Abstract
Risk is often an implicit theme in platform studies and is rarely made explicit in the analysis of platform power. The increased dependencies created by digital platforms and imposed on their complementors—the firms that provide the goods and services that attract users to digital platform ecosystems—can make risk harder to discern. Complementors like the game publisher Playtika that specialize in socially marginal commodities, like free-to-play gambling apps, make for a salient case study in how risk is built directly into the platform-complementor relationship. We use institutional analysis to conduct a close reading of Playtika's risk reporting in its financial disclosure documentation (e.g., annual reports) and investor relations communications, uncovering three distinct categories: financial risk, infrastructural risk, and regulatory risk. Taken together, this collection of institutional risks speaks to how platform governance places constraints on Playtika's business operations. We argue that risk is built directly into the complex operationalization of platform power, thus making it imperative to outline explicitly how it is differentiated between platforms and their complementors. Ultimately, we position Playtika's work to overcome institutional risks as representative of the volatile and asymmetrical power relations that shape the wider platform economy.
Introduction
In January 2021, the social casino firm Playtika launched its initial public offering (IPO) on the NASDAQ, reaching an $11 billion USD valuation by the end of its first day of trading (Takahashi, 2021). During the promotional campaign for its IPO, Playtika put itself out there as a top-tier game development firm destined for rapid growth. But underneath the hype, there was one detail that had gone unnoticed—this was not Playtika's first attempt at becoming a public company (Ross and Nieborg, 2021). Playtika's owners, the Chinese consortium Alpha Frontier, originally wanted Playtika to be listed on a Chinese stock exchange, but this was held up by government regulators concerned that its popular casino-style or “social casino” apps like Slotomania and Caesars Slots constituted illegal gambling (Ye, 2020). Despite Playtika's focus on new game genres and data analytics, Playtika was flagged as violating China's strict regulations on the distribution of gambling content, and its listing was subsequently blocked.
Playtika has consistently positioned itself as “not a gambling company” (Schechter, 2014) even though it was previously owned by Caesars Interactive Entertainment, an online entertainment division of the Caesars casino chain. Despite Caesars selling Playtika to Alpha Frontier in 2016, the popularity of Playtika's social casino apps and its past association with a major casino firm still tie it to the gambling industry. By relying on apps that facilitate “gamble-play” (Albarrán-Torres, 2018)—content that blends games and gambling—to break into the competitive mobile games market, Playtika has also opened itself up to increased regulatory scrutiny. This scrutiny is not limited to whether or not its apps violate state gambling laws but extends to the relationship between Playtika and the platforms that distribute its apps. Since Playtika relies exclusively on digital platforms for distribution, marketing, and monetization, this corporate relationship creates new forms of corporate risk, not just financially, but also at the infrastructural and regulatory levels. This is because risk—just like power—has become a much more diffuse problem in the platform economy, requiring close examination and unpacking to understand how it is managed in the context of digital platforms (Nieborg et al., 2024). As a case study, Playtika gives us the opportunity to make explicit the institutional relations of risk and volatility that are often left implicit in critical analyses of platform economics and platform power (van der Vlist and Helmond, 2021; van Dijck et al., 2019). Seen in this light, Playtika is a salient case study in how so-called complementors—the third-party firms that provide the services that bring users and revenue to digital platforms (Gawer, 2021)—must continually navigate significant challenges and uncertainty imposed on them by their platform partners.
To further unpack the notion of risk, instead of analyzing it as being unique and specific to Playtika, in this article, we position ourselves in the political economic tradition where risk constitutes a broader “socioeconomic relation” (Bilić and Prug, 2021) that is inherent to platform-complementor dependencies. We argue that corporate uncertainty, challenges, and threats shape much of Playtika's decision-making as well as how those decisions are discursively positioned to speak to investors, the business press, and sometimes the public (Dror, 2015). To analyze this discursive work, we apply an institutional analysis to Playtika's financial disclosure documentation. This method, grounded in critical political economy, takes annual reports, quarterly reports, investor presentations, and transcripts of investor calls as its units of analysis. These materials extensively disclose potential threats, as perceived by its executives, to a business’s ability to grow and innovate (Bilić and Prug, 2021). Crucially, the impetus behind our argument is that in the case of Playtika, much of this threat comes from its reliance on digital platforms.
