Working PaperPDF Available
September 2017
Ruth Berins Collier, V.B. Dubal, and Christopher Carter
Labor Platforms and Gig Work: The Failure to Regulate
Cite as: Ruth Berins Collier, V.B. Dubal, and Christopher Carter. (2017). “Labor Platforms and Gig Work: The
Failure to Regulate”. IRLE Working Paper No. 106-17.
Labor Platforms and Gig Work:
The Failure to Regulate*
Ruth Berins Collier
University of California, Berkeley
V.B. Dubal
University of California, Hastings College of the Law
Christopher Carter
University of California, Berkeley
September 2017
* We gratefully acknowledge the assistance of Anna Callis.
Since 2012, the platform economy has received much academic, popular,
and regulatory attention, reflecting its extraordinary rate of growth. This
paper provides a conceptual and theoretical overview of rapidly growing
labor platforms, focusing on how they represent both continuity and
change in the world of work and its regulation. We first lay out the logic of
different types of labor platforms and situate them within the decline of
labor protections and the rise of intermediated employment relations
since the 1970s. We then focus on one type of labor platformthe on-
demand platformand analyze the new questions and problems for
workers and the political problem of labor regulation. To examine the
politics of regulating labor on these platforms, we turn to Uber, which is
the easiest case for labor regulation due to its high degree of control over
work conditions. Because Uber drivers are atomized and ineffective at
organizing collectively, their issues are most often represented by
surrogate actorsincluding plaintiffsattorneys, alt labor groups, unions,
and even Uber itselfwhose own interests shape the nature of their
advocacy for drivers. The result of this type of politics, dominated by
concentrated interests and surrogate actors, has been a permissive
approach by regulators in both legislative and judicial venues. If labor
regulation has not occurred in this “easy” case, it is unlikely to occur for
gig work on other labor platforms.
Since 2012, the platform economy has received much academic, popular, and regulatory
attention reflecting its extraordinary rate of growth. While this growth is typically
presented in terms of the capitalization of platform companies, equally impressive is the
growth in individuals who earn money on the platform. Analysts estimate that monthly
participation grew ten-fold from October 2012 to September 2015. While this constitutes
only 1 percent of adults in the United States, the cumulative participation rate reached
4.2 percent by the end of that period. In this paper, we analyze the nature of platform
work and the politics of regulating it, focusing our study on a subset of these platforms,
specifically labor platforms, which connect workers with “requesters” for specific tasks of
varying lengths of time.1 In 2013 and 2014 the annual growth rates of labor platforms
ranged between 300 and 400 percent. While the growth rate has since slowed, it
continues to be robust.2
1 The other kind of platform included in this growth analysis is capital platforms in which people
sell goods or rent assets. The Online Platform Economy. (JPMorgan Chase Institute 2016: 3).
2 “The Online Platform Economy: What is the Growth Trajectory?” (JPMorgan Chase Institute
Along with rapid growth have come a number of regulatory issues concerning the world
of work these platforms generate. While labor platforms are often seen as disruptive, in
many ways they represent a continuation of earlier trends: the restructuring of capital to
achieve new employment relations, including new forms of “intermediated” employment
relations, and a shift to alternative or contingent forms of employment, unprotected by
employment and labor laws.
Labor platforms not only accelerate this trend, but also compensate for it, by providing
supplemental work to jobs that yield inadequate income or irregular hours. They also
relate both to other pathologies and to new forms of dynamism in the economy by, for
instance, compensating for inadequate pensions and retirement savings and providing
income for start-up entrepreneurs.
This paper provides a conceptual and theoretical overview of these rapidly growing
platforms, focusing on how they represent both continuity and change in the
transformation of the world of work and its regulation. We first lay out the logic of
different types of labor platforms and situate them within the decline of employment
relations and labor protections since the 1970s. We then focus our analysis on one type
of labor platformthe on-demand platformwhich poses new questions and problems
for workers and the political problem of regulating labor. Finally, we examine the case of
Uber, which in many ways is the easiest case for labor regulation.
Ultimately, as we show, little has been done to regulate Uber in a way that advances
drivers’ rights and benefits. As a dispersed, atomized interest group, drivers have been
mostly unable to mobilize collectively and to make effective claims in legislative arenas,
where concentrated interests are the predominant voices. Instead, drivers have, at
times, been mobilized in legislative arenas by surrogates, such as unions and alt-labor
organizations. Uber has also mobilized drivers but not on labor issues. While workers’
issues are largely ignored in legislative arenas, they have been taken up in courts, but
again primarily by surrogatesplaintiffs’ attorneys, who take the initiative in bringing
suits. All of these surrogates bring their own interests that shape their advocacy and
skew the representation of drivers’ interests. The result of a politics dominated by
concentrated interests and surrogate actors has been a permissive approach by
regulators that aims to encourage technological innovation and growth not only of the hi-
tech sector, but also of the “gig economy” in which workers engage in flexible, but
unprotected labor.3
Labor, or labor-brokerage, platforms are those that cybercoordinate the market of a
service worker and a requester of work for a defined task or project. The task or project
may last anywhere from a few minutes to several weeks. Workers are generally
considered to be independent contractors, rather than employees, and as such, are not
3 We define a gig worker as an independent contractor unprotected by employment and labor
laws, who is contracted by the task or project. Some definitions refer specifically to those who
offer their labor “through a digital marketplace” (Torpey and Hogan 2016).
covered by existing employment and labor laws.4 In this section, we examine both the
ways in which platform-coordinated work builds upon existing trends in the move to
contingent labor and the ways in which it is new. We also look at the nature of gig work
and the problems posed by “mediated” employment relations. Rather than the older
bilateral relations between worker and employer, these are trilateral relations, in which
the platform mediates the relationship between the worker and the user of that work.
Labor platforms are a type of “multi-sided platform,which have been analyzed as firms
that create value by facilitating the interaction between two groups with network benefits
(Evans and Noel 2007; Evans 2003). However, for the present purpose of analyzing
labor platforms, we find it useful to think of them within the larger context of restructuring
work relations and the trend toward mediated employment relationsa move often
undertaken by firms precisely to avoid the regulations and responsibilities that employee
relations entail.
Platform Labor as Contingent Work
“Disruption” and “creative destruction” have become omnipresent terms that arise in
discussions of the platform economy. These descriptors are often used to approve of
and justify the new developments. Yet one should be clear about what isand is not
being disrupted. Labor platforms provide more opportunities for gig work and make it
more efficient; however, they neither create a new world of work nor fundamentally
disrupt an existing pattern of employment relations.
Rather, labor platforms should be viewed as a step in a longer pattern of sectoral or firm
restructuring and a continuing dualization of the labor market: the growth of various
forms of “alternate,” contingent, or contract workers, who do not have the rights or social
protections of “employees,” as per employment and labor laws. Within that history of
restructuring, which began with economic globalization and the technological innovations
of the 1970s and 1980s, the platform economy takes two further steps. First, big data
and the algorithmic revolution have enabled a cyber-coordinated labor market, giving the
employer tools to intensify, accelerate, and expand the market for contract labor.5
Second, the spread of smartphone technology has enabled the possibility of labor
platforms, particularly on-demand platforms (see below), which are the focus of the
current study.
An interesting analysis of this recent but longer term history of capital and labor
restructuring is that by David Weil (2014), who analyzes what he calls the fissured
workplace, resulting from strategies of firms to shed in-house workers. Weil’s analysis
points to two important effects of this restructuring. First, it changes how gains are
shared, with fewer gains going to workers (76). Whereas wages were set with some
regard for notions of fairness in the old system of an “internal labor market,” the
restructured firm is concerned only with minimizing costs (83f). Responsibility for worker
4 Workers on a few platforms are considered employees.
5 These tools are not limited to contract labor or the platform economy. Employers use dynamic
just-in-time scheduling of workers to coincide with the ebb and flow of demand on very short
notice (and often insist that they be available in order to stay on the roll). Big data analytics have
also expanded the tools for analyzing and monitoring work. See Gleason and Lambert 2014,
Kaplan et al. 2015, Benn 2016.
protection and social costs are shifted out of the firm. Second, with fissured restructuring
a firm maintains an arms-length or mediated relationship with workers.
