Platforms and Cultural Production. Thomas Poell
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Название: Platforms and Cultural Production

Автор: Thomas Poell

Издательство: John Wiley & Sons Limited

Жанр: Кинематограф, театр

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isbn: 9781509540525

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СКАЧАТЬ 2014; Rietveld & Schilling, 2020). In turn, this balancing act on the part of platforms – between getting users on board and improving pricing structures – introduces uncertainty and risk for cultural producers. Next, we discuss these uncertainties and risks through the lens of platform evolution. This allows us to provide a more nuanced perspective on the highly contingent relationship between platforms and complementors – which is subject not only to strategizing and economic decision-making, but also to complex temporal shifts.

      Network effects and business model design – that is, pricing – each play a role in the complexity and volatility of platform markets. More pointedly, they contribute to the “unprecedented speed,” or velocity if you will, with which platform markets evolve and platform businesses expand (Cunningham & Craig, 2019: 37; see also Arriagada & Ibáñez, 2020). Recall the soaring growth of Facebook discussed in the chapter opening. In 2020, it made US$18.48 billion in profits – substantially more than Disney’s US$11 billion earnings that same year. What is more, The Walt Disney Company’s global empire was built over a span of nearly a century; Facebook’s ascent, meanwhile, took place over a decade. Network effects, both direct and indirect, heavily contributed to Facebook’s growth, as did the platform’s ability to “lock in” end-users and complementors through a variety of economic and technological means.

      For complementors, such evolution is made all the more difficult to navigate because of the unpredictable behavior of end-users at various stages of the lifecycle. As a platform evolves, there is an increase in end-user heterogeneity. End-users who join during a platform’s launch phase are labeled early adopters; they tend to invest more time and money in exploring new technology (Rietveld & Eggers, 2018; see also Rogers, 2003). This temporal dynamic, in turn, leads complementors to face a strategic decision about when to join a platform – or when to leave. While joining early is considered risky, joining later in a platform’s lifecycle means that competition among complementors will increase. What is more, complementors will encounter late adopters, end-users who tend to be more risk averse and less committed (Rietveld & Eggers, 2018). Then again, in the mature phase, the overall pool of consumers can be exponentially bigger.

      When a platform leaves the launch phase, it can alter its pricing strategy, but also opt to add more sides to its business. That is exactly what Facebook did in 2007. Initially, the social network functioned as a two-sided market, mediating between end-users (i.e., students) and advertisers. The launch of the Facebook Development Platform turned the network into a multisided platform after it invited content creators, such as Zynga, to create complementary innovations (Nieborg & Helmond, 2019).

      To maintain growth by attracting new users to all sides, major platform companies have morphed into parent or holding organizations that operate different platform subsidiaries. For example, YouTube is a subsidiary of Google, which is a subsidiary of Alphabet Incorporated. Google also operates other platform subsidiaries, such as Google Search and the Google Play Store. While Google is colloquially referred to as a platform, its ever-expanding collection of platform subsidiaries all operate different business models. YouTube’s advertising-driven business model is not the same as the main revenue source of its app store, Google Play, which derives revenue from a mix of advertising and transaction fees. Similarly, Facebook’s apps, particularly those they acquired (Instagram and WhatsApp), can be seen as subsidiaries, since each functions as a multisided market in its own right. One way to make analytical sense of how platform companies are structured is thus to see them as platform ecosystems (van Dijck et al., 2018). Returning to the role of platform evolution, these instances of market integration are relevant to complementors because the growth of each subsidiary solidifies a platform company’s control over its wider ecosystem.

      As millions of cultural producers from across industries and regions flock to platforms, questions emerge about the political economic implications of this influx. How do the economic characteristics and institutional relationships specific to platform markets – network effects, pricing, platform evolution, and ecosystems – impact the ability of cultural producers to create, distribute, market, and monetize content? Do platforms challenge or exacerbate existing economic inequalities already present in the cultural industries? To start with this last question, we are inclined to offer a less optimistic perspective. In platform economies, the distributions of value and resources are highly uneven. Network effects alone generate “a cycle whereby more users beget more users, which leads to platforms having a natural tendency towards monopolization” (Srnicek, 2017: 45). In the case of platform competition, if a winner emerges, it tends to become dominant (Barwise & Watkins, 2018).

      Consider our retelling of Zynga’s corporate history, which points to the familiar political economic dynamic of the accumulation of economic power on the part of a single entity – in this case, Facebook. The launch of any new platform represents a crucial moment for cultural producers. After all, it is during this pivotal juncture that platform operators may offer complementors incentives to get on board, similar to Facebook offering Zynga special access to its end-users and their data. At the same time, with each additional end-user that joins Facebook, the platform becomes more powerful: “Due to network effects and economies of scale and scope, platforms can achieve a level of user participation that consolidates their position in the market, further increasing their capacities for datafication” (Mansell & Steinmueller, 2020: 39). We have seen what this СКАЧАТЬ