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2024 | OriginalPaper | Buchkapitel

2. International Trade in a Global Digital Economy

verfasst von : Roman Pascal Kalin

Erschienen in: Digital Trade and Data Privacy

Verlag: Springer Nature Switzerland

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Abstract

The digital paradigm has far-reaching implications for the global economy and for cross-border trade. Digital technologies are driving a new phase of global economic integration. With respect to international trade, it is generally acknowledged that the digital transformation changes what is traded, who trades and how trade is conducted. Data has emerged as a vital economic resource in the digital economy, leading to an exponential increase in global data exchange and a surge in cross-border data flows. The economic shift from tangible to intangible assets in a digital economy is resulting in the emergence of a digital paradigm for cross-border trade. This chapter is dedicated to illustrating the novel dimensions of cross-border economic activity in the era of digital globalisation. This chapter lays the groundwork for analysing the development of regulations for these new elements within a trade context and provides a background for analysing the nexus with data privacy regulations.

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Fußnoten
1
See for example Tapscott (1996), p. 6. See infra Sect. 2.2.2.2.
 
2
See in this context for example Brynjolfsson and McAfee (2014); Lee (2018); McAfee and Brynjolfsson (2017); Schmidt and Cohen (2013); Schwab (2016).
 
3
This trend from tangible towards intangible assets is illustrated by Fritz Machlup’s compelling analysis of an expanding “knowledge industry”, cf. Machlup (1962), p. 37.
 
4
See for a definition of the concept of “digitisation” as distinct from “digitalisation” supra Sect. 1.​3. See for further explanation of the concept of “dataficationinfra Sect. 2.2.2.1.3.
 
5
The term “Big Data” is usually used vaguely and without consensus on a definition. Generally, it refers to novel insights generated by the exploitation of large amounts of unstructured data, see Mayer-Schönberger and Cukier (2014), p. 6: “Big Data refers to things one can do at a large scale that cannot be done at a smaller one, to extract new insights or create new forms of value, in ways that change markets, organizations, the relationship between citizens and governments, and more.”. See also infra Sect. 2.2.2.1.3.
 
6
Research on the subject of artificial intelligence (AI) has been carried out with moderate success for decades. Only recently researchers succeeded in making essential progress in this area, turning the field an important building block in the advancement of the digital age. See further particularly with respect to the technological development of AI Peng et al. (2021), pp. 3–6.
 
7
The concept of a “post-industrial” age was popularized by Daniel Bell, see Bell (2010).
 
8
See with regard to digital data Bantjes (2008). See further infra Sect. 2.2.2.1.3.
 
9
WTO (2018), pp. 16–19.
 
10
See Manyika et al. (2013), p. 24 for graphical representation of the data provided by the “Maddison Project” database “Statistics on world population, GDP and per capita GDP, 1–2008 AD”.
 
11
See for a discussion of the merits of the GPT concept Field (2008).
 
12
See Jovanovic and Rousseau (2005), pp. 1181–1186. See generally Bresnahan and Trajtenberg (1995). Cf. also Bekar et al. (2018), p. 1008. The authors employ a rather comprehensive definition of GPT that lists six key characteristics: (1) Complementarities with a cluster of technologies that define and support it, (2) Complementarities with a cluster of technologies that it enables, (3) Complementarities with a cluster of technologies that typically include those that are socially, politically and economically transformative, (4) No close substitutes, (5) Wide array of applications and (6) Initially crude but evolving in complexity.
 
13
Field (2008), p. 9. See for a more detailed analysis of ICT development David and Wright (2003).
 
14
Certainly, such immense transformations are not easily pinpointed to historical milestones. Rather, the interaction of technological innovation, socioeconomic development and economic globalization forms a historical fabric that can be dissected into different phases depending on the points of reference. For example, the relationship between technological upheaval, the concept of a self-regulating market, and the historical catastrophe of World War II has been identified within the context of a period of transformation, see Polanyi (2010).
 
15
WTO (2018), pp. 16–19.
 
16
Dreher et al. (2008), pp. 5–23; O’Rourke and Williamson (2002), p. 45.
 
17
Baldwin (2019), pp. 29–30.
 
18
Dreher et al. (2008), p. 8.
 
19
OECD (1969), p. 27. The section goes on “Directly or indirectly, the steam engine paved the way to the industrial society by making large quantities of cheap power available in any geographical location; computers are doing the same thing for another intangible commodity, information”.
 
20
Richard Baldwin identifies a four-step progression of the impact of disruptive technologies: economic transformation, upheaval, backlash and resolution. The author applies this pattern to the disruptive developments of the ICT revolution and forecasts a “globotic upheaval”, originating from the synchronisation of automation and globalisation, Baldwin (2019).
 
