, Volume 39, Issue 5, pp 895–918 | Cite as

Impact of ICT access on personal activity space and greenhouse gas production: evidence from Quebec City, Canada

  • Luis F. Miranda-Moreno
  • Naveen Eluru
  • Martin Lee-Gosselin
  • Tyler Kreider


This paper presents an approach to investigating the impact of information and communication technologies (ICTs) on travel behaviour and its environmental effects. The paper focuses on the spatial dispersion of out-of-home activities and travel (activity space) and greenhouse gas emissions (GHGs) at the level of the individual. An original method, combining spatial analysis in a geographic information system with advanced regression techniques, is proposed to explore these potentially complex relationships in the case of access to mobile phones and the internet, while taking into account the influence of socio-economics and built environment factors. The proposed methodology is tested using a 7-day activity-based survey in Quebec City in 2003–2004, a juncture of particular interest because these ICTs had recently crossed the threshold of 40 % (mobile phone) and 60 % (home-based internet) penetration at the time. The study period also largely pre-dates the era of mobile internet access. Among other results, socio-demographic factors were found to significantly affect both ICT access and travel out-comes. The built environment, represented by neighbourhood typologies, also played an important role. However, it was found that after controlling for the self-selection effect, built environment and socio-demographics, those who had a mobile phone available produced 30 % more GHGs during the observed week than those who did not. This higher level of GHG pro-duction was accompanied by a 12 % higher measure of activity dispersion. On the other hand, having internet access at home was associated with lower GHGs (−19 %) and lesser activity dispersion (−25 %). Possibly, mobile phones enable individuals to cover more space and produce more emissions, while the internet provides opportunities to stay at home or avoid motorized travel thus reducing emissions. The estimated effects of having a mobile phone were not only negative but also larger in magnitude from the environmental point of view than those of fixed internet access. However, the results of this study also suggest that access to mobile phones and internet may have substantial and compensatory effects at the individual level that are undetected when using model structures that do not take into account that unobserved factors may influence both ICT choices and travel outcomes.


ICT access Activity spaces Greenhouse emissions Land use Endogeneity 



The work described in this paper was undertaken on data developed from 2000 to 2008 by the PROCESSUS Network. It was supported primarily by the Social Sciences and Humanities Research Council of Canada as the Major Collaborative Research Initiative Access to activities and services in urban Canada: behavioural processes that condition equity and sustainability, GEOIDE, the Canadian Network of Centres of Excellence in geomatics, and the Ministère des transports du Québec. This work was also partially financed by the Fonds de recherche du QuébecNature et technologies, as part of the program Recherche partenariat contribuant réduction et séquestration gaz effet de serre. The authors would like to thank Pierre Rondier (Laval University), who built the relational database for the Québec City Travel and Activity Panel Survey as well as Philippe Barla (Laval University) for his invaluable assistance with the GHG estimation. The insightful suggestions by three anonymous reviewers for improvements to the paper were very appreciated.


