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Robustness of a Distributed Knowledge Management Model

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  • Kühn Pedersen, Mogens

    (Department of Informatics, Copenhagen Business School)

  • Holm Larsen, Michael

    (Department of Informatics, Copenhagen Business School)

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    Abstract

    In globalizing competitive markets knowledge exchange between business organizations requires incentive mechanisms to ensure tactical purposes while strategic purposes are subject to joint organization and other forms of contractual obligations. Where property of knowledge (e.g. patents and copyrights) and contractbased knowledge exchange do not obtain network effectiveness because of prohibitive transaction costs in reducing uncertainty, we suggest a robust model for peer produced knowledge within a distributed setting. The peer produced knowledge exchange model relies upon a double loop knowledge conversion with symmetric incentives in a network since the production of actor specific knowledge makes any knowledge appropriation by use of property rights by the actors irrelevant. Without property rights in knowledge the actor network generates opportunity for incentive symmetry over a period of time. The model merges specific knowledge with knowledge from other actors into a decision support system specific for each actor in the network in recognition of actor role differences. The article suggests a set of 9 static and 5 dynamic propositions for the model to maintain symmetric incentives between different actor networks. The model is proposed for business networks.

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    File URL: http://openarchive.cbs.dk/cbsweb/handle/10398/6487
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    Bibliographic Info

    Paper provided by Copenhagen Business School, Department of Informatics in its series Working Papers with number 2002-13.

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    Length: 12 pages
    Date of creation: 18 Mar 2009
    Date of revision:
    Handle: RePEc:hhs:cbsinf:2002_013

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    Postal: Department of Informatics, Copenhagen Business School, Howitzvej 60, DK-2000 Frederiksberg, Denmark
    Phone: +45 3815 3815
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    Web page: http://www.cbs.dk/departments/inf/
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