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Fuzzy Cognitive Mapping for MIS Decision-Making

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Fuzzy Applications in Industrial Engineering

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 201))

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Abstract

Traditional methods for modelling and defining Management Information System (MIS) decision-making tasks, have tended to centre around a systems science view of the world. This is largely in terms of modelling the individual, group, organisation, or system in relation to process and environmental boundaries. Whilst such approaches are excellent for citing the situational context of such decision-making tasks, this and other orthodox Operational Research (OR) techniques do not necessarily highlight or show those causal interdependencies which are dependent upon vague or ill-defined, ambiguous information. Fuzzy Logic, at its core, provides the researcher (be they academic or practitioner) with a multitude of techniques for handling uncertainty in this respect. As such, this article discusses and outlines the development of the application of Fuzzy Cognitive Mapping (FCM) to the MIS decision-making task of Information Systems Evaluation (ISE), in terms of the on-going research interests of the authors. Through defining the nature of ISE, the authors present two models of such investment appraisal techniques, and through the generation and simulation of their respective FCMs, provide further insight into this MIS decision making task. Finally the chapter concludes by discussing and analysing the development of this fuzzy technique as a valuable OR tool.

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Authors and Affiliations

  1. Information Systems Evaluation and Integration Network Group (ISEing) School of Mathematics, Information Systems & Computing, Brunel University, UK

    Amir Sharif & Zahir Irani

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  1. Amir Sharif
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  2. Zahir Irani
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Editors and Affiliations

  1. Industrial Department of Engineering Faculty Management, Istanbul Technical University, Campus Macka, Istanbul, 80680, Turkey

    Cengiz Kahraman Dr.

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Sharif, A., Irani, Z. (2006). Fuzzy Cognitive Mapping for MIS Decision-Making. In: Kahraman, C. (eds) Fuzzy Applications in Industrial Engineering. Studies in Fuzziness and Soft Computing, vol 201. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-33517-X_19

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  • DOI: https://doi.org/10.1007/3-540-33517-X_19

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