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Alternative Futures for the Digital Transformation: A
Macro-Level Schumpeterian Perspective
Zlatko Bodrožić, Paul S. Adler
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Zlatko Bodrožić, Paul S. Adler (2021) Alternative Futures for the Digital Transformation: A Macro-Level Schumpeterian
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Alternative Futures for the Digital Transformation:
A Macro-Level Schumpeterian Perspective
Zlatko Bodroˇ
zi´
c,
a
Paul S. Adler
b
a
Management Department, Universityof Leeds, Leeds LS2 9JT, United Kingdom;
b
Management and Organization Department, Marshall
School of Business, University of Southern California, Los Angeles, California 90089
Contact: z.bodrozic@leeds.ac.uk,https://orcid.org/0000-0003-1408-1924 (ZB); padler@usc.edu,
https://orcid.org/0000-0003-3800-6806 (PSA)
Received: January 13, 2020
Revised: December 29, 2020; June 20, 2021;
September 11, 2021
Accepted: October 2, 2021
Published Online in Articles in Advance:
https://doi.org/10.1287/orsc.2021.1558
Copyright: © The Author(s) 2021
Abstract. This paper develops and deploys a theoretical framework for assessing the pros-
pects of a cluster of technologies driving what is often called the digital transformation.
There is considerable uncertainty regarding this transformation’sfuturetrajectory,andto
understand and bound that uncertainty, we build on Schumpeter’s macro-level theory of
economy-wide, technological revolutions and on the work of several scholars who have ex-
tended that theory. In this perspective, such revolutions’trajectories are shaped primarily
by the interaction of changes within and between three spheres—technology, organization,
and public policy. We enrich this account by identifying the critical problems and the col-
lective choices among competing solutions to thoseproblems that together shape the trajec-
tory of each revolution. We argue that the digital transformation represents a new phase in
the wider arc of the information and communication technology revolution—aphase
promising much wider deployment—and that the trajectory of this deployment depends
on collective choices to be made in the organization and public policy spheres. Combining
in a 2 ×2matrixthetwomainalternativesolutionsonofferineachofthesetwospheres,
we identify four scenarios for the future trajectory of the digital transformation: digital au-
thoritarianism, digital oligarchy, digital localism, and digital democracy. We discuss how
these scenarios can help us trace and understand the future trajectory of the digital
transformation.
History: This paper has been accepted for the Organization Science Special Issue on Emerging Technolo-
gies and Organizing.
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Keywords:digital transformation •technological revolution •ICT •Schumpeter •management models •public policy •scenarios •
digital authoritarianism •digital oligarchy •digital localism •digital democracy
Introduction
Digital technologies such as artificial intelligence (AI), the
Internet of Things, big data analytics, robotics, digital plat-
forms, social media, blockchain, and three-dimensional
(3D) printing have the potential to transform vast swaths
of human activity. The term “digital transformation”is
often used to capture the commonalities and interdepen-
dencies within this cluster of emerging technologies and
the scope and magnitude of the revolutionary changes
they portend in industry and society (Nambisan et al.
2019,Vial2019, Lanzolla et al. 2020,Haneltetal.2021).
However, uncertainty about its future trajectory abounds.
Both practitioner literature and scholarly literature offer
extrapolations from the current situation, forecasts that
are sometimes pessimistic (e.g., “surveillance capitalism”
as delineated by Zuboff (2019)) and sometimes optimistic
(e.g., commons-based peer production as delineated by
Benkler (2006)). This paper aims to bound the uncertainty
about the direction that the digital transformation will
take, and to identify the collective choices we face in shap-
ing that direction. To do this, we advance a conceptual
framework that locates the factors that will shape this tra-
jectory, and we use this framework to identify several
plausible alternative scenarios for it.
The digital transformation is not simply a basket of
individual innovations: it is an interdependent cluster
of revolutionary technologies, where developments in
each technology affect many others. Moreover, the
trajectory of such an epochal transformation is shaped
by organizational and societal contexts, and those
contexts evolve in interaction with each other and
with technological changes. To understand such a
1
ORGANIZATION SCIENCE
Articles in Advance, pp. 1–21
ISSN 1047-7039 (print), ISSN 1526-5455 (online)
http://pubsonline.informs.org/journal/orsc
December 30, 2021
phenomenon, we need to shift attention from the
“micro”level of individual innovators and innovations
(Scott and Bruce 1994)andfromthe“meso”level of in-
dividual technologies and industries (Anderson and
Tushman 1990)tothe“macro”level of technological
revolutions as epochal, societal-scale phenomena.
A natural starting point for such a discussion is
Schumpeter’s classic works (Schumpeter 1934,1939,
1942). Although Schumpeter’s ideas are often de-
ployed in management and organization studies to
explain the behavior of individual firms and indus-
tries (Nelson and Winter 1982, Ahuja et al. 2008), his
macro-level theory of economy-wide technological
revolutions is only rarely invoked in our field, per-
haps reflecting something of a “theoretical vacuum”in
organization studies at that macro level (Stern and Bar-
ley 1996) (exceptions include Chandler and Hikino
1990,BarleyandKunda1992,Nelson1995,Lewinetal.
1999, Dosi and Marengo 2007,VaalerandMcNamara
2010). Since Schumpeter’s initial statements, scholarship
has advanced, and we offer here an account based on
the work of a school of neo-Schumpeterians who have
plumbed the history of such revolutions (most notably
Freeman and Louc¸a 2001;Perez2003,2010; Mazzucato
2015).
This macro-oriented strand of Schumpeter-inspired
scholarship (we will call it “macro-Schumpeterian”
for short) has identified five economy-wide technolog-
ical revolutions over the last two centuries: the original
“industrial revolution”based on machinery and water
power, followed by the steam-power-and-railway rev-
olution, then by the steel-and-electricity, automobile-
and-oil, and most recently the computers-and-data
revolution, aka the information and communication
technology (ICT) revolution. Viewed in this context,
the digital transformation appears as the latest phase
of the wider arc of the ICT revolution. Relying on
“reasoned history”—historical accounts that are based
on qualitative historical-comparative methods rather
than on formal quantitative, cliometric models (Freeman
and Louc¸a 2001,part1;Schumpeter1927,p.288,298)—
these macro-Schumpeterians have discovered some
striking regularities in the phases and dynamics of those
technological revolutions. We build on these findings to
argue that the future trajectory of the digital transfor-
mation will reflect changes in three main spheres—
technology, organization, and public policy—and in
their interaction. Whereas management scholarship has
devoted considerable attention to the interaction of
technology and organization, the study of such revolu-
tions demands that we pay equal attention to the public
policy sphere.
If, on the one hand, these retrospective regularities
provide precious clues, on the other hand, such regu-
larities should not obscure the contingency of history—
the choices that might have led to other outcomes.
Indeed, if our scholarship is to inform practice, it is criti-
cal that we understand the scope of the collective
choices we face today in shaping the future of the
digital transformation. Our framework therefore aims
to deepen macro-Schumpeterian theory by incorpo-
rating that indeterminacy. To do this, we look back
across prior revolutions to identify the types of prob-
lems in each sphere that held back the further develop-
ment of the technological revolution—we call them
“critical problems”—and the main competing solutions
on offer.
Turning to the future of the digital transformation,
we use this macro-Schumpeterian framework to guide
us to three propositions. First, in the technology
sphere, the critical problems appear to have been
largely overcome. Many of the technologies associated
with the digital transformation hold the promise of al-
lowing, at last, the deployment of the ICT revolution
to a much wider range of applications across industry
and everyday life. This deployment will be shaped by
the choices that will be made about how to respond to
the critical problems in the organization and public
policy spheres. Second, in the organization sphere, the
critical problem today lies in the limitations of the cur-
rently dominant management model, which we call
“Business Process.”Deployment will be influenced by
whether the choice is made to refine further that model
to offer even more control and exploitation benefits or
to supersede it with a model—we call it “Community-
and-Collaboration”—that better supports the empow-
erment of communities and bottom-up collaboration
across intra- and interfirm networks. Third, the choice
of management models will itself depend in con-
siderable measure on choices about public policy. The
critical problem here lies in the limitations of the
current “laissez-faire”public policy regime—aka
“neoliberalism”(Saad-Filho and Johnston 2005,Har-
vey 2007a)—which has been dominant in the United
States for the past four decades; deployment will be
shaped by whether the collective choice is to move fur-
ther in the direction of laissez-faire or to adopt a re-
gime based on a more proactive, system-building role
for government in the economy.
Putting together the main options for solving the
critical problems in the organization and public policy
spheres points to four alternative futures for the digi-
tal transformation. If a laissez-faire policy regime is
combined with an exploitive Business Process model,
we foresee a scenario evolving toward a corporate-
dominated digital oligarchy. If a system-building public
policy regime is combined with that Business Process
model, we foresee a scenario toward a government-
elite-dominated digital authoritarianism. If a laissez-faire
policy regime is combined in some local jurisdictions
with a Community-and-Collaboration model and in
other jurisdictions with a reinforced Business Process
Bodroˇ
zi´
c and Adler: Alternative Futures for Digital Transformation
2Organization Science, Articles in Advance, pp. 1–21, © 2021 The Author(s)
model, we foresee a patchwork pattern of digital local-
ism. If a system-building policy regime is combined
with wide diffusion of this new Community-and-Col-
laboration model, we foresee a scenario of digital democ-
racy. Given the United States’leading role in the ICT
revolution so far, our primary focus is on the prospects
for the digital transformation in the United States, but
we will also call out key factors that might shape differ-
ences across countries, orienting them to different
scenarios.
