Similarities and correlation between resident tourist overnights and Google Trends information in Portugal and its tourism regions

Authors

  • Maria Gorete Ferreira Dinis Instituto Politécnico de Portalegre
  • Carlos Manuel Martins Costa Universidade de Aveiro
  • Osvaldo Manuel Rocha Pacheco Universidade de Aveiro

Keywords:

Google Trends, Domestic tourism, search data, Portugal, Big Data.

Abstract

Over the last years, we observed an exponential growth in the number of tourism consumers that use the Internet as a source of information during a destination selection process. This process usually starts in a search engine, more specifically and likely on Google. Google Trends is a tool that displays data on the interest of people in a particular topic based on search trends. This data can probably be used by tourism organisations to help perform intelligent decision making, since it is available almost in real time and much earlier than the official statistical data. Indeed, this paper demonstrates that Google Trends is a tool that can provide useful and relevant information about the interests of individuals in relation to domestic tourism destinations at national and regional levels, and is focused on Google-search data regarding mainland Portugal and its tourism regions: North, Centre, Alentejo and Algarve. Our findings indicate that overnights spent in hotel establishments by the residents in Portugal are strongly correlated with the Google index, mainly in mainland Portugal, Alentejo and Algarve regions, and that the results improve when more municipalities names and the national or the regional tourism brands are included as search terms.

Author Biographies

  • Maria Gorete Ferreira Dinis, Instituto Politécnico de Portalegre

    Escola Superior de Educação e Ciências Sociais

    Turismo

  • Carlos Manuel Martins Costa, Universidade de Aveiro

    Departamento de Economia, Gestão, Engenharia Industrial e Turismo

    Turismo

  • Osvaldo Manuel Rocha Pacheco, Universidade de Aveiro

    Departamento de Engenharia Eletrónica e de Telecomunicações

    Eletrónica e Telecomunicações

References

Artola C, Galan E (2012) Tracking the future on the web: construction of leading indicators using Internet searches. Banco de Espana Occasional Paper, (1203). Accessed November, 25, 2012 in http://bit.ly/XRLfCf.

Azevedo C, Dinis MG, Breda Z (2010) Understanding visitors’ spatio-temporal distribution through data collection using information and communication technologies, Proceedings of the 10th International Forum on Tourism Statistics.

Baker S, Fradkin A (2011) What drives job search? Evidence from Google Search Data. SIEPR Discussion Paper No. 10-020. Stanford Institute For Economic Policy Research. Accessed July, 17, 2012 in http://stanford.io/1oKwdIJ.

Bloom consulting. (2015). Bloom Consulting Portugal City Brand Ranking 2015. Accessed September, 05, 2015 in http://bit.ly/1KX6Tcs.

Buhalis D, Law R (2008) Progress in information technology and tourism management: 20 years on and 10 years after the Internet-The state of eTourism research. Tourism Management, 29(4):609–623.

Buhalis D (2003) eTourism: Information technology for strategic tourism management. Pearson (Financial Times/Prentice Hall), London

Chamberlin G (2010) Googling the present. Economic & Labour Market Review, 4(12):56. Accessed November, 16, 2012 in http://bit.ly/UXfbLB.

Choi HC, Varian H (2009a) Predicting Initial Claims for Unemployment Benefits. Accessed November,12, 2011 in http://bit.ly/1snBiam

Choi HC, Varian H (2009b) Predicting the Present with Google Trends. Accessed November, 12, 2011 in http://bit.ly/1zODvPz.

Corrar LJ, Paulo E, Dias Filho, JM (2007) Análise multivariada para os cursos de administração, ciências contábeis e economia. Atlas, São Paulo.

Dinis MG, Costa C, Pacheco O (2013) Using Google Trends to obtain information about tourism. Innovation and Technology in Tourism and Hospitality applied research - Proceedings of the ISITH 2012,Colecção Politécnico da Guarda, Guarda: 91–104.

Gawlik E, Kabaria H, Kaur S (2011) Predicting tourism trends with Google Insights. Accessed December, 01, 2012 in http://stanford.io/V1lAWl.

Ginsberg J, Mohebbi MH, Patel RS, Brammer L, Smolinski MS, Brilliant L (2009) Detecting influenza epidemics using search engine query data. Nature, 457: 1012-1014. Accessed August, 16, 2011 in http://bit.ly/1so0jDn.

Google Trends (2015). Accessed February, 02, 2015 in http://www.google.pt/trends/.

Granka L (2010) Measuring agenda setting with online search traffic: influences of online and traditional media. Prepared for delivery at the 2010 Annual Meeting of the American Political Science Association, September 2-5, 2010. Accessed November, 28, 2012 in http://bit.ly/1r24t0T.

