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Abstract

The paper applies the radical view of Monopoly Capitalism to the digital platform economy. Based on the seminal ideas of Hymer and Zeitlin that led Cowling and Sugden to define the large monopolistic firm as a means to plan production from a unique centre of strategic decision-making, we attempt to develop a framework where digital platforms are conceived as an evolution of large transnational corporations. Power and control in our Monopoly Capitalism view are then meant not only in terms of market relations, but rather as levers for coordinating global production and influencing world societies. Applying this framework to the Amazon case, we highlight the key analytical dimensions to be considered: not only Amazon dominates other firms and suppliers through its diversification and a direct control of data and technology; its power is also linked to global labour fragmentation and uneven bargaining power vis-à-vis world governments, as in the Hymer and Cowling’s tradition.
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WORKING PAPER SERIES
Monopoly Capitalism in the Digital Era
Andrea Coveri a
Claudio Cozza b
Dario Guarascio c
a Department of Economics, Society and Politics, University of Urbino, Italy.
b Department of Economic and Legal Studies, University of Naples “Parthenope”, Italy.
c Department of Economics and Law, Sapienza University of Rome, Italy.
2021/33 October 2021
ISSN(ONLINE) 2284-0400
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Monopoly Capitalism in the Digital Era
Andrea Coveri
Department of Economics, Society and Politics, University of Urbino
E-mail address: andrea.coveri@uniurb.it
Claudio Cozza
Department of Economic and Legal Studies, University of Naples “Parthenope”
E-mail address: claudio.cozza@uniparthenope.it
Dario Guarascio
Department of Economics and Law, Sapienza University of Rome
E-mail address: dario.guarascio@uniroma1.it
This version: September 2021
ABSTRACT
The paper applies the radical view of Monopoly Capitalism to the digital platform economy. Based
on the seminal ideas of Hymer and Zeitlin that led Cowling and Sugden to define the large
monopolistic firm as a means to plan production from a unique centre of strategic decision-making,
we attempt to develop a framework where digital platforms are conceived as an evolution of large
transnational corporations. Power and control in our Monopoly Capitalism view are then meant not
only in terms of market relations, but rather as levers for coordinating global production and
influencing world societies. Applying this framework to the Amazon case, we highlight the key
analytical dimensions to be considered: not only Amazon dominates other firms and suppliers through
its diversification and a direct control of data and technology; its power is also linked to global labour
fragmentation and uneven bargaining power vis-à-vis world governments, as in the Hymer and
Cowling’s tradition.
Keywords:
Monopoly Capital, Monopoly Power, Digital Platforms, Amazon, Multinational corporation
JEL codes:
L12, L22, P12
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To be radical, or to be a scientist, is the same thing; it is a question of trying to go to
the root of the matter. For Marx, this meant trying to uncover the economic laws of
motion of modern society, that is, first of all, seeing society as an organism in motion
constantly changing and developing as it moves from its beginning to its end, and
second of all, searching in the economy, i.e., in changing conditions of production
and exchange, for the underlying basis of this motion. (Hymer, 1978, p. 16)
1. Introduction
1
Right before the explosion of the Covid-19 pandemic, a cover of The Economist (number
9182, February 2020) was dedicated to the “Big tech’s run”, questioning whether a time
of ‘techlash’ – namely, consumers and regulators who turn against giant tech firms was
over or not. After more than one year of pandemic, several events suggest why it is bound
to last: to name just a few, an even sharper income polarization; dramatic job losses
alongside a huge accumulation of wealth by Big Tech’s CEOs; new digital tax proposals
which however have not yet materialized.
However, a comprehensive theory on the nature of these firms and of the reasons behind
their astonishing rise is still lacking. According to us, this is also due to a widespread
adoption of a notion of ‘power’ merely in terms of ‘market power’, while Big tech
especially large digital platforms as Amazon, Facebook, and Google usually operate
across markets and countries by establishing hierarchical and semi-hierarchical relations
with formally independent actors they interact with. In this context, as we will try to
contend below, defining their sectoral scope and likewise their ‘market power’ can often
result misleading.
An alternative and more comprehensive meaning of power, that is the one coming from
theories of Monopoly Capital, is completely excluded from the mainstream debate on
digital platforms. This is not strange, as economists often exclude from their works those
previous analyses that are uncomfortable for their own theories. Let us think about
classical economists: while portions of their ideas have been included in mainstream
economics such as Smith’s invisible hand or Ricardo’s comparative advantages ,
others like an objective theory of value or the analysis of social classes have been
excluded. Needless to say, the most excluded has been Karl Marx, probably for the
political implications of his analysis: at the end of the 19th century an entire school of
thought was set-up to replace the Marxian theory of value with the subjective utility one.
2
Such an exclusion concerns a scientist that, conversely, made the effort to dialectically
include in his critical analysis all the contributions of his predecessors, especially Smith’s
and Ricardo’s.
Similarly, other radical economists of the 20th century have based their analysis upon the
inclusion of previous and dominant theories into their reflections. This is the case of
Stephen Hymer, whose neoclassical analysis of large multinational corporations evolved
1
An earlier and slightly different version of this work has been submitted to the Cambridge Journal of
Economics.
2
In Bohm-Bawerk’s words, “[a] national economics that leaves out the theory of subjective value is built
on air” (quoted in Bonar, 1888, p. 5).
3
into an analysis of imperialism. Or of Keith Cowling, who started from an industrial
organisation background to develop a theory of Monopoly Capitalism that, throughout
his life, evolved into a novel theory of the firm based on the notion of ‘control’.
In this work we argue that such a notion of ‘control’ is the key to understand the rationale
behind contemporary capitalism and, in particular, of large digital platforms, suggesting
that the latter share a number of characteristics already anticipated by Monopoly Capital
scholars, especially Hymer (1970, 1972), Cowling (1982), Cowling and Sugden (1987,
1998). Indeed, digital platforms give rise to major theoretical and regulatory challenges
when their power is analysed relying exclusively on a standard market-based approach.
First, the platform business model is based on the monopolization of all personal,
behavioural and economic information flowing through the network they control (Zuboff,
2019). This means that the distribution of information is radically asymmetrical,
effectively preventing the deployment of any competitive market mechanisms. Second,
the tendency of platforms to operate across sectors and to cross-subsidize market sides
relying on selective below-marginal-cost strategies makes most of the standard criteria
used to measure market distortions and dominant positions e.g., market shares, mark-
up levels, gap between actual and competitive prices useless (see Section 2). For these
reasons, one of the world’s leading digital platform, Amazon, has been epitomized by the
current chairman of the Federal Trade Commission (FTC) as ‘an antitrust paradox (Kahn,
2016).
In our view, the difficulties in understanding (and of antitrust policies in successfully
dealing with) platforms’ pervasive power are due to a fundamental flaw affecting all
mainstream economic analyses: the removal of a “non-market” conception of power, with
the result of leaving control, subordination, dependence and exploitation out of the
picture. Accordingly, we build on some of the most relevant insights of Monopoly Capital
theory and focus precisely on the (non-market) power of control to investigate the nature
and increasing dominance of tech giants, especially digital platforms. In particular, we
argue that the theoretical cornerstone concerns the relentless need of platforms to extend
their control in all possible directions: on labour, governments, suppliers, competitors,
clients. To this regard, we identify four drivers through which control is exerted and
power is accumulated.
