The Importance of ICT for Tourism Demand: A Dynamic Panel Data Analysis

  • Célia M. Q. Ramos
  • Paulo M. M. Rodrigues


The complementary nature of tourism products requires information to be easily accessible from different places around the globe. Electronic distribution in tourism has facilitated the sharing, communication and booking of products and has contributed to the increase of tourism demand as well as to the emergence of a new type of traveller: one who seeks more experiences and sophistication in his travels. The Internet is of increasing importance as a result of the sharp growth in the number of online reservations observed over recent years. Hence, current tourism demand analysis cannot neglect electronic tourism, so that in addition to typically used determinants, variables that represent the impact of the technological environment on the tourism activity also need to be considered. In this paper, using dynamic panel data models evidence is found that the Internet has encouraged the increase of tourism demand and may in fact be one of its determinants.


Panel Data Unit Root Test Cointegration Test Panel Data Model Panel Unit Root Test 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors thank Peter Nijkamp and two anonymous referees for valuable comments and suggestions.


  1. Baltagi BH, Kao C (2000) Nonstationary panels, cointegration in panels and dynamic panels: a survey, Center for policy research working papers 16, Center for Policy Research, Maxwell School, Syracuse UniversityGoogle Scholar
  2. Bazini E, Elmazi L (2009) ICT influences on marketing mix and building a tourism information system. China USA Bus Rev 8(2):36–45Google Scholar
  3. Bloch M, Segev A (1997) The impact of electronic commerce on the travel industry – an analysis methodology and case study. In: Proceedings of the thirtieth annual Hawaii international conference on system sciences, vol 4, IEEE, Maui, Hawaii, pp 48–58Google Scholar
  4. Breitung JM, Meyer W (1994) Testing for unit roots using panel data: are wages on different bargaining levels cointegrated. Appl Econ 26:353–361CrossRefGoogle Scholar
  5. Brida JG, Risso WA (2009) A dynamic panel data study of the German demand for tourism in South Tyrol. Tour Hospitality Res 9(4):305–313CrossRefGoogle Scholar
  6. Buhalis D (2003) eTourism: information technology for strategic management. Prentice Hall, LondonGoogle Scholar
  7. 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. Tour Manage 29:609–623CrossRefGoogle Scholar
  8. Buhalis D, O’Connor P (2005) Information communication technology revolutionizing tourism. Tour Recreation Res 30:7–16Google Scholar
  9. Choi I (2001) Unit root tests for panel data. J Int Money Finance 20:249–272CrossRefGoogle Scholar
  10. Crouch G (1994) The study of international tourism demand: a review of findings. J Travel Res 33(1):12–23CrossRefGoogle Scholar
  11. Cunha L (2003) Introdução ao Turismo, 2nd edn. Editorial Verbo, LisboaGoogle Scholar
  12. Daniel ACM, Rodrigues PMM (2005) Modelling and forecasting tourism demand in Portugal: what was done and what can we do? In: Recent developments in tourism research conference, FaroGoogle Scholar
  13. Dickey DA, Fuller WA (1979) Distribution of the estimators for autoregressive time series with a unit root. J Am Stat Assoc 74:427–431Google Scholar
  14. Engle RF, Granger CWJ (1987) Cointegration and error correction: representations, estimation and testing. Econometrica 55:252–276Google Scholar
  15. Fleischer A, Felsenstein D (2004) Face-to-face or cyberspace? Choosing the Internet as an intermediary in the Israeli travel market. Tour Econ 10(3):345–359CrossRefGoogle Scholar
  16. Garbin Praničević D (2006) Application of information and communication technologies (ICT) in tourism. An enterprise Odyssey: integration or disintegration (Proceedings), Galetić, Lovorka (ur.). Zagreb: University of Zagreb, Faculty of Economics and Business, pp 925–932Google Scholar
  17. Gretzel U, Mitsche N, Hwang Y, Fesenmaier D (2004) Tell me who you are and i will tell you where to go: use of travel personalities in destination recommendation systems. Inf Technol Tour 7:3–12Google Scholar
  18. Harris RDF, Tzavalis E (1999) Inference for unit roots in dynamic panels where the time dimension is fixed. J Econ 91:201–226Google Scholar
  19. Holtz-Eakin D, Newey W, Rosen HS (1988) Estimating vector autoregressions with panel data. Econometrica 56(6):1371–1395CrossRefGoogle Scholar
  20. Hurlin C, Mignon V (2004) Second generation panel unit root tests, THEMA-CNRS, Universite de Paris X, MimeoGoogle Scholar
