Application of Google Trends to Forecast Tourism Demand

Internet becomes a necessity in our modern lives. The rapid growth of Internet’s popularity results in a huge amount of data. Hence, big data analytics is on its berth to handle the data. One interesting research track of the big data literature focuses on “search engine data.” The analysis the search engine data is valuable because the business intelligence generated from the analysis offers insights for business opportunities. Google Trends is a popular target for studying search engine data, because it is readily available and easy to access. Because analyzing and forecasting things based on Google Trends can help various domain problems, this study proposes a systematic approach to obtain Google Trends search engine data, to explore usage of the data, and then to provide a forecast. We use Taiwan tourism demand as a study target, where both estimation and forecasting are done by our proposed method. The forecasting results are then compared with real data from the Taiwan Tourism Bureau.

[1]  Carey Goh,et al.  Exploring impact of climate on tourism demand , 2012 .

[2]  Melda Akın,et al.  A novel approach to model selection in tourism demand modeling , 2015 .

[3]  Fong-Lin Chu,et al.  Forecasting tourism demand with ARMA-based methods. , 2009 .

[4]  George Athanasopoulos,et al.  Modelling and Forecasting Australian Domestic Tourism , 2006 .

[5]  L. Moutinho,et al.  Modeling and forecasting tourism demand: the case of flows from Mainland China to Taiwan , 2008 .

[6]  Bau-Jung Chang,et al.  Agile Business Intelligence: Combining Big Data and Business Intelligence to Responsive Decision Model , 2018 .

[7]  K. Huarng,et al.  Internet software and services: past and future , 2011 .

[8]  Kun-Huang Huarng,et al.  A Study of Online Auction in YAHOO! TAIWAN( Contribution to 21 Century Intelligent Technologies and Bioinformatics) , 2008 .

[9]  H. Varian,et al.  Predicting the Present with Google Trends , 2009 .

[10]  Yue Chen,et al.  Data mining from web search queries: A comparison of google trends and baidu index , 2015, J. Assoc. Inf. Sci. Technol..

[11]  K. Huarng,et al.  The impact of online customer satisfaction on the yahoo auction in Taiwan , 2012 .

[12]  Katharine Armstrong,et al.  Big data: a revolution that will transform how we live, work, and think , 2014 .

[13]  Kun-Huang Huarng,et al.  Forecasting tourism demand by fuzzy time series models , 2012 .

[14]  K. Lahiri,et al.  A non-linear forecast combination procedure for binary outcomes , 2015, Social Science Research Network.

[15]  Nicole Koenig-Lewis,et al.  Seasonality research: the state of the art , 2005 .

[16]  T. Baum,et al.  Seasonality in tourism , 2001 .

[17]  John H. Gerdes,et al.  Using web-based search data to predict macroeconomic statistics , 2005, CACM.

[18]  Bing Pan,et al.  Forecasting hotel room demand using search engine data. , 2012 .

[19]  Stephen F. Witt,et al.  An Empirical Study of Forecast Combination in Tourism , 2009 .

[20]  C. Witt,et al.  Forecasting tourism demand: A review of empirical research , 1995 .

[21]  Huiyu Sun,et al.  Big Data Trip Classification on the New York City Taxi and Uber Sensor Network , 2018 .

[22]  H Eugene Stanley,et al.  Complex dynamics of our economic life on different scales: insights from search engine query data , 2010, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[23]  Çagdas Hakan Aladag,et al.  Forecast Combination by Using Artificial Neural Networks , 2010, Neural Processing Letters.

[24]  Giselle C. Guzman,et al.  Internet Search Behavior as an Economic Forecasting Tool: The Case of Inflation Expectations , 2011 .

[25]  L. Moutinho,et al.  An Advanced Approach to Forecasting Tourism Demand in Taiwan , 2007 .

[26]  Rob Law,et al.  Forecasting tourism demand with composite search index , 2017 .

[27]  Lucia Aiello,et al.  Internet as a "point of synergy" between communication and distribution: hypothesis of model applied to tourism , 2010, J. Digit. Content Technol. its Appl..

[28]  Rob Law,et al.  The Dynamics of Search Engine Marketing for Tourist Destinations , 2011 .

[29]  Andrea Guizzardi,et al.  Real-time forecasting regional tourism with business sentiment surveys , 2015 .

[30]  Kun-Huang Huarng,et al.  Viral effects of social network and media on consumers’ purchase intention , 2015 .

[31]  Yossi Matias,et al.  On the Predictability of Search Trends , 2009 .

[32]  Irem Önder,et al.  Forecasting international city tourism demand for Paris: Accuracy of uni- and multivariate models employing monthly data , 2015 .

[33]  C. Tisdell.  Basic economics of tourism : an overview. , 1998 .

[34]  Kun-Huang Huarng,et al.  The impacts of instructional video advertising on customer purchasing intentions on the Internet , 2010 .