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On why Uber has not taken over the world



Today it is common to see news headlines decrying the wildfire spread of the ‘gig economy’. We ask the exact opposite question: why aren’t more jobs now conducted via labour-based digital platforms, the primary method used in the gig economy? Surveys in the United States, United Kingdom and elsewhere indicate that gig work remains a very minor component of the labour market, and certainly isn’t overshadowing either regular employment or the contingent workforce (e.g. on-demand, part-time, contract, seasonal). The size of the gig economy is probably exaggerated because it is conflated with casual work per se (which has indeed grown) and non-labour platforms. Our paper argues that a central reason why labour-based digital platforms produce so few jobs is because it is inspired by a purist version of neoliberal capitalism, reductio ad absurdum, including strict market individualism and anti-unionism. This renders the gig economy unsustainable on its own terms, revealing its basic internal limits. The gig economy is a potent and dangerous pro-market fantasy, yet one whose imagined perfection is unsuitable to the realities of work on a large scale, hence why it has not proliferated more widely, thriving on the fringes instead.
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On why Uber has not taken over the world
Peter Fleming, Carl Rhodes & Kyoung-Hee Yu
To cite this article: Peter Fleming, Carl Rhodes & Kyoung-Hee Yu (2019): On why Uber has�not
taken over the world, Economy and Society, DOI: 10.1080/03085147.2019.1685744
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On why Uber has not taken
over the world
Peter Fleming, Carl Rhodes and Kyoung-Hee Yu
Today it is common to see news headlines decrying the wildfire spread of the gig
economy. We ask the exact opposite question: why arentmore jobs now con-
ducted via labour-based digital platforms, the primary method used in the gig
economy? Surveys in the United States, United Kingdom and elsewhere indicate
that gig work remains a very minor component of the labour market, and certainly
isnt overshadowing either regular employment or the contingent workforce (e.g.
on-demand, part-time, contract, seasonal). The size of the gig economy is prob-
ably exaggerated because it is conflated with casual work per se (which has
indeed grown) and non-labour platforms. Our paper argues that a central
reason why labour-based digital platforms produce so few jobs is because it is
inspired by a purist version of neoliberal capitalism, reductio ad absurdum, includ-
ing strict market individualism and anti-unionism. This renders the gig economy
unsustainable on its own terms, revealing its basic internal limits. The gig
economy is a potent and dangerous pro-market fantasy, yet one whose imagined
perfection is unsuitable to the realities of work on a large scale, hence why it has
not proliferated more widely, thriving on the fringes instead.
Keywords: future of work; gig economy; labour-based digital platforms;
neoliberalism; sharing economy; Uberization.
Copyright © 2019 Informa UK Limited, trading as
Taylor & Francis Group
Peter Fleming (corresponding author), Department of Management, UTS Business School,
1428 Ultimo Road Ultimo, Sydney, NSW 2007, Australia. E-mail: peter.fleming@uts.
Carl Rhodes, Department of Management, UTS Business School, 1428 Ultimo Road
Ultimo, Sydney, NSW 2007, Australia. E-mail:
Kyoung-Hee Yu, Department of Management, UTS Business School, 1428 Ultimo Road
Ultimo, Sydney, NSW 2007, Australia. E-mail:
Economy and Society
There has been much public and academic interest in the emergence of the
sharingor gig economy. Sometimes dubbed platform capitalism(Srnicek,
2016), this mode of employment sees individuals compete for jobs via online
platforms, using a work-performed payment structure (De Stefano, 2015). It
presents businesses with levels of labour flexibility not available through stan-
dard forms of waged employment because (a) payment pertains only to tasks
completed and (b) workers are not classified as employees, meaning that
employers can avoid the costs associated with regular jobs.
While some celebrate labour-based digital platforms as a harbinger of individ-
ual freedom in the modern workplace (see Sundararajan, 2017), critics highlight
the financial hardship that this can foster, using the neologism Uberization
(Fleming, 2017; Hill, 2015) to describe the conversion of regular work into con-
tingent, itinerant and insecure gigsmediated by digital algorithms and con-
trolled by large corporations. Because gig workers are treated as independent
business owners rather than employees, de facto employers are able to bypass
statutory requirements like paid holiday leave, pension contributions,
minimum wage, sickness insurance and protection from unfair dismissal
(Martin, 2016; Scholz, 2016; Stewart & Stanford, 2017).
Scholars and public commentators alike decry the exponential growth of the
gig economy and its slew of unincorporated workers. A study by the McKin-
sey Global Institute (2016) estimated that the gig economy now affects up to
30 per cent of the working-age population in the United States and Europe,
confirming earlier predictions regarding the rise of micro-jobs(see Inuit,
2010). In his critical analysis of US employment patterns, Hill (2015,p.2)
views Uberization as a runawaybusiness model that is rapidly destroying
regular work: it has spread outward from the tech nirvana in the Bay Area
[of San Francisco] to every corner of the world. The genie has been let out
of the bottle. Other commentators speak of the imminent demise of standard
jobs (Kessler, 2018) and even employment itself (Sundararajan, 2017). Adding
to this impression are attention grabbing headlines such as the Huffington Post
declaring, The Uberization of everything is happening(Freeman, 2015), The
Guardian announcing that The gig economy is coming(Sundararajan, 2015)
and on a more sanguine note, Forbes proclaiming, LetsUberizetheentire
economy!(Carney, 2014).
The exaggeration, especially in the popular media, likely stems from ambigu-
ities around definition and measurement, with all kinds of insecure work (e.g.
freelancing, part-time, etc.) being counted as part of the new gig economy.
Reports may also include non-labour online platforms (e.g. Airbnb, revenue
derived from eBay, etc.), which muddies the picture yet again. However, a
closer inspection of official statistics in countries reportedly in the grip of Uber-
ization reveals that work in the gig economy is remarkably small and marginal
compared to other forms of employment. For example, the US Bureau of
Labor Statistics (2018a) reports that contingent workers accounted for 1.3
2Economy and Society
per cent to 3.8 per cent of total employment in May 2017. Moreover, gig
workers only make up a fraction of that figure. The National Bureau of Employ-
ment Statistics estimated that 0.5 per cent of the US workforce is involved with
online intermediaries associated with platform capitalism (Katz & Krueger,
2016). In the United Kingdom, just 0.96 per cent of workers earned the majority
of their income through interaction with the gig economy in 2017 (Department
of Business, Energy and Industrial Strategy, 2017).
The above figures are surprisingly modest compared to what management
consultants and the media would have us believe. In many ways the existence
of the gig economy comes at the end of a long trajectory of changes to employ-
ment over the past 30 years, as characterized by the liberalization of labour laws,
the growth of flexible working and the reduced power of trade unions. Gig work
is the apogee of this in that it maximizes flexibility and freedom for employers in
terms of how they hire and remunerate labour. Thus it is not unreasonable to
assume that gig-based work would be attractive to any enterprise seeking flex-
ible employment under minimal regulation. That is to say, we can assume that if
employers in other sectors could Uberize their labour force (given the cost
savings) then they probably would without much hesitation. So there must
be something stalling the diffusion of on-demand digital platforms into the
wider employment sector. But what?
Clearly some jobs are not amenable to being organized via the gig economy. It
is hard to imagine, for example, senior managers, psychiatrists and funeral
directors being employed in this way. However, the percentage of non-Uber-
ized jobs must also include a considerable range of occupations that theoretically
could be restructured in accordance with platform capitalism. Might the orga-
nized labour movement be resisting the dissemination of Uber-jobs into other
occupations? Perhaps to a certain extent, but trade union activity in the
OECD has been weak overall (Stewart & Stanford, 2017; Wood et al.,2019).
Moreover, even powerful unions like the Licenced Taxi Drivers Association
(representing black cab drivers in London) have not halted the presence of
Uber in the United Kingdom. What about state regulation, is that containing
the gig economy? Also up to a point, but its size remains marginal even in
countries where the government has been relatively favourable, such as the
United States.