With this argument, our paper makes three main
contributions. First, aiming to theorize technological
revolutions at the societal level, we mobilize macro-
Schumpeterian theory and expand the two-way inter-
action of technology and organization to a three-way
interaction of technology, organization, and public
policy: we identify the dominant models in each of the
three spheres, and we show how their interplay shapes
the trajectories of macro-level technological revolu-
tions. Second, we augment macro-Schumpeterian the-
ory by developing a framework that accommodates
the contingency of history: by identifying the critical
problems and the competing alternative solutions, we
can clarify the collective choices ahead of us in the digi-
tal transformation. Third, we offer a theoretically and
historically informed framework that enables us to go
beyond the discussion of either optimistic or pessimistic
digital futures and outline a richer, more realistic set of
alternative futures for the digital transformation.
In the following sections, we first introduce the pro-
posed macro-Schumpeterian framework and the
three-way interaction of technology, organization,
and public policy and explain the role of critical prob-
lems and alternative solutions. We then discuss the
development of the digital transformation in each of
the three spheres, their respective critical problems,
and competing solutions. This leads to our discussion
of the four scenarios. We conclude by identifying
some directions for future research.
Macro-Schumpeterian Framework
Schumpeter (1934,1939,1942) saw technological revo-
lutionsascriticaltounderstandingcapitalism’scharac-
teristically uneven pattern of “creative destruction.”He
argued that capitalist development is shaped by techno-
logical competition between firms, encompassing inno-
vation in products, processes, raw materials, and ways
to organize business. A successful innovator will attract
a swarm of imitators. Moreover, there may be knock-on
effects as some innovations induce other, comple-
mentary innovations. Such systemic interdependencies
among technologies explain why innovations often
occur in clusters. The largest of these clusters form tech-
nological revolutions that affect not only individual in-
dustries but the entire structure of industry and fabric
of society.
The macro-Schumpeterians identify five technologi-
cal revolutions in the history of capitalism—rather
than lumping the first four into one big “Industrial
Revolution,”as do, for example, Brynjolfsson and
McAfee (2014). Their reasoned history of these various
revolutions (primarily: Freeman and Louc¸a 2001; Perez
2003,2010) has yielded some striking generaliza-
tions—“stylized facts,”as discussed by Helfat (2007)—
about the way they unfold.
1
First, revolutions take shape initially in one or two
“leading countries”—Britain in the Industrial Revolu-
tion and the steam-power-and-railways revolution,
the United States and Germany in the steel-and-elec-
tricity revolution, and the United States in the auto-
mobile-and-oil and ICT revolutions. The revolutions
then diffuse to other countries, mutating along the
way as they encounter diverse organizational and so-
cietal contexts.
Second, comparing the four prior revolutions in
their leading countries, we find a common phase pat-
tern: we summarize it here and discuss the underlying
dynamics. The technologies that eventually cohere as
the core of a technological revolution emerge during
an incubation period, whose duration seems to have
been rather variable across revolutions. At some
point, the most successful of these new technologies
draw the attention of investors and the installation pe-
riod begins with the rapid expansion of new “leading
industries,”and with the development of complemen-
tary product, process, and infrastructure innovations.
However, beyond those new industries, the rest of the
economy benefits much less from the new technolo-
gies, because the organizational forms and public poli-
cies inherited from the prior revolution are ill suited
to the new technologies. Moreover, the tensions asso-
ciated with the frenzy of investment in the new indus-
tries and the limited deployment across the rest of the
economy generate a period of financial, economic,
and social crisis. The urgency of the crisis and the
widely shared eagerness to ensure wide deployment of
the new technologies across the economy together
stimulate further innovations in organization forms
and public policies. Finally, the revolution enters a pe-
riod of exhaustion: here the developmental potential of
the new technologies is largely fulfilled, and this ex-
haustion encourages a shift in the direction of techno-
logical innovation efforts.
Third, the cumulative effect of technological, orga-
nizational, and public policy innovations in each revo-
lution yields a new paradigm in each of the three
spheres—paradigms that are in turn made obsolete by
the subsequent revolution. By analogy with the con-
cept of scientific paradigm (Kuhn 1970), we use
the term to refer to a constellation of interrelated con-
cepts that are institutionalized in practices and that
together set an agenda for future refinement. In the
Bodroˇ
zi´
c and Adler: Alternative Futures for Digital Transformation
Organization Science, Articles in Advance, pp. 1–21, © 2021 The Author(s) 3
technology sphere, paradigms emerge in the form of a
new “technological system”(Perez 2010). Technologi-
cal revolutions also stimulate paradigm changes in
the organization and public policy spheres, and the
pattern of change is distinctive within each sphere.
From a macro-Schumpeterian perspective, the dy-
namics that shape each technological revolution are a
function of the evolution within the technology, orga-
nization, and public policy spheres and interactions
between them. Each sphere in each technological
revolution is characterized by a revolution-specific
paradigm, which emerges as the cumulative result of
successive problem-solving cycles. In the following
paragraphs, we identify the main problem-solving
cycles and the main solutions—different types of
dominant models—yielded by these cycles in each of
the three spheres. We focus on the patterns found in
earlier revolutions and leave to the subsequent
section our discussion of how this history helps us
make sense of the ICT revolution and the digital
transformation.
Technology Sphere
In the macro-Schumpeterian account, technological in-
novations often cluster into waves—“revolutions”—
that yield new technological paradigms. Innovations
lead to revolutions if “bandwagons”of several differ-
ent innovations “roll”together (Freeman 1982, p. 67).
This is particularly likely in the presence of a general-
purpose technology (GPT) (Bresnahan and Trajten-
berg 1995) and the resulting complementarities and
synergies among associated technologies (Rosenberg
1979).
Generalizing across prior revolutions, the pattern
here appears to be that each new technological para-
digm emerges through two types of problem-solving
cycles. A first type is aimed at consolidating the new
GPT itself—yielding a set of foundational innovations
and establishing enough evidence of the GPT’s poten-
tial to attract innovators aiming to exploit it. A second
type is aimed at expanding and cheapening a set of
applications and complementary products.
Freeman and Louc¸a (2001)summarizethefoundation
of these generalizations in their analysis of prior techno-
logical revolutions. The original “industrial revolution”
(approximately 1750s–1840s) started in Britain. It was
based on water power as a GPT, on cotton, iron, and wa-
ter as core inputs, and on weaving and water-power
machinery. The emerging water-power-and-cotton para-
digm was augmented by new supporting infrastructure
(canals and roads), by new complementary technologies
(e.g., iron components of water wheels and weaving ma-
chinery), by new production processes (water-powered
industrial production of cotton products), and eventually
by new unanticipated applications (e.g., iron cutlery and
cooking tools).
The second technological revolution (approximately
1790s–1890s) also began in Britain, but the United States
was not far behind. It was based on steam power as a
GPT, on coal and iron as core inputs, and on the rail-
way. The emerging steam-power-and-railways para-
digm was augmented by new supporting infrastructure
(railway and telegraph networks), by new complementa-
ry technologies (e.g., the telegraph), by new production
processes (e.g., steam-powered industrial production of
machine tools that were independent of waterways),
and eventually by new unanticipated applications (e.g.,
steamships).
The third revolution (approximately 1850s–1940s)
saw the United States take the role of leading country.
This revolution was based on electricity as a GPT, on
iron as a core input, and on steel applications. The
emerging steel-and-electricity paradigm was aug-
mented by new supporting infrastructure (interconti-
nental trade enabled by robust steel ships), by new
complementary technologies (e.g., heavy engineer-
ing), by new production processes (more flexible pro-
duction processes that were independent of bulky
steam engines and based on deploying the electric
motor), and eventually by new unanticipated applica-
tions (e.g., the telephone).
The fourth revolution (approximately 1880s–1980s)
was based on the internal combustion engine as a
GPT, on oil as a core input, and on the automobile.
The emerging automobile-and-oil paradigm was aug-
mented by new supporting infrastructure (e.g., high-
ways and airports), new complementary technologies
(e.g., plastics), new production processes (assembly-
line-based mass production), and eventually by new
unanticipated applications (e.g., myriad new house-
hold applications).
These partly overlapping technological revolutions
also yielded new leading industries and exemplary
firms. Giant oligopolistic firms emerged in the installa-
tion period of each successive revolutions: Erie Railroad
and Pennsylvania Railroad; Bethlehem and United
States Steel; the “big three”auto companies, General
Motors, Ford, and Chrysler (Bodroˇ
zi´
candAdler2018).
The dominance of these firms was not only based on
their technological prowess but also on changes in the
organization and public policy spheres.
Organization Sphere
Inventions are consequential when they are taken up
by enterprises as innovations—when enterprises in-
vest in them, refine them, and bring the associated
products to market and new processes to scale. That
distinction between invention and innovation was one
of Schumpeter’s core insights. Macro-Schumpeterian
Bodroˇ
zi´
c and Adler: Alternative Futures for Digital Transformation
4Organization Science, Articles in Advance, pp. 1–21, © 2021 The Author(s)
research on prior revolutions shows that this innova-
tion process necessitates organizational changes. The
radically new technologies fit uneasily within the inher-
ited organizational paradigm, and each technological
revolution has thus led to a new organizational para-
digm. The historical record suggests that each new para-
digm emerged in two problem-solving cycles, with each
cycle yielding a new dominant “management model”—
a new body of ideas that offer management guidance on
how to deal with their technical and social tasks (Bod-
roˇ
zi´
candAdler2018).
In a primary cycle, a “paradigm-revolutionizing”
model emerges in response to the perceived inadequa-
cy of the then-prevailing organizational paradigm in
the face of the new technologies’potential. This prima-
ry cycle yields a new management model that obso-
letes the inherited paradigm and restores “external fit”
between key organizational elements and the new tech-
nologies’potential. It solves some of the misfit between
the technology and organization spheres but simul-
taneously generates dysfunctional misfitamongorga-
nizational elements. Its limitations spark a secondary
problem-solving cycle, which yields a new, “paradigm-
balancing”management model, which aims to reestab-
lish “internal fit”among organizational elements (Miller
1992) to harness the bottom-up innovation capacity of peo-
ple and organizations. This new balancing model helps to
stabilize the revolution’s organizational paradigm.
