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The Determinants of Technology Diffusion: Evidence from the UK Financial Sector

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  • Adrian Gourlay
  • Eric Pentecost

Abstract

We investigate the role of firm‐ and industry‐specific factors in the diffusion of automated teller machines in the UK financial sector. A duration model of technology adoption is employed in the empirical modelling and is applied to an annual panel of adoption histories over the period 1972–97. The main factors affecting the diffusion of new technology are found to be endogenous learning, cumulative learning‐by‐doing effects, firm size, growth and profitability, and price expectations. There is little evidence, however, to support the role of stock effects in the diffusion process. The results are found to be robust across a number of specifications of the baseline hazard function.

Suggested Citation

  • Adrian Gourlay & Eric Pentecost, 2002. "The Determinants of Technology Diffusion: Evidence from the UK Financial Sector," Manchester School, University of Manchester, vol. 70(2), pages 185-203, March.
    • Handle: RePEc:bla:manchs:v:70:y:2002:i:2:p:185-203
    DOI: 10.1111/1467-9957.00291
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    1. Kamalpreet Kaur & Mandeep Kaur, 2020. "Determinants of Diffusion and Adoption of ATM cum Debit Cards in Indian Banking Sector," Global Business Review, International Management Institute, vol. 21(5), pages 1263-1278, October.
    2. Mulu Gebreeyesus, 2015. "Firm adoption of international standards: evidence from the Ethiopian floriculture sector," Agricultural Economics, International Association of Agricultural Economists, vol. 46(S1), pages 139-155, November.
    3. Ullah, Barkat & Wei, Zuobao & Xie, Feixue, 2014. "ISO certification, financial constraints, and firm performance in Latin American and Caribbean countries," Global Finance Journal, Elsevier, vol. 25(3), pages 203-228.
    4. Arghya Ghosh & Munirul Nabin Haque, 2006. "Sequential technology adoption with asymmetric firms," The Journal of International Trade & Economic Development, Taylor & Francis Journals, vol. 15(2), pages 157-172.
    5. Wojciech Szewczyk & Anna Sabadash, 2013. "Macroeconomic Modelling of Public Expenditures on Research and Development in Information and Communication Technologies," JRC Research Reports JRC82943, Joint Research Centre.
    6. José Alberto Bayo-Moriones & Gilberto Carvalho-Vasconcelos & Fernando Lera-López, 2005. "A firm-level analysis of differences between adopters and non-adopters of ICT," ERSA conference papers ersa05p645, European Regional Science Association.
    7. Stefanie Haller & Iulia Siedschlag, 2011. "Determinants of ICT adoption: evidence from firm-level data," Applied Economics, Taylor & Francis Journals, vol. 43(26), pages 3775-3788.
    8. Juan Jung & Gonzalo Gómez-Bengoechea, 2022. "A literature review on firm digitalization: drivers and impacts," Studies on the Spanish Economy eee2022-20, FEDEA.
    9. Tamer Khraisha & Keren Arthur, 2018. "Can we have a general theory of financial innovation processes? A conceptual review," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 4(1), pages 1-27, December.
    10. Hudson, John & Orviska, Marta, 2013. "Firms’ adoption of international standards: One size fits all?," Journal of Policy Modeling, Elsevier, vol. 35(2), pages 289-306.
    11. Bos, Jaap W.B. & Kolari, James W. & van Lamoen, Ryan C.R., 2013. "Competition and innovation: Evidence from financial services," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1590-1601.
    12. Byoung-Min Kim & Richard Widdows & Tansel Yilmazer, 2005. "The determinants of consumers’ adoption of Internet banking," Conference Series ; [Proceedings], Federal Reserve Bank of Boston.
    13. Dahlke, Johannes & Beck, Mathias & Kinne, Jan & Lenz, David & Dehghan, Robert & Wörter, Martin & Ebersberger, Bernd, 2024. "Epidemic effects in the diffusion of emerging digital technologies: evidence from artificial intelligence adoption," Research Policy, Elsevier, vol. 53(2).
    14. Marc Fusaro, 2009. "The rank, stock, order and epidemic effects of technology adoption: an empirical study of bounce protection programs," The Journal of Technology Transfer, Springer, vol. 34(1), pages 24-42, February.
    15. Fuentelsaz, Lucio & Gómez, Jaime & Palomas, Sergio, 2009. "The effects of new technologies on productivity: An intrafirm diffusion-based assessment," Research Policy, Elsevier, vol. 38(7), pages 1172-1180, September.
    16. Yang Liu and Taoyuan Wei, 2016. "Market and Non-market Policies for Renewable Energy Diffusion: A Unifying Framework and Empirical Evidence from Chinas Wind Power Sector," The Energy Journal, International Association for Energy Economics, vol. 0(China Spe).

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