The Digital Economy. Tim Jordan
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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 also take this route. While there are other search engines and other online advertisers, in examining a specific digital economic practice it helps to focus on just one, and it makes sense to start with Google given its position as a pioneer of online advertising and one of the largest profit-generators in the digital economy.
Following an examination of Google’s economic practice, this chapter will pursue two directions. First, Google’s economic practice will be abstracted to try to identify its key elements. Particular attention will be paid to its digital elements – those which might signify a specifically digital economic practice – and to how this practice might have a possible wider applicability. Second, I will explore whether Google’s practice can be applied to or found in other search engine companies.
Googling as an Economic Practice
To examine a specific practice, it needs to be acknowledged that practices come from points of view. A practice is always with or from someone or something. Points of view come with intentions and meanings, with authors, actants and actors aiming to do certain things, even if sometimes they achieve only related or different things. Points of view are necessary entanglements with other points of view, not all of which are visible to each other. The individual who searches does not necessarily see the algorithm forming the answer, nor does the algorithm necessarily account for the computers it requires, which themselves alter environments through their hunger for electricity, rare metals and so on. The points of view can never all be collated; the ‘god’s eye view’ misleads with a false promise of totality (Haraway 1991: 189–98). Yet, points of view can anchor an analysis of a web of intersections though a focus on a certain perspective that brings into view economically significant practices.
Practices are materialised in repeated actions, ideas and relations, each practice making a particular context material. When a practice is performed, one materiality is realised leaving behind other possibilities. While the previous discussion established the importance of habits amid differing activities for understanding practices generally, moving to a specific set of practices (here those of searching) requires taking into account points of view and understanding the materiality and the moment of activities. When a practice is performed, for example when a search is made, a reality is cut – in Barad’s sense – out of the mess of entanglements that intersect in each specific moment and place. And in each cut where a materiality is made there will be multiple points of view, different ways of performing in the complexity of an overall practice (Barad 2007: 148–70). One matter realised once is still matter, but it only transforms into a socially, culturally, politically or