The evolution of the global digital platform economy: 1971–2021

Abstract

Plain English Summary
Some years, like some poets and politicians, are singled out for fame far beyond the common lot and 1971 was clearly such a year. One of the events of 1971 was the inventions of the microprocessor, a computer on a chip. This invention led to the creation of the personal computer, the internet, the smart phone, and cloud computing. Over the past 50 years, economic activities have been reorganized from large bureaucratic firms to a more networked form of organization for creating value for consumers and making money for companies. To further our understanding of this digital revolution, we provide a framework consisting of three interrelated concepts: digital technology infrastructure, multi-sided digital platforms, and platform-based ecosystems. Using a unique database over five decades, we test the hypothesis that new firms were needed to introduce digital technologies. Countries that did not promote new firms fell behind in adopting the new technologies.

Full text

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The Evolution of the Global Digital Platform Economy:
1971-2021
Zoltan J. Acs, George Mason University**
Abraham K. Song, George Mason University*
László Szerb, University of Pécs, Faculty of Business and Economics
David B. Audretsch, Indiana University
Éva Komlósi, MTA-PTE Innovation and Economic Growth Research Group
March 2021
Abstract: The emergence of digital technologies has significantly reduced the economic costs
of data—search, storage, computation, transmission—and enabled new economic activities.
Over the years, firms able to create a platform-based ecosystem have become a force of
“creative destruction.” Economic activities (C2C, B2C, B2B) have been reorganized around
platform-based ecosystems for value creation and value appropriation, which are orchestrated
by multisided platforms via the “digital hand.” To further understanding of the Digital Platform
Economy, this paper provides a conceptual framework consisting of three interrelated concepts:
digital technology infrastructure, multisided digital platforms, and platform-based ecosystems
(users and entrepreneurs). Quantifying the digital platform economy uncovers a European lag
in platformization relative to the United States and Asia; European incumbent firms have not
introduced new technologies in sufficient volume, and startups there have remained small and
not scalable.
Keywords: entrepreneurship; ecosystems; multisided platforms; platform economy; users;
transaction costs; digital economics.
JEL: L20; M13; O33; D23; D83
Acknowledgments: This paper grew out of a larger research project on systems of
entrepreneurship and entrepreneurial ecosystems, which was conducted over the past decade at
Imperial College Business School and the London School of Economics. The project built on
earlier work on national systems of entrepreneurship and the Global Entrepreneurship Index at
the University of Pecs, George Mason University and the GEDI Institute. We would like to
thank Robert Wuebker, Connie L. McNeely, Hilton L. Root, Silvio Vasmara, Esteban Lafuente,
Avi Goldfarb, and Saul Estrin for valuable comments, and seminar participants at 2018 and
2020 Conference on Digital Entrepreneurial Ecosystems hosted by the Center for
Entrepreneurship and Public Policy (George Mason University), 2019 Frontiers in International
Business Conference, “The Digital Economy in a Multi-Polar World” at Darla Moore School
of Business (University of South Carolina), 2020 “5th Annual Global Strategy and Emerging
Markets (GSEM) Conference: Competing in the Digital World,” SC Johnson College of
Business (Cornell University ) 2020 “Measuring the Digital Entrepreneurial Ecosystem:
Business Policy Implications” Research Policy Special Issue Conference for helpful comments.
The usual caveat applies.
*Lead Author: zacs@gmu.edu **Corresponding author: ksong7@gmu.edu

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1. Introduction
Some years, like some poets and politicians, are signaled out for fame far beyond the common
lot, and 1971 was clearly such a year. Like—1066, 1929, and 1945—it is a year that everyone
remembers. One was born before 1971 or after 1971. Fifty years ago America invented the
future: A reference to 1971 is shorthand for these events.
1
The 26th Amendment was ratified,
lowering the voting age to 18 from 21. NASDAQ, Greenpeace and Starbucks were founded.
Henry Kissinger’s secret July trip to China kicked off 50 years of diplomacy, trade and travel
between China and the U.S. It was the end of Brenton Woods—the posts war monetary
system—as the United States went off the gold standard. In November Intel Corporation
introduced the Intel 4004 chip. This was the first microprocessor—essentially a complete
computer on a chip—able to receive instruction and act as the brains of a general-purpose
computer. Although it was quickly replaced by better products the path to modern computing
became clear. Today, the most advanced computer chips, for example, the AMD EPYC Rome,
has upwards to 40 billion transistors.
2
What followed was a global technological revolution
without parallels in world history—The Digital Age (Sachs, 2020).
Bart Hobijn and Boyan Jovanovic (2001) argued that the arrival of the information technology
revolution in the 1970s created the need for new firms, as the stock market incumbents of the
day were unable to harness new digital technologies.
3
The stock price of incumbents fell
immediately after the information technologies arrived. After the mid-1970s, new firms were
needed to bring technology to market. Breakthroughs in technology favor new firms, for three
reasons: awareness of technology and skill, vintage capital, and vested interests. In the United
States, venture capital flowed to startups that built new industries (Gompers & Lerner, 2001);
Europe did not follow suit (Naudé, 2016); Asia took advantage of the opportunity (Root, 2020).
The events of 1971 precipitated a chain reaction a decade later to bring new firms online. In the
United States the 1980s ushered in the Reagan Revolution, which shifted the emphasis for
government policy from the giant corporation to entrepreneurs and startups (Gilder, 1981) and
severed the Galbraithian relationship between business, government, and labor.
4
The concept
of countervailing power (Galbraith, 1952) was abandoned, when then president Ronald Reagan
fired 33,000 striking air traffic controllers in 1982, signaling the government’s more balanced
position in business-labor relations. On January 8, 1982, a consent agreement between the U.S.
Justice Department and AT&T broke up the nation’s second-largest company (Evans &
Bornholz, 1983). AT&T had failed to keep up with technological change and did not introduce
new products into the market. The dearth of innovation led to the entry of new firms into the
telecommunication industry.
Moreover, in 1982, IBM founded in 1911, launched the personal computer, whose key
components, however, were supplied by two startups: Intel Corporation founded in 1968,
supplied the Intel 8088 chip with 29,000 transistors and Microsoft, founded in 1975, supplied
the disk operating system (DOS). This was the birth of the digital platform economy (DPE),
1
Wall Street Journal, Daniel Casse, ‘The Future Turns 50 This Year’, January 1, 2021.
2
Source: https://en.wikipedia.org/wiki/Transistor count
3
Also see Greenwood and Jovanovic (1999).
4
Gilder (1981, p. 43) explained that “the source of the gift of capitalism is the supply side of the economy.”

3
which changed the structure of the U.S. economy (Acs, 1984). Dale Jorgenson described the
onset of the information technology revolution and its economic impact, explaining that the
resurgence of the U.S. economy in the 1990s outran all but the most optimistic expectations.
He noted that, “The foundation for the American growth resurgence is the development and
deployment of semiconductors” (Jorgenson, 2001, p. 1).
5
The literature on the information technology revolution and the evolution of the American
growth resurgence is scattered over many different fields—economics, management, business,
computer science, information science, telecommunications, operations research, and
management science—making it difficult to fully understand from any one perspective.
6
The
purpose of the paper is to further understanding of the evolution of the global digital platform
economy. The paper develops a conceptual framework of the platform economy consisting of
three interrelated concepts: digital technology infrastructure, digital multi-sided platforms, and
platform-based ecosystems. The term DPE was coined in 2016 by Martin Kenney and John
Zysman as “a more neutral term that encompasses a growing number of digitally enabled
activities in business, politics, and social interaction.”
7
If the industrial revolution was
organized around the factory, the managerial revolution around the corporation, the information
technology revolution is organized around digital platforms, loosely defined (p. 62). But
whereas Kenny and Zysman, among others, focused on the nature of work, this paper focuses
on the changing structure of the economy and the evolution of the firms that made it possible
(Audretsch, 1995).
The paper makes three contributions. First, using a unique database over five decades of
surviving firms we test the Hobijn and Jovanovic (2001) thesis that the incumbents of the day
in the 1970s were unable to harness new technologies and that new firms were needed to create
the DPE (Audretsch, 1991). Second, we develop a conceptual framework of the DPE that
integrates the platform-based organization, their platform-based ecosystem, and the digital
technology infrastructure (Sussan & Acs, 2017; Song, 2019).
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Applying the DPE framework
to the global economy, we identify and measure the firms of the platform economy that have
publicly available data. We estimate that the global DPE consists of billions of supply-side and
demand-side users, millions of app developers, thousands of digital infrastructure firms, and
hundreds of multisided platform firms. Third, we provide a policy framework for analysis of
the global DPE focusing on the European Union, the United States and China.
9
The rest of this paper proceeds as follows. Section two presents the theoretical foundation of
digital economics and why digital markets give rise to platforms. Section three examines the
platform economy, focusing on the key actors (the platform organization, the platform-based
ecosystem, and enabling digital organizations). Section four measures the firms of the digital
platform economy for each component of the model. Section five presents the discussion, and
section six is the conclusion. We find that startups played a crucial role in the evolution of the
digital platform economy and offer insight into why some countries are ahead.
5
See Acs and Audretsch (1987, 1988, 1990); Audretsch (1991 ); Acs, Audretsch and Feldman (1992, 1994); Audretsch and
Feldman, 1996); Anselin, Varga and Acs (1997); Acs, Anselin and Varga, (2002).
6
For a review of the literature see Jia, Cusumano, and Chen (2019).
7
Also see Peitz and Waldfogel (2012).
8
See Nambisan (2017); Srinivasan and Venkatraman (2018); Nambisan, Siegel, and Kenney (2018); and Sahut, Iandoli, and
Teulon (2019).
9
For a comparison across countries, see, Acs, et al 2020, “The Digital Platform Economy Index: 2020, The GEDI
Institute, www.thegedi.org.

