Forecasting Chinese tourist volume with search engine data

Tourism Management

Volumn 46, Issue , 2015, Pages 386-397

  Yang, Xin ^a,b   Pan, Bing ^c   Evans, James A ^b   Lv, Benfu ^a  

^a UNIVERSITY OF CHINESE ACADEMY OF SCIENCES   (China)

^b UNIVERSITY OF CHICAGO   (United States)

^c School of Business   (United States)

Author keywords

Baidu Index; Chinese tourism market; Google Trends; Search engine data; Tourist volume forecast; Visitor prediction

Indexed keywords

FORECASTING METHOD; PREDICTION; TOURISM MARKET; TOURIST DESTINATION; TRAVEL BEHAVIOR; WORLD WIDE WEB; INTERNET; PREFERENCE BEHAVIOR; REGRESSION ANALYSIS; TOURIST BEHAVIOR; TRAVEL DEMAND; TREND ANALYSIS;

CHINA; HAINAN;

EID: 84907087642     PISSN: None     EISSN: 02615177     Source Type: Journal    
DOI: 10.1016/j.tourman.2014.07.019     Document Type: Article

References (51)

1. Abratt R., Nel D., Nezer C. Role of the market maven in retailing - a general marketplace influencer. Journal of Business and Psychology 1995, 10(1):31-55.
2. Althouse B.M., Ng Y.Y., Cummings D.A. Prediction of dengue incidence using search query surveillance. PLoS Neglected Tropical Diseases 2011, 5(8):e1258.
3. Alvarez-Diaz M., Mateu-Sbert J., Rossello-Nadal J. Forecasting tourist arrivals to Balearic Islands using genetic programming. International Journal of Computational Economics and Econometrics 2009, 1(1):64-75.
4. Andrew W.P., Cranage D.A., Lee C.K. Forecasting hotel occupancy rates with time series models: an empirical analysis. Journal of Hospitality & Tourism Research 1990, 14(2):173-182.
5. Askitas N., Zimmermann K. Google econometrics and unemployment forecasting. Applied Economics Quarterly 2009, 55(2):107-120.
6. Baram-Tsabari A., Segev E. Exploring new web-based tools to identify public interest in science. Public Understanding of Science 2011, 20(1):130-143.
7. Carneiro H.A., Mylonakis E. Google trends: a web-based tool for real-time surveillance of disease outbreaks. Clinical Infectious Diseases 2009, 49(10):1557-1564.
8. Carrière-Swallow Y., Labbé F. Nowcasting with google trends in an emerging market. Journal of Forecasting 2011, 32(4):289-298.
9. Chaitip P., Chaiboonsri C. Forecasting with X-12-ARIMA and ARFIMA: international tourist arrivals to India. Annals of the University of Petrosani Economics 2009, 9(3):147-162.
10. Chan C., Witt S., Lee Y., Song H. Tourism forecast combination using the CUSUM technique. Tourism Management 2010, 31(6):891-897.
11. Chen J., Chen Z.X., Xing L., Fu X.D. Forecasting of yunnan's international tourism demand based on bp neural network. Journal of Kunming Teachers College 2005, 27(4):89-91.
12. China Internet Network Information Center (CNNIC) Statistical report on Internet development in China 2013, Available online at. http://www1.cnnic.cn/AU/MediaC/rdxw/hotnews/201307/t20130722_40723.htm.
13. China National Tourism Administration Tourism statistics 2014, Available online at. http://www.cnta.gov.cn/html/rjy/index.html.
14. Choi H., Varian H. Predicting present with google trends. Economic Record 2012, 88(S1):2-9.
15. D'Amuri F. Predicting unemployment in short samples with internet job search query data 2009, University Library of Munich, Germany, Available online at. http://mpra.ub.uni-muenchen.de/18403/.
16. Dzielinski M. Measuring economic uncertainty and its impact on the stock market. Finance Research Letters 2012, 9(3):167-175.
17. Feng Y. An application of ARMA model in tourist prediction. Zhejiang Statistics 2008, 31(10):8-10.
18. Gawlik E., Kabaria H., Kaur S. Predicting tourism trends with google insights 2011, Retrieved from. http://cs229.stanford.edu/proj2011/GawlikKaurKabaria-PredictingTourismTrendsWithGoogleInsights.pdf.
19. Ginsberg J., Mohebbi M.H., Patel R.S., Brammer L., Smolinski M.S., Brilliant L. Detecting influenza epidemics using search engine query data. Nature 2009, 457(7232):1012-1014.
20. Goel S., Hofman J.M., Lahaie S.B., Pennock D.M., Watts D.J. Predicting consumer behavior with Web search. Proceedings of the National Academy of Sciences 2010, 107(41):17486-17490.
21. Goh C., Law R. Incorporating the rough sets theory into travel demand analysis. Tourism Management 2003, 24(5):511-517.
22. Hainan Tourism Bureau Tourist volume and income of Hainan province, December, 2012 2013, Available at, Accessed 26.11.13. http://www.visithainan.gov.cn/government/lvyoutongji/tongjihuizong/2012/201301/t20130129_37128.html.
23. Hand C., Judge G. Searching for the picture: forecasting UK cinema admissions using google trends data. Applied Economics Letters 2012, 19(11):1051-1055.