First, growth and diversification (Kenney et al., 2020). By dominating ‘strategic’ sectors
and services (e.g., logistics, online advertising and profiling, cloud services) that are
instrumental (complementary) for many other goods to be produced, distributed and sold,
and relying on predatory prices to enter high-value product segments, digital platforms
expand their sectoral scope increasing the amount of value extracted from markets and
third parties (e.g., Amazon’s increasing cut of sellers’ revenues). Second, R&D and
technological investments (Rikap and Lundvall, 2020; Zuboff, 2019). By investing
heavily and selectively in technological domains such as Big data, Cloud computing,
Artificial Intelligence (AI), Machine Learning (ML) that are key to control information
networks and their physical counterparts, digital platforms lock-in and subsume to their
strategies those interacting with them (e.g., users trading privacy for the access to social
networks, consumers facing high switching cost, third parties that cannot avoid relying
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on platforms to advertise or sell their products). Third, labor fragmentation and
surveillance (Alimahomed-Wilson and Reese, 2020). Often perceived as immaterial
entities employing a small number of well-paid high skilled workers that are free to
unleash their own creativity (Vallas and Schor, 2020), platforms operations and value
capture rely instead on fragmentation, surveillance and the (direct and indirect)
exploitation of a large and geographically dispersed workforce (Bogliacino et al., 2019;
Tubaro et al., 2020). Digital networks are powered indeed by millions of individuals
scattered around the world and subject to heavy workloads coupled with unprecedented
levels of control of the working activity e.g., online workers training AI algorithms and
‘polishing’ web contents, Amazon Mechanical ‘Turkers’ (De Stefano, 2016); blue collars
employed in platforms-related logistics facilities. Not surprisingly, a relevant share of
platforms’ strategic actions and investments are directed at maintaining a tight control
over these workers (Delfanti, 2021). Fourth, governments and ‘retaliatory power’ (Ietto-
Gillies, 2002; Culpepper and Thelen, 2020). Because of the scale of their activities, their
control of a politically vital asset such as private information and their de facto alliance
with a strongly locked-in customer base (Culpepper and Thelen, 2020), platforms can
counter hostile institutions and regulations (e.g., regulations aimed at limiting the
appropriation of personal data, increasing taxation, reducing the scope of their activities,
and protecting the workforce directly and indirectly employed by platforms). To this aim,
they leverage a retaliatory power going far beyond that of earlier transnational
corporations (Rehman and Thelen, 2020).
Overall, our contribution adds to the extant literature by exploring each of these drivers
of power accumulation with the aim to show how the search for a growingly pervasive
control over both the economic, technological, and political domains represents the
multifaceted and, in ‘Hegelian’ terms, unifying element characterizing digital platforms.
Moreover, the conceptual framework provided is further qualified by means of an
application of the former to the Amazon case, with the aim to assess whether the strategic
decisions which inform its business model provides support to our theoretical
reconstruction.
The article is organized as follows. Section 2 reviews the literature on digital platforms
highlighting the economic and political aspects which have fostered their growth. In
Section 3 we recall the notions of control and power in Hymer and Cowling and sketch
our theoretical framework. In Section 4 we apply our framework to digital platforms,
highlighting similarities and discontinuities with respect to the transnational corporations
investigated by Monopoly Capital scholars (Cowling and Sugden, 1987, 1988). We then
focus on the Amazon case and make use of our conceptual framework to explore the deep
logic behind its strategy and operations. Section 5 summarizes the main achievements of
the work and discusses some policy implications.
2. Digital platforms: a brief review of the literature
From an historical point of view, the power of digital platforms can be traced back to an
act of ‘virtual colonization’. It was December 1991. In a purely ‘Polanyian’ fashion, the
bipartisan-supported Al Gore-sponsored ‘High Performance Computing Act’
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transformed a public space, the Internet, hitherto free from capitalistic accumulation, into
an arena wherein value creation, capture and concentration will soon take place at
unprecedented size and speed.
3
This is what Greenstein (2001) called the
commercialization of the Internet’. Henceforth, the fears of those warning Capitol Hill
about letting the structure and management of the network [Internet] becoming
dominated by just a few, powerful private-sector gatekeepers (O’Mara, 2020 p. 291)
gradually become reality. In 2021, four largest US tech companies, including the three
major digital platforms Amazon, Google and Facebook are together worth more than
the entire Tokyo Stock Exchange. Amazon alone is worth more than Germany’s whole
Dax index. Notably, this scenario does not appear to be affected by the 2020’s US
Congress investigation on Amazon, Apple, Google and Facebook dominance’ or by the
discussion of new antitrust laws targeting digital corporations (Popiel, 2020).
Interestingly, the business model of digital platforms came to the fore less than two
decades after the ‘shareholder revolution’ that shifted power from large Fordist
companies to financialized multinationals relying on aggressive outsourcing, asset
stripping, and labor-reducing strategies (on this point, see Rahman and Thelen, 2020). In
a shareholder value-oriented world, stock price was the core metric of success, and share
value rested heavily on hitting analysts’ quarterly profit projections (Lazonick and
O’Sullivan, 2000; Krippner, 2005). Conversely, with the advent of digital platforms,
‘short-termism’ seems to fade away: digital corporations often report low operating
profits and show a business model which is oriented to the reinvestment of cash flows,
especially in R&D activities. In other terms, financial capital appears having suddenly
become ‘patient’, being attracted by the prospect of large platform companies to dominate
the entire economic space in the medium run.
In academic research, the increasing market concentration due to the remarkable rise of
platforms and data-related business models contributed to the flourishing of studies in a
number of disciplinary domains, among which: management, economics, sociology,
political science, antitrust, labor and media studies (see, among others, Evans and Gawer,
2016; Kenney and Zysman, 2020; Montalban et al., 2019; Culpepper and Thelen, 2020;
Feldman et al., 2021). In particular, the literature on the economics of information
technology identified several mechanisms which may lead to a growing concentration of
digital markets (for an extensive review, see Calvano and Polo, 2021). Digital platforms
especially those known as transaction platforms, e.g., Amazon, Airbnb, eBay and Uber
compete in what Rochet and Tirole (2003, 2006) have called two-sided (or even multi-
sided) markets, i.e., markets that involve two groups of agents and in which the benefit
of one group joining a platform depends on the size of the other group joining the platform
(Evans, 2003; Parker and Van Alstyne, 2005; Armstrong, 2006; Evans and Schmalensee,
2008). These markets typically give rise to (i) network effects, both direct and indirect;
(ii) economies of scale, due to their cost structure and data-driven business model; and
(iii) greater product differentiation, thanks to the huge amount of data that platforms are
3
As O’Mara (2020) documents in detail, the network upon which the Internet is built, the National Science
Foundation Network (NFSNET), was aimed at empowering academic research not allowing any
commercial use. No less relevantly, the knowledge and technology base underlying the NFSNET is the
result of decades long public investment programs.
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able to gather. It follows that network externalities and a cost structure such that high
fixed costs are combined with little or no marginal costs (causing average costs to fall
dramatically as size increases) allow platforms to displace new entrants and consolidate
a dominant position in the market (Varian et al., 2004). Adopting a market perspective,
such network effects are at the roots of the strong lock-in syndrome characterizing
customers and third parties relying on platforms (Parker et al., 2016). Although network
effects existed prior to online platforms, today these effects are magnified by the business
model of modern digital platforms, whose expansion relies on capturing, storing, and
processing data from millions of users on the web by means of sophisticated computer
algorithms (Evans and Gawer, 2016).
In this regard, the growing dominance of platforms seem to be based on their increasingly
pervasive control of all relevant information flowing throughout the society (Kenney and
Zysman, 2016, 2020). To quote Rahman and Thelen (2018, p. 178), platforms gain
unprecedented power “through their capacity to extract and harness immense amounts of
data in ways that allow them to operate as critical intermediaries and market makers
[achieving a] level of market dominance that inspires comparison to classic monopolies
of the nineteenth and twentieth centuries corporations”. In other terms, by owning and
controlling data, platforms dictate the terms of interaction between workers and
employers, buyers and sellers, clients and contractors, creators and viewers, and
advertisers and consumers. To use an expression made popular by Zuboff (2015), the
growth of the platforms over time implies therefore a continuous improvement and
refinement of the technology of surveillance.
According to Zuboff (2015, 2019), the accumulation of surveillance assets relies on two
key factors, namely technology and network size. First, large platforms as Amazon,
Facebook or Google invest relentlessly and selectively in technologies (see above) and
knowledge domains that ensure dominance in data mining and processing: data storage,
cloud computing, artificial intelligence (AI), machine learning (McKinsey, 2017; Fanti et
al. 2020; Kenney et al., 2021). Keeping such a persistent technological advantage makes
these platforms an inescapable gateway for those who need to: search information (e.g.,
Google), digitize and produce services and contents (e.g., Amazon Web Services,
UpWork), work (e.g., Amazon Mechanical Turk, Uber), buy and sell (e.g., Ebay, Amazon
marketplace, Alibaba), communicate (e.g., Facebook, Instagram), advertise products and
services (e.g., Google). Second, as networks’ size and scope increase, the amount of data
the platform can syphon out grows too. It follows that the degree and stringency of its
control over the economic space increases as well; in fact, as the efficiency and the
economic value (reflected by the evolution of platforms’ stock prices) of the network
rises, network users are increasingly locked-in on both the supply and the demand side
(for a thorough discussion, see Parker et al. 2016)
Nonetheless, Rikap (2021) highlighted a relevant dichotomy in the operation of
platforms. On the one hand, they promote the centralization of capital through mergers
and acquisitions. On the other, differently from the traditional monopolies analyzed by
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Baran and Sweezy (1966), platforms rely on a vertical disarticulation of the value chain.