Through our analysis, we identify three distinct categories of risk faced by Playtika in its role as a complementor: financial risk, infrastructural risk, and regulatory risk. These three categories emerge from our close reading of the risk reporting sections of Playtika's financial disclosure documentation as well as statements made in their investor communications. As we will elaborate on further in this article, financial risk denotes the ways that digital platforms are able to intervene in and curtail Playtika's corporate growth. Infrastructural risk, then, relates to how the means of distribution, access to data, and technological resources that Playtika relies on for app production and distribution threaten its ability to retain (i.e., market) and monetize the users of their apps. Finally, the company's close ties to the gambling industries invite increased legal and regulatory attention, from both state jurisdictions and via strict platform governance frameworks. Taken together, this collection of institutional risks speaks to how platform governance places constraints on Playtika's business operations. Before we conduct our institutional analysis, we start by theorizing how risk can be used as an analytic for understanding digital platform economics and do so from a political economy, economic sociology, and platform studies perspective. We argue that risk is built directly into the complex operationalization of platform power, thus making it imperative to outline explicitly how it is differentiated between platforms and their complementors. Ultimately, we position Playtika's work to overcome institutional risks as representative of the volatile and asymmetrical power relations that shape the wider platform economy.
Theorizing risk in digital platform economics
In the context of studying digital platform economics, risk is not always a consideration when analyzing relations between platforms and their complementors. Although risk is built into the business operations of any company and, therefore, also digital platform companies, it is not often analyzed as a foundational component of how corporate relationships between platforms and complementors are organized. That is to say, risk is often an implicit theme in platform studies but not necessarily connected to the ways in which digital platform companies wield institutional power. To address this gap, we argue that risk is an integral element of platform power. By elevating risk as our analytic, we aim to contribute a more holistic understanding of the power asymmetries and unequal relations inherent in digital platform economics. To begin theorizing risk in platform economics, we conduct an overview of three bodies of literature that address risk both explicitly and implicitly in relation to the operationalization of power by digital platforms: the political economy of communication, economic sociology, and critical platform studies. In political economy, risk is discussed as a core operational logic in the commodification of culture; it is an inherently risky business (Hesmondhalgh, 2019). However, this model of risk can be too static. Therefore, we draw on economic sociology, particularly Caliskan et al.'s (2025: 309) study of digital platforms like Google, to consider the process of “stacked economization” that brings together networks, devices, and actors into a set of complex and interrelated “economization modes.” After that, we turn to critical platform studies to evaluate how risk has become integrated across the different networks of platform power, creating increased volatility and contingency (Poell et al., 2022). Before introducing our methodology, let us unpack these approaches.
The political economic approach to risk
The political economy of communication has closely analyzed how the high investment of capital required for media production carries a significant amount of financial risk. This is because “the decision to finance entertainment is always a gamble” (Mirrlees, 2013: 66). It is not certain if a TV show, film, or game is going to be a hit and pay off. Historically, the cultural industries have been heavily blockbuster-driven, with a small percentage of big hits subsidizing the losses from those products that do not achieve success in the market (Hesmondhalgh, 2019). These high up-front costs mean that there is a great deal invested in ensuring that as much value as possible is extracted, or “captured” as economists would say, along the circuits of production, distribution, and consumption (Mirrlees, 2013). This typically means, for example, pursuing high levels of vertical and horizontal corporate integration to create higher barriers to market entry or to push out potential competitors that would represent a threat to the control of well-positioned firms in the communications market (Fitzgerald, 2015). Political economists are particularly attentive to how “conglomeration and corporate synergy” strategies (Hardy, 2014: 91) emerge from the need to maximize control over their chosen market and constrain attempts by other firms to push into their markets. These strategies are primarily studied for their efforts to expand profit and protect against financial risk. To be sure, conglomeration as a corporate strategy is still widely pursued by both incumbent transnational media conglomerates, such as Disney, as well as platform companies, such as Amazon and Tencent (Jia et al., 2022).
A common strategy to recoup the high cost of media production has been to attract advertising revenue. Political economists have focused on how advertising practices have evolved in conjunction with changing industry practices (Hardy, 2024). Platform companies like Google and Facebook—as well as some highly popular creators on platforms like YouTube (Joseph and Bishop, 2024)—derive substantial revenue from commodifying large groups of users by selling their attention to advertisers. In contrast, our object of study—Playtika—derives most of its revenues from in-app purchases and cannot look to advertising to recoup costs. Instead, Playtika must invest significant resources to grow and retain an audience that can be monetized by enticing them to spend money on virtual goods. The decision not to primarily monetize audience attention changes the dynamics of financial risk for Playtika as they are deeply embedded in and affected by the mechanisms of app store infrastructures. Like other complementors on digital platforms who primarily rely on in-app revenue, the costs associated with running an in-app business have increased because of the mandatory payment of platform fees (nominally 30%) on all transactions. As such, platform ownership is tied to what Srnicek refers to as the “value appropriation” (Srnicek, 2021: 29) process by platform companies like Apple, Google, and Meta, who make these fees a condition of accessing their app stores and app development tools.
