Beyond the Factory Paradigm: Digital Nomadism and the Digital Future(s) of Knowledge Work Post-COVID-19

Abstract

What are the potential futures of knowledge work, given its transformation into almost exclusively digital work during the COVID-19 pandemic crisis? Our ongoing research program on digital nomadism informs a Hegelian dialectical analysis and an envisioning of the future(s) of knowledge work. We contrast the Factory paradigm of work (thesis), exemplified by the “ideal type” of the 9-to-5 corporate worker, with the Hypermobility paradigm of work (antithesis), exemplified by the ideal type of the digital nomad. Reflecting on this contrast, we envision the possible digital futures of knowledge work as a continuous spectrum, ranging from a future based on the Digital Taylorism paradigm of work to a future based on the Worker Autonomy paradigm of work. These futures are discussed in terms of different approaches to organizing work, working with technology, delineating work/life boundaries, and provisioning the social safety net. IS researchers are uniquely positioned to perform research and inform decision-making in all these areas, and thus make a difference in determining whether the future we end up with more closely resembles Digital Taylorism or the Worker Autonomy vision.

Full text

ISSN 1536-9323
Journal of the Association for Information Systems (2020) 21(6), 1379-1401
doi: 10.17705/1jais.00641
EDITORIAL
1379
Beyond the Factory Paradigm: Digital Nomadism and the
Digital Future(s) of Knowledge Work Post-COVID-19
Blair Wang1, Daniel Schlagwein2, Dubravka Cecez-Kecmanovic3, Michael C. Cahalane4
1University of New South Wales, Australia, blair.wang@unsw.edu.au
2University of Sydney, Australia, schlagwein@sydney.edu.au
3University of New South Wales, Australia, dubravka@unsw.edu.au
4University of New South Wales, Australia, m.cahalane@unsw.edu.au
Abstract
What are the potential futures of knowledge work, given its transformation into almost exclusively
digital work during the COVID-19 pandemic crisis? Our ongoing research program on digital
nomadism informs a Hegelian dialectical analysis and an envisioning of the future(s) of knowledge
work. We contrast the Factory paradigm of work (thesis), exemplified by the “ideal type” of the 9-
to-5 corporate worker, with the Hypermobility paradigm of work (antithesis), exemplified by the
ideal type of the digital nomad. Reflecting on this contrast, we envision the possible digital futures
of knowledge work as a continuous spectrum, ranging from a future based on the Digital Taylorism
paradigm of work to a future based on the Worker Autonomy paradigm of work. These futures are
discussed in terms of different approaches to organizing work, working with technology, delineating
work/life boundaries, and provisioning the social safety net. IS researchers are uniquely positioned
to perform research and inform decision-making in all these areas, and thus make a difference in
determining whether the future we end up with more closely resembles Digital Taylorism or the
Worker Autonomy vision.
Keywords: Digital Work, Remote Work, Knowledge Work, Digital Futures, COVID-19, Future of
Work, Factory paradigm, Digital Nomadism, Hypermobility, Dialectics
Dorothy E. Leidner was the accepting senior editor. This paper was submitted on May 20, 2020 and underwent one
revision.
1 Paradigms of Knowledge Work
The need for informed exposition of the potential futures
of knowledge work has never been as urgent as it is now
with substantial changes underway. Knowledge workers,
in general, are people whose jobs entail “thinking for a
living … [and] the creation, distribution or application of
knowledge” (Davenport, 2005, p. 9), such as scholars,
librarians, artists, scientists, engineers, lawyers, bankers,
etc. (Davenport, 2005; Pyöriä, 2005). In the wake of
COVID-19, the conventional norms and practices of
knowledge work have suddenly shifted toward digitally
conducted work. We may be observing the dawn of a new
era of knowledge work. This is a world for which we have
no playbook (Chik & Benson, 2020) since much of pre-
COVID-19 discourse and research is inherently backward
looking. Given this paucity of informed, forward-looking
analysis, we examine the potential digital future(s) of
knowledge work, following its transformation into almost
exclusively digital work during the COVID-19 pandemic.
We envision what post-COVID-19 knowledge work will
look like by reflecting on tendencies and trajectories that
are already visible in the present. History and current
research, including our own research program on digital
nomadism, inform our analysis of knowledge work trends
during and after the COVID-19 pandemic.

Beyond the Factory Paradigm
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For many past decades, a way of working centered
around what we call the Factory paradigm has been
the widely accepted understanding of “work” in
society. The Factory paradigm is defined by the rigid
norms and arrangements developed to optimize
manufacturing processes during the Industrial
Revolution. These norms and arrangements were
notably formalized in the Taylorist principles of
increasing economic output by decomposing work into
simple parts and measuring each part using
quantitative performance metrics as a basis of control
(Taylor, 1911). The popularization of Taylorist
principles has entrenched scientific management into
our collective consciousness archetypes such as the 9-
to-5 workday of the typical corporate office job. Thus,
the current norms of knowledge work are,
problematically, modeled on factory work, despite the
substantial differences between the two. Peter Drucker
argued almost two decades ago that we ought to move
beyond these standards and into better practices for
knowledge work, cautioning, at the same time, that “it
will predictably take a good many years before we
have worked these out” (Drucker, 2002, p. 8).
Drucker’s day may have come.
The proliferation of the internet and digital
technologies (Berger, Denner, & Roeglinger, 2018)
has amplified such critique of the Factory paradigm of
knowledge work (Moravec, 2013; Golden &
Gajendran, 2018). It can be argued that all forms of
work currently include aspects of digital work, directly
or indirectly (Orlikowski & Scott, 2016), yet
knowledge work, in particular, can be performed
entirely digitally and remotely over the internet with
relative ease. Remote digital work (or telework) is
therefore increasingly feasible (Boell, Cecez-
Kecmanovic, & Campbell, 2016), making commuting
to the office or factory unnecessary. This challenge to
the Factory paradigm has been brought to the forefront
of public consciousness during the COVID-19
pandemic. During the COVID-19 pandemic,
governments around the world have declared public
health emergencies and mandated societal lockdowns.
To comply with these lockdowns, knowledge workers
all around the world have been requested to vacate
corporate offices and work from home as remote
digital workers (Hamzelou, 2020). This mass departure
from ways of working grounded in the Factory
paradigm has therefore suddenly prompted knowledge
workers to question what “going to work” means. “The
ultimate work-from-home experiment” (Liang, 2020,
p. 1) seems primed for propelling a new paradigm of
work (Parthasarathy, 2020). By looking beyond the
Factory paradigm, we join the ongoing debate and ask:
What are the potential future(s) of knowledge work,
given its transformation into almost exclusively digital
work during the COVID-19 pandemic? How could IS
research help to navigate these futures?
To envision what this post-COVID-19 world might
look like, we contrast the Factory paradigm with its
opposite, what we call the Hypermobility paradigm
(Green, 2020; Cook, 2020; Mancinelli, 2020). The
Hypermobility paradigm entails the large-scale
realization of various mobilities—a concept used in the
sociology literature (Sheller & Urry, 2006). We
consider the case of “digital nomadism” as an
archetypical exemplar of hypermobility (Green, 2020;
Cook, 2020; Mancinelli, 2020). Digital nomadism
emerged in the 2010s, with knowledge workers
engaging in a new lifestyle of leisure travel enabled by
digital work, allowing them to generate income while
traveling as a way of life (Schlagwein, 2017;
Schlagwein, 2018). The idealized view of a digital
nomad is that of a contemporary knowledge worker—
travel blog, web designer, affiliate marketer, social
media influencer—sitting on a tropical beach or in a
trendy coworking space, working on a laptop,
producing work for clients while admiring the tropical
scenery (Cook, 2020). Digital nomadism seems to
encompass the antithesis of the factory-corporate
model of knowledge work, a possible paradigm shift
of the knowledge work sectors (Kuhn, 1962; Riemer &
Johnston, 2019).
In this editorial, we take a dialectical approach toward
envisioning the future of knowledge work. We
consider the Hypermobility paradigm as an antithetical
challenger to the current Factory paradigm of
knowledge work. The dialectical reasoning process is
outlined in detail in the following section. At its core,
it entails a detailed understanding of the incumbent
Factory paradigm (the “thesis”) and contrasting it with
its challenger, the Hypermobility paradigm (the
“antithesis”). The dialectical resolution of tensions
between the thesis and the antithesis results in the
synthesis, envisioning a spectrum of possible futures
of knowledge work by focusing on two extreme yet
plausible new paradigms of knowledge work. We call
these potential future paradigms Digital Taylorism and
Worker Autonomy. Our envisioning highlights that the
impending decisions of individuals, organizations, and
governments are consequential for moving us
collectively closer toward one of these two future
scenarios. IS researchers are uniquely positioned to
inform these decisions—the making of these futures—
through research and commentary.
2 Dialectical Reasoning for
Envisioning the Future
“Prediction is very difficult, especially about the
future,” according to the famous saying variously
attributed to Niels Bohr and Mark Twain. Nonetheless,
we endeavor to envision the post-COVID-19 digital
future(s) of knowledge work by building on a range of
philosophical and theoretical concepts briefly
discussed in this section.