21
See for an introduction, Godin (2008), p. 8.
 
22
See for a concise description, Bell (2010), Forword 1976, XC: “The concept “post-industrial” is counterposed to that of “pre-industrial” and “industrial”. A pre-industrial sector is primarily extractive, its economy is based on agriculture, mining, fishing, timber and other resources such as natural gas or oil. An industrial sector is primarily fabricating, using energy and machine technology, for the manufacture of goods. A post-industrial sector is one of processing in which telecommunications and computer are strategic for the exchange of information and knowledge.”.
 
23
In this context, the pioneering work of Fritz Machlup merits attention, Machlup (1962), p. 9: “The production of knowledge is an economic activity, an industry, if you like. Economists have analysed agriculture, mining, iron and steel production, the paper industry, transportation, retailing, the production of all sorts of goods and services, but they have neglected to analyse the production of knowledge.”.
 
24
An economy can be separated into two domains: The first is involved in the transformation of matter and energy from one form into another. The second is involved in transforming/information from one pattern into another. The two domains are linked and inseparable.[…] The question is the relative contribution of each partner in producing economic wealth.”, Porat (1977), p. 2.
 
25
Brynjolfsson and McAfee (2014), pp. 119–121.
 
26
Haskel and Westlake (2017), pp. 7–15.
 
27
Corrado et al. (2005), pp. 22–30.
 
28
Corrado et al. (2009), p. 662.
 
29
See only Corrado et al. (2005), pp. 11–15. As rising productivity constitutes a crucial driver of economic growth, the early debate on the relevance of intangible assets for growth is frequently associated with a so-called productivity paradox, which was described by US economist Robert Solow as follows: “You can see the computer age everywhere except in the productivity statistics”, cf. Solow (1987).
 
30
OECD (2013a), pp. 26–29.
 
31
Negroponte (1996), p. 163.
 
32
Abbate (2000), p. 1.
 
33
Brynjolfsson and McAfee (2014).
 
34
Dosi and Galambos (2013).
 
35
See further Schwab (2016).
 
36
In view of differing perceptions, a 2018 background note for the G20 Working Group on Trade and Investment, which compiles the perspectives of various international organisations such as OECD, UNCTAD and WTO, simply suggests the term “New Industrial Revolution”, see OECD (2018).
 
37
These three elements are frequently identified as the building blocks of the digital era, see for example WTO (2018), pp. 24–28.
 
38
The term Moore’s Law is based on the statement of the co-founder of the Intel Corporation (at the time head of research and development for Fairchild Semiconductor), Gordon Moore, who in 1965 predicted, that the number of transistors on a semiconductor would double annually, see Moore (1965). In the mid-1970s, Moore corrected this forecast to a period of about two years. “Moore’s Law”, however, is not the only “law” that shapes the digital era. “Gilder’s Law”, for example, states that bandwidth grows at least three times faster than computing power and according to “Metcalfe’s Law” the value of a network scales as the square of the number of those connected to it, see Wilson (2012).
 
39
Hilbert and López (2011), pp. 63–65.
 
40
The problem of grasping the underlying mathematical implications of exponential growth is famously described by an old fable about the invention of the chessboard in which the inventor demands as reward one grain of rice on the first square of the chessboard, then two on the next, adding up to 264 grains of rice. Kurzweil (2001) describes this as follows: “By the end of the first half of the chess board, the inventor had accumulated one large field’s worth (4 billion grains), and the emperor did start to take notice. It was as they progressed through the second half of the chessboard that the situation quickly deteriorated.”.
 
41
Brynjolfsson and McAfee (2014), pp. 45–47. In reference to the analogy to the chessboard (see fn. above), Erik Brynjolfsson and Andrew McAfee point out that starting in 1958 (the first time the U.S. Bureau of Economic Analysis noted “information technology” as a distinct corporate investment category) exponential growth of processing power would have reached the second half of the chessboard (32 doublings) in 2006.
 
42
Moore (1965), p. 114.
 
43
For example, see Simonite (2016).
 
44
See for example McBride (2019).
 
45
World Bank Group (2016), pp. 42–46. See further Clarke et al. (2015); Manyika et al. (2013), pp. 24–28; OECD (2013b), pp. 9–12.
 