Platforms have another competitive advantage over complementors through their ability to pass on significant costs to app developers and publishers, forcing them to take on more of the risk. As Fitzgerald (2015: 81) notes regarding mobile game development: “in exchange for reduced barriers to entry and a higher degree of creative autonomy…app-based game developers assume all the development costs and risks.” While a television network might share in the costs of production through “deficit financing” (Lotz, 2019) or a game publisher may finance an app developers’ distribution and marketing costs (Kerr, 2017), platforms have largely avoided taking on these direct costs themselves. This means platforms can derive a substantial portion of their revenue from complementor firms—as well as commodify the audiences they bring in—while having very little stake in the outcome.
Economic sociological approaches to risk
The political economy of communication offers a great deal of insight into the risks and uncertainties inherent to media and cultural production (Winseck, 2024). However, some of its discussion of risk can be either too top-down or too static. Therefore, it is important to consider a view of digital platforms that is dynamic and strategically organized. For this expanded view, we turn to economic sociology—specifically the work of Caliskan et al. (2025)—who argue for thinking of digital platforms as being organized around the dynamic process of “stack economization.” Extending work on crypto exchanges (Caliskan, 2023) and Google's advertising ecosystem (MacKenzie et al., 2023), Caliskan et. al's (2025) framework models digital platforms a set of arrangements or computational “stacks”: economic exchanges (markets); users directly trading with each other (barter); or receiving a part of a platform service for free in exchange for another source of value (gift). This more comprehensive approach is contrasted with the “interface model” (2025:308) popularized by management scholars, in which platforms merely coordinate and cross-subsidize economic exchanges. Thus, platforms do not simply facilitate transactions but also facilitate a wide range of different activities among developers, business sellers, and users, all of which are considered to be platform “actors.”
While risk is not an explicit focus of “stack economization,” economic sociologists do point out that uncertainty is built into the organization of digital platforms. It arises due to the “contingent coordination” (2025:309) among platform holders and platform “actors,” as their interactions continuously evolve to address new problems and unanticipated needs. As a result, platform actors are able to apply novel strategies that can help them mitigate their risk on digital platforms or organize themselves in a way that can enact changes in a platform's regulatory framework. What we take away from this understanding of platform power is that any analysis of risk and uncertainty must account for platforms as continuously evolving architectures. From this point of view, risk and uncertainty are not just transactional, as in some critical political economy approaches, but a mutually constitutive process that is part of how infrastructural and regulatory issues are negotiated on digital platforms. This accords with an institutionalist approach in political economy that acknowledges the role of uncertainty as a key part of economic risk (Winseck, 2024). Playtika is an example of risk-taking as it aimed to exploit a regulatory gap in platform governance by hybridizing gambling with free-to-play game design, thereby enabling the “social casino” to become both a distinctive genre and lucrative segment of the platform economy.
We must note that our own analysis only partially embraces an economic sociological perspective. Whereas economic sociology considers the broader strategies and actions of individual end-users, creators, and sellers active on digital platforms, our approach, by contrast, is more focused on the specific institutional relations between digital platform companies and complementors. We do so because Playtika's reliance on app store infrastructures creates a different set of dependencies compared to platform-dependent economic actors, like gig workers (Vallas and Schor, 2020) and individual ad buyers (MacKenzie et al., 2023), which have been a focus of economic sociology case studies of digital platforms. To put it another way, while Playtika has been able to help develop social casino games as a distinctive category, the company has had little control over the recommendation or discoverability systems that can determine success or failure on the Apple or Google Play app stores. However, we do appreciate and consider Caliskan et al.’ (2025: 320) call for avoiding “platform reductionism” to further nuance the asymmetries of platform power.
Platform studies approaches to risk
The political economy of communication has been particularly attentive to the financial implications related to corporate risk and uncertainty, while economic sociology further nuances the strategic dynamics constituting platform markets. Yet to fully account for how complementors are unequal partners vis-á-vis digital platforms, further attention on the institutional implications of infrastructural and regulatory risk in the platform economy is required. After all, digital platforms have been able to dynamically organize themselves within “infrastructural nodes of power” (van Dijck et al., 2019: 9). While digital platform companies like Meta, Google, Apple, and Tencent signal concentrated levels of corporate power, their institutional and infrastructural power is distributed across various social networks, app stores, and singular “service-based” platforms (van der Vlist and Helmond, 2021). Even though there is extensive analysis of how platform power is increasingly present across industries, society, and even the state (van Dijck et al., 2018), infrastructural and regulatory risk is rarely forwarded explicitly as an analytic to discuss the politics of platform economics.
