IDEAS home Printed from https://ideas.repec.org/p/aal/abbswp/00-6.html
   My bibliography  Save this paper

Technological Diffusion Patterns and their Effects on Industrial Dynamics

Author

Listed:
  • Machiel van Dijk
  • Önder Nomaler

Abstract

By focussing on cumulativeness and spillover effects of technological knowledge, theories on technological regimes are predominantly supply side oriented in explaining industrial dynamics. This paper introduces demand side considerations as an additional explanation for industrial dynamics. Given variations in consumer preferences over quality and network sizes of technologies, and different degrees of compatibility between succeeding technologies, we investigate how the resulting differences in the timing and frequency of new technology adoptions effect the industrial dynamics. The simulation results of the model indeed suggest a relationship between different patterns of new technology adoptions and the dynamics of the firm population.

Suggested Citation

  • Machiel van Dijk & Önder Nomaler, 2000. "Technological Diffusion Patterns and their Effects on Industrial Dynamics," DRUID Working Papers 00-6, DRUID, Copenhagen Business School, Department of Industrial Economics and Strategy/Aalborg University, Department of Business Studies.
    • Handle: RePEc:aal:abbswp:00-6
    as

    Download full text from publisher

    File URL: https://wp.druid.dk/wp/20000006.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Silverberg, Gerald & Lehnert, Doris, 1993. "Long waves and 'evolutionary chaos' in a simple Schumpeterian model of embodied technical change," Structural Change and Economic Dynamics, Elsevier, vol. 4(1), pages 9-37, June.
    2. Evans, David S, 1987. "The Relationship between Firm Growth, Size, and Age: Estimates for 100 Manufacturing Industries," Journal of Industrial Economics, Wiley Blackwell, vol. 35(4), pages 567-581, June.
    3. Evans, David S, 1987. "Tests of Alternative Theories of Firm Growth," Journal of Political Economy, University of Chicago Press, vol. 95(4), pages 657-674, August.
    4. Geroski, Paul A, 1999. "The Growth of Firms in Theory and in Practice," CEPR Discussion Papers 2092, C.E.P.R. Discussion Papers.
    5. Malerba, Franco & Orsenigo, Luigi, 1996. "Schumpeterian patterns of innovation are technology-specific," Research Policy, Elsevier, vol. 25(3), pages 451-478, May.
    6. Silverberg, Gerald & Verspagen, Bart, 1994. "Collective Learning, Innovation and Growth in a Boundedly Rational, Evolutionary World," Journal of Evolutionary Economics, Springer, vol. 4(3), pages 207-226, September.
    7. Jovanovic, Boyan, 1982. "Selection and the Evolution of Industry," Econometrica, Econometric Society, vol. 50(3), pages 649-670, May.
    8. Shy, Oz, 1996. "Technology revolutions in the presence of network externalities," International Journal of Industrial Organization, Elsevier, vol. 14(6), pages 785-800, October.
    9. Breschi, Stefano & Malerba, Franco & Orsenigo, Luigi, 2000. "Technological Regimes and Schumpeterian Patterns of Innovation," Economic Journal, Royal Economic Society, vol. 110(463), pages 388-410, April.
    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. Alex Coad, 2007. "Firm Growth: a Survey," Post-Print halshs-00155762, HAL.
    2. Coad, Alex, 2007. "Testing the principle of `growth of the fitter': The relationship between profits and firm growth," Structural Change and Economic Dynamics, Elsevier, vol. 18(3), pages 370-386, September.