46
See Mueller et al. (2007), p. 244. There is another frequently cited definition adopted by the U.S. Federal Networking Council (FNC): ““Internet” refers to the global information system that -- (i) is logically linked together by a globally unique address space based on the Internet Protocol (IP) or its subsequent extensions/follow-ons; (ii) is able to support communications using the Transmission Control Protocol/Internet Protocol (TCP/IP) suite or its subsequent extensions/follow-ons, and/or other IP-compatible protocols; and (iii) provides, uses or makes accessible, either publicly or privately, high level services layered on the communications and related infrastructure described herein.”, FNC (1995). Internet Society (2015).
 
47
United States International Trade Commission (2013), pp. 1–9.
 
48
United States International Trade Commission (2013), pp. 1–9.
 
49
OECD (2017b), p. 18.
 
50
UNCTAD (2015a), pp. 34–43.
 
51
World Bank Group (2016), pp. 42–46.
 
52
Tapscott (1996), p. 17.
 
53
Schumpeter (1949), pp. 65–74. Such “combinatorial innovation” is not a new phenomenon of the digital era, it is a pattern that has already been observed in previous transformational phases and has recently been described in connection with the Internet as follows “Every now and then a technology, or set of technologies, comes along that offers a rich set of components that can be combined and recombined to create new products. The arrival of these components then sets off a technology boom as innovators work through the possibilities.”, cf. Varian (2004), pp. 1–48.
 
54
Open Source” in this context means that the source code of a piece of software is open and freely accessible.
 
55
McAfee and Brynjolfsson (2017), p. 231. The authors define the “crowd” as new participants and practices enabled by the net and its attendant technologies.
 
56
Thierer (2014), p. 3 defines permissionless innovation as “the tinkering and continuous exploration that takes place at multiple levels—from professional designers to amateur coders; from big content creators to dorm-room bloggers; from nationwide communications and broadband infrastructure providers to small community network-builders.”.
 
57
The terms data, information and knowledge are usually put into precisely this sequence within the context of epistemology, cf. Casalini and López González (2019), p. 11.
 
58
In this particular context Lord Kelvin may be quoted: “I often say that when you can measure what you are speaking about, and express it in numbers, you know something about it; but when you cannot measure it, when you cannot express it in numbers, your knowledge is of a meagre and unsatisfactory kind[…]”, William Thomson (1891), p. 73. From here it was only a short way to management theory’s influential author Peter Ducker’s quote: “What you can’t measure, you can’t manage”.
 
59
OECD (2015c), p. 449.
 
60
See only Capgemini Consulting (2012), p. 7. See supra Sect. 1.​3 for an explanation of the scopes of “digitisation” used in this context, in particular in distinction to what is referred to as the process of “digitalisation”.
 
61
Tapscott (1996), pp. 96–97.
 
62
Hilbert and López (2011), p. 63.
 
63
Cukier (2010); World Bank Group (2016), p. 244.
 
64
Reinsel et al. (2018), p. 3. One zettabyte corresponds to 10 to the power of 21 bytes, 1000 exabytes or one billion terabytes.
 
65
This is a dynamic field of research which can only be presented here in the broad outlines required for a legal assessment, see for example Carrière-Swallow and Haksar (2019), pp. 13–19. See further Jones and Tonetti (2020); MIT Technology Review (2016).
 
66
Mayer-Schönberger and Cukier (2014), pp. 102–104.
 
67
Viktor Mayer-Schönberger and Kenneth Cukier describe “datafication” as putting a phenomenon in a “quantified format so it can be tabulated and analysed”, Mayer-Schönberger and Cukier (2014), p. 78. This marks a clear demarcation from “digitisation” as the mere fact of transforming analogue information into a computer-readable format, Mayer-Schönberger and Cukier (2014), p. 83.
 
68
Mayer-Schönberger and Cukier (2014), p. 76, p. 83. See also Lycett (2013), p. 382.
 
69
Brynjolfsson and McAfee (2014), pp. 50–51.
 
70
Cf. for a definition Boswarthick et al. (2012), p. 2: “The role of M2M is to establish the conditions that allow a device to (bidirectionally) exchange information with a business application via a communication network, so that the device and/or application can act as the basis for this information exchange.”.
 
71
OECD (2017b), p. 19.
 
72
In this context, the term “data exhaust” has emerged for the digital trace that people leave and the data that is lost in the word as a by-product of people’s actions and movements, Mayer-Schönberger and Cukier (2014), pp. 113–116.
 
73
For an overview of Big Data techniques and technologies, cf. Manyika et al. (2011), pp. 27–36. However, some commentators emphasize that the observation of an abundance of data tends to obscure the fact that there is actually a scarcity of relevant data MIT Technology Review (2016), p. 3. See regarding the difference between AI and Big Data Peng et al. (2021), pp. 6–8.
 
