Paper short abstract:

Playlist has become one of the most important ways listening and music taste is being shaped, through which the majority of music listeners consume and discover their music. In this article, we explore how value is allocated algorithmically in the streaming music economy.

Paper long abstract:

We have always listened to music curated by DJs, pop-chart compilers, producers, and friends. However today the computer generated Playlist has become one of the most important ways listening and music taste is being shaped. There is a wealth of literature on the recommender systems in general, and playlist algorithms in particular, exploring the mechanisms of algorithms (Garcia-Gathright et al., 2018) platforms’ ‘curatorial power’ (Eriksson, 2020; Morris, 2015; Prey, 2020), the impact on values and culture (Hodgson, 2021; Seaver, 2022), and the impact on consumers and production (Hesmondhalgh et al., 2023). However there is a dearth of research on how these algorithms are shaped by the financial goals of the recorded music business, and in turn shape the business.

In this article, we aim to fill this gap by exploring how value is allocated algorithmically in the streaming music economy. Understanding this is particularly important, due to the changing dynamics in which music streaming is increasingly understood as an asset rather than a commodity (Sun and Stewart, forthcoming). We draw on concepts such as assetisation (Birch and Muniesa, 2020), rentiership (Birch, 2020; Christophers, 2020) as well as algorithmic rents (O’Reilly et al., 2023) and demonstrate how the playlist becomes a way of extracting value from back-catalogue assets, rather than exploiting the commodity value of individual songs and current artists. From this, we explore how the dominance of music playlist gets in the way of other potential forms of innovation, leading to a lock-in.