Viewed through the lenses of Schumpeter’s(1942)
theory of creative destruction—and the critical role of
the destructive moment—it is not hard to see why the
primary cycles typically led to unbalanced models
that left in their wake considerable labor strife, and
that thus triggered secondary, balancing cycles. The
dialectical tension between paradigm-revolutionizing
and paradigm-balancing models was captured in or-
ganization theory in the contrast between rational,
technical models and normative, commitment-
oriented ones drawn by Barley and Kunda (1992).
Market and Hierarchy were the dominant organizing
principles in the former, and Community was more
salient in the latter (Adler 2001).
We can illustrate by pointing to the two cycles in
some of the prior revolutions (as reviewed by
Bodroˇ
zi´
c and Adler 2018). In the steel-and-electricity
revolution, the radical technological innovations asso-
ciated with steel production and electric power af-
forded higher throughput speed and greater efficiency
in factory layout. This challenged managers and engi-
neers to rethink workstation design and workflow
plans. The prevailing organizational paradigm inher-
ited from the steam-power-and-railways revolution
did not offer answers: Frederick Taylor’s organiza-
tional innovations, developed and implemented in
leading steel firms such as Bethlehem Steel, emerged
in response. Scientific Management integrated these
organizational innovations into a coherent, new man-
agement model characterized by time-and-motion
studies, new principles in plant layout, and more ra-
tional and equitable incentive payments.
However, in the form in which it was most frequent-
ly implemented, Scientific Management also generated
dysfunctions, such as highly regimented work and
weakly motivated factory workers. These dysfunctions
in turn triggered a secondary cycle of organizational
innovations focused on restoring greater internal fit.
This cycle coalesced around the Human Relations
model, which aimed to create greater harmony in
workplaces by encouraging individualized personal
consideration in supervisor-employee relations. It was
the synthesis of the Scientific Management and Hu-
man Relations models that defined the dominant orga-
nization paradigm (which we call the “Factory”para-
digm) in the early decades of the 20th century.
The next revolution, the automobile-and-oil revolu-
tion, brought a proliferation of cheap, mass-produced
consumer goods, challenging firms to respond to the
different “purse and purpose”of different consumers.
The Factory paradigm did not offer answers to this
problem, and in response, organizational innovators
in the automobile industry (most notably Alfred Sloan
in General Motors) created the “Strategy-and-
Structure”model, which was subsequently diffused
across the corporate landscape: semiautonomous
business units were assigned the responsibility for of-
fering mass-produced goods and services to differen-
tiated market segments. The dysfunctions of that
Strategy-and-Structure model, such as poor quality
and low worker involvement, were subsequently ad-
dressed by the emergence of a paradigm-balancing
model—“Quality Management.”The synthesis of the
Strategy-and-Structure and Quality Management
models defined the organizational paradigm (which
we call the “Corporation”paradigm) of the second
half of the 20th century.
We should note that causality runs both ways be-
tween the technology and organization spheres. Tech-
nological innovation (e.g., widely available electrical
power) triggered organizational innovation (e.g., fac-
tory reorganization based on Scientific Management),
which in turn triggered technological innovation (e.g.,
the development of new variants of electric motors
and electric-powered machinery that offered more flex-
ibility in factory layout). The interplay of technology
and organization spheres alone, however, does not ex-
plain why leading steel and automobile firms turned
into powerful oligopolies.
Public Policy Sphere
Macro-Schumpeterian research on the history of prior
revolutions suggests that the two-way interaction of
Bodroˇ
zi´
c and Adler: Alternative Futures for Digital Transformation
Organization Science, Articles in Advance, pp. 1–21, © 2021 The Author(s) 5
technology and organization has both shaped and been
shaped by their interaction with a third sphere—public
policy. In this sphere too, each revolution saw two suc-
cessive problem-solving cycles, which each generated a
distinct model of public policy—a public policy
“regime.”(Weadoptthedefinition of policy regimes of-
feredbyMayandJochim(2013,p.428)as“the govern-
ing arrangements for addressing policy problems.”)
In the installation period of each of the prior techno-
logical revolutions, growing concern with the misfit
between the new technologies and the inherited pub-
lic policy regime typically led to a shift in public poli-
cies toward laissez-faire, taking a somewhat different
coloration in each revolution. In practice, this has
meant not so much a retreat of the state as breaking
down restrictions on the business sector that were in-
herited from the prior public policy regime (such as
labor laws, banking regulations, etc.) and that might
stand in the way of the enthusiastic flow of investment
into the new core industries. The primary goal was to
unleash the energy associated with the potential for
private-value creation. A laissez-faire policy regime
lifted roadblocks to investments in the new cluster of
technologies, but it also allowed the emergence of giant
oligopolies in key industries (in successive revolutions:
railways; steel and electricity; automobile and oil),
growing inequality, and the erosion of market-
stabilizing regulations. The latter fueled an investment
frenzy (successively: the canal mania, the railway mania,
the Gilded Age, the Roaring Twenties), and these fren-
zies have all culminated in society-wide financial, eco-
nomic, and institutional crises (successively: the Panic
of 1847 in Britain and the 1870s depression in United
States, followed in the United States by the 1890s de-
pression, and then by the 1930s Great Depression).
In the course of each of the prior revolutions, these
crises led to a reorientation of public policy toward a
system-building role for government—both to absorb
the crisis and to assure the wider deployment of the
new technologies beyond the leading industries. In-
deed, the macro-Schumpeterians have shown that,
whereas the installation period was often assisted by
public policies aimed at increasing the rate of private-
sector innovation, the deployment period has typi-
cally been associated with public policies that also
aimed to shape the overall direction of innovation
(Mazzucato 2015). The authoritative power of govern-
ment created a shared sense of the likely course of
economic development, which in turn strengthened
investor confidence. The system-building regimes—
again, with a somewhat different coloration in each
revolution—established critical material and social in-
frastructure and shared more equally the fruits of the
technological revolution.
Adopting again the creative-destruction lenses of
Schumpeter (1942, p. 70), we can see why a laissez-faire
public policy regime typically dominates initially, but
why it also leads to a crisis, triggering a system-building
regime in its wake. The dialectical tension between these
two policy regimes was articulated by political scientists
such as Hirschman (2002)asacontrastbetweenprivate
versus public interests and by political economists such
as Polanyi (1968) as a contrast between a disembedded
economy versus one that is re-embedded.
To illustrate the contrast, consider the steel-and-elec-
tricity revolution, whose installation period started in
the 1870s. It gave rise to a massive wave of investment
in machine-based manufacturing and agriculture, to the
huge increase in inequality known as the Gilded Age,
to the emergence of giant steel firms (whose owners
were denounced as “robber barons”), and eventually to
the Panic of 1893 and the deep depression of 1893–1897.
The subsequent shift from installation to deployment
during the Progressive era was marked not only by
government support for the creation of the country’s
comprehensive “network of power”(Hughes 1993)but
also by a broad campaign to eliminate government cor-
ruption, by the first serious enforcement of the Sherman
Antitrust Act of 1890 (which was strongly opposed by
advocates of laissez-faire policies but supported by so-
cial movements), by the introduction of women’ssuf-
frage, by the creation of the Federal Reserve, and by a
range of system-building rural reforms (Freeman and
Louc¸a 2001).
Consider the automobile-and-oil revolution, whose
installation period ran from approximately 1910 to
1930 (Freeman and Louc¸a 2001). The opportunities
represented by the new technology prompted a wave
of investment and accelerated productivity growth
and thereby contributed to the dynamism of the Roar-
ing Twenties. Public policy moved in a laissez-faire di-
rection. As President Coolidge famously stated in
1923: “the business of America is business”(Wilson
2016, p. 24). Weak regulation encouraged a frenzy of
speculative stock market investment and a rapid ex-
pansion of consumer credit for the new commodities
(cars, appliances, etc.). Levels of concentration grew in
core industries (most notably, in the growing share of
the Big Three in the auto industry). Inequality soared.
Agricultural employment collapsed as productivity
growth accelerated, leading to social crisis in rural
areas. Public policy did little to boost consumer
purchasing power, and investment and production
rapidly outstripped demand. The combination of
these factors (among others) led to the Wall Street
Crash of 1929 and the Great Depression.
In response to this crisis, a new public policy model
emerged in the New Deal. New regulations were
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introduced to stabilize the banks and financial markets.
Government encouraged the expansion of investment
in the real economy and supported home mortgage
loans. Legislation formalized the role of unions, and
these unions negotiated wage increases in line with pro-
ductivity increases, thereby ensuring growing demand
for the output of a technological dynamic manufactur-
ing sector. This system-building regime also responded
to the opportunities created by the automobile-and-oil
revolution with massive public investment in high-
ways, creating the transport infrastructure on which we
still rely (Gordon 2000).
Robustness of This Framework
The present paper aims to build on and expand this
macro-Schumpeterian foundation to understand the
digital transformation. However, before proceeding,
we should address some potential limitations and ex-
plain why they should not deter us.
First, some doubt that innovations cluster so strongly
(Puffert 2003). Many historians of technology recoil at
the idea that we can reduce the historical record of the
manifold technologies to a series of neatly discrete tech-
nological revolutions. Historians of management and
public policy might have a similar reaction. We see this
as a matter of the difference in taste between lumpers
and splitters.
Second, there is debate about the connection between
these technological revolutions and the “Kondratieff”
cycles of gross domestic product growth and contrac-
tion of about 50–60 years in duration (Kondratieff 1979).