Journal of the Association for Information Systems
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2.1 Dialectical Reasoning and Multiple
Futures
First, we use Hegelian dialectics as a method of
scholarly reasoning. This form of reasoning is based on
Hegel’s analytical observation of a forward
progression of human history based on thesis–
antithesis–synthesis (Maybee, 2019; Van de Ven &
Poole, 1995). Hegelian dialectics has informed
scholars from Marx to Habermas, as well as IS
research (e.g., Karjalainen, Sarker, & Siponen, 2019;
Gibbs, Rozaidi, & Eisenberg, 2013). We use Hegelian
dialectics as a model to reason “forward” in time.
The outcome of our Hegelian dialectical reasoning
approach is multiple plausible futures; we resist the
allure of predicting a single future (Shaw 1979). The
concept of futures (plural) comes from the field of
future studies and builds on the comparative analysis
of both actualities (what currently is) and potentialities
(what could be) (Chiasson et al. 2018; Feenberg 2005).
This follows a metaphysical view in which the future
is not maktoob (Arabic: “already written [in the book
of God]”) but instead “created through choice and
action,” nondeterministic but not random, manmade
within the space of the “assumed fundamental aspects
of human, social and/or physical science principles”
(Hovorka & Peter, 2018, p. 166).
The dialectical argument draws from existing,
conflicting paradigms of knowledge work (thesis and
antithesis) and current tendencies, including those
emerging from the COVID-19 crisis, to arrive at two
future extreme scenarios that demarcate the range of
possible futures (synthesis). In other words, there is a
multitude of possible futures between the two
extremes. Considering the extremes may help us to
outline the full space of potentialities and hopefully
inform our choices, as they will determine the actual
future that we will end up with.
2.2 Paradigms and Ideal Types
To conceptualize the dominant thinking found across
the thesis, antithesis, and the range of futures
constituting the synthesis, we draw on Kuhn’s notion
of paradigm. Based on the analysis of the actual history
of the natural sciences, Kuhn defined paradigms as the
incommensurable sets of scientific standards and ways
of looking at the world in particular eras (Kuhn, 1962).
Kuhn’s work caused a metaphorical earthquake in the
philosophy of science because that field had previously
entertained a naive “accumulation of knowledge,
steady progression” view of science. Kuhn’s concept
of paradigms has previously been referred to in the
“paradigm wars” in IS (e.g., between interpretivism
and positivism) (Mingers, 2004; Hassan & Mingers,
2018). This concept has also been used to refer to
transitions between incompatible ways of thinking
beyond science such as the seismic shift from physical
media to digital/streaming models in the music
industry (Riemer & Johnston, 2019). Here, we are
taking this second, wider view on paradigms:
fundamental shifts in ways of thinking in any area of
society (in science or elsewhere).
Finally, in order to exemplify the paradigms across
thesis, antithesis, and synthesis, we also draw on the
Weberian concept of the “ideal type” (Idealtypus). An
ideal type draws attention to particular social
phenomena by articulating them as an abstract analytic
archetype, accentuating certain characteristics,
elements, and points of view (Weber, 1904). The
“idea” of the ideal type refers to the stylized, archetype
representing an idea (it does not refer to the “best” or
“optimal,” as is sometimes misunderstood). The 9-to-
5 corporate worker can, for example, be seen as an
ideal type (archetype, exemplar) of the Factory
paradigm of knowledge work. Similarly, the digital
nomad can be seen as an ideal type of the
Hypermobility paradigm (D’Andrea, 2006). For the
two futures outlined below, we treat the cyborg
(Haraway, 1987) as an ideal-type worker of the Digital
Taylorism paradigm, while the knowmad (Moravec,
2013) is an ideal type worker of the Worker Autonomy
paradigm.
We draw on Weick’s fundamental processes of work
(Weick, 1974; Puranam, Alexy, & Reitzig, 2014) to
coherently describe the paradigms and highlight the
dialectical tensions and clashes between them. Puranam
et al. (2014) developed four processes for assessing new
(digital) ways of organizing: task allocation, reward
distribution, information provision, and task division.
However, we set our focus slightly wider, beyond this
operational view. For the digital future(s) of knowledge
work, we consider: (1) organizing work, i.e., how task
allocation and task division are organized; (2) working
with technology, i.e., the role that technology plays in
organizing and managing work; (3) delineating
work/life boundaries, i.e., how work and nonwork are
related; and (4) provisioning the social safety net, i.e.,
how the responsibility for social safety (e.g., health care,
pensions) is organized among workers, organizations,
and society. The framework of dialectical reasoning
underlying our argument is summarized in Figure 1.
Figure 1 shows the fundamental thesis–antithesis–
synthesis structure of dialectical reasoning (and historical
progression). Figure 1 shows the role of the COVID-19
pandemic as a catalyst that accelerates the dialectical
tensions or clashes between the paradigms. COVID-19
hence accelerates the historical progression toward the
range of possible futures. The future may fall anywhere
between the two extremes of Digital Taylorism and the
Worker Autonomy paradigms of knowledge work.
COVID-19 has moved the timeline of digital and
knowledge work forward by years or decades—the
future may thus come much sooner than expected.

Beyond the Factory Paradigm
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Figure 1. Conceptual Framework for Dialectical Reasoning
3 Thesis: The Factory Paradigm
of Knowledge Work
This section analyses the dominant Factory paradigm
of knowledge work, exemplified by the 9-to-5
corporate worker ideal type. This paradigm is
described according to the above four fundamental
processes underlying work. In our critical assessment,
this paradigm has shortcomings given the current
circumstances and the nature of knowledge work.
In a nutshell, the typical 9-5 corporate-worker
environment, featuring a downtown corporate office
organized in cubicles, is governed by the norms of the
Factory paradigm, using a Taylorist centralized control
approach to organizing work, which is a mechanizing
and standardizing approach to working with
technology, a workplace concentration approach to
delineating work/life boundaries, and an
institutionalization of the “Fordist bundle” for the
provisioning of a basic social safety net. We explore
these characteristics in more detail below.
3.1 Defining Characteristics
3.1.1 Organizing Work: Taylorist
Centralized Control
In the Factory paradigm, work is organized according
to the management principles that emerged in the
Industrial Revolution (around 1800). These were
formalized and summarized in the influential work of
Frederick Taylor (Taylor, 1911). Taylor’s theorization
of science-based management formed the foundations
of what is now referred to as Taylorism (Leijonhufvud,
1984; Littler, 1978). Taylorism promotes guaranteed
levels of economic output, delivered at high levels of
efficiency, achieved through the decomposition of
complex work activities into simple, routine, and
standardized tasks. Taylorism entails surveillance and
the detailed measurement of the execution of tasks and
compensation of workers based on their output.
Planning and control are largely in the hands of
designated workplace authorities at the top of the
organizational hierarchy. Furthermore, in Taylorism,
planning and control assume accurate and complete
information about the environment and about the
production process itself. In modern knowledge work,
Taylorist centralized control is applied in more subtle
and implicit forms. For instance, it involves underlying

