Abstract
Close to one-fifth of adults living in advanced societies do not use the Internet. Unfortunately, they are also those who might be more likely to benefit from the support of social services. Understanding who are these analog citizens is therefore a crucial task for any government. In this paper we develop a statistical model to capture the demographic profile of Internet usage. We formally consider spatial auto-correlation in order to properly measure the relative impact of age, education, income, gender and geography on the probability of Internet usage. Based on close to 30,000 observations we observe that age is by far the most important demographic determinant of Internet usage. Geography exhibits a significant impact, both complex and completely overshadowed by the age/education/income triad. We then examine three groups in more detail: seniors, dropouts/homeless living in cities, and members of First Nations living in remote communities.
Similar content being viewed by others
Notes
Estimates available on request.
References
Adler, R. (2006). Older Americans, broadband and the future of the net. Santa Clara: SeniorNet.
Agarwal, R., Animesh, A., & Prasad, K. (2005). Social interactions and the ‘Digital Divide’: Explaining regional variations in Internet use, Working paper RHS-06-024. Robert H. Smith School of Business, University of Maryland.
Agarwal, R., Animesh, A., & Prasad, K. (2009). Social interactions and the ‘Digital Divide’: explaining regional variations in Internet use. Research Note, Information Systems Research, 20(2), 277–294.
Alpeyev, P., & Yoshinori, E. (2010). The iPad leads Apple to the elderly, Bloomberg Business Week, 12 Aug 2010.
Atkin, D. J., Jeffres, L. W., & Neuendorf, K. A. (1998). Understanding Internet adoption as telecommunications behavior. Journal of Broadcasting and Media, 42(4), 475–490.
Bergadaà, M., et Hebali M. J. (2001). Attitudes des seniors à l’égard d’Internet. Proceedings of the Marketing and Consumer Behavior Conference, Lalonde-les-Maures (France).
Caradec, V. (1999). Vieillissement et usage des technologies. Une perspective identitaire et relationnelle. Communication et personnes âgées, 17(96), 45–96.
Carstensen, L. L., & Mikels, J. A. (2005). At the intersection of emotion and cognition—Aging and the positivity effect. Current Directions in Psycological Science, 14(3), 117–121.
Colin, C., & Kerjosse, R. (2000). Handicaps-Incapacités-Dépendance. Premiers travaux d’exploitation de l’enquête HID. Montpellier: Proceedings.
Collins, J. L., & Wellman, B. (2010). Small town in the Internet society: Chapleau is no longer an Island. American Behavioral Scientist, 53(9), 1344–1366.
CRTC (2013). Communication Monitoring 2013.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–339.
Dugdale, A., Daly, A., Papandrea, F., & Maley, M. (2005). Accessing e-government: Challenges for citizens and organizations. International Review of Administrative Sciences, 71(1), 109–118.
Grubesic, TH. (2002). Spatial dimensions of Internet activity. Telecommunications Policy, 26, 363–387.
Héritier, A. (2003). Composite democracy in Europe: the role of transparency and access to information. Journal of European Public Policy, 10(5), 814–833.
Hale, T., Cotton, SR., Drentea, P., & Goldner, M. (2010). Rural-urban differences in general and health-related Internet use. American Behavioral Scientist, 53(9), 1304–1325.
Horrigan, J., Rainie, L., Allen, K., Boyce, A., Madden, M., & O’Grady, E. (2003). The ever-shifting Internet population: A new look at Internet access and the digital divide, Pew Internet & American Life Project.
ITU (2009a), Information Society Statistical Profiles 2009—Americas.
ITU (2009b), Information Society Statistical Profiles 2009—Europe.
Jayroe, T. J., & Wolfram, D. (2012). Internet searching, tablet technology and older adults. Proceedings of ASIST (Baltimore), 49(1), 1–3.
King, W. R., & He, J. (2006). A meta-analysis of the technology acceptance model. Information & Management, 43, 740–755.
Lederer, A. L., Maupin, D. J., Sena, M. P., & Zhuang, Y. (2000). The technology acceptance model and the World Wide Web. Decision Support Systems, 29, 269–282.
Marsh, L., & David R. C. (2002). Spline regression models, SAGE University Paper. Series: Quantitative applications in the social sciences, vol 137.
McLeman, Robert, Noraj Foy & Kristin Clark (2010). Adaptive capacity-building and sustainable development in Canadian rural and remote communities: The role of information and communication technologies. Unpublished SSHRC Grant Report.
Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1), 17–23.
OECD. (2000). Literacy in the information age: Final report of the international adult literacy survey.
Peslak, A. (2004). An analysis of regional and demographic differences in United States Internet usage. First Monday, 9(3).
Porter, C. E., & Donthu, N. (2006). Using the technology acceptance model to explain how attitudes determine Internet usage: The role of perceived access barriers and demographics. Journal of Business Research, 59, 999–1007.
Rice, E., Monro, W., Barman-Adhikari, A., & Young, S. D. (2010). Internet use, social networking, and HIV/AIDS risk for homeless adolescents. Journal of Adolescent Health, 47(6), 610–613.
Rogers, E. M. (1995). Diffusion of innovations (4th ed.). New York: Free Press.
Rosen, L. D., & Weil, M. M. (1995). Adult and teenage use of consumer, business, and entertainment technology: Potholes on the information superhighway? Journal of Consumers Affairs, 29(1), 55–84.
Wilkelstein, J. A., & Cortez E. M. (2010). How and Why public libraries can, should and do facilitate the use of the Internet by the homeless: a look at the programs. Barriers and political climate, Communication presented at BOBCATSSS, Parma (Italy)
Zeithaml, V. A., & Gilly, M. C. (1987). Characteristics affecting the acceptance of retailing technologies: A comparison of elderly and nonelderly consumers. Journal of Retailing, 63(1), 49–68.
Acknowledgments
This research has been made possible in part by a grant from APSI (Québec). We would like to thank CEFRIO and SOM for graciously making precious data available to our scrutiny. We would also wish to thank Mrs Thérèse Grenier, head of the LaSarre’s Community Futures Development Corporation for her invaluable assistance.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Gauvin, S., Granger, K. & Lorthiois, M. Analog citizens. Electron Commer Res 15, 365–386 (2015). https://doi.org/10.1007/s10660-015-9185-4
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10660-015-9185-4