The Digital Economy. Tim Jordan

nor Spotify, for example, are addressed in detail – they do qualitatively examine a multiplicity of digital economic practices, both successful and unsuccessful. This case study work will then be developed with concepts drawn from key debates in existing digital economy theory. The three debates examined are free labour, information surpluses as exploitation, and the breakdown of the producer/consumer divide. All three have substantial existing literatures, but Chapter 7 will show that, in the face of case study evidence and conceptual analysis, all three have significant failings needing further theorisation. Such a plan, it should be noted, means that there will be a significant shift in tone as the argument moves into theoretical debates. Whereas the case study chapters engage with the daily matters of digital economic practices, attempting to both follow and excavate how such practices are formed from different actions and perspectives among users, platform owners, platform workers and so on, examining existing theories of these practices involves conceptualisation. Issues such as the information drawn from freely given activities that users provide to social media, that in turn underpin revenue through advertising, will be repeatedly mentioned within the complexity and materiality of practices, and it requires a shift of emphasis to start drawing out such issues by exploring conceptualisations of them. Practices always involve ideas about what is happening within them, and ideas always refer to (even if obliquely) and rely on a sense of relevant practices; in this sense the shift is one of emphasis from primarily diagnosing the meaning of economic actions in digital contexts to theorising across such contexts how recurrent actions are structured and may be conceived.

      This move to conceptualisation will provide the basis for a model of digital economic practices to be proposed through three linked divisions – value, property and profit – to be set out in Chapter 8. The first two divisions address the creation of a value that is realised by collective activities, such as search or gaming, linked to different forms of information property. Once a digital platform instantiates such a connection, it becomes possible for the third division of profit to be added through a monetisation strategy. Three main monetisation strategies are identified: targeted advertising, disintermediation and reintermediation, and rent not buy. Within this model, the possibility always remains that a digital economic practice may refuse to seek monetisation for profit and instead offer information as a distributed property. In the latter case, radical options open up for digital economic practices that offer information able to be used simultaneously and completely by everyone who can access it.

      Following this modelling of the digital economy, Chapter 9 will consider broad policy questions. The first key issue is to establish where a digital economic practice exists: what is the jurisdiction appropriate to any digital economic company? The argument is made that location can be defined by using the activities of platform users as these are located in places, instead of the information flows resulting from these activities as these are transferable across boundaries. Following this, policy issues around tax are examined, particularly in relation to taxes that derive from the places in which digital economic activities occur. The discussion also includes an examination of the possibility of micro-taxation. Third, the chapter addresses labour issues, particularly those arising in relation to platforms that monetise users freely given time in activities on a platform and to disintermediation monetisation strategies that avoid regulation (particularly regulation of the service providers associated with each platform). Finally, the more radical possibilities offered by information as a distributed property are explored in the context of debates over the information commons.

The final arguments of the book address how the evidence of the case studies and the model of the digital economy fit into wider discussions of the nature of twenty-first-century global economies. Digital economic practices depend on the collective activities and communities of users, and have managed to insert profit-making into the most intimate spaces of everyday life through these collective moments. The challenge and urgency of digital economic practices is to address this takeover, for profit, of socially essential and intimate activities, such as searching for information or making friends.

Notes

1 The Financial Times methodology can be found at www.ft.com/content/1fda5794–169f-11e5-b07f-00144feabdc0. The Fortune 500 gives the most recent available numbers but ranks companies by revenue. The figures come coded to thirty-eight economic sectors according to the FTSE/Russell Industry Classification Benchmark, a scale that is mirrored in the Fortune ranking (FTSE/Russell 2016). To decide on the top-level sectors I compared the classification used by FT and Fortune to other influential classification models: the United Nations International Standard Industrial Classification, the related European Union Statistical Classification of Economic Activities, and Standard and Poor’s Global Industry Classification Standard. I distilled from this analysis six top-level categories: digital, financial, manufacturing, extractive, retail and services. Following this I reviewed all the 500 companies and their existing classification, allocating companies that clearly seemed to fit a broad understanding of the digital economy to the digital category. 2 These years were chosen for several reasons in addition to the datasets being available, in a context where such datasets may be sold for greater sums than academic budgets allow. First, they offer a decade-long view of a stabilised digital economy after the 1997–2002 dot.com bubble and NASDAQ crash. Second, changes in data format make other years difficult to access and use. Third, 2017, though derived from a different ranking, was the most recent data available. In light of the definitional issues that this chapter will explore, a subsequent project would be to revisit and extend this statistical view based on a consistent and coherent definition of the digital economy. 3 All figures in the rest of this chapter, unless otherwise indicated, come from Fortune 2017. 4 This is not unlike Butler’s account of the importance of iteration in performativity, or Derrida’s of the impossibility of repetition – if something is an exact repeat then it is the same thing as the original, if it is not exact then it is not a repeat – both of which are solved, in complex ways, by noting that it is the cultural or social logic of a particular context that tells all those entangled that this is a repeated entanglement (Butler 1997: 150; Derrida 1988; Jordan 2013: 41–5).

2 Search and Advertise

      Let me start with wealth. In the first three months of 2018, Google¹ had a total income of 31.1 billion US dollars (a 26 per cent increase compared to the first three months of 2017), 85 per cent of which, or $26.6 billion, was brought in by advertising. In the same period Google’s net income, or profit, was $9.4 billion (Alphabet Inc. 2018b). In the second three months of 2018, the company’s total income was $32.7 billion, advertising brought in $28 billion (86 per cent), and net income was $3.1 billion (or $8.2 billion excluding fines) (Alphabet Inc. 2018a). A surplus or profit of $12.5 billion in six months is wealth.

      Google’s profit has always been dependent on revenue from advertising that is driven from its search engine. Formed in 1998, the company began as a website with one feature, its search engine. The first ever Google webpage was just the name Google and a box in which a search query could be entered. Its distinctive search capabilities attracted the attention of investors, who funded its losses in the early years. In 2000 Google lost $14.1 million, double its previous year’s losses, but was soon to launch an advertising program called ‘Adwords’. In 2001 the company showed a profit of $7 million, its first ever profit, rising to $100 million the following year, and then steadily upward to a yearly profit $19.5 billion in 2016, $12.6 billion in 2017, and $12.5 billion in the first half of 2018 (Auletta 2011; Levy 2011; Alphabet Inc. 2017).

      Such figures sometimes lead to the judgement that ‘Google is an advertising company’, but while the source of revenue and profit is undeniable, advertising hardly defines Google’s economic practice. It is also not alone as a search engine – before it were Alta Vista, Ask Jeeves and others, alongside it are Baidu, Bing, DuckDuckGo, Mojeek and others. Google is also not alone in monetising a service through advertising – Facebook, many computer games, web portals and other sites