Beyond the specific types of fissuring analyzed by Weil, a larger trend in the US has
been a shift from full-time, regulated, and protected employment to a casualization and
informalization of work and a demutualization of risk. A number of studies have pointed
to the increase in contingent or “non-standard” work, such as temp-agency workers,
direct-hire temps, and independent contractors.6 This sector of the workforce grew 75
percent faster than the overall workforce from 1980 to 1993 (Belous 1995: 863, 867;
Middleton 1996: 557, 564), and by 1995, contingent workers constituted about 32
percent (Weil 2014: 272).
Explanations of this change in the nature of work are rooted in both the demand and
supply side of the labor market. Employers have turned to contingent work as firms
have altered their strategies in response not only to globalization and technology, but
also to legal and regulatory incentives (Befort 2002). At the same time, there has been
some increase in demand for this work, particularly for the purposes of achieving work-
family balance, supplementing stagnant wages, compensating for unemployment, and
coping with “just-in-time” work.
With respect to employment trends, then, the labor platform economy is not so
“disruptive.” Rather, the work “flexibility” and, in most cases, the independent contractor
model of most labor platforms in the gig economy are a continuation and an acceleration
of more general developments in the nature of work. Little data is available to assess the
size contribution of the platform economy to the more general trends (Bernhardt 2014).
After robust growth in the period from 1980 to 1993, the relative size of the larger
category of alternative work showed little change in the following decade, 1995-2005
(Weil 2014: 272; Katz and Krueger 2016: 3). However, growth subsequently took off.
Katz and Krueger calculate a 50 percent increase from 2005-2015 in the number of
individuals using alternative work as their primary work, accounting for “all of the net
employment growth in the US economy (7). The timing of this growth corresponds to
the Great Recession and the subsequent recovery. Using this same data, we calculate
that platform work constitutes about one fourth of this recent growth of contingent work.
This figure, however, underestimates the total growth in platform workers because most
participants do not use the platform as their primary source of income (JPMorgan Chase
Institute 2016: 24).
The growth in platform gig work not only contributes to the trend toward part-time, short-
duration, and low-wage jobs in the US economy, but also importantly supplements and
compensates for these developments in the off-line labor market. Platform gig work is a
form of flexible employment that is available to a worker between, “around,” or in
addition to other jobs that have disappeared, are themselves irregular or “flexible,” or are
inadequate sources of income. As offline work becomes more unstable and precarious,
the platform economy, with its tremendous increase in search efficiency and lower
transaction costs in the labor market, is a compensatory mechanism for the changing
nature of offline work. Empirical evidence suggests that income from labor platforms is
6 See, for example, De Stefano 2015; Aloisi 2016; Hill 2015; Standing 2011; and Lambert, et al.
used in this compensatory way to cope with volatility in offline income (in contrast to
income from so-called capital platforms, which are those on which individuals rent assets
or sell goods).7 Platform income “fits” into recent traits of the larger labor market in other
ways as well. It can compensate for insufficient retirement pensions or “early”
unemployment occasioned by the difficulty middle-aged workers face finding jobs after
being laid off; it can be a way to limit or cope with student debt; and it can be an
opportunity for flexible income while launching a start-up.
Decommodification of Contingent Work
From the perspective of the worker, the shift to gig work can also be seen in terms of a
shifting boundary between socializedor monetizedand unsocialized labor, that is,
between paid and unpaid labor (Huws 2003: 68). The labor platform, as well as the
offline shift from employee to independent contractor status, represents this shifting
boundary between paid and unpaid work, or the decommodification of work, in at least
two senses.
First, it is a form of piecework remuneration, so that downtime, such as paid breaks,
lunch time, vacation, and sick-leave, that was considered part of the work in the “good
job,” full-time employee model is now unpaid, or decommodified. Second, what we will
refer to as risk work, which is an in-kind payment in the employee model, is now a form
of unpaid labor foisted on the worker. Grossman and Woyke discuss the “unbundling” of
work, so that primary benefits that traditionally accompany employment are excluded
from the contractor model (2015: 6-7). However, it is not only that a set of benefits, like
health insurance and retirement savings are no longer available or that risk has shifted
from the employer to the worker (Hacker 2006). Although these changes are extremely
important and much discussed, the further point is that the work that is involved in
acquiring the benefit is not that of an HR department. It is unpaid, “outsourced,self-help
work. It is often an extremely complicated and on-going process to figure out how to
choose the best health care insurance or IRA, how to manage money or comply with
required quarterly IRS payments, and how to continue training and advance a career
path. Along with the changing distribution of risk are the issues of a steep learning curve
and the unpaid task of managing these complex information-intensive tasks. For many
people, including the highly educated, these tasks may even incur the cost of hiring a
specialist to take them over. On the other hand, some of this unpaid work may also
become automated. For example, Uber recently announced that it was making a robo-
financial advisor available to some of its drivers (Kokalitcheva 2016).8
Another example of this decommodified risk work is labor spent ensuring payment for
completed work. For example, our surveys and interviews as well as a review of online
driver forums reveal that Uber drivers engage in a substantial amount of unpaid work, to
7 In line with this compensatory use of labor platforms, a more recent update to that study
indicates that the recent job recovery has coincided with a slowing of the rate of growth in
participation on labor platforms since August 2014although it continues to double annually
(JPMorgan Chase Institute 2016).
8 It may be noted that while from the point of view of the worker, the gig economy may be seen as
a shift from decommodification to self-help work, the discussion below indicates that from the
point of view of the consumer the gig economy is part of a shift in the other direction: from self-
help to commodified work.
ensure that Uber has calculated their pay correctly, a particularly onerous task given the
opaqueness of algorithms involved in a “flexible” or dynamic price structure (see below),
and then, if necessary, to try to contact Uber to correct errors in their earning
Mediated Employment Models and the Issue of Control
The labor platform economy is also a continuation of the trend in firm restructuring and
the move to more “distant” and mediated models of employment relations. Weil
analyzes these offline models in terms of the mediated relationship between the worker
and those setting certain specifications for the work, or the “lead firm. This relationship
is intermediated in various ways by, for instance, a staffing agency or
subcontracting/supply-chains. The labor platform is a different kind of mediated or
trilateral relationship between a worker, a “user/requester” of that labor, and the platform.
The key questions become if the platform can be considered the “lead firm” and how
much control and responsibility it has (or should have).
The issue of control is deeply rooted in the regulation of the kind of work that expanded
in the 20th century, rather than the type that has been growing in the 21st century. The
worlds of work in these two historic eras are quite different. Marx famously predicted that
the proletarian employment relation, whereby workers sold their labor to an employer
who controlled conditions of work, would become more and more generalized. Work
laws were developed in the 20th century to regulate this proletarian relationship, defining
it as an “employee” relationship and granting certain protections to the employee.10 Not
only did the employee relationship fail to encompass “all” of the working class, but
toward the end of the 20th century, as just discussed, it was in retreat. This retreat
raises two basic regulatory issues regarding platform gig work. First, where do labor
platforms fit into the existing regulatory regime regarding employees? Second, if labor
platforms do not fit the old employee category, should the definition be expanded, should
new categories be devised, or should new forms of social protection independent of
employment be adopted?
The degree of control exerted by the labor platform varies considerably. At one end,
some platforms operate as a more efficient, electronic version of the employment
agency model. Others, however, are more interventionist in the relation between the
worker and requester and, crucially, exert more control over conditions of work. In those
cases, most notably platforms like Uber, the question arises of where responsibility lies
for work conditions. This question mirrors a similar dilemma in more complex, non-
platform models, such as outsourcing and supply chains. Is, for instance, a U.S. brand
designer responsible for work conditions down the supply chain? Along similar lines, a
major regulatory dispute that has arisen with interventionist labor platforms is the issue
of worker classification. Are the workers independent contractorsa type of
9 Uber recently admitted to systematically underpaying drivers in both New York City and
Philadelphia (Bhuiyan 2017). In response, in May 2017, Uber implemented an upfront pricing
scheme that at least nominally increased the transparency of driver pay (Perea 2017).
