In Platform Capitalism, Nick Srnicek seeks to address what he sees as a profound oversight in the existing literature on digital capitalism. One set of contributions focuses on emerging technologies and their implications for privacy and surveillance but ignores the economic analysis of ownership and profitability. Another set critically analyses the values embodied in corporate behaviour but neglects the broader context of a capitalist system. A further set addresses the ills of the ‘sharing economy’ but fails to situate these in terms of broader economic trends. Finally, there are those which analyse the emerging economic trends in the technology sector but treat them in a way which is decontextualised from wider historical changes.
In contrast, he intends to offer “an economic history of capitalism and digital technology, while recognising the diversity of economic forms and the competitive tensions inherent in the contemporary economy” (loc 155). This involves “abstracting from them as cultural actors defined by the values of the Californian ideology, or as political actors seeking to wield power” (loc 166) and instead simply taking “major tech companies” as “economic actors within a capitalist mode of production”. Such an undertaking requires that we distinguish the technology sector from the digital economy. The former is relatively small, employing around 2.5% of the US labour force and contributing around 6.8% of the value added by private companies (loc 157). In contrast, the digital economy has taken on a systemic importance that is obscured if we analyse it on a sectoral basis:
we can say that the digital economy refers to those businesses that increasingly rely upon information technology, data, and the internet for their business models. This is an area that cuts across traditional sectors –including manufacturing, services, transportation, mining, and telecommunications –and is in fact becoming essential to much of the economy today. Understood in this way, the digital economy is far more important than a simple sectoral analysis might suggest. In the first place, it appears to be the most dynamic sector of the contemporary economy –an area from which constant innovation is purportedly emerging and that seems to be guiding economic growth forward. The digital economy appears to be a leading light in an otherwise rather stagnant economic context. Secondly, digital technology is becoming systematically important, much in the same way as finance. As the digital economy is an increasingly pervasive infrastructure for the contemporary economy, its collapse would be economically devastating. Lastly, because of its dynamism, the digital economy is presented as an ideal that can legitimate contemporary capitalism more broadly. The digital economy is becoming a hegemonic model: cities are to become smart, businesses must be disruptive, workers are to become flexible, and governments must be lean and intelligent.
His analysis locates the nascent importance of the digital economy against a backdrop of a “long decline in manufacturing probability” across a “sluggish production sector”. Digitalisation has been seized upon a set of mechanisms through which these problems might be ameliorated, leading to the growth of the platform as the business model best able to ensure returns from these emerging opportunities (loc 178). This represents a historicisation of the platform, drawing out the linkages between the contemporary platforms which dominate the breathless discourse of ‘disruption’ and earlier upheavals in capitalism which digitalisation played an (often under-acknowledged) part in. For instance, consider the technological prerequisites which allowed a transition from Fordism to post-Fordism, driven by a crisis of overcapacity and overproduction in global markets:
Companies were increasingly told by shareholders and management consultants to cut back to their core competencies, any excess workers being laid off and inventories kept to a minimum. This was mandated and enabled by the rise of increasingly sophisticated supply chain software, as manufacturers would demand and expect supplies to arrive as needed. And there was a move away from the mass production of homogeneous goods and towards increasingly customised goods that responded to consumer demand.
The point is not that technology was the agent of these changes but rather that it facilitated new ways of organising production in time and space. Recognising the political agency involved in the onset of neoliberal ‘reforms’ shouldn’t detract from an appreciation of the role technology played in allowing the reorganisation of production. Historicising the digital economy necessitates that we understand this interplay between digitalisation and financialisation from the outset, something which of course came to the fore with the dot com boom.
Astonishingly, nearly 1% of US GDP consisted of VC invested in tech companies at the height of the sector in the late 1990s, with 50,000 companies formed and over $256 billion invested in them. This influx of capital facilitated a ‘growth before profits’ model which is still familiar today, licensed by the expectations of immense wealth to be generated if enough market share was captured in a still hazily envisioned digital economy. This speculative boom led to a vast investment in digital infrastructure through which our contemporary digital economy was able to emerge:
This excitement about the new industry translated into a massive injection of capital into the fixed assets of the internet. While investment in computers and information technology had been going on for decades, the level of investment in the period between 1995 and 2000 remains unprecedented to this day. In 1980 the level of annual investment in computers and peripheral equipment was $ 50.1 billion; by 1990 it had reached $ 154.6 billion; and at the height of the bubble, in 2000, it reached an unsurpassed peak of $ 412.8 billion. 16 This was a global shift as well: in the low-income economies, telecommunications was the largest sector for foreign direct investment in the 1990s –with over $ 331 billion invested in it. Companies began spending extraordinary amounts to modernise their computing infrastructure and, in conjunction with a series of regulatory changes introduced by the US government, 18 this laid the basis for the mainstreaming of the internet in the early years of the new millennium. Concretely, this investment meant that millions of miles of fibre-optic and submarine cables were laid out, major advances in software and network design were established, and large investments in databases and servers were made.