  21. Im KS, Pesaran MH, Shin Y (2003) Testing for unit roots in heterogenous panels. J Econ 115:53–74Google Scholar
  22. Kao C (1999) Spurious regression and residual-based tests for cointegration in panel data. J Econ 90:1–44Google Scholar
  23. Levin A, Lin CF (1992) Unit root tests in panel data: asymptotic and finite sample properties. Department of Economics, University of California, San DiegoGoogle Scholar
  24. Levin A, Lin C-F, Chu C-SJ (2002) Unit root tests in panel data: asymptotic and finite sample properties. J Econ 108:1–24Google Scholar
  25. Maddala GS, Wu S (1999) A comparative study of unit root tests with panel data and new simple test. Oxford Bull Econ Stat 61:631–652CrossRefGoogle Scholar
  26. Marcussen C (2009) Trends in European Internet distribution of travel and tourism services, Centre for Regional and Tourism Research, Denmark (on-line), Disponível em URL: Data do último acesso: 19 Oct 2011
  27. Matyas L, Sevestre P (eds) (2008) The econometrics of panel data. Springer, Berlin, Third completely new editionGoogle Scholar
  28. Mavri M, Angelis V (2009) Forecasting the growth of e-Tourism sector: the case study of mediterranean countries. Tourismos Interdiscip J Tour 4(3):113–125Google Scholar
  29. McCoskey S, Kao C (1998) A residual-based test of the null of cointegration in panel data. Econ Rev 17:57–84CrossRefGoogle Scholar
  30. O’Connor P (1999) Electronic information distribution in tourism and hospitality. CAB International, OxfordGoogle Scholar
  31. Paskaleva KA (2010) Developing integrated eTourism services for cultural heritage destinations. Int J Serv Technol Manage 13(3/4):247–262CrossRefGoogle Scholar
  32. Pease W, Rowe M, Cooper M (2005) The role of ICT in regional tourism providers. Asia Pac J Econ Bus 9(2):50–85Google Scholar
  33. Pedroni P (2004) Panel cointegration; asymptotic and finite sample properties of pooled time-series tests with applications to the PPP hypothesis. Econ Theory 3:579–625Google Scholar
  34. Poon A (1993) Tourism, technology and competitive strategies. CAB International, WallingfordGoogle Scholar
  35. Quah D (1994) Exploiting cross-section variation for unit root inference in dynamic data. Econ Lett 44:9–19CrossRefGoogle Scholar
  36. Ramos CMQ, Rodrigues PMM, Perna F (2009) Sistemas e Tecnologias de Informação no Sector Turístico. Revista Turismo & Desenvolvimento RT&D 12:21–32Google Scholar
  37. Scarpelli MC (2010) Hysteris nas exportações brasileiras: uma análise de cointegração com dados em painel, Tese de Mestrado, Faculdade de Economia, Administração e Contabilidade de Ribeirão Preto da Universidade de São PauloGoogle Scholar
  38. Sheldon P (1989) Travel industry information systems. In: Witt S, Moutinho L (eds) Tourism marketing and management handbook. Prentice Hall, London, pp 589–592Google Scholar
  39. Sheldon PJ (1997) Tourism information technology. CAB International, WallingfordGoogle Scholar
  40. Smith R, Fuertes AM (2010) Panel time-series. Cemmap, LondonGoogle Scholar
  41. Song H, Witt SF (2000) Tourism demand modelling and forecasting: modern econometric approaches. Pergamon, New YorkGoogle Scholar
  42. Song H, Witt SF, Li G (2009) The advanced econometrics of tourism demand. Routledge/Taylor and Francis, New YorkGoogle Scholar
  43. Uysal M (1998) The determinants of tourism demand: a theoretical perspective. In: Ioannides D, Debbage KG (eds) The economic geography of the tourist industry: a supply-side analysis. Routledge, New YorkGoogle Scholar
  44. Verbeek M (2004) A guide to modern econometrics of panel data. Wiley, LondonGoogle Scholar
  45. Werthner H, Klein S (1999) Information technology and tourism – a challenging relationship. Springer, ViennaCrossRefGoogle Scholar
  46. Witt SF, Witt CA (1995) Forecasting tourism demand: a review of empirical research. Int J Forecast 11:447–475CrossRefGoogle Scholar
  47. WTO (2001) E-business for tourism – practical guidelines for tourisms destinations and businesses, World Tourism OrganizationGoogle Scholar
  48. Xiang Z, Fesenmaier D (2006) Assessing the initial step in the persuasion process: meta tags on destination marketing websites. Inf Technol Tour 8:91–104Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Célia M. Q. Ramos
    • 1
  • Paulo M. M. Rodrigues
    • 2
    • 3
  1. 1.ESGHT – Universidade do AlgarveFaroPortugal
  2. 2.Banco de PortugalLisbonPortugal
  3. 3.Colégio de CampolideUniversidade Nova de LisboaLisboaPortugal

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