Solving problems of project management with a self enforcing network (SEN)

Christina Klüver ()
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Christina Klüver: University of Duisburg-Essen

Computational and Mathematical Organization Theory, 2012, vol. 18, issue 2, No 3, 175-192

Abstract: Abstract The usage of AI techniques when dealing with problems of management always implies the task to understand the respective problem in terms of these techniques, in this case in terms of a specific neural network. That is, by the way, at its core a hermeneutical problem, namely of “understanding” the problem situation in the sense of hermeneutics. I shall demonstrate how a specific self-organized learning network that we have newly developed can be applied to problems of project management. This new network SEN will be described and its possibilities are shown by the application to different problems of project management, e.g. the selection of suited collaborators for a specific project, the classification of problematic customers or also the selection of suited procedures for project management in a specific firm. The SEN seems to be a universal instrument for different purposes as many reactions from managers in several large firms have shown. In particular SEN seems to be more suited for practical problems than some standard software we compared with SEN.

Keywords: Self organized learning; Neural networks; Self enforcing network; Project management (search for similar items in EconPapers)
Date: 2012
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DOI: 10.1007/s10588-012-9118-x

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