That being said, one area in platform studies where risk is addressed explicitly is in the case of uneven and sometimes arbitrary content moderation practices of platforms (Gillespie, 2018). The value platforms add is moderation; that is, to flag content as “risky” or not “advertiser-friendly,” with YouTube's “Adpocalypse” being a recurring example where this approach asserted itself (Caplan and Gillespie, 2020; Joseph and Bishop, 2024). These close examinations are relevant to understanding the “platformization of cultural production” (Poell et al., 2022), in which risk is not necessarily a primary analytic category. As noted earlier, risk also has structural characteristics that go beyond individual end-users or creators; its manifestation affects groups of firms, such as game developers, that integrate infrastructurally with digital platforms to be able to distribute content. Therefore, we focus on complementors in order to make the infrastructural risks of the platform economy more explicit.
Complementor is a term with origins in management studies (Gawer, 2021), denoting those third-party or partner firms that provide complementary innovations—that is, content or services to diversify a platform's offerings, such as game apps. Poell et al. (2022) elaborated on the complementor concept, bringing it into dialogue with platform studies in order to foreground a critical perspective on platform power. In this view, complementors are given room to grow, but only at the discretion of platform operators. At the infrastructural level, platforms continuously reconfigure the circumstances under which complementors operate. For instance, one change in the way a platform-provided Software Development Kit (SDK) collects data can fundamentally alter a complementor's ability to reach and commodify users. Thus, as complementors, app developers like Playtika are exposed to significant volatility and uncertainty as a result of their platform dependency.
To put this another way, infrastructure has become a key focus across media and communication studies, encompassing a wide range of investigations into the foundational structures that undergird communication as well as broader social systems. Hesmondhalgh et al. (2023) have raised concerns about the concept of “infrastructure” being applied to too many distinct apparatuses and social phenomena, diluting its original meaning and analytical power. Sharing this concern, we focus on “platform infrastructure,” a term used by Hesmondhalgh et al. (2023) to characterize the embedded protocols and technologies (e.g., SDKs and APIs) that facilitate interoperability and influence complementors’ access to users (Poell et al., 2022). In their study of the infrastructural aspirations of digital platforms, Plantin et al. (2018: 298) note that while developers derive substantial benefit from having access to a platform’s software, data, and reach, they are also inherently dependent on “the platform's “conception of users, functionality, and design values.” As a result, platform dependency reshapes how complementors engage in cultural production across a wide range of cultural industry segments.
In sum, platform studies scholars have pointed out the destabilizing and contingent effects of the direct application of infrastructural and regulatory power to complementors and users. However, how such power translates into risks faced by complementors is not always clearly articulated. Therefore, we argue that making risk explicit requires an empirical investigation into how platform complementors, like Playtika, navigate and mitigate risk as part of their institutional relationship with digital platforms. Next, let us introduce our methodology to analyze how risk manifests in the corporate operations of platform complementors.
Method—institutional analysis
Something that tremendously aids our efforts in studying risk in the digital platform economy is that risk reporting is an explicit legal requirement for all annual and quarterly reports filed with the US Securities and Exchange Commission. Due to the legal liabilities that can result from improper disclosure, the risk sections of public companies tend to be extensive, covering all risks perceived and potential—from the loss of high-value personnel to the impact of relying on third-party services for distribution (Bilić and Prug, 2021). As such, financial disclosure documentation is part of a larger discourse of investor relations communications that also includes quarterly investor calls, presentations, and company promotion through trade press.
Ultimately, the goal of these communications is to impress upon current and potential investors that the firm in question has secured a “financial value proposition” (Elmer, 2017), where dynamic, scalable “growth” is in the process of being achieved. These disclosures center on risks, adding context to potential threats and challenges to business operations. Thus, this documentary material comprises a highly relevant set of sources for developing a clear picture of how risk is both articulated and mitigated by platform-dependent complementors like Playtika. That said, financial disclosure documentation and investor relations communications are never to be considered neutral documents; large sections often act as promotional tools or may downplay a firm's liabilities (Dror, 2015; Nam, 2020). Institutional analysis—also articulated in political economy of communication as the “institutional approach” (Wasko, 2004)—is a critical method for analyzing financial data and business communication with a long history in political economy. This approach analyzes corporate ownership, consolidation, control, and the commodification of content and users across the media and communication industries. We use this method to explain Playtika's risks as delineated in its financial disclosure documentation and investor communications.
In our analysis, we draw on Corrigan's (2018: 2575) approach of “burrowing down” and “listening in” to code our data; the former involves delving into available financial data, creating charts or tables that help visualize a firm's operations. In the case of Playtika, we focused not only on its financial metrics but also on key indicators reported as “non-financial performance metrics,” such as daily active users, monthly active users, and average revenue per daily active user, to track how it communicates its potential value. Part of our close reading of Playtika's financial documentation includes the S-1 registration statement, also known as a prospectus (Elmer, 2017), which is provided to investors before a company's Initial Public Offering (IPO). Analyzing this information furnished some significant disclosures from Playtika's days as a privately held company and helped us to better contextualize its approach to financial and infrastructural risk. Second, “listening in” can be seen as a form of discourse analysis that pays attention to how corporate elites frame their activities, which is helpful in further understanding Playtika's approach to risk disclosure (Corrigan, 2018). By “listening in,” we were able to better contextualize how external factors like the COVID-19 pandemic or changes to a platform privacy's policy affected the company's performance indicators.