4
In other words, unlike transnational corporations of the last century whose advantages
were related to the size of their tangible capital, intellectual monopolies [i.e., large digital
platforms] concentrate intangible assets, while deconcentrating tangible ones” (Rikap,
2020, p. 4). More remarkably, Rikap and Harari-Kermadec (2020) pointed out that in
most analyses within the Monopoly Capital tradition e.g., Hilferding (1985), Lenin
(1916) and Baran e Sweezy (1966) planning relations between individual capitals
competing or exchanging in the market were substantially excluded. In other words, these
scholars lucidly recognized the monopolistic character of capitalism as it was emerging;
yet, as Rikap and Harari-Kermadec (2020, p. 5) wrote, “planning outside the factories
as a power relation of subordination that takes over the subordinate individual capital’s
capacity to organize and coordinate its production processes is still absent [in these
authors].” Conversely, as we further contend below, such ‘planning outside of factories’
theoretically overcoming the ‘predominance of competition’ – can be found in Hymer’s
and Cowling’s contributions.
3. Theoretical background: the notions of ‘power’ and control in
Hymer and Cowling
An appropriate starting point to understand how Hymer and Cowling’s view of Monopoly
Capitalism is Hymer’s analysis of the firms’ efficiency contradictions. He clearly detects
the extension of control as a means of large (multinational) corporations for organising
an international division of labour: “multinational corporations are torn in two directions.
On the one hand, they must adapt to local circumstances in each country. This calls for
decentralised decision making. On the other hand, they must coordinate their activities in
various parts of the world and stimulate the flow of ideas from one part of their empire to
another. This calls for centralised controls” (1970, p. 445, emphasis added). Moreover,
investigating the law of uneven development, Hymer identifies a tendency towards a
hierarchical division of labour between geographical regions corresponding to the vertical
division of labour within the firm. It would tend to centralize high-level decision-making
occupations in a few key cities […] and confine the rest of the world to lower levels of
activity and income (1972, p. 114). The continuity of Hymer’s notion of control appears
therefore clear, moving from a theory of the firm’s behaviour to an analysis of
imperialism having at its core the multinational corporate capital.
An extension of Hymer’s notion of control within an industrial organisation framework
is offered by Keith Cowling. Cowling (1982, p. 5) is “interested in demonstrating the
extent of capitalist control over the degree of monopoly, and thus over the distribution of
income, […] to isolate those factors which determine the degree of monopoly”. Therefore,
Cowling looks at Monopoly Capitalism from multiple angles: his industrial organisation
background is used to analyse the source of profits in an oligopolistic market structure,
both theoretically and empirically. His work is complex precisely because it represents
4
A similar phenomenon led Bellofiore (2011) to coin the expression of ‘centralization without
concentration’.
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an “attempt at merging together macro and micro elements through the links between
monopoly power, degree of monopoly and macro analysis” (Ietto-Gillies 2005, p.160).
This way, Cowling has stepped away from mainstream economics without adopting the
purely macroeconomic approach of 20th century Marxism. As a consequence of this
strategy, “his radical counterparts sometimes labelled his approach as ‘Neoclassical
Marxism’” (Pitelis and Tomlinson, 2017, p. 187).
Interestingly, a common feature that we detect between Hymer and Cowling is that, in
their earlier analyses, they both seem to touch the key point of their theoretical approach
without making it explicit. Consistently, when Cowling (1982, chapter 4, also based on
Cowling et al., 1980) deals with ‘mergers and managerialism’, he is implicitly interested
in a wider analysis of what modern corporations are, that is attaining a novel theory of
the transnational firm. However, he would only make it explicit in his subsequent works
with co-authors (Cowling and Sugden, 1987, 1994, 1998; Cowling and Tomlinson, 2005,
2011).
In this context, what is worth emphasizing for our purposes is the shift that these authors
operated by moving from an analysis focused on the internal characteristics of the firm
where Hymer’s contributions can be interpreted in continuity with contemporary authors
such as Penrose and Chandler (Pitelis, 2002) to a theoretical perspective which includes
firms’ external relations in order to grasp the deepest economic and political nature of
giant corporations. In particular, taking the latter perspective makes it possible to
highlight the power relations that inform the bargaining position of firms towards other
firms, labour, and governments. What results is therefore a definition of the firm as a
“means of coordinating production from one centre of strategic decision-making”,
extended to a cross-border coordination in the case of the transnational corporations
(Cowling and Sugden, 1987, p. 12).
Most importantly, the notion of ‘control’ which results from this perspective is not merely
concerned with the internal ability of coordinating resources as in the Penrosean tradition.
Conversely, it is rather a form of power as an external relation towards other economic
and institutional actors, namely firms, suppliers, trade unions and governments. To use
Cowling and Sugden’s words, “the power to make strategic decisions is the power to plan
the overall direction of production in the firm. This includes the power broadly to
determine a firm’s geographical orientation, its relationship with rivals, with governments
and with its labour force” (Cowling and Sugden, 1998, p. 64). Consistently, the notion of
‘control’ should be conceived as defined by Zeitlin (1974): “the power to make strategic
decisions includes the ability to plan a corporation’s relationships with other corporations,
its relationships with governments and employees, and its geographical orientation” (see
Branston et al., 2006, p. 191). In this sense, Cowling and Sugden (1998) endorsed a shift
from a market-oriented to a production-oriented perspective. Consistently, they opposed
what they considered the “excessive concern with markets and exchanges” (p. 60) at the
core of the mainstream theory of the firm, according to which all exchanges ‘external’ to
9
firms’ legal boundaries should be conceived as market transactions, i.e., as purely inter-
firm market relationships.
5
The landing of Cowling and Sugden’s approach is a rather optimistic view of “an
alternative non-hierarchical system […] relating to flexible specialisation and industrial
districts” (Cowling and Sugden, 1998, p. 82) as a means to go ‘beyond capitalism’. This
view also inspired other theories of large corporations as network firms (e.g., Ietto-Gillies,
2002) where the main issue becomes re-balancing the existing power unbalances among
firms. Or, more generally, recent theories paying more attention to the wider public
interest (Branston et al., 2006; Cowling and Tomlinson, 2011). However, we believe this
is only a partial way to use Hymer’s and Cowling and Sugden’s idea of the large
monopolistic firm as a means to coordinate and plan production from a unique centre of
strategic decision-making.
For sure, these strategic decisions encompass decisions that are both internal and external
to the firm, with external ones referring most of all to subcontracting relations with
(formally) independent suppliers. This is key in the digital platform economy and it has
been accepted also in more mainstream perspectives, alongside persistent critical
approaches (e.g., Strange and Humphrey, 2019, or Buckley and Strange, 2015). In all
these contributions, while it is recognised that power in markets is more than simply
“price margin” and has to do with the above mentioned ‘planning outside of factories’,
still relationships are always ‘market relations’. This seems limited as compared to the
theoretical advancements of Hymer, Cowling and Sugden. Power relations between giant
firms and a wide range of different actors (extensively studied in other disciplines such
as sociology or political science) are still completely ignored in current economic
literature, precisely because they cannot be explained in terms of market relations. So our
question is: can we give an economic interpretation of such relationships, going beyond
pure market relations?
Saying, as the literature on GVCs has largely shown, that weaker firms involved in
subcontracting/outsourcing activities with a ‘lead firm’ means a ‘power asymmetry’ in
contractual terms is a key aspect, but it is not the only one. Weaker firms competing
among themselves to become subcontractors of lead firms are implicitly asked to modify
their internal structure and competences to win this race. In other words, as agreed in
current economic literature, their internal organization of production is not completely
5
While Cowling and Sugden’s conceptualisation of the modern corporation is remarkably different to the
neoclassic theory of the firm whose Coasian pillars make it mainly based on transaction costs , prominent
scholars such as Strange and Newton (2006) argued that Hymer’s approach could be considered an
anticipation of Gereffi’s (1994, 1999) to the analysis of lead firms in global value chains (GVC) ;
conversely, they contend that it would be substantially different from the theoretical framework of Cowling
and Sugden (1987, 1998). Although an in-depth discussion on the (dis)continuities between Hymer,
Cowling and GVCs scholars as Gereffi goes far beyond the scope of this work (on this see also Strange and
Humphrey, 2019), according to our reading important commonalities between these authors can be found.