10 When passed in the early part of the 20th century, U.S. employment and labor laws granting
workers protections did not exclude independent contractors from their coverage. Rather,
contractors were excluded from these protections after much litigation and post-war legislation
(see Dubal 2017a).
microentrepreneuror are they employees protected by labor and employment laws and
regulations? The issue is an old one, and such classification disputes have arisen
across the service industry since the 1970s. What is new here is that labor platforms
claim to be tech companies that only supply software.
Thus, the move to a contingent and “distant” workforce has a long history, and the
questions of control and responsibility of work conditions have also arisen in offline work.
However, the claims of the platform around this question are new and arise in a more
dramatic context around the issue of innovation, technology, and a supposedly “new”
As noted above, we focus our analysis on one of the many kinds of platforms that seem
to proliferate daily: the labor platform. These are platforms that facilitate the selling of
labor to perform a task or service for monetary compensation. They are distinct from a
number of other types of platforms on which individuals rent assets or sell goods “peer-
to-peer,” such as Airbnb and Etsy, or engage in “consignment” work, such as YouTube
(Kenney and Zysman 2016). They also differ from those such as Craigslist, Monster, or
Career Builder, which are electronic bulletin boards or classified ads. The labor
platforms that are of current interest are those that specialize in temporary contract labor
and coordinate the exchange between the worker and the requester of that work.
Types of Labor Platforms
A basic distinction can be made between what is increasingly referred to as
crowdsourcing vs. on-demand platforms, or crowdwork vs. on-demand or in-person work
(De Stefano 2015; Aloisi 2016). Crowdwork is arranged for and fulfilled remotely and
online, whereas on-demand work is fulfilled in person, “in the physical world” (De
Stefano 2015: 478). Crowdwork platforms therefore construct a potentially global labor
market that integrates high- and low-wage economies, whereas on-demand platforms
construct a local market (although such a platform can expand to many localities, it
organizes separate, local markets).
Labor platforms may also be distinguished by the skill of the work. Skill is a crosscutting
dimension, as both crowdwork and on-demand work may be relatively skilled or
relatively unskilled. (See Figure 1).
Figure 1. Types of Labor Platforms
High Skill
UpWork (coders, editors,
lawyers, accountants)
UrbanSitter, Medicast (MD
house calls), Angie’s list (blue-
collar skilled), GlamSquad
Perhaps the best-known example of low-skilled crowdwork is that on Amazon
Mechanical Turk (AMT) in which workers carry out microtasks of “extremely parceled
activities [which are] often menial [and] monotonous.”11 Other tasks demand high-skilled
workers, such as coders, designers, and a variety of professional services. On-demand
work also spans skill levels. At the low-skill end are a large variety of delivery tasks of
many types (food from restaurants or chefs, goods from retail stores, or, in the case of
Uber, oneself) or services such as housecleaning and dog walking. At higher skill levels
are electricians, care takers, doctors, and lawyers.
Uber is a special case in a number of ways. Per the distinctions above, it is an exemplar
of the low-skilled, on-demand or in-person platform. Further, it is in some respects a
hybrid platform in that it has been seen also as a platform for monetizing an asset
(similar to Airbnb), since the original idea was to monetize the otherwise “unusedtime
of car ownership. However, unlike a car-sharing/renting platform (e.g.,, Uber
most fundamentally is a labor platform on which the driver works. Indeed, Uber has
encouraged and facilitated the leasing of cars in order for drivers to be able to work on
the platform.
Efficiency on Labor Platforms
The application of technology on labor platforms increases efficiency but in a way quite
distinct from conventional applications of technology. The Fordist model of full-time
employment, for instance, increased productivity by applying technology to the
production processto the labor process itself. It thereby enabled higher wages, along
with increases in worker productivity. The use of robotics follows this same conventional
model of increasing labor productivity through the introduction of capital goods. The logic
of labor platforms is different. The technology of the platform can be thought of not as
making the worker more productive in the actual production process but rather as
making the market more efficient by lowering transaction costs. Gig work, which is a
central part of the business model of most labor platforms, takes advantage of this
efficiency. The technology of labor platforms achieves efficiency by, in effect, shifting
the balance between the gig and the search.
Put another way, the work of a freelancer or independent contractor can be thought of in
two parts: 1) the unpaid work of looking for a gig and making a contract, and 2) the paid
work of fulfilling the contract. The remuneration from the paid production component
must cover the unpaid search component. The technology of the platform makes the first
of these more efficient, but does not affect the productivity of the worker during the
second. Thus, wages rise by working more gigs per time period, assuming the same
rate of remuneration for the paid gig/contract work.
Maintaining this wage rate may be a particular challenge on crowdwork platforms, which
put pressure on wage rates by globally integrating high- and low-wage labor markets.
To some extent, by shifting the balance between the unpaid search and the paid gig,
total remuneration can be maintained even with a lower price per gig, because more
gigs can be fit into the freed up, formerly unpaid search time. However, the degree to
11 De Stefano 2015: 474. See also Irani 2015. There also exist high-skill tasks on AMT.
which the requester will enjoy the greater efficiency through lower prices or the worker
will enjoy higher compensation through more gigs in a given time period will vary by the
type of work and the particular platform, as well as by the regulatory framework.
This last point, the possibility of lowering the price per gig, may be important for the
business model of certain kinds of platforms. On-demand platforms, such as Uber, may
have an interest in a low price for the paid component, putting the burden for maintaining
or even increasing income on the technology-driven speed-up efficiency of the unpaid
search. As we discuss below, Uber uses this logic of efficient service provision through
its software to argue that intensifying the rate of paid work (more gigs per unit time)
allows income to be maintained even at lower wage-rates per gig. Drivers, however,
refute the claim that income is maintained.
Platform Growth
Growth on the platform typically occurs through two routes: diversification of services
available on the platform and expanding the market for a given service. Many
crowdwork platforms are quite unspecialized, covering a wide diversity of tasks, skills,
and prices. In-person, on-demand platforms vary in their degree of specialization, many
beginning as single-service platforms (rides, restaurant delivery, meal preparation and
delivery, laundry tasks, dog walking, etc.). Uber is a prime example of a diversification
strategy in terms of the types of cars available for ride hailing, the riding services offered
(e,g., individual or pooled), delivery of other products, and perhaps ultimately a much
greater set of logistics services. The diversification strategy is reflected in Uber’s recent
change of its motto from “Everyone’s Private Driver” to “Where Lifestyle meets Logistics”
(Lobel 2016: 102).
Most on-demand platforms initially attempt to grow by expanding the number of workers
and requesters for a given service. Crowdsourcing platforms tend to be W2B (worker to
business) coordinators, which match “workers” or taskers with a variety of skills and
expertise to requesters (or taskmasters), who are in business, or are “producers” in that
the tasks are generally inputs that the requesters use in some production process. By
contrast, on-demand platforms are W2C (worker to consumer) coordinators, which
match workers or taskers to final consumersprimarily making personal services
available to consumers. The low-skill services are those that most people are used to
carrying out themselves, and the idea is to commodify these generally domestic “self-
help” tasks by purchasing the services of household help, such as cooks, washers,
cleaners, drivers, gardeners, babysitters, and those who would do other chores for the
household, like walking the dog or picking up and delivering packages, dry cleaning, or
purchases. In another sense, the provision of these tasks or chores constitutes a
massification of “servant” tasks through their decomposition: instead of hiring a whole
servant, one hires these household or personal consumption services (or
“personalistics”12 ) by the chore or task. With this decomposition, individual chores
become affordable for those who cannot hire a servant, and the market for household
help ultimately expands by going down the stratification hierarchy. Such market
expansion for these chores depends on their provision at a lower cost.
12 This term was suggested by William Stafford.
The market for ride-hailing is particularly interesting in this respect. Studies have shown
a bifurcation in the use of taxis, which is greatest among both high and low income
groups (Schaller 2016: 10). Thus, expansion might depend on not only an offer that is
attractive or affordable down the income hierarchy to create a mass market, but also
intensification of use at the low end. Both of these strategies have a low-cost logic.13
For the worker, this on-demand or in-person economy thereby represents a low-wage
strategy. The low-wage strategy has both a micro and a macro contradiction. At the
micro level, wages must be high enough to recruit workers. At a macro level it meets a
constraint on aggregate demand to the extent that the model becomes generalized: the
potential for expansion depends on the income distribution and the size of the middle
or even the upper-middle class. However, unlike Fordism, as a low-wage model it may
generate a class of workers unable to afford what is produced.