In seeking an alternative explanation we propose that rather than being a
synonym for sharing, the gig economy represents an extreme variant of neolib-
eral capitalism for its workers. Here we follow Harveys(2005) definition:
Neoliberalism is in the first instance a theory of political economic practices that
proposes that human well-being can best be advanced by liberating individual
entrepreneurial freedoms and skills within an institutional framework character-
ized by strong private property rights, free markets and free trade [] state
interventions in markets (once created) must be kept to a bare minimum
because, according to the theory, the state cannot possibly possess enough infor-
mation to second-guess market signals (prices) and because powerful interest
Peter Fleming et al.: On why Uber has not taken over the world 3
groups will inevitably distort and bias state interventions (particularly in democ-
racies) for their own benefit. (Harvey, 2005,p.2)
This culturally pervasive form of capitalism translates into the workplace and
the gig economy or labour-based digital platforms more specifically as the
ultra-marketization, rationalization, individualization and subordination of
(both private and working) life to the logic of accumulation. This mode of capit-
alism effectively sidesteps labour market safety nets and regulations, leaving it as
a basic form of unencumbered economic exchange between capital and labour in
a nominally open marketplace.
Hence our argument. Labour-based digital platforms are an almost too
perfect expression of neoclassical economic theory, especially pertaining to
abstract market individualism. Too perfect is the operative phrase. This
version of capitalism is so pure and unalloyed (from a theoretical perspective
at least) that it is largely unworkable in practice. Labour-based digital platforms
bump up against the limits of feasible and reproducible economic activity,
marking the logical end point of the process of neoliberalization thats been
underway in economies around the world since the 1980s. Importantly, we
are not suggesting that employment hasnt been significantly degraded over
the last 40 years. It undoubtedly has (Kalleberg, 2018; Standing, 2017; Weil,
2017). But the gig economy still remains a minor facet of that trend for
reasons we seek to explain.
Defining and measuring the gig economy
Even though the term gig economyhas been in use for about a decade (Uber,
for example, was founded in 2009) there has been significant confusion regard-
ing its definition and measurement. There are several causes. As previously
noted, accounts in the media often conflate workers in the gig economy with
those who earn revenue from capital/asset based platforms (including Airbnb
and Etsy), sell goods online (eBay) and engage in consignmentactivities
with firms like YouTube (Collier et al.,2017; Constantiou et al.,2017). The
labour-based digital platforms that concern us are distinct, involving the
selling of labour time rather than acting as a landlord or selling goods and ser-
vices. Furthermore, casual work, freelancing, contracting and part-time
employment, while not new, are often confused with employment in the gig
economy. This in turn impedes accurate measurement, since not all contingent
and alternativework arrangements (as they are labelled in the United States,
for instance) involve labour-based digital platforms or gig jobs.
Given these difficulties, our paper will precisely define the gig economy and
then map this definition against available data concerning its size in a number of
OECD countries. In particular, we examine the United States (where platform
capitalism originated), the United Kingdom, Australia and several European
countries. These countries were chosen as examples of advanced economies
4Economy and Society
governed by a liberal democratic state that have embraced neoliberal reforms
since the 1980s. These reforms include market deregulation, de-unionization
of the workforce, privatization of public enterprises and the valuing of market
relations as a natural and superior mode of socio-economic organization
(Brown, 2015). It is this context that we suggest is significant for our explanation
of employment trends as they relate to both the economic realities and social
implications of Uberization.
What is the gig economy?
Our focus is on labour services provided via digital platforms. This is not to be
confused with similar arrangements relating to self-employment, contracting
work, agency jobs, part-time, seasonal roles and so-forth. The US Bureau of
Labor Statistics (BLS) (2018b, n.p.) admitted to this classificatory problem in
relation to its Contingent Work Supplement (CWS), which was appended to
the Current Population Survey (CPS) between 1995 and 2017:
many definitions of gig workers include people in temporary jobs, indepen-
dent contractors, on-call workers, and day laborers all of which can be esti-
mated with CWS data. However, many definitions also include people in
types of work arrangements that did not exist when the survey was last
The notion of self-employment (which is extensively used in the gig economy)
aptly illustrates the confusion. Of course, self-employment predates the emer-
gence of the gig economy and can take on various forms. An owner operator of a
bakery and a Lyft driver both fall into this category, but only the Lyft driver is a
gig worker. Employment law has therefore sought to distinguish the incorpor-
atedself-employed from the unincorporatedself-employed. Whereas the
owner operator of the bakery is an incorporated worker since they own and
run a legal corporate entity the Lyft driver is an unincorporatedworker.
S/he is not legally a corporate body but is nevertheless an independent business
concern in his or her own right, hired by another organization in a manner that
is casual and peripatetic.
However, even this distinction does not quite capture the specific character-
istics of the gig economy. The term labour-based digital platforms indicates why,
in that it alludes to the use of an electronic intermediary (e.g. an Uber app) to
match nominally private workers with consumers in a real-time, on-demand
fashion. The BLS (US Bureau of Labor Statistics, 2018b) recently made a
notable innovation in this regard. When trying to isolate this category of
employment, it added four new questions to its 2017 CWS, honing in on the
electronic element to differentiate gig workers from other seasonal labourers,
part-time employees and so-forth. They approach the gig economy as, electro-
nically mediated work, defined as short jobs or tasks that workers find through
Peter Fleming et al.: On why Uber has not taken over the world 5
websites or mobile apps that both connect them with customers and arrange
payment for the tasks. Additionally,
[i]n this type of employment arrangement, workers
.use a companys website or mobile app to connect to clients or customers
and obtain short jobs, projects, or tasks;
.are paid by or through the company that owns the website or mobile app;
.choose when and whether to work; and
.may do these short jobs, projects, or tasks in person or online. (n.p.)
A similar definition is forwarded by other researchers in the United States. For
example, the US Census Bureau and National Bureau of Economic Research state,
we define gig employmentas one-time jobs where workers are employed on a
particular task or for a defined period of time. A gig worker is not paid a wage or
salary; does not have an implicit or explicit contract for a continuing work
relationship; and does not have a predictable work schedule or predictable earn-
ings when working. (Abraham et al.,2017, p. 10)
The UK government has echoed these protocols when defining the gig
economy. While not as methodologically advanced as their US counterparts,
the most accurate study of gig workers (commissioned by the Department of
Business, Energy and Industrial Strategy, 2017, p. 4) observes, the gig
economy involves the exchange of labour for money between individuals or
companies via digital platforms that actively facilitate matching between provi-
ders and customers, on a short-term and payment by task basis.
Measuring the gig economy
Due to the ambiguity surrounding the boundaries of the gig economy, measure-
ment systems that collect data on the topic have, historically, been fraught with
difficulty. However, with recent definitions yielding a more accurate and delim-
ited picture of gig work, a number of methodologies have been developed that
have aimed to gauge its size. The most ambitious attempts have been conducted
in the United States. As mentioned above, since 1995 the BLS has appended a
CWS to the CPS to measure contingent and alternative employment. Contin-
gent workers are defined as persons who do not expect their jobs to last or
who report that their jobs are temporaryand alternative workers identified
as independent contractors, independent consultants, or freelance workers,
regardless of whether they are self-employed or wage and salary workers
(US Bureau of Labor Statistics, 2018a, n.p.). The CPS consists of a probability
selected sample of 60,000 households. The questionnaire is administered in
person or over the phone and relies on both self and proxy reporting (where
one household member describes the activities of all other members), with
the time frame of last weekused.
6Economy and Society
Because contingent and alternative work arrangements are too broad for iso-
lating digital platform workers, the 2017 CSW added four extra questions (see
Appendix). They were designed to identify household members who had
earned income through in-person electronically mediated work or jobs done
entirely online. The additional questions also asked whether this was their
main or secondary income source. One concern was that some respondents
might not view their participation in the platform economy as paid employment
and thus misreport their true status by answering no. The BLS decided it
would be too complicated to add further questions to control for this. Moreover,
although the extra four questions were rigorously pilot tested, analysts discov-
ered that many respondents were answering yesif they used any type of app in
their work environment (which happened to include a vice president of a major
bank, a police officer and a surgeon), thus producing a false positive result. This
was detected by comparing their answers to the confidential microdata logged in
the rest of the CPS and CSW. Consequently, analysts recoded the data to
control for these false positives, as well as a number of false negatives.
