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Group Decision Support Using Fuzzy Cognitive Maps for Causal Reasoning

Author

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  • M. Shamim Khan

    (Murdoch University)

  • Mohammed Quaddus

    (Curtin University of Technology)

Abstract

Cognitive maps have been used for analysing and aiding decision-making by investigating causal links among relevant domain concepts. A fuzzy cognitive map (FCM) is an extension of a cognitive map with the additional capability of representing feedback through weighted causal links. FCMs can be used as tools for both static as well as dynamic analysis of scenarios evolving with time. An FCM represents an expert's domain knowledge in a form that lends itself to relatively easy integration into a collective knowledge base for a group involved in a decision process. The resulting group FCM has the potential to serve as a useful tool in a group decision support environment. An appropriate methodology for the development and analysis of group FCMs is required. A framework for such a methodology consisting of the development and application phases is presented.

Suggested Citation

  • M. Shamim Khan & Mohammed Quaddus, 2004. "Group Decision Support Using Fuzzy Cognitive Maps for Causal Reasoning," Group Decision and Negotiation, Springer, vol. 13(5), pages 463-480, September.
    • Handle: RePEc:spr:grdene:v:13:y:2004:i:5:d:10.1023_b:grup.0000045748.89201.f3
    DOI: 10.1023/B:GRUP.0000045748.89201.f3
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    References listed on IDEAS

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    1. Yoram Wind & Thomas L. Saaty, 1980. "Marketing Applications of the Analytic Hierarchy Process," Management Science, INFORMS, vol. 26(7), pages 641-658, July.
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    Cited by:

    1. van Kouwen, Frank & Dieperink, Carel & Schot, Paul P. & Wassen, Martin J., 2007. "Interactive Problem Structuring with ICZM Stakeholders," Natural Resources Management Working Papers 9555, Fondazione Eni Enrico Mattei (FEEM).
    2. Alexandra S Penn & Christopher J K Knight & David J B Lloyd & Daniele Avitabile & Kasper Kok & Frank Schiller & Amy Woodward & Angela Druckman & Lauren Basson, 2013. "Participatory Development and Analysis of a Fuzzy Cognitive Map of the Establishment of a Bio-Based Economy in the Humber Region," PLOS ONE, Public Library of Science, vol. 8(11), pages 1-14, November.
    3. Marilena - Aura Din & Cristina Coculescu, 2015. "Modeling Of Urban Policies For Housing With Fuzzy Cognitive Map Methodology," Romanian Economic Business Review, Romanian-American University, vol. 9(2), pages 276-290, December.
    4. Frank van Kouwen & Card Dieperink & Paul P Schot & Martin J Wassen, 2009. "Computer-Supported Cognitive Mapping for Participatory Problem Structuring," Environment and Planning A, , vol. 41(1), pages 63-81, January.
    5. Jozsef Mezei & Peter Sarlin, 2014. "Aggregation operators for the measurement of systemic risk," Papers 1412.5452, arXiv.org, revised Dec 2014.
    6. Youngseok Choi & Habin Lee & Zahir Irani, 2018. "Big data-driven fuzzy cognitive map for prioritising IT service procurement in the public sector," Annals of Operations Research, Springer, vol. 270(1), pages 75-104, November.
    7. Rashaad E. T. Jones & Erik S. Connors & Mary E. Mossey & John R. Hyatt & Neil J. Hansen & Mica R. Endsley, 2011. "Using fuzzy cognitive mapping techniques to model situation awareness for army infantry platoon leaders," Computational and Mathematical Organization Theory, Springer, vol. 17(3), pages 272-295, September.
    8. Marina Anokhina, 2020. "Parameters of the strategy for managing the economic growth of agricultural production in Russia," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 66(3), pages 140-148.
    9. G Montibeller & V Belton, 2006. "Causal maps and the evaluation of decision options—a review," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(7), pages 779-791, July.
    10. Frank van Kouwen & Carel Dieperink & Paul P. Schot & Martin J. Wassen, 2007. "Interactive Problem Structuring with ICZM Stakeholders," Working Papers 2007.52, Fondazione Eni Enrico Mattei.
    11. Alizadeh, Somayeh & Ghazanfari, Mehdi, 2009. "Learning FCM by chaotic simulated annealing," Chaos, Solitons & Fractals, Elsevier, vol. 41(3), pages 1182-1190.

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