Tripartite Relations and Worker Autonomy on the Platform
The online gig economy embodies a tripartite relationship between the platform, the
worker, and the requester of the work or service. All labor platforms that are not simply
electronic bulletin boards provide some services. Examples are payment processing,
ratings or reviews, background checks, and information about worker credentials. A
basic issue is whether the platform exercises some degree of control over the exchange
between the worker and the requester. The platform can exercise control over various
conditions of work, but perhaps the most important form of control concerns the process
of price or wage setting.
On some platforms, workers can set their own rate and offer their labor at a stated price.
The requester then chooses among workers on the basis of this offer, combined with
other information about worker experience, qualifications, and ratings by past requesters
on the platform. On other platforms, the requester lists a task or project at a set price,
and workers decide if they want to apply. In these cases, the platform does not control
wage rates, though it might indirectly affect them by constructing a larger market of
workers and requesters. Platforms like Angie’s List can more directly affect the wage
rate by delineating a “fair price” range that must be met. Still others, particularly low-
skilled on-demand platforms like Uber, many delivery platforms such as Postmates, and
other services, such as Swifto dogwalking and Handy housecleaning, set the price of
In addition to price, the platform may control other aspects of the work as well. In
general, the platforms that exert greater control are on-demand platforms, which tend to
be worker-to-consumer (W2C) platforms. These more controlling W2C platforms
coordinate the same, relatively unskilled tasks repeatedly whereas on W2B (worker-to-
13 While Schaller finds that taxi use is highest among lower and upper income groups, we do not
have data that suggests the same is true for users of Transportation Network Companies, or
TNCs, like Uber. While we lack data on the frequency of use, a 2015 Pew survey found that 26
percent of high-income individuals (those making above $75,000 a year) have used a ride-hailing
service like Uber and Lyft compared to 10 percent of low-income individuals (those making less
than $30,000 a year). Since public transit is the cheaper option, one might hypothesize that low-
income use is more occasional, more restricted to necessary situations, and thus a harder market
to expand.
business) crowd-sourced platforms, work is more “customized.” Matching worker and
requester thus becomes a logistically easier task for on-demand platforms, and control
over matching allows these platforms to also control pricing and thereby workers’ wages.
Platform control is important because it has been raised as a central issue on many
platforms, particularly Uber. For drivers, it is a source of worker dissatisfaction. It is also
the most salient legal criterion for employee status. Most platforms maintain that
workers are not employees but rather independent contractors who maintain autonomy
in their work, particularly over hours and the decision to accept a gig. Thus, the nature
of platform control over conditions of work is a central issue for labor regulation in the gig
In examining the regulation of worker issues on on-demand labor platforms, Uber is a
particularly good case for analysis. It has the longest record of regulation and thus
provides an empirical base for examining the politics of regulation. Also, because of the
unusual amount of control Uber exercises over work, its regulation brings the labor issue
into sharpest relief. Uber presents perhaps the “easiest” case of regulation of employee
rights, both because of the high degree of control exerted by the platform and because it
presents more favorable conditions for collective action by platform workers. If
regulating these issues is difficult in the case of Uber, regulation should be particularly
unlikely in other cases.
Uber is also an interesting case for analysis because it has become so emblematic of
the labor platform economy. Its paradigmatic position can be seen in, for instance, Hill’s
use of “Uber Economy” in the subtitle of his book and the numerous hits (almost 50,000)
that “uberization” turns up in a Google search.14 As such, a study of Uber may uncover
issues that are important in regulating the gig economy and labor platforms more
Uber was launched in San Francisco in 2010 as UberCaban app for livery services,
which connected passengers to existing licensed black car and limousine drivers. In
June 2012, Lyft and Sidecar launched apps with a different model, which altered both
the ride-hailing industry and its century-old regulatory framework. Two traits were
integral to these new apps: non-professional private drivers using their own cars and a
suggested, non-mandatory price for the ride. The model was thus closer to a peer-to-
peer or “sharing economy” model, on which in fact it was based. A month later, Uber
launched UberXas a similar model but with a key difference. Instead of a non-
mandatory price (as with Lyft), Uber set the fare, a trait that also distinguished it from
taxis, whose rates are set by municipal governments. The following year UberX
expanded to many more cities in the U.S. With the use of private drivers in their own
cars, Uber, Lyft, and Sidecar distinguished themselves from and maintained that they
were software companies and as such should not be subject to the same regulations as
traditional transportation companies.
14 It turned up an additional 285 on Google Scholar. Uberize” turned up over 27,000 hits on
Google and 50 on Google Scholar (August 11, 2017).
With this new model, Uber presented a particular challenge to an existing and highly
regulated sector. Many other on-demand platforms construct new markets in personal
services where virtually none previously existed (e.g., pick-up and delivery of many
types and meal preparation). Uber, however, enters, expands, and improves an existing
market. It presents competition for an existing sector that is already highly regulated and
that has used that regulation to defend itself by limiting entry. Uber not only “breaks”
those barriers to entry, but also provides what is widely regarded as a significant
improvement in service: greater availability, faster matching of customers to drivers, and
cheaper prices, as well as safety and consumer protection measures like price estimates
and route monitoring. This challenge to taxis has resulted in a sharp decline in both
medallion values and the number of taxi drivers in US cities (Barro 2015). In New York
City, for instance, ride-hailing companies outnumber taxicabs by four to one, and the
value of medallions has declined to one-fifth of their 2013 worth (Walker 2017).
The entry of Uber left unsettled a number of issues concerning proper licensing, public
safety, and consumer protection that were regulated for taxis and limos. Taxi interests
saw regulating Uber on these issues in terms of competition and sought to ban Uber or
at least to impose similar regulations to level the playing field. Uber recognized that rider
trust was central to the success of its model, and the company adopted a set of driver
checks and car requirements and argued that it had sufficiently addressed issues of
consumer protection and safety. Regulators, however, generally considered these “self-
regulatory” measures inadequate. Thus, regulation around these issues became
contested, pitting taxi interests against Uber and arousing the interest of public officials
responsible for ride-hailing regulation.
The result has been widespread regulation of Uber and similar companies by both cities
and states. Municipal governments have traditionally regulated taxis, and they have
generally moved to regulate Uber upon its arrival. State legislatures, which have
historically played a limited role in regulating the taxi sector, have also often intervened
to regulate Uber. As of August 2016, 34 states passed such legislation (see Collier,
Dubal, and Carter 2017). However, conspicuously absent in this list of regulations are
those related to labor. This absence is particularly notable given the prominence of
public conversations over the work conditions and employment status of Uber drivers.15.
The nature of Uber’s control over the labor performed by its drivers is central to these
debates about employment status and working conditions more generally. As putative
independent contractors, Uber drivers are able to set their own schedules and accept or
reject “gigs. However, Uber exercises a great degree of control over many aspects of
the gig, particularly over issues of the pace of work (e.g., who gets a request and how
long one has to respond) and the operation of the rating system, an often opaque
system that can lead to driver “deactivation,” or suspension, as several analyses have
detailed (Lee et al. 2015; Rosenblat and Stark 2016). The issues of price setting and
control of hours merit further discussion, as Uber uses incentives to influence driver
15 Taxi interests have not made demands for labor regulation. Taxi drivers (whether or not they
are medallion holders) are not employees (with the exception of those in Las Vegas) but rather,
they have been independent contractors since the taxi sector was restructured in the 1970s
(Dubal 2017a).
behavior, including when and where drivers work.
As mentioned above, Uber, like many delivery platforms, unilaterally sets prices, unlike
crowdwork platforms and many other on-demand platforms. It sets prices to achieve its
goals of increasing market-share vis-à-vis competition or of breaking into a new market.