Lastly, our analysis should be considered as a structural one that first and foremost focuses on Playtika's institutional position as a complementor in the platform ecosystem. This means that our analysis does not address the specific experiences of users who play social casino apps and how they conceptualize the way risk manifests in their own lives. Likewise, our analysis also does not include questions pertaining to the labor of game developers within these firms, but instead how Playtika responds to the specific corporate pressures exerted on them by digital platforms.
Between the games and gambling industries: Playtika's rise as a platform complementor
To contextualize our analysis, let us situate Playtika's rise as a platform complementor historically. The company's ability to break into the platform economy was enabled through a combination of external capitalization by investors and incumbents in the games and gambling industries and by taking advantage of the so-called free-to-play monetization model to distribute gambling commodities that would fly under the radar of regulators. This historical context helps provide the necessary circumstances under which Playtika has been especially attentive to risk in its relations with digital platforms.
Playtika was founded in Herzliya, Israel, in 2010 by Robert Antokol and Uri Shahak. Rather than being completely new to the games and gambling industries, both founders had experience as well as ties to both industries. Although Israel is not as prominent a player in the global game industry compared to, for example, the USA, Canada, China, or South Korea, the founders of Playtika had industry experience and “insider” advantages. Antokol had previously run a game studio called Cmate SA, a developer of casual games for handsets and cellphones that was eventually acquired in the mid-2000s by Oberon Media. Playtika's co-founder Uri Shahak had experience in digital gambling, working for the popular online casino company 888 as its senior games manager (Tsipori, 2011). This pedigree in both the games and gambling industries explains why Playtika's first and most prominent game was Slotomania—a mobile game that combines simulated slot machines with design elements and mechanics popularized by social and casual mobile game apps (Albarrán-Torres, 2018). Thus, Playtika was a well-connected start-up aware of the challenges of producing and distributing gambling games online.
After less than a year in business, Playtika was acquired by Caesars Interactive Entertainment, an online venture of the Caesars casino chain. Playtika's appeal to the casino behemoth was its ability to distribute gambling-style games online at a time when the legality of online gambling was still in question (Schechter, 2014). For context, to be taxed and regulated as a gambling product, it must have chance (no control of the outcome), consideration (money paid), and a prize (something of value won) (Rose, 2014). Since social casino apps, like other mobile app games, are distributed for free and offer only in-game prizes with no outside monetary value (King et al., 2019), they have been able to avoid gambling classification and thus regulation (Ross and Nieborg, 2021). Furthermore, since social casino apps are technically not a form of gambling, they do not need to follow the strict rules governing odds and the payout of winnings, which are necessary in electronic gambling machines (Rose, 2014).
Caesars’ investments in Playtika proved to be crucial, allowing it to expand as a social casino company. Yet, future growth necessitated finance capital. In 2016, Playtika saw another round of funding—being capitalized at $4.4 billion USD—when it was acquired by Alpha Frontier, a consortium of Chinese companies led by Yuzu Shi, the CEO of Chinese gaming firm Giant Network Group (Baker and Lampert, 2016). This influx of cash paved the way for a round of European acquisitions of several casual game developers like Seriously, Wooga, and Pacific Interactive. It also allowed Playtika to focus on other casual gaming genres beyond the social casino genre. However, in 2020, after being denied a listing on the Chinese stock exchange due to the aforementioned concerns over illegal gambling, Playtika went public on the NASDAQ. With this historical overview in mind, let us consider how Playtika mitigates risks from its varied platform dependencies and articulates this for investors.
Analysis
Analyzing financial risk
A consistent theme across Playtika's financial disclosure documentation is the financial pressures it faces from aligning its corporate aspirations with those of digital platforms. When going public, Playtika stated that 80% of its business was derived via app store distribution, specifically Google, Apple, and Facebook (Playtika, 2020), making these platforms the primary monetization avenue. Thus, any changes or fluctuations to these third-party platforms, even minimal ones, imply instant financial exposure. A risk mitigation that Playtika deploys is to incentivize players to use its so-called “direct-to-consumer” platforms (Playtika, 2023b) as an alternative platform infrastructure. This includes a webstore available on Playtika's main website where users can play its popular titles including Slotomania, World Series of Poker, and June's Journey. From the same website, users can also download some of these game apps directly onto Android phones, thereby bypassing sanctioned downloads via the Google Play app store. Apple does not provide this functionality. By these alternative distribution channels, Playtika can both directly “fulfill virtual items,” thus collecting more of each purchase, and also “have the discretion to establish the virtual items’ prices” (Playtika, 2024: 67), meaning that they can offer price points and special offers that are otherwise disallowed on app stores.