In association with the National Bureau of Employment Research, Katz and
Krueger (2016) conducted another study of the gig economy in the United
States that was done before the BLS released results of its extended survey
in September 2018. Katz and Krueger contracted the RAND Institute to
administer an online survey of alternative work arrangements to individuals
in its American Life Panel, with approximately 6,000 respondents invited to
participate (using a compilation of methods, including a random digit dial
sample and a snowball sample). Respondents were asked whether the alternative
work arrangement was their only form of income and also if it was digitally
mediated (so as to isolate gig workers from other employment categories).
The BLSs classification hierarchy was replicated so that the data could be com-
pared with the CWS. However, in contrast to the CSW, this study avoided
proxy measurements in order to gain more accurate results. In addition, as
stated in the report,
the CWS imposes a hierarchical skip logic (e.g. if a worker is on a temporary help
or on-call job, she is not asked whether she is a freelancer) that we did not follow
(i.e. we asked workers on temporary help and on-call jobs if they were indepen-
dent contractors or freelancers) to gather more complete information on work
arrangements. (Katz & Krueger, 2016,p.4)
In the British context, and operationalizing the definition cited earlier, the
Department of Business, Energy and Industrial Strategy (2017) used two
methods of measurement. First, a NatCen Panel involving a probability-based
online survey of 2,184 people in Britain (excluding Northern Ireland) where
Panel members were randomly selected through the British Social Attitudes
survey was used. And second, research firm YouGov Omnibus was commis-
sioned to conduct a non-probability online panel survey (sequenced over five
waves) of 11,354 people.
Peter Fleming et al.: On why Uber has not taken over the world 7
Seeking to identify European trends in the gig economy, a major study was
undertaken by a consortium consisting of the Foundation for European Pro-
gressive Studies, Uni Europa and the University of Hertfordshire (see Huws
et al., 2017). The percentage of the population using digital labour platforms
(which they termed crowd workers) was measured in the United Kingdom,
Sweden, Germany, Austria, the Netherlands, Switzerland and Italy. Crowd
work was defined as paid work via an online platform(Huws et al., 2017,
p. 16; also see Vermeylen et al., 2017). These workers were delineated from
other employment arrangements through a disaggregated data collection
process. This was because, crowd work as a source of income may overlap
with [and needs to be distinguished from] other sources of income derived
from online platforms, for instance through the sale of goodsand online
search for work via online platforms may overlap with other forms of online
job-searchthat are in fact distinct (Huws et al., 2017, p. 14). The approach
allowed researchers to estimate the degree to which individuals depended on
the gig economy for their primary source of income.
The researchers also commissioned Ipsos MORI to survey a random sample of
the population in each country using online methods (United Kingdom [2,238
respondents], Sweden [2,416 respondents], Germany [2,180 respondents],
Austria [1,969 respondents], Italy [2,199 respondents], Switzerland [2,001
respondents] and the Netherlands [2,126 respondents]). Additional face-to-face
research methods were conducted in Switzerland [1,205 respondents] and the
United Kingdom [1,794 respondents]. The face-to-face method was included
to correct for any bias concerning internet users. As online surveys oversample
respondents who regularly use the internet, the estimations provided in the
studies above present a ceiling for the scale of gig work in these economies.
However, in the UK case, for example, the difference between face-to-face and
online respondents was found to be negligible.
The size of the gig economy
These methodologies are important for providing an accurate measurement of
the gig economy, especially in light of the considerable publicity that surrounds
its development. As discussed earlier, the media hype has been intense. A press
release by the McKinsey Global Institute (2016), for example, attracted much
media attention when it stated that the gig economy makes up 30 per cent of
the workforce in the United States and United Kingdom. Such claims are com-
monplace. Research by the Freelancers Union, for example, asserted that up to
36 per cent of the US workforce are freelancing and thus part of the gig
economy. Similarly, a study by BMO Wealth Management (2018,p.1)in
Canada argued that the labour market has shifted from one characterized by
stable or permanent employment to a gig economyof temporary or contracted
employment, where an on-demand, freelance or contingent workforce is becom-
ing the norm.
8Economy and Society
There is little doubt that insecure and precarious employment has signifi-
cantly increased in advanced capitalist countries (see ILO, 2018; OECD,
2015). The neoliberalization of many of the worlds increasingly interconnected
economies has been a major driver. It follows from the deregulation of employ-
ment, the decline of trade unions, stagnating wages and the valorization of zero-
hours and at willcontracts (Herod & Lambert, 2016). The question is, how
much of this can be explained by an encroaching gig economy? The results
of the BLS (US Bureau of Labor Statistics, 2018a,2018b) survey in the
United States can be divided into two parts. Pertaining to the CWS, it was
found that in May 2017 between 1.3 and 3.8 per cent held contingent jobs.
In 2005 the figure was higher (between 1.8 per cent and 4.1 per cent of
workers). Regarding alternative work arrangements, as of May 2017, 6.9 per
cent were independent contractors, 1.7 per cent were on-call workers and 0.6
per cent were workers supplied by contract firms. However, the results from
the extra four questions that focused on electronically mediated work are
what really interest us. As it turns out, 1 per cent of workers fell into this
Katz and Kruegers(2016, p. 1) study indicates that workers in alternative
work arrangements (defined as temporary help agency workers, on-call
workers, contract workers, and independent contractors or freelancers) com-
prised 15.8 per cent of the US workforce. This figure stood at 10.7 per cent
in 2005. Workers hired out by contract companies rose from 1.4 per cent in
2005 to 3.1 per cent in 2015 (notably higher than the BLSs 2017 CWS).
And finally, workers who provide services through online intermediaries,
such as Uber or Task Rabbit, accounted for 0.5 per cent of all workers in 2015.
In the United Kingdom, the study commissioned by the Department of
Business, Energy and Industrial Strategy (2017) found that 4.4 per cent of
the population had worked in the gig economy in 2017, although only 9 per
cent of this figure earned the majority of their income this way. In total then,
0.96 per cent of the working population in the United Kingdom were regular
gig workers. The multiple nation survey by Huws et al.(2017) revealed that
the number of adults who earned more than 50 per cent of their income in
the gig economy was 1.6 per cent of the population in the Netherlands, 5.1
per cent in Italy, 2.3 per cent in Austria, 2.5 per cent in Germany, 2.7 per
cent in Sweden, 2.7 per cent in the United Kingdom and 3.5 per cent in Swit-
zerland. Concerning this group, between 43 and 63 per cent regarded this work
as their main job. In the United Kingdom, for example, only 1.1 per cent of
workers were significant participants in the gig economy.
We included Australia in this analysis to understand how these small figures
compared to an advanced economy in a very different part of the world. The
Australian Bureau of Statistics (2017) shows that casual workers comprised
25.1 per cent of the total workforce, an increase from 23.5 per cent in 2012.
Much of this work is called full-time casualemployment, with large increases
in the hospitality industry in particular. But how many of these jobs are located
in the gig economy? A study commissioned by the New South Wales (NSW)
Peter Fleming et al.: On why Uber has not taken over the world 9
Department of Finance, Services and Innovation (2015) gives some estimates in
the state of NSW. It examined all variants of platform capitalism, including ser-
vices relating to transportation, accommodation, education, labour hire and so-
forth. It found that approximately 45,000 residents had earned income from gig
work in the last year (or 1.6 per cent of the NSW population), with an unknown
percentage of that relying on it as their sole source of income. We note that the
proportion of these residents engaging in labour-based platforms (which exclude
accommodation) would be smaller still. Business activity in the gig economy
consisted of 4 per cent of the overall accommodation industry and 2 per cent
of the point-to-point transport sector.
Why is the gig economy still tiny?
