Thomas Poell - Platforms and Cultural Production

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,” a platform has to have a compelling reason to charge end-users for access. In 2008, when Apple’s app store opened its virtual doors, premium priced games were the norm; more than a decade later, the great majority of game apps adopted the freemium business model. At times, it is surprising how quickly new business models are adopted. The 30 percent fee structure Google and Apple charge app developers for in-app transactions has been in place since 2010; only recently has this pricing standard started to shift. 8These examples, though, are specific to Google and Apple. In China, for example, there is a much greater variety of app store operators, hardware manufacturers, and business models (Zhao, 2019).

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.

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.