Playtika's consistent promotion of its direct-to-consumer platforms in its annual reports (Playtika, 2024, 2025) as well as its investor communications (Playtika, 2023a, 2024) is a direct result of the significant platform fees levied on Playtika. Looking through its disclosure documentation, we can trace the effective distribution and monetization costs charged by Google, Apple, and Facebook. In Playtika's S-1 registration statement, the company provided a breakdown for the revenue it generated on each platform between 2017 and 2019; the period before Playtika became a public company. Since setting up app stores, platforms have charged a nominal 30% fee for every in-game transaction. This has become a core part of what Srnicek (2021: 38) refers to as “infrastructural rents” that fuel platform profit margins. Playtika states that: “Payment processing fees and other related expenses for in-app purchases made through our proprietary platforms are typically 3–4%, compared to a 30% platform fee for third party platforms. We generally expect the cost of revenue to fluctuate proportionately with revenues” (Playtika, 2020: 78). These concern fees put on in-app purchases (e.g., of virtual currency), whereas advertising revenue is not subject to platform fees. In table 1, we list Playtika's gross revenues on all three major third-party platforms, as well as the 30% fees.
Playtika's gross revenue and fees extracted per platform, 2017–2019.
Note: Gross revenues are in millions of dollars USD and taken from Playtika's S-1 registration statement (Playtika, 2020). Platform fees are in millions of dollars USD and are calculated based on a nominal fee of 30% taken by Apple, Google, and Facebook on their app stores.
What our overview in Table 1 shows is that between 2017 and 2019, Playtika paid a combined $314.4 million, $391.83 million, and $469.5 million in platform transaction fees. This is their highest cost of revenue line item. Notably, in some cases, this is double what the company spends on research and development in the same period. These rents also represent a form of financial risk that puts a 30% downwards pressure on their entire operations, which they must continually mitigate, regardless of how much or how little revenue they generate from in-app purchases. Since going public in 2021, Playtika has made efforts to increase purchases made through its direct-to-consumer platforms to more than 33%, demonstrating the direct financial value of platform-independent distribution (Playtika, 2025). Despite Playtika positioning its focus on direct-to-consumer as a competitive advantage to investors, it remains deeply reliant on app store distribution for a majority of its revenue. The ubiquity and reach of app stores and social networks will likely keep Playtika tied to platform distribution and monetization infrastructures in the long-term, even as they try to incentivize their users to use their in-house, off-platform services instead.
Analyzing infrastructural risk
As discussed earlier, platform infrastructures shape how apps are developed, distributed, and monetized. While developers like Playtika can access global audiences through the Apple App Store or Google Play, they must follow the platform's directives in terms of pricing models or app design. In response, Playtika has sought to gain infrastructural independence by building its own proprietary infrastructures. In its first call to investors after Playtika became a public company, Slotomania is said not to be “a game” but “a platform” (Playtika, 2021). At the heart of Playtika's claims are its proprietary data analytics suite, Playtika Digital Studio (originally called “Boost”), which is said to have the ability to analyze player behavior in order to increase overall player spend. This process of user “datafication” is, of course, common among all platforms and game apps (van Dijck et al., 2018). However, there is more at stake for Playtika when it makes these claims. Ultimately, it needs to demonstrate to investors that it can increase “customer lifetime value,” a key performance indicator in the mobile games space where the overall spending of a user becomes greater than the cost to acquire them. One way to do so is to build in-house technology. Additionally, we argue that by setting up their own data analytics operations, Playtika can claim a level of infrastructural independence. However, by virtue of being integrated with platforms, Playtika acknowledges that it is vulnerable to platforms’ shifting priorities, ranging from changing how users are acquired (i.e., attracted via advertising) to being forced to grapple with near-constant and often unexpected technology changes (Playtika, 2020). To address this, Playtika positions itself as being able to overcome this risk, or even control its audience, regardless of what game they are playing or where they are playing it, thus delivering revenue stability and exponential growth.