These studies of labour-based digital platforms in nine major OECD countries
clearly indicate that the percentage of workers involved in the sector is surpris-
ingly small when compared to excessive claims in the popular media. Sensa-
tional headlines about Uber colonizing the future of work are obviously
unwarranted. By the same token, there is clear evidence of growing job insecur-
ity and casualization in neoliberal economies (also see Kalleberg, 2018; Stand-
ing, 2017; Weil, 2017). This begs the question as to why the gig economy is
not at the forefront of that process. If employers could successfully apply gig-
based contracts to their workforce, we surmise, then many would be doing
so, taking advantage of enhanced workforce flexibility and scalability, shifting
the risk or economic volatility to workers, and limiting the need for capital
As we highlighted in the introduction, it would seem reasonable to assume
that some jobs are simply not amenable to digital platforms and self-employ-
ment. However, that cannot be the only reason for the modest percentages
since surely more than just 1.1 per cent of jobs (in the UK context, for
example) could theoretically be Uberized. Government regulation might also
be an impediment. But even in countries where the state is congenial to these
business models, the gig economy remains marginal. And given declining
union density in most of the countries we inspected, employee resistance to
Uberization does not provide a compelling explanation either.
Our paper posits another interpretation that we believe helps explain why the
gig economy remains so small. Like other critics, we contend that the so-called
sharing economy has little to do with sharing, especially when it comes to
labour-based digital platforms. It is instead an extreme variant of capitalism,
one that has been largely stripped of the vestiges of labour protection and regu-
lation, and thus rendering employment a rudimentary matter of market based
economic exchange between capital and labour. The adjective extremeregis-
ters the isolating, monetarized and hyper-controlled individualism that gig
work entails (also see Hill, 2015; Martin, 2016), marking it out as the logical con-
clusion of the liberalization and deregulation of employment that has
10 Economy and Society
characterized advanced capitalism to date (Baccaro & Howell, 2011). In other
words, the gig economy reflects the hallmarks of an abstract economic ideal
closely associated with neoclassical theory. As Griswold (2018, n.p.) observes
in relation to Uber:
Economists love Uber because it is the closest you can get to taking the pure
economic theory of [neoliberal] textbooks and summoning it to life. Uber
created a massive open market, governed first and foremost by the forces of
supply and demand. Along the way it broke up the taxi monopoly, taught
people to accept surgepricing, and ushered concepts long confined to econ
101 into the popular discourse.
This brings us to our key argument. While the gig economy is a good textbook
example of neoliberal economic theory applied to the real world of labour
exchange, it is in fact too pure, and thus largely unworkable as a standalone
entity. We suggest that labour-based digital platforms betray the limits of the
logic of contemporary capitalism itself, adumbrating the absolute threshold of
what economic agents can sustain. This is so not only from labours point of
view, but as we argue below, the business firms as well.
With the word limit, we register the boundary of an ideas application which
cannot be crossed without undermining that idea in practice. Take the example
of free market capitalismas celebrated by libertarian economists. A completely
free market society (liberated from all state intervention) would be impossible,
of course, because it would flounder on its own immanent limitations (since
Polanyi [1944] revealed long ago that so-called free markets require an active
state-formation in order to function). Some suggest that this intrinsic limit is
true of neoliberal capitalism more generally given its abstract and overtly-ideo-
logical character (e.g. see Duménil & Lévy, 2011; Harvey, 2015; Perelman,
2011). We agree, but believe that the gig economy presents a distinct and
exemplary manifestation of this tendency: based on its own axiomatic principles,
the gig economy if it were dominant simply could not reproduce itself in any
sustainable manner. Hence one reason, we contend, as to why labour-based
digital platforms have not been automatically rolled out across other industries
and sectors.
Let us now examine these limits in more detail.
Economic limitations
A number of features of labour-based digital platforms epitomize the extreme
ideals of neoliberal economic theory. The worker is largely decollectivized
and individualized, technically operating as an independent business owner.
Supply and demand (or surges) determine the nature and intensity of the
work. Labour is paid only for what they do in terms of task and time. Operators
take on full individual responsibility for their economic survival, absorbing
Peter Fleming et al.: On why Uber has not taken over the world 11
overhead costs and managing the exchange of effort/motivation. Furthermore,
trade unions are difficult to develop in this isolating environment, and in some
cases actively thwarted by gig firms and court rulings.
The hypothetical vision of an economic universe consisting only of indepen-
dent and self-sufficient individuals who compete in an open market pervades
the likes of Friedrich HayeksThe road to serfdom (1944), a seminal text in
the neoliberal canon (see Fleming, 2018; Mirowski, 2013). Uberization has
merely added a computerized search and matchapp and algorithm to techno-
logize the libertarian dream. Hayeks economic theories are notoriously abstract,
of course; hence why a very different reality is experienced by platform workers
when applied to the real world of commerce. Worker income is the most con-
spicuous discrepancy. In contrast to the rich entrepreneurnarrative thatsso
often used to legitimate the phenomenon, mounting evidence shows that gig
workers earn significantly less compared to others performing similar tasks in
both the regular and contingent economy (De Stefano, 2015; Kessler, 2018;
Scholz, 2016).
Five important points follow.
First, it is clearly difficult for platform workers to earn sufficient income in the
context of Western capitalism, especially with rising living costs (accommodation,
energy, food, education,etc.) in metropolitan areas (Zhang, 2016). Contrary to the
promise of micro-entrepreneurship, most gig workers do not possess enough
capital or proprietary technology to engage in entrepreneurial activity and are
instead relegated to the transactional workforce in an economic environment
blighted by widening inequality (Ahsan, 2018). Low income stems from a
business model that relies on self-employment to absorb most of the associated
costs and is designed to undercut traditional service providers on price. More-
over, linking wages to supply and demand in such a devout fashion also serves
to push down income. As heterodox economists have noted, most labour
markets (particularly concerning unskilled and semi-skilled jobs) cannot really
function according to the idealized doctrine of supply and demand, especially
during an economic downturn. That is because wages end up edging ever
closer to zero (see Galbraith, 2008, p. 154). As a result, the prospect of earning
a living solely as a platform-worker begins to look like an impossible task.
Second, given the economic precarity surrounding gig work, it is probable
that a significant motivation deficit will deter labour from participating in it
fully, particularly in economies where vestiges of the welfare state still offer
an alternative. Relatedly, it is unsurprising that, as the labour statistics discussed
earlier show, most participants use it as a supplementary or secondary source of
income. Hence, the relatively small figures in the data concerning full-time gig
workers. This gives the gig economy a rather parasitical flavour because it
indirectly relies on other forms of income (be it from less precarious work, gov-
ernment welfare, etc.) to function rather than being a self-sustaining sector in its
own right.
Third, those workers who do find themselves relying on labour-based digital
platforms for their primary source of income must be prepared to work
12 Economy and Society
unusually long hours in order to earn a livelihood. This is borne out by the fact
that surveys (in the United Kingdom, for example, see House of Commons,
Work and Pensions Committee, 2017a) find that a high percentage of gig
workers seek ever more hours. The sector demographically overrepresents
younger people (Huws et al., 2017), who are arguably better equipped to deal
with unpredictable and sometimes extreme periods of work, as well as take on
personal debt and have multiple jobs.
Fourth, the punitive management systems deployed by some firms (such as
penalizing courier drivers who fail to find a replacement in the event of their
absence) can add to the pressure to continue working. Here the limits of the
gig economy literally become physiological, as illustrated in the horrific case of
Don Lane, an independent courier driver for UK firm DPD (Booth, 2018).
Having been diagnosed with diabetes, Lane was unable to seek proper treatment
because the company fined him £150 per day if he could not arrange a replace-
ment. After collapsing several times at the wheel, he died in January 2018 having
worked at DPD for 19 years.
