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Long-Run Forecasting of Emerging Technologies with Logistic Models and Growth of Knowledge

Author

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  • Dmitry Kucharavy

    (LGeco - Laboratoire de Génie de la Conception - INSA Strasbourg - Institut National des Sciences Appliquées - Strasbourg - INSA - Institut National des Sciences Appliquées)

  • Eric Schenk

    (LGeco - Laboratoire de Génie de la Conception - INSA Strasbourg - Institut National des Sciences Appliquées - Strasbourg - INSA - Institut National des Sciences Appliquées)

  • Roland de Guio

    (LGeco - Laboratoire de Génie de la Conception - INSA Strasbourg - Institut National des Sciences Appliquées - Strasbourg - INSA - Institut National des Sciences Appliquées)

Abstract

In this paper applications of logistic S-curve and component logistics are considered in a framework of long-term forecasting of emerging technologies. Several questions and issues are discussed in connection with the presented ways of studying the transition from invention to innovation and further evolution of technologies. First, the features of a simple logistic model are presented and diverse types of competition are discussed. Second, a component logistic model is presented. Third, a hypothesis about the usability of a knowledge growth description and simulation for reliable long-term forecasting is proposed. Some interim empirical results for applying networks of contradictions are given.

Suggested Citation

  • Dmitry Kucharavy & Eric Schenk & Roland de Guio, 2009. "Long-Run Forecasting of Emerging Technologies with Logistic Models and Growth of Knowledge," Post-Print halshs-00440438, HAL.
    • Handle: RePEc:hal:journl:halshs-00440438
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00440438
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    References listed on IDEAS

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    1. James G. March, 1991. "Exploration and Exploitation in Organizational Learning," Organization Science, INFORMS, vol. 2(1), pages 71-87, February.
    2. David F. Scott & William G. Jens & Raymond E. Spudeck, 1991. "Analysis," Challenge, Taylor & Francis Journals, vol. 34(6), pages 58-60, November.
    3. Baumol, William J, 1972. "On Taxation and the Control of Externalities," American Economic Review, American Economic Association, vol. 62(3), pages 307-322, June.
    4. Meade, Nigel & Islam, Towhidul, 1995. "Forecasting with growth curves: An empirical comparison," International Journal of Forecasting, Elsevier, vol. 11(2), pages 199-215, June.
    5. Charles H. Anderton, 2003. "Conflict and Trade in a Predator/Prey Economy," Review of Development Economics, Wiley Blackwell, vol. 7(1), pages 15-29, February.
    6. Makridakis, Spyros & Hibon, Michele, 2000. "The M3-Competition: results, conclusions and implications," International Journal of Forecasting, Elsevier, vol. 16(4), pages 451-476.
    7. Patrick Llerena & Mireille Matt (ed.), 2005. "Innovation Policy in a Knowledge-Based Economy," Springer Books, Springer, number 978-3-540-26452-1, December.
    8. Modis, Theodore, 2007. "Strengths and weaknesses of S-curves," OSF Preprints r5zk7, Center for Open Science.
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    Cited by:

    1. Marco Civico, 2019. "The complexity of knowledge sharing in multilingual corporations: evidence from agent-based simulations," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 46(4), pages 767-795, November.

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