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2. The ITR and the Cost of Information
The information technology revolution (ITR) is about digital technology and the representation
of information in bits (Shannon, 1948), and digital economics examines whether and how
digital technology changes economic activity (Goldfarb & Tucker, 2019). Information in bits
reduces the cost of storage, computation, and transmission of data; digital technologies reduce
five distinct costs that affect economic activities: search, replication, transportation, tracking,
and verification. Lower search costs lead to more matching and peer-to-peer platforms, which
increases the efficiency of trade. Most of the major technology firms can be seen as platform-
based businesses, and there are two main reasons why digital markets give rise to platforms
(Jullien, 2012). First, platforms facilitate matching because they provide a structure that can
create efficient matches by taking advantage of low search costs. Second, platforms increase
the efficiency of trade through lower search costs, lower reproduction costs, and lower
verification costs (Goldfarb & Tucker, 2019, p. 13).
Transaction cost economics explain the rise of the managerial economy and the hierarchical
organization as a choice between markets or hierarchies. The shift from the managed economy
to the platform economy requires a different approach—digital technology. Digital technology
changes economic activity by reducing costs, and agents solve an optimization problem
(Goldfarb & Tucker, 2019). There is a key assumption in transaction cost models—that the
transaction is the unit of analysis. Agents check factors that impact transaction costs, including
transaction properties (asset specificity, information asymmetries, and uncertainty) and agents’
properties (bounded rationality and opportunism). Once these costs are estimated, the agent
chooses the cost-minimizing governance structure—that is, the market or the hierarchy. These
properties primarily create three types of costs: information costs (searching supplies,
distribution channels, etc.); bargaining costs (contract regulating relationship between the firm
and the suppliers or customers); and monitoring costs (quality control). How do transaction
costs differ from information costs? Information costs are part of transaction costs, but they are
different in at least two ways. First, information cost strategies mostly use the agent (and its
effort) as the unit of analysis that solves an optimization problem in a model. Second,
information costs usually occur when an agent acts or makes an effort, and these costs often are
not minimized but optimized; in fact, optimization is the desired goal. Good managers do not
try to save money by scouting a few potential suppliers; they strive to find the best or close-to-
best suppliers.
The central economic accomplishment of the ITR is the reduction of information costs via
multisided platforms: the digital hand of platforms (Evans, Hagiu, & Schmalensee, 2008). In
the industrial age (1800-2000) economic decisions were made by management. In the digital
age (2000-present) economic decisions are made by software programs (Sachs, 2020).
Platforms and platform-based ecosystems create markets where none existed previously
because of high costs. While the corporation was able to reduce transaction costs by bringing
markets inside the organization, thereby making economies of scale and scope possible, this
hierarchical management was achieved at a cost, as there are costs attached to using the
organization, albeit less than using the market (North, 1992). By reducing the need for
bureaucracy, the platform organization has been able to reduce costs—search and information
costs, bargaining and decision-making costs, and policing and enforcement costs—to almost
zero. Moreover, the associated costs of authority and power have also been reduced by
substituting networks for bureaucracy (Ferguson, 2018). With huge computing power,

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sophisticated algorithms, and big data, market transactions mediated through multisided
platforms have reduced the cost of and the need for hierarchy and hierarchical power.
Table 1 outlines the evolution of the economy over three centuries by presenting the key
parameters and the main economic theories that have explained economic development and its
accomplishments during those 300 years. The coordination in the 21st century shifts from the
visible hand of management to the digital hand of platforms. The platform organization replaces
the vertically integrated firm via network effects. This new organization form has a global
ecosystem that did not exist under managerial authority. The main form of knowledge is human
capital with much less physical capital. The engine that drives the digital economy is the
microprocessor as it reduces the cost of storage, computation and transmission of data.
Table 1: The Evolution of Markets, Hierarchies, and Networks.
Category
19th Century
20th Century
21st Century
Coordinator
The Invisible Hand of the
Market
The Visible Hand of
Management
The Digital Hand of
Platforms
Organizational Form
The Factory
The Corporation
The Platform
Institution
The Market
Hierarchy
Networks
Governance
Entrepreneur
Managerial Authority
Ecosystem Governance
Knowledge
Knowledge with People
Knowledge in Physical
Capital
Knowledge in Human
Capital
Geography
Local
National
Global
Economic Theory
General Equilibrium
Theory
Transaction Costs,
Economics, and
Institutional Economics
Two-Sided Markets,
Network Theory and
Complex systems
Engine
Steam
Internal combustion
Microprocessor
Energy
Coal
Oil
Electricity
Transportation
Goods
People
Information
Note: See Chandler (1977) on the visible hand of management.
As pointed out above, the DPE has been 50 years in the making, and each decade since the
1970s has seen major advances. As shown in Figure 1, the 1970s saw the development of the
microprocessor, the 1980s the personal computer (PC), the 1990s the internet, the 2000s the
smart phone, and the 2010s cloud computing. These advances are both sequential and additive,
in other words they are evolutionary (Audretsch, 1995).
The development of semiconductor technology saw its application to the PC. In 1980,
Commodore Business Machines sold one million machines. In 1982, IBM launched the first
widely available PC, which had an operating system made by Microsoft, the first platform
company, and a chip made by Intel. In 1983, Compaq introduced a portable PC compatible with
the IBM PC. The first killer app of the PC world was Lotus 123. Microsoft launched the
Windows 1.0 operating environment to go with the personal computer in 1985, and the 1990s
saw the launch of the internet.
AOL was founded in 1989 to provide internet access via the existing landline technology, and
it was a huge success before the introduction of high-speed internet. Between 1989 and 1998,
AOL grew from 100,000 members to more than 14 million. Yahoo and Netscape joined the
field in 1994, and the next year Microsoft introduced Windows 95, bundled with Internet
Explorer. Google appeared on the scene in 1998. During the 1990s, these software companies
made access to the WWW, the laptop, and the search engine an essential part of global business.

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By the end of the 1990s, the infrastructure of the digital transformation in terms of service
providers and the continued progress in chip technology had set the stage for the 2000s. In
effect, this infrastructure is the backbone of the ITR, and it is analogous to the highway system
and the automobile.
The 2000s saw the launch of the smartphone and the emergence of the platform-based
ecosystem. In 2007, the five major mobile phone manufacturers—Nokia, Samsung, Motorola,
Sony Ericsson, and LG—collectively controlled 90 percent of the industry’s global profits.
Apple’s iPhone burst onto the scene that year and began gobbling up market share. By 2015,
the iPhone was singlehandedly generating 92 percent of global profits in the mobile phone
market, while all but one of the former incumbents made no profit at all.
By 2010, the digital revolution was well under way, with enormous growth and huge progress
in the sophistication of semiconductors, the internet, and its service providers. The DPE was in
place with platform organization and a platform-based ecosystem of users and agents.
Moreover, the platform companies identified the importance of the ecosystem and developed
business models to create and extract value. The founding of Airbnb, Uber, Snap, Facebook,
Twitter, WhatsApp, Open Table, and a host of social media companies ignited the platform
revolution in the second decade of the 21st century. In 1971, the five largest U.S. companies by
revenue were IBM, AT&T, Eastman Kodak, General Motors, and Standard Oil of New Jersey
(Exxon); 50 years later the five most valuable companies in the United States were Apple,
Amazon, Microsoft, Facebook, and Google—each valued at or near $1 to $2 trillion.
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On the surface the evidence seems to support Habijn and Jovanovic (2001) conjecture that new
firms were needed to introduce the new technologies. Of the 167 publically traded companies
that make up the DPE 86% were startups in their decade. While during the 1970 there was a
mix of old and new firms introducing microprocessors, the key breakthroughs came from Intel
and ADM both started in 1968. By the 1980s computer industry was dominated again by old
and new firms, however, the gap had narrowed. During the 1990 with the introduction of the
internet and search engines almost all of the firms were now startups.
In the 2000s while there were still old firms in the smart phone market many of the firms were
now new. By the 2010s as cloud computing took off with the emergence of social media and
transaction platforms almost all the firms introducing digital technologies were startups
confirming what Habijn and Jovanovic (2001) predicted for the early decades of the platform
revolution. There are two key caveats. First, the most successful of the platform companies
operated in more than one technology. For example, Apple, Google, Amazon, Facebook,
Microsoft, Alibaba, Tencent are active in computers, smart phones and cloud computing.
Second, as the technology became newer it favored startups over incumbents. Of the 58
companies in cloud computing 51 are startups.
10
See https://www.androidcentral.com/alphabet-becomes-fourth-trillion-dollar-company.

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Figure1. The Evolution of the Digital Platform Economy
Source: https://www.chinawhisper.com/top-20-most-popular-websites-in-china/; https://www.worldatlas.com/articles/the-25-largest-internet-companies-in-the-world.html;
https://www.cbinsights.com/research-unicorn-companies; https://www.visualcapitalist.com/biggest-tech-companies-market-cap-23-years/;
https://www.youtube.com/watch?v=MirrGCbsIp4; https://www.forbes.com/top-digital-companies/list/#tab:rank; https://en.wikipedia.org/wiki/Transistor_count;
https://www.statista.com/chart/4112/smartphone-platform-market-share/; https://fxssi.com/top-10-most-valuable-companies-in-the-world
Note: Semiconductor firms are in red; personal computer firms are in blue; internet firms are in green; smartphone firms are in orange; digital platform firms are in purple. Bolded are
the seven most valuable multisided platforms: Google, Apple, Facebook, Amazon, and Microsoft (a group of U.S. firms commonly known as “GAFAM”); also, China’s Alibaba and
Tencent. In parenthesis are founding dates. * denotes that the company is privately held, otherwise public. The list attempts to include major firms in each technological innovation but
is not intended to be comprehensive. Broadband and cellular service provider firms are not included. Some firms appear more than once. Panasonic was formerly Matsushita Electric
Industrial Co. Harris Corporation was the parent of Intersil (Harris Semiconductor). Broadcom was formerly Avago Technologies (1961-2016). Dotdash was formerly About.com. Paypal
resulted from a merger of Confinity (1998) and X.com (1999). Nippon Electric Company was founded in 1899 and renamed NEC Corporation in 1983. Activision Blizzard was founded
in 2008 through the merger of Activision (1979) and Vivendi Games (1996). Rakuten was MDM, Inc. between 1997 and 1999. The Priceline Group was priceline.com before 2014, and
the Priceline Group Inc. renamed itself Bookings Holding Company in 2018. Fiserv dates back to the 1984 merger of Sunshine State Systems, Inc. and First Data Processing. A major
unit of CompuServe (founded 1969), the CompuServe Network Services, was formed in 1982 and became the first major commercial online service provider. Tencent developed WeChat,
a multipurpose messaging, social media, and mobile payment system, in 2011. Viber, a cross-platform voice over IP (VoIP) and instant messaging software application, was developed
in 2010 by Viber Media, which was acquired by Rakuten in 2014. In 2013, PayPal acquired the mobile payment service Venmo (founded 2009). Paytm is a fintech company owned by
One97 Communications Ltd. (founded August 2010). Fidelity National Information Services, Inc (or FIS) acquired Worldpay, the largest U.S. merchant acquirer, in 2019.