Claims such as these appear throughout Playtika's financial disclosure documentation and investor relations communications: “Once we acquire games, we enhance the scale and profitability of those games by applying our live operations and…the Playtika Boost platform” (Playtika, 2020: 99). Playtika Digital Studio software is meant to achieve its results by slotting individual players on “journeys” that keep them playing, potentially for years. User data rather than game design is put forward as what will bring forth increased revenue and higher returns on investment. This claim is reiterated in an interview where Antokol states: “We know exactly what the player is going to do, we know exactly when the player is going to pay or not pay” (Takahashi, 2022). Playtika claims that its own proprietary platform can latch onto moments of impatience or dedication to increase its revenue. Despite these claims, as Caliskan et al. (2025: 319) note, user activity is often much complex and not predictable and at times can lead to a “subversion” of intended infrastructure. While our institutional analysis did not pick up an explicit subversion of Playtika's data infrastructure by users, a more nuanced picture emerges when we scrutinize Playtika's user metrics.
While many game studios rely on third-party data analysis software, Playtika has built these capabilities in-house, with the idea that it is delivering the real-time data that it needs to overcome the infrastructural uncertainties of digital platforms. Regardless of how an app store may change, building out its own technology allows Playtika to better analyze, monitor, and retain its user base. Aspirational corporate goals such as these raise a critical question: Has Playtika actually been able to successfully control its audience and deliver consistent growth in revenue? A quick review of Playtika's user and monetization metrics, shown in Table 2, belies this narrative.
Playtika's average user counts and revenues per user, 2017–2024.
Note: User totals derived from Playtika's S-1 registration statement and annual reports for 2021–2024 (Playtika, 2020, 2022a, 2023a, 2024, 2025).
Not visible in Table 2 is a moment of drastic infrastructural breakdown in the platform economy, one that demonstrates how platform infrastructures directly impact the infrastructural dependence among complementors (Nieborg and Poell, 2025). We are talking about the introduction of new privacy provisions by Apple on its iOS platform. In 2021, Apple automatically opted mobile phone users out of the identification for advertisers (IDFA) functionality, a way for advertisers to track users across apps. That is, IDFA gave app developers, such as Playtika, a device identifier, which was used to more accurately target users with personalized ads. For app developers specifically, IDFA served as the key utility to help them identify players who stopped playing and offer them incentives to return to the app. This scenario of infrastructural breakdown reaffirms Hesmondhalgh et al. (2023)’s main point about the “discipline” imposed by platforms—the possibility of Playtika being able to wrest more control of its audience is foreclosed by the fact that its technologies are necessarily integrated with Apple's iOS (platform) infrastructure. Playtika tried to subsequently downplay the significance of IDFA's impact on its operations—tying their ability to weather these incoming changes to its aforementioned data analytics capabilities (Playtika, 2022b). Ultimately, Playtika was affected, as was every app developer (Nieborg and Poell, 2025), serving as a vivid reminder of the impact of infrastructural platform power.
Back to Table 2, the effect of IDFA deprecation can be seen when surveying Playtika's performance, from 2017 to going public in 2020, and the years since. Playtika reached a peak in monthly active users in 2020—this was a period when tech and game companies saw a huge boost in overall user engagement and revenue due to the COVID-19 lockdowns. There has been a steady decline in its user base since, even as it has acquired other game companies. To offset this decline, Playtika has been able to increase the average spending per user from its already active user base, but this has come amid inconsistent and declining metrics for monthly users. This pattern of decline indicates not only internal challenges—like dissatisfaction with the playstyles offered or monetization of apps—but also external ones. In addition to user privacy changes, Playtika is also heavily affected by app store recommendation systems that allow (some) apps to rise to the top, while permitting the vast majority to fall into obscurity (Morris and Morris, 2019). The declines in users and revenue have been significant enough that in 2022 Playtika laid off 650 staff and suspended all new game development until it could reverse the trends of user decline in its most popular game apps (Habib-Valdhorn and Mandelbaum, 2022). Despite its claim to be able to exert more control over its users through superior data analytics, the data necessary to provide these same analytics is rooted in platform infrastructures.
Analyzing regulatory risk
Playtika's vulnerabilities extend beyond financial and infrastructural dependencies due to Playtika's origins as a developer of free-to-play gambling commodities. In our analysis, we understand regulatory risk as representing internal and external forms of platform governance (Gorwa, 2019), which complementors are subject to. Here we include both a platform's internal guidelines and frameworks (e.g., terms of service) and external regulatory frameworks they execute, think of state-based regulation on gambling, which affect the distribution and design of Playtika's game apps. This understanding of institutional pressures further underscores the contingency of apps produced by complementors, who must continually make changes to avoid being de-emphasized in app stores or removed entirely (Gillespie, 2022). Even considering the recent legalization of online sports betting and app-based digital casinos in North America, Australia, and a number of European countries, Playtika's ties to social casino still pose a systemic risk. Case in point: being blocked from the Chinese stock exchange. This is why Playtika has historically tended to be circumspect about its connection to the gambling industry.