  1. Alexander, B., Ettema, D., et al.: Fragmentation of work activity as a multi-dimensional construct and its association with ICT, employment and socio-demographic characteristics. J. Transp. Geogr. 18(1), 55–64 (2010)CrossRefGoogle Scholar
  2. Axhausen, K.W., Scott, D.M., König, A., Jürgens, C.: Locations, commitments and activity spaces, paper presented at survive workshop, Bonn, December 2001, Arbeitbericht Verkehrs-und Raumplanung, 96. IVT, ETH Zürich, Zürich (2001)Google Scholar
  3. Barla, P., Miranda-Moreno, L.F., Lee-Gosselin, M.: Urban travel CO2 emissions and land use: a case study for Quebec City. Transp. Res. D 16, 423–428 (2011)CrossRefGoogle Scholar
  4. Bhat, C.R., Sivakumar, A., Axhausen, K.W.: An analysis of the impact of information and communication technologies on non-maintenance shopping activities. Transp. Res. B 37, 857–881 (2003)CrossRefGoogle Scholar
  5. Bhat, C.B., Eluru, N.: A copula-based approach to accommodate residential self-selection effects in travel behavior modeling. Transp. Res. B 43, 749–765 (2009)CrossRefGoogle Scholar
  6. Buliung, R.N., Kanaroglou, P.S.: Urban form and household activity-travel behaviour. Growth Chang. 37, 174–201 (2006)Google Scholar
  7. Buliung, R.N., Remmel, T.K.: Spatial analysis, open source and activity-travel behaviour research: home-rang and centrographic estimation capabilities of the aspace package. J. Geogr. Syst. 10, 191–216 (2008)CrossRefGoogle Scholar
  8. Buliung, R.N., Roorda, M.J., Remmel, T.K.: Exploring spatial variety in patterns of activity-travel behaviour: initial results from the Toronto travel-activity panel survey (TTAPS). Transportation 35(6), 697–722 (2008)CrossRefGoogle Scholar
  9. Choo, S., Mokhtarian, P.L.: Telecommunications and travel demand and supply: aggregate structural equation models for the US. Transp. Res. A 41, 4–18 (2007)CrossRefGoogle Scholar
  10. Couclelis, H.: From sustainable transportation to sustainable accessibility: can we avoid a new tragedy of the commons? In: Janelle, D.G., Hodge, D.C. (eds.) Information, place and cyberspace, pp. 341–356. Springer, Berlin (2000)Google Scholar
  11. De Graaff, T., Rietveld, P.: Substitution between working at home and out-of-home: the role of ICT and commuting costs. Transp. Res. A 41, 142–160 (2007)Google Scholar
  12. Foss, S., Couclelis, H.: Throwing space back in: a tale of Indian fishermen, ICT and travel behaviour. J. Transp. Geogr. 17, 134–140 (2011)CrossRefGoogle Scholar
  13. Fuchs, C.: The implications of new information and communication technologies for sustainability. Environ. Dev. Sustain. 10, 291–309 (2008)CrossRefGoogle Scholar
  14. Harding C., Patterson, Z., Miranda-Moreno, LF., Zahabi A.: Modeling the effect of land use on activity spaces. Paper presented at the transportation research board (TRB) 91st Annual Meeting, Washington DC (2012)Google Scholar
  15. Kenyon, S., Lyons, G.: Introducing multitasking to the study of travel and ICT: examining its extent and assessing its potential importance. Transp. Res. A 41, 161–175 (2007)Google Scholar
  16. Kenyon, S.: The ‘accessibility diary’: discussing a new methodological approach to understand the impact of Internet use upon personal travel and activity participation. J. Transp. Geogr. 14, 123–134 (2006)CrossRefGoogle Scholar
  17. Kim T., Goulias, K.G.: Cross sectional and longitudinal relationships among information and telecommunication technologies, daily time allocation to activity and travel, and modal split using structural equation modeling. In: 83rd annual transportation research board meeting, Washington DC, 11–15 Jan 2004Google Scholar
  18. Koenig, B.E., Henderson, D.K., Mokhtarian, P.L.: The travel and emission impacts of telecommuting for the state of California telecommuting, pilot project. Transp. Res. C 4, 13–32 (1996)CrossRefGoogle Scholar
  19. Lee-Gosselin, M., Miranda-Moreno, L.: What is different about spontaneous urban activities that were planned with the aid of ICTs? Some early evidence from Québec, Canada. J. Transp. Geogr. 17, 104–114 (2009)CrossRefGoogle Scholar
  20. Lee, J., Wong, D.W.S.: Statistical analysis with arcview GIS. Wiley, New York (2001)Google Scholar