As stressed by Ietto-Gillies (2002, p. 51), linking Hymer and Cowling & Sugden reflections on labour
fragmentation, “a natural extension of this idea of control as removal of conflicts is in the area of control
over labour which is considered by Hymer (1970 and 1972) […] The fragmentation of labour over many
nation-states allows the TNCs to exercise wider control over labour in strategies of divide and rule (Cowling
and Sugden, 1987; Sugden, 1991) and to remove conflicts with labour”. See also Balcet and Ietto-Gillies
(2020).
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free, but it is constrained by standards and explicit requests by lead firms. That, in the
end, induce a constant structural and technological change in their counterparts,
modifying the DNA of these ones. Of course, it is the market transaction between lead
firms and subcontractors the act that formally requests this modification; but, if these
small firms do not accept to modify themselves, they would hardly survive. Following an
evolutionary perspective, it means that their structural change is an intrinsic request of
survival, it is an ‘internal need’ that is just ‘confirmed’ when a successful transaction with
a lead firm is taking place. In extreme cases, smaller firms might have to change their
structure in advance, even if the contractual agreement with the lead firm will not take
place (unsuccessful transaction).
Why should this mechanism be limited to subcontracting firms? We can simply extend
this reasoning, even starting from that specific case. If subcontracting firms have to
survive and adapt to the giant firms’ requests, they would probably need to ask their
employees (or external collaborators) a longer or more intense working day. Extending
this view to all workers in a specific location, we then might want to check the level of
unionization there: so if a trade union of workers is stronger in a country and weaker in
another one, power relations vis-à-vis trade unions would mean that in some countries the
working day would be longer and in other it would disappear, for a global re-organisation
of work induced by few giant firms (in line with the late Hymer writing about
imperialism). All these events (successful/unsuccessful subcontractors; length and
intensity of their employees’ working day; strength/weakness of trade unions) will result
in different behaviors of workers as ‘consumers’. Again: this is largely discussed in terms
of market preferences, but when a person is buying a different commodity on a market, it
is simply the last step of an internal change of that person (influenced in the past by radio
and TV advertising, nowadays more by the ownership of data on the web, as discussed
above). Finally, all these changes (in people behavior and in firms’ demography having
an impact on quantity and quality of jobs) have an impact on governments’ decision about
public spending. The decision on opening/closing a factory by a lead firm is just the most
evident fact of power unbalances: governments are in a way obliged to use public money
to try and attract/keep that firm’s production. Or, to give another example, the existence
of firms in a strategic sector in a country (that might need to put more public money to
sustain it) is clearly depending on the strategic decisions of those lead firms: the
governments of countries where many subcontractors are active, would probably use
public money for other purposes or for sustaining other sectors. The internal organization
of the lead firm directly and indirectly shapes the sectoral specialization of countries.
In synthesis: if it is true that few giant firms can influence the world economy with their
market power, then it cannot be denied that such a power (and control) automatically
involves many other aspects of economic and social life. That is just another way to mean
that capitalistic accumulation progressively takes the control over the whole society from
a decreasing number of decision-making centres, that is centralization of capital as an
additional step after the real subsumption of labor under capital (Marx, 1867). Over the
last decades, giant transnational corporations have been at the top of this process; today,
among them it seems that a sub-set of most digitalized ones will be in charge of shaping
11
the world economy. For this reason, we try and adapt our perspective to the digital
platform economy and to the Amazon case in the following sections.
4. Power, control and digital platforms
4.1 Digital platforms as an evolution of large transnational corporations
In this section we argue that digital platforms, particularly those controlling large
networks and operating as a de facto infrastructure (e.g., Amazon, Apple, Facebook,
Google on this point, see, among others, Rehman and Thelen, 2020; Kenney et al.,
2021), can be interpret as a data-driven evolution of the transnational corporations
described by Hymer, Cowling and followers. Consistently, if for these authors control is
the key to understand the very nature of corporations, for digital platforms controlling the
economic space is an existential objective’ (Parker et al. 2016).
Data-related technologies allow giant platforms to improve their command on actors they
interact with in at least two ways. First, leading platforms as Google or Amazon try to
maintain or increase the competition among complementors yet retaining a certain degree
of control over the overall digital (and physical) architecture (Gawer and Cusumano,
2014). This allows stimulating complementors’ innovativeness, intangible and
competence sharing, so to syphon out (via acquisitions or imitation) what is more strategic
and valuable in their production. This is an implicit monopoly of both actual and
potential innovation. By the same token, as noted by Zhu and Liu (2018), platforms such
as Amazon use data to detect and in some cases penetrate market segments that show the
greatest potential for success, competing directly with third-party sellers. The result is
that many third-party vendors despite having previously developed successful products
are pushed out of the market, thereby further consolidating the ‘market control’ exerted
by the marketplace orchestrator. In addition, by including new markets within the network
perimeter, giant tech corporations increase the dependence of those relying on them
resizing or eliminating altogether market alternatives e.g., Uber vs traditional taxi,
Amazon’s marketplace vs third parties own websites, Facebook and Instagram vs
competing social networks.
These elements may contribute to magnify the degree of dependence that both customers
and suppliers have vis-à-vis platforms (1970, 1972). On the one hand, once a supplier or
a third-party seller must rely on a given platform to reach all or most of her customer base
the alternatives become surviving by submitting to the strategic decisions of the platform
(e.g., charge a certain discount, modify products in a certain way, not using competing
platforms), or exiting the market altogether. On the other hand, the broader,
heterogeneous and efficient the content of the network (e.g., number of friends and
participants in a social network, goods and services sold on the online marketplace), the
greater the cost that customers bear should they wish leaving the platform because of
unilaterally undesirable actions performed by the latter (Parker et al. 2016). Accordingly,
as larger and diverse the network, as vast the amount of information owned by the
platform, as effective the retaliatory actions that the latter can put in place to avoid a
resizing of the network itself.
12
Second, the technological infrastructure combined with monopolization of the access to
information gateways allows digital platforms to concentrate in their hands an immense
amount of power while asset ownership and risks remain highly decentralized (Zuboff,
2019; Kenney et al., 2021). Following but going beyond the transational corporation by
Monopoly Capitalism scholars, the platform can therefore exert an improved form of
architectural control by positioning itself as the de facto leader of an international
division of labor that originates beyond the confines of the company. As argued, this
provides the platform with the ability to subsume, adapt, and profit from the innovative
efforts made by its formally independent complementors. As noted by Durand and
Milberg (2020), the data centralization which results from platforms’ capability to
generate, control, and manage information allows these firms to exert a panopticon
control over value chains and learn from their partners’ business procedures, thereby
improving (at almost no cost) their innovation capabilities.
6
More broadly, at the base of this dynamic is a progressive shift of market power along
the value chain, from product and content producers to platforms, which benefits from
being involved in global networks whose governance is ultimately based on power
relationships (Gereffi, 1994, 1999; Bair, 2005; Gereffi et al., 2005; Mahutga, 2012; Dallas
et al., 2019; Strange and Humphrey, 2019). Again, what is worth emphasizing for our
purposes is the strategic behavior adopted by large tech corporations in GVCs, that
mostly thanks to their financial, organizational and data-based assets allow them to
pursue an orchestration of economic actors populating their production and innovation
networks which often resembles an effective extension of their strategic planning power
outside their formal boundaries. Following previous insights provided by Cowling and
Sugden (1987), we therefore stress that the boundaries of these giant corporations end up
being really enlarged as their internal production planning is effectively combined with
the direct and indirect subordination of formally independent suppliers and institutional
actors they globally interact with.