Journal of the Association for Information Systems
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influential concepts such as “management by
objectives” or “balanced scorecard” (Dinesh &
Palmer, 1998). Taylorism in modern knowledge work
may also involve packaging centralized control as
seemingly “fun” company social events and
regimented “playful” corporate culture (Fleming,
Bolton, & Sturdy, 2009). The mindset underlying
Taylorist centralized control is illustrated in the
following quote:
The timesheets are particularly important
to junior accountants because the
chargeable time recorded is used to
calculate the individual accountant’s
utilization figures and utilization targets.
These targets form part of their
performance measures and a failure to meet
the target (or having a utilization below
your peers) could have negative
consequences. (Ladva & Andrew, 2014, p.
642).
3.1.2 Working with Technology:
Mechanizing and Standardizing
In the Factory paradigm, work is centered around
technology (historically, production machinery) that
executes tasks based on precise measurement and
standardization. Previously, imprecise artisan craft
handiwork was replaced by precise production
schedules, movements of materials and workers, and
operations of factory machines. The role of the human
was merely to fill in the gaps between machines’
operations, based on a highly specialized, repetitive,
division of labor, typically on an assembly line that
produced goods from start to finish. These concepts are
famously presented in Adam Smith’s “Pin-Maker
Parable” in The Wealth of Nations, in which ten
workers can produce 48,000 pins on an assembly line
of subdivided labor, but not a single pin individually
(Smith, 1776). In modern knowledge work,
mechanization and standardization is visible in
technologies such as enterprise resource planning
(ERP) systems, which mechanize and standardize the
collection and processing of business data to inform
key performance indicators (KPIs), such as in the
context of business process reengineering/
management (Davenport & Short, 1990; Lingyu et al.,
2010; Selmeci et al., 2012). More recently,
mechanization and standardization have become
visible in people analytics systems. People analytics
systems apply algorithmic techniques to workforce
management in ways that are ethically problematic
because they lack transparency in processes (opacity),
oversimplify human behavior (datafication), or
manipulate people to act against their own ethical
judgment or intuition (nudging) (Gal, Jensen, & Stein,
2020). Overall, the endurance of the Factory
paradigm’s mechanization and standardization in the
knowledge economy shows how the “technological
structures of industrial production enforce and
reproduce the social structures of industrial society”
(Rogers, 2008, p. 94).
3.1.3 Delineating Work/Life Boundaries:
Workplace Concentration
In the Industrial Revolution, work became
concentrated in factories because of the invention of
steam engines and other heavy machinery that could
not be transported to workers’ homes—workers had to
go to the machinery. The most efficient arrangement
was to concentrate work around these machines in
factories (Nanda & Browne, 1977). Factories then
tended to aggregate in geographical areas (Mokyr,
2001). Furthermore, the assembly line model
(introduced by Ford and others) required workers to
gather at specific places at specific times to execute
synchronized tasks. This workplace concentration
(Mokyr, 2001) spatially organized work and workers
around industrial equipment. In corporate knowledge
work, workplace concentration has only been
minimally transformed and generally takes the form of
high-rise office buildings in urban centers.
Concentration still occurs in geographical formations
ranging from specific streets within a city (e.g., Wall
Street) to entire areas (e.g., Silicon Valley). Workplace
concentration also necessitates that workers live near
their place of work (a Sydney office worker cannot
reasonably live in Tokyo). As workers often cannot
afford housing in city centers, they thus often commute
from suburbs to urban centers for work. The working
hours are typically standardized to 9-to-5 workdays in
40-hour workweeks (Nanda & Browne, 1977).
3.1.4 Provisioning the Social Safety Net:
Institutionalizing the Fordist Bundle
The Factory paradigm and the Taylorist regimentation
of workers’ lives into repetitive and alienating work,
combined with the increasing power imbalance and
wealth inequalities between factory owners
(capitalists, owners of the means of production) and
workers (doing the actual working), has attracted
compelling criticism, notably by Karl Marx in Das
Kapital (Marx, 1867). Marx famously predicted (and
inspired) socialism as an alternative to capitalism,
offering a social safety net provided by the state.
Marx’s ideas led to a number of socialist transitions,
via democratic vote or revolutions. Yet, today, most
nations are either decidedly free-market (capitalist)
economies (e.g., USA) or are “socialist” by name only
and increasingly resemble free-market economies
(e.g., China). In free-market economies, the primary
social safety net is the Fordist bundle (Vitaud, 2018;
Vitaud, 2019). The Fordist bundle is named after
Henry Ford, who, in 1926, introduced the weekend and
the 40-hour week to all his workers to improve
workers’ well-being:

Beyond the Factory Paradigm
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We have decided upon and at once put into
effect through all the branches of our
industries the five-day week. Hereafter
there will be no more work with us on
Saturdays and Sundays. These will be free
days, but the men, according to merit, will
receive the same pay equivalent as for a full
six-day week. A day will continue to be eight
hours, with no overtime … in the old days,
before we had management and power, a
man had to work through a long day in
order to get a bare living. Now the long day
would retard both production and
consumption … within a comparatively
short time I believe the practice will be so
general in industry that it be made
universal. (Henry Ford, quoted in Crowther,
1926, pp. 613-616)
The Fordist bundle refers to social institutions
providing security for workers (e.g., stable work
contracts, paid leave for illness and parenthood, health
insurance). Workers achieved these social benefits
through a mixture of negotiation with owners as well
as political action (e.g., voting for worker parties,
unionization, etc.) (Kasmir, 1999).
3.2 Critical Assessment
The Factory paradigm’s key characteristics underpin
the often taken-for-granted understanding of “(going
to) work” in modern society. This has serious
implications for knowledge work. Knowledge work is
often more creative than mechanical assembly-line
work. Taylorist centralized control, as an approach to
organizing work, has been critiqued as ineffective for
creative thinking (Brown & Lauder, 2010). In
knowledge worker settings, Taylorism tends to reduce
rather than improve knowledge worker performance
(Parker, 1998) because of its disregard for individual
privacy and its outdated assumptions of clearly
defined, highly standardized tasks (Langfred &
Rockmann, 2016; Bernstein, 2012).
Mechanizing and standardizing as an approach to
working with technology has been identified as
unhelpful for knowledge work for similar reasons
(Moravec, 2013). Modern technology conceptually
promises to fully automate work, taking over any
mundane tasks (e.g., Wei & Peters, 2018), hence
freeing up human workers. Yet Ford’s 40-hour
workweek has become a myth. Longer hours are
common for knowledge workers competing for jobs
and careers, and 90-120-hour workweeks have been
reported as a “badge of honor” (Hewlett & Luce, 2006,
p. 49) in certain industries (e.g., banking). Emails on
weekends and after-hours work have become accepted,
common, and even expected. Karoshi (Japanese for
“death by overwork”) has been recognized as an
“international work (health) hazard” (Li, 2016, p. 139)
and the negative impact of long work hours on
work/life balance have been widely recognized
(Fleetwood, 2007).
Workplace concentration emerged based on the
constraints imposed by industrial machinery; however,
this seems no longer relevant for knowledge work in
the digital age. Mobile computing offers opportunities
for spatially and temporally flexible working
arrangements (Golden & Gajendran, 2018).
Nevertheless, commuting to a physical office
continues to be widely practiced, leading to countless
hours spent in grinding rush-hour traffic, vastly
overpriced downtown real estate, and significant child
care struggles for families, among other issues.
Finally, institutionalizing the Fordist bundle as an
approach to provisioning the social safety net has
gradually been eroded and seems even dated. While an
overall improvement of society through efficient
markets and production had been assumed (by leading
economists post-WW2), empirically, such gains have
seemingly mostly propelled the so-called “one-
percenters,” and wealth distribution has become
increasingly unequal (Piketty, 2013). The social safety
net has been substantially diminished in tandem with
decreasing unionization, workplace regulations, and
full-time employment (Vitaud, 2019; Vitaud, 2018).
Although the loss of such protections is not uniform
across nations, the Fordist bundle has been widely
eroded, leading to an “acceleration in the operation of
disciplinary neoliberalism” (Dukelow & Kennett,
2018, p. 483).
Given the many shortcomings of the Factory paradigm,
one might question whether it represents the best
possible system for knowledge work and workers.
Indeed, the paradigm’s constituent components were
never designed for knowledge work and digital work
and largely exist as historical artifacts. The Factory
paradigm and the 9-to-5 corporate worker ideal type
stand in stark contrast to the promising new paradigm
of hypermobility and digital nomadism.
4 Antithesis: The Hypermobility
Paradigm of Knowledge Work
The new Hypermobility paradigm offers a promising,
fundamentally different approach to organizing work,
working with technology, delineating work/life
boundaries, and provisioning the social safety net, as
outlined below. The Hypermobility paradigm is
exemplified by the ideal type of the “digital nomad”
(Green, 2020; Cook, 2020; Mancinelli, 2020). As
briefly mentioned above, digital nomads are a rapidly
growing group of location-independent knowledge
workers that travel the world for lifestyle, experience,
and global arbitrage (earning a high income while
living in low-cost countries). Digital nomads work
digitally, using internet connections, laptops, mobile