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3. The Platform Economy
The term platform economy or more precisely the digital platform economy encompasses a
growing number of digitally enables activities in business, politics and social integration (Kenny
and Zysman, 2016, p. 62). We propose three main ways to think about the DPE based on the
literature: digital technology infrastructure, multisided digital platforms, and platform-based
ecosystems (users and entrepreneurs). Saadatmand, Lindgren, and Shultze (2019) describe “digital
platforms as an emergent organizational form characterized by technology and social processes:
(1) a technological architecture constituted of a modular core, standardized interfaces and
complementary extensions, and (2) a set of governance mechanisms to manage an ecosystem of
independent complementors who complete the platform’s value proposition by co-creating its
value” (p. 1).
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A thin layer of management represents the organizational and strategy parts of the
platform.
3.1 Digital Multisided Platforms
Alongside the shift from hierarchies to networks over the last few decades is a new breed of
businesses equipped with digital technologies that has disrupted industries, including finance,
communications, advertising, and operating systems, as well as various internet-based industries
ranging from real estate to transportation. Some are startups that have become new market
leaders—Uber and Airbnb, Facebook and Amazon, Apple, Netflix, and Google. Many of them are
“matchmaker” businesses whose core competency is the ability to match one group of users with
another by reducing information costs. Advancements in information and communications
technologies opened a pathway for these businesses. More specifically, platforms are enabled by
technological openness (architectural interface specification) and organizational openness
(governance), both of which are mediated by the platform owner. This rise of digital multisided
platforms as avenues for value creation, value capture, appropriation, and innovation is commonly
known as platformization. A looser definition of a platform is where social and economic
interactions are mediated online, often by apps.
In the industrial economics view, platforms, variously referred to as two-sided markets, multisided
markets, or multisided platforms, are seen as special kinds of firms that facilitate exchange by
allowing direct transactions between different types of consumers who could not otherwise transact
(Armstrong, 2006; Evans & Schmalensee, 2008; Evans, 2003; Rochet & Tirole, 2003, 2006;
Rysman, 2009). Network effects (also called network externalities) between the two sides of the
market are seen as central in this tradition—so much so that Rysman (2009, p. 127) states that, “in
a technical sense, the literature on two-sided markets could be seen as a subset of the literature on
network effects” (Cusumano et al., 2019).
One significant insight from the economic view of platforms is that, in order to understand how
platforms create value, we need to change the fundamental unit of analysis of market interactions
away from the traditional two-agent dyadic interaction into a three-agent triangular set of
transactions. In the traditional model, sellers sell directly to buyers, and buyers are attracted
primarily by features of the goods being sold, such as quality and price. In a platform, sellers do
11
For a review of the literature, see Rysman (2009); Gawer (2009); McIntyre and Srinivasan (2017); de Reuver, Sorensen, and
Basole (2018); Jacobides, Cennamo, and Gawer (2018); Jia, Cusumano, and Chen (2019).

9
not sell directly to buyers; rather, both are different “sides” of the platform, which brings the two
market actors together. In addition to the products’ quality and price, having more sellers tends to
attract more buyers, and having more buyers tends to attract more sellers. This back and forth is a
positive feedback loop that we refer to as platform-mediated network effects (Cusumano et al.,
2019).
A number of features distinguish platform businesses from traditional businesses. First, platform
businesses are intermediaries or matchmakers whose core competency is in reducing or eliminating
transaction costs (Coase, 1937). Interestingly, platforms reduce transaction costs in the market
outside the firm, rather than inside the firm, as was the case in traditional businesses (Evans &
Schmalensee, 2016). Second, platform businesses are demand-side driven, meaning that users play
a far more central role in the business model. Accumulating users is critical for platform businesses
in terms of generating quality matches and value appropriation. For platforms that get it right, the
effects of positive feedback will self-reinforce the growth of platform users and value. Industries
with network effects are known for having winner-takes-all tendencies (Schilling 2002). Third,
digital technology is deeply embedded in the core value proposition and existence of platform
businesses. In the last two decades, increased computing power and decreased computing costs
have enabled a continuous stream of innovations in the IT sector (Jovanovic & Rousseau, 2005;
Bresnahan & Trajtenberg, 1995). Proliferation of the internet, open source software, and cloud
computing have generally lowered the costs of experimentation (Nanda & Rhodes-Kropf, 2016;
von Briel, Davidsson, & Recker, 2018).
Platform organizations need to manage their platform-based ecosystem for billions of users and
millions of entrepreneurs across the globe. They also are embedded in local ecosystems, such as
Silicon Valley, Seattle, and Beijing. In effect, the platform organization originates in a region where
firms rely on the local knowledge base, knowledge spillover, and the human capital that powers
the platform organization (Acs, Braunerhjelm, Audretsch, & Carlsson, 2009). It may even be
integrated into a local campus ecosystem, such as Stanford University (Miller & Acs, 2017). In
effect, there may not be a regional entrepreneurial ecosystem that is independent of the platform
organization’s ecosystem, which is simultaneously local and global (Song, 2019; Acs, Stam,
Audretsch, & O’Connor, 2017; Stam, 2015; Acs, Autio, & Szerb, 2014).
3.2 The Platform-Based Ecosystem
One of the main institutional differences, if not the main difference, between the managed economy
and the platform economy is the role of the platform-based ecosystem. While a large literature has
now developed on entrepreneurial ecosystems, it often is confusing because a regional based
entrepreneurial ecosystem has no governance structure, no revenue and no network (Velt, Torkeli,
& Line, 2020). Many have argued that entrepreneurial ecosystems appear to be a regional or local
phenomenon (Stam, 2015), but when comparing entrepreneurial ecosystems with platform-based
ecosystems, including the role of digital technology, it is evident that the platform-based ecosystem
is immediately global in nature, with billions of users and millions of agents (Sussan & Acs,
2017).
12
Platform-based ecosystems are developed and nurtured not by regions or governments but
by platform organizations. Ecosystem governance, the rules by who gets on a platform, and the
12
Malecki (2018) emphasized the regional aspect of entrepreneurial ecosystems, and Cavallo, Ghezzi, and Balocco (2018) focused
on the present debates and future directions.

10
rules of good behavior are determined by the owners of the platform firms (Nambisan, Zhara and
Lou, 2019).
Sussan and Acs (2017) were among the first to recognize the shortcomings in the ecosystem
literature. They observed a significant gap in the conceptualization of entrepreneurship in the
digital age, which ignores the fundamental role of knowledge as a resource in the economy. To
address this gap, Sussan and Acs proposed a novel framework the digital entrepreneurial
ecosystem, which integrates two separate but related literatures on ecosystems—namely, the digital
ecosystem literature and the entrepreneurial ecosystem literature. This new framework situates the
platform-based ecosystem in the broader context of users, agents, infrastructure, and institutions,
such that two biotic entities (users and agents) actuate individual agency, and two abiotic
components (digital infrastructure and digital institutions) form the external environment.
13
Song
(2019) further refined the digital entrepreneurial ecosystem framework and expanded it to include
multisided platforms.
14
The ITR elevated the role of users and agents, as well as the creation of platform-based ecosystems
that facilitate their social and economic activities. These platforms offer important benefits to
agents, such as access to established markets, reliable transactions, and guaranteed operability. In
effect, platforms have dramatically lowered the cost of developing and distributing mobile
applications and other complementary products that connect to platforms, which worldwide app
developers and other agents can exploit using heterogeneous knowledge resources. In short,
entrepreneurial innovation closes the gap between supply opportunity and demand needs within
platforms. Using technology effectively and mobilizing production factors by third-party
complementors increases platform efficiency. Figure 2 shows the relationship between users and
agents and how they populate multisided platforms.
Digital User Citizenship consists broadly of consumers (demand side) and producers (supply side)
that are proficient in platform usage. Digital users connect to each other for economic and social
activities through the internet and mobile devices on various digital platforms. Diffusion rates to
these technologies attest to their utility and to users’ willingness to adopt them. Online participation
thus requires a certain level of digital trust (e.g., user privacy) and digital proficiency (e.g., writing
code, writing a movie review, rating a restaurant). Users should abide by the civic norms of the
digital space and be discouraged from cybercrime (Terranova, 2000).
Digital technology entrepreneurs are third-party agents that partake in experimentation, innovation,
and value creation and use hardware/software to build products that connect to innovation
platforms. This reconfiguration combines technology entrepreneurship and digital
entrepreneurship (Giones & Brem, 2017). In the information systems literature, “digital artifact” is
the term used to describe a digital component, application, or media content that is part of a product
and offers functionality and value to the end user (Ekbia, 2009; Kallinikos, Aaltonen, & Marton,
2013).
Tom Goodwin (2015), senior vice president of strategy and innovation at Havas Media, observed
that “these companies are indescribably thin layers that sit on top of vast supply systems (where
13
Nambisan, Wright, and Feldman (2019) approached the subject from the digital transformation side and how it has
transformed entrepreneurship and innovation.
14
See also Nambisan (2017); Srinivasan and Venkatraman (2018); Nambisan et al. (2018); Sahut et al. (2019).

