What are contemporary practices of collaborative funding and financing for artists, and how are institutional funders involved? To address this question, we map contemporary funding models in the Netherlands. We identify three ways in which governments and other (semi-public or private) entities engage in collaborative funding and financing: cooperating funds, which are similar to traditional subsidies but cater to artists who do not fit into a single category; pooled funds, newly created resources aimed at marketable initiatives with the potential for revolving structures; and matching funds, which come in three variants with an expected flywheel effect. With upfront matching funds, governments can incentivize each other. Hubs are physical spaces with incubator qualities that encourage additional funding. And platform-supported matching funds rely on technology to crowd in resources from both institutional funders and fans. The implications of our study suggest that collaborative funding models can increase financial resources for artists and promote productivity and inclusivity, although they may also involve coordination costs that reduce net funding. For policymakers, it is essential to design and coordinate these models carefully to ensure they remain fair, effective, and capable of providing sustained support over time. We conclude by speculating on the future role of artificial intelligence in artist funding, based on insights generated by artificial intelligence itself.
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Ellen Loots
Erasmus University Rotterdam
Carolina Dalla Chiesa
Erasmus University Rotterdam
Yosha Wijngaarden
Erasmus University Rotterdam
Journal of Cultural Management and Cultural Policy / Zeitschrift für Kulturmanagement und Kulturpolitik
Erasmus University Rotterdam
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Loots et al. (Wed,) studied this question.
synapsesocial.com/papers/68e9b1c1ba7d64b6fc132363 — DOI: https://doi.org/10.1177/27018466251369006