IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v10y2022i4p539-d745373.html
   My bibliography  Save this article

Collective Intelligence in Design Crowdsourcing

Author

Listed:
  • Jonathan Dortheimer

    (MTRL Laboratory, Faculty of Architecture and Town Planning, Technion—Israel Institute of Technology, Haifa 3200003, Israel)

Abstract

This study investigates how collective intelligence emerges in crowdsourcing for architectural design. Previous studies have revealed that collective intelligence emerges from collaboration and can outperform individual intelligence. As design is a highly collaborative practice, collective intelligence plays a vital role in the design process. In this study, we compare the structure of two architectural design crowdsourcing systems using several methods. The results of the analysis suggest that design crowdsourcing systems can give rise to the following three types of collective intelligence: (1) discussive, which emerges from a conversation between designers and clients; (2) synthetic, which emerges from a parallel and sequential design development; and (3) evaluative, which is based on the wisdom of the crowd in evaluating and selecting designs. The article concludes with recommendations for collaborative design method.

Suggested Citation

  • Jonathan Dortheimer, 2022. "Collective Intelligence in Design Crowdsourcing," Mathematics, MDPI, vol. 10(4), pages 1-24, February.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:4:p:539-:d:745373
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/10/4/539/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/10/4/539/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jim Giles, 2005. "Internet encyclopaedias go head to head," Nature, Nature, vol. 438(7070), pages 900-901, December.
    2. Ethan Bernstein & Jesse Shore & David Lazer, 2018. "How intermittent breaks in interaction improve collective intelligence," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 115(35), pages 8734-8739, August.
    3. David Engel & Anita Williams Woolley & Lisa X Jing & Christopher F Chabris & Thomas W Malone, 2014. "Reading the Mind in the Eyes or Reading between the Lines? Theory of Mind Predicts Collective Intelligence Equally Well Online and Face-To-Face," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-16, December.
    4. Anita Williams Woolley, 2009. "Means vs. Ends: Implications of Process and Outcome Focus for Team Adaptation and Performance," Organization Science, INFORMS, vol. 20(3), pages 500-515, June.
    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. Jiali Wang & Changbing Tang & Jianquan Lu & Guanrong Chen, 2023. "Toward Zero-Determinant Strategies for Optimal Decision Making in Crowdsourcing Systems," Mathematics, MDPI, vol. 11(5), pages 1-21, February.

    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. Runsten, Philip, 2017. "TEAM INTELLIGENCE: THE FOUNDATIONS OF INTELLIGENT ORGANIZATIONS - A Literature Review," SSE Working Paper Series in Business Administration 2017:2, Stockholm School of Economics.
    2. Oubrich, Mourad & Hakmaoui, Abdelati & Benhayoun, Lamiae & Solberg Söilen, Klaus & Abdulkader, Bisan, 2021. "Impacts of leadership style, organizational design and HRM practices on knowledge hiding: The indirect roles of organizational justice and competitive work environment," Journal of Business Research, Elsevier, vol. 137(C), pages 488-499.
    3. Wei Luo & Julia Adams & Hannah Brueckner, 2018. "The Ladies Vanish? American Sociology and the Genealogy of its Missing Women on Wikipedia," Working Papers 20180012, New York University Abu Dhabi, Department of Social Science, revised Jan 2018.
    4. Aaltonen, Aleksi Ville & Seiler, Stephan, 2014. "Quantifying spillovers in open source content production: evidence from Wikipedia," LSE Research Online Documents on Economics 60284, London School of Economics and Political Science, LSE Library.
    5. Hackett, Edward J. & Leahey, Erin & Parker, John N. & Rafols, Ismael & Hampton, Stephanie E. & Corte, Ugo & Chavarro, Diego & Drake, John M. & Penders, Bart & Sheble, Laura & Vermeulen, Niki & Vision,, 2021. "Do synthesis centers synthesize? A semantic analysis of topical diversity in research," Research Policy, Elsevier, vol. 50(1).
    6. Charles Ayoubi & Boris Thurm, 2023. "Knowledge diffusion and morality: Why do we freely share valuable information with Strangers?," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 32(1), pages 75-99, January.
    7. Enrico Imbimbo & Federica Stefanelli & Andrea Guazzini, 2020. "Adolescent’s Collective Intelligence: Empirical Evidence in Real and Online Classmates Groups," Future Internet, MDPI, vol. 12(5), pages 1-16, April.
    8. Demidov, Denis & Frahm, Klaus M. & Shepelyansky, Dima L., 2020. "What is the central bank of Wikipedia?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    9. Suddaby, Roy & Ganzin, Max & Minkus, Alison, 2017. "Craft, magic and the re-enchantment of the world," European Management Journal, Elsevier, vol. 35(3), pages 285-296.
    10. Hervé, Fabrice & Zouaoui, Mohamed & Belvaux, Bertrand, 2019. "Noise traders and smart money: Evidence from online searches," Economic Modelling, Elsevier, vol. 83(C), pages 141-149.
    11. Nicolas Jullien, 2012. "What We Know About Wikipedia: A Review of the Literature Analyzing the Project(s)," Post-Print hal-00857208, HAL.
    12. Goodall, Amanda H. & Osterloh, Margit, 2015. "Women Have to Enter the Leadership Race to Win: Using Random Selection to Increase the Supply of Women into Senior Positions," IZA Discussion Papers 9331, Institute of Labor Economics (IZA).
    13. Ewa S. Callahan & Susan C. Herring, 2011. "Cultural bias in Wikipedia content on famous persons," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(10), pages 1899-1915, October.
    14. Satterstrom, Patricia & Polzer, Jeffrey T. & Kwan, Lisa B. & Hauser, Oliver P. & Wiruchnipawan, Wannawiruch & Burke, Marina, 2019. "Thin slices of workgroups," Organizational Behavior and Human Decision Processes, Elsevier, vol. 151(C), pages 104-117.
    15. Marianne Bertrand & Esther Duflo, 2016. "Field Experiments on Discrimination," NBER Working Papers 22014, National Bureau of Economic Research, Inc.
    16. Angeliki Antoniou, 2019. "Compatibility of Small Team Personalities in Computer-Based Tasks," Challenges, MDPI, vol. 10(1), pages 1-12, May.
    17. Ben Weidmann & David J. Deming, 2020. "Team Players: How Social Skills Improve Group Performance," NBER Working Papers 27071, National Bureau of Economic Research, Inc.
    18. Philipp Poschmann & Jan Goldenstein, 2022. "Disambiguating and Specifying Social Actors in Big Data: Using Wikipedia as a Data Source for Demographic Information," Sociological Methods & Research, , vol. 51(2), pages 887-925, May.
    19. Sheen S. Levine & Michael J. Prietula, 2014. "Open Collaboration for Innovation: Principles and Performance," Organization Science, INFORMS, vol. 25(5), pages 1414-1433, October.
    20. Ethan Mollick & Ramana Nanda, 2016. "Wisdom or Madness? Comparing Crowds with Expert Evaluation in Funding the Arts," Management Science, INFORMS, vol. 62(6), pages 1533-1553, June.

    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:gam:jmathe:v:10:y:2022:i:4:p:539-:d:745373. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.