Fifth and finally, turning to the structure of the economy as a whole, the small
returns accrued to suppliers in the platform sector results in a minimal capacity
to generate system-wide value. In this sense, the old insight by John Maynard
Keynes (2007 [1936]) still rings true: workers are also consumers. The relatively
high wages of manufacturing workers in earlier decades generated consumption
patterns that sustained demand and economic growth, as illustrated in the
mythology of Henry Fordsfive dollar day. A decline in effective real wages
(and the labour share of GDP) will inevitably have a negative effect on wider
growth. The gig economy is the thin end of the wedge when it comes to a down-
ward cycle of declining wages, low demand and stagnating productivity. Using
the gig economy as a generalizable model in the economy would ironically
undermine capitalism rather than help it grow.
Socio-political limitations
In light of the economic unsustainability (from the workers perspective) of
labour-based digital platforms, a number of governments have recently realized
that although the gig economy offers cheap labour to (de facto) employers and
consumers, it can be fairly expensive to the state itself. A report by the UK gov-
ernment (2017) found that, like other low paid workers, those who participated
in the gig economy accessed welfare state provisions (such as healthcare on the
National Health Service), as one would expect. However, gig economy firms in
the United Kingdom make no National Insurance contributions because their
workforces are technically self-employed. Moreover, gig workers pay signifi-
cantly less tax contributions than regular job holders. The report concludes
that gig economy companies are free riding on the welfare state(House of
Commons, Work and Pensions Committee, 2017b). It is not an exaggeration
to deduce that if everyone was employed as gig workers then there would be
Peter Fleming et al.: On why Uber has not taken over the world 13
no universal healthcare and no universal pension scheme in Britain. This again
highlights the parasitical tendencies underscoring the gig economy; it depends
on institutional resources that lie beyond its organizational remit, and to which it
does not contribute, in order to operate.
This surfaces a number of socio-political limits inherent to labour-based
digital platforms. The first pertains to the negative ramifications that the gig
economy can have on the social and personal lives of its workers. Given the
pressure to work and the coercive management systems guiding the labour
process (via app-based technologies), family life, for example, inevitably
suffers. As Wood et al.(2019, p. 56) demonstrate, the control mechanisms
used in many gig jobs can lead to social isolation, working unsocial and irregular
hours, overwork, sleep deprivation and exhaustion. Overwork and fatigue are
not exclusive to the gig economy, of course. However, here we can note how
market individualism (the premium placed on economic self-reliance), author-
itarian control (punitive fines and obtrusive app commands) and financial des-
peration, all of which are relatively unremitting in the digital platform labour
process, can create severe negative externalities for workers, as the awful case
of Don Lane mentioned above indicates.
The second socio-political limitation necessarily follows from this: namely,
the conflict and industrial antagonism that gig work can incite between labour
and capital. For example, the large number of lawsuits that Uber has contended
with since 2009 is unusual and clearly a drain on the companys resources. In the
United States, the OConnor v. Uber Technologies, Inc and Yucesoy v. Uber
Technologies,Inc cases regarding driver misclassification (both pending at the
time of writing) could potentially see 250,000 drivers reimbursed for vehicle
costs and lost tips since 2013. In the United Kingdom, Uber v Aslam has also
challenged the self-employed status of drivers. Uber lost the initial case and
the subsequent appeal, but then appealed again to the Court of Appeal
(which it lost) and now the US Supreme Court (still pending).
Despite the state generally siding with platform providers in the neoliberal
West (e.g. see the US Supreme Court [2018] ruling regarding arbitration
clauses for contract workers), one could easily surmise that the social disruption
and political antagonism (not to mention considerable legal expenses) that
labour-based digital platforms attract might deter industry leaders/investors
in other sectors. It casts doubt not only on the scalability of digital capitalism
but even its future existence given current levels of legal contestation.
Indeed, the sheer number of court cases that Uber faces around the world (pro-
longed by interminable appeals) can easily give one the impression that the
world is going to war with Uber(Dickinson, 2018, n.p.).
Organizational limitations
The limitations discussed above are triggered by the negative externalitiesof
digital platforms. In addition, we suggest that Uberization is also dysfunctional
14 Economy and Society
and unsustainable on its own terms as a business model. That is to say, even in
the most favourable and propitious environments (where negative externalities
were minimal) the gig economy would still face severe difficulties in reprodu-
cing itself, making it unlikely that other industries and sectors would adopt
labour-based digital platforms. These organizational limitations have three
key features.
First, labour-based digital platforms clearly take a major cue from the neolib-
eral quest to de-professionalize occupations. This drive has a long lineage. For
instance, Milton Friedman (1980) famously argued that the American Medical
Association should not hold a monopoly over the certification of medical prac-
titioners. Private firms and individuals should also be able to offer their exper-
tise in an open, competitive marketplace, providing that customers were willing
to purchase such services. Similarly, Uber bypasses taxi training and certifica-
tion, flirting with the informal economy in ever contentious ways.
This absence of professionalization, although liberating organizations from
regulatory standards, invariably raises problems about safety and consumer con-
fidence. Passenger security was the main reason that London refused to renew
Ubers licence in 2017. This inherent weakness of platform capitalism also
extends to worker safety. For example, an Australian study of Airtasker
(which offers handyman services, among others) revealed unqualified personnel
being used to break up and dispose of asbestos (Unions NSW, 2018). It is easy
to see why many occupations that require expert qualifications and formal over-
sight (even of the most basic kind) would be legally, economically and morally
wary about reinventing themselves as gig-based service providers open to all,
posing a significant limit to its expansion.
Second, even if gig economy jobs could be successfully professionalized, the
use of self-employment (i.e. dealing with workers as isolated, independent
business owners) represents another barrier to their proliferation. When survey-
ing the rise of market individualism in the employment sector, Herbert Simon
(1991, p. 237) remarked that treating employees as independent windowless
Leibnizian monadsis a risky business strategy. In many cases, formal organiz-
ations are superior to open markets when it comes to managing labour power.
The social cohesiveness and cooperation that organizations foster tends to facili-
tate skill acquisition, sharing of tacit knowledge (especially team work), the
coordination and motivation of staff and overall goodwill. By contrast, gig
work lacks continuity and opportunities for holistic worker development,
undermining complex problem solving abilities and the elicitation of discretion-
ary effort from the workforce (Kessler, 2018). For gig firms, productivity
increasingly depends on the platforms ability to embed inducements into
their reward structure and utilize electronic monitoring to sanction deviant be-
haviour, which is far less reliable than traditional organizational controls (Fried-
man, 2014).
Digital platform firms clearly recognize this problem. They are ideologically
smitten by the undiluted ideals of Hayekian market individualism, but want to
have their cake and eat it too. On the one hand (or formal level), gig firms seek to
Peter Fleming et al.: On why Uber has not taken over the world 15
avoid the costs/risks/responsibilities associated with regular employment (since
these have been socialized through market forces as Hayek encouraged). On the
other (or informal level), they desire a highly controlled, pliant and dependent
workforce, deploying an unprecedented surveillance system to achieve this end.
A firm like Lyft gets away with it, but probably only just. In many industries,
we aver, the contractual and task sequestration engendered by quasi self-
employment would simply hamper organizational effectiveness and customer
trust. This is illustrated by non-gig firms, in the taxi industry, for example,
appropriating technologies used by platform companies, but minus the Lebnit-
zianemployment arrangements. Here the same technology is successfully inte-
grated into a regular or contingent workforce, providing customers with a
security premiumcompared to services sourced in the gig economy.
The third organizational limit of Uberization pertains to the considerable role
that speculative capital has played in shaping the contours of the gig economy,
especially the major corporations involved (Langley & Leyshon, 2017). While
the innovativeness of this business model initially attracted significant venture
capital and equity, overall performance has been patchy to say the least. For
example, to date Uber and Lyft have never recorded profits, choosing instead
to pursue high-growth business strategies and draw on sizable cash reserves
to stay afloat (Sherman, 2017).