74
Mayer-Schönberger and Cukier (2014), p. 7. See also Boyd and Crawford (2012), p. 663.
 
75
Boyd and Crawford (2012), p. 665; Cukier (2010).
 
76
In view of these paradigmatic shifts, some have already declared the end of the theory, see Anderson (2008). This, however, probably proves to be premature, see Boyd and Crawford (2012), p. 666; Mayer-Schönberger and Cukier (2014), pp. 70–72.
 
77
Lane (1999), p. 317. See for further references and an account of the many definitions established to date OECD (2020), pp. 34–47; Willemyns (2021), pp. 47–51. Similarly, the term “Internet Economy” has been used by the OECD to underscore the significance of the Internet as a critical economic infrastructure of the “new” economy, see for example OECD (2013b), pp. 6–7. See also OECD (2008).
 
78
UNCTAD (2017a), p. 156.
 
79
Hofheinz and Mandel (2015), p. 4; OECD (2019b), p. 17. Economies of scale are not a unique feature of the digital economy. Rather, they have driven the industrial economy before, for example, in the case of mass production. Yet, digital business models tend to scale “without mass”, see Brynjolfsson et al. (2008), p. 23.
 
80
United States International Trade Commission (2013), pp. 2–31.
 
81
Brynjolfsson and McAfee (2014), pp. 61–63.
 
82
Andreessen (2011) has stated in this context: “Six decades into the computer revolution, four decades since the invention of the microprocessor, and two decades into the rise of the modern Internet, all of the technology required to transform industries through software finally works and can be widely delivered at global scale.”.
 
83
OECD (2019b), p. 17.
 
84
Burri (2017a), p. 6.
 
85
Mims (2018).
 
86
Nguyen and Paczos (2020), pp. 10–12. On p. 5 the report explains: “[…] data-enabled businesses are companies that have developed revenue generation strategies fully reliant on data and that would not exist without access to large amounts of data and advanced data analytics. On the other hand, data-enhanced businesses exploit data to better coordinate pre-existing business operations, facilitate decision-making and to introduce new goods and services; data does not alter or determine their core business models.”.
 
87
MIT Technology Review (2016), p. 1.
 
88
Carrière-Swallow and Haksar (2019), pp. 19–29 summarize the current state of research in this context.
 
89
Pélissié du Rausas et al. (2011), p. 22.
 
90
Brynjolfsson and McAfee (2014), pp. 107–124; IMF (2018).
 
91
See with regard to cross-border data flows infra Sect. 2.3.2.3.
 
92
Cf. for a review of approaches to measuring the economic value of data Nguyen and Paczos (2020), pp. 32–36.
 
93
Carrière-Swallow and Haksar (2019), pp. 9–19.
 
94
MIT Technology Review (2016), p. 4.
 
95
Carrière-Swallow and Haksar (2019), pp. 13–14; Jones and Tonetti (2020), p. 2820; Mandel (2017), p. 4; MIT Technology Review (2016), p. 4.
 
96
Pistor (2020), p. 106. See also with regard to regulatory implications Aaronson (2021).
 
97
Pistor (2020), pp. 104–111.
 
98
See Nguyen and Paczos (2020), pp. 20–21.
 
99
OECD (2015c), pp. 22–32.
 
100
OECD (2019b), p. 19; The Economist (2013).
 
101
OECD (2013c).
 
102
OECD (2019c), pp. 20–21.
 
103
Kenney et al. (2021), pp. 38–40.
 
104
Goldfarb and Tucker (2017), pp. 6–15.
 
105
McRae (2015).
 
106
Lane (1999), p. 319.
 
107
Johnston (2018).
 
108
See further Ayyagari et al. (2018).
 
109
Brynjolfsson and McAfee (2014), p. 60. The term “network effect” describes the fact that a network has a greater value for a user with increasing participation of other users in the same network. Classic examples are social media services and AppStores or so-called platform companies such as AirBnB and Uber.
 
110
McAfee and Brynjolfsson (2017), pp. 211–218.
 
111
Atluri et al. (2018), pp. 8–11; United States International Trade Commission (2013), pp. 2–3.
 
112
Wolf (2005), p. 14, p. 19.
 
113
Baldwin (2011); WTO (2018), pp. 16–19.
 
114
See for example Manyika et al. (2016), pp. 23–43; Negroponte (1996), pp. 165–167; Tapscott (1996), pp. 64–66.
 
115
Lund and Manyika (2016), p. 2 identify three distinct ways digital technologies transform globalisation: (1) The proliferation of digital goods such as books and movies that can be delivered cost-effectively at a global scale; (2) “Digital wrappers” around traditional products such as sensors that enable other types of flows; (3) The emergence of online platforms for production, exchange and consumption. See also Manyika et al. (2016), pp. 33–41.
 