Journal of the Association for Information Systems
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phones, and coworking spaces. They often describe
digital nomadism as the antithesis to the
“rat race” of corporate, employed, and location-bound
work. We draw on the digital nomadism phenomenon
to illustrate the wider Hypermobility paradigm, which
also extends to many other forms of work (electronic
freelancing, sharing economy, etc.).
The following outline of digital nomadism—as an
exemplar and ideal type of hypermobility—is based on
our research program on this emerging phenomenon
(since 2015). We draw on extensive ethnographic work
conducted across the world, including digital nomad
destinations such as Indonesia, Thailand, Taiwan,
Estonia, Germany, and Portugal. Based on such rich
ethnographic material, including participant-
observations and interviews with digital nomads and
those with whom they interact, we provide firsthand
accounts of digital nomads.
4.1 Defining Characteristics
4.1.1 Organizing Work: Emergent
Organizing
In the Hypermobility paradigm emerging in digital
nomadism, there is no workplace authority physically
located alongside the knowledge worker. There is
therefore no Taylorist implementation of workplace
surveillance, planning, and rigid regimentation. In this
sense, the Hypermobility paradigm promises an escape
from the Taylorist surveillance apparatus in which
“you’ve got to be seen, you’ve got to be here” (in the
office) and is instead moving toward a way of working
that treats “people like adults, rewarding them for the
work that they do as opposed to the amount of time
they sit at the office” as “Marc,”
1
a digital nomad, puts
it. Digital nomads are typically freelancers and
entrepreneurs rather than employees (Schlagwein &
Jarrahi, 2020). They take personal responsibility for
their business outcomes, achievements, or failures.
Leadership and status among digital nomads are fluid
and based on the ability to construct a digital identity,
“to give and receive” (digital nomads value sharing
and reciprocity), and to build and engage a community
(Prester, Cecez-Kecmanovic, & Schlagwein, 2019b).
Lacking affiliation with formal organizations, digital
nomads solicit projects and partnerships with other
digital nomads based on current and emerging business
needs. A digital nomad, “Evelyn,” interviewed in Bali,
explains a typical scenario:
We outsourced [tech support] to a web
developer [in another time zone] who runs
a business similar to ours and he provides
emergency cover during the hours when we
sleep. So, if there’s some emergency, like if
1
All interview subjects’ names are pseudonyms.
a website goes down, all our clients know
that they can call the telephone answering
service and they will be put through to him
and he will fix the problem and then charge
us … I met him at a meetup … We don’t ever
want to hire; we decided early on, we didn’t
like working for people and we don’t want
other people to have to work for us and go
into the office at a set time, stuck on a set
salary. We really hope that we’ll grow by
finding other people, freelancers, small
businesses, that we can team up with,
provide solutions to clients and they can live
the life that they want to live.
Such emergent, dynamic organizing characterizes the
overall decidedly social, informal, and semistructured
approach taken by the Hypermobility paradigm of
organizing work. The “meetup” is one of many similar
events organized regularly by digital nomads in
coworking spaces, travel destinations, and online
communities. Despite the distributed nature of digital
nomadism, prices and projects are often based on
social as much as business reasons (e.g., wanting to
work with a particular person). Emergent organizing
between freelancers and small companies in the
Hypermobility paradigm, based on a multitude of
factors (beyond economic gain and efficiency alone),
offers an alternative to the Factory paradigm’s
centralized top-down control model.
4.1.2 Working with Technology: Mobility
and Serendipity
In digital nomadism, both work and life are centered
around digital technologies, including the use of a
network of various online platforms and digital tools
(Sutherland & Jarrahi, 2017; Nash et al., 2018). These
digital technologies enable digital nomads to work
remotely and pursue the digital nomadism lifestyle.
Social media such as Facebook and YouTube can
enable serendipitous encounters that facilitate the
formation and maintenance of business relationships,
ultimately supporting the mobilization of digital
nomads, as explained by “Ashley”:
I use Facebook for everything now, which is
not something that I would have said a few
years ago. [There was a time when] I hadn't
posted anything for five years… There are
Facebook networking groups for anything.
Once I had identified my ideal client, the
type of people that I want to work for, I
looked for Facebook groups that are full of
those people ... Also, sometimes I’m meeting
other travelers. For instance, you meet a lot
of YouTubers when you’re traveling. I’ve

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done some like animations and bumpers for
YouTube videos. I’ve designed branded T-
shirts for this one YouTube couple…
As the above quotes illustrates, digital technologies are
central to digital nomads’ mobility and to
serendipitous business and social encounters. Digital
technologies facilitate travel and connect digital
nomads with communities of people who may become
friends, clients, and/or collaborators. These organically
emerging, technology-enabled networks stand in
contrast to the mechanized and standardized ways of
working with technology according to the Factory
paradigm. The Hypermobility paradigm thus offers an
innovative approach to working with technology and
an alternative to the increasingly outdated approach of
“planning” technology for the Factory paradigm.
4.1.3 Delineating Work/Life: Merging Work
and Life
The Hypermobility paradigm rejects the spatial and
temporal workplace concentration of the Factory
paradigm. Notably, digital nomadism entails an active
and explicit rejection of the 9-to-5 workweek and the
cubicle in the attempt to gain professional, spatial, and
personal freedom (Reichenberger, 2018). The
flexibility to work wherever and whenever is central to
digital nomadism. The professional and work time of
digital nomads is merged and interwoven with their
leisure, travel, and personal time. That is, both spatially
and temporally, digital nomads separate work and
other life activities much less definitively than other
workers. This is most striking with travel bloggers and
social media influencers, where work and life cannot
be distinguished in any meaningful way. Digital
nomads typically chose projects and create business
opportunities based on interest in the subject matter,
thus conflating working for money with pursuing
interests. The distinction between professional
colleagues and private friends also often collapses,
becoming simply networks of individuals who are both
friends and business contacts. Digital nomadism is
characterized by “life-hacking” and the use of tools to
support autonomy, self-management, health,
proactivity, and self-actualization (Wang et al., 2018).
To-do lists, project overviews, calendars self-
management, and the popular “bullet journals” are
often organized with no distinction between work/paid
projects, “for fun” projects, and other endeavors. There
is no distinction between private versus work email,
there are no dress codes, and every day is casual
Friday. Digital nomads may create several digital
identities for different projects, contexts, experiments
etc., yet the separation between professional/work
versus private/leisure spheres characterizing the
Factory paradigm is abandoned as an outdated
dichotomy.
4.1.4 Provisioning the Social Safety Net:
Hyperaware Interjurisdictional
Prospecting
The Hypermobility paradigm is not based on the
conventional Fordist bundle. Digital nomadism takes
this to the extreme by rejecting the very notion of
settling into a particular organization or nation state at
all (i.e., rejecting the entities that would traditionally
provide the “bundle” of social safety measures). As
they roam from place to place, digital nomads’ safety
net is largely individually created and based on
hyperawareness of geopolitical and socioeconomic
conditions (e.g., the rights one has with passport X in
country Y). This can be called “interjurisdictional
prospecting” (Wang et al., 2019, p. 5) for possibilities
and opportunities.
The digital nomads’ response to COVID-19 pandemic
and the lockdowns is illustrative of their attitudes and
approaches. A US-American digital nomad couple,
“Juliet” and “William,” that we previously interviewed
(in Finland) were sheltering in place (in Japan) during
our second interview about their COVID-19 response:
Juliet: I'll do some research and then I'll
put it away for a few days and then take
another look ... I like to know the
probabilities of where we could go. We’re
really not going to be able to understand, as
US passport holders, what countries will let
us in, until maybe two weeks out from our
departure. … But I’m quite comfortable
with this idea that we’re going to let the
times we’re in, and the various government
policies, dictate where we go next.
William: We’re just here to roll with it and
see what comes. … I feel very fortunate that
the worst-case scenario for us is that we go
to America. It’s just a ridiculous thing to
say: that our failsafe, that the worst thing
that happens to us, is that we end up [back]
in America.
The digital nomad couple appears comfortable with the
prospect of “rolling with it” and seeing what comes
next because their nomadic lifestyle has emotionally
and practically prepared them for uncertain
circumstances. Some younger digital nomads may be
engaged in temporary nomadic adventure travel—akin
to a Wanderjahr or gap year (Wang et al., 2018)—and
may not necessarily be preparing for a long-term
lifestyle. However, many other digital nomads, such as
the above couple (in their 50s), are serious about their
choice of lifestyle and have considered its
implications. They do not find it scary to organize their
social safety in a DIY fashion, via hyperaware
interjurisdictional prospecting instead of relying on
organizations or national safety nets. “Retiring early”
and “financial independence” are common concepts in