In this respect, platform capitalism (as represented by the corporations that
dominate it) is beginning to look more like a risky speculative experiment
conducted by wealthy plutocrats rather than a sound business proposition
with a durable future (Airbnb is a rare exception among unicornstart-ups
given its profitability, but recall we are only dealing with labour-based
digital platforms in this paper). Industry reluctance to adopt labour-based
digital platforms is perhaps reinforced by the corporate finance strategy
pursued by its major players: the need for excessive speculative investment,
an expectation of long-term losses and an almost myopic growth-focused
approach that is risky and without a proven track record apropos economic
Conclusion: if Uber isnt our future then what is?
In light of the preceding analysis, our argument can be encapsulated as thus:
platform capitalism represents the limit of the trajectory that economies in the
United States, United Kingdom and Australia have followed since the 1980s
in terms of employment. The gig economy reflects an unadulterated and
idealistic version of capitalism as far as the labour market is concerned;
indeed, it is so extreme that for many, if not most, states, workers and
employers, it has pushed the possibilities of neoliberalism beyond what can
be deemed reproducible or sustainable. We contend that this is a major
reason why labour-based digital platforms and gig jobs have not proliferated
more thoroughly.
16 Economy and Society
What does our argument mean for the future of work, if indeed that future
doesnt consist of labour-based digital platforms becoming a widespread
phenomenon? It might be tempting to infer from our paper that if gig jobs rep-
resent an extreme version of capitalism, then other forms of contingent work
(like casual, part-time, freelance and agency jobs, for example) are somehow
more moderate and employee-friendly by comparison. We do not support
that inference; precarious jobs too often involve exploitation, low wages and
abusive management hierarchies (see Kalleberg et al., 2000). They do not,
however, apply to the letter the abstract ideals of neoclassical theory in the
same uncompromising manner that gig jobs do. Most low-paid contingent
jobs actually necessitate features that (partially, at least) override the private
individualism of anonymous market relations so ardently lionized by neolib-
erals. This does not make them any less exploitative, of course; far from it.
While gig jobs themselves are not propagating, the ideology of the gig
economy and what it implies for the wider workforce clearly is. In this sense,
it is not simply the number of gig jobs that matter; more importantly, it is
the expectations that labour-based digital platforms instil among employees in
the rest of the economy that is troubling. A recent UK study found, for
example, that an oppressive feeling of precariousness has quietly descended
over most occupations, regardless of whether they are in the gig economy or
not. Around 70 per cent of workers are worried about their employment situ-
ation: economic insecurity now stretches right throughout our labour
market, including within jobs that appear safe on the surface(Balaram &
Wallace-Stephens, 2018, n.p.). Culturally then, Uberization may operate in
an insidious fashion, not only by exploiting its immediate (albeit small) work-
force but by also casting millions of other jobs in a doubtful light. All of a
sudden hard won rights look like questionable privileges.
Renewed regulation and legislative efforts are clearly required to reign in the
gig economy. While there are indications that municipal and national authorities
have started to do this, most have focused on environmental externalities (e.g.
pollution) and, in the case of ride sharing platforms, addressing passenger
safety concerns. For example, the European Court of Justice ruled in 2018
that Uber was a transport company and not a platform match service, thereby
opening its operations to driver background checks and vehicle licensing
requirements and inspections (Khan, 2018). Large North American cities
such as New York City, Los Angeles and Toronto, have recently moved to
impose congestion taxes on vehicles driven in the metropolitan area in response
to growth in Uber and other ride sharing vehicles.
Regulations of this sort are relatively innocuous and may even be welcomed
by labour-based digital platforms given the veneer of legitimacy they can confer.
However, governments and courts have been more reluctant to alter legal fra-
meworks defining the employment status of workers in the gig economy and/
or their rights to collective bargaining and work-based benefits (Collier et al.,
2017). While we sympathize with scholars who have criticized the master-
servantbifurcation inherent in todays employment law that classifies
Peter Fleming et al.: On why Uber has not taken over the world 17
workers as either employees at the mercy of employers or as independent con-
tractors(Harris & Krueger, 2015; Lobel, 2017, p. 65), we do not see the cre-
ation of a third category of dependent contractors/independent workersas
an adequate solution.
Our contribution to this discussion emphasizes the intrinsic limits of the
labour-based platform business model. It is simply unable to reproduce itself
for important reasons. A largely unreformed continuation of the gig economy,
therefore, can only have a sapping and corrosive effect on the wider socio-econ-
omic system that props it up. As such, it certainly should not act as a template,
either concretely or symbolically, for the employment sector as a whole. For us,
this observation provides a strong case for legislative reforms that guarantee uni-
versal rights such as freedom of association, collective bargaining and access to
workerscompensation and health/safety benefits. The judicial viability of this
will depend on pre-existing legal norms, of course, since labour laws in the
United States and Europe, for example, can vary significantly (see Thelen,
2018). Nonetheless, such legislative reforms would not only counter platform
companiesabuse of gaps in the governance of emergent forms of economic
activity, but more importantly, they might also begin to redress the alarming
growth in the casualization of work more generally. In the absence of such
reforms, while it is highly unlikely that Uberization will usurp regular work
as conventionally believed, we can still expect it to have an unfavourable influ-
ence on the rights of workers far beyond its own immediate sphere.
Disclosure statement
No potential conflict of interest was reported by the authors.
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Additional Questions in the 2017 Contingent Worker Supplement of the
Current Population Survey
Q1 Some people find short, IN-PERSON tasks or jobs through companies that
connect them directly with customers using a website or mobile app. These com-
panies also coordinate payment for the service through the app or website.
For example, using your own car to drive people from one place to another,
delivering something, or doing someones household tasks or errands.
Does this describe ANY work (you/NAME) did LAST WEEK?
Q1a Was that for (your/NAMEs) (job/(main job, (your/NAMEs) second
job)) or (other) additional work for pay?
Q2 Some people select short, ONLINE tasks or projects through com-
panies that maintain lists that are accessed through an app or a website.
Peter Fleming et al.: On why Uber has not taken over the world 21
These tasks are done entirely online, and the companies coordinate payment
for the work.
For example, data entry, translating text, web or software development, or
graphic design.
Does this describe ANY work (you/NAME) did LAST WEEK?
Q2a Was that for (your/NAMEs) (job/(main job, (your/NAMEs) second
job)) or (other) additional work for pay?
Peter Fleming is Professor at UTS Business School in Sydney, Australia. His research
focuses on the transformation of work and employment in the era of neoliberal capitalism.
He is the author of several books on related topics, including The death of homo economicus
(2017, Pluto) and Sugar daddy capitalism: The dark side of the new economy (2019, Polity
Carl Rhodes is Professor of Organization Studies at UTS Business School in Sydney,
Australia. His research critically investigates ethico-political dimensions of organizations
and working life, with a special focus on justice, equality, resistance, dissent and democ-
racy. His most recent books are Disturbing business ethics: Emmanuel Levinas and the poli-
tics of organization (Routledge, 2019) and CEO society: The corporate takeover of everyday
life (Zed, 2018, with Peter Bloom).
Kyoung-Hee Yu is Associate Professor at UTS Business School in Sydney, Australia.
Kyoung-Hees research has focused on institutional and organizational change processes
affecting work and employment. Her recent work has examined collective action and
politics in institutional change, the international mobility of workers and issues of
inclusion, and comparative employment relations in Asia. Kyoung-Hees work has
been published in Organization Studies, the British Journal of Industrial Relations,
Human Relations, and Work, Employment & Society.
22 Economy and Society
... It is related to neoliberalisation, since some of the more prominent platforms (Uber again) not only advocate the weakening of worker protections but also fascinate market-fundamentalist thinkers (Moazed and Johnson, 2016). It is related to marketisation since coordination within the app takes place via competition (Fleming et al, 2019;Greer and Umney, 2022), and the market becomes more customer facing, disrupting the social protections that might level the competitive playing field or redistribute income towards workers. ...
... The key point is that in many of these sectors, in many local, national and online markets, the platform model exists only on the margins. However, at present, with isolated exceptions (for example, Fleming et al, 2019;Azzellini et al, 2022), there is little scholarship which specifically examines the organisational limits of platformisation. In the Book a Tiger example, the platform model faced problems not necessarily connected to the availability of investors, or of institutional context, but primarily organisational challenges related to the contingencies of the industry and the task it was seeking to perform -to which the platform was not well-suited. ...