116
Castro and McQuinn (2015), pp. 2–8; OECD (2015c), pp. 71–91.
 
117
Lund et al. (2019), pp. 5–9, pp. 14–17.
 
118
See also the explanation at Ashton-Hart (2016), pp. 140–142; Casalini and López González (2019), pp. 10–11.
 
119
Ashton-Hart (2016), pp. 133–138. However, the Internet is not a fully global phenomenon, see Manyika et al. (2016), pp. 39–41.
 
120
López González and Jouanjean (2017), p. 7.
 
121
Friedman (2000), p. 9. Consequently, the transformation initiated by the disruptive force of technological innovation leads some to proclaim globalisation 4.0, cf. World Economic Forum (2019).
 
122
McNamara and Newman (2020), pp. E71–E73.
 
123
The Economist (2010).
 
124
See with further references OECD (2015a), pp. 35–42.
 
125
López González and Ferencz (2018); ICC (2016); Lund et al. (2019); Meltzer (2014a); United States International Trade Commission (2017); WTO (2018).
 
126
Goldsmith and Wu (2006), pp. 147–177.
 
127
Burri (2017a); Meltzer (2015); WTO (2018), pp. 19–20.
 
128
3D-printing is a prime example of emerging data-, and service-centric dimensions in international trade. While the printing instructions can be made available digitally via the Internet, a tangible product can be generated on the recipient side thus shortening or potentially entirely bypassing current value chains. See Fan and Meixner (2020); WTO (2018), pp. 93–95.
 
129
In 2016 the value of imports of digitisable goods by WTO Members (not accounting for EU-intra trade), constituted around 0.8% of total imports, plummeting from 2.86% in 2000, WTO (2018), pp. 92–93.
 
130
International Trade Centre (2016), pp. 43–44.
 
131
Lund and Tyson (2018).
 
132
Cf. for example Burri (2017a), pp. 9–14; López González and Ferencz (2018), pp. 9–12.
 
133
Anderson and van Wincoop (2004), p. 691.
 
134
Anderson and van Wincoop (2004), p. 691; WTO (2018), pp. 64–66.
 
135
Freund and Weinhold (2004), p. 178. According to the econometric model of the USITC, the Internet significantly reduces trade costs of US imports and exports in digitally intensive sectors by about 26% on average, United States International Trade Commission (2014), pp. 65–66. See also with further information Riker (2014), pp. 3–4.
 
136
Allen (2014); WTO (2018), p. 64. In trade in services, information and transaction costs are the most important trade barriers, accounting for 30% of the total trade costs variation, WTO (2018), p. 65.
 
137
Terzi (2011), pp. 747–748.
 
138
Lendle et al. (2012), p. 19. Using a dataset on eBay cross-border transactions and comparable offline trade flows, the authors estimated a distance effect on trade flows about 65% smaller online than offline. However, physical distance is likely to reduce trade even in online products and services that are essentially free of trade costs, see further Blum and Goldfarb (2006).
 
139
Lund and Manyika (2016), p. 5; UNCTAD (2017c), pp. 53–55.
 
140
Evans and Gawer (2016), pp. 5–6.
 
141
OECD (2019c), pp. 28–32.
 
142
See further Manyika et al. (2016), p. 32.
 
143
A 2011 McKinsey & Co. survey of more than 4800 SMEs in 12 countries showed that on average, companies using Internet with a high intensity grow twice as quickly as low-web-intensity companies, export twice as much as they do, and create more than twice as many jobs, cf. Lund and Manyika (2016), p. 8; Pélissié du Rausas et al. (2011), pp. 17–18.
 
144
See for example Meltzer (2014a). The strengthening of SMEs, for example in LDCs, is, however, counterbalanced by the growing competitive advantage of the developed nations, which, due to advancing technological development, can rarely be compensated for by economically underdeveloped regions and therefore requires strategic political intervention, see UNCTAD (2017b), p. 17.
 
145
Varian (2005); Manyika et al. (2016), pp. 43–44.
 
146
Hofheinz and Mandel (2015), pp. 4–5; Meltzer (2014a), pp. 5–7.
 
147
Vézina and Melin (2013).
 
148
Lund and Manyika (2016), p. 8; OECD (2017a), pp. 27–28.
 
149
WTO Members have refrained from formally defining the term “trade facilitation”, both because of the inability to agree on the delimitation and because of the desire not to exclude aspects of future work. It can be, however, broadly described as “the simplification, modernization, and harmonization of export and import processes”, WTO (2015), pp. 34–36.
 