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digital nomadism: one works until sufficient wealth is
acquired (e.g., 1 million USD) rather than until
retirement age (i.e., 65 years of age). There is no entity
responsible for ensuring a digital nomad’s retirement.
4.2 Critical Assessment
The Hypermobility paradigm and its digital nomad
ideal type present a stark contrast to the Factory
paradigm and its 9-to-5 corporate-worker ideal type.
This paradigm’s approaches to organizing work,
working with technology, delineating work/life
boundaries, and provisioning the social safety net are
different in fundamental ways. The model integrates
the possibilities enabled by specialized skills,
globalization, travel networks, and the nature of digital
knowledge work.
Digital nomadism emphasis freedom and
independence and may, indeed, sound like a dream
come true for many. Digital nomads typically express
enthusiastic levels of satisfaction with their lifestyle
because of the high levels of freedom it offers. Yet
such freedom also comes with potentially unintended
consequences. The spatial and temporal conflation of
leisure and work may negatively impact digital
nomads (Nash et al., 2018) and some report feeling
“permanently anxious and stressed because their labor
productivity is not high enough compar[ed] to the
opportunities they have” (Kuzheleva-Sagan & Nosova,
2014, p. 136). This constant tension about how to use
one’s time is expressed by “Emily”:
I’ve just felt a bit exhausted … the beauty of
this lifestyle is you kind of merge business
and pleasure, I’m in another country
because I can be, so I want to enjoy that and
explore it, but then I have my work to do as
well and I need to do that because that’s
enabling me to be here.
The DIY approach to ensuring a social safety net has
obvious risks. Almost overnight, the COVID-19
pandemic has temporarily halted digital nomadism. (In
the long term, however, the pandemic may increase the
number of digital nomads because of the vast number
of organizations and knowledge workers who are now
experienced in remote work.) This illustrates a
fundamental problem of digital nomadism. When
everything goes smoothly, digital nomads do well.
However, when unexpected personal or global crises
hit—such as wars or conflicts, backlash against
globalization, economic downturns, personal or family
health issues, or, in this case, a global pandemic—
where will digital nomads who are essentially without
a home country turn to? Taxation regimes for digital
nomads often do not exist, which means that digital
nomads may exist in a tax- and insurance-free zone.
This poses long-term risks for digital nomads in a
world organized for settlers. Nations may be at risk of
losing taxpayers entirely, or, at best, may feel
compelled to engage in a global “race to the bottom”
in terms of attractive tax rates (as is already happening
with corporate taxes). It is uncertain whether a digital
nomad’s home country will be willing to extend
coverage (e.g., pensions, health care costs) should
things not go according to plan.
Despite problems and issues with digital nomadism
and Hypermobility, it is an innovative and
contemporary paradigm specifically suitable for digital
knowledge work, and it presents a complete antithesis
to the dominant thesis, the Factory paradigm of
knowledge work. Digital nomadism certainly offers
many elements from which one can learn. Importantly,
considerations of the future of knowledge work should
take into account the conceptual tensions between the
two paradigms and learn lessons from both. Taylorist
centralized control is, as discussed in the previous
section, increasingly ineffective; however, expecting
knowledge workers around the world to immediately
switch to emergent organizing seems unrealistic and,
for many, an undesired ideal.
A consideration of the future of knowledge work
would also need to resolve tensions between
approaches to working with technology. Mechanizing
and standardizing work processes constrain knowledge
workers’ ability to innovate yet carry with them an aura
of reliability (e.g., ERP or analytics), compared to the
deferment to chance implicit in using technology
primarily for enabling mobility and serendipity (e.g.,
social media). Furthermore, a consideration of the
future of knowledge work would also need to resolve
tensions between approaches to work/life balance.
COVID-19 calls into question whether we will
continue to rely on office buildings and the 9-to-5
workday but navigating work/life conflation has
proven challenging, even for digital nomads actively
seeking it. The prospect of all knowledge workers
living with no sense of boundary between work and life
therefore seems quite daunting. Finally, a
consideration of the future of knowledge work would
also need to resolve tensions between approaches to
provisioning the social safety net. The Fordist bundle
is unraveling, yet hyperaware interjurisdictional
prospecting involves significant uncertainty and
assumes digital literacy skills and levels of passport
privilege (in addition to other forms of privilege) that
not all knowledge workers have access to.
This dialectical tension has been accelerated by the
COVID-19 pandemic. In our assessment, the pandemic
will continue to juxtapose and further accelerate the
confrontation between the two paradigms. This is
largely because “many organizations have shifted to
remote-working models almost overnight” (McKinsey
& Company, 2020a, p. 2), forcing a “crisis-induced
digital transformation” (Bartsch et al., 2020, p. 1). This
has made what, in many organizations, was previously

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an uncommon or unaccepted way of working (i.e.,
remote work) a common experience of knowledge
workers worldwide. Faced with the dilemma “between
stopping production altogether or taking on the health
risk of continuing business as usual” (Bartik et al.,
2020, p. 2), most organizations very quickly changed
their stance on flexible and remote work. While some
knowledge workers may accept commutes and
restrictions in spatial flexibility and happily return to
the office, others might consider whether an ocean
view villa in Bali would be an acceptable replacement
for the “work-from-home bedroom office” of 2020.
Organizations will begin to consider whether the cost
of downtown real estate is justified given that a
knowledge worker in a low-cost environment (e.g.,
Thailand, remote) may be willing (and able) to work
for a lower salary compared to one in a high-cost
environment (e.g., Bay Area, in office).
The sudden turn of events surrounding COVID-19
certainly gives urgency to the question of what the
digital future of knowledge work will look like. In light
of the events of 2020, will analysts, traders, writers,
admins, developers, accountants etc. go back to the
“factory”? Will they become location-independent
freelance nomads? Or will there be a third, different
model of knowledge work that emerges? The future of
knowledge work (and of most other things) is
indeterminate yet it is not arbitrary. Hence, drawing
from the tendencies and trajectories discussed, we
envision the spectrum of possible scenarios for the
digital futures of knowledge work as plausible
syntheses and resolutions of the dialectic tensions
between the above paradigms.
5 Synthesis: The Digital Future(s)
of Knowledge Work
There are a number of possible paths that the future of
knowledge work can take, emerging from the
catalyzing effect of the digital transformation of work
during the unprecedented COVID-19 pandemic. We
focus on outlining two extreme forms of what is
possibly to come, partly inspired by the dichotomy of
McGregor’s Theory X and Theory Y (McGregor,
1960). To envisage and, at the same time, provide
grounded conjectures about such possible futures, we
draw from the dialectic tensions between the Factory
paradigm and Hypermobility/digital nomadism, as
well as some current trends, indicators, and tensions
that have already emerged in the course of the COVID-
19 pandemic. Of course, the eventual historically
actualized future may fall somewhere between the two
extremes (or unexpected developments may open new
trajectories).
5.1 The Digital Taylorism Paradigm
The future shaped by the Digital Taylorism paradigm
and its “cyborg” ideal type is one extreme on the
spectrum of possible digital futures of knowledge
work. Digital Taylorism is a version of digitally driven,
optimized-for-efficiency work that, in principle,
adheres to Taylorism; however, it redesigns work by
drawing on the technology-enabled efficiency
potential (rather than poorly adopting it, as the factory
model does). That is, the control and ownership
structures of the Factory paradigm embrace the
concepts associated with digital work and “life-
hacking,” impose tight time-management on
knowledge work, and do away with the physical office
and inefficient commutes (like the Hypermobility
paradigm).
5.1.1 Organizing Work: Machine-Controlled
Work Arrangements
Organizing work in this future paradigm is based on the
argument that the ineffectiveness of conventional
Taylorism can be overcome using digital technologies.
That is, big data, people analytics, artificial intelligence
(AI), and deep learning are central to Digital Taylorism
(Holford, 2020). Compared to the Hypermobility
paradigm, the approach to organizing work in this future
will be “emergent” in a different sense—it will be
emergent only insofar as directives emerge from
algorithms and deep-learning neural networks
processing huge datasets. In this future, machines will
control the work of both machines and human workers
in business processes that are automated as much as
technically and economically possible. The majority of
companies have already been implementing some form
of task, decision-making, and conversation automation
(McKinsey & Company, 2020b). Machine-controlled
work arrangements based on big data and machine
learning have increasingly arisen during the COVID-19
pandemic (Whitelaw et al., 2020; Lalmuanawma,
Hussain, & Chhakchhuak, 2020). Examples include AI-
informed disaster-responses to COVID-19 (Dwivedi et
al., 2020), deep learning for medical triage (Liang et al.,
2020), and a (somewhat) AI-written op-ed published in
The Guardian (The Guardian, 2020). In the Digital
Taylorism future, machine-controlled work
arrangements will match people with tasks and clients
based on performance data and considering fitness, age,
learning ability, machine-defined KPIs, and “stretch
goals.” Algorithms will “direct workers by restricting
and recommending, evaluate workers by recording and
rating and discipline workers by replacing and
rewarding” (Kellogg, Valentine, & Christin, 2020, p.
366). In Digital Taylorism, work arrangements will be
based on dynamically recalibrating machine managers,
which will be based on AI and deep learning to optimize
human knowledge work toward maximum efficiency.
Humans, including owners, may not be able to audit or
comprehend the machine decisions, yet many will