11
the costs are) and interface with a huge number of users (where the money is).” Finally, platforms
give a firm a competitive advantage over traditional business. Stephen Elop, the CEO at Nokia,
stated in a company memo that, “our competitors aren’t taking our market share with devices; they
are taking our market share with an entire ecosystem.”
15
Apple and Google opened up their
platforms and provided application programming interfaces, software development kits, and other
boundary resources that enabled complementors to access, customize, and exploit market
opportunities within their digital platforms.
Figure 2: The Digital Entrepreneurial Ecosystem
Source: Song (2019)
Note: Sections shaded in yellow are the two biotic entities, namely, digital users and agents.
3.3 Digital Technology Infrastructure
The final building block of the DPE is the Digital Technology Infrastructure. As digital
technologies increasingly become more service focused, socially embedded, and laden with
intensive human interactions, a more open, inclusive, global, dynamic, and flexible view of digital
infrastructure (DI) is needed to capture the effects of digitalization (Tilson, Lyytinen, & Sørensen,
2010). The term “digital technology infrastructure” is used interchangeably with information
infrastructure, IT infrastructure, and e-infrastructure (Henfridsson & Bygstad, 2013).
15
Our competitors aren't taking our market share with devices; they are taking our market share with an entire ecosystem.

12
Anchored in digital technologies, DI is a socially embedded mechanical system that includes
technological and human components, network, systems, and processes that generate self-
reinforcing feedback loops. DI thus links systems and networks at the global, national, regional,
industry, and/or corporate levels, and it is constantly changing because of its diverse base of
installed digital technologies and users who are designers or operators of these systems (Tilson et
al., 2010). In that sense, DI does not have a single defined set of functions or strict boundaries.
Rather, multiple layers of systems and processes are at work simultaneously, which results in a
decentralized, shared, and distributed DI that is not subject to a single centralized stakeholder’s
control. DI is often researched within an organizational setting or a community of practice (e.g., a
group of IT professionals).
As control of the digital infrastructure is distributed across multiple actors, such as designers,
developers, and users, it is difficult to govern (Henfridsson & Bygstad, 2013). The open access and
open standards of the internet allow anyone to develop and share applications. DI is constantly
evolving and is therefore “a system that is never fully complete and the public and ordinary
organizational members can be trusted to invent and share good uses” (Zittrain, 2008, p. 43). While
there are standards among its members, a static set of standards is impossible to attain. Furthermore,
the bottom-up nature of DI and the top-down reality of most organizational structure make
governance of DI a particular challenge.
Being an open system, DI allows participants to contribute freely, with few boundaries. It thus
becomes an enabler for individual innovators, as long as they follow standard interfaces (Hanseth
& Lyytinen, 2010; Zittrain, 2008). Because of DI’s flexibility and feedback loop capabilities,
internet entrepreneurs in Silicon Valley display new forms of learning by creating new paths of
innovation, which leads to new services and products that reinforce DI as a basis for innovative
activity.
Cloud computing services, the use of remote servers over a network, have revolutionized how
business is conducted today. These servers provide various functionalities, such as storage,
processing, security, and analytics. From messaging to file-sharing, payment to data management,
surveys to website building, there is not an industry untouched by cloud computing. Cloud services
have opened new business opportunities for both corporations and startups alike. The leaders in
the cloud computing services are: Microsoft Azure, Amazon Web Services, Google Cloud, IBM
Cloud, and Oracle Cloud Infrastructure. Many of these leaders are multi-sided platforms
recognizing the importance of IT infrastructure for digital platform economy. Consider that
Google’s main consumer products like its search engine, Gmail, YouTube, and Google Drive are
all cloud-based applications. These applications are transformative also for businesses. Large
amounts of data can be stored and accessed efficiently and at low cost, all provided with guaranteed
security and flexibility. Furthermore, using modern technologies, such as artificial intelligence and
machine learning, vast quantities of data are not only stored but analyzed, and then converted to
valuable business intelligence, a competitive moat.
Governments can only encourage digital entrepreneurship projects after investing in the necessary
digital infrastructure. They usually do so ex ante so they can invest in digital projects ex post. The
quality of government investment in digital infrastructure conditions the outcomes of digital
entrepreneurship. Once these investments are in place, entrepreneurship projects will emerge
(Kenny & Zysman, 2016).

13
4. The Firms of the Digital Platform Economy
When economists think about the economy, the role of firms and factor markets—the supply side—
take center stage. In managerial capitalism, the giant corporation is the central organization of
interest, as factor markets are internalized and the market mechanism is replaced by the modern
business enterprise in allocating resources and guiding the economy (Marris, 1964). A much more
diverse set of organizations exists in the platform economy, and technology plays a more
fundamental and varied role than it did in the managed economy. The platform economy
externalizes at least some of the factor markets to the ecosystem—a group of autonomous actors
bound together by complementarities and distributed governance. Two sets of actors, agents and
users, populate the platform-based ecosystem that multisided platforms rely on for innovation
(agents) and revenue (users). The platform-based ecosystem plays a role in both value creation and
value capture (Evans and Schmalensee, 2007, 2016).
What types of firms populate the DPE? Figure 3 shows the relationship between four types of firms
in the platform economy. Platform owners occupy the digital platform quadrant.
Telecommunications service and equipment firms occupy the digital infrastructure quadrant. They
provide services to users, who in turn provide revenue to platform firms that carry out the matching
between supply- and demand-side users. Supply-side users, with the largest number of firms in the
platform economy, are nontechnology organizations that include merchants of all kinds—including
restaurants, Uber drivers, and the self-employed. New technology-based firms, which number in
the millions, carry out most of the innovation in the platform economy. They include hardware and
software firms including app developers.
16
The size distribution of firms in the platform economy
is highly skewed, with a small number of very large firms, thousands of medium-size firms, and
millions of small firms.
Figure 3: The Digital Platform Economy
Note: Sections shaded in green are the digital users, digital entrepreneurs, and digital platforms that make up platform-based
ecosystems.
16
See Rochet and Tirole (2003, 2006); Gawer (2009); Evans and Schmalensee (2008, 2016).

14
Firstly are the digital infrastructure firms that encompass most of the technologies, which make the
digital economy possible. They include the internet, the WWW, cloud computing, cellular systems,
algorithms, and big data—the tools of the ITR. The digital infrastructure is made possible by
communications equipment firms (computer hardware, semiconductors) and telecommunications
service firms. These digital infrastructure firms provide the hardware and software, and service
companies tie the global digital economy together. The Forbes top 100 digital firms represent the
largest digital infrastructure firms in the world. Of these, about three-quarters are infrastructure
firms: twenty-nine are telecommunication services firms, fifteen are semiconductor firms, seven
make computer hardware, and four make communications equipment. They cover a more diverse
set of countries than platform companies: twenty-seven U.S., ten Japanese, four Chinese, three
Netherlands, three Hong Kong; the U.K., France, and Canada each have two; thirteen countries
have one company each.
17
Table 2: Digital Infrastructure Firms (Fortune’s Digital 100)
Fortune
Rank
Company
Industry
Country
Market Cap,
$Billions
IPO
3
Samsung Electronics
Semiconductors
South Korea
292.6
3/1/1938
5
AT&T
Telecommunications
Services
United States
214.5
10/5/1983
7
Verizon Communications
Telecommunications
Services
United States
226.8
10/7/1983
8
China Mobile
Telecommunications
Services
Hong Kong
138.3
9/3/1997
12
Intel
Semiconductors
United States
250.9
7/18/1968
13
Softbank
Telecommunications
Services
Japan
104.1
9/3/1981
14
IBM
Computer Services
United States
105.7
6/16/1911
16
Nippon Telegraph & Tel
Telecommunications
Services
Japan
83.5
4/1/1985
17
Cisco Systems
Communications
Equipment
United States
194.7
12/10/1984
18
Oracle
Software & Programming
United States
169.5
6/16/1977
19
Deutsche Telekom
Telecommunications
Services
Germany
79.4
1/1/1995
20
Taiwan Semiconductor
Semiconductors
Taiwan
277
2/21/1987
21
KDDI
Telecommunications
Services
Japan
67.2
6/1/1984
22
SAP
Software & Programming
Germany
167.0
4/1/1972
23
Telefónica
Telecommunications
services
Spain
24.4
4/19/1924
24
América Móvil
Telecommunications
Services
Mexico
54.4
9/25/2000
25
Hon Hai Precision
Electronics
Taiwan
40.8
2/20/1974
26
Dell Technologies
Computer Hardware
United States
40.6
2/1/1984
27
Orange
Telecommunications
Services
France
31.8
1/1/1998
28
China Telecom
Telecommunications
Services
China
22.8
4/27/1995
17
See https://www.forbes.com/top-digital-companies/list/.

15
29
SK Hynix
Semiconductors
South Korea
48.6
2/1/1983
30
Accenture*
Computer Services
Ireland
136.8
1/1/1989
31
Broadcom*
Semiconductors
United States
126.3
1/1/1961
32
Micron Technology
Semiconductors
United States
55.5
10/5/1978
33
Qualcomm
Semiconductors
United States
101.4
7/1/1985
35
China Unicom
Telecommunications
Services
Hong Kong
16.6
1/6/2009
36
HP
Computer Hardware
United States
24.4
1/1/1939
37
BCE*
Telecommunications
Services
Canada
37.4
1/1/1983
38
Tata Consultancy
Services
Computer Services
India
103.9
4/1/1968
39
Automatic Data
Processing*
Business & Personal
Services
United States
64.1
1/1/1949
40
BT Group*
Telecommunications
Services
United Kingdom
13.7
1/1/1980
41
Mitsubishi Electric
Electrical Equipment
Japan
27.4
1/15/1921
42
Canon
Business Products &
Supplies
Japan
20.1
8/10/1937
44
Saudi Telecom
Telecommunications
Services
Saudi Arabia
52.5
4/21/1998
46
Texas Instruments*
Semiconductors
United States
114.8
1/1/1951
48
Phillips
Health Care Equipment &
Services
Netherlands
42.1
5/15/1891
49
Etisalat
Telecommunications
Services
United Arab
Emirates
5.5
10/5/1976
51
ASML Holding*
Semiconductors
Netherlands
156.2
1/1/1984
52
Salesforce.com*
Software & Programming
United States
172.2
1/1/1999
53
Applied Materials
Semiconductors
United States
55.1
11/10/1967
55
SingTel*
Telecommunications
Services
Singapore
28.9
1/1/1879
56
Adobe
Software & Programming
United States
210.8
12/1/1982
57
Xiaomi
-
China
309.1
4/6/2010
58
Telstra
Telecommunications
Services
Australia
26.1
7/1/1975
59
Vmware*
Software & Programming
United States
65.0
1/1/1998
60
TE Connectivity
Electronics
Switzerland
26.4
6/29/2007
61
SK Holdings
Oil & Gas Operations
South Korea
12.9
1/1/1953
62
Murata Manufacturing
Electronics
Japan
37.3
10/1/1944
63
Cognizant
Computer Services
United States
30.5
1/26/1994
64
NVIDIA
Semiconductors
United States
233.9
4/1/1993
66
Telenor*
Telecommunications
Services
Norway
21
1/1/1855
67
Vodafone*
Telecommunications
Services
United Kingdom
42.5
1/1/1982
68
SK Telecom
Telecommunications
Services
South Korea
13.5
3/29/1984
69
Vivendi
Telecommunications
Services
France
29.3
12/11/1987
71
Infosys
Computer Services
India
40.9
7/7/1981
72
China Tower Corp.
-
China
30.8
7/15/2014
73
Swisscom
Telecommunications
Services
Switzerland
26.9
1/1/1998
74
Corning*
Communications
Equipment
United States
19.6
1/1/1851
76
Rogers Communications*
Telecommunications
Services
Canada
20.5
1/1/1960