150
Paperless trading is defined by UNESCAP as “taking place on the basis of electronic communications, including exchange of trade-related data and documents in electronic form”, UNESCAP (2016), Article 3 (a).
 
151
Duval and Kong (2017), p. 1.
 
152
Ferencz et al. (2022), p. 12.
 
153
Manyika et al. (2016), pp. 35–36; WTO (2018), pp. 84–87.
 
154
OECD (2017a), pp. 11–33.
 
155
WTO (2019), pp. 14–16.
 
156
OECD (2017a), pp. 24–31; UNCTAD (2015b), p. 2; WTO (2019), pp. 14–16.
 
157
Chander (2009), p. 281.
 
158
Chander (2009), p. 282.
 
159
Lanz and Maurer (2015), pp. 2–8; Low (2013), p. 63; Miroudot and Cadestin (2017), pp. 9–13; World Bank Group et al. (2017), pp. 141–152.
 
160
Lund et al. (2019), pp. 25–41.
 
161
See for the rationale of measuring trade in value added terms, Elms and Low (2013), pp. 83–159.
 
162
Low (2013), p. 61; OECD (2017a), p. 30.
 
163
WTO (2019), p. 45. Cf. in this context OECD and WTO (2024) for a TiVA (Trade in Value Added) database.
 
164
See with regard to services, in particular, Chander (2009). Anupam Chander also expects further “dematerialisation” of the service infrastructure, i.e., the systems and practices that create trust, promote social objectives and resolve disputes, cf. Chander (2009), pp. 304–308.
 
165
See generally WTO (2019), pp. 14–16.
 
166
See with regard to the relevant debate in WTO law infra Sect. 3.​3.​2.​1.
 
167
Vandermerwe and Rada (1988), p. 318.
 
168
Vandermerwe and Rada (1988), p. 314.
 
169
Companies increasingly provide ancillary services to their clients, in some cases transforming a simple sale into a contract for a larger package of services, often tied to a long-term lease, OECD (2019b), p. 18. See for example Marr (2015).
 
170
This phenomena of integrating digital technologies into manufacturing is widely described as Industry 4.0, see Lee et al. (2014), p. 8.
 
171
This term was coined by Vandermerwe and Rada (1988). Other authors reference this effect as “servicizing” or the “manuservice”, see Low (2013), p. 66. Cf. for an in-depth definition Miroudot and Cadestin (2017), p. 8, here it is explained that: “the word ‘servicification’ was introduced later to describe a broader shift towards services not only in sales of firms but also in the way they produce”. See also Lanz and Maurer (2015); Willemyns (2021), pp. 44–46.
 
172
Vandermerwe and Rada (1988), p. 314.
 
173
See with further references Carrière-Swallow and Haksar (2019), p. 13.
 
174
See OECD (2014b), pp. 8–9. There is no standard definition for Cloud Computing. The U.S. Institute of Standards and Technology (NIST) defines it as “a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction”, see Mell and Grance (2011), p. 2. See for an introduction to the legal principles governing this technology Hon (2017); Millard (2013).
 
175
United States International Trade Commission (2013), pp. 2-27–2-35.
 
176
Van der Marel (2019), p. 737.
 
177
Chander (2012), p. 31; Manyika et al. (2016), p. 38.
 
178
Meltzer (2014a), pp. 17–20; Nguyen and Paczos (2020), p. 28.
 
179
United States International Trade Commission (2013), pp. 5-1–5-2. See also with further references Burri (2017a), pp. 13–14; Nguyen and Paczos (2020), p. 28; U.S. Department of Commerce (2016), pp. 4–7.
 
180
Chander and Lê (2015), pp. 713–735; Pasadilla (2020).
 
181
Sen (2018), pp. 325–327.
 
182
Casalini and López González (2019), pp. 14–15.
 
183
Ferracane (2017), p. 2.
 
184
WTO (2018), pp. 135–136. See in this context the OECD Digital Services Trade Restrictiveness Index Regulatory Database which identifies and catalogues barriers that affect trade in digitally enabled services across 50 countries OECD (2024).
 
185
Ferracane and van der Marel (2018), p. 15.
 
186
Chander and Lê (2015); Cory (2018), pp. 3–5. See with further references regarding allegations of digital protectionism Aaronson (2019), p. 546.
 