... The starting point is the failure of large platforms like Uber to make a profit. The outstanding example of this is Fleming et al (2019), who draw on Polanyi to argue that the 'pure' marketisation to which platforms aspire is an ineffective method to coordinate work. This helps explain why so many platforms fail to make a profit, and why some switch to directly employing people independently of the actions of workers or regulators, for example in response to business problems. ...
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This article examines the assumptions behind the sociology of work and industrial relations literature on online labour-based platforms. This literature has critically examined working conditions and worker resistance in platform work, but it has done so without criticising what we call the ‘metanarrative of the platform economy’. This metanarrative enables a weaving together of platform work with broader trends such as precarisation, neoliberalisation, financialisation and marketisation, but it makes it difficult for scholars to explain the small size of the platform workforce or to understand the diverse forms that platforms take. We argue that in order to understand the limits and diversity of platforms it is important to understand the inherent problems of platforms as capitalist business models. We suggest a research agenda that decentres some of the better-known platform models (ridesharing and food delivery) and carries out in-depth studies of work and exchange in other sectors.
... Uberization can be defined based on five characteristics: a shift in the competitive landscape with new digital players (Freeman, 2015;Daidj, 2017;Viot, 2018), the use of digital capacities as catalysts (Fichman et al., 2014;Viot, 2018), the introduction of business model innovations with platform business models (Viot, 2018;Jin and Shin, 2020;Li et al., 2021), the offer of an equivalent service delivered at a lower price (Viot, 2018;Apte and Davis, 2019), and the use of crowd workers who rely on digital platforms and their own resources for paid word (Fleming et al., 2019). If traditional companies fear being uberized (Cen et al., 2016;Kane, 2018), the real impact of uberization on manufacturers also depends on their ability to navigate with transformations induced by the digital turn to I4.0. ...
... Fifth, uberization relies on crowd workers providing a service based on their own resources (e.g. a car with transportation services, a bike with food delivery companies) and using a digital platform (Fleming et al., 2019). In their study about the company Uber and the future of work, Fleming et al. (2019) connect uberization to the phenomenon of 'crowd workers' (p. ...
... Fifth, uberization relies on crowd workers providing a service based on their own resources (e.g. a car with transportation services, a bike with food delivery companies) and using a digital platform (Fleming et al., 2019). In their study about the company Uber and the future of work, Fleming et al. (2019) connect uberization to the phenomenon of 'crowd workers' (p. 8) defined as the population using digital platforms for paid work. ...
The transformations generated by Industry 4.0 (I4.0) are interwoven with digitalization. I4.0 involves the digital turn of manufacturing companies, changing the way they operate, their business models, and by extension, their interaction with digital players. Nonetheless, the future of I4.0 regarding its interaction with digital players and the phenomenon of uberization has scarcely been examined. Thus, this research adopts a participatory and systemic foresight approach to explore the trajectories of I4.0 in the face of uberization. The study was conducted with a working group of 22 members from academia and practice. Four scenarios and related action plans were produced. The results emphasize that uberization is not necessarily a process to be endured by manufacturers, but it could be chosen or even co-constructed with different actors if manufacturers address key challenges such as rethinking their business models and adapting their factors of production. The scenarios indicate the dynamics of uberization as contingent on technological developments and on industrial policy choices, changes in consumer behavior, and access to multiple funding sources. Finally, the study provides practical implications regarding the dynamics of collaboration between SMEs and large groups, on one hand, and between manufacturing companies and digital players, on the other hand.
... (Urry 2007, Freudendal-Pedersen and Kesselring 2018, Kesselring et al. 2020 In case one would have to single out an emblematic form of sharing mobilities it probably would be Uber. (Fleming et al. 2019, Rosenblat 2019 Uber is an example for something commonly known as ridesharing. ...
... (Cohen and Kietzmann 2014) However, the history of Uber has many controversies around the working conditions of the drivers and the actual environmental benefits it creates. (Tcholakian 2017, Balding et al. 2018, Fleming et al. 2019) Another controversial example for commercialized sharing mobilities are bikesharing systems, which increasingly exist in many cities around the world. (Shaheen, Guzman, et al. 2012) Bikesharing has its roots in the anarchist scene of Amsterdam of the mid-1960s and came into global appearance when advertisement companies discovered the potential to combine a supposedly sustainable form of transportation with their interests in gaining advertisement space in cities. (Tironi 2014) In recent years sharing mobilities expanded to nearly every other vehicle, e.g. ...
... In view of these developments, there is burgeoning interest in what the proliferation of a business model based on outsourcing means for the economy. Most works in this area, however, have focused on how consumers and labor are impacted (Judd and Krueger Alan 2016;Thor et al. 2018;Hall et al. 2018;Peter et al. 2019). This study looks at the business itself by considering whether young firms could and should grow in this way. ...
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This paper empirically explores the nexus between the intensity of outsourcing by an entrepreneur and its ability to scale up in size. Intensity is measured as a continuous index to proxy for the share of jobs being contracted out. Using a non-parametric Cox proportional hazard model, the paper estimates the odds that a firm grows into a medium or large firm as a function of outsourcing intensity. Two strategies stand out. In one case, the firm contracts about 10 per cent of its workforce and doubles its chance of scaling up. In the second case, the firm contracts more than 90 per cent of its workforce and the odds go up by 2.5 times. A priori, firms in both groups are indistinct in many ways, except that firms choosing to grow with minimal outsourcing show early signs of growth. The latter firms grow to larger sizes, create more jobs, pay higher wages, and are more likely to export and conduct research. Firms growing by extreme outsourcing are only apter at surviving. Resource-based view of firms and management capability seem to be part of the explanation for the observed behavior.
... They require conventional organizational structures. Fleming, Rhodes, and Hu (2019) showed this using a thought experiment whereby a business school employs teaching staff via an Uber app. Unsurprisingly, sheer chaos ensues. ...
... The mobilisation of surplus labour to carry out tasks on a piecework basis done by fewer full-time employees tends to create a relative labour surplus, leading to the intensification of competition among workers (Standing, 2016). The dominant narrative of flexibility and freedom in the 'sharing economy' also deviates from the reality in which labourers feel compelled to work long hours to compensate for the low hourly income and precarious position (Fleming et al., 2019). This further intensifies the competition in the labour market that only benefits the platform capital. ...
This paper addresses the questions of corporate power represented by digital platforms. We undertake a conceptual analysis of platform power so that it can provide an explanation of key motivations and behaviours for monopolisation in the platform economy. We argue that there emerges a hierarchical power structure in which platform companies relentlessly pursue power over users, and small platforms increasingly depend on big tech and financial capital. Drawing theoretical insights from the monopoly capital school and empirical evidence from platform companies in China, this paper further explores the macroeconomic implications of platform monopolisation and financialisation. It is demonstrated that the hierarchical power structure in the platform economy may increase income inequality, exacerbate overcapacity and generate financial instability.
... Yet, three considerations weigh against extrapolating from this the demise of bureaucracy. First, it is far from clear that this platform-based "free agent" model will prevail outside a limited band of activities where work can be so rigorously individualized (Fleming, Rhodes, & Yu, 2019). Second, Uber relies on a centralized scheduling system and close prescription and monitoring of the work of its drivers. ...
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This study examines the relationship between the online labour force and real economic factors. Since the Online labour index is one of the main determinants of the GIG economy, this study also reveals which macroeconomic variables the GIG economy is based on. The aim of the study is to determine the effect of real economic factors (unemployment, economic growth, inflation) on the count of online platform users. As a result of the econometric analysis conducted with Turkey's data set for the period of June 2017 -January 2021, it has been determined that real economic factors have a statistically significant effect on the count of online platform users. According to the results of the analysis, the increase in unemployment rate and economic growth will cause an increase in the count of online platform users, while increase in inflation will cause an opposite effect.