Whereas Schumpeter argued that technological revolu-
tions explained these long waves (Mager 1987), some
macro-Schumpeterians see only a looser connection
(Perez 2003,2010). This is an interesting question, but it
does not have much impact on the questions addressed
in the present paper.
Third, our focus on these three spheres means
leaving aside a range of other contextual factors that
surely play a role. Culture, for instance, has had a sig-
nificant impact on the trajectory of technological revo-
lutions (see the discussion of Perez and Leach (2018)
on the importance of lifestyle changes). We make this
simplification to avoid escalating theoretical complex-
ity; however, the framework can be expanded in the
future.
Fourth, we abstract from major, relatively unpre-
dictable events like wars, volcanic eruptions, and
pandemics, which can affect a technological revolu-
tion’s trajectory (as noted by Schot and Kanger 2018
and Kaldor 2021). Both of the 20th century’sworld
wars, for example, had important effects (Jaworski and
Fishback 2018). In contrast, a focus on public policy
has the advantage of bringing into focus the means by
which we might collectively influence the trajectory of
the revolution currently underway.
Finally, whereas macro-level macro-Schumpeterian
historical research has revealed a strong pattern across
prior revolutions, it has been less helpful in identify-
ing the uncertainties and options facing actors as they
made the various choices that gave rise to that pattern.
Here is where we propose to augment the macro-
Schumpeterian framework, as we explain in the fol-
lowing subsection.
From Ex Post Regularities to Ex Ante Choices
Our review of prior revolutions revealed some impor-
tant regularities across them. In reality, however, each
of the prior technological revolutions encountered
“forks in the road”where different choices could have
led to different outcomes. A rigorous account of tech-
nological revolutions—especially one that aims to in-
form the collective choices ahead of us with the digital
transformation—must therefore dive deeper and char-
acterize these forks in the road.
We saw that in each of the prior revolutions there
were two main types of problem-solving cycles in
each of the three spheres. In each cycle, a critical prob-
lem came into focus as the impediment to the progress
of the revolution—visible in significant system-level
performance limitations and disappointing rates of
system-level performance improvement (David 1990,
David and Wright 1999).
2
There was considerable un-
certainty about how to overcome such critical prob-
lems. Innovators entered uncharted territory here and
different actors advocated competing, alternative op-
tions. Our account brought to the fore the repeated se-
quence (across revolutions) in the types of solutions
retained: however, we need to unpack this observed
ex post pattern to reveal the underlying ex ante
choices and the options not retained. We review the
three spheres in turn to offer some illustrations.
In the technology sphere, in the narrative offered
previously, each revolution encountered critical prob-
lems that cluster in two broad types: one related to
consolidating the core GPT, and another, more hetero-
geneous cluster related to the dearth of creative appli-
cations that would drive wider deployment beyond
the core industries. We can illustrate the critical prob-
lems and alternative solutions for both types with ex-
amples from the fourth technological revolution (the
automobile-and-oil revolution). For the first type: be-
fore the internal combustion engine became recog-
nized as the GPT, some vehicles were powered by
steam or electric engines. The internal combustion
engine only became dominant after a series of techno-
logical innovations led to its higher efficiency relative
to those alternatives (Freeman and Louc¸a 2001). Con-
sider the second type: many accessories and compo-
nents for automobiles were initially made of natural
materials such as metal, wood, rubber, and leather.
With the advent of oil-based plastics, cheaper and
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lighter alternatives emerged, becoming increasingly
dominant in the course of the 20th century, even if
some product lines continued to rely on the natural
materials to signal their luxury status (Freeman and
Louc¸a 2001). (The 21st century might witness a rever-
sal of the 20th century's choices: the re-emergence of
the electric motor and of materials that are not syn-
thetic and are easier to recycle).
Turning to the organization sphere, the historical pat-
tern of retained solutions that we described previously
was the following: in each revolution, a first problem-
solving cycle led to the emergence of a paradigm-
revolutionizing model, which was dominant in the
earlier phases of the revolution, and a second cycle led
to a paradigm-balancing model, which was dominant
in the later phases. This pattern should not obscure the
variety of possible resolutions of the critical problems
in each of the cycles, and the vigorous debates among
proponents of alternative models. Consider the third
technological revolution (steel-and-electricity). A coer-
cive form of Scientific Management became the domi-
nant model in the installation period of this revolution;
however, from its early years, that option was in com-
petition with a more participative one proposed by
Frank and Lillian Gilbreth and other like-minded orga-
nizational innovators (Nyland 1998).
Consider the Human Relations model, which
emerged in the deployment period of that revolution to
rebalance the coercive Scientific Management model
and restore greater internal fit. Human Relations was
just one of the options competing for hegemony in the
1920s and 1930s. In comparison with the more vigorous
paradigm-balancing options on offer—such as ones
based on a vision of “industrial democracy”(Jacoby
1985)—it proposed a relatively modest rebalancing,
aiming to inject more individualized personal consider-
ation into supervisor-employee relations.
In the public policy sphere, installation periods’
problem-solving cycles led to laissez-faire regimes
and deployment periods’cycles led to system-
building regimes. However, here too, this regularity
should not obscure the variety of possible resolutions
of critical problems in each of the cycles and the vigor-
ous debates between proponents of competing re-
gimes. These options were already visible in the very
early history of the United States, as a conflict between
Alexander Hamilton, who urged a system-building
regime, and Thomas Jefferson who advocated a
laissez-faire approach (Parenti 2020).
Consider for example the fourth technological revolu-
tion (automobile-and-oil). The public policy regime during
the installation period of this revolution (culminating in
the Roaring Twenties) was strongly laissez-faire ori-
ented, promoting deregulation and privatization.
However, even during this period, system-building al-
ternatives (e.g., public ownership of infrastructure) had
their promoters, and in some local jurisdictions (e.g.,
New York), those solutions were implemented with
some success (Wilson 2016). Conversely, during the cri-
sis and early deployment phases (1930s and 1940s), a
strong system-building regime emerged in the form of
the New Deal. However, even during World War II,
there were strong voices advocating a return to laissez-
faire (Wilson 2016).
Indeed, in prior technological revolutions, critical
problems in each of the three spheres could have been
resolved in alternative ways. In the organization
sphere, these alternatives represent different resolu-
tions of the dialectical tension between paradigm-
revolutionizing and paradigm-balancing goals,
whereas in the public policy sphere, the alternatives
represent different resolutions of the tension between
laissez-faire’s push for private-value creation and
system-building’s push for public-value creation. Let
us now turn to the digital transformation and use this
framework to understand its critical problems and al-
ternative solutions.
Digital Transformation in Macro-
Schumpeterian Perspective
Writing in 2021, we appear to be in an extended peri-
od of crisis that began with the dot.com crash, contin-
ued with the 2008 financial crisis, and continues as yet
unresolved. Although the COVID-19 pandemic is an
externally induced shock, its fatal consequences for
vulnerable groups of the society are an indicator of
burning issues in public policy. This crisis condition is
one of many indicators suggesting that we are at the
inflection point—the crisis period—that typically sep-
arates installation and deployment in a technological
revolution (Perez 2010). The following subsections test
that idea by assessing the state of each of the three
spheres and putting that state in historical perspective.
Technology Sphere: Ready for Deployment
We argue that the digital transformation is the latest
phase in the wider arc of the ICT revolution. This ICT
revolution is essentially a computers-and-data re-
volution that conjoins, as did preceding revolutions, a
new general-purpose technology (here, the computer)
and new core inputs (here, digital data) to create the
germs of a new technological paradigm. This emerging
ICT paradigm was augmented by new supporting
infrastructure (notably, the Internet; subsequently, so-
cial media), new complementary technologies (e.g.,
those pertaining to telecommunications), and new
computer-controlled production processes. New appli-
cations such as the smart phone (complemented by
myriad “apps”), and a family of application-oriented
digital technologies (e.g., AI, the Internet of Things, big
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data analytics, robotics, social media, blockchain, and
3D printing) have further expanded the ICT paradigm.
A broad consensus has emerged that this family of
digital technologies offers exciting prospects for very
wide deployment. Grounds for this optimism are visi-
ble when we examine the longer arc of the key ICT
technologies (Table 1). The earlier, installation period
of the ICT revolution faced critical problems related to
the utilization of the computer as a GPT. One of these
problems was the transmission of data between com-
puters: the lack of an adequate infrastructure for the
core input of the ICT revolution impeded the devel-
opment of the whole cluster of technologies. This
critical problem was solved (if not optimally: see Bel-
lovin et al. 2006) with the development of the Inter-
net as an open, semipublic platform: this innovation
profoundly affected the trajectory of the whole ICT
cluster, and gradually the entire economy. With the
emergence of the Internet, the diffusion of further in-
novations accelerated, and network effects began
transforming entire industries (Kushida and Zysman
2009).
The second type of critical problem then emerged in
the technology sphere—the need for cost-effective, user-
friendly applications that could appeal to a wider set of
industries and activities. The more recent innovations
associated with the digital transformation promise to
solve that critical problem, and thereby take the revolu-
tion far beyond the core “tech”industries that incubated
this revolution (World Economic Forum 2020). We note,
for example, the development of high-powered AI and
its use in fields such as biology and chemistry (Benaich
and Hogarth 2021); the enormous potential of the Inter-
net of Things in both industry and households (Ranger
2020); the emergence of blockchain, which opens new
possibilities for smart contracting and collaboration
(Murray et al. 2022); and the range of commercial and
scientific applications for low-cost, high-powered visual-
ization tools (The Economist 2020).