16
78
Kyocera
Electronics
Japan
19.6
4/1/1959
79
NXP Semiconductors*
Semiconductors
Netherlands
31.4
1/1/2006
80
DISH Network
Broadcasting & Cable
United States
18.2
3/4/1996
82
Altice Europe*
Broadcasting & Cable
Netherlands
4.7
1/1/2001
83
TELUS*
Telecommunications
Services
Canada
21.3
1/1/1990
84
Capgemini
Computer Services
France
19.0
10/1/1967
86
Analog Devices*
Semiconductors
United States
44.6
1/1/1965
87
Lam Research*
Semiconductors
United States
46.4
1/1/1985
88
DXC Technology
Business & Personal
Services
United States
4.1
4/3/2017
89
Legend Holding*
Computer Hardware
China
2.8
1/1/1984
90
Lenovo Group
Computer Hardware
Hong Kong
6.7
11/1/1984
92
Tokyo Electron
Semiconductors
Japan
40.2
11/11/1963
93
Keyence
Electronics
Japan
100.8
5/27/1974
94
Telkom Indonesia
Telecommunications
Services
Indonesia
21.2
10/23/1856
95
Nokia
Communications
Equipment
Finland
24.4
5/12/1865
96
Fortive
Electrical Equipment
United States
22.8
7/1/2016
97
Ericsson*
Communications
Equipment
Sweden
30.8
1/1/1876
99
Fujitsu
Computer Hardware
Japan
23.3
6/20/1935
100
Hewlett Packard
Enterprise
Computer Hardware
United States
12.2
11/1/2015
Source: Fortune’s Digital 100 (2019). Author’s calculations.
Note: There are 79 digital infrastructure firm in total. Fortune’s rank, industry, and country are based on Fortune’s Digital 100.
Market cap and IPO are augmented by the author. Market cap as of July 1, 2020. Only public companies are included in the list. *
denotes that only the year founded is provided. Month and date are imputed as January 1 of the same year.
Second, are the platforms firms and the platform owners, which are actually rather small in number
but their reach is immense. Cusumano et al. (2019) conducted a three-year study, in which they
identified 9 hybrid platform organizations, 18 innovation platform organizations, and 25
transaction platform organizations. From 1995 to 2015, 209 platform organizations failed, with an
average survival rate of almost five years.
What has happened since 2015? Three major trends are worth highlighting. First is the increase in
the number of digital platforms, from around 50 in 2015 to about 150 in 2020. According to IoT
Analytics, there has been a 2.4- fold increase in the number of publicly traded platforms within the
last five years. The second major trend is the rising dominance of major hybrid platform companies.
Hybrid companies, whose nexus of control extends to both innovation and transaction platforms,
are strengthening their competitive moats. In 2018, Amazon’s share of the U.S. e-commerce market
hit 49 percent.
18
In 2018, more than 90 percent of all internet searches took place through Google
and the subsidiary company YouTube.
19
Apple dominates the global handset market by capturing
66 percent of industry profits and 32 percent of overall handset revenue.
20
The third major trend is
the continued globalization of digital platforms The U.S. platform companies—Facebook,
Amazon, Apple, Netflix, and Google—enjoyed first-mover advantages in the European Union,
which is now a fully saturated market. The number of online users is projected to triple between
18
See https://techcrunch.com/2018/07/13/amazons-share-of-the-us-e-commerce-market-is-now-49-or-5-of-all-retail-spend/.
19
See https://www.businessinsider.com/how-google-retains-more-than-90-of-market-share-2018-4.
20
See https://9to5mac.com/2019/12/19/apple-takes-home-a-third-of-smartphone-revenue-two-thirds-of-profits/.

17
2015 and 2022 and to hit 6 billion.
21
The lion’s share of user growth will come from emerging
markets. This time around, U.S. platforms face stiff competition from China’s Baidu, Alibaba, and
Tencent, and all are in pursuit of lucrative markets in India, Indonesia, Brazil, and other emerging
economies. The top ten platform firms are listed below. Six of the ten are hybrid organizations with
both innovation and transaction platforms.
Table 3: Digital Multisided Platform Firms (Fortune’s Digital 100)
Fortune
Rank
Company
Industry
Country
Market Cap
(2020)
IPO
Platform Type
1
Apple
Computer Hardware
United
States
1,591.0
4/1/1976
Hybrid
2
Microsoft
Software &
Programming
United
States
1,556.0
4/4/1975
Hybrid
4
Alphabet
Computer Services
United
States
985.3
9/4/1998
Hybrid
6
Amazon
Internet & Catalog
Retail
United
States
1,415.0
7/5/1994
Hybrid
10
Facebook
Computer Services
United
States
671.8
2/1/2004
Hybrid
11
Alibaba
Internet & Catalog
Retail
China
580.7
4/4/1999
Hybrid
15
Tencent Holdings
Computer Services
China
620.9
11/11/1998
Transaction
34
PayPal
Consumer Financial
Services
United
States
206.8
12/1/1998
Transaction
43
Booking Holdings
Business & Personal
Services
United
States
68.0
1/1/1996*
Investment/
Holding
45
JD.com
Internet & Catalog
Retail
China
92.7
6/18/1998
Transaction
50
Baidu
Computer Services
China
41.4
1/1/2000
Transaction
54
Recruit Holdings
Business & Personal
Services
Japan
55.0
8/26/1963
Transaction
65
eBay
Internet & Catalog
Retail
United
States
36.9
9/3/1995
Transaction
70
Naspers
Broadcasting & Cable
South
Africa
78.9
5/12/1915
Investment/
Holding
75
Fidelity National
Information
Business & Personal
Services
United
States
84.6
1/1/1968*
Transaction
77
Nintendo
Recreational Products
Japan
53.0
9/23/1889
Transaction
81
Rakuten
Internet & Catalog
Retail
Japan
12.2
2/7/1997
Transaction
85
Activision Blizzard
Recreational Products
United
States
59.3
2/8/1991
Transaction
91
NetEase
Computer Services
China
58.9
6/1/1997
Transaction
98
Fiserv
Software &
Programming
United
States
65.9
7/31/1984
Transaction
Source: Fortune’s Digital 100 (2019). Cusumano et al. (2018) and Evans and Gawer (2016). CBInsights. Author’s calculations.
Note 1: Evans and Gawer (2016) use the term “integrated” instead of “hybrid,” but these terms are used interchangeably. For the sake of consistency,
we use just “hybrid.” There are 20 multisided platform firms in total Fortune’s rank, industry, and country are based on Fortune’s Digital 100. Market
cap and IPO are augmented by the author. Platform Type is adapted from Cusumano et al. (2018) and Evans and Gawer (2016). Market cap is as of
21
See https://www.axios.com/more-than-half-of-world-population-on-the-internet-mary-meeker-c4d623d6-32c1-47c0-b30e-
5f934af88744.html.