  21. Lenz, B., Nobis, C.: The changing allocation of activities in space and time by the use of ICT-“fragmentation” as a new concept and empirical results. Transp. Res. A 41, 190–204 (2007)Google Scholar
  22. Lyons, G.: The reshaping of activities and mobility through new technologies. J. Transp. Geogr. 17, 81–82 (2009)CrossRefGoogle Scholar
  23. Maddala, G.S.: Limited-dependent and qualitative variables in econometrics. Cambridge University Press, Cambridge (1983)Google Scholar
  24. Manaugh K. El-Geneidy, A.: What makes travel local? Defining and understanding local travel behaviour. World Symposium on Transport & Land Use Research (WSTLUR), Whistler, BC, Canada. J. Transp. Land use (2011) (accepted)Google Scholar
  25. Miranda-Moreno, L., Bettex, L., Zahabi, A., Kreider, T., Barla, P.: A simultaneous modeling approach to evaluate the endogenous influence of urban form and public transit accessibility on distance travelled. Transp. Res. Rec. 2255, 100–109 (2011)CrossRefGoogle Scholar
  26. Mokhtarian, P.L., Salomon, I.: Modeling the choice of telecommunications: a case of the preferred impossible alternative. Environ. Plan. 28, 1859–1876 (1996)CrossRefGoogle Scholar
  27. Mokhtarian, P., Salomon, I.: Emerging travel patterns: do telecommunications make a difference? In: Mahmassani, H. (ed.) In perpetual motion: travel behaviour research opportunities and application challenges. Pergamon, Oxford (2002)Google Scholar
  28. Nobis, C., Lenz, B.: Changes in transport behavior by the fragmentation of activities. Transp. Res. Rec. 1894, 249–257 (2004)CrossRefGoogle Scholar
  29. Nobis, C., Lenz, B.: Communication and mobility behaviour—a trend and panel analysis of the correlation between mobile phone use and mobility. J. Transp. Geogr. 17, 93–103 (2009)CrossRefGoogle Scholar
  30. OECD: Greener and smarter: ICTs, the environment and climate change, organisation for economic co-operation and development (OECD), report ( Accessed 05 Nov 2011 (2010)
  31. Rai, R.K., Balmer, M., Rieser, M., Vaze, V.S., Schönfelder, S., Axhausen, K.W.: Capturing human activity spaces, new geometries. Transp. Res. Rec. 2021, 70–80 (2007)CrossRefGoogle Scholar
  32. Roy, A.D.: Some thoughts on the distribution of earnings. Oxf. Econ. Pap. 3(2), 135–146 (1951)Google Scholar
  33. Roy P., Martínez, A.J., Miscione, G. Zuidgeest, M.H.P., van Maarseveen M.F.A.M.: Using social network analysis to profile people based on their e-communication and travel balance. J. Transp. Geogr. (2012) (in press)Google Scholar
  34. Salomon, I.: Telecommunications and travel. J. Transp. Econ. Policy 19(3), 219–235 (1985)Google Scholar
  35. Sasaki, K., Nishii, K.: Measurement of intention to travel: considering the effect of telecommunications on trips. Transp. Res. C 18, 36–44 (2003)CrossRefGoogle Scholar
  36. Schönfelder, S., Axhausen, K.W.: Activity spaces: measures of social exclusion? Transp. Policy 10(4), 273–286 (2003)CrossRefGoogle Scholar
  37. Srinivasan, K., Athuru, S.R.: Modeling interaction between internet communication and travel activities: evidence from Bay Area, California, travel survey 2000. J. Transp. Res. Rec 1894, 230–240 (2004)CrossRefGoogle Scholar
  38. Srinivasan, K., Raghavender, P.N.: Impact of mobile phones on travel: empirical analysis of activity-chaining, ride-sharing and virtual shopping. J. Transp. Res. Board 1977, 258–267 (2006)CrossRefGoogle Scholar
  39. Wang, D., Law, F.: Impacts of information and communication technologies (ICT) on time use and travel behavior: a structural equations analysis. Transportation 34(4), 513–527 (2007)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC. 2012

Authors and Affiliations

  • Luis F. Miranda-Moreno
    • 1
  • Naveen Eluru
    • 1
  • Martin Lee-Gosselin
    • 2
  • Tyler Kreider
    • 1
  1. 1.Department of Civil Engineering and Applied MechanicsMcGill UniversityMontrealCanada
  2. 2.École Supérieure d’Aménagement du Territoire et de Développement Régional, and Centre de Recherche en Aménagement et DéveloppementUniversité LavalQuebec CityCanada

Personalised recommendations