Most importantly, when strategies aimed at controlling and extracting value from labour
are at stake, digital platforms show both similarities and discontinuities as compared to
what Cowling and Sugden (1987, 1994) highlighted with respect to the corporations of
the last century. A first aspect is related to the workforce directly employed by digital
platforms; in this regard, a significant segmentation is in order. On the one hand, we find
a circumscribed group of high-skilled high-wage workers, often owning companies’
stocks, who are charged with managing the network’s digital infrastructures (e.g., cloud,
servers, algorithms), analysing data, performing research and developing related
technologies. For platforms, attracting the best expertise in fields such as physics,
mathematics, and computer science is vital to maintaining efficiency and maximize the
value of the network, ensure its ubiquity, and make users increasingly dependent on it.
6
This interpretation also sheds light on the logic behind the ecosystems of innovation having giant
technology corporation as major orchestrator. For example, the App Store owned by Apple represents a
powerful tool for leveraging third-party applications, thereby accelerating innovation at a pace Apple could
not have achieved with in-house developers alone (Rikap, 2018). In this way, digital platforms take
advantage of a potentially unlimited pool of external innovators, whose fortunes increasingly depend on
being able to join albeit in a subordinate position the innovation ecosystem controlled by digital
platforms themselves.
13
Leading platforms compete hard with each other for these skills.
7
On the other hand, there
are those employed in the low value-added phases of the production process (e.g., the
Amazon’s logistics workers, the ‘click-workers’ that moderate contents and ‘clean’
Facebook, Google or Youtube interfaces). Although important for the functioning of the
network, this workforce is highly fragmented and workers are mostly hired with
precarious work arrangements and often lack adequate welfare protections. A second
aspect concerns the tighter control that platforms exert on workforce thanks to advanced
technological devices combined with peculiar techno-organizational practices, e.g.,
individual monitoring tools ensuring the achievement of given production targets (as the
Amazon’s electronic bracelet for a thorough analysis, see Delfanti, 2021), gamification
to stimulate competition among workers. These strategies allow for a leap forward in the
surveillance of workers and giant tech corporations use this ‘surveillance power’ on the
timing and modalities of work activity to optimize business production planning and
prevent any form of labour organization (Prassl, 2018).
8
Finally, softening governments’ constraints on their actions as well as alleviating the tax
burden are also strategic objectives of the corporations analysed by authors such as
Cowling and Sugden (1987, 1994) and Ietto-Gillies (2002). Digital platforms take a leap
forward also in this respect. This can be assessed in the first place by looking at the huge
amounts of money these companies have spent on lobbying to dissuade governments from
taking measures that could limit their economic power to illustrate, Facebook, Amazon,
Apple, and Google together spent over $ 20 million on lobbying just in the first half of
2020,
9
showing a growing trend compared to previous years (UNCTAD, 2019).
Secondly, the strong reliance on intellectual properties combined with their global scale
make shifting the tax burden easier for giant platforms than for traditional, tangible-
intensive corporations (Prasad and Sounderpandian, 2003; Rikap, 2020). Thirdly, as
Culpepper and Thelen (2020) have pointed out, the dependence of increasingly large
masses of consumers on their services provides platforms with a de facto ‘consensus base’
that is likely to discourage governments from hostile actions.
7
‘Amazon, Facebook and others in tech will commit $300 million to the White House’s new computer
science push’, Vox.com, https://www.vox.com/2017/9/26/16364662/amazon-facebook-google-tech-300-
million-donald-trump-ivanka-computer-science; ‘Amazon, Google Poised for Race to Hire High-Tech
Talent’, The Wall Street Journal, https://www.wsj.com/articles/amazon-google-chase-software-
developersbut-not-the-same-ones-1542133719; ‘STEM education as a diversity driver in tech’,
AboutAmazon.com, https://www.aboutamazon.com/news/community/stem-education-as-a-diversity-
driver-in-tech; ‘Google, Microsoft, Apple, Amazon, and tech’s battle for the hearts and classrooms of
teachers’, GeekWire, https://www.geekwire.com/2018/google-microsoft-apple-amazon-techs-battle-
hearts-classrooms-teachers/ (last access: May 15th, 2021).
8
‘Amazon patents wristband that tracks warehouse workers' movements’, The Guardian,
https://www.theguardian.com/technology/2018/jan/31/amazon-warehouse-wristband-tracking; ‘If
Workers Slack Off, the Wristband Will Know’, The New York Times,
https://www.nytimes.com/2018/02/01/technology/amazon-wristband-tracking-privacy.html; ‘Amazon
expands gamification program that encourages warehouse employees to work harder’, The Verge,
https://www.theverge.com/2021/3/15/22331502/amazon-warehouse-gamification-program-expand-fc-
games (last access: May 30th, 2021).
9
‘Big Tech spends over $20 million on lobbying in first half of 2020, including on coronavirus legislation’,
CNBC, https://www.cnbc.com/2020/07/31/big-tech-spends-20-million-on-lobbying-including-on-
coronavirus-bills.html (last access: May 16th, 2021).
14
To sum up, the ability of digital platforms to leverage data to expand their dominance can
be conceived as an updated and extended version of that ‘power of control’ described by
Cowling and Sugden (1987, 1994). Nonetheless, platforms’ power involves a multiplicity
of dimensions, which may at least partially vary according to the specific digital platform
investigated. Accordingly, in the next section we apply our framework to the analysis of
the Amazon case.
4.2 The Amazon case
If digital platforms represent an evolution of the capitalist enterprise towards a greater
concentration of power and control, Amazon can be considered their role model (Kenney
and Zysman, 2020).
10
Established in 1994 as an e-commerce book retailer, it now operates
in a wide array of sectors including retail (e-commerce and brick-and-mortar), logistics,
video, music, entertainment (e.g., gaming platforms as Twitch), data storage and web-
services, financial services for both consumers and firms (e.g., Amazon Pay), smart
devices (e.g., Alexa, Amazon Halo), autonomous cars (e.g., Amazon Zoox). Likewise,
few years after the start of its activities in the US, Amazon expanded geographically
gaining massive market shares all over the world, excluding China (where similar
national platforms operate). Such ubiquity is reflected in some of the Amazon’s most
popular nicknames: the everything and the everywhere store (Rikap, 2020).
Indeed, there is nothing strictly new in the Amazon case. Like other transnational
corporations (Cowling and Sugden, 1987; Ietto-Gillies, 2002), Amazon expands
geographically to find more demand; relies on innovation and outsourcing to reduce costs
and extract more value from labor; invests on marketing and advertising to influence
customers, trying to make the latter as dependent on its services as possible; lobbies to
obtain favorable regulations from governments and elaborates strategies to reduce the
amount of taxes to pay (Zingales, 2017).
What marks a discontinuity is the pervasiveness of the control that this platform exerts
over the economy by means of a ‘decentralized’ concentration of power (Kenney et al.,
2020; Culpepper and Thelen, 2020). In fact, in line with the idea of Cowling and Sugden
(1998) that control is maintained on strategic issues by giant firms, Amazon expands its
control over a multitude of markets investing exclusively on those assets and technologies
allowing to maintain a tight control of its digital and physical networks. As for the other
large digital platforms (e.g., Google, Facebook) extracting and harnessing data is the key
to accumulate economic power and control (Zuboff, 2015, 2019). In this case, however,
power goes beyond controlling data gateways.
On the one hand, by rapidly expanding the number of goods available on its marketplace
(Kenney and Zysman, 2020), Amazon becomes the first option for an increasing number
10
The Amazon case has been recently analyzed by Kenney et al. (2020). These authors propose an
analytical framework composed of eight vectors of expansion, highlighting that once a platform like
Amazon develops its technological, organizational, and financial advantage, ‘it can not only quickly scale
up in its original business, but leverages its assets in one industry to enter new industries’ (p. 5). A similar
study is provided by Aversa et al. (2020).
15
of customers, wholesale, and third-party sellers all over the world.