If, on the one hand, the technologies of the digital
transformation seem poised for wide deployment, on
the other hand, it is much less clear what form this de-
ployment will take. In contrast to the development of
the Internet, the development of these emerging tech-
nologies is increasingly dominated by large private
companies such as Google and Facebook (Benaich and
Hogarth 2021). Whereas the new technologies facili-
tate globalized commercial, financial, and social inter-
action and new forms of collaboration, participation,
and democracy, they also enable control, manipulation,
and surveillance. Network effects and permissive pub-
lic policies have enabled high levels of concentration in
Table 1. Timeline of the ICT Revolution
Critical problems in the
evolution of the digital
paradigm Period Major shift Founding of exemplary organizations
Development of core ICT
foundations
1960s Incubation of computer components 1968: Intel
1970s Rapid rise of mainframe computers 1975: Microsoft
1976: Apple
1977: Oracle
1980s Rapid rise of personal computers 1982: Adobe
1984: Dell
1985: Cisco
1987: McAfee, Huawei
1990s Emergence of networked computers and
Internet
1993: Nvidia
1994: Amazon, Yahoo
1996: eBay
1998: Google, PayPal, Tencent
1999: Napster, Alibaba
Development of digital
technologies that facilitate a
wider variety of applications
2000s Emergence of mobile, social, platform, and
cloud technologies
2001: Wikipedia
2003: MySpace
2004: Facebook
2005: YouTube
2006: Twitter, Spotify
2008: Airbnb
2009: Uber, WhatsApp, Pinterest, Bitcoin
2010s Emergence of AI, big data, Internet of
Things, blockchain
2010: Instagram, DeepMind
2011: Banjo, Snapchat
2012: ThoughtSpot
2013: Databricks
2014: SenseTime, Zoox
2015: Ethereum
2015: CloudMinds, OpenAI
2016: Argo AI, Clarivate Analytics
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industry, and the resulting behemoths have gathered a
vast amount of data about customers—as have govern-
ments about their citizens—even as the mechanisms of
data gathering and use have been kept remarkably
opaque (Faraj et al. 2018,Zuboff2019). Battles for con-
trol over data and the underlying technologies have
led to international tensions between the United States
and China (e.g., in 2020 regarding the role of Huawei
in communications infrastructure).
This discussion of the current state of the technol-
ogy sphere leads to the first of our three summary
propositions:
Summary Proposition 1. The emergence of the family
of application-oriented digital technologies represents a
maturation of the new ICT technological paradigm. It sig-
nals that the ICT revolution is ready to move from the in-
stallation period to the deployment period. Our current
uncertainty as to the future trajectory of this revolution is
caused not only by our ignorance but also by the underde-
termined nature of this deployment period. Deployment
will be shaped by choices yet to be made in the organiza-
tion and public policy spheres.
Organization Sphere: Between Business Process
and Community-and-Collaboration
The ICT revolution is stimulating the emergence of a
new organizational paradigm—the Network paradigm
(Benkler 2006, Castells 2011). Viewed from the vantage
point of our macro-Schumpeterian model, this Net-
work paradigm appears to have been initially triggered
by a paradigm-revolutionizing Business Process man-
agement model. This Business Process model was a
response to the first critical problem in the organization
sphere of the ICT revolution—the mismatch of ICT
technologies and the siloed character of the inherited
organizational paradigm. The tall walls between units
within the firm and between the firm and its upstream
and downstream exchange partners were seen as im-
pediments to exploiting the new technologies’poten-
tial. This critical problem was frequently identified as
the main reason for the ICT revolution’s“productivity
paradox”—the surprisingly slow productivity gains
during this period in industry taken as a whole (Solow
1987, David and Greenstein 1990, Macdonald et al.
2000).
This situation prompted a problem-solving cycle
that yielded the concept of “business process re-
engineering”(Hammer 1990): here, new technologies
were used to break the siloes that characterized the in-
herited organizational paradigm. Firms were urged to
use the new technologies to rationalize their business
processes across the value chain, to outsource
“noncore”activities and employees, and to bridge in-
ternal and external boundaries (Davenport and Short
1990, Hammer 1990, Ashkenas et al. 2015). Although
business process reengineering was widely criticized
and rapidly dropped as a label, the more general idea
of a “process orientation”within and between organi-
zations (Majchrzak and Wang 1996) persisted, repre-
senting the core of the Business Process model. It
enabled the coordination of global supply chains
(Sturgeon and Lester 2002, Garcia-Dastugue and Lam-
bert 2003), contributing to the rise of “supply chain
management”as an important new management con-
cept (Cooper et al. 1997).
These organizational innovations prompted and
then in turn shaped technological innovation, particu-
larly in the form of standardized interfaces and link-
ages that facilitated the flow of information across
boundaries both within and between firms. Processes
were of course important loci of innovation in prior
revolutions: here what was novel was the use of ICT to
expand vastly the reach and increase the granularity of
management control and value capture, both within
and between firms, by deploying a combination of hi-
erarchical authority and market power.
The Business Process model was accompanied by
dysfunctions (paralleling the emergence of dysfunc-
tions caused by the primary cycle of prior revolu-
tions). Most critically, process reengineering and
outsourcing often disrupted the fabric of collective
tacit knowledge shared by experienced employees
both within and across firm boundaries, which in turn
limited innovativeness and flexibility (Davenport et al.
2003). In the macro-Schumpeterian perspective, the
need to address these dysfunctions appears as a sec-
ond critical problem in the organization sphere, one
that might potentially trigger the emergence of a
paradigm-balancing model.
Whereaswehaveconsiderableevidenceforthe
importance of the Business Process model as a paradigm-
revolutionizing model, the corresponding paradigm-
balancing model is still in gestation. Nevertheless,
the pattern in prior revolutions and the recent trends
in management publications are sufficiently clear to
point us to our second summary proposition:
Summary Proposition 2. The trajectory of the digital
transformation will depend on the response to the current
critical organizational problem of the ICT revolution.
More specifically, it will depend on whether the Business
Process model is refined further to generate greater man-
agement control and value-capture benefits, or a new
model emerges that better supports community-building
and collaboration in networks. We call this alternative the
Community-and-Collaboration model. (The contrast be-
tween the two models is presented in Table 2.)
The current popularity of a number of management
concepts points to the emergence of a balancing model
based on community and collaboration. The literature on
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“open innovation”embraces the potential of collabora-
tion among firms to generate innovation (Chesbrough
2006, Gassmann 2006). Research on crowdsourcing
(Majchrzak and Malhotra 2020) shows how “collabo-
rative crowdsourcing”enriches Business Process–
oriented types of “idea searching.”The emphasis on
(re)creating the fabric of collaboration is central in some
(but not all) online communities (Faraj et al. 2011), cow-
orking spaces (Garrett et al. 2017,Spinuzzietal.2019),
ecosystems (Datt´
ee et al. 2018), and crowdfunding plat-
forms (Belleflamme et al. 2014, Leung and Sharkey 2014).
The goal of cultivating collaboration among community
members underlies management concepts like scrum,
agile, and DevOps in software development (Schwaber
and Beedle 2002,Conboy2009).
3
Within firms, Commu-
nity-and-Collaboration approaches appear in a range of
forms, from producer cooperatives to advanced forms of
participative management in conventional capitalist
firms. Between firms, it can take the form of “managed
ecologies”(Altman et al. 2021)andthe“collaborative
communities”discussed by Snow et al. (2009).
The contours of this Community-and-Collaboration
model are still somewhat undefined, but they appear
to fit the general characteristics of paradigm-balancing
models in aiming to harness bottom-up innovation
capacity. As with previous revolutions, it does so by
renewing the salience of the Community principle in
the organization of various activities, while at the
same time introducing a new type of community. Ear-
lier revolutions’balancing models relied on forms of
community that were based on tradition or affectual
ties. This revolution, by contrast, with its process ori-
entation, seems to rely on and stimulate the emergence
of a new type of community—one that is capable of
supporting key processes by bringing together large
networks of very heterogeneous groups of people
around a sense of “shared purpose”(Adler and
Heckscher 2018). The “purpose”of such communities
can be more localized and mundane—for example, to
develop a software utility—or it can be more elevated,
like responding to a “grand challenge”such as the
climate emergency. In either form, its day-to-day
management relies on collaborative goal setting,
contribution-based rewards offering low-powered fi-
nancial incentives combined with prominent social in-
centives, formal systems that enable rather than coerce,
Table 2. Two Management Models for the Digital Transformation
Primary, paradigm-revolutionizing
management model
Secondary, paradigm-balancing
management model
Current alternative models Business Process model: Rationalizing
internal and external processes, enabling
exploitation and value capture
Community-and-Collaboration model:
Recreating social fabric, enabling
collaboration toward shared purpose
Model’s role in technological revolutions Obsoleting the inherited organizational
paradigm and establishing the new
organizational paradigm
Rebalancing the new organizational
paradigm
Harnessing the new possibilities generated
by the new technology cluster
Harnessing the bottom-up innovation
capacity of people and organizations
Re-establishing external fit by overcoming
the limitations of the inherited model in
this new technological context
Re-establishing internal fit by overcoming
the limitations of the primary model
Historical examples of models Line-and-Staff in steam-power-and-
railways revolution
Industrial betterment in steam-power-and-
railways revolution
Scientific Management in steel-and-
electricity revolution
Human Relations in steel-and-electricity
revolution
Strategy-and-Structure in automobile-and-
oil revolution
Quality Management in automobile-and-oil
revolution
Theorizations of the contrast between
models
Rational/technical (Barley and Kunda
1992)
Normative/human (Barley and Kunda
1992)
Environmental fit (Miller 1992) Internal fit (Miller 1992)
Market and Hierarchy as dominant
organizing principles (Adler 2001)
Community as dominant organizing
principle (Adler 2001)
Key features of the current alternatives Use technology to eliminate labor Use technology to augment labor
capabilities
Outsource to arm’s-length suppliers Build collaborative interfirm networks
Build asymmetrical power relations Build shared power
Pursue market goals: exploitation and
value capture
Pursue shared purpose: exploration and
collaboration
Examples of contrasting concepts
supporting the current alternatives
Strategic alliances (Barney and Hansen
1994)
Ecosystem (Jacobides et al. 2018)
Idea searching (Majchrzak and Malhotra
2020)
Collaborative crowdsourcing (Majchrzak
and Malhotra 2020)
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and distributed leadership (Adler and Heckscher
2018).
