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Learing Induced Criticality In Consumers' Adoption Pattern: A Neural Network Approach

Author

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  • Franck Plouraboue
  • Alexandre Steyer
  • Jean-Benoit Zimmermann

Abstract

The aim of this paper is to lay the foundations of 3 social influence based approach for the diffusion of an innovation or a technological standard. A model built on the principles of a neural network is proposed and a learning procedure is set up, making the network formation endogenous, the strength of connections among agents being determined by their shared histories, Referring to the concept of criticality developed by physicists, it shall be shown that learning, in a social structure, can lead the network to a critical state, called 'learning induced criticality, where some agents are able to exert a macroscopic influence over the network. The distribution of influence spheres' size follows a Pareto law. This approach shows an interesting similatry with that of the social coherence in sociology, whereby individuals within a social structure are led to share a close assessment of a given innovation.

Suggested Citation

  • Franck Plouraboue & Alexandre Steyer & Jean-Benoit Zimmermann, 1998. "Learing Induced Criticality In Consumers' Adoption Pattern: A Neural Network Approach," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 6(1), pages 73-90.
  • Handle: RePEc:taf:ecinnt:v:6:y:1998:i:1:p:73-90
    DOI: 10.1080/10438599800000014
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    Cited by:

    1. Rossi, Federica, 2002. "An introductory overview of innovation studies," MPRA Paper 9106, University Library of Munich, Germany, revised Jun 2008.
    2. R. Cowan & N. Jonard & J.-B. Zimmermann, 2006. "Evolving networks of inventors," Journal of Evolutionary Economics, Springer, vol. 16(1), pages 155-174, April.
    3. Deroian, Frederic, 2002. "Formation of social networks and diffusion of innovations," Research Policy, Elsevier, vol. 31(5), pages 835-846, July.
    4. Schade, Sven & Buxmann, Peter, 2005. "A Prototype to Analyse and Support Standardization Decisions," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 35795, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    5. Cowan, Robin, 2004. "Network models of innovation and knowledge diffusion," Research Memorandum 016, Maastricht University, Maastricht Economic Research Institute on Innovation and Technology (MERIT).
    6. Nicolas Carayol & Jean-Michel Dalle, 2003. "The ‘problem of problem choice’: A model of sequential knowledge production within scientific communities cientific communities," Working Papers of BETA 2003-12, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    7. Carayol, Nicolas & Dalle, Jean-Michel, 2007. "Sequential problem choice and the reward system in Open Science," Structural Change and Economic Dynamics, Elsevier, vol. 18(2), pages 167-191, June.

    More about this item

    Keywords

    diffusion; adoption; social influence; network externality; learning; criticality JEL Classification: A12; A14; DI1; D83; 033;

    JEL classification:

    • A12 - General Economics and Teaching - - General Economics - - - Relation of Economics to Other Disciplines
    • A14 - General Economics and Teaching - - General Economics - - - Sociology of Economics
    • D11 - Microeconomics - - Household Behavior - - - Consumer Economics: Theory
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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