IDEAS home Printed from https://ideas.repec.org/a/spr/comaot/v13y2007i3d10.1007_s10588-006-9001-8.html
   My bibliography  Save this article

Analysis of meeting protocols by formalisation, simulation, and verification

Author

Listed:
  • Catholijn M. Jonker

    (Delft University of Technology)

  • Martijn C. Schut

    (Vrije Universiteit Amsterdam)

  • Jan Treur

    (Vrije Universiteit Amsterdam)

  • Pınar Yolum

    (Bogazici University)

Abstract

Organizations depend on regular meetings to carry out their everyday tasks. When carried out successfully, meetings offer a common medium for participants to exchange ideas and make decisions. However, many meetings suffer from unfocused discussions or irrelevant dialogues. To study meetings in detail, we first formalize general properties of meetings and a generic meeting protocol to specify how roles in a meeting should interact to realize these properties. This generic protocol is used as a starting point to study real-life meetings. Next, an example meeting is simulated using the generic meeting protocol. The general properties are formally verified in the simulation trace. Next, these properties are also verified formally against empirical data of a real meeting in the same context. A comparison of the two traces reveals that a real meeting is more robust since when exceptions happen and the rules of the protocol are violated, these exceptions are handled effectively. Given this observation, a more refined protocol is specified that includes exception-handling strategies. Based on this refined protocol a meeting is simulated that closely resembles the real meeting. This protocol is then validated against another set of data from another real meeting. By iteratively adding exception handling rules, the protocol is enhanced to handle a variety of situations successfully.

Suggested Citation

  • Catholijn M. Jonker & Martijn C. Schut & Jan Treur & Pınar Yolum, 2007. "Analysis of meeting protocols by formalisation, simulation, and verification," Computational and Mathematical Organization Theory, Springer, vol. 13(3), pages 283-314, September.
    • Handle: RePEc:spr:comaot:v:13:y:2007:i:3:d:10.1007_s10588-006-9001-8
    DOI: 10.1007/s10588-006-9001-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10588-006-9001-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10588-006-9001-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Scott Moss & Helen Gaylard & Steve Wallis & Bruce Edmonds, 1998. "SDML: A Multi-Agent Language for Organizational Modelling," Computational and Mathematical Organization Theory, Springer, vol. 4(1), pages 43-69, March.
    2. Zini, Floriano & Giulioni, Gianfranco & Reinicke, Michael & Streitberger, Werner & Eymann, Torsten, 2005. "Analysis of simulation environment," Bayreuth Reports on Information Systems Management 8, University of Bayreuth, Chair of Information Systems Management.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Matthew L. Bolton, 2013. "Automatic validation and failure diagnosis of human-device interfaces using task analytic models and model checking," Computational and Mathematical Organization Theory, Springer, vol. 19(3), pages 288-312, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. J. Gareth Polhill & Dawn C. Parker & Daniel Brown & Volker Grimm, 2008. "Using the ODD Protocol for Describing Three Agent-Based Social Simulation Models of Land-Use Change," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(2), pages 1-3.
    2. Scott Moss, 2000. "Canonical Tasks, Environments and Models for Social Simulation," Computational and Mathematical Organization Theory, Springer, vol. 6(3), pages 249-275, September.
    3. Bruce Edmonds, 1999. "Gossip, Sexual Recombination and the El Farol Bar: Modelling the Emergence of Heterogeneity," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 2(3), pages 1-2.
    4. Adolfo Lopez Paredes & Cesáreo Hernández Iglesias, 1999. "Beyond Experimental Economics: Trading Institutions and Multiagent Systems," Computing in Economics and Finance 1999 1351, Society for Computational Economics.
    5. Tibor Bosse & Jan Treur, 2006. "Formal Interpretation of a Multi-Agent Society As a Single Agent," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 9(2), pages 1-6.
    6. Mark Hoogendoorn & Catholijn M. Jonker & Martijn C. Schut & Jan Treur, 2007. "Modeling centralized organization of organizational change," Computational and Mathematical Organization Theory, Springer, vol. 13(2), pages 147-184, June.
    7. Oswaldo Terán & Johanna Alvarez & Magdiel Ablan & Manuel Jaimes, 2007. "Characterising Land Holding Size Distributions in a Forest Reserve," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(3), pages 1-6.
    8. Tibor Bosse & Catholijn M. Jonker & Jan Treur, 2007. "Simulation And Analysis Of Adaptive Agents: An Integrative Modeling Approach," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 10(03), pages 335-357.
    9. Lopez-Paredes, Adolfo & Hernandez-Iglesias, Cesareo & Gutierrez, Javier Pajares, 2002. "Towards a new experimental socio-economics: Complex behaviour in bargaining," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 31(4), pages 423-429.

    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:spr:comaot:v:13:y:2007:i:3:d:10.1007_s10588-006-9001-8. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.