24. Jeng J., Fesenmaier D.R. Conceptualizing the travel decision-making hierarchy: a review of recent developments. Tourism Analysis 2002, 7(1):15-32.
25. Kan M.L., Lee Y.B., Chen W.C. Apply grey prediction in the number of Tourist. 2010 Fourth International Conference on IEEE Genetic and Evolutionary Computing 2010, 481-484. Shenzhen, China. http://doi.ieeecomputersociety.org/10.1109/ICGEC.2010.126.
26. Kholodilin K.A., Podstawski M., Siliverstovs B., Bürgi C. Google searches as a means of improving the nowcasts of key macroeconomic variables (No. 946) 2009, German Institute for Economic Research, Discussion papers.
27. Law R., Au N. Aneural network model to forecast Japanese demand for travel to Hong Kong. Tourism Management 1999, 20(1):89-97.
28. Levy S. Inside google's China misfortune. Fortune 2011, Available online at. http://tech.fortune.cnn.com/2011/04/15/googles-ordeal-in-china/.
29. Lim C., McAleer M. Time series forecasts of international travel demand for Australia. Tourism Management 2002, 23(4):389-396.
30. Liu X. The selection of econometric model on forecasting Guilin tourist number. Journal of Guangxi University Wuzhou Branch 2008, 18(2):17-21.
31. Marcucci J. "Google it!" Forecasting the US unemployment rate with a google job search index 2009, University Library of Munich, Germany, Available online at. http://mpra.ub.uni-muenchen.de/18732/.
32. McLaren N., Shanbhogue R. Using internet search data as economic indicators. Bank of England Quarterly Bulletin 2011, 51(2):134-140.
33. Pan B., Litvin S.W., Goldman H. Real users, real trips, and real queries: an analysis of destination search on a search engine. Annual Conference of Travel and Tourism Research Association (TTRA 2006). Dublin, Ireland 2006.
34. Pan B., Wu D.C., Song H. Forecasting hotel room demand using search engine data. Journal of Hospitality and Tourism Technology 2012, 3(3):196-210.
35. Pew Internet & American Life Project Internet user demogrpahics 2013, Available online at. http://www.pewinternet.org/data-trend/internet-use/latest-stats/.
36. Qiu X. Scenic area apologized and denied being attacked 2013, Available online at. http://news.xinhuanet.com/fortune/2013-10/04/c_125482946.htm.
37. Ripberger J.T. Capturing curiosity: using Internet search trends to measure public attentiveness. Policy Studies Journal 2011, 39(2):239-259.
38. Scott S.L., Varian H.R. Bayesian variable selection for nowcasting economic time series 2013, NBER working paper. Available online at:. http://www.nber.org/papers/w19567.pdf.
39. Song H., Li G. Tourism demand modeling and forecasting-A review of recent research. Tourism Management 2008, 29(2):203-220.
40. Song H., Witt S. Tourism demand modeling and forecasting: Modern econometric approaches 2000, Pergamon Press, Oxford.
41. Song H., Witt S.F., Li G. The advanced econometrics of tourism demand 2008, Routledge, New York.
42. Sterling G. Shake up in Chinese search market as engines merge 2013, Available online at. http://searchengineland.com/shake-up-in-chinese-search-market-as-secondary-engines-merge-171818.
43. Vaughan L., Romero-Frías E. Web search volume as a predictor of academic fame: an exploration of google trends. Journal of the American Society for Information Science and Technology 2013, 65(4):707-720.
44. Vosen S., Schmidt T. Forecasting private consumption: survey-based indicators vs. Google Trends. Journal of Forecasting 2011, 30(6):565-578.
45. Weatherford L.R., Kimes S.E. Acomparison of forecasting methods for hotel revenue management. International Journal of Forecasting 2003, 19(3):401-415.
46. Weng G., Zhen Z., Liu Y., Zhang X. Tourism forecasting based on GM-Markov model: a case study of inbound tourism in China. Journal of Yanshan University: Philosophy and Social Sciences Edition 2008, 2:109-112.
47. Wu L., Brynjolfsson E. The future of prediction: How google searches foreshadow housing prices and sales 2009, Working paper, Available at. http://ssrn.com/abstract=2022293.
48. Xiang Z., Pan B. Travel queries on cities in the United States: Implications for search engine marketing for tourist destinations. Tourism Management 2011, 32(1):88-97.
49. Yang Y., Pan B., Song H. Predicting hotel demand using destination marketing organization's WEB traffic data. Journal of Travel Research 2014, 53(4):433-447.
50. Zhang Y.J. The impact of financial development on carbon emissions: an empirical analysis in China. Energy Policy 2011, 39(4):2197-2203.
51. Zhang Z., Li Q. QuestionHolic: hot topic discovery and trend analysis in community question answering systems. Expert Systems with Applications 2011, 38(6):6848-6855.