IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v166y2005i3p741-755.html
   My bibliography  Save this article

Agent-based modeling on technological innovation as an evolutionary process

Author

Listed:
  • Ma, Tieju
  • Nakamori, Yoshiteru

Abstract

No abstract is available for this item.

Suggested Citation

  • Ma, Tieju & Nakamori, Yoshiteru, 2005. "Agent-based modeling on technological innovation as an evolutionary process," European Journal of Operational Research, Elsevier, vol. 166(3), pages 741-755, November.
  • Handle: RePEc:eee:ejores:v:166:y:2005:i:3:p:741-755
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(04)00413-8
    Download Restriction: Full text for ScienceDirect subscribers only

    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. John H. Miller, 1998. "Active Nonlinear Tests (ANTs) of Complex Simulation Models," Management Science, INFORMS, vol. 44(6), pages 820-830, June.
    2. Loet Leydesdorff, 2001. "Technology and Culture: the Dissemination and the Potential 'Lock-In' of New Technologies," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 4(3), pages 1-5.
    3. Lee Altenberg, 1994. "Evolving Better Representations Through Selective Genome Growth," Working Papers 94-02-008, Santa Fe Institute.
    4. David B. Audretsch, 1995. "Innovation and Industry Evolution," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262011468, January.
    5. Gérard Ballot & Erol Taymaz, 1999. "Technological Change, Learning and Macro-Economic Coordination: an Evolutionary Model," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 2(2), pages 1-3.
    6. Nigel Gilbert & Andreas Pyka & Petra Ahrweiler, 2001. "Innovation Networks - a Simulation Approach," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 4(3), pages 1-8.
    7. Robert Axelrod, 1997. "Advancing the Art of Simulation in the Social Sciences," Working Papers 97-05-048, Santa Fe Institute.
    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. Guoyin Jiang & Feicheng Ma & Youtian Wang, 2012. "A review on the evolution of user acceptance behaviour in collaborative e-commerce," International Journal of Electronic Finance, Inderscience Enterprises Ltd, vol. 6(1), pages 62-78.
    2. Pudmenzky, Alexander, 2006. "On the advantages of non-cooperative behavior in agent populations," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 71(1), pages 1-8.
    3. Moradi, Mohammad H. & Razini, Saleh & Mahdi Hosseinian, S., 2016. "State of art of multiagent systems in power engineering: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 814-824.
    4. Amini, Mehdi & Wakolbinger, Tina & Racer, Michael & Nejad, Mohammad G., 2012. "Alternative supply chain production–sales policies for new product diffusion: An agent-based modeling and simulation approach," European Journal of Operational Research, Elsevier, vol. 216(2), pages 301-311.
    5. Wang, Ziyi & Wennersten, Ronald & Sun, Qie, 2017. "Outline of principles for building scenarios – Transition toward more sustainable energy systems," Applied Energy, Elsevier, vol. 185(P2), pages 1890-1898.
    6. Pan, Xiaojun & Li, Shoude, 2016. "Dynamic optimal control of process–product innovation with learning by doing," European Journal of Operational Research, Elsevier, vol. 248(1), pages 136-145.
    7. Ma, T. & Grubler, A. & Nakamori, Y., 2009. "Modeling technology adoptions for sustainable development under increasing returns, uncertainty, and heterogeneous agents," European Journal of Operational Research, Elsevier, vol. 195(1), pages 296-306, May.
    8. Cao, Kai & Feng, Xiao & Wan, Hui, 2009. "Applying agent-based modeling to the evolution of eco-industrial systems," Ecological Economics, Elsevier, vol. 68(11), pages 2868-2876, September.
    9. Leitner, Stephan & Rausch, Alexandra & Behrens, Doris A., 2017. "Distributed investment decisions and forecasting errors: An analysis based on a multi-agent simulation model," European Journal of Operational Research, Elsevier, vol. 258(1), pages 279-294.
    10. Ma, Tieju & Nakamori, Yoshiteru, 2009. "Modeling technological change in energy systems – From optimization to agent-based modeling," Energy, Elsevier, vol. 34(7), pages 873-879.
    11. Stephan Leitner, 2014. "A simulation analysis of interactions among intended biases in costing systems and their effects on the accuracy of decision-influencing information," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 22(1), pages 113-138, March.
    12. Stephan Leitner & Friederike Wall, 2015. "Simulation-based research in management accounting and control: an illustrative overview," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 26(2), pages 105-129, August.
    13. J. Farmer & Cameron Hepburn & Penny Mealy & Alexander Teytelboym, 2015. "A Third Wave in the Economics of Climate Change," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 62(2), pages 329-357, October.
    14. Stephan Leitner & Doris Behrens, 2015. "On the fault (in)tolerance of coordination mechanisms for distributed investment decisions," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 23(1), pages 251-278, March.

    More about this item

    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:eee:ejores:v:166:y:2005:i:3:p:741-755. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/locate/eor .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.