IDEAS home Printed from https://ideas.repec.org/a/zna/indecs/v7y2009i1p106-116.html
   My bibliography  Save this article

Expert Team Decision-Making and Problem Solving: Development and Learning

Author

Listed:
  • Simona Tancig

    (University of Ljubljana)

Abstract

Traditional research of decision-making has not significantly contributed towards better understanding of professional judgment and decisions in practice. Researchers dealing with decision-making in various professions and natural settings initiated new perspectives called naturalistic, which put the expert in the focus of research and the expertise thus entered the core of decision-making research in natural situations. Expert team is more than a group of experts. It is defined as a group of interdependent team members with a high level of task related expertise and the mastering of team processes. There have been several advances in understanding of expertise and the team. By combining theories, models, and empirical evidence we are trying to explain effectiveness and adaptation of expert teams in problem-solving and decision-making in complex and dynamic situations. A considerable research has been devoted to finding out what are the characteristics of experts and expert teams during their optimal functioning. These characteristics are discussed as input, process and output factors. As input variables the cognitive, social-affective, and motivational characteristics are presented. Process variables encompass individual and team learning, problem solving and decision-making as presented in Kolb's cycle of learning, in deeper structures of dialogue and discussion, and in phenomena of collaboration, alignment, and distributed cognition. Outcome variables deal with task performance - activities.

Suggested Citation

  • Simona Tancig, 2009. "Expert Team Decision-Making and Problem Solving: Development and Learning," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 7(2), pages 106-116.
  • Handle: RePEc:zna:indecs:v:7:y:2009:i:1:p:106-116
    as

    Download full text from publisher

    File URL: http://indecs.eu/2009/indecs2009-pp106-116.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    decision-making; paradigm; expert team; learning; adaptation;
    All these keywords.

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:zna:indecs:v:7:y:2009:i:1:p:106-116. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Josip Stepanic (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.