mainland Chinese tourists’ satisfaction with Hong Kong and the UK using tourist satisfaction index. Journal of China Tourism Research, 8(4), 373-394.
  35. Pan, B., Wu*, D. C., & Song, H. (2012). Forecasting hotel room demand using search engine data. Journal of Hospitality and Tourism Technology, 3(3), 196-210.
  36. Wu, D. C., Li, G., & Song, H. (2012). Economic analysis of tourism consumption dynamics: A time-varying parameter demand system approach. Annals of Tourism Research, 39(2), 667-685.
    https://doi.org/10.1016/j.annals.2011.09.003
  37. Page, S. J., Song, H., &Wu*, D. C. (2012). Assessing the impacts of the economic crisis and swine flu on inbound tourism demand in the UK. Journal of Travel Research, 51(2), 142-153.
    https://doi.org/10.1177/0047287511400754
  38. Wu, D. C., Li, G., & Song, H. (2011). Analysing tourism consumption: A dynamic system of equations approach. Journal of Travel Research, 50(1), 46-56.
    https://doi.org/10.1177/0047287509355326
  39. Athanasopoulos, G., Hyndman, R. J., Song, H., & Wu, D. C.  (2011).The tourism forecasting competition. International Journal of Forecasting. 27(3), 822–844.
    https://doi.org/10.1016/j.ijforecast.2010.04.009
  40. Song, H., Witt, S. F., Wong, K. K. F., & Wu, D. C. (2009). An empirical study of tourism demand forecast combination. Journal of Hospitality and Tourism Research, 33, 3-29.
    https://doi.org/10.1177/1096348008321366
  41. Wong, K. K. F., Song, H., Witt, S. F., & Wu, D. C. (2007). Tourism forecasting: To combine or not to combine? Tourism Management, 28, 1068-1078.
    https://doi.org/10.1016/j.tourman.2006.08.003

Research Grants as PI

  1. 2024-2027 National Natural Science Foundation of China (72374226). Project title: Big data analytics, demand system models and tourism regional synergy in the Greater Bay Area. (RMB 410 thousand) (PI)
  2. 2022-2023 Department of Culture and Tourism of Guangdong Province, Statistical Project: Tourist satisfaction evaluation for Guangdong province based on big data mining—Cases of Guangzhou and Jiangmen. (RMB 5 thousand) (PI)
  3. 2019-2023 Guangdong Natural Science Foundation for Distinguished Young Scholar (2020B1515020031). Project title: Interval combination forecasting of tourism demand: Methods and applications. (RMB 1000 thousand) (PI)
  4. 2016-2019 National Natural Science Foundation of China (71573289). Project title: The combination of forward-looking, backward-looking and expert judgment: A new framework and empirical study of tourism demand modeling and forecasting (RMB 576 thousand) (PI)
  5. 2012-2014 National Natural Science Foundation of China for Young Professionals (71103206). Project title: Nonlinear modeling for the relationship between tourism development and economic growth in China (RMB 190 thousand) (PI)
  6. 2013-2015 Sun Yat-sen University’s Fundamental Research Funds for the Central Universities in China. An econometric analysis on mainland Chinese demand for Hong Kong tourism. 2013.1-2015.12. (75 thousand) (PI)
  7. 2012-2013 China Postdoctoral Science Foundation. Tourism demand and economic growth: A nonlinear modelling perspective (50 thousand) (PI)
  8. 2013-2014 Guangdong Tourism Administration. TSA Information System: Construction and Application (1.98 million) (PI)
  9. 2012-2013 Guangdong Tourism Administration. TSA Information System: Framework and Construction (1.58 million) (PI)
  10. 2011-2012 Guangdong Tourism Administration. Guangdong Tourism Satellite Accounts: Theory and Practice. (2.2 million) (PI)

Teaching Subjects

Undergraduate level: Introduction to econometrics, Tourism big data forecasting and decision, Market research methods, Business statistics, Tourism innovation and leadership

PhD/MPhil level: Contemporary topics in tourism research; Tourism and health management

EMBA/MBA level: Data, model and decision; Smart healthcare management and innovation; Quantitative Methods; Thesis writing

 

Academic Services and Achievement

  • 2025-now,  Fellow, International Association for China Tourism Studies (IACTS, https://www.chinatourismiacts.org/）
  • 2025-now, Standing board member, China Information Economics Society （CIES, www.cies.org.cn）
  • 2020-2022, Tourism and Hospitality Section (THS), International Institute of Forecasters (IIF)
  • 2020-2024, Board director, International Institute of Forecasters (IIF)
  • 2020-present Outstanding Young Scholar, International Association for China Tourism Studies (IACTS）
  • Editorial board member: Annals of Tourism Research (2022-), Journal of Travel Research(2018-), Tourism Economics (2018-), Asia Pacific Journal of Tourism Research (2021-), Journal of China Tourism Research (2021-), Journal of Hospitality and Tourism Insights（2021.7-）, 旅游论坛
  • Guest editor: “Tourism Forecasting: New Trends and Issues” of Tourism Economics
  • Guest editor: “Big data analytics and forecasting in hospitality and tourism” of International Journal of Contemporary Hospitality Management