Central to its business model is an on-going change in prices to achieve market
efficiency by equilibrating supply and demand. It sets pricesand hence wagesin four
distinct ways. First, surge pricing consists of constant, algorithmically controlled price
changes, which are implemented without advanced warning and in a “disaggregated”
way. That is, price changes can be for a larger or smaller geographic area and for an
unknown amount of time, which may be very short. The goal is to induce drivers to high-
demand areas.16 Second, peak pricing operates in the same way, but at set times, such
as rush hour. Third, fare cuts have been implemented in most markets from time to time
to generate long-term growth, create demand when entering new markets or massifying
the market in existing localities to make it more affordable. Finally, driver bonuses, to
maintain or expand supply can be quite frequent, with a changing and often bewildering
array of conditions. Thus, Uber sets prices/wages in a fluid and dynamic way that often
cannot be anticipated by the driver. Drivers confront uncertainty not only from unknown
fluctuations in demand, but also from the changing price of a trip. Not only is price-
setting beyond the control of drivers, but drivers must learn how to optimize these
complex incentives. Driver forums are filled with discussions about the advantages or
disadvantages of following a surge and of pursuing constantly changing bonus
Uberand many driversemphasizes the benefits arising from drivers’ flexibility in
controlling their schedules (Hall and Krueger 2017). The idea of flexible hours lies at the
heart of the argument for independent contractor status. As noted above, driving for
Uber is particularly attractive to those for whom Uber driving is a compensatory
mechanism and who must accommodate driving hours to other income-earning activities
or responsibilities, or who are driving casually for extra income. It affords little to those
for whom for-hire driving is a full-time activity, many of whom drive well over forty hours
a week. Even for many “casual” drivers, however, flexibility is diminished by the fact that
the choice of hours is highly incentivized by Uber’s dynamic surge pricing (Goncharova
2017). Controlled dynamic pricing may mean “flexibility” in the sense of the irregularity of
profitable hours and the strategic choice to work only at profitable times of higher hourly
Uber thus exerts a great deal of control over work conditions, including prices and the
ratings systemand thus continuation on the platform. It also exerts control by
fluctuating incentives in order to meet changing demand. To the extent this practice
works, it conditions and thereby reduces the autonomous flexibility of drivers and allows
Uber to capture the benefits of flexible scheduling. Uber also controls “self-regulatory,” or
self-imposed, requirements that affect safety and consumer protection. Drivers are often
16 Our interviews with drivers, however, suggest that this incentive does not always work. Many
drivers avoid surge areas because they are short-lived, and there is no guarantee of getting a
surge passenger. Computer scientists at Northeastern have confirmed this through modeling
(Chen et al. 2015). More recently, driver commentators have noticed a significant decrease in
surge requests from the platform (Campbell 2017c).
responsible for ensuring compliance with these regulations, such as maintaining their car
in a way that conforms to company rules. This level of control highlights the issue of
employment status, which, as discussed above, is primarily determined by the degree of
control exercised over workers. The issue is complicated by the tripartite relationship in
which the platform intermediates between the worker and the “user” or “requester” of
work. Such a high level of control is not indicative of independent contractor status, and
the employment status of the driver has become a major issue of contention.
Uber has typically resisted most regulations, but within this general pattern, it has most
forcefully opposed those regulations that 1) give drivers the rights and benefits
traditionally associated with employment, and 2) constrain the supply of drivers. With
respect to the first, while those advocating employee status point to Uber’s significant
control over conditions of work, Uber argues that it is not an employer but simply offers
the software that matches riders with drivers. If workers were classified as employees of
the platform, they would have the right to form a labor union and potentially negotiate
their conditions of employment. They would also be covered under preexisting laws that
establish minimum wages, Social Security contributions, overtime compensation, and
other employment safety nets. Provision of these social protections would undoubtedly
result in a dramatic increase in the cost of operation. Uber has thus fought
reclassification attempts and laws that extend employee rights.
Uber also opposes regulations that are seen as restricting the ease of entry for drivers,
which allows for a flexible workforce that can be continually expanded and replaced.
The platform relies on easy entry for many reasons: because many of its drivers are
temporary, part-time, or even casual drivers, and because many, including those who
intend to drive full time, do not remain long on the platform. As former Uber Vice
President, David Plouffe, said, “For most people, driving on Uber is not even a part-time
jobit’s just driving an hour or two a day, here or there, to help pay the bills” (Uber
Newsroom 2015). The business model requires two types of flexibility: 1) hourly flexibility
to meet demand peaks, and 2) ease of entry, not only to accommodate seasonal
fluctuation and expansion, but also to compensate for an extremely high rate of worker
attrition, which persists both because many drivers consider Uber as short-term or stop-
gap work and because of dissatisfaction. Analysis based on Uber data indicates that
nearly half of Uber drivers will remain active for less than one year (Hall and Krueger
2015). Because of the desire to expand and massify the ride-hailing sector combined
with this drop-off rate and the short-term flexibility of supply inherent in the model, Uber
considers it crucial to minimize hurdles to driver entry.
For both casual and especially fulltime Uber drivers, the high degree of control over work
has led to widespread driver grievances, as is evident in several analyses as well as
many online driver forums.17 Grievances have to do with selection and management of
the workforce, prices, and quality standards, including car requirements or
specifications, driver ratings, and deactivation, and the difficulty of calculating driver
earnings and of contesting mistakes or unfair ratings (see for example, Rosenblat and
Stark 2016, De Stefano; Campbell 2017a; Campbell 2017b). Some of these, like driver
ratings, involve algorithmic control of work conditions, which also raises issues of
17 E.g.,, Uber Forum, Uber Chariot, The Uber Drivers Subreddit
Uber drivers have had little capacity to make effective claims for addressing these
grievances. Gig work generates difficult conditions for collective action because of the
dispersion and atomization of workers. In fact, Uber drivers are better positioned than
most gig workers to mobilize collectively. First, and perhaps most importantly, the high
level of control Uber exercises over work conditions generates many shared complaints.
Second, and relatedly, drivers share a single common target of grievanceUber. Third,
spaces exist where drivers congregate and where they have the potential to get to know
one anothermost prominently at pick-up locations such as airports.18 Fourth, drivers
have generated several active online forums and blogs that are available for exchange
of information and coordination. Nevertheless, even with these relative advantages,
Uber drivers face a number of collective action problems.
One challenge to collective mobilization is that drivers comprise a diverse, segmented
workforce with potentially diverging demands. Some workers participate full-time and
depend wholly on Uber for incomeand may have incurred expenses by buying or
renting appropriate cars for the purpose. Others work part-time to supplement other
work, and still others work quite casually. As a result, driver interests are not always
aligned on priorities such as flexibility and certain rights and benefits. Also, while Uber
itself is an identifiable target, given the nature of the app, no immediate boss or
supervisor is known or visible to workers to bring demands and grievances. Despite
available spaces for drivers to interact with each other, workers who wish to mobilize
may not have repeated interactions with the same Uber drivers, even in gathering hubs.
Our interviews indicate that few drivers visit online forums and blogs.
Thus, despite some advantages, Uber drivers have not overcome collective action
problems. Drivers’ interests and claims have been instead most often initiated and
pursued in regulatory venues (both in courts and legislatures) by non-driver actorsor
surrogates as we refer to them. The three most important are labor surrogatesunions
and alt-labor groupsprivate plaintiffs’ attorneys, and Uber itself.19 These surrogates
both articulate drivers’ interests and bias their representation, which is colored by their
own “outsider” perspectives. Below we briefly review attempts at driver collective action
and then analyze the strategies, activities, and conflicts of interest of these three types of
Collective Action by Drivers
The challenges to drivers’ collective action are reflected in the low turnout and limited
success of the few driver-led protests that have occurred since 2014. Most protests
against Uber are small, often attracting fewer than 30 participants. Moreover, these
protests are sporadic and have generally not led to sustained pressure necessary to
elicit a response to drivers’ demands.
18 Recently, Uber, like Lyft, has begun to offer “greenlight spots,” where drivers can get
assistance from an Uber representative. These spaces may serve as a location for drivers to
congregate and discuss demands.
