While we have discussed network effects and pricing discretely, we did so for analytical purposes. In reality, they are interrelated, giving way to a dizzying number of economic issues and questions faced by all actors in platform ecosystems. Managing end-users and complementors is an inherently dynamic process (Gawer, 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.
Platform Evolution and Ecosystems
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.
The dynamic process of optimizing business models and a platform’s efforts to getting users on board can be understood as platform evolution – an idea that captures the fact that a platform company’s institutional relationships are contingent and subject to continuous change. Business scholars distinguish between different phases of platform evolution and a platform’s placement along a “lifecycle.” In the “launch phase,” business scholar Annabelle Gawer (2020) explains, “platforms prioritize growth through network effects.” In this stage, platforms can decide to provide complementors with a range of perks and incentives, ranging from free access to advanced tools, special accreditations (e.g., badges or certifications), to increased visibility on the platform (Helmond et al., 2019). After reaching a tipping point, platforms enter the “maturity” phase, during which time they become more selective with whom they partner. As such, a platform’s lifecycle impacts platform-dependent cultural production. For instance, recent research suggests that, in the aggregate, individual cultural producers tend to become less economically significant later in a platform’s lifecycle (Rietveld et al., 2020).
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).
One important “side,” or user group, that is integrated with platform companies when they mature includes various intermediaries that range from talent agencies to digital advertising companies. For example, if creators want to scale up or professionalize their operations, they can team up with what used to be called “multichannel networks”: companies that combine the role of agent, publisher, and marketing agency (Cunningham & Craig, 2019; Lobato, 2016). Likewise, game and news companies active on Facebook depend heavily on “data intermediaries” (e.g., data analytics companies, mobile marketing agencies, etc.), which are “an assemblage of human actors, code, software and algorithms that are active in shaping the circulation and integration of new forms of data” (Beer, 2018: 476). Complementors may opt to use Facebook’s built-in data tools, but, to make the company’s expansive Social Graph legible and to extend the platform’s capabilities, data intermediaries provide a wide range of complementary innovations not offered by Facebook (Helmond et al., 2019). It is important to note that many of the newly emergent platform intermediaries – from multichannel networks to dataanalytics companies – have been acquired by either legacy media conglomerates, such as Disney, or platform companies. These examples show that legacy actors in the cultural industries are far from obsolete. Rather, they tend to reposition themselves to provide services to platform-dependent cultural producers, often by integrating with platform infrastructures.
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.
The winner takes all?
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,