Although Playtika downplayed its gambling connections in public statements, in its corporate disclosures, it is more candid about the risks free-to-play gambling presents to its core business model, as well as the overall institutional challenges it faces from platform rules and regulations. Playtika acknowledges this by highlighting increased concerns over the “blurring of lines between gambling and video game products” (Playtika, 2020: 24) that result in calls for increased controls not so much over the ability to engage in real-money gambling, which is impossible in social casino apps, but over gambling content. The resulting threats to their business include discontinued platform access, higher platform fees, abrupt technical changes, content being blocked, or being “out of compliance” with a platform's terms of service (Playtika, 2020). In its 2023 annual report, Playtika reported that due to gambling regulations, Google blocked Slotomania, Caesars Slots, and World Series of Poker from being distributed in 13 countries in the Middle East (Playtika, 2024). In 2024, Slotomania was briefly banned in Indonesia and then reinstated (Playtika, 2025). Playtika also lists litigation across jurisdictions in their most recent annual reports, such as pending lawsuits in Israel, and also in US states like Tennessee and Alabama, over its apps violating gambling laws (Playtika, 2024, 2025). While Playtika's initial focus on social casino gave them a foothold in this genre, it has also exposed the company to platform rules surrounding games that were adjacent to, or included content related to, simulated gambling.
The overriding risk that is flagged in Playtika's disclosure documents is how legal scrutiny could force them to change how they operate their in-game economies, which is the key driver of their revenue. In 2019, Playtika, along with other social casino developers like Big Fish Casino and DoubleDown Interactive, came under increased scrutiny for its apps potentially constituting illegal forms of gambling. Various lawsuits were brought against all three developers and associated publishers in Washington State, accusing Playtika and the other social casino developers of violating the state’s gambling laws (Farivar, 2020). At stake was whether the digital currency offered in their games could constitute something of real value, one of the three variables necessary to be qualified as gambling, which could change the nature of how their games would be regulated. Playtika settled the lawsuit for $38 million USD (McAfee, 2021) and agreed to make changes to their social casino apps, such as allowing players to self-exclude—essentially ban themselves from the game apps (Weldon, 2020). These instances highlight the inherent power asymmetries between digital platforms and complementors—and, above all, to whom risk is downloaded. Google and Apple can profit, quite handsomely, we must say, from the distribution of social casino apps. At the same time, the legal exposure faced by digital platforms is easily mitigated “simply” by removing, blocking, or removing game apps. Despite trying to push into other genres and away from such risky commodities, Playtika still must contend with the uncertainties of being almost completely reliant on digital platforms.
Conclusion
In this article, we have conducted an institutional analysis of Playtika, a prominent developer of social casino apps, to demonstrate how risk is operationalized in digital platform economics and structures relations between platforms and complementors. Through an empirical investigation of Playtika's financial disclosure documentation and investor relations communications, we have noted volatile, asymmetrical power dynamics of the platform economy, revealed in the ways that financial, infrastructural, and regulatory risks are embedded in how complementors connect to digital platforms. In particular, we have aimed to center risk as an analytic in the study of platform power, addressing gaps in economic and technical analyses of platforms where risk is often undertheorized or left implicit. Playtika is a representative case study because of how its focus on legally gray games and gambling commodities has both deepened its risk awareness and led it to adopt specific strategies to overcome its institutional burdens. By bringing together financial and user data, we have been able to develop an empirically rich picture of complementor firm behavior under conditions of platform dependency. Playtika's response has been to double down on corporate acquisition and data analytics that have yet to provide the exponential growth so prized by investors.
Playtika's convergence of games and gambling is indicative of a series of specific approaches to mitigating risk on digital platforms. One that, perhaps, befalls those kinds of apps that are deemed subversive, transgressive, or illegal. Through its financial disclosure documentation, like the registration statement it filed for its IPO, to its annual reports and investor calls, Playtika explicitly highlights the costs and significant challenges it faces from relying on platforms for the distribution of its game apps and the majority of its revenue. Playtika's financial disclosure documentation, through its combination of financial and user metric data, and contextualizing “narrative elements” (Bilić and Prug, 2021) create a clear picture of the asymmetries between platforms and complementors. While complementors try to mitigate or overcome these risks, platforms have multiple tools at their disposal to curb the independence of their complementors. By centralizing control over key sites of financial and infrastructural integration (Poell et al., 2022), platforms ensure that complementors are rarely able to escape uncertainty and contingency. Seen in this light, Playtika is a microcosm of the unsustainable affordances of a platform-dominated ecosystem where platforms operate, like the “house” in a casino, determining “winners” and “losers” for their own benefit. As long as the platform economy is operationalized along the uneven distribution of risk, platform complementors will always be dealt a bad hand.
Footnotes
Acknowledgements
None.
Funding
The authors received no financial support for the research, authorship, and/or publication of this article.
Declaration of Conflicting Interests
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
