Читать книгу The Digital Economy - Tim Jordan - Страница 8

The problem of defining the digital economy can be articulated by asking what may seem an odd question: are Apple, Microsoft, Google and Facebook all part of the digital economy? This may seem an odd question, as for so many analyses of the digital economy Apple and Microsoft are not just part of the digital economy but are exemplars of it. However, in the case of Apple and Microsoft, it is possible to argue that they are essentially old-fashioned manufacturing industries – they make stuff and sell it, and what they sell happens to be digital or informational products (Bruns 2008: 2). After all, an operating system or an iPhone are commodities for sale. Of course, both companies are more complex than this and include a range of other economic practices, but at their heart their profits and ability to survive and thrive derive principally from creating a commodity and selling it. Google and Facebook cannot be described in this way. Both offer a free service – search, sociality – that allows them to generate information about their users and then profit from advertising that is targeted on the basis of that information (Turrow 2011). I will return to these practices later, but here their relevance is to question how I and the OECD made the numbers speak, because in both cases the assumption was made that Apple, Microsoft, Google and Facebook were all part of the digital or information economy. Yet both Apple and Microsoft’s revenues come out at over 80 per cent on selling ‘things’. In the case of Apple, iPhones, iPads, Macs and ‘other’ products made up 83 per cent of its revenue in the final financial quarter of 2017, with ‘services’ such as iTunes, AppleCare, ApplePay and so on accounting for most of the rest. Microsoft’s top four revenue streams in 2017 were Office, server products, the Windows operating system and the Xbox, amounting to around 80 per cent of all revenue. Both companies have long histories of inventing digital commodities and then selling them, in economic terms not entirely unlike Ford inventing and selling cars (Bishop 2017; Apple 2017).

In attempting to untangle these issues, the OECD’s definition is problematic. The report cited above is based on an earlier OECD paper that defined how it would measure the information economy (OECD 2011). Conceptually this is presented as two linked diagrams, both of which assume what they are trying to explain. The first diagram links the following groups: ICT supply, ICT infrastructure, ICT demand, ICT products, Information and electronic content, and ICT in a wider context. Rather than explaining what is meant by ‘ICT’, information, communication and technology are simply imported with it as concepts prior to their definition, creating a circularity. The second diagram outlines what is called the S curve, which conceptualises preparedness for e-commerce in three stages: e-readiness (the infrastructures needed for e-commerce); e-intensity (the state of use, value, nature of e-commerce); and e-impact (the value added potentially by e-commerce). Again, explaining what ‘e’ means is avoided by assuming it. From here the OECD falls back into prior categorisations and, employing the rather vague diagrammatic concepts just outlined, designates some existing statistical categories as measures of the information society.

Similarly, the top 500 company statistics from FT and Fortune build on existing sectoral definitions which were re-grouped to create a new sector. With only a couple of individual companies excepted, the digital economy sector was made up of the following categories: computer software; computers; office equipment; entertainment; information technology services; internet services and retailing; network and other communications equipment; semiconductors and other electronic components; telecommunications; and wholesalers in electronics and office equipment. This list should immediately throw up uneasiness about whether it is grasping a ‘digital sector’ or even any one kind of economic activity. Similarly, the existing categorisation of companies under these headings likewise raises as many questions as answers. Netflix is categorised as an information technology service but Disney and Time Warner are treated as entertainment companies. While the latter pre-date the former and the digital economy, they are closely related to Netflix in their developing economic activities. The network equipment category includes Cisco, which rather like Apple might be considered more a company that ‘makes products that happen to look digital and sells them’ than a company with a specific digital activity. Without a better understanding of what digital economic activity is, then, it is difficult to separate out companies in order to generate sectoral statistics. With such difficulties, it is hard to make numbers talk about the digital economy.

What is the standard that would allow the classification of companies as digital? Making the numbers speak is not easy because the skills required to manipulate them are not always the same as those needed to give them a framework which creates their voice. And it is that framework that is missing. In short there is a definitional problem; neither the OECD nor the existing economic sectoral categories answer the core question: how is the economic practised in such a way that it might be considered digital?

While there is a significant populist literature on the digital economy, this work is light on theorisation of what constitutes digital economic practice. The work of Tapscott is perhaps the most famous here, in particular his book The Digital Economy. First published in 1995 and updated twenty years later, this was originally, and remains, a series of anecdotes in search of a theory, offering no real framework or appreciation of what the digital economy might mean other than having something to do with computers, the internet and money (Tapscott 2015). A number of Marxist theorists have argued that the digital economy is based on a new type of rent or on the extraction of surplus value (the latter particularly in relation to free labour). These arguments will be returned to in Chapter 7, as there are some useful ideas here, but because it posits the same capitalism operating across all sectors, the Marxist attempt to understand a digital sector presupposes that surplus value or rent will be found to be the sources of profit and the drivers of economic activity. As such, this is not so much a theory of the digital economy as a presumption that extending Marxist economics to digital interactions will be sufficient to theorise that economy (Fuchs 2014; Dean 2012). Zuboff (2019) claims a new stage in capitalism that succeeds the Fordist period has arisen with digital technologies. Her account will also be drawn on but because it focuses entirely on the economic practices associated with advertising online and does not examine other potential economic practices it is a restricted view. Her claim that there is a ‘surveillance capitalism’ – echoing Balkin (2008) and others who have identified the rise of the ‘surveillance state’ – accordingly both assumes the digital economy has restructured the whole economy and limits what practices might make up the digital economy to those Google relies on (meaning also that surveillance and advertising developments in the digital and the internet prior to Google are not given appropriate attention, as they are for example in Turrow’s (2011) work).

What the problem of statistics makes clear is that a theory encompassing and connecting the elements of the digital economy and defining its specificity is missing. The remainder of this book will take up the task of providing such a theory, beginning with a clearer articulation of the question being asked.