Journal of the Association for Information Systems
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accept and welcome such decisions because the machine
will be automatically optimized toward achieving
predefined goals. This departs from traditional
Taylorism, which relies on human managers, direct
social control, and fixed bureaucratic structures.
5.1.2 Working with Technology: Cyborgizing
Knowledge Work
In this future, under the paradigm of Digital
Taylorism, the approach to working with technology
will transpose the mechanization and standardization
from the Factory paradigm onto the digital
technologies (online platforms, digital tools etc.) of
the Hypermobility paradigm. As a result, workers
will become “cyborgs,” i.e., “theorized and fabricated
hybrids of machine and organism” (Haraway , 1987,
p. 2). The Digital Taylorism paradigm’s ideal type of
cyborg is a human worker who is functionally
entwined with the machine and unable to perform
work optimally without the machine’s support. This
trend has been outlined as “heteromation” (Ekbia &
Nardi, 2014; Ekbia & Nardi, 2017). During COVID-
19, heteromated cyborg work has accelerated, as
individuals’ cost/benefit analysis (and hence
acceptance) of interacting with a machine instead of
a human has shifted: “before COVID-19, people said
they would prefer a human element to their
interactions … COVID-19 may start to change
consumer preferences, as human contact has become
a risky activity that may be harmful to people’s
health” (Coombs, 2020, p. 2). In this future of Digital
Taylorism, cyborgized knowledge work will be about
the substitution or augmentation of the human mind
with the robotic mind. This can already be seen in
nascent examples such as algorithmic journalism
(Dörr, 2015) and predictive policing (Meijer &
Wessels, 2019). Furthermore, physical artifacts, such
as the brain-implant chip of Elon Musk’s Neuralink
company (Pisarchik, Maksimenko, & Hramov, 2019),
may be predecessors to the future cyborgization of
knowledge work. The aim is to optimize human
knowledge workers in order to receive the maximum
output from human resources and to remain
competitive in fully digital, transparent, global
markets.
5.1.3 Delineating Work/Life Boundaries:
Prioritizing Work Above Personal Life
In this future, the approach to delineating work/life
boundaries combines the Factory paradigm’s demand
for workers’ full attention during work hours with the
Hypermobility paradigm’s work/life conflation. In the
extreme, to be selected for highly competitive jobs
workers must be willing to work at any and all hours
(within biological and health limitations). How much a
knowledge worker is willing to work will be part of their
job negotiation: a disadvantage in cognitive capacity
could thus be made up by a willingness to work longer
and harder. The examples given above of overworked
commercial bankers and karoshi existed before the mass
proliferation of digital technologies (brokers,
consultants, professors, etc. often work vastly more than
the 35-40 hour ideal because of intense competition);
however, digital technologies are currently exacerbating
this phenomenon through a vicious cycle that enables
greater efficiency and intrusion of work into other
aspects of life, fueling a “Silicon Valley” culture of
living life “at 2x (double) speed” (Wajcman 2019, p.
316). This has prompted the design of digital
technologies with values inscribed in them capable of
minimizing sleep or microdosing stimulants or
psychedelics (for work, not recreation), depending on
the workday ahead. Digital Taylorism fully digitalizes,
automates (e.g., hire/fire decisions), and exploits the
inherent gamification and competitiveness of a
“perfect,” “free” labor market.
For workers, the result of iterating through this cycle
will likely manifest as a 9-to-9 instead of a 9-to-5
workday for six instead of five days per week (i.e.
“996”), culminating in a 72- rather than 40-hour
workweek. This is already the standard in the IT sector
in rapidly modernizing economies such as China
(Zhang et al., 2020). As Jack Ma, founder of tech giant
Alibaba, states:
I personally think that working “996” is a
huge blessing … Without exceeding the
efforts and hours of your peers, how can you
expect to achieve superior results? … If you
want to join Alibaba, you better be prepared
to work 12 hours a day, otherwise what is the
point of hiring you? There is no shortage of
workers who spend 8 hours a day sitting
comfortably at an office desk, eating lunch
every day in the company cafeteria and being
admired. One can hire someone like that off
the street. (cited in Liang 2019, p. 1).
During the COVID-19 pandemic, it was found that the
average knowledge worker in North America and
Europe worked 8% more hours per day (DeFilippis et
al., 2020), supporting the contention that remote
workers tend to work longer hours (Felstead &
Henseke, 2017). In China, the lived experience of the
“996 in the office” is now “996 in your living room”;
it has not changed the reality of “KPIs heavier than a
mountain” (Liu 2020, p. 1). In this future shaped by the
Digital Taylorism paradigm and its cyborg ideal type,
it is expected that such prioritization of work above the
personal and social life of knowledge workers will
become the norm. Given the improvements in AI and
analytics over recent years, coupled with the
anticipated post-COVID-19 economic downturn, it
may become necessary to “sweat the assets” using
digital means to stay afloat, and knowledge workers
may be compelled to accept tougher conditions in
exchange for a decent paycheck.

Beyond the Factory Paradigm
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5.1.4 Provisioning the Social Safety Net:
Normalizing the Gig Economy
The collapse of the Fordist bundle means that, in
Digital Taylorism, everyone must provision their own
safety nets through an acceptance of “rolling with it”
and seeing what comes next (as described above).
However, for many knowledge workers in this future,
this does not mean interjurisdictional prospecting but
rather prospecting for opportunities, such as looking
for work in the gig economy, given fewer and
increasingly competitive full-time work opportunities.
Gig economy workers are among the most
economically vulnerable of all workers, as has been
demonstrated during the COVID-19 pandemic
(Whyte, 2020; Fredman et al., 2020). Nevertheless,
there has been strong pressure on many workers,
including knowledge workers, to turn to smaller
freelance projects, or gig jobs, to “continue their hustle
just to meet basic needs,” including healthcare
(Chohan, 2020, p. 8). The Digital Taylorism paradigm
and its cyborg ideal type leverage gig-based hiring
rather than traditional employment to provide
frictionless scalability (up or down), market-based
pricing, and full automatic control over a “global on-
demand workforce” (Altenried, 2020, p. 145). This is
very cost efficient. For any digital worker who might
calculate healthcare, pension/retirement, and high
housing costs into their asking price, there is always a
just-as-good alternative digital worker living in a low-
cost area who is willing to take none of these costs into
account. The latter worker will be hired by a hiring AI
in nanoseconds, and all the AI’s owner has to do is pay
the new digital worker. While digital nomads may
have thus far been able to make use of global arbitrage,
the corporate AI will be able to do so as well.
Healthcare and retirement funding is not the AI’s
problem to solve; this is to be handled by the
“independent contractor.” Since all “employees” have
now been replaced with such contractors, this problem
is of no concern to the AI decision maker, who will
certainly suffer no sleepless nights over decisions
made.
5.2 The Worker Autonomy Paradigm
We envision a different future in the Worker
Autonomy paradigm, featuring a knowmad ideal type
of knowledge worker (a knowmad has the flexibility
and work attitude of the digital nomad but not
necessarily the globe-trotting lifestyle). Here, the
forward trajectory and historical synthesis of the thesis
and the antithesis play out vastly differently from
Digital Taylorism.
5.2.1 Organizing Work: Democratizing
Decision-Making
In this future, COVID-19 accelerates the trend toward
an approach to organizing work that addresses the
shortcomings of the Factory paradigm’s centralized
control through a cultural shift in organizing and
leadership. Specifically, leadership moves toward
cultivating the kind of emergent organizing exemplified
in the Hypermobility paradigm by empowering workers
to make their own decisions rather than imposing
preconceived decisions and bureaucratic structures upon
them. Decisions are made in a fluid and engaging way—
through design thinking, creative brainstorming, and
democratizing decision-making instead of imposing
control and force. This trend toward democratized
decision-making and improving worker welfare,
attracting and retaining workers, and increasing
engagement has been a visible trend, not least of all in
the ICT sector. Focusing on the intrinsic motivations
and the desire for self-determination (Deci & Ryan,
2000; Deci & Ryan, 1980), the evidence has repeatedly
shown that letting go of control and empowering
workers is efficient and successful, particularly for
knowledge workers (Pink, 2009; Gambardella,
Khashabi, & Panico, 2020; Ariely et al., 2005). It
represents a fundamental shift in the mindset of many
organizations regarding control. For an analogy, the
bazaar model of open source software (OSS)
development (Raymond, 1999) initially greatly irritated
technology companies following the cathedral model of
proprietary development (e.g., Microsoft), yet
companies did, in some cases, switch to the OSS
paradigm (e.g., IBM endorsing Linux, not without
having lost substantial time and money on proprietary
operating system developments following the old
paradigm; Microsoft is now following suit). Karl
Weick’s work has also shown that commitment to
mutual respect, trust, diversity, loose coupling (i.e.,
accounting for the possibility that information is not
complete), and attentive communication and sincere
interrelating lead to successful collective action
(Eisenberg, 1990; Weick, 2009; Weick & Roberts,
1993). Self-organization— from the 2019 Greta
Thunberg climate change movement to many cases of
COVID-19 collective actions (Mirbabaie et al., 2020)—
illustrate that modern, successful leadership that is about
“influencing” and trusting (instead of “measuring and
controling”). Being able to shape but not determine
trajectories might be more suitable for modern
knowledge work than a leader-servant or principal-
agent (control, functional) idea of managing and leading
collectives of knowledge workers.
5.2.2 Working with Technology: Proliferating
Human Creativity
In this future, shaped by the Worker Autonomy
paradigm, the approach to working with technology will
be aimed toward the empowerment of human
innovations and human creativity (quite the opposite of
cyborgization or heteromation). The use of some
automated systems (e.g., big data, analytics, AI,
algorithms, and deep learning) will still feature in this

