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Sharing Knowledge When it Cannot be Made Explicit: The Case of Product Lifecycle Management Systems

Author

Listed:
  • Pierre-Emmanuel Arduin

    (DRM - Dauphine Recherches en Management - Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres - CNRS - Centre National de la Recherche Scientifique)

  • Julien Le Duigou

    (UTC - Université de Technologie de Compiègne, Roberval - Roberval - UTC - Université de Technologie de Compiègne)

  • Marie-Hélène Abel

    (Heudiasyc - Heuristique et Diagnostic des Systèmes Complexes [Compiègne] - UTC - Université de Technologie de Compiègne - CNRS - Centre National de la Recherche Scientifique)

  • Benoit Eynard

    (UTC - Université de Technologie de Compiègne, Roberval - Roberval - UTC - Université de Technologie de Compiègne)

Abstract

Information systems often strengthen a preference for working alone: interoperability as much as interpretation variance restrain the ability of people and systems to interact and to work together within an extended enterprise. In this article, the authors propose to extend product lifecycle management (PLM) systems in order to share not only (1) knowledge that has been made explicit and which is strongly contextualized so that there is no interpretation variance, but also (2) knowledge that cannot be made explicit and which remains tacit knowledge, needing social interaction and shared understanding to be actually shared. The use of a collaborative platform is proposed in this article in order to allow stakeholders to produce a shared understanding of what a concept means through the use of ontologies. The conditions as well as the limits of the proposition are discussed at the end of this article.

Suggested Citation

  • Pierre-Emmanuel Arduin & Julien Le Duigou & Marie-Hélène Abel & Benoit Eynard, 2018. "Sharing Knowledge When it Cannot be Made Explicit: The Case of Product Lifecycle Management Systems," Post-Print hal-01893333, HAL.
    • Handle: RePEc:hal:journl:hal-01893333
    DOI: 10.4018/IJKBO.2018100102
    as

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    Keywords

    Knowledge management; Information systems;

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