11
In turn, this opens
the way to ‘predatory’ pricing strategies (Rikap, 2020), mainly based on discounts and
markets subsidization, through which new markets and sectors are continuously
penetrated. As a result, together with its reach, Amazon increases the amount of data
usable to further refine market strategies as well as to empower the AI algorithms
governing the platform. On the other hand, control strategies extend also to the ‘physical
world’. This can be firstly assessed by looking at the direct management of warehouse
and logistics services, namely the physical counterpart of the Amazon’s virtual
marketplace. By maximizing efficiency and reducing bottlenecks, Amazon ensures that
the goods customers may want to purchase are actually ‘a click away’ from their doorstep
(Culpepper and Thelen, 2020). Secondly, the penetration into brick-and-mortar retail
sectors should be emphasized. In this case, control assumes the form of the ‘omnichannel’
retailing. By leveraging the power and resources acquired thanks to its dominant position
in the e-commerce industry, Amazon makes strategic investments to offer the widest
possible range of products (e.g., books, grocery, but also autonomous i.e., self-driving
electric vehicles), including those that are less easily manageable online such as
perishable goods (e.g., fresh food). In this way, Amazon aims to gain prominent positions
in high value-added industries and counter the actions of direct competitors such as
Walmart.
This pervasiveness is rewarded by the financial market, with Amazon’s share value
registering a sharp rise in recent years. To illustrate, as of February 2021, Amazon’s
market capitalization was 1.557 trillion U.S. dollars, making it the most valuable U.S.-
based internet company. As Figure 1 shows, this occurs despite Amazon accumulated
relatively small profits compared to total revenues since its birth (see also Khan, 2016).
Accordingly, this data points out that is the expectation of further expansion that drives
Amazon’s market value.
12
As previously mentioned, this circumstance could also lead to
think that capital has become patient, looking for rewards in the less near future than
for very short-term profits. On closer inspection, however, this argument can be further
articulated. As noted by Rikap (2020, pp. 20-21), “[a]s far as the stock price keeps rising,
shareholders will still benefit in the short-term”. Consequently, one should be cautious in
concluding that investors’ hunger for overnight profits has vanished with the advent of
digital platforms.
11
Amazon operates both as first-party seller by setting the price and selling directly the goods provided by
wholesale suppliers; and as third-party seller, allowing third parties to retail goods using, according to
specific terms and conditions, its marketplace.
12
On June 16, 2017, Amazon announced it was buying the upscale grocery food chain Whole Foods for $
13.7 billion. An hour later, Amazons shares were up 3 percent, pushing the companys value up by $ 14
billion. Basically, Amazon bought the sixth US supermarket chain without shelling out a penny (Eisen,
2017).
16
Figure 1. Annual net sales and net income of Amazon, 2004-2020
Source: authors’ elaboration on data sources from Statista.com
Note: Data are expressed in billion U.S. dollars.
Overall, Amazon’s strategies to enforce and expand its control over the economic system
are complex and heterogeneous and recall elements typical of the 1990s’ transnational
corporations while introducing brand new ones (Rehman and Thelen, 2020; Kenney et
al., 2020). Below, a first comprehensive assessment of these elements is provided.
Growth and diversification of the digital marketplace
The number of markets and sectors included in the Amazon’s marketplace increases
constantly (Kahn, 2016; Kenney et al., 2020; Rikap, 2020). As countries and subscribers
grow, so does the number of vendors and sellers relying on Amazon to enlarge their
market. By using cross-subsidization techniques i.e., using the resources accumulated
in a certain market or sector to offer below-cost prices and penetrate new ones (Rochet
and Tirole, 2003) , Amazon thus further expand and diversify its marketplace (Haucap
and Heimeshoff, 2014). In this regard, Figure 2 reports the evolution over the last twenty
years of the third-party sellers’ share of gross merchandise sold on Amazon. Notably, this
magnitude experienced a rapid growth after the Great Financial Crisis, reaching 62% in
2020, meaning that just over a third of products sold on Amazon’s marketplace are
Amazon-branded. The only way to combine this apparently negative data for Amazon
with the consolidation of its economic and financial dominance is by interpreting the
former as a rough indicator of Amazons growing power to expand its network by
subordinating an increasing number of independent actors to its own benefit.
0
50
100
150
200
250
300
350
400
Net sales Net income
17
Figure 2. Share (%) of physical gross merchandise sales sold on Amazon by
independent third-party sellers as opposed to Amazon’s own first-party retail sales
Source: authors’ elaboration on data sources from Statista.com
This also increases the amount of data to be used for targeted marketing strategies aimed
at binding existing customers and attracting additional ones. The tools used to extract
value from suppliers and vendors are, in turn, commission, advertising and fulfillment
fees (those that Amazon charges when it directly manages packaging and delivery).
Although vendors can choose whether or not to rely on Amazon’s fulfillment services,
those who want to take advantage of frontline services such as Amazon Prime are obliged
to pay such fees.
13
Similarly, advertising fees become de facto mandatory under penalty
of loss of visibility (and customers) on the marketplace. Overall, as the size of the
marketplace has grown in size, Amazon’s fee share has grown substantially, reaching
roughly 30% according of recent estimates (Mitchell et al., 2020). No less relevantly, the
product sectors wherein Amazon relies on its own branded goods to directly compete with
sellers using the same marketplace has also increased. This strategy is put in place both
as a deterrent, to ensure suppliers and vendors compliance to the platform’ strategy, as
well as a traditional way of expanding market shares (Zhu and Liu, 2018). The main
purpose is twofold: destroying the attractiveness of digital and physical alternatives to the
Amazon’s marketplace; increasing control over the platform’s users. Notably, as control
increases, the autonomy of customers (affected by data harnessing, targeted marketing
and induced consumption behavior; Culpepper and Thelen, 2020) and of suppliers and
sellers (informally forced to follow Amazon’ pricing strategies and discount policies;
Mitchell et al., 2020) decreases. From this point of view, cost-cutting strategies based
on job reduction and low wages and aimed at avoiding the exit from the marketplace
(under the conditions set by Amazon though) are the same as those used by industrial
subcontractors in the 1980s and 1990s: at the bottom of “pyramidal structures of
subcontracting relations […] a large number of highly substitutable small sweatshops
13
Amazon Prime is a paid service offered by Amazon, which allows customers to take advantage of the
possibility of receiving their purchased products in a short delivery time, as well as several other services
(e.g., Prime Music, Prime Video, Prima Reading).
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
55%
60%
65%
18
compete in order to obtain their place in the network” (Sacchetti and Sugden, 2003, pp.
683-684).
Data and technology
Amazon investments and innovations are mostly directed at assets and technologies
related to data extraction, storage, and analysis. Among the key technologies there are:
cloud computing, machine learning and AI (Fanti et al., 2020; Rikap, 2020). Besides,
investments and patenting are directed at technologies linked to surveillance practices and
smart objects. Regarding surveillance (Zuboff, 2015), technologies such as facial and
motion recognition are of special relevance to Amazon. These are at the basis of a set of
devices allowing to maximize the control, and thus the value extracted, from workers
employed in its warehouses (Hanley and Hubbard, 2020; Delfanti, 2021). The
development and implementation of such devices is aimed both at direct surveillance of
labor; and, through data mining, at the design of labor-saving process innovations.
Similarly, investments in robotics are aimed at increasing efficiency and at reducing the
share of human labor involved in the packaging and shipping processes (Delfanti and
Frey, 2021). Geo-localization technologies are in turn developed to monitor and increase
productivity of drivers and delivery staff. R&D on autonomous guided vehicles (AGV),
drones and related technologies are also directed at improving logistics and surveillance
practices. Concerning smart objects, R&D investments on AI and natural language
recognition led to disruptive product innovations as Alexa (Kenney and Zysman, 2020).
The latter is a digital personal assistant designed to create a ‘smarter’ environment
allowing the assisted individual to purchase a good from the marketplace or Amazon
Prime Video with a simple voice command. As in the case of the Kindle e book reader,
introduced by Amazon's research labs in 2007 (Kenney et al., 2020), a product innovation
like Alexa increases users’ dependence on the company' services providing more room
for data harnessing and control. Finally, investments in cloud computing and data storage
technologies are crucial to the growth of one of the Amazon’s key branches: Web
Services (AWS).
14
Of course, increasing size and technological capabilities in terms of
cloud computing and storage is important per se, in order to manage the overall Amazon’s
digital infrastructure. Building on such capabilities, however, Amazon manage to become
one of the major suppliers of cloud and web-services in the world. This has added a
relevant source of revenue further enhancing the platform's ability to capture and analyze
data (Kenney et al., 2020).
