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Creativity Under Fire: The Effects of Competition on Creative Production

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  • Daniel P. Gross

    (Harvard Business School and NBER)

Abstract

Though fundamental to innovation and essential to many industries and occupations, individual creativity has received limited attention as an economic behavior and has historically proven difficult to study. This paper studies the incentive effects of competition on individuals' creative production. Using a sample of commercial logo design competitions and a novel, content-based measure of originality, I find that intensifying competition induces agents to produce original, untested ideas over tweaking their earlier work, but heavy competition drives them to stop investing altogether. The results yield lessons for the management of creative workers and the implementation of competitive procurement mechanisms for innovation.

Suggested Citation

  • Daniel P. Gross, 2020. "Creativity Under Fire: The Effects of Competition on Creative Production," The Review of Economics and Statistics, MIT Press, vol. 102(3), pages 583-599, July.
    • Handle: RePEc:tpr:restat:v:102:y:2020:i:3:p:583-599
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    References listed on IDEAS

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    Cited by:

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    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. Pavel Kireyev, 2016. "Markets for Ideas: Prize Structure, Entry Limits, and the Design of Ideation Contests," Harvard Business School Working Papers 16-129, Harvard Business School.
    4. Enzo Brox & Daniel Goller, 2024. "Tournaments, Contestant Heterogeneity and Performance," Papers 2401.05210, arXiv.org, revised Oct 2024.
    5. Marchenko, Maria & Sonnabend, Hendrik, 2022. "The Never Ending Book: The role of external stimuli and peer feedback in user-generated content production," Department of Economics Working Paper Series 320, WU Vienna University of Economics and Business.
    6. 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.
    7. James Lee Caton, 2019. "Creativity in a theory of entrepreneurship," Journal of Entrepreneurship and Public Policy, Emerald Group Publishing Limited, vol. 8(4), pages 442-469, September.
    8. Daniel P. Gross, 2017. "Performance feedback in competitive product development," RAND Journal of Economics, RAND Corporation, vol. 48(2), pages 438-466, May.
    9. Rubén Poblete Cazenave, 2021. "Reputation Shocks and Strategic Responses in Electoral Campaigns," Tinbergen Institute Discussion Papers 21-049/V, Tinbergen Institute.
    10. Erina Ytsma, 2022. "Effort and Selection Effects of Performance Pay in Knowledge Creation," CESifo Working Paper Series 10153, CESifo.
    11. Naudé, Wim & Bray, Amy & Lee, Celina, 2021. "Crowdsourcing Artificial Intelligence in Africa: Findings from a Machine Learning Contest," IZA Discussion Papers 14545, Institute of Labor Economics (IZA).
    12. Yanhui Wu & Feng Zhu, 2022. "Competition, Contracts, and Creativity: Evidence from Novel Writing in a Platform Market," Management Science, INFORMS, vol. 68(12), pages 8613-8634, December.
    13. Joel O. Wooten, 2022. "Leaps in innovation and the Bannister effect in contests," Production and Operations Management, Production and Operations Management Society, vol. 31(6), pages 2646-2663, June.
    14. Segev, Ella, 2020. "Crowdsourcing contests," European Journal of Operational Research, Elsevier, vol. 281(2), pages 241-255.
    15. Vivek Bhattacharya, 2021. "An Empirical Model of R&D Procurement Contests: An Analysis of the DOD SBIR Program," Econometrica, Econometric Society, vol. 89(5), pages 2189-2224, September.
    16. Milan Miric & Nan Jia & Kenneth G. Huang, 2023. "Using supervised machine learning for large‐scale classification in management research: The case for identifying artificial intelligence patents," Strategic Management Journal, Wiley Blackwell, vol. 44(2), pages 491-519, February.
    17. Prithwiraj Choudhury & Ryan T. Allen & Michael G. Endres, 2021. "Machine learning for pattern discovery in management research," Strategic Management Journal, Wiley Blackwell, vol. 42(1), pages 30-57, January.

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    More about this item

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • M52 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics - - - Compensation and Compensation Methods and Their Effects
    • M55 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics - - - Labor Contracting Devices
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D

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