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Collaborative Decision Making: A Connectionist Paradigm for Dialectical Support

Author

Listed:
  • T. S. Raghu

    (School of Accountancy and Information Management, Arizona State University, Tempe, Arizona 85287)

  • R. Ramesh

    (Department of Management Science and Systems, School of Management, State University of New York at Buffalo, Buffalo, New York 14260)

  • Ai-Mei Chang

    (Information Resources Management College, National Defense University, Washington, District of Columbia 20319)

  • Andrew B. Whinston

    (Department of Management Information Systems, University of Arizona, Tucson, Arizona 85721)

Abstract

The facilitation and analytical support of argumentation-based collaborative decision making is the focus of this research. We model collaborative decision making as an argumentation process. We develop a connectionist modeling framework, a network representation formalism for argument structures, connectionist network mechanisms, and their models of computations to extract the behavior of argument structures. We use two examples from the case study literature to illustrate the concepts. Several interesting properties of the connectionist network models are observed from our computational results. We find that although the length of the computation is affected by parametric values, the final activation levels of the units are largely unaffected. We observe that the initial activation levels of the defeasible units seem to have no effect on their final activation levels. The proposed modeling approach generates valuable insights into the characteristics of specific argumentative discussions. While the intention of this work is not to introduce the connectionist paradigm as a means to bring arguments to a closure (resolution), we show that certain resolution mechanisms can be easily implemented under the connectionist framework.

Suggested Citation

  • T. S. Raghu & R. Ramesh & Ai-Mei Chang & Andrew B. Whinston, 2001. "Collaborative Decision Making: A Connectionist Paradigm for Dialectical Support," Information Systems Research, INFORMS, vol. 12(4), pages 363-383, December.
  • Handle: RePEc:inm:orisre:v:12:y:2001:i:4:p:363-383
    DOI: 10.1287/isre.12.4.363.9705
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    References listed on IDEAS

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    1. Ian I. Mitroff & Richard O. Mason & Vincent P. Barabba, 1982. "Policy as Argument---A Logic for Ill-Structured Decision Problems," Management Science, INFORMS, vol. 28(12), pages 1391-1404, December.
    2. R. Ramesh & Andrew B. Whinston, 1994. "Claims, Arguments, and Decisions: Formalisms for Representation, Gaming, and Coordination," Information Systems Research, INFORMS, vol. 5(3), pages 294-325, September.
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    Cited by:

    1. Hemant Jain & Balaji Padmanabhan & Paul A. Pavlou & T. S. Raghu, 2021. "Editorial for the Special Section on Humans, Algorithms, and Augmented Intelligence: The Future of Work, Organizations, and Society," Information Systems Research, INFORMS, vol. 32(3), pages 675-687, September.
    2. Wong, Christina W.Y. & Lai, Kee-hung & Cheng, T.C.E. & Lun, Y.H. Venus, 2015. "The role of IT-enabled collaborative decision making in inter-organizational information integration to improve customer service performance," International Journal of Production Economics, Elsevier, vol. 159(C), pages 56-65.
    3. Jesus Gonzalez-Feliu & Joëlle Morana, 2010. "Collaborative transportation sharing: from theory to practice via a case study from France," Post-Print halshs-00460923, HAL.

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