IDEAS home Printed from https://ideas.repec.org/a/taf/ecinnt/v19y2010i4p325-347.html
   My bibliography  Save this article

Innovative cardiological technologies: a model of technology adoption, diffusion and competition

Author

Listed:
  • Thomas Grebel
  • Tom Wilfer

Abstract

Technology diffusion of medical innovations is a complex evolutionary process. The specificities on the demand as well as on the supply side have a crucial impact on their diffusion paths. This paper aims to investigate the diffusion process of two competing innovative technologies in the health care sector. The case of percutaneous aortic valve replacement in heart medicine serves as an example. A simple model illustrates the decision-making process of adopters and suppliers that shape the evolution of a new market. Thereby, network externalities and individual learning bias the market outcome such as increasing returns to adoption and may lead to technological 'lock-ins'.

Suggested Citation

  • Thomas Grebel & Tom Wilfer, 2010. "Innovative cardiological technologies: a model of technology adoption, diffusion and competition," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 19(4), pages 325-347.
    • Handle: RePEc:taf:ecinnt:v:19:y:2010:i:4:p:325-347
    DOI: 10.1080/10438590802482019
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/10438590802482019
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/10438590802482019?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jovanovic, Boyan & Nyarko, Yaw, 1996. "Learning by Doing and the Choice of Technology," Econometrica, Econometric Society, vol. 64(6), pages 1299-1310, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Thomas Grebel, 2011. "Innovation and Health," Books, Edward Elgar Publishing, number 14375.
    2. Spyros Arvanitis & Euripidis N. Loukis, 2014. "Investigating the effects of ICT on innovation and performance of European hospitals," KOF Working papers 14-366, KOF Swiss Economic Institute, ETH Zurich.
    3. Barros Pedro Pita & Martinez-Giralt Xavier, 2015. "Technological Adoption in Health Care – The Role of Payment Systems," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 15(2), pages 709-745, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Maria Minniti & William Bygrave, 2001. "A Dynamic Model of Entrepreneurial Learning," Entrepreneurship Theory and Practice, , vol. 25(3), pages 5-16, April.
    2. Fofack, Hippolyte, 2008. "Technology trap and poverty trap in Sub-Saharan Africa," Policy Research Working Paper Series 4582, The World Bank.
    3. E. Young Song, 2005. "Temporary Protection and Technology Choice under the Learning Curve," Review of International Economics, Wiley Blackwell, vol. 13(2), pages 391-396, May.
    4. Boyan Jovanovic, 2009. "When should firms invest in old capital?," International Journal of Economic Theory, The International Society for Economic Theory, vol. 5(1), pages 107-123, March.
    5. Chen, Cheng & Senga, Tatsuro & Sun, Chang & Zhang, Hongyong, 2023. "Uncertainty, imperfect information, and expectation formation over the firm’s life cycle," Journal of Monetary Economics, Elsevier, vol. 140(C), pages 60-77.
    6. Maurice Schiff & Yanling Wang, 2010. "North-South Technology Spillovers: The Relative Impact of Openness and Foreign R&D," International Economic Journal, Taylor & Francis Journals, vol. 24(2), pages 197-207.
    7. Marconi, G. & de Grip, A., 2014. "Education and growth with learning by doing," ROA Research Memorandum 010, Maastricht University, Research Centre for Education and the Labour Market (ROA).
    8. Illoong Kwon, 2005. "Threat of Dismissal: Incentive or Sorting?," Journal of Labor Economics, University of Chicago Press, vol. 23(4), pages 797-838, October.
    9. Boerner, Lars & Severgnini, Battista, 2015. "Time for growth," LSE Research Online Documents on Economics 64495, London School of Economics and Political Science, LSE Library.
    10. Cujean, Julien & Bustamante, Maria Cecilia & Frésard, Laurent, 2019. "Knowledge Cycles and Corporate Investment," CEPR Discussion Papers 14152, C.E.P.R. Discussion Papers.
    11. Schaling, Eric & Eijffinger, Sylvester & Tesfaselassie, Mewael, 2004. "Heterogenous information about the term structure, least-squares learning and optimal rules for inflation targeting," Research Discussion Papers 23/2004, Bank of Finland.
    12. Moreno-Galbis, Eva, 2012. "The impact of TFP growth on the unemployment rate: Does on-the-job training matter?," European Economic Review, Elsevier, vol. 56(8), pages 1692-1713.
    13. Canton, Erik J. F. & de Groot, Henri L. F. & Nahuis, Richard, 2002. "Vested interests, population ageing and technology adoption," European Journal of Political Economy, Elsevier, vol. 18(4), pages 631-652, November.
    14. Mateos-Planas, Xavier, 2000. "Schooling and distortions in a vintage capital model," Discussion Paper Series In Economics And Econometrics 30, Economics Division, School of Social Sciences, University of Southampton.
    15. Toshihiko Mukoyama & Latchezar Popov, 2014. "The Political Economy of Entry Barriers," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 17(3), pages 383-416, July.
    16. Schaling, E., 2003. "Learning, Inflation Reduction and Optimal Monetary Policy," Discussion Paper 2003-74, Tilburg University, Center for Economic Research.
    17. Boyan Jovanovic & Sai Ma, 2023. "Growth through learning," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 50, pages 211-234, October.
    18. Zohal Hessami, 2016. "How Do Voters React to Complex Choices in a Direct Democracy? Evidence from Switzerland," Kyklos, Wiley Blackwell, vol. 69(2), pages 263-293, May.
    19. Ben Klemens, 2021. "Attributing Value to Patents and Trademarks in Complex Production Chains," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 12(2), pages 842-875, June.
    20. Rema Hanna & Sendhi Mullainathan & Josh Schwartstein, 2012. "Learning Through Noticing: Theory and Experimental Evidence in Farming," CID Working Papers 245, Center for International Development at Harvard University.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:ecinnt:v:19:y:2010:i:4:p:325-347. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/GEIN20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.