18
July 1, 2020. Only public companies are included in the list. * denotes that only year founded is provided. Month and date are imputed as January 1
of the same year. Recruit Holdings, Fidelity National Information, Activision Blizzard and Fiserv did not appear in their list, so we augmented the
table, classifying them as transaction platforms.
Note 2: A transaction platform matches demand-side and supply-side users. An innovation platform allows complementary innovators to build
products and services within the platform-based ecosystem. A hybrid platform consists of both innovation and transaction platforms.
Note 3: see Appendix Table A3 for an expanded list
Third, are the new technology-based firms that develop the software and populate the multisided
platforms. According to Evans Data Corporation, there were 26.4 million software developers in
the world in 2019.
22
In 2008, there were 500 mobile apps on the first iteration of Apple’s App
Store; in 2018, there were 20 million registered iOS developers catering to 500 million weekly
visitors to the App Store alone. The top 100 global software developers reveal some interesting
trends. The U.S. leads the list with 40 firms, or 45 percent of the total, followed by India with 20
firms, Ukraine with 6, and Canada with 3. The U.K., Romania, and Russia have 2 each.
23
Table 4: Top 10 Global Mobile Application Companies
Firm
Firm Size
Min. Project Size
Hourly Rate
Location
Founded
1
ScienceSoft
501-1000
Undisclosed
$50-$99/hr
United States
1989
2
VironIT
50-250
$5,000+
$25-$49/hr
Belarus
2004
3
Intellectsoft
250-999
$25,000+
$50-$99/hr
United States
2007
4
WillowTree
250-999
$50,000+
$150-$199/hr
United States
2007
5
Atomic Object
50-249
Undisclosed
$100-$149/hr
United States
2001
6
Rightpoint
200-500
$50,000+
$150-$199/hr
United States
2007
7
ArcTouch
50-250
$25,000+
$100-$149/hr
United States
2008
8
Cleveroad
50-249
$10,000+
$25-$49/hr
Ukraine
2014
9
Konstant Infosolutions
50-249
$5,000+
< $25/hr
India
2003
10
Exadel
500-1000
$50,000+
$25-$49/hr
United States
1998
Source: Softwareworld.com, updated October 4, 2020
Note: See Appendix A for a complete list.
The final set of firms is the supply-side users on multisided platforms. The number of users on both
the demand side and the supply side is huge, with 3.8 billion people worldwide having
smartphones.
24
Facebook alone has more than 2.7 billion monthly active users (demand-side
users).
25
Facebook also attracts 9 million active advertisers.
26
Amazon has 150 million Prime
members (demand-side users).
27
Amazon also has 6 million suppliers on its platform (supply-side
users).
28
There are 75 million Uber riders (demand-side users), who are served by a total of 3.9
million drivers globally (supply-side users).
29
Didi Chuxing claims that its 31 million drivers
(supply-side users) provide rides to 550 million users (demand-side users).
30
Airbnb has 150
22
See https://www.daxx.com/blog/development-trends/number-software-developers-world.
23
See https://www.softwareworld.co/top-mobile-app-development-companies-in-usa/.
24
See https://www.statista.com/statistics/330695/number-of-smartphone-users-worldwide/.
25
See https://www.statista.com/statistics/264810/number-of-monthly-active-facebook-users-worldwide/.
26
See https://www.statista.com/statistics/778191/active-facebook-advertisers.
27
See https://www.statista.com/statistics/829113/number-of-paying-amazon-prime-members/.
28
See https://www.marketplacepulse.com/articles/amazon-merchants-selling-more-than-1-million-a-year.
29
See https://www.businessofapps.com/data/uber-statistics/.
30
See https://www.cnbc.com/2019/08/05/chinese-rideshare-giant-didi-makes-big-move-in-driverless-car-
race.html#:~:text=Chinese%20ride%2Dhailing%20giant%20Didi,of%20Beijing%20seven%20years%20ago.

19
million users (demand-side users) and more than 650,000 hosts (supply-side users) worldwide.
31
The global mobile gaming audience is estimated at 2.2 billon users (demand- side users).
32
Appendix A explains the methodology for identifying the firms of the platform economy.
5.Discussion
How do we interpret and understand the evolution of the global DPE in the 21st century (Audretsch,
1995)? Political economy may offer a key. According to Brian Arthur (Root, 2020, p. xv),
“economics before 1870 was concerned with two great problems. One was allocation within the
economy: how quantities of goods and services and their prices are determined within and across
markets or between trading countries. The other was formation within the economy: how an
economy emerges and changes its structure over time (Acs, 1984). In the years since 1870 and the
development of neoclassical economics . . . allocation came to constitute ‘economic theory’ itself:”
the marginal revolution (Blaug, 1962). Questions of formation thus faded from the core of
economic theory, and economics had little to say about adaption, adjustment, innovation, the
formation of institutions, and structural change itself. The formation problem was not easily
mathematized, thus it was left to political economists who restricted themselves to case studies and
qualitative theories. This branch of economic theory was open to scholars from different
persuasions as seen, for example, in the literature on National Systems of Innovation and the
Theory of National Advantage, among others, that undermined Europe’s approach to startups
(Naudé, 2016).
Two new political economy frameworks emerged in the 1990s to explain the evolution of the ITR.
The first was National Systems of Innovation (Edquist & Johnson, 1997; Lundvall, 1992; Nelson,
1993), whose main theoretical underpinnings were (1) that knowledge is a fundamental resource
in the economy, and (2) that knowledge is produced and accumulated through an interactive and
cumulative process of innovation that is embedded in a national institutional context. National
systems assumed that all of this takes place in existing firms, so there is no need for new firms or
entrepreneurship to bring the technology to market. The second conceptual framework was the
Porter Diamond Theory of National Advantage (Porter, 1990), which identified an interactive
system that propelled a country to prominence. The four facets of the Porter theory represented
four interrelated determinates: firm strategy, structure and rivalry; demand conditions; related and
supporting industries; and factor conditions. Porter emphasized factor conditions because a country
can create these for itself, including but not limited to knowledge, a large pool of talent,
technological innovation, infrastructure, and capital—all embedded in regional clusters.
33
The Theory of National Advantage and National Systems of Innovation had three assumptions in
common. First, they agreed that knowledge is a fundamental resource in the economy; second, they
agreed that knowledge is produced through the interactive process of institutional embeddedness;
and third, both relied on existing firms to implement the new technologies. Both approaches had a
large theoretical literature, empirical research, and policy recommendations. However, because
both left out of their analysis the role of new firms that was Jovanovic’s great insight, they had
31
See https://ipropertymanagement.com/research/airbnb-statistics.
32
See https://techjury.net/blog/mobile-gaming-statistics/.
33
These approaches were both underpinned by endogenous growth theory (Romer, 1990).

20
limited usefulness in understanding the new information technologies because incumbent firms did
not implement the new technologies (Jovanovic, 1982, 2001, 2019; Evans & Jovanovic, 1989).
Why did the ITR favor new firms? Technology breakthroughs favored new firms for three reasons:
awareness and skills, vintage capital, and vested interests (Hobijn & Jovanovic, 2001). First,
managers of an old firm may not know what a new technology offers or may be unable to
implement it. As noted above, when IBM entered the PC market it did not have the ability to
develop an operating system quickly, so it turned to Intel for its microprocessor and to Microsoft
for its disk operating system. Second, an old firm’s human and physical capital is tied to its current
practices, and it may not be converted easily to new technologies. Abandoning investment in old
technologies may not make sense. When the Berlin Wall fell, countries in Central Europe were
reluctant to give up their vintage capital, even in the face of far superior Western methods.
Unencumbered by the past, new firms have more incentive to invest in new technologies (Acs,
1984). When the biotechnology revolution took off in the 1970s, it was startups that introduced the
new technologies. Existing pharmaceutical companies’ human capital was in chemistry, while the
biotechnology breakthroughs were in biology. Third, workers and management in an older firm,
especially if they belong to a union, may resist new technologies because it devalues their skills.
In so doing, they may harm the interests of the firm and the shareholders by lowering the value of
the firm.
Zoltan Acs and David Audretsch (1988) found that young (small) firms introduced 2.38 more
innovations per employee than their larger counterparts. Moreover, they found (1) that total
innovations are negatively related to concentration and unionization which supports Hobijn and
Jovanovic’s third point; and (2) that innovation is positively related to R&D, skilled labor, and the
degree to which large firms comprise the industry, which supports both Lundvall and Porter.
However, innovations emanated from the small (young) firms in the industry, not from incumbents,
which undermined a key assumption of both National Systems of Innovation and the Theory of
National Advantage. The mechanism by which new firms acquired knowledge was knowledge
spillovers (Jaffe, 1989; Acs, 2012) and it was financed through venture capital (Gompers and
Lerner, 2001; Estrin, Khavul and Wright, 2020).
34
The major theoretical underpinning of European economic policy postulated that existing firms
will introduce the new technologies. How have these propositions influenced economic
performance in the European Union as a whole and in its individual countries? In one of the largest
studies on the subject of Europe’s entrepreneurial future, Elert, Henrekson, and Sanders (2019, p.
6) stated that, “overall, the data suggests that contemporary Europe has a comparatively less fertile
‘ecosystem’ for Schumpeterian/high-impact entrepreneurship than the U.S., and in some respects
even relative to China and East Asia. In Eastern Europe, much of the self-employment is marginal
necessity-driven entrepreneurship, whereas in Western Europe the base of self-employment may
be broad, but opportunities to grow into the global competitors of the future, in particular, seem
34
That the public sector was responsible for the evolution of the DPE in the late 20th century is greatly exagerated by
Mariana Mazzucato (2013). The bureaucratic structure of the managed eaconomy was unable to initiate the
implementation of the new technologies and the state had even less success. See Wennberg (2019) for an
alternative view.

21
limited.” As global technology takes shape on a battleground between China and the United States,
Beijing and Washington are in the driver’s seat, while Europe is finding it harder to set the rules of
the road.
35
6. Conclusion
In the hierarchical world of the 20th century, giant firms and the state needed and relied on each
other, especially after the Second World War (Carter, 2020). The state needed the corporation to
create a growing and successful economy, and the corporations needed the state for market
stability: labor markets, capital markets, financial markets, foreign exchange markets, and
international markets. Both government and the corporation relied on the hierarchical order. In this
world, as Niall Ferguson (2018) makes clear, “the tower represents hierarchy and the crucial
incentive that favored hierarchical order was that it made the exercise of power more efficiently.”
This symbiotic relationship between the market and the state, as Lindblom (1977, p. ix) makes
clear, is that the greatest distinction between one government and another is the extent to which the
government replaces markets or markets replace the government; it is not an either-or.
What has happened in the 21st century with the reemergence of autonomous networks is that the
balance between the state and the market shifted as the hierarchy was replaced by networks. The
state maintained its bureaucracy, but with nothing or little to manage, as networks are less about
power than hierarchies (Mazzucato, 2013). This also explains why, in the United States, the
European Union, and China, the political establishment clings to power while society largely
dismantled hierarchy in the private sector and the majority of the electorate is deeply alienated from
the political establishment (Root, 2020). The struggle, therefore, is now over liberty, with the state
and society in conflict over how to tame the despotic leviathan. Daron Acemoglu and James
Robinson (2019), arguing for a Swedish-style soft socialist polity, claim that a strong leviathan
must counterbalance a strong civic society. They advocate for the two to work together, whereas
we see the strong leviathan as a threat to the self-organizing dynamic networks driven by the
innovation of the platform economies (Harari, 2019). Future research needs to examine this
question further in the context of the ITR and the rise of the global DPE.
35
See https://www.nytimes.com/2020/09/11/world/europe/eu-us-china-echnology.html?referringSource=articleShare.

