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The Evaluation of Creativity

Author

Listed:
  • Michela Chessa

    (Université Côte d'Azur, France
    GREDEG CNRS)

  • Benjamin Prissé

    (Singapore University of Technology and Design, Singapour)

Abstract

Creativity is the basis of any innovation. However, there is a long and well documented academic dispute about how to best assess creativity. The Consensual Assessment Technique (CAT) is the most widely used instrument for this task. The CAT is based on a consensual definition of creativity: a product is creative to the extent that expert raters independently agree upon this judgment. It operates on the principle that no external factors should impact the assessment. In this paper, we ask whether this holds true, and we scrutinize the CAT by experimentally investigating potential discrepancies in evaluations of drawings due to three external factors: order effects, social norms, and communication. Our results confirm the robustness of the CAT in serving as a valuable method for assessing creativity at the aggregate level. However, we also identify certain weaknesses at the individual level, particularly regarding the evaluation of drawings in first positions and when subjects are allowed to communicate.

Suggested Citation

  • Michela Chessa & Benjamin Prissé, 2024. "The Evaluation of Creativity," GREDEG Working Papers 2024-16, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.
    • Handle: RePEc:gre:wpaper:2024-16
    as

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    References listed on IDEAS

    as
    1. Armin Falk & James J. Heckman, 2009. "Lab Experiments are a Major Source of Knowledge in the Social Sciences," Working Papers 200935, Geary Institute, University College Dublin.
    2. Giuseppe Attanasi & Michela Chessa & Sara Gil-Gallen & Patrick Llerena, 2021. "A survey on experimental elicitation of creativity in economics," Revue d'économie industrielle, De Boeck Université, vol. 0(2), pages 273-324.
    3. Gary Charness & Daniela Grieco, 2023. "Creativity and Corporate Culture," The Economic Journal, Royal Economic Society, vol. 133(653), pages 1846-1870.
    4. Emanuela Marrocu & Raffaele Paci, 2012. "Education or Creativity: What Matters Most for Economic Performance?," Economic Geography, Taylor & Francis Journals, vol. 88(4), pages 369-401, October.
    5. Edmund Phelps, 2015. "Mass Flourishing: How Grassroots Innovation Created Jobs, Challenge, and Change," Economics Books, Princeton University Press, edition 1, number 10058-2.
    6. Dan Ariely & Uri Gneezy & George Loewenstein & Nina Mazar, 2009. "Large Stakes and Big Mistakes," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 76(2), pages 451-469.
    7. Glenn Dutcher & Cortney S. Rodet, 2022. "Which two heads are better than one? Uncovering the positive effects of diversity in creative teams," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 31(4), pages 884-897, November.
    8. Gary Charness & Daniela Grieco, 2019. "Creativity and Incentives," Journal of the European Economic Association, European Economic Association, vol. 17(2), pages 454-496.
    9. Rodet, Cortney S., 2022. "Does cognitive load affect creativity? An experiment using a divergent thinking task," Economics Letters, Elsevier, vol. 220(C).
    10. Sanjiv Erat & Uri Gneezy, 2016. "Incentives for creativity," Experimental Economics, Springer;Economic Science Association, vol. 19(2), pages 269-280, June.
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    More about this item

    Keywords

    Creativity; Innovation; Consensual Assessment Technique; Experiments;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • I25 - Health, Education, and Welfare - - Education - - - Education and Economic Development
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives

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