    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. Dosi, Giovanni & Nelson, Richard R., 2010. "Technical Change and Industrial Dynamics as Evolutionary Processes," Handbook of the Economics of Innovation, in: Bronwyn H. Hall & Nathan Rosenberg (ed.), Handbook of the Economics of Innovation, edition 1, volume 1, chapter 0, pages 51-127, Elsevier.
    2. Marco Guerzoni & Luigi Riso & Marco Vivarelli, 2025. "Was Robert Gibrat right? A test based on the graphical model methodology," Small Business Economics, Springer, vol. 64(2), pages 475-488, February.
    3. Giulio Bottazzi & Angelo Secchi, 2006. "Explaining the distribution of firm growth rates," RAND Journal of Economics, RAND Corporation, vol. 37(2), pages 235-256, June.
    4. Cefis, Elena & Ciccarelli, Matteo & Orsenigo, Luigi, 2007. "Testing Gibrat's legacy: A Bayesian approach to study the growth of firms," Structural Change and Economic Dynamics, Elsevier, vol. 18(3), pages 348-369, September.
    5. Daria Ciriaci & Pietro Moncada-Paternò-Castello & Peter Voigt, 2016. "Innovation and job creation: a sustainable relation?," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 6(2), pages 189-213, August.
    6. Michael Pfaffermayr, 2007. "Firm Growth Under Sample Selection: Conditional σ-Convergence in Firm Size?," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 31(4), pages 303-328, December.
    7. Emmanuelle Fauchart & Max Keilbach, 2009. "Testing a model of exploration and exploitation as innovation strategies," Small Business Economics, Springer, vol. 33(3), pages 257-272, October.
    8. Kim, Jungho & Lee, Chang-Yang, 2016. "Technological regimes and firm survival," Research Policy, Elsevier, vol. 45(1), pages 232-243.
    9. Canarella, Giorgio & Miller, Stephen M., 2018. "The determinants of growth in the U.S. information and communication technology (ICT) industry: A firm-level analysis," Economic Modelling, Elsevier, vol. 70(C), pages 259-271.
    10. Lee, Chang-Yang, 2010. "A theory of firm growth: Learning capability, knowledge threshold, and patterns of growth," Research Policy, Elsevier, vol. 39(2), pages 278-289, March.
    11. Pei-Chou Lin & Deng-Shing Huang, 2008. "Technological Regimes and Firm Survival: Evidence Across Sectors and Over Time," Small Business Economics, Springer, vol. 30(2), pages 175-186, February.
    12. Pei-Chou Lin & Deng-Shing Huang, 2006. "Technological Regimes and Firm Survival: Evidence across Sectors and over Time," IEAS Working Paper : academic research 06-A012, Institute of Economics, Academia Sinica, Taipei, Taiwan.
    13. Oznur Ozdamar & Eleftherios Giovanis & Sahizer Samuk, 2020. "State business relations and the dynamics of job flows in Egypt and Turkey," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 10(4), pages 519-558, December.
    14. Quader, Syed Manzur, 2017. "Differential effect of liquidity constraints on firm growth," Review of Financial Economics, Elsevier, vol. 32(C), pages 20-29.
    15. Bruno Cassiman & Masako Ueda, 2006. "Optimal Project Rejection and New Firm Start-ups," Management Science, INFORMS, vol. 52(2), pages 262-275, February.
    16. Wright, Mark, 2004. "Firm Size Dynamics in the Aggregate Economy," Santa Cruz Department of Economics, Working Paper Series qt4rs4202s, Department of Economics, UC Santa Cruz.
    17. Sakai, Koji & Uesugi, Iichiro & Watanabe, Tsutomu, 2010. "Firm age and the evolution of borrowing costs: Evidence from Japanese small firms," Journal of Banking & Finance, Elsevier, vol. 34(8), pages 1970-1981, August.
    18. F. Voulgaris & G. Agiomirgianakis & T. Papadogonas, 2015. "Job creation and job destruction in economic crisis at firm level: the case of Greek manufacturing sectors," International Economics and Economic Policy, Springer, vol. 12(1), pages 21-39, March.
    19. Gavin Reid & Zhibin Xu, 2012. "Generalising Gibrat: using Chinese evidence founded on fieldwork," Small Business Economics, Springer, vol. 39(4), pages 1017-1028, November.
    20. Emiliano Santoro, 2006. "Macroeconomic fluctuations and the firms' rate of growth distribution: evidence from UK and US quoted companies," Department of Economics Working Papers 0606, Department of Economics, University of Trento, Italia.

    More about this item

    Keywords

    tecnological knowledge; demand; consumer preferences; industrial dynamics;
    All these keywords.

    JEL classification:

    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O14 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Industrialization; Manufacturing and Service Industries; Choice of Technology
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:aal:abbswp:00-6. 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: Keld Laursen (email available below). General contact details of provider: https://www.druid.dk/ .

    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.