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future; however, only in so far as they support human
creative capacities, leaving humans responsible and in
control of algorithmic automation and including the
option not to use algorithms. This approach addresses
the fundamentally problematic lack of transparency (or
often intelligibility) of automated systems (Gal et al.,
2020) as well as their short-circuiting of human-based
learning pathways for tacit knowledge (Riemer & Peter,
2020), their exclusion of contextual specificities
(Hadjimichael & Tsoukas, 2019), and their tendency
toward “algorithmic pollution” (Marjanovic, Cecez-
Kecmanovic, & Vidgen, 2018). As of the time of
writing, technological solutions (such as AI or the
various tracking apps) have contributed little to
combatting the COVID-19 pandemic (Rowe,
Ngwenyama, & Richet, 2020) and have primarily
attracted attention because of their efficient capacity to
algorithmically spread misinformation on social media
(Depoux et al. 2020). While technology may be useful
for narrowly defined, simpler tasks, trust in human
ability and creativity have and will beat automated
knowledge work. In the Worker Autonomy paradigm,
knowledge workers are treated as independent,
responsible professionals, in charge of which
technology they want to use for which purposes.
In this future, based on the COVID-19 digital
transformation of work, telehealth may continue to be
used, but will always be based on the needs and wishes
of medical providers and patients (Smith et al. 2020;
Zhou et al. 2020b), rather than on AI-based advice
(Strickland, 2019, p. 1). Lectures in schools and
universities may be remote and may employ a variety of
technologies (Zhou et al., 2020a), but will principally
feature real teachers and professors rather than AI-based
“intelligent tutor[s]’ (Selwyn, 2019, p. 67) or AI-based
grading (Chin, 2020). In this future, technology will be
used when it supports the human spirit in “creative
appropriation” (Feenberg, 2005)—for example, by
rapidly circulating advice on how to make hand sanitizer
or face shields to the masses via social media (Cohen &
Cromwell, 2020). The common thread, and fundamental
part of the Worker Autonomy paradigm, is that
technology is subordinate to human experience, creative
thinking, and tacit knowledge. It is widely recognized
that technology either cannot replace human
professional knowledge workers or, in the few cases
where this may be possible, human workers are still
necessary to exercise ethical judgment and apply value
principles, thus preventing dependence on technology
that may be prone to making mediocre decisions that
cannot be audited, understood, or corrected in the future.
5.2.3 Delineating Work/Life Boundaries:
Planning for Fluidity
In the Worker Autonomy paradigm, the approach to
delineating the boundaries of work/life is flexible and
can respond to change. Like the approach seen in the
future shaped by Digital Taylorism, this approach
implies workers’ attention outside of the Factory
paradigm’s 9-to-5 workday. However, here, the
intrusion into evenings and weekends is not enforced
by emails and KPIs; rather, the knowmad empowered
by professional autonomy, is responsible for
organizing his or her own work schedule (Prester,
Cecez-Kecmanovic, & Schlagwein, 2019a).
Management is fundamentally about personal skills in
organizing knowledge work, personal time
management, and other techniques—as exemplified by
digital nomads’ self-managing responsibilities and
knowledge work (Wang et al., 2018), according to
individual experiences, personality and personal
needs, and the totality of professional and private tasks
at hand. There is no micromanagement or leadership
via surveillance and control. The mindset is one of
fluidity (Mol & Law, 1994; Kakihara & Sorensen,
2002), in which “boundaries come and go, allow
leakage or disappear altogether, while relations
transform themselves without fracture” (Mol & Law,
1994, p. 643). COVID-19 has demonstrated that work
can be performed, often much more effectively, if
planning is left to individual workers based on their
localized circumstances.
The lockdown conditions, have, by accident,
demonstrated widely that knowledge workers may
perform perfectly well in fluid and flexible
arrangements. As discussed above, in the context of
working from their bedrooms or patios, workers
homeschooling their children (Li, Ghosh, & Nachmias,
2020), running errands and shopping (Richards &
Rickard, 2020; Paul & Chowdhury, 2020), and
managing health (Usher, Durkin, & Bhullar, 2020)
during “work hours” has actually positively impacted
overall performance. Many knowledge workers feel
they can perform work duties more efficiently away
from the office and, in general, find this more flexible,
fluid organization of work/life to be less stressful.
Time for family, health, and other private matters is
simply allocated to the most suitable and logical time
periods, as is work time. Working out at the gym or
going shopping outside of peak times may not only
result in knowledge workers who are less stressed but
also in workers who might just free up that extra hour
for work at a better time. While knowledge workers, as
a whole, have increased their work hours during the
COVID-19 pandemic, knowledge workers may
eventually be able to leverage the efficiencies associated
with working remotely to reduce the number of hours
they work. Indeed, research suggests that 5-hour
workdays produce results at least equal to 8-hour
workdays and that 4-day workweeks may be more
effective than 5-day workweeks for knowledge workers
(Foster, 2020). The Factory paradigm has forced people
to live close to work. In the Worker Autonomy
paradigm, this is replaced with spatial flexibility. Instead
of commuting in rush-hour traffic to a downtown
corporate cubicle, workers will likely be happier,

Beyond the Factory Paradigm
1392
healthier, and more productive if they are allowed to
choose own work space/time (this could mean
redesigning city homes, moving to green countrysides,
working in local coworking spaces, or, yes, even
engaging in digital nomadism) (Terzon, 2020). This
fluid work model will allow workers to merge
professional and private responsibilities and goals in a
seamless manner. For organizations, it will improve
productivity and worker retention; it will also decrease
urban density, property prices, traffic, and pollution,
thus benefiting everyone in society. At the time of
writing, a number of organizations have indicated that
knowledge workers will be allowed to continue working
from home, if so desired, even after the COVID-19
pandemic resolves.
5.2.4 Provisioning the Social Safety Net:
Upskilling Toward Lifelong Learning
In the future of the Worker Autonomy paradigm, there
will be a recognition that the increasing breakdown of
the Fordist bundle means that people must provision
their own safety nets. While this implies the same
overall objective as in the Digital Taylorism paradigm,
the path toward achieving this objective is different in
this case. Instead of constructing a safety net based on
short-term gigs and projects, the approach here will be
to construct a safety net based on ongoing upskilling,
working toward lifelong learning, and striving toward
upward career progression, whether as employees or
freelancers. John Moravec articulates this ideal of the
future knowledge worker as an empowered knowmad:
Of particular importance is the emerging
class of borderless, “new” workers; or, as I
like to call them, knowmads. [A knowmad is]
a nomadic knowledge worker—that is, a
creative, imaginative and innovative person
who can work with almost anybody, anytime
and anywhere. Industrial society is giving
way to knowledge and innovation work … in
the knowledge society into which we are
moving, individuals are central. Knowledge
is not impersonal, like money. Knowledge
does not reside in a book, a databank, a
software program; they contain only
information. Knowledge is always embodied
in a person, carried by a person; created,
augmented, or improved by a person; applied
by a person; taught by a person and passed
on by a person. The shift to the knowledge
society therefore puts the person in the center.
(Moravec 2013, pp. 79-80)
Moravec identifies COVID-19 as a turning point in
rethinking the relationship between education and work
(Moravec 2020). The future of work, including the feared
replacement or transformation of jobs through robotics,
AI, automation, etc., increasingly affects white-collar
knowledge workers rather than only blue-collar workers,
as in previous waves of automation. The trend toward
upskilling and lifelong learning—as opposed to the idea
of a one-off degree that ensures a conventional career
path—has certainly accelerated during the COVID-19
pandemic. Governments have started providing funding
for the reskilling and upskilling of workers in recognition
of the digitalization of work and the resulting changed
and increased skill requirements (Duffy, 2020). While
organizations and governments may be more willing to
provide at least some social security benefits in a world
that settles on a Worker Autonomy paradigm of work (as
opposed to a world that accepts Digital Taylorism), the
onus will still be on the individual to provide their own
social safety nets. In particular, a mindset of personal
growth, self-reliance, upskilling, and lifelong learning
may be foundational to empower knowledge workers
both intellectually and economically.
6 Discussion and Outlook
There is very little doubt that the future of knowledge
work is digital and that the COVID-19 pandemic has fast-
tracked the digital transformation of work. But how will
digital knowledge work be organized in the future? In our
argument—using dialectical reasoning, contrasting a
corporate work/Factory paradigm (as the thesis) with a
digital nomadism/Hypermobility paradigm (as the
antithesis), and forward-thinking current trends
accelerated by COVID-19—we envisioned two futures of
digital knowledge work. They are both extreme yet
plausible scenarios that each extrapolate certain aspects of
the existing paradigms. In the first future vision, the
Digital Taylorism paradigm brings with it a cyborgized
nature of knowledge work in which digital technology
decomposes, measures, and optimizes work toward
maximum efficiency. In the second future vision, the
Worker Autonomy paradigm empowers knowmad
workers that engage in fluid work arrangements and take
charge of technology, their education, and their life
trajectories. Table 1 summarizes the two existing and the
two envisioned paradigms side by side, summarizing
Sections 2-5 above.
The future may look different in different locales, for
different industries, or at different times. The purpose of
envisioning extremes of possible futures—instead of
presenting a median prediction of a single future—is to
emphasize that different futures are conceptually and
practically possible. Which future we will ultimately find
ourselves in—likely a hybrid of the two extremes—
depends on our collective aspirations and actions going
forward.
Some elements that are bringing the future about, such as
the COVID-19 pandemic, are largely out of our control.
However, for the most part, the human collective is in
charge of creating the digital future of knowledge work
and choosing the world in which we would like to live.
Technologies can be rolled out and discarded, market
rules can be changed; the agency is with us.