187
Castro and McQuinn (2015), pp. 2–8.
 
188
Manyika et al. (2016), pp. 73–79; National Board of Trade (2014), pp. 9–12; Nguyen and Paczos (2020), pp. 24–25.
 
189
Casalini and López González (2019), p. 8.
 
190
López González and Jouanjean (2017), p. 10; Willemyns (2021), pp. 27–30.
 
191
OECD (2015a), pp. 90–93.
 
192
See for a historical perspective Drake (1995), p. 267; Tietje (2012), pp. 46–49.
 
193
Manyika et al. (2016), pp. 23–42; OECD (2015b), p. 5.
 
194
This is the case in particular for transfers involving personal data, see Kuner (2013), p. 27.
 
195
Schwartz (2013), p. 1628.
 
196
Kuner (2013), p. 2.
 
197
Article 29 Data Protection Working Party (2012), p. 17.
 
198
Hon (2017), p. 134.
 
199
OECD (2015b), p. 5. For example, Voice-over-the-Internet Protocol (VoIP) has generated a surge in global cross-border telephone calls and cross-border computer-to-computer Skype calling has similarly skyrocketed, see Lund and Manyika (2016), p. 2.
 
200
Aaronson and Leblond (2018), p. 250.
 
201
United States International Trade Commission (2017), pp. 45–49.
 
202
Manyika et al. (2016), pp. 30–31.
 
203
Lund et al. (2019), p. 72.
 
204
Meltzer (2016), p. 8.
 
205
Manyika et al. (2016), p. 73.
 
206
See for example Casalini and López González (2019). Beyond the trade context (often in the context of addressing aspects of data privacy), the synonymous terms of transnational or transborder data flows are more frequently employed, cf. for example Drake (2016), p. 8.
 
207
See on the relationship between political geography and the rise of digital technologies, Drake (1995); de La Chapelle and Fehlinger (2016).
 
208
Gresser (2013).
 
209
See for example Aaronson (2021), p. 344; Streinz (2019), p. 323.
 
210
Ashton-Hart (2016), pp. 135–143.
 
211
Ashton-Hart (2016), p. 138.
 
212
Ashton-Hart (2016), pp. 136–140; Casalini and López González (2019), pp. 9–10.
 
213
Streinz (2019), pp. 323–324.
 
214
Aaronson (2021), p. 344; Streinz (2019), p. 323.
 
215
Ashton-Hart (2016), p. 141.
 
216
See only OECD (2014a), pp. 18–23.
 
217
See only OECD (2013b). See also supra Sect. 2.2.1.2.
 
218
Admittedly, the challenges of measuring the wider digital economy are generally of a broader nature, see OECD (2013b), pp. 12–14. However, there are overlaps, for example, in the area of the typification of the relevant actors of digital transactions due to similar classification of digital transactions on a national and global level, see OECD (2019a), p. 238; OECD and IMF (2017), p. 4; OECD and IMF (2018), p. 5.
 
219
Mandel (2014), p. 2; OECD (2015a), pp. 78–95; Nguyen and Paczos (2020), pp. 29–31; U.S. Department of Commerce (2016), p. 6; Yakovleva and Irion (2020), p. 206.
 
220
Aaronson and Leblond (2018), p. 249; Mandel (2014), pp. 10–13; U.S. Department of Commerce (2016), pp. 7–10.
 
221
OECD (2015a), p. 34.
 
222
Mandel (2014).
 
223
Manyika et al. (2014), pp. 30–31.
 
224
Manyika et al. (2016).
 
225
Hofheinz and Mandel (2015).
 
226
Alaveras and Martens (2015), pp. 6–10; Mandel (2014), pp. 9–10; OECD (2015a), p. 78; Yakovleva and Irion (2020), pp. 205–207.
 
227
Alaveras and Martens (2015), pp. 6–10.
 
228
Manyika et al. (2016), pp. 30–31; Lund et al. (2019), p. 72.
 
229
OECD (2015a), p. 78; Yakovleva and Irion (2020), p. 206.
 
230
Nguyen and Paczos (2020), p. 19.
 
231
Cf. National Board of Trade (2014), p. 8. See also with further references, Sen (2018), pp. 343–345. The widely recognized category of “personal data” is further elaborated infra Sect. 4.​2.​3.
 
232
Casalini and López González (2019), pp. 11–12.
 
233
U.S. Department of Commerce (2016), p. IV. In a recent trade policy review the EU has set out “To better assess the size and value of cross-border data flows the Commission will create a European analytical framework for measuring data flows.”, European Commission (2021), p. 15, para. 3.2.3.
 
