Abstract
Broadband (BB) communications lie at the heart of any developing information and digital society. Employing the Gompertz model in a time-series study, we analyze the factors that influence the diffusion of fixed and mobile broadband across the OECD countries that have been categorized into five groups based on the stage of innovation, between 1998 and 2015. We find that although the diffusion time is similar for both technologies, the mobile broadband diffusion’s inflection time is asymmetric over the symmetric fixed broadband. The adoption time is almost double compared to the fixed, revealing a strong preference mostly of the developed countries on fixed broadband technology. Moreover, three out of the five innovation categories, in the classification method, the early adopters, early and late majority are really close to Roger’s criteria, aligning with recent literature findings, where countries are clustered into three groups, categorized by their diffusion rates and diffusion speeds.
Similar content being viewed by others
Change history
10 November 2022
Year in issue publication should be 2021
References
Koutroumpis, P. (2019). The economic impact of broadband: Evidence from OECD countries. Technological Forecasting and Social Change, 148. https://doi.org/10.1016/j.techfore.2019.119719.
Lin, M. S., & Wu, F. S. (2013). Identifying the determinants of broadband adoption by diffusion stage in OECD countries. Telecommunications Policy, 37(4–5), 241–251. https://doi.org/10.1016/j.telpol.2012.06.003.
MacVaugh, J., & Schiavone, F. (2010). Limits to the diffusion of innovation: A literature review and integrative model. European Journal of Innovation Management, 13(2), 197–221. https://doi.org/10.1108/14601061011040258.
Majeed, M. T. (2020). Do digital governments foster economic growth in the developing world? An empirical analysis. Netnomics, 21, 1–16. https://doi.org/10.1007/s11066-020-09138-4.
Meade, N., & Islam, T. (2003). Modelling the dependence between the times to international adoption of two related technologies. Technolology Forecasting and Social Change, 70(8), 759–778. https://doi.org/10.1016/S0040-1625(02)00356-6.
Meade, N., & Islam, T. (2006). Modelling and forecasting the diffusion of innovation - A 25-year review. International Journal of Forecasting, 22(3), 519–545. https://doi.org/10.1016/j.ijforecast.2006.01.005.
Meade, N., & Islam, T. (2015). Forecasting in telecommunications and ICT-A review. International Journal of Forecasting, 31(4), 1105–1126. https://doi.org/10.1016/j.ijforecast.2014.09.003.
Rogers, E. (2003). Diffusion of innovations theory. New York Free Press.
Rouvinen, P. (2006). Diffusion of digital mobile telephony: Are developing countries different? Telecommunications Policy, 30(1), 46–63. https://doi.org/10.1016/j.telpol.2005.06.014.
Teklemariam, M. H., & Kwon, Y. (2020). Differentiating mobile broadband policies across diffusion stages: A panel data analysis. Telecommunications Policy, 44(8). https://doi.org/10.1016/j.telpol.2020.102006.
Winsor, C. (1932). The Gompertz curve as a growth curve. Proceedings of the National Academy of Sciences of the United States of America, 18(1), 1–8. https://doi.org/10.1073/pnas.18.1.1.
Wu, F.-S., & Chu, W.-L. (2010). Diffusion models of mobile telephony. Journal of Business Research, 63(5), 497–501. https://doi.org/10.1016/j.jbusres.2009.04.008.
Yamakawa, P., Rees, G., Salas, J. M., & Alva, N. (2013). The diffusion of mobile telephones: An empirical analysis for Peru. Telecommunications Policy, 37(6–7), 594–606. https://doi.org/10.1016/j.telpol.2012.12.010.
Acknowledgments
The authors would like to thank their colleagues in the University of Athens for their fruitful comments.
Author information
Authors and Affiliations
Corresponding author
Appendix
Appendix
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Aravantinos, E., Varoutas, D. A revisit of fixed and mobile broadband diffusion in the OECD: a new classification. Netnomics 22, 71–84 (2021). https://doi.org/10.1007/s11066-021-09145-z
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11066-021-09145-z