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Beyond the realm of cash: street performers and payments in the online world

Author

Listed:
  • Meg Elkins

    (RMIT University)

  • Tim R. L. Fry

    (RMIT University)

Abstract

Street performers are able to contribute to a fabric of a city’s creative dynamic. The exchange for money between a street performer and an audience is a changing landscape. As less cash is carried on people’s person and audiences want to participate in exchange, the industry is ripe for disruption. The paper uses a unique data set from the online busking platform ‘The Busking Project’ to analyse individual donations to 3757 active buskers. Using a Heckman selection model, we find that the number of fans does influence the number of donations and the artist’s genre matters for the likelihood of receiving donation and the amount received. Musicians are more likely to receive a donation; however, it is a smaller donation amount than other performers. The method of payment for receiving a donation and the anonymity of the donor also influences the amount received. The geographic location matters for receiving a donation but not the amount received.

Suggested Citation

  • Meg Elkins & Tim R. L. Fry, 2022. "Beyond the realm of cash: street performers and payments in the online world," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 46(2), pages 231-248, June.
    • Handle: RePEc:kap:jculte:v:46:y:2022:i:2:d:10.1007_s10824-021-09421-8
    DOI: 10.1007/s10824-021-09421-8
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    More about this item

    Keywords

    Busking; Digitisation; Social media; Platform economy; Heckman selection;
    All these keywords.

    JEL classification:

    • Z11 - Other Special Topics - - Cultural Economics - - - Economics of the Arts and Literature
    • O35 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Social Innovation
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models

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