Abstract
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.
Keywords
- 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.
This is a preview of subscription content, access via your institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
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 University
Bazini E, Elmazi L (2009) ICT influences on marketing mix and building a tourism information system. China USA Bus Rev 8(2):36–45
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 48–58
Breitung JM, Meyer W (1994) Testing for unit roots using panel data: are wages on different bargaining levels cointegrated. Appl Econ 26:353–361
Brida JG, Risso WA (2009) A dynamic panel data study of the German demand for tourism in South Tyrol. Tour Hospitality Res 9(4):305–313
Buhalis D (2003) eTourism: information technology for strategic management. Prentice Hall, London
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 29:609–623
Buhalis D, O’Connor P (2005) Information communication technology revolutionizing tourism. Tour Recreation Res 30:7–16
Choi I (2001) Unit root tests for panel data. J Int Money Finance 20:249–272
Crouch G (1994) The study of international tourism demand: a review of findings. J Travel Res 33(1):12–23
Cunha L (2003) Introdução ao Turismo, 2nd edn. Editorial Verbo, Lisboa
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, Faro
Dickey DA, Fuller WA (1979) Distribution of the estimators for autoregressive time series with a unit root. J Am Stat Assoc 74:427–431
Engle RF, Granger CWJ (1987) Cointegration and error correction: representations, estimation and testing. Econometrica 55:252–276
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):345–359
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 925–932
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 7:3–12
Harris RDF, Tzavalis E (1999) Inference for unit roots in dynamic panels where the time dimension is fixed. J Econ 91:201–226
Holtz-Eakin D, Newey W, Rosen HS (1988) Estimating vector autoregressions with panel data. Econometrica 56(6):1371–1395
Hurlin C, Mignon V (2004) Second generation panel unit root tests, THEMA-CNRS, Universite de Paris X, Mimeo
Im KS, Pesaran MH, Shin Y (2003) Testing for unit roots in heterogenous panels. J Econ 115:53–74
Kao C (1999) Spurious regression and residual-based tests for cointegration in panel data. J Econ 90:1–44
Levin A, Lin CF (1992) Unit root tests in panel data: asymptotic and finite sample properties. Department of Economics, University of California, San Diego
Levin A, Lin C-F, Chu C-SJ (2002) Unit root tests in panel data: asymptotic and finite sample properties. J Econ 108:1–24
Maddala GS, Wu S (1999) A comparative study of unit root tests with panel data and new simple test. Oxford Bull Econ Stat 61:631–652
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: http://www.crt.dk/UK/staff/chm/trends.htm. Data do último acesso: 19 Oct 2011
Matyas L, Sevestre P (eds) (2008) The econometrics of panel data. Springer, Berlin, Third completely new edition
Mavri M, Angelis V (2009) Forecasting the growth of e-Tourism sector: the case study of mediterranean countries. Tourismos Interdiscip J Tour 4(3):113–125
McCoskey S, Kao C (1998) A residual-based test of the null of cointegration in panel data. Econ Rev 17:57–84
O’Connor P (1999) Electronic information distribution in tourism and hospitality. CAB International, Oxford
Paskaleva KA (2010) Developing integrated eTourism services for cultural heritage destinations. Int J Serv Technol Manage 13(3/4):247–262
Pease W, Rowe M, Cooper M (2005) The role of ICT in regional tourism providers. Asia Pac J Econ Bus 9(2):50–85
Pedroni P (2004) Panel cointegration; asymptotic and finite sample properties of pooled time-series tests with applications to the PPP hypothesis. Econ Theory 3:579–625
Poon A (1993) Tourism, technology and competitive strategies. CAB International, Wallingford
Quah D (1994) Exploiting cross-section variation for unit root inference in dynamic data. Econ Lett 44:9–19
Ramos CMQ, Rodrigues PMM, Perna F (2009) Sistemas e Tecnologias de Informação no Sector Turístico. Revista Turismo & Desenvolvimento RT&D 12:21–32
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 Paulo
Sheldon P (1989) Travel industry information systems. In: Witt S, Moutinho L (eds) Tourism marketing and management handbook. Prentice Hall, London, pp 589–592
Sheldon PJ (1997) Tourism information technology. CAB International, Wallingford
Smith R, Fuertes AM (2010) Panel time-series. Cemmap, London
Song H, Witt SF (2000) Tourism demand modelling and forecasting: modern econometric approaches. Pergamon, New York
Song H, Witt SF, Li G (2009) The advanced econometrics of tourism demand. Routledge/Taylor and Francis, New York
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 York
Verbeek M (2004) A guide to modern econometrics of panel data. Wiley, London
Werthner H, Klein S (1999) Information technology and tourism – a challenging relationship. Springer, Vienna
Witt SF, Witt CA (1995) Forecasting tourism demand: a review of empirical research. Int J Forecast 11:447–475
WTO (2001) E-business for tourism – practical guidelines for tourisms destinations and businesses, World Tourism Organization
Xiang Z, Fesenmaier D (2006) Assessing the initial step in the persuasion process: meta tags on destination marketing websites. Inf Technol Tour 8:91–104
Acknowledgements
The authors thank Peter Nijkamp and two anonymous referees for valuable comments and suggestions.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Ramos, C.M.Q., Rodrigues, P.M.M. (2013). The Importance of ICT for Tourism Demand: A Dynamic Panel Data Analysis. In: Matias, Á., Nijkamp, P., Sarmento, M. (eds) Quantitative Methods in Tourism Economics. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-2879-5_6
Download citation
DOI: https://doi.org/10.1007/978-3-7908-2879-5_6
Published:
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-2878-8
Online ISBN: 978-3-7908-2879-5
eBook Packages: Business and EconomicsEconomics and Finance (R0)