Looking forward to the prospects of the digital
transformation, we see two main types of responses to
the current critical problem in the organization
sphere; each type points to a different scenario and
different type of network. In the first type, the Busi-
ness Process model remains dominant and integrates
the Community-and-Collaboration model only par-
tially, perhaps only at a symbolic and rhetorical level.
In the second type, the Community-and-Collaboration
model becomes dominant and incorporates the ad-
vances of the paradigm-revolutionizing model while
transcending its limitations.
This fork in the road is particularly visible in the case
of platform companies. In many of the dominant plat-
forms, we see the first type of scenario: the Business
Process model remains dominant, even as its dysfunc-
tions have become increasingly visible, and there is lit-
tle evidence that the Community-and-Collaboration
model is diffusing. The massive network effects of dig-
ital technologies generate “winner-takes-all”competi-
tive dynamics that subordinate Community to Market
priorities. Consider Facebook. Yes, Facebook created
opportunities for users to communicate, and this social
media technology could support the flourishing of
community; but that potential was not fulfilled: Face-
book’s deployment of this technology is dominated by
a Business Process logic (exchanging clicks for adver-
tising dollars), and the company jealously guards its
ability to repurpose the resulting data regardless of
users’interests or preferences (notoriously in the case
of Cambridge Analytica). Governance of this network
is controlled by and for the platform owner (Srinivasan
2019,2020). Or consider Amazon Marketplace. Here
too, the actors on both sides of the platform are weak
relative to the platform owner. Digital technologies are
used to control and eliminate labor. Amazon uses data
on their suppliers’sales to design and under-price
competing products. The Business Process model
helps exploit “platform dependency”—the asymmetri-
cal power relation between platform users and plat-
form owners (Kenney et al. 2020, Schor 2020)—and in
the process, undermines community.
The second type of scenario could be easily imag-
ined: In the case of platforms such as Facebook, the
network would not be controlled by the platform
owner but would be operated by and for the commu-
nity of users. In the case of Amazon, data would not
be used to enable Amazon’s owners to capture more
private value but would help build a community
among suppliers that would enable them collectively
and collaboratively to improve their offerings. The
power relations between platform users and owners
could be much more symmetrical.
The choices made at this fork in the road will also
have a major impact on the future path of the techno-
logy sphere. In the first type of scenario, new technolo-
gies such as AI, robots, and autonomous vehicles
might be the basis for a future governed by a small
number of companies—like Facebook, Google, and
Amazon—who rely on the Business Process model
to intensify their control and surveillance, or by au-
thoritarian governments for the same benefit. Alterna-
tively, if the Community-and-Collaboration model
were to prevail, these technologies could be used to en-
hance organizational transparency and accountability
(Albu and Flyverbom 2019) and AI could create and
enrich jobs rather than destroy and impoverish them
(Acemoglu and Restrepo 2020). Worker-owned plat-
form cooperatives, where members collectively set
fares, compensation, and investment, could displace
extractive platforms (Scholz and Schneider 2017).
Which path will the digital transformation take?
History suggests that this depends in part on choices
made in the public policy sphere.
Public Policy Sphere: Between Neoliberal
Laissez-Faire and Proactive System-Building
As was the case in previous revolutions, the dominant
public policy regime in the installation period of the
ICT revolution was a laissez-faire type. The enthusi-
asm for the potential of the new technologies conflicted
with the inherited public policy regime, and the latter
gave way to the current instantiation of laissez-faire—
“neoliberalism”as it is frequently referred to (Saad-
Filho and Johnston 2005, Harvey 2007a, Cahill et al.
2018).
4
Each new laissez-faire regime differs from the
preceding ones, jast as each new system-building re-
gime does. In particular, neoliberalism is relatively
novel inter alia in its focus on privatizing the delivery
of public services. Bernstein (2006) describes this neo-
liberal form as a YOYO regime: “you’re on your own.”
Enthusiasm among investors for the new technolo-
gies’potential led to a stock-market frenzy, which
government encouraged by scaling back financial
regulations: the Clinton administration abrogated the
long-standing Glass-Steagall Act and refused to regulate
the expanding market for derivatives. The network ef-
fects so common among the new core technologies
might have led to antitrust action, but in the enthusiasm
of the installation period, antitrust enforcement was
scaled back rather than intensified—yielding platform
oligopolies such as Amazon, Apple, Facebook, Google,
and Microsoft. Similarly, the outsourcing encouraged by
the Business Process model prompted the proliferation
of independent contractors and, in the face of this devel-
opment, labor regulations were ignored when they
would have barred the misclassification of so many em-
ployees. Online retailers like Amazon were allowed to
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sell into states without collecting the corresponding sales
tax. Many of the leading platform companies relied on
business models in which users were offered free access
while data about them were captured and sold to adver-
tisers
—yet privacy regulations were remarkably absent. (Eu-
rope imposed somewhat stricter privacy rules with the
General Data Protection Regulation.)
The neoliberal laissez-faire regime thus encouraged
installation; however, as we move toward deployment,
a new critical problem has emerged in the misfitbe-
tween the technology and public policy spheres. Moves
toward neoliberalism have led to extreme income in-
equality, stagnant real wages for most, and exacerbated
employment insecurity, which all limit the mass market
for new digitally enhanced consumer goods. The emer-
gence of giant oligopolies has raised urgent questions
about market power and political influence. Moreover,
the exciting possibilities of digital technologies—helping
us address critical issues in sustainability, education,
healthcare, and advance opportunities like autono-
mous automobiles—are held back by doubts among
firms and investors as to which direction deployment
will take and how fast it will unfold. Deployment is
further handicapped by lack of investment in the
requisite social and material infrastructure. In prior
revolutions, massive system-building investments in
canals, railways, electric grids, and highway systems
were key enablers of deployment. Whereas in some
countries government has played a bigger role than in
the United States in telecommunications infrastructure
(resulting, for example, in wider use of broadband at
lower cost), neither in Europe nor the United States
has government adopted a policy regime that prom-
ises to address the material and social infrastructure
required to unleash the full potential of the digital
transformation.
Faced with this critical problem in the public policy
sphere, we are today at a fork in the road. One option is
to go yet further in a laissez-faire direction: the system-
building efforts necessary for deployment could be led
by private firms. If a laissez-faire regime went further in
dismantling antitrust regulation and in further weaken-
ing labor laws protecting employees and unions, per-
haps platform oligopolies such as Amazon, Apple,
Facebook, Google, and Microsoft could create the neces-
sary systems, not as tax-funded public goods and serv-
ices but as investor-financed private ones (Rikap and
Lundvall 2020). Proponents of the neoliberal laissez-faire
view highlight the advantages of retaining initiative in
the hands of private firms and point to the dangers of
“government failure”(Winston 2006). It is not clear,
however, how this option, which seems destined to
further aggravate income inequality and economic
precariousness, would sustain effective demand for
these new digital goods and services. And the political
costs of leaving so many people “behind”are high: it
prompts the emergence of nationalist populist move-
ments, which in turn creates political havoc.
The alternative to a neoliberal laissez-faire regime
in the current technology revolution is still taking
shape but some powerful concepts are emerging
(Schot and Steinmueller 2018). Mazzucato (2021)syn-
thesizes several of these concepts in her description of
a new form of system-building regime (which we call
“proactive”), where government proactively creates
public value by taking the lead in system-building
“missions”—integrated programs that create knowl-
edge and infrastructure in the public interest, and that
guide private industry and investment in a more sus-
tainable direction. (On public value, also see O'Flynn
2007.) Mazzucato argues that reliance on private-value
creation by industry, as expressed in the neoliberal
laissez-faire regime, might lead to some important tech-
nological innovations such as autonomous vehicles,
wearable devices, or cheaper solar panels, but will
not enable us to deploy the ICT revolution across the
wider spectrum of applications in education, healthcare,
mobility, or energy systems. The creation of a compre-
hensive smart-energy system, for example, requires co-
ordinated changes in electricity, heating, buildings, and
transportation systems (Lund et al. 2017), and it is diffi-
cult to see how we can achieve this coordination and
mobilize the required investment if the effort is led by
the currently dominant oligopolies. This brings us to our
third summary proposition:
Summary Proposition 3. In the face of the current criti-
cal public policy problem, the choice is whether to strengthen
further neoliberal laissez-faire or to move toward a proactive
system-building regime. The choice between these two options
will enable and constrain choices in the organization sphere,
and in combination, these two choices will condition the fu-
ture trajectory of the digital transformation. (The contrast
between these options is presented in Table 3.)
Laissez-faire and system-building regimes are charac-
terized by a dialectical tension similar to the one we ob-
served in the organization sphere. Arguments in favor
of a proactive system-building regime are triggered by
thedysfunctionsofneoliberalisminthefaceofthepoten-
tialities of the ICT revolution. The extended period of
crisis that separates installation and deployment, which
beganwiththedot.comcrashandcontinuesunresolved,
has “unfrozen”debateoverwhichpathismorepromis-
ing. The installation period under neoliberal auspices
has brought considerable destruction in its wake—the
destructive part of Schumpeter’s“creative destruction”—
and a proactive system-building regime looks increas-
ingly attractive as a way to get to the creative part. The
counterargument is that system-building efforts could
better be led by the private sector.
