IDEAS home Printed from https://ideas.repec.org/a/bla/sysdyn/v39y2023i2p152-170.html
   My bibliography  Save this article

Mental models, cognitive maps, and the challenge of quantitative analysis of their network representations

Author

Listed:
  • Sumaiya Haque
  • Hesam Mahmoudi
  • Navid Ghaffarzadegan
  • Konstantinos Triantis

Abstract

Cognitive maps, or mental maps, are externalized portrayals of mental models—people's mental representations of reality and their presumptions about how the world works. They are often used as the intermediary step toward uncovering individuals' presumptions of the outside world. Yet, the next step is often vague: once one's understanding of the real world is mapped, how can we systematically evaluate the maps and compare and contrast them? In this note, we review several common approaches to analyzing cognitive maps, some rooted in network theories, and apply them to a dataset of 30 graduate students who analyzed a complex socioenvironmental problem. Our analysis shows that these methods provide inconsistent results and often fall short of capturing variations in mental models. The analysis points to a lack of effective methods for examining such maps and helps articulate a major research problem for systems‐thinking scholars. © 2023 System Dynamics Society.

Suggested Citation

  • Sumaiya Haque & Hesam Mahmoudi & Navid Ghaffarzadegan & Konstantinos Triantis, 2023. "Mental models, cognitive maps, and the challenge of quantitative analysis of their network representations," System Dynamics Review, System Dynamics Society, vol. 39(2), pages 152-170, April.
  • Handle: RePEc:bla:sysdyn:v:39:y:2023:i:2:p:152-170
    DOI: 10.1002/sdr.1729
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/sdr.1729
    Download Restriction: no

    File URL: https://libkey.io/10.1002/sdr.1729?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
    ---><---

    References listed on IDEAS

    as
    1. Manuel Brauch & Andreas Größler, 2022. "Holistic versus analytic thinking orientation and its relationship to the bullwhip effect," System Dynamics Review, System Dynamics Society, vol. 38(2), pages 121-134, April.
    2. Michael A. Levy & Mark N. Lubell & Neil McRoberts, 2018. "The structure of mental models of sustainable agriculture," Nature Sustainability, Nature, vol. 1(8), pages 413-420, August.
    3. Krystyna A. Stave, 2002. "Using system dynamics to improve public participation in environmental decisions," System Dynamics Review, System Dynamics Society, vol. 18(2), pages 139-167, June.
    4. Arash Baghaei Lakeh & Navid Ghaffarzadegan, 2015. "Does analytical thinking improve understanding of accumulation?," System Dynamics Review, System Dynamics Society, vol. 31(1-2), pages 46-65, January.
    5. Payam Aminpour & Steven A. Gray & Antonie J. Jetter & Joshua E. Introne & Alison Singer & Robert Arlinghaus, 2020. "Wisdom of stakeholder crowds in complex social–ecological systems," Nature Sustainability, Nature, vol. 3(3), pages 191-199, March.
    6. John D. Sterman, 1989. "Modeling Managerial Behavior: Misperceptions of Feedback in a Dynamic Decision Making Experiment," Management Science, INFORMS, vol. 35(3), pages 321-339, March.
    7. Yearworth, Mike & White, Leroy, 2013. "The uses of qualitative data in multimethodology: Developing causal loop diagrams during the coding process," European Journal of Operational Research, Elsevier, vol. 231(1), pages 151-161.
    8. Schaffernicht, Martin & Groesser, Stefan N., 2011. "A comprehensive method for comparing mental models of dynamic systems," European Journal of Operational Research, Elsevier, vol. 210(1), pages 57-67, April.
    Full references (including those not matched with items on IDEAS)