Labor fragmentation and surveillance
Amazon's workforce can be broken down into two main components. A limited group of
high-skilled workers, mostly concentrated in the STEM area. These are employed in
knowledge-intensive activities related to the management of Amazons digital
infrastructures and the development of new products and processes. These workers are
primarily located in Silicon Valley and are a key resource in the pursuit of the company's
14
Amazon's AWS segment - a cloud computing platform that allows businesses to rent space on a server
network generated net sales of $ 45.4 billion and operating income of $ 13.5 billion in fiscal 2020. This
is Amazon segment reporting the highest operating income (it accounts for approximately 59% of total
operating income). Amazon controls about a third of the global cloud market, nearly double its next closest
competitor.
19
technology and growth strategies (O’ Mara, 2020). The largest portion of the global
workforce employed by Amazon, however, is made up of those in logistics warehouses
and fleets engaged in deliveries. In addition, there are the so-called ‘crowd workers’ (Berg
et al., 2018), managed by the Amazon Mechanical Turk (AMT) labor platform (De
Stefano and Aloisi, 2019). These workers perform online micro-tasks related to the
maintenance and cleaning of Amazon's digital interfaces (e.g., checking image layout,
reporting and correcting typos on this point, see Tubaro et al., 2020). Workers employed
in logistics, delivery as well as AMT crowd workers are exposed to very high levels of
fragmentation, which in turn is mainly dictated by technological, organizational, and
institutional factors. First, as outlined above and documented by Delfanti and Frey (2021),
Amazon makes significant technological investments aimed at supervising workers,
transmitting orders as effectively as possible, evaluating performance in real time, and
imposing sanctions. Second, organizational practices e.g., intense work rhythms,
frequent shift changes, gamification contribute to worker isolation and fragmentation
(Prassl, 2018). Third, Amazon openly contrasts unionization.
15
This combination of
elements contributes to high levels of workers’ alienation allowing Amazon to extract a
large amount of value from its workforce. Finally, the practice of outsourcing also greatly
contributes to weakening the bargaining power of workers. In fact, alongside those
directly employed by Amazon in logistics and delivery, a large share of workers is hired
by external companies to carry out auxiliary tasks to the logistics and shipping process.
These workers often earn lower wages and are exposed to worse working conditions,
thereby generating downward competition within Amazon’s overall workforce.
Governments and retaliatory power
For digital platforms, the most opposed regulations are those that would restrict the ability
to extract and use personal data. Hindering their key strategic tool for exercising control,
these regulations are vigorously opposed (Houser and Voss, 2018). Moreover, Amazon
implements strategies aimed at warding off hostile regulations especially those related
to worker protection and reducing the tax amount. With regard to the latter aspect,
Amazon takes advantage of its international dimension by locating warehouses where it
can benefit from local tax credits (Kenney et al., 2020); and headquarters in countries
with relatively low corporate taxes.
16
Regarding the countermeasures put forth to fight
hostile regulations, a non-negligible portion of the resources accumulated through its core
activities are invested in lobbying activities (Public Citizen, 2021). Furthermore, as the
1990s corporations, Amazon relies on its retaliatory power to neutralize undesired
15
In April 2021, Amazon warehouse workers in Alabama (US) failed to unionize. Amazon’s aggressive
anti-union campaign has been extensively documented in the press; see, inter alia, Greene, 2021;
Greenhouse, 2021; Sainato, 2021. In Europe, the ability of unions to organize Amazon workers is not that
difficult. For example, the largest share of workers employed in logistics functions in Italy have joined in
the past years a class union called Si Cobas; moreover, in March 2021, a first national strike along the entire
Amazon supply chain occurred in Italy. Major strikes by Amazon workers also occurred in Germany in
2013, in France in 2014, in Italy in 2017 and in Spain in 2018 (Massimo, 2021).
16
The headquarter of Amazon EU is in Luxembourg. This year, out of record sales of €44bn (£38bn)
Amazon did not have to pay any corporation tax to the Grand Duchy (see ‘Amazon had sales income of
€44bn in Europe in 2020 but paid no corporation tax’, The Guardian,
https://www.theguardian.com/technology/2021/may/04/amazon-sales-income-europe-corporation-tax-
luxembourg; last access: May 16th, 2021).
20
regulation and influence governments. In advanced economies characterized by an
inexorable downsizing of manufacturing employment and a widespread precariety in
services, the thousands employed in an Amazon warehouse represent a strong attractive
to national and local governments. This represents both a bargaining instrument and a
blackmail weapon: Amazon can threaten to move a plant if regulatory and fiscal
conditions become unfavorable. According to Culpepper and Thelen (2020, p. 290),
however, the ability of platforms like Amazon to influence governments has additional
and distinguishing features. In fact, [u]nlike previous generations of large companies on
which the broader economy came to depend, such as railways or utility companies,
today’s largest platforms enjoy a tight, even intimate, connection to their users…platform
firms that achieve a certain economic scalewhich need not reach monopoly
proportionsbenefit from the direct relationship they enjoy with a large number of
consumers who rely on the platform as it becomes integrated into the fabric of their daily
lives. In other terms, dominant platforms cultivate and benefit from a privileged
alliance with consumers providing a formidable source of opposition to regulation that
threatens these corporations’ strategies.
To conclude, we argue that the elements listed so far (i.e., expansion and diversification,
technological investment and data harnessing, labor fragmentation and surveillance, and
countering actions to stop hostile government activities) can be interpreted as part of a
single strategy aimed at increasing control over the economy. In other words, the main
strategic objective of modern giant platforms is to extend their hierarchical power beyond
the boundaries of the enterprise by controlling all relevant physical and digital gateways
as to condition the decisions taken by consumers, suppliers, governments and other
stakeholders. In this context, the ultimate goal is to extract as much value as possible from
both the work directly employed and connected to the operation of the platform (digital
and physical); and, indirectly, from that employed by those who depend on the platform
to carry out their economic activities (e.g., locked-in suppliers, vendors, self-employed;
see Kim, 2017; Weise, 2019). In this regard, Amazon proved to be a paradigmatic
combination of ‘old and new’. One face, the one appearing on televisions, smartphones,
and devices, is that of continuous innovations, unbeatable prices, and cutting-edge
entertainment content. The old face, which Amazon shows only inside its warehouses,
resembles a new form of Taylorism characterized by high levels of surveillance,
alienation and exploitation of labour.
5. Concluding remarks
This work sought to provide an analysis of the dominant role assumed by giant digital
platforms in contemporary capitalism by following the radical perspective put forward by
Monopoly Capitalism scholars. In particular, we offered a framework aimed at
highlighting how Hymer and Cowling’s theoretical heritage may prove crucial to
understand current monopoly power in the digital platform economy. Most notably, we
argued that leading digital platforms should be conceived as planning actors whose
objective is to extend their control on other actors involved in their production and
innovation network. Accordingly, we contended that the needs and scopes of the latter
21
came to be subordinated to the needs and scopes defined by giant corporations’ strategic
decision-makers. Furthermore, we applied our framework to the analysis of Amazon,
being the latter one of the most powerful and at the same time more peculiar digital
platform of our times. This allowed us to highlight the multiplicity of aspects that, in our
opinion, provide support for our reconstruction. More precisely, we identified four
dimensions along which Amazon exerts its power of control, namely the growth and
diversification of its digital marketplace; the monopolization of commodified data and
the leverage on technology; the fragmentation and surveillance of the workforce; and its
strong bargaining power vis-à-vis governments.
We conclude this work with two final observations. The former deals with some policy
aspects that can be derived from our analysis. In particular, we suggest that a progressive
strategy aimed at both economic and political democracy should put efforts towards to
the decommodification of personal data through socialization of data and platform
infrastructures. Following the Marxian tradition, we contend that any market-based
antitrust policy would in fact risk being short-sighted since it does not tackle the private
property of the crucial asset of XXI capitalism. Alike, as stressed by Rikap (2021), more
stringent privacy protection policies risk to further strength the privatization of data, as
by fostering private ownership of the latter they contribute to the privatization of
knowledge. Conversely, as a public good, data could be effectively managed for the
benefit of society as a whole; the reason lies on the fact that, since data feed the algorithms
that we all use, they are crucial to improve the services we all need. Although this
discussion goes far beyond the scope of this work, we suggest that the dialectical
challenge should therefore concern the struggle to democratically manage data for society
as a whole without giving up the opportunities they can provide for shared prosperity.