Coping with the eventual crash through lowering mortgage rates in turn sowed the seeds of the future housing bubble. The story is one of a continued ‘asset-price Keynesianism’ where interest rate reductions were used to encourage continued rises in asset prices, seeking to encourage investment and consumption in the absence of deficit financed stimulus or any resurgence in the manufacturing sector. This low interest rate environment within the global economy has, argues Srnicek, provided “a key enabling condition for parts of today’s digital economy to arise” (loc 377) by reducing returns on a range of assets and encouraging investors to seek higher yields elsewhere. This is the context within which platforms emerged and were readily able to find vast investment, even in the absence of profitability. But what are platforms?
What are platforms? At the most general level, platforms are digital infrastructures that enable two or more groups to interact. They therefore position themselves as intermediaries that bring together different users: customers, advertisers, service providers, producers, suppliers, and even physical objects. More often than not, these platforms also come with a series of tools that enable their users to build their own products, services, and marketplaces. Microsoft’s Windows operating system enables software developers to create applications for it and sell them to consumers; Apple’s App Store and its associated ecosystem (XCode and the iOS SDK) enable developers to build and sell new apps to users; Google’s search engine provides a platform for advertisers and content providers to target people searching for information; and Uber’s taxi app enables drivers and passengers to exchange rides for cash. Rather than having to build a marketplace from the ground up, a platform provides the basic infrastructure to mediate between different groups. This is the key to its advantage over traditional business models when it comes to data, since a platform positions itself between users, and as the ground upon which their activities occur, which thus gives it privileged access to record them.
He identifies three key characteristics of platforms which are interconnected:
- Platforms mediate interaction between groups, providing an epistemic privilege in relation such interactions (and their potential monetisation). They are a mechanism for producing and extracting data from interactions.
- Platforms are reliant on network effects, such that their value to users grows in line with the number of such users. This leads to a ‘winner-takes-all’ or ‘winner-takes-most’ dynamic. The more a platform grows, the easier it is for it to grow more and the potential value of its epistemic privilege increases in line with this.
- Platforms often use cross-subsidisation to encourage more users on to the network, exhibiting a dynamic pricing structure often entailing free products and services because of the gains that can be made elsewhere. This helps encourage more users on to the platform.
The mediating character of platforms means they “gain not only access to more data but also control and governance over the rules of the game” (loc 636). With this comes the challenge of facilitating continued growth within a competitive environment, using cross-subsidisation and leveraging network effects to position oneself as the central platform within a domain of activity. However in spite of these shared characteristics, different types of platform have emerged within different spheres of social life. Srnicek identifies 5 types:
The first type is that of advertising platforms (e.g. Google, Facebook), which extract information on users, undertake a labour of analysis, and then use the products of that process to sell ad space. The second type is that of cloud platforms (e.g. AWS, Salesforce), which own the hardware and software of digital-dependent businesses and are renting them out as needed. The third type is that of industrial platforms (e.g. GE, Siemens), which build the hardware and software necessary to transform traditional manufacturing into internet-connected processes that lower the costs of production and transform goods into services. The fourth type is that of product platforms (e.g. Rolls Royce, Spotify), which generate revenue by using other platforms to transform a traditional good into a service and by collecting rent or subscription fees on them. Finally, the fifth type is that of lean platforms (e.g. Uber, Airbnb), which attempt to reduce their ownership of assets to a minimum and to profit by reducing costs as much as possible.
Much of his subsequent analysis concerns the competitive conditions under which each type of platform operates, as well as how this is shaping the emerging field and platform capitalism as a whole. I don’t agree with all of it but it’s definitely worth reading in full. I understand his core points to be the following:
- The necessity of ‘data extraction’ has a basis in a longer term crisis of profitability within capitalism. These are, in effect, technical fixes for a systemic deterioration afflicting manufacturing and platforms represent a formalisation of these into a new emergent form.
- The financial conditions under which this platform economy has been able to emerge were historically specific and should not be assumed to continue indefinitely. The infrastructure through which ‘data extraction’ become technically viable, as well as the emergence of platforms as operating businesses were deeply dependent upon this.
- Platforms as emergent forms exhibit characteristics which shape competition between them, as well as guiding the unfolding of the digital economy as a whole. The fierce competition between them, the competitive challenges specific to categories of platforms, the dynamics of network effects and the affordances of their cash hoarding are leading to platform isomorphism. They have an inevitable drive towards monopoly, further incentivised by the dynamics of accruing investment, which leaves them orientated towards becoming owners of the infrastructure of society.
The analysis of platform tendencies is probably my favourite part of the book. He talks about expansion of extraction, positioning as a gatekeeper, convergence of markets and enclosure of ecosystems. These are analysed in the final chapter in some detail and offer a convincing meso-level account of the claimed macro tendency towards monopoly or oligopoly.
Categories: Digital Sociology