Journal of the Association for Information Systems
1393
Table 1. Comparison of Thesis, Antithesis, and Synthesis
Thesis
Antithesis
Synthesis
Paradigm
Factory paradigm
Hypermobility
paradigm
Digital Taylorism
paradigm
Worker Autonomy
paradigm
Ideal type
9-to-5 corporate
worker
Digital nomad
Cyborg
Knowmad
Organizing work
Taylorist centralized
control
Emergent organizing
Machine-controlled
work arrangements
Democratizing
decision-making
Working with
technology
Mechanizing and
standardizing
Mobility and
serendipity
Cyborgizing
knowledge work
Proliferating human
creativity
Delineating work/life
Workplace
concentration
Merging work and life
Prioritizing work
above personal life
Planning for fluidity
Provisioning the
social safety net
Institutionalizing the
Fordist bundle
Hyperaware
interjurisdictional
prospecting
Normalizing the gig
economy
Upskilling and
lifelong learning
The future shaped by the Digital Taylorism paradigm
may seem dystopian, at least from the knowledge
workers’ perspective (perhaps not from the
owners’/shareholders’ perspective). The machine-
controlled work arrangements and cyborgizing of
knowledge work that Digital Taylorism supports could
certainly deliver some impressive gains in efficiency
in the short-term future (which would also benefit
workers in their role as consumers, of course).
Arguably, the first manifestations can already be seen
in how work is organized for Uber drivers or Amazon
warehouse workers. Modern free-market economies,
through inherent, competitive market logic, force a
constant push toward efficiency. Although some
organizations may not wish to push for longer work
hours to increase productivity, their competition in the
global market will not likely be constrained by such
concerns. Digital Taylorism is already becoming
entrenched because of existing Taylorism-inspired
social beliefs and values (Holford, 2019). As
automation increasingly takes over standard
knowledge tasks, human creativity and judgment will
be stifled and truncated, creating potential long-term
risks (Brown & Lauder, 2010; Holford, 2020).
The future shaped by the Worker Autonomy paradigm
and knowmads may seem more utopian (from the
knowledge workers’ perspective). There are nascent
examples of how this work might look, including
remote working arrangements, digital upskilling
efforts, and digital nomads as reference points. Here,
much concerted action will be required; as this future
must be made, it is unlikely to be actualized “on auto-
pilot.” For example, countries could legally restrict
working hours of knowledge workers, prevent
classifying independent contractors as such, or outlaw
workplace surveillance. These are political decisions;
the market will not push for such changes. The long-
term prospects may be better for workers, but
potentially also organizations and society overall (as
indicated above, at least some studies suggest workers
may be more efficient if “sweated” less; also, workers
may have fewer health problems because of less stress,
less traffic, and more time recreation; a time-poor
worker may consume less, etc.)
There are a number of predicted COVID-19 impacts
on this trajectory. First, knowledge work has become
digital work and location-independent work in the
wake of the COVID-19 pandemic. Remote workers in
the past have been seen as the odd ones out, isolated
and disconnected from fellow workers if accepted at
all (Boell, Cecez-Kecmanovic, & Campbell, 2016;
Gajendran & Harrison, 2007; Pyöriä, 2011). In the
post-COVID-19 world, remote digital work will likely
become much more common and widely accepted by
both workers and organizations. As there seems to be
both economic efficiencies as well as lifestyle benefits
associated with remote work, the change to a
substantial share of remote knowledge workers may be
rapid. Second, there will be widespread shifts in
mindset and how “work” is fundamentally viewed. The
lockdowns have visibly displaced a deeply entrenched
taken-for-granted way of working that is grounded in
the Factory paradigm of knowledge work. This will
pave the way for a new future of knowledge work, with
much cultural and cognitive inertia (the technology has
been around for years) having been shattered and
removed by COVID-19.
Third, the forced slowdown of society during the 2020
lockdowns was felt by many to be a relief from the
constant forward pressure (for those not having to
confront a lack of personal wealth and inadequate
social safety nets in an economic slowdown). Many
more knowledge workers may now be open to explore
ways of working beyond corporate models. Digital
nomads have succeeded in creating an alternative
paradigm of knowledge work that focuses on the lived
experience of the worker, not on the technical

Beyond the Factory Paradigm
1394
requirements of efficiency. We anticipate that these
and other niche models of work are now being
considered by a vastly larger number of knowledge
workers than before COVID-19. Finally, as with other
major events, weak organizations will fail and upstarts
will take the market share in the recovery. That is,
COVID-19 will likely accelerate economies in the
midterm (as did even more vastly devastating events
such as WW2). Several organizations have certainly
benefited from the problems of others (e.g., streaming
services instead of cinemas etc.). Disruptions trigger
changes.
The envisioning of possible futures of digital
knowledge work calls IS researchers to action. The IS
research community has a privileged opportunity to
contribute insights that could draw attention to and
warn of the potential perils of Digital Taylorism for
quality of life and help articulate the opportunities and
tangible steps that can be taken to empower Worker
Autonomy (we assume most readers agree with our
preferred choice of future). The challenge for IS
researchers will be to frame problems, conduct
research, and communicate findings that demonstrate
the power of IS to engender cultural, organizational,
and societal changes toward the preferred future—such
as toward democratizing decision-making, supporting
human creativity, enabling fluid and flexible work
arrangements, and supporting the upskilling of the
population. Shaping the digital future of knowledge
work is not an analytical and explanatory endeavor;
rather, it is a forward-looking, value-sensitive, and
normative one.
With this call in mind, in this editorial, we hope to
stimulate a conversation about the future of digital
knowledge work and the possibilities (and threats)
created by the COVID-19 disruptions. To enable such
a conversation, we have endeavored to open up
horizons for those advocating pure efficiency and
Digital Taylorism as the only viable future and those
looking for alternative ways of working and leveraging
digital technology for richer human lives. The more we
expand our horizons, the more we will be able to
engage in conversations with the possible work futures
and with each other, in our local organizations and
across organizations, in our communities and in
society at large. By suggesting a vocabulary for such a
conversation, including showing vast differences in
how the future might play out, we hope to assist in
addressing bigger and deeper questions about the
nature and meaning of digital knowledge work that are
of critical importance for confronting possible futures
and acting responsibly.
Overall, we believe that COVID-19 has brought us to
a critical juncture in the history of knowledge work.
COVID-19 has catalyzed change toward vastly
different futures—Digital Taylorism versus Worker
Autonomy. Which of the two future visions will
become a reality has not yet been decided. Aware of
the possibilities, we have an opportunity to exercise
our human agency and work toward the future that best
serves the interests of workers, organizations, and
societies worldwide.
7 Acknowledgments
This work was supported by an Australian Research
Council Discovery Project (DP190102780) and by an
Australian Government Research Training Program
Scholarship.

Journal of the Association for Information Systems
1395
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About the Authors
Blair Wang is a PhD teaching fellow at the UNSW Business School, The University of New South Wales, Sydney,
Australia. His research interests include digital nomadism, digital work, critical theory and critical IS research. Through
both his research and teaching work, he aspires to empower the next generation of knowledge workers to thrive in the
digital future(s) of knowledge work—whatever these future(s) may look like.
Daniel Schlagwein is an associate professor of information systems at The University of Sydney, co-editor-in-chief
of the Journal of Information Technology and co-leader of the Digital Disruption Research Group. His research focuses
on digital work, digital nomadism, crowdsourcing and IT-enabled openness. He has published over 50 peer-reviewed
papers including in journals such as the European Journal of Information Systems, the Information Systems Journal,
the Journal of Information Technology, the Journal of the Association for Information Systems and The Journal of
Strategic Information Systems. He received best paper of the year awards from the Association for Information Systems
(AIS), the Association for Information Science and Technology, Information Technology & People and The Journal
of Strategic Information Systems. Daniel was awarded the AIS Early Career Award in 2016, the Journal of the
Association for Information Systems Best Reviewer Award in 2016 and the AIS Best Information Systems Publication
Award in 2017.
Dubravka Cecez-Kecmanovic is scientia professor of information systems at the UNSW Business School, The
University of New South Wales, Sydney, Australia. Her research interests include qualitative, critical, sociomaterial
and process-oriented research that contributes to deeper insights into and understanding of IS phenomena and their
social and ethical consequences in organizational and broader societal contexts. Her papers have been published in
leading IS journals including MIS Quarterly, Journal of the Association for Information Systems, Information Systems
Journal, European Journal of Information Systems, Journal of Information Technology, and Journal of Strategic
Information Systems. She served on many editorial boards and is currently a senior editor at Journal of the Association
for Information Systems, Information Systems Journal, and Information & Organization. She is Senior Scholar and a
Fellow of the Association for Information Systems.
Michael C. Cahalane is a senior lecturer and deputy head of school (Education) at the UNSW Business School, The
University of New South Wales, Sydney, Australia. He obtained his bachelor's degree as well as PhD in information
systems as the University College of Cork (Ireland). His research interests include qualitative and ethnographic
research, as well as the study of online communities, gamification, and virtual reality. His papers have been published
in leading IS journals and conference proceedings.
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