22
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27
Appendix A: The Firms of the Digital Platform Economy
Digital Users. Access to the internet and smartphone ownership is the pre-requisites to participating in the DPE.
Internet World Stats keeps track of internet users globally (see A1.1).
36
The penetration rate varies widely by continent,
from a high of 90 percent in North America to a low of 42 percent in Africa. Because over 70 percent of the world’s
population is in Africa and Asia, the worldwide internet penetration rate is 62 percent. These numbers translate into
4.8 billion out of 7.8 billion people in the world having access to the internet.
The number of smartphone users has increased steadily and is forecast to grow by several hundred million in the next
few years (see A1.2). According to Newzoo, worldwide smartphone ownership in 2016 was 2.5 billion; the number
had increased to 3.5 billion by 2020.
37
China, India, and the United States have the highest number of smartphone
users, each with over 100 million. Smartphone unit sales are leveling off, but the market still has high potential to grow,
particularly in the emerging markets, such as China and India. The leading smartphone vendors are Samsung, Apple,
and Huawei, which make up half of global sales. Putting these numbers together, we estimate that between 3.5 billion
and 4.8 billion people make up the demand-side users.
A1.1. Digital Users: Demand Side
World internet usage and population statistics, 2020 (Q2 estimates)
World Regions
Population
Populatio
n
Internet Users
Penetration
Growth
Internet
(2020 Est.)
% of
World
30-Jun-20
Rate (%
Pop.)
2000-
2020
World
%
Africa
1,340,598,447
17.2%
566,138,772
42.2%
12441%
11.7%
Asia
4,294,516,659
55.1%
2,525,033,874
58.8%
2109%
52.2%
Europe
834,995,197
10.7%
727,848,547
87.2%
592%
15.1%
Latin
America/Caribbean
654,287,232
8.4%
467,817,332
71.5%
2489%
9.7%
Middle East
260,991,690
3.3%
184,856,813
70.8%
5527%
3.8%
North America
368,869,647
4.7%
332,908,868
90.3%
208%
6.9%
Oceania/Australia
42,690,838
0.5%
28,917,600
67.7%
279%
0.6%
WORLD TOTAL
7,796,949,710
100.0%
4,833,521,806
62.0%
1239%
100.0%
Source: http://www.internetworldstats.com/
Notes: Internet usage and world population statistics estimates are for July 20, 2020. Population numbers are based on
data from the United Nations Population Division. Internet usage information comes from data published by Nielsen
Online, the International Telecommunications Union, GfK, local ICT regulators, and other reliable sources.
A1.2. Digital Users: Demand Side
Number of smartphone users worldwide from 2016 to 2021 (in billions)
2016
2.5
2017
2.7
2018
2.9
2019
3.2
2020*
3.5
2021*
3.8
36
See https://www.internetworldstats.com/stats.htm.
37
See https://newzoo.com/insights/articles/newzoos-global-mobile-market-report-insights-into-the-worlds-3-2-billion-
smartphone-users-the-devices-they-use-the-mobile-games-they-play/.

28
Source: Newzoo (2019)
Supply-side users are digital users that supply a good or service on a platform. Broadly speaking, digital users on the
supply side include Uber drivers and Airbnb hosts, sellers on eBay and Amazon Marketplace, and all the small and
medium-size enterprises that have an online presence, whether through their own website, a Facebook page, a Linkedin
profile, a YouTube channel, or a Twitter account. Finding good indicators to measure the supply-side users (especially
economy-wide) was more challenging. Consider a few examples. Amazon has 6 million suppliers on its platform
(supply-side users).
38
Uber has 3.9 million drivers globally (supply-side users). Didi Chuxing has 31 million drivers.
39
Airbnb has more than 650,000 hosts worldwide.
40
All of these are users on the supply-side.
Another group of supply-side users are advertisers. The highest number of active advertisers is on the Google platform,
but the company does not disclose the number of international advertisers it has. According to research conducted by
Macquarie, in 2015, Google had 4 million advertisers and Facebook had 2 million. As of 2019, Google App campaign
catalogs 3 million sites and apps and reaches more than 800 million active users.
41
Unlike Google, Facebook publishes information on its advertisers, which is the only reliable way to estimate the
number of advertisers worldwide. Furthermore, according to the Social Media Examiner, Facebook is the leading social
media platform used by marketers worldwide: 94 percent of marketers using social media platforms rely on Facebook
to advertise their business (see A1.3). As of 2020, Facebook has 9 million active advertisers (see A1.4), which include
major corporations, as well as local mom-and-pop shops.
42
Most of these advertisers are small and medium-size
enterprises that depend on Facebook to reach their customers.
A1.3. Digital Users: Supply Side
Social media platforms used by marketers worldwide 2020
Facebook
94%
Instagram
76%
LinkedIn
59%
Twitter
53%
YouTube
53%
Pinterest
25%
Messenger bots
13%
Snapchat
5%
Source: Social Media Examiner (2020, January)
A1.4. Digital Users: Supply Side
Number of active advertisers on Facebook from 1st quarter 2016 to 1st quarter 2020 (in millions)
Q1 ’16
3
Q3 ’16
4
Q3 ’17
6
Q4 ’17
6
Q1 ’18
6
Q1 ’19
7
Q3 ’19
7
Q1 ’20
8
Q2 ’20
9
Source: Facebook (2020, July)
Note: The Facebook mobile platform includes Facebook Messenger, Instagram, WhatsApp, and various other products.
38
See https://www.marketplacepulse.com/articles/amazon-merchants-selling-more-than-1-million-a-year.
39
See https://www.cnbc.com/2019/08/05/chinese-rideshare-giant-didi-makes-big-move-in-driverless-car-
race.html#:~:text=Chinese%20ride%2Dhailing%20giant%20Didi,of%20Beijing%20seven%20years%20ago.
40
See https://ipropertymanagement.com/research/airbnb-statistics.
41
See https://www.blog.google/products/ads/new-innovations-grow-your-app-business-ads./
42
See https://www.statista.com/statistics/778191/active-facebook-advertisers/.

29
Digital advertising spending is one way to measure the number of the supply-side users. According to the 2018 IAB
Internet Advertising Revenue Report released by IAB, almost 70 percent of digital advertising spending (about $73
billion) goes to Google, Facebook, and Amazon. This means that total digital advertising spending worldwide tops
$100 billion.
43
Digital Entrepreneurs. In the DPE, digital entrepreneurs are the complementors that build on the platform-based
ecosystem. These are software developers building mobile apps and web-based services that increase the value
proposition of multisided digital platforms. There is limited information on who constitutes these digital entrepreneurs.
According to Evans Data Corporation’s Global Development Population and Demographics Study published in 2016,
the number of developers involved in mobile app development was 12 million in 2016;
44
when the company began
tracking the number of app developers for the first time in 2006, the number was less than 2 million. The number of
developers who target Android platforms is 5.9 million, the number who target iOS platforms is 2.8 million. Developers
targeting iOS outnumber those targeting Androids by more than 200,000 in North America, but developers in the rest
of the world more often target Android platforms. According to Janel Garvin, CEO of Evans Data, “Mobile devices
are everywhere, but while most modern applications support mobile devices, not all developers are working on the
client target side. Some are server or backend oriented or are concentrating more on the application logic or more and
more on newer machine learning implementations.”
45
There are now various listings online that track mobile application development companies. The most comprehensive
listing is Clutch, which claims to have vetted 4,000 app development companies to find the best. As of September
2020, the list includes just under 20,000 firms. Software World has identified more than 7,000 mobile app development
companies in the U.S. and curated a list of the best global companies.
46
The list in A2 ranks the top 88 firms globe-
wide. The average age of these firm (measured in 2020) is 11.2 years. The youngest are year-old startups (InnovationM
UK, MyAppGurus, and SegWitz Tech), and the oldest is 31 years old (Zco). The U.S. accounts for about half of these
companies (43), followed by India (20), Ukraine (7), UK (4), Canada (3), and Russia and Romania (each 2). Belarus,
Egypt, Israel, Malaysia, Poland, Australia, and Vietnam have one each. About 30 firms employ between 1 and 50
workers; 44 employ between 50 and 250 workers; only about 14 employ between 250 and 1,000 workers. Project sizes
range between $1,000 and $75,000. The most common range was between $10,000 and $50,000. The hourly rate
ranged from $25 to $199.
A2. Top Global Mobile Application Development Companies
Firm
Firm Size
Min Project Size
Hourly Rate
Location
Founded
1
VironIT
50 – 250
$5,000+
$25 – $49 / hr
Belarus
2004
2
Zco
250 – 999
$10,000+
$25 – $49 / hr
United States
1989
3
WillowTree
250 – 999
$50,000+
$150 – $199 / hr
United States
2007
4
Fueled
50 – 250
$75,000+
$150 – $199 / hr
United States
2007
5
Atomic Object
50 – 249
Undisclosed
$100 – $149 / hr
United States
2001
6
Rightpoint
200 – 500
$50,000+
$150 – $199 / hr
United States
2007
7
ArcTouch
50 – 250
$25,000+
$100 – $149 / hr
United States
2008
8
Intellectsoft
250 – 999
$25,000+
$50 – $99 / hr
United States
2007
9
Konstant Infosolutions
50 – 249
$5,000+
< $25 / hr
India
2003
10
ScienceSoft
501 – 1000
Undisclosed
$50 – $99 / hr
United States
1989
11
Cleveroad
50 – 249
$10,000+
$25 – $49 / hr
Ukraine
2014
12
FATbit Technologies
50 – 249
$1000+
$25 – $49 / hr
India
2004
13
Algoworks
50 – 249
$5,000+
$25 – $49 / hr
United States
2006
14
Blue Label Labs
50 – 249
$25,000+
$100 – $149 / hr
United States
2009
15
Y Media Labs
250 – 999
$50,000+
$150 – $199 / hr
United States
2008
16
Ramotion
10 – 50
$50,000+
$50 – $99 / hr
United States
2009
17
Dot Com Infoway
50 – 249
$10,000+
$20 – $49 / hr
India
2000
18
ChopDawg.com
11 – 50
$25,000+
$100 – $149 / hr
United States
2009
43
See https://www.iab.com/wp-content/uploads/2019/05/IAB-Internet-Advertising-Revenue-Report-FY-2018.pdf.
44
See https://evansdata.com/press/viewRelease.php?pressID=244.
45
See https://evansdata.com/press/viewRelease.php?pressID=244.
46
See https://www.softwareworld.co/top-mobile-app-development-companies/.