234
U.S. Department of Commerce (2016), p. 3. The categorization was initially introduced by a report of the Commerce Department’s Office of the Chief Economist.
 
235
U.S. Department of Commerce (2016), p. 1.
 
236
U.S. Department of Commerce (2016), pp. 7–16.
 
237
Nguyen and Paczos (2020), p. 29. See also supra Sect. 2.2.2.1.3.
 
238
López González and Jouanjean (2017), p. 10.
 
239
Mandel (2014), pp. 5–7.
 
240
U.S. Department of Commerce (2016), p. 7.
 
241
Mandel (2014), pp. 2–3; Meltzer (2019), pp. 27–28; U.S. Department of Commerce (2016), p. 3, p. 8.
 
242
Meltzer (2014b), p. 8.
 
243
See for further challenges in the measurement of “digital trade” OECD (2019a), p. 238.
 
244
See for example Meltzer (2014a). See further Nicholson and Noonan (2014), p. 5. Digitally Deliverable Services are defined therein as “services that are principally or largely enabled by information and communication technologies (ICT)”.
 
245
van der Marel (2015).
 
246
Cf. UNCTAD (2015b), pp. 8–15. The report defines ICT-Enabled Services as “services products delivered remotely over ICT networks”.
 
247
U.S. Department of Commerce (2016), pp. 11–12.
 
248
Mandel (2014), p. 2. This is acknowledged by Jessica R. Nicholson and Ryan Noonan, who primarily refer to category two of the above introduced typology of data flows by the U.S. Economics and Statistics Administration referring to “flows of data that are traded between a seller and buyer at a market price”, Nicholson and Noonan (2014), p. 4.
 
249
See with further references Yakovleva and Irion (2020), p. 206.
 
250
See for example WTO (2017), p. 2, para. 1.9: “There is value embedded in the control, management, and flow of data, and the way developing countries treat it will determine which development path they take in the digital age.”.
 
251
Meltzer (2019), p. 35; Mitchell and Mishra (2019), pp. 396–397.
 
252
Casalini and López González (2019), p. 15; Ferracane (2017), p. 2.
 
253
See Burri (2017b), p. 70; Chander and Lê (2015), pp. 679–713; Goldsmith and Wu (2006), pp. 13–29, pp. 49–63.
 
254
See with regard to a fragmentation of the Internet generally Hill (2012).
 
255
Cory and Dascoli (2021); Willemyns (2021), pp. 64–73.
 
256
Chander and Lê (2015), p. 680.
 
257
Ferracane (2017), p. 2. See further Mishra (2019), pp. 1–2; Svantesson (2020), pp. 8–11. See also Article 3 (5) Regulation (EU) 2018/1807 of the European Parliament and of the Council of 14 November 2018 on a framework for the free flow of non-personal data in the EU, defining data localisation requirement as: “any obligation, prohibition, condition, limit or other requirement provided for in the laws, regulations or administrative provisions of a Member State or resulting from general and consistent administrative practices in a Member State and in bodies governed by public law, including in the field of public procurement, without prejudice to Directive 2014/24/EU, which imposes the processing of data in the territory of a specific Member State or hinders the processing of data in any other Member State.”.
 
258
Casalini and López González (2019), pp. 16–24; Svantesson (2020), pp. 8–9.
 
259
Mishra (2019), p. 2; Willemyns (2021), pp. 64–69.
 
260
Ferracane (2017), p. 3.
 
261
Ferracane (2017), p. 4.
 
262
Ferracane (2017), p. 5.
 
263
Kaplan and Rowshankish (2015), p. 1.
 
264
Casalini and López González (2019), pp. 16–24; National Board of Trade (2014), pp. 12–16.
 
265
Casalini and López González (2019), p. 13; Chander and Lê (2015), pp. 713–735; Mishra (2015), pp. 144–151. See with further references Nguyen and Paczos (2020), pp. 28–29.
 
266
See with regard to data privacy infra Sect. 4.​3.​3.​4.
 
267
Svantesson (2020), p. 8.
 
268
Negroponte (1996), p. 11.
 
269
Schumpeter (1994), pp. 81–87.
 
270
Dyson et al. (1996), p. 295: “In technology, economics, and the politics of nations, wealth - in the form of physical resources - has been losing value and significance.”.
 
271
OECD (2013b), p. 12.
 
272
López González and Jouanjean (2017), pp. 7–12; WTO (2018), p. 9.
 
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Metadaten
Titel
International Trade in a Global Digital Economy
verfasst von
Roman Pascal Kalin
Copyright-Jahr
2024
DOI
https://doi.org/10.1007/978-3-031-73857-9_2

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