INE (2014) Estatísticas do Turismo 2013. Instituto Nacional de Estatística, Lisboa

Jansen BJ, Ciamacca CC, Spink A (2008) An analysis of travel information searching on the web. Information Technology & Tourism, 10(2):101-118

Judge G, Hand C (2010) Searching for the picture: forecasting UK cinema admissions making use of Google Trends data. Department of Economics Discussion Paper Nº 162. University of Portsmouth Business School. Accessed November, 20, 2012 in http://bit.ly/1o12y0j.

Kaushik A (2010) Web analytics 2.0: The art of online accountability & science of customer centricity. Wiley, Indianapolis

Mathieson A, Wall G (1982) Tourism, economic, physical and social impacts. Wiley, London

Maroco J (2007) Análise Estatística com utilização do SPSS (3ª Ed.). Edições Silabo, Lisboa

Pan B, Wu DC, Song H (2012) Forecasting hotel room demand using search engine data, Journal of Hospitality and Tourism Technology, 3(3):196¬–210

Pan B, Xiang Z, Fesenmaier D, Law R (2009) Destination Online Competitiveness and Search Engine Marketing. http://bit.ly/1LfPnDe.Accessed 16 August 2012

Pan B, Litvin S, Goldman, H (2006) Real users, real trips, and real queries: An analysis of destination search on a search engine. Paper presented at the Annual Conference of Travel and Tourism Research Association (TTRA 2006). Ireland, Dublin, 16 - 18 June

Pan, B, Litvin, SW, O’Donnell, TE (2007) Understanding accommodation search query formulation: The first step in putting ‘heads in beds’. Journal of Vacation Marketing, 13(4): 371–381.

Sidi N, Scacciavillani F, Ali F (2010) Forecasting Tourism in Dubai. Dubai International Finance Centre: Economic Note n.º 8. Accessed August, 06, 2011 in http://www.difc.ae/publications.

Saderson M, Kohler J (2004) Analyzing geographic queries. In the proceedings of SIGIR Workshop on Geographic Information Retrieval: The 27th Annual International ACM SIGIR Conference. Sheffield, UK, 25 - 29 July 2004

Scheitle CP (2011) Google's Insights for Search: A Note Evaluating the Use of Search Engine Data in Social Research. Social Science Quarterly, 92(1): 285–295. Accessed April, 23, 2012 in http://bit.ly/1ssqJUr.

Shimshoni Y, Efron N, Matias Y (2009) On the Predictability of Search Trends (draft). Google, Israel Labs. Accessed November, 15, 2012 in http://bit.ly/1zjL573.

Smith GP (2012) Google Internet search activity and volatility prediction in the market for foreign currency. Finance Research Letters, 9(2):103-110. Accessed November, 27, 2012 in http://bit.ly/1lEiEGc.

Smith E, White S (2011) What Insights Can Google Trends Provide About Tourism in Specific Destinations? UK: ONS. Accessed June, 10, 2012 in http://bit.ly/1o13x0r.

Scmidt T, Vosen S (2009) Forecasting private consumption: survey-based indicators vs. Google Trends, Ruhr Economic Papers 155, RWI. Accessed November, 24, 2011 in http://bit.ly/1so26rQ.

StatCounter (2014) StatCounter Global Stats: search engine. StatCounter. Accessed July, 01, 2014 in http://bit.ly/1v0s56K.

Soudabeh D, Ruth C, Kelli H, Vanessa D (2014) Novel Data Sources for Women’s Health Research: Mapping Breast Screening Online Information Seeking Through Google Trends, Academic Radiology, (21)9: 1172–1176

Suoy T (2009) Query Indices and a 2008 Downturn: Israeli Data. Bank of Israel: Research Department. Discussion Paper No. 2009.06. Accessed January,15, 2012 in http://bit.ly/Z29izI.

Varian, H (2014) Big Data: New Tricks for Econometrics. Accessed November, 30, 2015 in http://bit.ly/1e2m9V4.

Wllard SD, Nguyen MM (2013) Internet search trends analysis tools can provide real-time data on kidney stone disease in the United States; Urology; 81 (1): 37–42

Xang Z, Fesenmaier DR (2006) Assessing the initial step in the persuasion process: Meta tags on destination marketing websites. Information Technology & Tourism, 8(2): 91–104

Xiang Z, Gretzel U, Fesenmaier DR (2009) Semantic representation of the online tourism domain. Journal of Travel Research, 47(4): 440 – 453

Xang Z, Pan B (2011) Travel queries on cities in the United States: Implications for search engine marketing for tourist destinations. Tourism Management, 32(1): 88–97

Yang AC, Tsai SJ, Huang NE, Peng CK (2011) Association of Internet search trends with suicide death in Taipei City, Taiwan, 2004–2009. Journal of affective disorders, 132(1): 179–184

Downloads

Published

08.01.2024

Issue

Section

Tourism/Hospitality: Research Papers

How to Cite

Similarities and correlation between resident tourist overnights and Google Trends information in Portugal and its tourism regions. (2024). Tourism & Management Studies, 13(3), 15-22. https://tmstudies.net/index.php/ectms/article/view/940

Most read articles by the same author(s)