19 Other surrogate actors for workers include NGOs, foundations, and academic analysts.
The majority of the driver protests against Uber have been in response to fare cuts,
which translate into lower driver earnings per ride (Campbell 2016a).20 In Fall 2014, for
example, drivers in cities across the United States protested an indefinite rate cut of 20
percent (Kosoff 2014). In some cities, such as New York, Seattle, Santa Monica, and
San Francisco, these protests attracted over one hundred drivers (Hill 2015: 90). In the
next two years, Uber again slashed prices. When Uber cut rates by as much as twenty
percent in 2016, San Francisco Bay area drivers took to the streets in protest (Said
2016). Yet, collective action has failed to reverse the cuts and has thus far not prevented
additional cuts (Krisher and Sell 2017; Campbell 2016a).21
In a second form of protest, drivers have tried to coordinate by collectively turning off
their Uber apps, often during periods of peak ridership (Hill 2015: 90; Burns 2014). The
San Francisco Uber driver boycott during the 2016 Super Bowl took this form in an
attempt to demand higher rates and better pay structure more generally (Alba 2016). Yet
significant barriers prevent the widespread success of this method of collective action.
First, despite all the publicity around this event, drivers seemed unaware of the call for a
boycott (Campbell 2016a). Second, though strikes around events such as the Super
Bowl attract maximum potential disruption and publicity, they are also moments of
predictable surge pricing, which are particularly attractive to drivers and provide
incentives for them to ignore the boycott. Similarly, these boycotts contain their own
contradictions, as they themselves create a driver shortage, to which the algorithm
responds with higher prices to entice other drivers onto the road with the promise of
higher earnings. These incentives may be higher among drivers for whom Uber is not
their primary source of income and whose strategy is to take advantage of the flexibility
and drive only when the prices and demand are high. Indeed, despite the publicity
leading up to the Super Bowl boycott, few drivers participated. (Hook 2016).
Even the largest driver-led protests have achieved only modest success at best. In New
York, demonstrations have periodically drawn the support of hundreds of drivers. The
largest to date occurred in fall 2014, when over one thousand drivers went to the streets
and turned off their apps to protest recent rate cuts and increases in the commission the
company retains on each ride (Griswold 2014). Many were also protesting a new policy
requiring drivers of Uber’s premium services to accept requests for cheaper services or
risk the deactivation of their accounts (Bhuiyan 2014b). Shortly after the protest, Uber
reversed this decision, but did not yield to the other demands. Nor, two years later, did
Uber respond to a second wave of New York protests against rate cuts, which once
again attracted hundreds of drivers (Feuer 2016).
Thus, drivers have largely been unable to mount successful collective action. The only
successes, and even then very limited, have occurred in New York, which represents a
particularly lucrative market, where the costs of ignoring driver protests may be
unusually high. Similarly, many drivers in New York view Uber as a long-term career and
depend on ridesharing companies for the bulk of their income (Bhuiyan 2014a). The high
20 Although Uber argues that lower rates increase demand and thus preserve total earnings,
drivers report a decline in earnings (Campbell 2016b).
21 Uber reduced rates in January of 2014, 2015, and 2016 in response to the “winter slump”
(Campbell 2016b). It also periodically reduced rates in select cities to increase ridership and
undercut the prices of other rideshare companies (Lawler 2016).
stakes for New York driversand for Uberfacilitate mobilizing in response to
demands. But drivers’ limited success reflects the problems drivers face in acting
Labor Organizations as Surrogates
Because of collective action problems, drivers are primarily represented by surrogates.
These include both traditional unions and alt-labor organizations, which have been
divided in their approach to the issue of employment status: they either fight drivers’
putative independent contractor status or accept it and try to achieve improvements
within that status.22 The different approaches taken by these labor surrogates reflect
variation in their own interests.
Some unions, like the national AFL-CIO, take the position that Uber drivers are
employees under the law and that they must fight for that legal recognition. This position
extends the conventional strategy and organizing model that unions have historically
pursued. It is a direct challenge to Uber’s business model and, for the union, avoids the
financial liabilities associated with organizing independent contractors. Union
representatives have met with drivers, strategized around potential litigation and
legislative proposals, filed court cases against Uber, and officially objected to court
settlements that do not recognize employee status. Yet, this traditional union model,
which centers on employment status, may not be the most salient interest of many
drivers, who may prefer or prioritize a more selective allocation of rights and benefits to
accompany the flexibility of independent contractor status.
Other union surrogates, including the Teamsters Local 117 in Seattle, have accepted the
independent contractor status of Uber drivers, but insisted on their right to bargain
collectively. These efforts to extend bargaining rights to independent contractors have
been pursued in legislative venues and have been supported by union attorneys, who
have been frustrated by years of ineffective misclassification suits in the courts. The
union thus attempts to increase its constituency by representing a new group of workers
in collective bargaining, albeit a group that does not have employee status.
Still other unions have likewise largely accepted the independent contractor status of
drivers but have foregone the traditional struggle not only for employee status, but also
for the right to collective bargaining and the relative job security associated with it.
Instead they seek to increase their membership by representing non-unionized members
in discussions with Uber over work conditions. The International Association of the
Machinists and Aerospace Workers (an AFL-CIO member), for example, has pursued
direct negotiations with Uber in its efforts to represent Uber drivers. Rather than
advocating legislation that would confer new rights for independent contractors, they
created an “Independent Drivers Guild” (IDG), which struck a private agreement: Uber
agreed to establish grievance procedures and discuss market-based portable benefits
for drivers in New York City in exchange for the IDG’s commitment not to challenge the
independent contractor status of drivers.23 The Teamsters Joint Council 7 in Northern
22 (Dubal 2017a). Unions are acutely aware that collectively organizing putative independent
contractors puts them at risk for anti-trust or price-fixing allegations.
23 In effect, the IDG made an agreement to not organize work stoppages against Uber. As long
California attempted to create a similar California-based workers’ association when Uber
agreed to fund such an association as part of a class action settlement. The Teamsters
effort, however, was thwarted when the settlement was thrown out by a judge.24
In addition to unions, alt-labor groups have also acted as surrogates to represent drivers.
Again, these actors have their own set of interests. One notable case is the Freelancers’
Union, which has for the past twenty years been a voice for highly skilled independent
contractors. Unlike most unions, this alt-labor group has its origin in representing a
category of workers for whom employment status is not an issue. It thus celebrates the
“contractor” category and the flexibility and freedom that comes with it but believes that
more needs to be done to protect freelancing workers. Their embrace of independent
contractor status has made them an attractive partner for Uber. Indeed, the Freelancers’
Union became a paid consultant for Uber and was charged in 2016 with creating a plan
to provide portable benefits for drivers, which would be transferable from one platform
employer to another (Horowitz 2016).
Another important alt-labor group is the New York Taxi Workers Alliance (NYTWA),
formed in 1998 to represent taxi workers, a group that has not had employee status
since the mid-1970s (Dubal 2017b). It since has expanded its membership base to
include some Uber drivers in New York City, where regulations imposed greater parity
with the taxi sector. Nevertheless, its primary defense of taxi rather than Uber drivers is
reflected in its strong advocacy for employee status for Uber drivers, which the NYTWA
never advocated for taxi drivers. The NYTWA adopts this strategy as a way to
undermine Uber’s business model and thereby limit the competition Uber represents for
taxi drivers. Its representation of Uber drivers is thus shaped by potential conflicts
between taxi and Uber drivers.
Thus, labor groupsboth unions and alt-labor groupshave primarily taken three
approaches: fighting for reclassification of drivers as employees, accepting independent
contractor status but fighting for collective bargaining rights, and accepting independent
contractor status but attempting to form workers’ associations. As we discuss in more
detail below, these approaches correspond to three venuescourts, legislatures, and
private settings. Those who fight for employee status do so in courts alongside
surrogate plaintiffs’ attorneys. Those who organize drivers for collective bargaining
without contesting the classification of drivers do so in the legislative arena. And those
unions that form worker associations do so in private, non-governmental venues in
negotiation with Uber.
as drivers are considered “independent contractors,” a labor organization that facilitates a strike
by Uber drivers would risk anti-trust liability.