Accordingly, an “overthrown” of the modern Monopoly Capitalism pursued through a
socialization of data and their definition as digital global public goods might give room
to a renewed technological and social feasibility of democratic social planning, also
allowing new forms of democracy.
As a final remark, we suggest that the approach we have followed could be worthy of
being extended to further investigate the historical evolution of Monopoly Capital to date.
In fact, by neglecting the powerful explanations of capitalist control as provided by
Hymer and Cowling’s contributions, economic theory is still lacking behind the fast pace
of contemporary capitalism. What we see today appears to be largely a manifestation of
what Hymer and Cowling foresaw, namely the outcome of a tendency towards the
concentration of monopoly power in the hands of a few giant corporations. As John
Powers, President of Charles Pfizer Corporation, has put it, ‘Practise is ahead of theory
and policy’” (Hymer, 1972, p. 115). Looking at the names of the major profit makers after
more than a year of pandemic makes it easy to recognize how much the theories of
Monopoly Capitalism can still teach us.
22
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We are currently living in an era of change induced by a new technological cycle that promises to redefine our culture, our society and our economy. Artificial Intelligence (AI), Machine Learning (ML), Big Data (BD), blockchain, robotics, the Internet of Things (IoT), the metaverse and the rest of cutting-edge technologies are leading a new innovative wave that is plunging us fully into the so-called IV Industrial Revolution. Given this panorama of change, it is obvious that the entire Spanish economy and its productive fabric will be totally affected. Precisely, in this thesis we want to focus our attention on how one of the most representative sectors of our economy, tourism, is facing this wave of innovation. As was already the case with the emergence of the technological leap of Information and Communications Technology (ICTs), this new innovative impulse promises to transform the sector, although with some notable differences: this new wave will bring changes that are increasingly rapid, continuous and intense over time, posing a major challenge, perhaps as never seen before, for the tourism industry. The tourism sector is one of the most consolidated and important economic sectors in the world. During the last decades, it has established itself as one of the fastest growing and largest sectors worldwide, setting a record figure of 1.5 billion international tourists in 2019, surpassing those of 2018 by almost 5% (WTO, 2020). This translates into a contribution of more than 10% to the Gross Domestic Product (GDP) worldwide, more than 7% of total international trade and nearly 30% of world exports of services, keeping pace globally with the value of oil or automobile exports, thus making tourism one of the top five activities in world trade (WTTC, 2019). Justifying the economic importance also for the Spanish case, international tourist arrivals in 2019 exceeded 83.5 million travelers, accounting for more than 11% of the total international market and a growth in travelers of almost 1% compared to 2018 figures. Thus, tourism is established as a fundamental pillar of the Spanish economy, due to its contribution to GDP, employment or economic growth, well above the rest of the OECD countries (Figure 1.1), and due to the compensating role of the external imbalance that the Spanish economy suffers structurally (Pedreño-Muñoz and Ramón-Rodríguez, 2009). These characteristics give it an undeniable resistance to the latest economic crises, although it is true that the COVID-19 pandemic has overexerted it, has forced it to transform itself once again and has made evident the excessive dependence of our economy on tourism, due to its multiplier effect on the rest of the economy, because of the transversal nature of the consumption of tourist demand. In this globalizing context and the integration of new digital technologies in practically any area of society, it is unthinkable that the evolution of the sector should be linked to the digital economy, being one of its basic pillars of development (Hojeghan and Esfangareh, 2011). This digital revolution is taking place in an environment where the number of tourists worldwide is growing steadily, with the rate of growth of tourism demand exceeding the rate of growth of the economy, due to the emergence of emerging countries, the greater ability of young generations to travel and the lower costs of air travel, and represents a significant opportunity for digital innovation in the sector. As we will discuss below, the sector in question is characterized by a low capacity to generate innovation, although at the same time it is extremely sensitive to the adaptation of its structure to new technologies. This fact implies a constant need for renewal within the sector in order to adapt its competitive capacity through the new innovations already mentioned. In fact, as we will see in this thesis, there are many examples in the literature on the adaptation of the sector to BD and AI, clean energy, mobile technology, augmented reality, IoT, virtual assistants or blockchain, among others. But all these advances have as their starting point a common element: data. These are the key element to raise the productivity of companies and make the most of these technologies, so having the ability to collect, exchange, process and analyze data is indispensable in any industry. The introduction of data and algorithms oriented to price management, demand capture, user segmentation and optimization of value chain processes, among other applications, as a fundamental part of the structure of any industry has a fundamental impact on the study of industrial economics. Researchers, public administrations, companies and all the actors involved must adapt to this new reality, implement policies that promote the digitization of the productive fabric and address new lines of research to understand the new participants, thus achieving a greater understanding of this data-driven tourism. Precisely here lies one of the main strengths of tourism compared to other sectors: it has a huge amount of varied, dispersed and representative information, as it is produced by the 'digital footprint' of the tourist on each trip. The challenge for companies in the sector, from large hotel companies to SMEs, is to make the most of this data. Otherwise, they will be swept away by new technology companies, whose main source of business is innovation, and not the tourism sector. In fact, the new technological reality of the industry has created a competitive environment in which technology-based disruptors, who know how to create new markets by satisfying untapped needs, coexist with traditional players who generally do not have the capacity to innovate. Under these premises, this doctoral thesis aims to review the economic principles of tourism from an innovative perspective, analyze the potential impact of the application of AI in the tourism industry at all levels and the need for the use of machine learning algorithms in research in the sector. To this end, first of all, the conceptual framework on which it is framed is constructed. Chapter II of the thesis is devoted to a review of the evolution of the concept of innovation and its importance in economic theory. For this purpose, theoretical references that have studied the role of technology and innovation in economic growth, such as Schumpeter, Solow, Romer or Lucas, are studied. The aim is to understand the impact that the disruptive changes we are experiencing in the economy are having, in order to subsequently apply them to the transformation of the structure of the tourism industry. It is precisely in Chapter III where an applied analysis of innovation and the impact of new technologies on the tourism sector is carried out. It will study the state of innovation in the tourism sector, making important clarifications on the sector's capacity to adapt or develop innovations. In addition, it will explain the digital principles that are transforming the tourism industry and the new research cycle derived from the emergence of BD and which is led by techniques based on ML algorithms, thus justifying the choice of the tourism sector as a case study. Chapter IV provides a complete review of the transforming process that the structure of the tourism industry is undergoing due to the technological paradigm shift. Thus, it studies how these innovative processes are developing a new tourism demand based on data, how the tourism value chain is being reinvented, how tourism prices are set in a market with almost perfect information, what challenges are posed for the labor and training market in the sector, and what role they play in the emergence of new technology-based competitors in the sector. In Chapters V and VI, Airbnb is chosen as an applied case study, as it is representative of all the challenges faced by the sector in terms of technology, political regulation, market intervention, reinterpretation of the tourism value chain, emergence of economic or pandemic shocks that researchers must face. The applied analysis of Airbnb aims to contribute to the research of the sector in this empirical context dominated by BD and by the increasingly imperative need to apply machine learning-based algorithms to understand the different challenges posed by Airbnb in the sector, highlighting among them the processing and simplification of huge databases. Chapter V has as a case study Madrid, the capital of Spain and the fourth destination by number of Airbnb ads in Europe. For this applied case, we study whether the COVID-19 pandemic had a significant impact on the structure of Airbnb supply and demand. For this purpose, the study starts from a logit model of hedonic panel data, different alternative methods of variable selection and likelihood tests are applied to confirm the existence of the structural change affecting the decision making when renting an apartment from the Platform. This work aims to contribute to the research of the sector, and specifically of Airbnb, based on BD. Chapter VI focuses the study on the Valencian Community, one of the main sun and beach tourist destinations, to carry out an analysis on the pricing of tourist accommodation on the platform. This case study aims to analyze whether the application of ML algorithms allows companies to optimize prices in a more efficient way than traditional models. To this end, the performance of a traditional hedonic pricing model is compared to an estimation model based on neural networks to demonstrate the best fit in the predictive capacity of machine learning-based techniques when setting prices. Thus, the doctoral thesis constitutes a valuable and novel contribution to the new research cycle in the sector. It proposes an exhaustive review of all the implications and applications of new technologies in tourism and the advantages of using machine learning based analysis techniques for researchers in their study.
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