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The collective choice we make in the public policy
sphere also has an impact on the organization sphere.
To illustrate this impact, consider ride hailing. On the
one hand, Uber is a prototypical “extractive”platform
based on the Business Process model. Uber’s growth in
the United States, facilitated by laissez-faire, has led to
some benefits for passengers (cost, convenience) and
drivers (access to part-time employment) but also to
considerable negative externalities (lower pay levels,
reduced support for public transportation, city conges-
tion). Uber stands as emblematic of the installation pe-
riod frenzy, driven not by a sustainable business case,
but by the zeal of investors convinced there is a pot of
gold at the end of the rainbow (Horan 2019).
On the other hand, cooperatives such as the Green
Taxi Cooperative in Denver (Colorado) and the ATX
taxi cooperative in Austin (Texas) (Schneider 2016,
Scholz 2017, Borowiak and Ji 2019) offer an alternative
closer to the Community-and-Collaboration model.
However, it is hard to see how such a management
model can generalize across the economy without a
turn away from neoliberal laissez-faire, through re-
newed antitrust enforcement and stronger regulations
ensuring workers are not inappropriately treated as
independent contractors. As long as Uber can treat
drivers as independent contractors, as long as laws
limit the collective action options available to such in-
dependent contractors, and as long as Uber can use
predatory pricing to drive out competitors, Uber will
be able to pay drivers much less than any cooperative
and keep their dominant market position. Is there a
scenario in which public policy could support the
development of a superior community-oriented alter-
native, such as a public transportation system that
embodies the flexibility and convenience of Uber? We
turn to such options in the next section.
Scenario Analysis
It follows from the preceding sections that different so-
cieties, characterized by different responses to the criti-
cal problems that have emerged in the organization
and public policy spheres, will deploy differently the
emerging technologies of the digital transformation.
Our analysis in the previous sections suggests the
basic choices available in each of the two spheres:
(1) In the organization sphere, deployment can be
guided by a Market- and Hierarchy-based Business
Process model, or alternatively by a Community-based
paradigm-balancing model (Community-and-Collabo-
ration)—either dominating networks to capture value
or empowering community to create value.
Table 3. Two Public Policy Regimes for the Digital Transformation
Laissez-faire policy regime System-building policy regime
Current alternative regimes Neoliberalism: Government supports
primacy of private-value creation by
self-organizing markets
Proactive public policy: Government leads
public-value creation through system-
building missions
Regime’s role in the technological
revolution
Buttress the autonomy of firms in the
economic playing field
Tilt the economic playing field in the
direction of the desired change
Enable private-value creation through
deregulation and privatization
Lead public-value creation to address
“grand challenges”and “grand
opportunities”
Keep political influence out of economic
activity
Exert political influence to prevent
negative externalities; subsidize positive
externalities; expand public enterprise
Historical examples of consequences
of regime
Railway mania Comprehensive US railway system
Steel mania Comprehensive US electricity system
Roaring Twenties Comprehensive automobile-based
transportation system
Theorization of the contrast between
regimes
Private interest (Hirschman 2002) Public interest (Hirschman 2002)
Disembedded economy (Polanyi 1968) Re-embedded economy (Polanyi 1968)
Key features of the current alternatives Private innovation systems that advance
the deployment of AI and other
technologies
Public innovation systems that advance the
deployment of AI and other
technologies
Technology sovereignty in the hands of
private firms
Technology sovereignty in the hands of
public institutions
Government and courts strengthen
property rights of technology firms with
respect to data and knowledge
Government and courts strengthen public
and citizen property rights with respect
to data and knowledge
Examples of contrasting concepts
supporting the current alternatives
Minimal state (Nozick 1974) Entrepreneurial state (Mazzucato 2015)
Free-market economy (Friedman 1970) Smart, green growth (Perez 2019)
New public management (Barzelay 2001) Mission economy (Mazzucato 2021)
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(2) In the public policy sphere, deployment can be
guided by a neoliberal laissez-faire regime based on
faith in self-organizing markets and the primacy of
private-value creation, or alternatively by a proactive
system-building regime where government advances
missions aimed at creating public value.
Combining the two key choices, we can identify four
scenarios for the future trajectory of the ICT revolution
and the digital transformation: development can pro-
ceed toward digital oligarchy, digital authoritarianism,
digital localism, or digital democracy. (On the value of
scenarios in management and organization research, see
Hoffman and Jennings (2021)andFarjoun(2008).) These
four scenarios represent “corner solutions”(Figure 1),
and most real-world cases will be situated between these
extremes. We outline the four scenarios, and then dis-
cuss their heuristic value.
Digital Oligarchy
Oligarchy means rule by the few, but we follow Aristot-
le and use it to refer to rule by the wealthy few (Miller
2017). Digital oligarchy is a scenario that combines a
neoliberal laissez-faire regime with a Business Process
management model. Government plays little active role
in stimulating technology development or deployment,
leaving it to market forces—and to digital oligopolies as
they emerge through market competition—to set the
direction of the digital transformation.
The United States has moved in this direction since the
1970s. Over this same period, and partly encouraged by
this shift in regime, the Business Process model diffused
across U.S. industry. This diffusion was fastest in the
new core industries of the ICT revolution. These new
conditions, characterized by a winner-takes-all logic en-
couraged by the strong network effects of the ICT revolu-
tion, were fertile ground for the rise of oligopolists such
as Amazon, Apple, Facebook, Google, and Microsoft.
These firms’market and political power enabled them
to buy innovative technology startups (e.g., Amazon
acquired Zoox; Apple, Siri; Facebook, Instagram; Google,
DeepMind; and Microsoft, Skype) and to integrate them
into their ever more powerful platform empires (Umeh
2016, Radziwill 2018). As a consequence, emerging tech-
nologies are increasingly shaped by these corporate
giants. In this scenario, these giants’property rights
preempt national data- and technology-sovereignty.
Surveillance—extracting and selling data culled from
users in ways kept secret from those users—is a key
source of profit(Zuboff2019). Even free-speech rights be-
come a matter of private corporate policy rather than
public policy, as platforms like Facebook, Twitter, and
YouTube decide who and what to censor.
Digital Authoritarianism
The digital authoritarianism scenario combines a proac-
tive system-building regime with a Business Process
management model. Here government plays an active
role in investing in technology development and de-
ployment, and thus creating public value—albeit public
value as understood by an unaccountable governing
elite (Polyakova and Meserole 2019, Khalil 2020). Hierar-
chy functions as the key organizing principle within
government and between government on the one hand
and private enterprises and citizens on the other. Com-
munity is suppressed—social networks are restricted—
because it might threaten government control. Deploy-
ment of digital technologies is steered in a way that
keeps technology sovereignty in the hands of a powerful
state elite and equips that elite with effective systems for
surveillance and control. Surveillance is legitimized by
a low rate of criminality, by nationalist appeals, and/or
by aggregate economic growth. Authoritarian rule has
performed rather well in accelerating economic growth
in “developing”economies—witness China (Yang 2006)
and Singapore (Verweij and Pelizzo 2009).
Digital Localism
Digital localism combines a laissez-faire public policy re-
gime at the national level with a variety of management
models at the local level, yielding a patchwork pattern
where the Community-and-Collaboration model pre-
vails in some jurisdictions and Business Process in others.
With a laissez-faire public policy, central government
plays little role in shaping the direction of deployment.
We might expect this to lead generally to digital oli-
garchy; however, in some local contexts, alliances of
actors might push successfully for the resolution of ur-
gent local problems, shaping the decisions of local ju-
risdictions. Local jurisdictions might opt for policies
more supportive of the Community-and-Collaboration
alternative, and they might be powerful enough to
block the entry of giant corporations and to mobilize
citizens and local businesses toward community
wealth building. (Hess and Gottlieb 2009, Dubb 2016).
Deployment of digital technologies can be organized
here to ensure a certain level of technology sovereignty
for the local community, as in Barcelona for example
(Eizaguirre et al. 2017). Whereas change at the local
level may be easier, the digital localism scenario fore-
goes the potential benefits of scale and interconnectivi-
ty at the national level.
Digital Democracy
A digital democracy scenario combines a proactive
system-building regime with a Community-and-
Collaboration management model. In contrast to digi-
tal oligarchy, government here not only encourages
private-sector initiative and responds energetically to
the resulting negative social and environment exter-
nalities but also shapes the direction of technology de-
velopment and deployment in a purposeful way. In
contrast to digital localism, deployment activates all
Bodroˇ
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Organization Science, Articles in Advance, pp. 1–21, © 2021 The Author(s) 15
levels of government and society, harnessing network
effects and other positive externalities on a national lev-
el. In contrast to digital authoritarianism, here deploy-
ment is steered in a way that strengthens collaboration
and enriches and activates community by widening
and deepening democratic participation. The formal
systems of government in this scenario play an enabling
rather than coercive role, fostering rather than suppress-
ing community initiative. Whereas an authoritarian re-
gime is fearful of the political risks of community, a
democratic one would activate community in neighbor-
hoods and organizations and in relations between the
public and government. Technology sovereignty would
be in the hands of citizens.
Notwithstanding the fact that no major country has
thus far embraced a digital democracy scenario, macro-
Schumpeterians like Perez (2009) and Mazzucato (2018)
argue that this is the most likely path to deployment
success, given the historical record of previous re-
volutions, where deployment was stimulated by the
combination of a system-building policy regime and a
paradigm-balancing management model. The other
three scenarios seem less likely to tap the digital trans-
formation’sfullpotential.