24 O’Connor v. Uber, CV 13-03826-EMC, which remains an active case, was almost settled
during the summer of 2016. However, the federal judge overseeing the case threw out the
proposed settlement as unfair to the class of drivers. In addition to the monetary terms of the
proposed settlement, the non-monetary terms included the creation, funding, and Uber-
recognition of a drivers’ association (similar to the IDG). Before the settlement was thrown out,
Teamsters Joint Council 7 announced their intention to become the drivers’ association for
California-based Uber drivers. They held two organizing meetings with Uber and Lyft drivers in
the San Francisco Bay Area in the summer of 2016. However, since the settlement was judicially
discarded in August 2016, Uber drivers who had been in contact with Teamsters JC7 have not
heard from the union.
Contest Contractor
Accept Contractor
Status and Organize
Workers for Collective
Accept Contractor
Status and Organize
Workers for
Workplace Voice &
Legislatures (Cities and
Private Consultation
with Uber
Labor Groups
AFL-CIO (National)
Teamsters Local 117
Teamsters Joint
Council 7
(Northern California);
Machinists NY (AFL-
Freelancers Union
Private Plaintiffs’ Attorneys
Private plaintiffs’ attorneys have also acted on behalf of drivers. They have primarily
pursued misclassification class action lawsuits to certify Uber drivers as employees for
wage purposes. Their focus on suits regarding wagesand not, for instance,
misclassification suits regarding safety net protections like unemployment insurance or
workers’ compensationcorresponds to their own private interests, as wage settlements
can yield a financial windfall for these plaintiffs’ attorneys. Market mechanisms thus play
an important role in incentivizing private enforcement regulation (Farhang 2011: 5).
Further, these same financial payoffs have incentivized them to settle court cases
without a resolution to the underlying issue of employee status. To date, despite dozens
of class actions of Uber drivers filed in states across the country, not one has made it to
trial. While employment status has been decided by some courts in Europe and Africa,25
the issue remains unresolved in the US, despite the fact that it was raised here first.
Uber “Surrogate” Action
Uber itself has also acted as a surrogate on behalf of workers’ interests. It defends
workers by presenting itself as a source of work. It mobilizes drivers to fight against
regulations, while posing the threat of disinvestment, or leaving the market. It thus
makes an argument that equates drivers’ interests with those of the viability of the
company. The Uber app provides the company with a means of communication that
enables Uber to coordinate drivers in these anti-regulatory campaigns and “solves” their
collective action problem by providing a mechanism (an easy way on the app to “click”
on a message and add their signature”) for petitioning regulators. In this way, Uber
frames the terms of grassroots mobilization and leverages its power to skew and limit
the representation and demands of workers. Walker (2014) has referred to this kind of
25 See Mukherjee 2017 and Lomas 2016.
mobilization, mostly by businesses, as a “subsidized public” (22). He notes that the
“subsidized public may be one in which elites have become more dominant players, but
this need not entail the assumption that incentivized activists are disingenuous” (36).
That is, drivers generally want Uber to continue to provide flexible jobs. Nevertheless,
the terms and forms of their participation in the regulatory process are determined by
Uber. The result is a biased representation of drivers’ interests.
The collective action problems of Uber drivers are not unique to them but rather are part
of a more general challenge to worker mobilization posed by the very nature of gig work.
More unusual, however, is the fact that Uber drivers work on a platform that exercises a
very high degree of control over their conditions of work. With limited capacity to
organize and no clearly defined way of making demands of the platform, drivers are left
to rely on surrogates, who organize the representation of drivers’ interests but in the
process may bias these interests as they work to achieve policy outcomes that reflect
their own preferences. The following section details how surrogates have represented
drivers in legislative and judicial venues.
The regulatory issues affecting Uber arise in multiple venues: legislative processes in
city councils and state assemblies, administrative processes in city and state regulatory
bodies, and judicial processes in courts. Issues related to labor have only rarely been
addressed in legislative arenas, where regulation of issues related to safety, consumer
protection, and competition has been more predominant (Collier, Dubal, Carter 2017).
By far, most regulatory action on labor issues has occurred in courts through private
enforcement litigation brought by plaintiffs’ attorneys presenting class action suits. While
scholars, journalists, and politicians have debated the need to resolve the larger
question of whether gig workers, like Uber drivers, are entitled to certain basic rights and
benefits traditionally associated with employment, little to nothing has been
accomplished in either legislative or judicial arenas to this end.
Legislative Venues
At the state level, labor issues have attracted very little attention, and no action has
actually changed the status quo for drivers. Only two states have attempted to address
issues faced by workers. The first was California in 2016, when Assemblywoman
Lorena Gonzalez’s office, in conjunction with long-time labor attorney Richard
McCracken, authored legislation to give California’s independent contractors the right to
bargain collectively. However, due to fractious positions within California’s labor
community over regulatory approaches to Uber, the bill was preemptively pulled before it
was even introduced. The second bill addressing labor is projected to be introduced in
New York State in late 2017. It is a highly contested bill to create a portable benefits
fund for independent contractor workers. That bill, which is sponsored by State Senator
Diane Savino and crafted in conjunction with Tech:NYC, a trade group, would codify the
independent contractor status of workers like Uber drivers and, in exchange, provide that
companies devote 2.5 percent of each transaction to a fund for portable benefits
(Eidelson 2017). In a contrary move, Uber has successfully lobbied several other states
to pass legislation to codify independent contractor status but without any such driver
benefits: Mississippi, North Carolina, Ohio, Arkansas, Florida, and West Virginia have
declared this status for drivers on ride-hailing platforms, like Uber. In Alaska, the state
legislature also intervened under pressure from Uber, overriding a state regulatory board
decision and exempting Uber from requirements to comply with workers’ compensation
At the city level, labor issues have also been nearly absent. The lone exception is
Seattle, where in 2015 drivers gained the right to unionize as independent contractors.26
The initiative for this ordinance was taken by Teamster attorney, Dmitri Igzitlin, who
worked alongside two Seattle city councilmembers to introduce legislation that allowed
Uber drivers in the city to organize despite their independent contractor status. Igzitlin,
like McCracken in California, observed that large companies evade enforcement of
employee status for their workers, even when a court decides in favor of employee
status.27 Rather than suing Uber for misclassification and converting drivers to employee
status to organize them, he worked to craft a law to provide drivers the right to bargain
collectively regardless of their independent contractor status. The ordinance
unanimously passed, allaying unions’ fears that they would suffer from anti-trust liability
for organizing Uber drivers. Uber, leveraged its structural and instrumental power
(Collier, Dubal, Carter 2017) to mobilize against this regulation, arguing that it would
make it impossible to maintain the fluid and large labor supply the company requires.
While these efforts did not convince the Seattle city council to abandon its efforts, Uber
mounted a strong legal challenge to the new labor regulation. Following enactment of
the ordinance, Uber and Lyft, alongside the Right to Work Foundation, mobilized drivers
to challenge the ordinance. The district court found for the city of Seattle, pronouncing
the challenge “too early” and speculative,but the ordinance remains blocked due to a
temporary injunction requested by the National Chamber of Commerce.28 The outcome
of this effort on labor issues, however, remains far from clear.
Judicial Venues
Issues of workers’ rights have more often been addressed in courts. These cases have
primarily been brought by private plaintiff’s attorneys. Yet, because of procedural
problems with certifying a class and the financial temptation for attorneys to settle before
trial, collective workers’ rights have not yet been successfully defended in the judicial
26 A bill more broadly targeting freelance workers was passed in New York but had little impact on
Uber drivers. The “Freelance Isn’t Free Act” requires that anyone in New York City who hires a
freelancer “must agree in writing to a timeline and procedure for payment.” While non-payment
for agreed upon services is already illegal, the ordinance sets up a system of recourse for those
who are not paid, including a fine for repeat offenders. See Bahler 2016.
27 These companies instead shift their business model to make their workers look more like
independent contractors, as FedEx did in response to successful misclassification litigation
almost a decade earlier (Dubal forthcoming).
