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Understanding the drivers of broadband adoption: the case of rural and remote Scotland

Author

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  • S Howick

    (University of Strathclyde)

  • J Whalley

    (University of Strathclyde)

Abstract

Broadband has been described as a transforming technology and is now widely available in many developed countries. However, broadband availability is not the same as broadband adoption. If the socio-economic benefits of broadband are to be realized, then adoption needs to be both understood and encouraged. This is particularly important in rural and remote areas. This paper explores the factors that drive broadband adoption in one particular rural and remote area; rural and remote Scotland. A causal model and a quantitative simulation model are developed indicating how the various drivers of adoption interact with one another. Both models show that past policy initiatives have impacted on the rate of adoption. However, the greatest impact could be achieved if future policy initiatives target those people who show no interest in adopting broadband. The paper concludes by suggesting that this work has implications for rural and remote areas all around the world.

Suggested Citation

  • S Howick & J Whalley, 2008. "Understanding the drivers of broadband adoption: the case of rural and remote Scotland," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(10), pages 1299-1311, October.
    • Handle: RePEc:pal:jorsoc:v:59:y:2008:i:10:d:10.1057_palgrave.jors.2602486
    DOI: 10.1057/palgrave.jors.2602486
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    References listed on IDEAS

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    Cited by:

    1. Z Irani & Y K Dwivedi & M D Williams, 2009. "Understanding consumer adoption of broadband: an extension of the technology acceptance model," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(10), pages 1322-1334, October.
    2. Oliver Falck & Siegfried Schönherr, 2016. "An Economic Reform Agenda for Croatia: a comprehensive economic reform package prepared for the Croatian Statehood Foundation," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 70.
    3. 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.
    4. Claudio Agostini & Manuel Willington, 2010. "Radiografía de la Brecha Digital en Chile: ¿Se Justifica la Intervención del Estado?," ILADES-UAH Working Papers inv245, Universidad Alberto Hurtado/School of Economics and Business.
    5. M Günther & C Stummer & L M Wakolbinger & M Wildpaner, 2011. "An agent-based simulation approach for the new product diffusion of a novel biomass fuel," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(1), pages 12-20, January.
    6. Amanda Davies, 2021. "COVID-19 and ICT-Supported Remote Working: Opportunities for Rural Economies," World, MDPI, vol. 2(1), pages 1-14, March.
    7. Nirupam Mukhopadhyay & Narayan Chandra Nayak, 2024. "Catalyzing change: a cross-country perspective on diffusion patterns of green innovation," Environment Systems and Decisions, Springer, vol. 44(4), pages 853-871, December.
    8. Ovando, Catalina & Pérez, Jorge & Moral, Antolín, 2015. "LTE techno-economic assessment: The case of rural areas in Spain," Telecommunications Policy, Elsevier, vol. 39(3), pages 269-283.
    9. Mingers, John & White, Leroy, 2010. "A review of the recent contribution of systems thinking to operational research and management science," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1147-1161, December.

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