Heuristic Value of the Scenarios
Most real-world cases will be situated between the
extremes represented by these four scenarios (as pre-
sented in Figure 1). Therefore let us now show the heu-
ristic value of this scenario matrix as a map for analyzing
concrete cases.
First, Figure 1could be used to locate different coun-
tries or supranational unions and trace their zig-zag
trajectories. A comprehensive analysis of any specific
country would require a paper of it its own, but some
observations might be useful.
5
The United States has
been the global leader in the installation period of the
ICT revolution: the combination of a dominant Business
Process model and a neoliberal laissez-faire regime has
strengthened the position of the giant U.S.-based plat-
form firms. It is not clear, however, that this digital oli-
garchy scenario will allow the United States to retain
leadership as we move into deployment, given the re-
treat of both the federal government and the private sec-
tor from R&D investment and the escalating inequalities
in income and wealth (Soskice 2020). We should note
that the United States is not a pure case of laissez-faire:
the defense and security domains, for example, seem to
operate under a more system-building public policy re-
gime and are largely exempt from budget cuts.
China too has relied mainly on the Business Process
model but has married that with a system-building
policy regime. Government control over the economy
has become considerably more selective since the re-
forms of the late 1980s and early 1990s, offering a
more laissez-faire regime in important sectors of the
economy; this has yielded giant digital oligopolies of
its own (e.g., Tencent and Alibaba) operating under
the umbrella of digital authoritarianism (Lundvall
and Rikap 2022). It remains to be seen whether that
mix is stable or whether the growing power of private
enterprise will threaten the control of the Communist
Party (Csanadi 2016).
The European Union seems to be aiming for
middle-way solutions somewhere between digital oli-
garchy and localism. However, such a middle way
Figure 1. (Color online) Four Scenarios for the Digital Transformation
Dominance of proactive system-building
public policy regime
Dominance of
Business Process
management
model
Digital
authoritarianism
Digital
democracy
Dominance of
Community-and-
Collaboration
management model
Digital
oligarchy
Digital
localism
Dominance of neoliberal laissez-faire
public policy regime
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16 Organization Science, Articles in Advance, pp. 1–21, © 2021 The Author(s)
has encountered roadblocks, generating neither glob-
ally competitive tech firms nor dominant public plat-
form alternatives. In the interim, smaller innovative
tech firms in Europe are assimilated into the U.S. tech
platform empires, such as in the case of Google’s ac-
quisition of British DeepMind (Rikap and Lundvall
2020). Efforts to find a middle way might risk getting
“stuck in the middle.”
Zooming in from the country level to smaller units
of analysis, we can also use this map to explore empir-
ically the effects of alternative management models
and public policy regimes on specific sectors and re-
gions that may operate under different models and re-
gimes, as noted previously for the U.S. civilian versus
defense sectors or as noted by Kattel and Mergel
(2019) for Estonia’s ICT sector versus other sectors.
We could also use the four scenarios as a heuristic to
inform meso-level research (reviewed by Ahuja et al.
2008), to understand, for example, the political strate-
gies of organizations. The tech giants have actively
lobbied for a laissez-faire regime in the United States
and in Europe (Brannon 2019, Corporate Europe Obser-
vatory 2020). Given that China is the only country
where major competitors to these giants have emerged,
it would seem that their strategies have been largely
successful. What then are the prospects for platform co-
operatives? Taxi cooperatives have encountered enor-
mous difficulties when trying to “share the road”with
Uber (Schneider 2016,Scholz2017,BorowiakandJi
2019). As noted earlier, under the prevailing neoliberal
laissez-faire regime, Uber undermines the cooperatives’
competitive viability by offering customers unbeatable
prices. Our scenario matrix suggests that where inter-
ests diverge so fundamentally, the most effective strate-
gic choice for taxi cooperatives might be to seek out
arrangements with local governments to pursue a digi-
tal localism scenario, with rules of the game that favor
small cooperatives.
Conclusion
This paper aimed to develop a conceptual framework
for understanding and bounding the uncertainty re-
garding the future trajectory of the digital transforma-
tion. To that end, we expanded Schumpeter’stheoryof
technological revolutions and the macro-Schumpeterian
account of prior revolutions, and we explored how the
trajectory of those revolutions was shaped by the emer-
gence of critical problems and competing solutions in
the triple system of technology, organization, and pub-
lic policy. Given the advanced state of technology to-
day, the future of the digital transformation hinges on
choices to be made between the competing solutions in
the organization and public policy spheres: in the for-
mer, the choice appears to be between the currently
dominant Business Process model or an emerging
Community-and-Collaboration model, and in the latter,
between the currently dominant neoliberal laissez-faire
regime or an emerging proactive system-building alter-
native. The conjunction of these two choices suggested
four scenarios for the future trajectory of the digital
transformation: digital oligarchy, digital authoritarian-
ism, digital localism, and digital democracy. Given the
uncertain evolution of management models and public
policy regimes, it is easy to understand the current
deep uncertainty about the future trajectory of the digi-
tal transformation. In the United States, Zuboff (2019)
argues that we are headed toward “surveillance capital-
ism”and a digital oligarchy scenario. However, de-
bate—and political struggle—continue in both public
policy and organization spheres: the die is not cast.
We hope that the framework we have advanced
here and the conclusion to which it leads us will en-
courage future research on the forces shaping the
choices we face. This paper focuses on the nature of
these choices, but we need to understand who is do-
ing the choosing and how. Future research should
aim to identify the specific actors involved in the
digital transformation and how their power and inter-
actions both shape and are shaped by choices in man-
agement models and public policy. We should explore
the competition and cooperation between the various
groups and individuals involved—competing firms
and sectors, innovative practitioners, academic theo-
rists, gurus popular in the media, consultancy firms,
institutional entrepreneurs in government agencies,
unions, and social movements. They all played roles
in previous revolutions (Bodroˇ
zi´
c2008) and will
surely play important roles in this one. What net-
works do these actors form and how do these
networks shape the course of this technological revo-
lution? Which actors promote and which resist the
broadening of government’s role and the transforma-
tion of management models? How do these struggles
unfold over time? What are the mechanisms underly-
ing the persistence of inherited management models
and policy regimes? Political-economy theory, social
movement theory, and neo-institutionalist theory
might provide powerful conceptual tools for this
kind of analysis.
Whether the digital transformation serves the needs
of the people and the planet, or, alternatively, serves to
reinforce structures of inequality and domination will
depend on the choices and actions of citizens, innova-
tors, movement activists, and policy makers. We can
choose to create and implement digital tools, manage-
ment practices, and public policies to support surveil-
lance of activists, to enable corporate censorship, or to
empower local communities, or even to reinvigorate
democracy. Management and organization scholars
have a role to play in informing these choices.
Bodroˇ
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Organization Science, Articles in Advance, pp. 1–21, © 2021 The Author(s) 17
Acknowledgments
The authors thank the Special Issue senior editors, especially
Diane Bailey and Samer Faraj, and the three anonymous re-
viewers for insightful and constructive feedback throughout
the review process. The paper has also benefited from com-
ments by Stan Karanasios, Ann Majchrzak, Carlota Perez,
Florenta Teodoridis, Charles Umney, Eero Vaara, the seminar
participants of the 2019 Special Issue Paper Development
Workshop at the University of California, Santa Barbara, of
the Organizations & Strategy working group at the
University of Southern California, and of the European
Group for Organizational Studies 2019 Subtheme “Historical-
Evolutionary Organization Studies: Understanding the Past
to Shape the Future.”The authors also thank Stan Karanasios
for help in compiling the timeline in Table 1.
Endnotes
1
On the nature and importance of stylized facts in scholarship, see
Helfat (2007, p. 187), who characterizes them as “observations that
have been made in so many contexts that they are widely under-
stood to be empirical truths, to which theories must fit.”
2
Theoretically, we can connect the notion of a critical problem to
the concept of reverse salient: “A salient is a protrusion in a geomet-
ric figure, a line of battle, or an expanding weather front. As techno-
logical systems expand, reverse salients develop. Reverse salients
are components in the system that have fallen behind or are out of
phase with the others”(Hughes 1987,p.66–67). We build on Hugh-
es’s observation that reverse salients have often emerged outside the
technology sphere—in the constraints of prevailing organizational
forms or limited access to finance, for example.
3
The Community-and-Collaboration model transcends the more
common concept of “community of practice”: the latter typically re-
fers to communities that share a common discipline and socialization
informing their occupational practice. Such a bounded form of com-
munity would be less adequate to bridge the diverse occupations and
perspectives that need to be recombined in the Network paradigm.
4
“Neoliberalism is a theory of political economic practices propos-
ing that human well-being can best be advanced by the maximiza-
tion of entrepreneurial freedoms within an institutional framework
characterized by private property rights, individual liberty, unen-
cumbered markets, and free trade”(Harvey 2007b, p. 22).
5
During technological revolutions, the trajectories of “leading
countries”and countries that are “catching up”differ. For a com-
parative analysis of the evolution of management models in some
countries that were catching up during the prior two technological
revolutions, see Guillen (1994). For a discussion of contemporary
catching-up strategies, see Whittaker et al. (2020).
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Zlatko Bodro ˇ
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cis an associate professor in technology, or-
ganization, and sustainability at the University of Leeds. He
received his PhD from the University of Helsinki. His research
interests include the interaction of technology, organization,
and public policy, with a particular focus on the digital trans-
formation and the transition to a sustainable society.
Paul S. Adler holds the Harold Quinton chair in business
policy at the University of Southern California. He grew up
in Australia, received his PhD in economics and manage-
ment in France, and moved to the United States in 1981. His
work focuses on the management of complex organizations
and business/government/society interactions.
Bodroˇ
zi´
c and Adler: Alternative Futures for Digital Transformation
Organization Science, Articles in Advance, pp. 1–21, © 2021 The Author(s) 21
