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Segmental new-product diffusion of residential broadband services

Author

Listed:
  • Robertson, Alastair
  • Soopramanien, Didier
  • Fildes, Robert

Abstract

Aggregate models of innovation diffusion do not capitalise on valuable consumer adoption dynamics that may be useful to policy makers and market planners. The non-diffusion choice literature shows quite clearly that these dynamics may indeed be very important factors in the diffusion process. The authors present a segmental broadband diffusion model that is estimated from consumer survey data that measure the effect that household income has on its propensity to adopt this technological product. The results suggest that early broadband adopters are mostly made up from wealthy households and only as time progresses do less well off households adopt. The findings presented in this paper will be important to market planners and policy makers requiring a relatively simple technique that forecasts segmental innovation diffusion.

Suggested Citation

  • Robertson, Alastair & Soopramanien, Didier & Fildes, Robert, 2007. "Segmental new-product diffusion of residential broadband services," Telecommunications Policy, Elsevier, vol. 31(5), pages 265-275, June.
  • Handle: RePEc:eee:telpol:v:31:y:2007:i:5:p:265-275
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    Citations

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    Cited by:

    1. Tony H. Grubesic, 2015. "The Broadband Provision Tensor," Growth and Change, Wiley Blackwell, vol. 46(1), pages 58-80, March.
    2. Guseo, Renato & Guidolin, Mariangela, 2015. "Heterogeneity in diffusion of innovations modelling: A few fundamental types," Technological Forecasting and Social Change, Elsevier, vol. 90(PB), pages 514-524.
    3. Saurabh Panwar & P. K. Kapur & Ompal Singh, 2019. "Modeling Technological Substitution by Incorporating Dynamic Adoption Rate," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 16(01), pages 1-24, February.
    4. Zhang, Jing & Liang, Xiong-jian, 2012. "Promoting green ICT in China: A framework based on innovation system approaches," Telecommunications Policy, Elsevier, vol. 36(10), pages 997-1013.
    5. Levin, Stanford L. & Schmidt, Stephen & Scott, Graham, 2016. "Broadband Adoption: Translating the Digital Divide Literature into Effective Government Policies and Actions," 27th European Regional ITS Conference, Cambridge (UK) 2016 148684, International Telecommunications Society (ITS).
    6. Guseo, Renato, 2016. "Latent heterogeneity effects in modelling individual hazards: A non-proportional approach," Technological Forecasting and Social Change, Elsevier, vol. 105(C), pages 89-93.
    7. Guseo, Renato & Mortarino, Cinzia & Darda, Md Abud, 2015. "Homogeneous and heterogeneous diffusion models: Algerian natural gas production," Technological Forecasting and Social Change, Elsevier, vol. 90(PB), pages 366-378.
    8. Turk, Tomaž & Trkman, Peter, 2012. "Bass model estimates for broadband diffusion in European countries," Technological Forecasting and Social Change, Elsevier, vol. 79(1), pages 85-96.
    9. Darda, Md Abud & Guseo, Renato & Mortarino, Cinzia, 2015. "Nonlinear production path and an alternative reserves estimate for South Asian natural gas," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 654-664.
    10. Guseo, Renato & Schuster, Reinhard, 2021. "Modelling dynamic market potential: Identifying hidden automata networks in the diffusion of pharmaceutical drugs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    11. Meade, Nigel & Islam, Towhidul, 2015. "Forecasting in telecommunications and ICT—A review," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1105-1126.
    12. Sang-Gun Lee & Eui-bang Lee & Chang-Gyu Yang, 2014. "Strategies for ICT product diffusion: the case of the Korean mobile communications market," Service Business, Springer;Pan-Pacific Business Association, vol. 8(1), pages 65-81, March.

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