    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. Crabolu, Gloria & Font, Xavier & Eker, Sibel, 2023. "Evaluating policy complexity with Causal Loop Diagrams," Annals of Tourism Research, Elsevier, vol. 100(C).
    2. Maria Cleofe Giorgino & Federico Barnabè & Martin Kunc, 2020. "Integrating qualitative system dynamics with accounting practices: The case of integrated reporting and resource mapping," Systems Research and Behavioral Science, Wiley Blackwell, vol. 37(1), pages 97-118, January.
    3. Martin F. G. Schaffernicht & Stefan N. Groesser, 2016. "A competence development framework for learning and teaching system dynamics," System Dynamics Review, System Dynamics Society, vol. 32(1), pages 52-81, January.
    4. Lane, David C. & Rouwette, Etiënne A.J.A., 2023. "Towards a behavioural system dynamics: Exploring its scope and delineating its promise," European Journal of Operational Research, Elsevier, vol. 306(2), pages 777-794.
    5. Federico Cosenz & Guido Noto, 2016. "Applying System Dynamics Modelling to Strategic Management: A Literature Review," Systems Research and Behavioral Science, Wiley Blackwell, vol. 33(6), pages 703-741, November.
    6. Thompson, James P. & Howick, Susan & Belton, Valerie, 2016. "Critical Learning Incidents in system dynamics modelling engagements," European Journal of Operational Research, Elsevier, vol. 249(3), pages 945-958.
    7. Kirsten Davis & Navid Ghaffarzadegan & Jacob Grohs & Dustin Grote & Niyousha Hosseinichimeh & David Knight & Hesam Mahmoudi & Konstantinos Triantis, 2020. "The Lake Urmia vignette: a tool to assess understanding of complexity in socio‐environmental systems," System Dynamics Review, System Dynamics Society, vol. 36(2), pages 191-222, April.
    8. Payam Aminpour & Heike Schwermer & Steven Gray, 2021. "Do social identity and cognitive diversity correlate in environmental stakeholders? A novel approach to measuring cognitive distance within and between groups," PLOS ONE, Public Library of Science, vol. 16(11), pages 1-18, November.
    9. White, Leroy, 2016. "Behavioural operational research: Towards a framework for understanding behaviour in OR interventions," European Journal of Operational Research, Elsevier, vol. 249(3), pages 827-841.
    10. Hendijani, Rosa, 2021. "The effect of thinking style on dynamic systems performance: The mediating role of stock-flow understanding," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 95(C).
    11. Rosa Hendijani, 2021. "Analytical thinking, Little's Law understanding, and stock‐flow performance: two empirical studies," System Dynamics Review, System Dynamics Society, vol. 37(2-3), pages 99-125, April.
    12. Pluchinotta, Irene & Salvia, Giuseppe & Zimmermann, Nici, 2022. "The importance of eliciting stakeholders’ system boundary perceptions for problem structuring and decision-making," European Journal of Operational Research, Elsevier, vol. 302(1), pages 280-293.
    13. Elsawah, Sondoss & McLucas, Alan & Mazanov, Jason, 2017. "An empirical investigation into the learning effects of management flight simulators: A mental models approach," European Journal of Operational Research, Elsevier, vol. 259(1), pages 262-272.
    14. John Sterman, 2018. "System dynamics at sixty: the path forward," System Dynamics Review, System Dynamics Society, vol. 34(1-2), pages 5-47, January.
    15. Liang Qi & Cleotilde Gonzalez, 2015. "Mathematical knowledge is related to understanding stocks and flows: results from two nations," System Dynamics Review, System Dynamics Society, vol. 31(3), pages 97-114, July.
    16. Sy, Charlle, 2017. "A policy development model for reducing bullwhips in hybrid production-distribution systems," International Journal of Production Economics, Elsevier, vol. 190(C), pages 67-79.
    17. Pastore, Erica & Alfieri, Arianna & Zotteri, Giulio, 2019. "An empirical investigation on the antecedents of the bullwhip effect: Evidence from the spare parts industry," International Journal of Production Economics, Elsevier, vol. 209(C), pages 121-133.
    18. Berry, D. & Naim, M. M., 1996. "Quantifying the relative improvements of redesign strategies in a P.C. supply chain," International Journal of Production Economics, Elsevier, vol. 46(1), pages 181-196, December.
    19. Towill, Denis R. & Zhou, Li & Disney, Stephen M., 2007. "Reducing the bullwhip effect: Looking through the appropriate lens," International Journal of Production Economics, Elsevier, vol. 108(1-2), pages 444-453, July.
    20. Laura Schmitt Olabisi & Amadou Sidibé, 2023. "Observations from a system dynamics modeling field school in Mali," System Dynamics Review, System Dynamics Society, vol. 39(1), pages 80-94, January.

    More about this item

    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:bla:sysdyn:v:39:y:2023:i:2:p:152-170. 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: Wiley Content Delivery (email available below). General contact details of provider: http://onlinelibrary.wiley.com/journal/10.1111/0883-7066 .

    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.