Abstract
The management decision making process is becoming increasingly complicated as more detailed and extensive data is available in this information age. The ability of human decisions makers to consistently analyse huge volumes of data and to do so in a repeatedly identical manner is questionable. This uncertainty about consistency and the cost in time and money creates the need for an artificial intelligent system. The system must be capable of processing large quantities of data and imitate the human decision making process but in a more consistent and cost effective manner. The authors employ a user centred fuzzy system, which is based on a hierarchical system, employing scalable fuzzy membership functions. The hierarchical structure of the system is self adjusting to facilitate the particular business problem and user’s decision making process. The fuzzy membership functions are scaled to reflect the human precedence given to particular data in the decision making process. The proposed system supports decision making in any data intense management decision making processes. Two case studies are presented, “The supplier selection process” and “The corporate acquisition process”. The development of this system is intended to illustrate that a fuzzy system can aid management in the most complicated management decision making processes.
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Maguire, L., McCloskey, T., Humphreys, P., McIvor, R. A User Centred Approach to Management Decision Making. In: Ruan, D., Chen, G., E. Kerre, E., Wets, G. (eds) Intelligent Data Mining. Studies in Computational Intelligence, vol 5. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11004011_22
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DOI: https://doi.org/10.1007/11004011_22
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Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26256-5
Online ISBN: 978-3-540-32407-2
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