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refer to those groups not consisting of end-users as institutional actors, which we understand as companies or individual entrepreneurs. Thus, we distinguish between end-users and the producers of cultural content, the latter of whom, as noted in Chapter 1, we consider to be part of a broader group of institutional actors we refer to as complementors.

Second, the platform companies we examine in this book are not mere matchmakers; they also strategically open the boundaries of their firms to stimulate external innovations by complementors (Baldwin & Woodard, 2009; Gawer, 2020). In this respect, platform companies such as Google, Apple, and Facebook differ from “transaction” platforms at the heart of the gig-economy, which Nick Srnicek describes as “lean platforms” (2017: 73). An example of the latter are transportation platforms such as DiDi, Lyft, and Uber, which aggregate drivers and passengers, but they do not allow those drivers to develop and distribute complementary innovations (e.g., apps that provide additional services). A platform such as Facebook, by contrast, does allow complementors to develop external innovations. The “social games” developed by Zynga, the game developer we discussed in the Introduction, are examples of such innovations. Not only did Facebook “match” Zynga with players, but the platform also opened the boundaries of its platform to build games that integrate with Facebook’s data infrastructure and technology (Nieborg & Helmond, 2019).

      To be sure, the institutional relationships between platforms and complementors are not of primary concern to all platform scholars; there is, however, widespread consensus that a fundamental tension arises when platforms open their boundaries in the way that Facebook has. When doing so, platforms have the potential to be a democratizing force – providing market access and economic opportunity – while simultaneously staying fully in control (Constantinides et al., 2018). That is, platforms selectively open their boundaries to complementors, but do so under the economic and infrastructural conditions of their choosing, which will be discussed more extensively in the following chapters (de Reuver et al., 2018; Tilson et al., 2010).

      Because those platform companies active in the cultural industries tend to do both – serve as matchmakers and allow for external innovations – they are considered “hybrids” that “combine transaction and innovation functions” (Gawer, 2020). Integrating these two characteristics brings us to a third aspect specific to how platforms active in the cultural industries operate as companies: their business models.⁵ Most legacy media conglomerates, such as Disney, follow an intellectual property (IP) ownership model, “which is designed to create scarcity through copyright” (Cunningham & Craig, 2019: 101). In other words, Disney tasks its subsidiaries – e.g., Walt Disney Pictures, Marvel, Lucasfilm, and Pixar – to create original cultural content, often at tremendous cost, which is then licensed or used to promote branded products, encourage the sale of tickets to parks and musicals, or simply create additional content based on its original IP (Wasko, 2020).

Conversely, platform companies are notoriously averse to being considered media companies (Napoli & Caplan, 2017), a narrative which we challenge in subsequent chapters. Instead of creating or commissioning cultural content to be sold to consumers, their main sources of revenue include advertising (Google, Baidu, Facebook), selling hardware at a premium (Apple, Samsung), or e-commerce and cloud hosting (Amazon, Alibaba). This is not to say that these companies never create or commission media content.⁶ Since the mid-2010s, Apple, Amazon, and other platform businesses have invested billions of dollars in IP-based cultural commodities, such as movies and TV-shows.⁷ Yet, looking at their balance sheets, the revenue derived from these operations is secondary to their primary business model, which relies on the aggregation of institutional connections and data, and/or facilitating transactions. In sum, a platform’s main source of revenue matters deeply because it determines the complementors to which a platform may grant more or less favorable conditions.

       Network effects and pricing

      To better understand the political economy of multisided markets, it is necessary to identify the core economic principles constituting these markets and the subsequent strategic decisions faced by platform companies. These principles and decisions, together, shape the economic horizon of cultural producers. Two are particularly relevant: network effects and pricing.

      Like all digital and physical networks, platforms leverage economies of scale because they benefit from internet connectivity, which, in turn, allows for network effects. So-called direct network effects dictate that the more users who join a network, the more valuable that network becomes (Katz & Shapiro, 1985). These effects, or what economists call “network externalities,” are especially pronounced in digital markets, where marginal costs – the costs of adding additional units or users – are low. Network effects help explain the potential for rapid growth: if platform markets expand, which is never assured, its growth can be sudden and swift. Apps such as Snapchat, TikTok, Instagram, WeChat, and WhatsApp are all prime examples of rapid diffusion when direct network effects are positive.

We should emphasize that direct network effects are not unique to platforms and apps: any company active in digital markets may benefit from adding additional users. What sets multisided (i.e., platform) markets apart from traditional market structures – both physical and digital – is that they also engender “indirect” or “crossside” network effects (Evans & Schmalensee, 2016; Rochet & Tirole, 2003). This means that, when positive, the more users joining a platform market on one side, the more valuable the platform becomes for users on the other side. To return to the two-sided market example of game consoles: the more players who have a PlayStation, the more valuable the game console becomes for game publishers. And vice versa, a broader catalogue of games (i.e., more complementors) offers a better value proposition to players who consider buying a new game platform. This example goes to show that network effects significantly impact complementors: since they are part of the same market (or network) as a platform company, they can benefit from a platform’s growing pool of end-users. In our opening example, game developer Zynga harnessed Facebook’s then-swift popularity to great effect.

      The design of a platform’s business model shapes the economic environment in which platform-dependent cultural producers operate. When creating a platform market, platform operators are faced with a series of fundamental strategic challenges, such as: which side to attract first? Complementors or end-users? Supply or demand? That is, operators must address a “chicken-and-egg problem” and be careful to “get both sides on board” (Rochet & Tirole, 2003: 990). Likewise, there is the challenge of pricing. A key decision is whether, when, and how much to either charge or subsidize which side: end-users, cultural producers, or other types of complementors. Two-sided markets can use the income they generate from one side to provide free access to the other side. For example, in the case of Facebook – as with most social networks – access to the platform is free for end-users, their access is subsidized by advertisers. In Google’s and Apple’s app stores, end-users can download a variety of apps for free, but developers are charged a 30 percent fee over any monetary transaction.

      A platform company’s options in designing a business model are dependent on a number of economic variables that differ from platform to platform and from market to market. These variables can include a company’s primary sources of revenue and profit and/or industry norms.

      We already briefly touched upon the first variable, a platform’s primary business model. How a platform generates revenue determines its strategic orientation and its ability – or inability – to grow. As we have seen, the constant maneuvering on the part of the platform directly impacts complementors. For instance, it matters greatly which side – end-users or complementors – a platform favors at which time. Consider Google: in both its YouTube and Search businesses, it has shown a consistent inclination to appease advertisers over end-users or content creators (Caplan & Gillespie, 2020; Rieder & Sire, 2014).

A second variable impacting a platform’s pricing decisions are the actions of competitors and industry norms. Given how the digital media economy has evolved with its provisions of the proverbial “free lunch,”

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