Purpose The purpose of this study is to deepen our understanding of the well-being of transient organizations/groups and to use this to develop a novel conceptual framework of gig worker well-being during times of crisis. Design/methodology/approach A qualitative approach was adopted combining in-depth semi-structured interviews and daily diaries. Twenty-two workers working in the sharing economy were recruited. Thematic analysis was conducted for the diary and interview data. Findings The findings illustrate a complex picture of sharing economy workers’ four dimensions of well-being, including physical, subjective, psychological and social well-being. A number of the COVID-19 pandemic contexts, such as more time, restriction, economic recession and uncertainty, were seen to influence these workers’ well-being in different ways including both positive and negative impacts. The precarious nature of gig work within the sharing economy was also found influential, which includes flexibility, uncertainty, temporality and diversity. Furthermore, the specific contexts of the hospitality, tourism and event industry (such as labor-intensive, low esteem, self-value and purpose in life) had also impacted gig workers physical and psychological well-being in various ways. Research limitations/implications This study complements the gig workers’ view of the sharing economy by investigating their well-being during the COVID-19 pandemic. In addition, this study reveals the complex and various influences hospitality, tourism and events industry contexts made, amplified by the pandemic. Methodologically, the daily diary approach applied in this research has captured gig workers’ instant feelings and thoughts, which enriches the current understanding of gig workers’ well-being. Practical implications From the findings and the newly developed conceptual framework, practical implications are proposed focusing on how the tourism, hospitality and event industries should look after their gig workers’ well-being in the COVID-ized environment. From the physical well-being perspective, businesses should consider partnering with gym operators to provide corporate packages or discounted membership to their gig workers. From psychological well-being perspective, a recognition system integrating gig workers would be useful to strengthen gig workers’ perception of value in their jobs. In addition, technology can be used to introduce more resources to their gig workers, particularly when distancing. Originality/value A conceptual framework is developed, which captures the influence of both “internal” and “external” determinants of gig worker well-being during times of crisis. This research contributes to theory by developing a framework of well-being in the context of the sharing economy, as well as explicitly addressing how the uncertainty and precariousness of sharing economy work and the hospitality, tourism and event industry contexts relate to well-being. This model is likely to have applicability beyond COVID-19 as the pandemic made clear many existing challenges – rather than just simply creating new ones.
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This article evaluates the job quality of work in the remote gig economy. Such work consists of the remote provision of a wide variety of digital services mediated by online labour platforms. Focusing on workers in Southeast Asia and Sub-Saharan Africa, the article draws on semi-structured interviews in six countries (N = 107) and a cross-regional survey (N = 679) to detail the manner in which remote gig work is shaped by platform-based algorithmic control. Despite varying country contexts and types of work, we show that algorithmic control is central to the operation of online labour platforms. Algorithmic management techniques tend to offer workers high levels of flexibility, autonomy, task variety and complexity. However, these mechanisms of control can also result in low pay, social isolation, working unsocial and irregular hours, overwork, sleep deprivation and exhaustion.
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The advent of the sharing/gig economy has created new forms of employment embedded in new labor practices. Advocates of the sharing economy frame it in salutary terms, lauding its sustainability, decentralization, and employment-generation capabilities. The workers of the gig economy are seen as independent contractors under law rather than employees, and the owners of the gig economy platforms celebrate this categorization as a form of entrepreneurship. In this paper, we use insights from the entrepreneurship literature to examine this claim critically. Taking Uber as an exemplar, we look at the arguments behind the company’s contention that its drivers are actually “partners” who are engaged in entrepreneurship, and demonstrate why these claims are problematic. We utilize a stakeholders’ theory framework that initiates a dialogue between ethics and entrepreneurship in order to focus on the mechanisms that help ensure ethical practices in the sharing economy and to examine the efficacy of these mechanisms. We also discuss the role of the entrepreneurship literature in promoting entrepreneurial behaviors that lead to income inequality. We conclude by arguing that the sharing economy reflects the intensification of an ongoing neoliberal trend that misuses the concept of entrepreneurship in order to justify certain forms of employment practices, and make a case for regulatory oversight.
This book discusses the transformation of firms into platforms-companies providing software and hardware products to others-that has occurred in many economic sectors. This massive transformation resulted from switching capitalism into data, considering them as a source for economic growth and resilience. Changes in digital technologies contributed much to the relationships between companies and their workers, clients, and other capitalists, who increasingly began to rely on data. Dr. Nick Srnicek critically reviews "platform capitalism", putting new forms of the business model into the context of economic history, tracing their evolution from the long downturn of the 1970s to the economic boom of the 1990s and to the consequences of the 2008 financial crisis. The author demonstrates that the global economy was re-divided among a few of the monopolistic platforms and shows how these platforms set up new internal trends for the development of capitalism. © 2019 National Research University Higher School of Economics. All Rights Reserved.
To monitor trends in alternative work arrangements, the authors conducted a version of the Contingent Worker Survey as part of the RAND American Life Panel in late 2015. Their findings point to a rise in the incidence of alternative work arrangements in the US economy from 1995 to 2015. The percentage of workers engaged in alternative work arrangements—defined as temporary help agency workers, on-call workers, contract workers, and independent contractors or freelancers—rose from 10.7% in February 2005 to possibly as high as 15.8% in late 2015. Workers who provide services through online intermediaries, such as Uber or TaskRabbit, accounted for 0.5% of all workers in 2015. Of the workers selling goods or services directly to customers, approximately twice as many reported finding customers through off-line intermediaries than through online intermediaries.
I use the case of the transportation network company Uber as a lens to explore the comparative politics of the platform economy in Europe and the United States. Within the advanced capitalist world, different countries have responded in very different ways to this new service, from welcome embrace and accommodating regulatory adjustments to complete rejection and legal bans. I analyze Uber’s arrival and reception in the United States, Germany, and Sweden, documenting three very different responses to this disruptive new actor. I show that conflicts over Uber centered on different issues in the three countries. These differences were consequential because the specific regulatory “flashpoints”that Uber provoked mobilized different actors, inspired the formation of different coalitions, and shaped the terms on which conflicts over Uber were framed and fought.
Undoing democracy : neoliberalism's remaking of state and subject -- Foucault's birth of biopolitics lectures : the distinctiveness of neoliberal rationality -- Revising Foucault : homo politicus and homo oeconomicus -- Disseminating neoliberal rationality I : governance, benchmarks and best practices -- Disseminating neoliberal rationality II : law and legal reason -- Disseminating neoliberal rationality III : higher education and the abandonment of citizenship -- Losing bare democracy and the inversion of freedom into sacrifice.
Neoliberalism--the doctrine that market exchange is an ethic in itself, capable of acting as a guide for all human action--has become dominant in both thought and practice throughout much of the world since 1970 or so. Writing for a wide audience, David Harvey, author of The New Imperialism and The Condition of Postmodernity, here tells the political-economic story of where neoliberalization came from and how it proliferated on the world stage. Through critical engagement with this history, he constructs a framework, not only for analyzing the political and economic dangers that now surround us, but also for assessing the prospects for the more socially just alternatives being advocated by many oppositional movements.
This book was originally published by Macmillan in 1936. It was voted the top Academic Book that Shaped Modern Britain by Academic Book Week (UK) in 2017, and in 2011 was placed on Time Magazine's top 100 non-fiction books written in English since 1923. Reissued with a fresh Introduction by the Nobel-prize winner Paul Krugman and a new Afterword by Keynes’ biographer Robert Skidelsky, this important work is made available to a new generation. The General Theory of Employment, Interest and Money transformed economics and changed the face of modern macroeconomics. Keynes’ argument is based on the idea that the level of employment is not determined by the price of labour, but by the spending of money. It gave way to an entirely new approach where employment, inflation and the market economy are concerned. Highly provocative at its time of publication, this book and Keynes’ theories continue to remain the subject of much support and praise, criticism and debate. Economists at any stage in their career will enjoy revisiting this treatise and observing the relevance of Keynes’ work in today’s contemporary climate.