30
19
Robosoft Technologies
250 – 999
$50,000+
$50 – $99 / hr
United States
1996
20
MLSDev
50 – 249
$10,000+
$25 – $49 / hr
Ukraine
2009
21
Credencys Solutions Inc.
51 – 200
$10,000+
$25 – $40 / hr
United States
2008
22
Droids On Roids
11 – 50
$50,000+
$50 /hr
United States
2011
23
Evon Technologies
50 – 249
$1,000+
<$25/ hr
India
2006
24
iMOBDEV Technologies
11 – 49
Undisclosed
$25 / hr
India
2009
25
Rootstrap
50 – 249
$10,000+
$100 – $149 / hr
United States
2011
26
Simpalm
10 – 49
$10,000+
Undisclosed
United States
2009
27
RipenApps
100 – 200
$5000+
< $25 / hr
India
2017
28
Redwerk
50 – 80
$4000+
$25 – $45 / hr
Ukraine
2005
29
Fusion Informatics
50 – 249
$10000+
$25 – $49
Canada
2000
30
MAAN Softwares
50 – 150
$50,000+
< $25 / hr
United States
2012
31
Cubix
51 – 200
$25,000+
$25 – $49 / hr
United States
2008
32
Krify
80 – 100
$1,000+
< $25 / hr
India
2005
33
Skelia
250 – 999
$1,000+
$25 – $49 / hr
Ukraine
2008
34
Exyte
10 – 49
$1,000+
$50 – $99 / hr
Russia
2014
35
Blue Whale Apps
10 – 49
$10,000+
$100 – $149 / hr
United States
2006
36
ENO8
11 – 50
$25,000+
$100 – $149 / hr
United States
2016
37
Railwaymen
50 – 100
$15,000+
$50 – $99 / hr
Poland
2009
38
Vipra Business
50 – 249
$5,000+
$25 – $49 / hr
United States
2014
39
Sunflower Lab
10 – 49
$10,000+
$50 – $99 / hr
United States
2010
40
Umbrella IT
50 – 250
$25,000+
$50 – $99 / hr
Russia
2009
41
DxMinds Technologies
51 – 99
$5000+
$25 – $50 / hr
United States
2007
42
MyAppGurus
50 – 150
Undisclosed
$25 / hr
United States
2019
43
BrillMindz
51 – 200
$1000+
$25 / hr
India
2011
44
FOONKIE MONKEY
50 – 249
$50,000+
$50 – $99 / hr
United States
2010
45
Gomeeki
11 – 50
$25,000+
$100 – $149 / hr
Sydney, Australia
2008
46
IPHS Technologies
50 – 249
$10,000+
$30 / hr
United States
2013
47
Nimble AppGenie
11 – 50
$75,000+
$25 / hr
United Kingdom
2017
48
Enozom
25 – 50
$10,000+
Not Provided
Egypt
2012
49
Alphonic Network Solutions
20 – 50
$1,000+
<$25 / hr
India
2013
50
CTinformatics
51 – 150
Undisclosed
$15 – $20 / hr
India
2006
51
Queppelin
50 – 249
$10,000+
< $25 / hr
India
2010
52
Riseapps
10 – 49
$25000+
$25 – $49 / hr
United States
2016
53
InApps Technology
10 – 49
$10,000+
$18 – $25 / hr
Vietnam
2016
54
Softuvo Solutions
10 – 49
$1000+
< $25 / hr
India
2016
55
Digit Bazar
11 – 49
10,000+
$25 / hr
India
2014
56
MSApps
10 – 49
Undisclosed
$50 – $99 / hr
Israel
2013
57
KBA Systems
11 – 50
N/A
$25 / hr
India
2015
58
IT Solution24x7
11 – 50
$5,000+
$25 / hr
Canada
2015
59
SegWitz Tech
1 – 50
$1,000+
$50 – $99 / hr
Malaysia
2019
60
Lemeor
10 – 49
$20,000+
$25 – $49 / hr
Ukraine
2014
61
InnovationM UK
50 – 249
$5,000+
< $25 / hr
United Kingdom
2019
62
Fluper
201 – 500
$15000+
$25 / hr
India
2013
63
hedgehog lab
50 – 250
$50,000+
$100 – $149 / hr
United Kingdom
2007
64
MindSea
10 – 49
$10,000+
$100 – $149 / hr
Canada
2007
65
Daffodil Software
250 – 999
$10,000+
< $25 / hr
India
1999
66
Dom & Tom
50 – 250
$50,000+
$150 – $199 / hr
United States
2009
67
Iflexion
50 – 250
$10,000+
$25 – $49 / hr
United States
1999
68
Appinventiv
250 – 999
$10,000+
< $25 / hr
United States
2014
69
Hyperlink InfoSystem
50 – 249
$10,000+
< $25 / hr
India
2011
70
AndPlus
10 – 49
$50,000+
$150 – $199 / hr
United States
2009
71
SteelKiwi
50 – 249
$10,000+
$25 – $49 / hr
Ukraine
2011
72
App Partner
10 – 49
$25,000+
$100 – $149 / hr
United States
2011
73
Magora
50 – 249
$10,000+
$50 – $99 / hr
United Kingdom
2010
74
Appstem
10 – 50
$50,000+
$150 – $199 / hr
United States
2010

31
75
Small Planet Digital
10 – 49
$100,000+
$100 – $149 / hr
United States
2009
76
QBurst
1000 – 9999
$5,000+
$25 – $49 / hr
India
2004
77
Hakuna Matata
50 – 249
$5,000+
< $25 / hr
India
2006
78
Softeq
50 – 249
$50,000+
$25 – $49 / hr
United States
1997
79
Halcyon Mobile
50 – 249
$25,000+
$25 – $49 / hr
Romania
2005
80
TriState Technology
50 – 249
$5,000+
< $25 / hr
India
2010
81
Matellio
50 – 249
$5,000+
< $25 / hr
United States
2012
82
Experion Technologies
250 – 999
$75,000+
$25 – $49 / hr
United States
2006
83
MOBIKASA
10 – 49
$10,000+
$50 – $99 / hr
United States
2010
84
Seasia Infotech
500 – 999
$10,000+
$30 – $50 / hr
United States
2000
85
openGeeksLab
50 – 249
$10,000+
$25 – $49 / hr
Ukraine
2015
86
Tapptitude
10 – 49
$10,000+
$25 – $49 / hr
Romania
2013
87
Intuz
50 – 249
$10,000+
$25 – $49 / hr
United States
2008
88
NMG Technologies
10 – 49
$1,000+
< $25 / hr
United States
2008
Source: Softwareworld.com, updated July 7, 2020
A3: Additional Digital Multisided Platform Companies
Company
Geography
Category
IPO
Exit Value ($B)
Total Raised Before Exit ($M)
AutoNavi
China
Software (non-internet/mobile)
40360
2.3
40
BATS Global Markets
United States
Financial
42475
1.8
N/A
Betfair
United Kingdom
Internet
40473
2
N/A
Box
United States
Internet
42027
1.7
562
Castlight Health
United States
Internet
41712
1.4
178
Chegg
United States
Internet
41591
1.1
249
Criteo
France
Internet
41577
1.7
56
Decolar
Argentina
Internet
42998
1.8
342
Delivery Hero
Germany
Internet
42916
5.1
1750
Demand Media
United States
Internet
40564
1.5
235
Etsy
United States
Internet
42110
1.8
95
eviCore Healthcare
United States
Healthcare
43018
3.6
427
ExactTarget
United States
Internet
40991
1.2
234
Freelancer.com
Australia
Internet
41593
1.1
NA
Gogo
United States
Internet
41446
1.5
468
Groupon
United States
Internet
40851
12.7
1143
GrubHub Seamless
United States
Internet
41733
2
84
HomeAway
United States
Internet
40700
2.2
496
Jumei International Holdings
China
Internet
41775
3.3
167
Just Eat
United Kingdom
Internet
41732
2.4
129
King Digital Entertainment
Ireland
Internet
41724
7.1
46
Lending Club
United States
Financial
41984
5.4
263
LinkedIn
United States
Internet
40682
4.3
103
Markit
United Kingdom
Business Products & Services
41809
4.3
750
Meitu
China
Mobile & Telecommunications
42713
4.9
10
MongoDB
United States
Software
43027
1.2
311

32
NEXON
Japan
Internet
40892
7.2
NA
OnDeck Capital
United States
Internet
41990
1.3
394
Pandora
United States
Internet
40709
2.6
56
Qudian
China
Internet
43026
7.9
961
Redfin
United States
Internet
42944
1.2
167
RenRen
China
Internet
40668
1.7
NA
Rocket Internet
Germany
Business Products & Services
41914
8.5
1527
Roku
United States
Consumer Products & Services
43006
1.1
200
Rovio Entertainment
Finland
Mobile & Telecommunications
43007
1.1
76
Sea
Singapore
Internet
43028
4.8
722
Shopify
Canada
Internet
42145
1.3
122
Sky-Mobi
China
Internet
40523
2.1
NA
Snap
United States
Mobile & Telecommunications
42796
24.8
2614
Square
United States
Mobile & Telecommunications
42327
2.9
717
Tableau Software
United States
Software (non-internet/mobile)
41411
2
15
Takeaway.com
Netherlands
Internet
42643
1.1
119
Tesla
United States
Automotive & Transportation
40358
1.6
268
The Trade Desk
United States
Internet
42634
1
253
Twilio
United States
Mobile & Telecommunications
42544
1.2
233
Ucar Group
China
Mobile & Telecommunications
42573
5.5
1369
Wayfair
United States
Internet
41914
2.4
358
Workday
United States
Internet
41194
4.5
196
Yandex
Russian Federation
Internet
40688
1.3
5
Youku Tudou
China
Internet
40521
2.4
105
Zalando
Germany
Internet
41913
6.8
149
Zulily
United States
Internet
41593
2.6
139
Zynga
United States
Internet
40893
7
1848