A decision support system for identifying and representing likely crucial organizational know-how and knowing that

  • Ghrab S
  • Saad I
  • Gargouri F
 et al. 
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Abstract

This paper discusses the issues of classification, evaluation and cartography of organizational knowledge in the medical field. Its aim is to propose an Organizational Know-How/Knowing That Decision Support System (O2K-DSS) which can be applied to practical decision situations. O2K-DSS aims to propose a preference model based on multi-criteria decision support tools which allow the selection, the classification and the sorting of decision objects like know-how/knowing that in our case. Our goal is to propose a new category of decision class for ‘likely crucial know-how’/‘likely crucial knowing that’ which represents the subset of knowledge insufficient for knowledge capitalisation at time t. In fact, we classify know-how/knowing that into three decision classes: (1) the first class Cl1 for ‘non crucial know-how’/‘non crucial knowing that’ which represents the subset of knowledge whose level of validation is sufficient for not capitalising it, (2) the second class Cl2 for ‘likely crucial know-how’/‘likely crucial knowing that’ which represents the subset of knowledge whose level of validation is insufficient for capitalising it at time t and (3) the third class Cl3 for ‘crucial know-how’/‘crucial knowing that’ which represents the subset of knowledge whose level of validation is sufficient for capitalising it. These knowledge decision class categories are represented in cartography. © 2014 Taylor & Francis.

Author-supplied keywords

  • decision class
  • know-how/knowing that based decision support system
  • know-how/knowing that cartography
  • likely crucial know-how/knowing that
  • preference model

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Authors

  • Sahar Ghrab

  • Ines Saad

  • Faiez Gargouri

  • Gilles Kassel

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