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Wisdom of stakeholder crowds in complex social–ecological systems

Author

Listed:
  • Payam Aminpour

    (Michigan State University)

  • Steven A. Gray

    (Michigan State University
    Leibniz-Institute of Freshwater Ecology and Inland Fisheries
    Collective Intelligence Unit, Copenhagen Business School)

  • Antonie J. Jetter

    (Portland State University)

  • Joshua E. Introne

    (Syracuse Univeristy)

  • Alison Singer

    (Northern Arizona University)

  • Robert Arlinghaus

    (Leibniz-Institute of Freshwater Ecology and Inland Fisheries
    Humboldt-Universität zu Berlin)

Abstract

Sustainable management of natural resources requires adequate scientific knowledge about complex relationships between human and natural systems. Such understanding is difficult to achieve in many contexts due to data scarcity and knowledge limitations. We explore the potential of harnessing the collective intelligence of resource stakeholders to overcome this challenge. Using a fisheries example, we show that by aggregating the system knowledge held by stakeholders through graphical mental models, a crowd of diverse resource users produces a system model of social–ecological relationships that is comparable to the best scientific understanding. We show that the averaged model from a crowd of diverse resource users outperforms those of more homogeneous groups. Importantly, however, we find that the averaged model from a larger sample of individuals can perform worse than one constructed from a smaller sample. However, when averaging mental models within stakeholder-specific subgroups and subsequently aggregating across subgroup models, the effect is reversed. Our work identifies an inexpensive, yet robust way to develop scientific understanding of complex social–ecological systems by leveraging the collective wisdom of non-scientist stakeholders.

Suggested Citation

  • 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.
  • Handle: RePEc:nat:natsus:v:3:y:2020:i:3:d:10.1038_s41893-019-0467-z
    DOI: 10.1038/s41893-019-0467-z
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    Citations

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    Cited by:

    1. Joshua Aaron Becker & Douglas Guilbeault & Edward Bishop Smith, 2022. "The Crowd Classification Problem: Social Dynamics of Binary-Choice Accuracy," Management Science, INFORMS, vol. 68(5), pages 3949-3965, May.
    2. 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.
    3. Ghani, Latifah Abdul & Mahmood, Noor Zalina, 2023. "Modeling domestic wastewater pathways on household system using the socio-MFA techniques," Ecological Modelling, Elsevier, vol. 480(C).
    4. 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.
    5. Tong, De & Sun, Yiyu & Tang, Junqing & Luo, Zhenying & Lu, Jinfeng & Liu, Xuan, 2023. "Modeling the interaction of internal and external systems of rural settlements: The case of Guangdong, China," Land Use Policy, Elsevier, vol. 132(C).
    6. Zare, Fateme & Jakeman, Anthony J. & Elsawah, Sondoss & Guillaume, Joseph H.A., 2024. "Bridging practice and science in socio-environmental systems research and modelling: A design science approach," Ecological Modelling, Elsevier, vol. 492(C).
    7. Nathan Brugnone & Noam Benkler & Peter Revay & Rebecca Myhre & Scott Friedman & Sonja Schmer-Galunder & Steven Gray & James Gentile, 2024. "Is from ought? A comparison of unsupervised methods for structuring values-based wisdom-of-crowds estimates," Journal of Computational Social Science, Springer, vol. 7(2), pages 1327-1377, October.
    8. Haeussler, Carolin & Vieth, Sabrina, 2022. "A question worth a million: The expert, the crowd, or myself? An investigation of problem solving," Research Policy, Elsevier, vol. 51(3).
    9. Kelly F. Robinson & Mark R. DuFour & Jason L. Fischer & Seth J. Herbst & Michael L. Jones & Lucas R. Nathan & Tammy J. Newcomb, 2023. "Lessons Learned in Applying Decision Analysis to Natural Resource Management for High-Stakes Issues Surrounded by Uncertainty," Decision Analysis, INFORMS, vol. 20(4), pages 326-342, December.

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