Buccafusco and Garcia (2021)
Contents
Source Details
Buccafusco and Garcia (2021) | |
Title: | Pay-to-Playlist: The Commerce of Music Streaming |
Author(s): | Buccafusco, C., Garcia, K. |
Year: | 2021 |
Citation: | Buccafusco, C. and Garcia, K. (2021) Pay-to-Playlist: The Commerce of Music Streaming. 12 UC Irvine L. Rev (forthcoming 2021) |
Link(s): | Open Access |
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About the Data | |
Data Description: | Data were collected from interviews with members of the music industry, including independent labels, executives, distribution directors, artist managers, and artists from a range of genres. |
Data Type: | Primary data |
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Cross Country Study?: | No |
Comparative Study?: | No |
Literature review?: | No |
Government or policy study?: | No |
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Abstract
“Payola—sometimes referred to as “pay-for-play”—is the undisclosed payment, or acceptance of payment, in cash or in kind, for promotion of a song, album, or artist. Some form of pay-for-play has existed in the music industry since the 19th century. Most prominently, the term has been used to refer to the practice of record labels paying radio DJs to play certain songs in order to boost their popularity and sales. Since the middle of the 20th century, the FCC has regulated this behavior—ostensibly because of its propensity to harm consumers and competition—by requiring that broadcasters disclose such payments.
As streaming music platforms continue to siphon off listeners from analog radio, a new form of payola has emerged. In this new streaming payola, record labels, artists, and managers simply shift their payments from radio to streaming music platforms like Spotify, YouTube, TikTok, and Instagram. Instead of going to DJs, payments go to playlisters or to influencers who can help promote a song by directing audiences toward it. Because online platforms do not fall under the FCC’s jurisdiction, streaming pay-for-play is not currently regulated at the federal level, although some of it may be subject to state advertising disclosure laws.
In this Article, we describe the history and regulation of traditional forms of pay-for-play, and explain how streaming practices differ. Our account is based, in substantive part, on a novel series of qualitative interviews with music industry professionals. Our analysis finds the normative case for regulating streaming payola lacking: contrary to conventional wisdom, we show that streaming pay-for-play, whether disclosed or not, likely causes little to no harm to consumers, and it may even help independent artists gain access to a broader audience. Given this state of affairs, regulators should proceed with caution to preserve the potential advantages afforded by streaming payola and to avoid further exacerbating extant inequalities in the music industry.”
Main Results of the Study
The study finds that the ‘traditional justifications for payola regulation aren’t particularly convincing’ in the streaming context. These traditional justifications include:
• That payola causes harm to consumers, as monetary motives ultimately lead to inferior music, and failure to disclose sponsorships compromises consumers’ ability to make informed decisions.
• That payola causes harm to competition as when artists have to pay for their music to be paid, this will necessarily harm artists with fewer resources.
Instead, the study identifies that the main means of promoting music are now through playlists and influencers on social media, particularly short-form video sites such as TikTok. As such, additional regulation here may in fact increase barriers to entry for lesser-known performers.
Policy Implications as Stated By Author
[[Has intervention-response::The study advises that ‘lawmakers […] tread carefully when considering whether and how to regulate streaming payola, or to subject either users or the platform to copyright liability for these uses’. Further, as many short-form music videos do not compete with streaming revenue, and are frequently transformative, there may be a minimal value in regulating these activities given they likely fall within the ambit of fair use.]]
Coverage of Study
Datasets
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