28 The district court’s decision on the lawsuit sponsored by Uber (Clark v. City of Seattle , 2017
BL 298107, W.D. Wash., No. 2:17-cv-00382, 8/24/17) will likely be appealed. The 9th circuit is
scheduled to hear oral argument on a separate lawsuit appeal filed by the National Chamber of
Commerce’s lawsuit against the city of Seattle regarding the legality of this ordinance in
December 2017. The 9th circuit has temporarily blocked implementation of the ordinance at the
behest of the Chamber. Chamber of Commerce of the U.S. v. City of Seattle , 9th Cir., No. 17-
35640, 8/29/17.
arena. While an undisclosed number of individual Uber drivers have won employee
status in administrative hearings for purposes of their wages, workers compensation,
and/or unemployment insurance, these cases are not binding for other drivers. In both
the collective and individual contexts, Uber has settled or attempted to settle many
cases as a strategy to avoid an adverse ruling; in some cases they have actually settled
for more than a plaintiff would have made at trial just to make the case disappear.
To date, two important private enforcement class actions against Uber remain unsettled:
O’Connor v. Uber and NYTWA v. Uber. O’Connor, filed in 2013, was the first class
action filed against Uber. O’Connor alleged that Uber misclassified drivers under
California wage laws. Brought by a Boston-based plaintiff’s attorney and filed in the
Northern District of California, the case attracted attention when a large class of plaintiffs
was certified by the judge.29 A ruling in favor of the plaintiffs would have constituted a
major challenge to Uber. While the district court’s decision to certify a large class was
eventually overturned by the 9th circuit, dozens of copycat lawsuits followed all over the
After the plaintiffs’ attorney in O’Connor attempted to settle the lawsuit, the NYTWA
mobilized California drivers to object to the settlement. On behalf of New York Uber
drivers, they also filed a state wage and Fair Labor Standards Act lawsuit in federal
district court in New York in July 2016. Although the court decided that the NYTWA
could not be party to the suit, despite the fact that it represents a large percentage of
Uber drivers, the case remains active.
While private plaintiffs’ attorneys have brought a number of cases, the government has
brought few. Only two administrative agencies have publicly initiated investigations
against Uber. In February 2016, the National Labor Relations Board Region 20 (San
Francisco) filed a suit against Uber in federal court for failing to comply with the NLRB’s
investigation of the company’s alleged violations of the National Labor Relations Act
(NLRA). The NLRB Region 20 is conducting a coordinated investigation on behalf of
NLRB regions across the country on whether or not Uber is an employer. In another
case, the chief investigator for the Alaska Workers’ Compensation Board initiated an
investigation against Uber in 2015, when Uber first entered Alaska. The Board fined
Uber $71,000 for misclassifying their workers as independent contractors under Alaska’s
workers’ compensation laws. Uber subsequently left Alaska. Two years later, however,
the Alaska legislature passed a bill essentially overriding the Board’s finding and
specifically exempted Uber from workers’ compensation laws (Asher-Schapiro 2017).
Uber returned.
29 Due to the proliferation of arbitration agreements in contracts, membership in consumer and
worker class actions have been limited to those few who “opt out” of the arbitration agreement.
In the O’Connor case, Judge Edward Chen initially found Uber’s arbitration clausehidden in its
drivers’ contractto be unenforceable because it was accompanied by another unenforceable
waiver of rights. Thus, a large number of driverseven those who had not opted out of the
arbitration agreementwere certified in the class. The 9th Circuit, however, eventually reversed
Judge Chen’s decision, enforcing the arbitration agreement and diminishing the size of the class
and the potential impact of a decision in O’Connor. The plaintiffs’ attorney has since attempted to
arbitrate the individual claims of those drivers who were excluded from the class.
The recent and rapid growth of the platform economy raises a number of questions
regarding if and how to regulate a work relationship that is intermediated by an online
platform. This expanding world of work represents both a continuation of a longer-term
move toward contingent work and a “fissured” workplace, in which the relation between
the supplier and demander of labor is more distant and intermediated. Labor platforms
are quite varied in the way in which they are situated regarding this intermediating role,
raising a number of regulatory issues regarding the rights and benefits to which workers
are entitled.
Uber is a crucial case in the analysis of labor regulation: compared to most labor
platforms and independent contractor work relations, it comes closest to the kind of
control over work conditions envisioned in legal definitions of employee status. Yet
drivers, as atomized actors, have found it difficult to mobilize for pro-labor outcomes.
While some driver protests have been mounted, they are generally small, infrequent,
and not immediately successful. Instead, drivers are most often represented by
surrogates, who act in their own interests and thereby shape the representation of
drivers. Although city councils and legislatures have enacted regulations on safety,
consumer protection, and competition issues, regulations addressing drivers’ rights and
benefits have been almost entirely absent in these elected venues. Despite the relative
frequency with which they are brought to court, labor issues have gone largely
unregulated in that venue as well. Consonant with the interests of plaintiffs’ attorneys
who bring these cases, class actions related to workers’ rights have been settled,
dismissed, or stalled without resolution of whether drivers are owed traditional
employment protections.
Legislative and court venues each have potential advantages and disadvantages. The
fact that labor issues have been introduced more frequently in courts reflects their “low
barriers to entry,” as cases can be brought by attorneys representing one or a relatively
small group of drivers. Legislative venues, on the other hand, have higher barriers to
entry, as drivers must mobilize collectively in relatively large numbers to influence the
regulatory process. We have found little evidence to suggest that drivers are capable of
effectively coordinating such action without the assistance of surrogates, who, apart from
Uber, are also relatively politically weak in legislative arenas. Another contrast lies in the
potential for policy innovation. In courts, labor regulation appears as a “backwards-
looking” matter, with courts attempting to “fit” drivers into existing categories (e.g.,
employee) that may be outmoded or too narrowly focused for the realities of work in the
gig economy. In contrast, legislative venues can innovate, devising new categories and
regulations and updating long-standing forms of worker classification.
To date, across the U.S., regulations that address labor issues have only rarely been
adopted. To the extent that Uber is an easycase for regulation, this finding suggests
that regulations advancing labor issues for gig work on other platforms are unlikely.
Alba, D. (2016, February 16). Angry Uber Drivers Threaten to Make a Mess of the Super
Bowl. Wired. Retrieved from
Aloisi, A. (2016). Commoditized Workers. Case Study Research on Labour Law Issues
Arising from a Set of ‘On-Demand/Gig Economy’ Platforms. Comparative Labor
Law & Policy Journal 37(3), 653-690.
Asher-Schapiro, A. (2017, June 28). Uber Still Doesn’t Get It: Company Docs Reveal
Flimsy Plan for Injured Workers. The Intercept. Retrieved from
Bahler, K. (2016, October 28). New York’s Freelancer Pay Law is Good News for Gig
Workers Everywhere. Money. Retrieved from
Barro, J. (2015, January 7). New York City Taxi Medallion Prices Keep Falling, Now
Down About 25 Percent. The New York Times. Retrieved from
Befort, S. F. (2002). Labor and Employment Law at the Millennium: A Historical Review
and Critical Assessment. Boston College Law Review 43, 351-460.
Belous, R. S. (1995). The Rise of the Contingent Work Force: The Key Challenges and
Opportunities. Washington and Lee Law Review, 52(3), 863-878.
Benn, E. (2016, August 29). Get Ready for an NFL Data Blitz. San Francisco Chronicle.
Retrieved from
Bernhardt, A. (2014). Labor Standards and the Reorganization of Work: Gaps in Data
and Research. IRLE Working Paper No. 100-14. Retrieved from
Bhuiyan, J. (2014a, September 19). Behind the Scenes of Uber’s Biggest Driver Strike.
Buzzfeed News. Retrieved from
Bhuiyan, J. (2014b, September 12). Uber Caves to Striking Drivers’ Demands. Buzzfeed
News. Retrieved from
Bhuiyan, J. (2017, May 23). Uber admits that it has underpaid tens of thousands of
drivers in New York since late 2014. Recode. Retrieved from
Burns, R. (2014, October 22). The Sharing Economy’s ‘First Strike’: Uber Drivers Turn
Off the App. In These Times. Retrieved from
Campbell, H. (2016a, January 8). Uber to Cut Rates in More than 100 Cities. The
Rideshare Guy. Retrieved from
Campbell, H. (2016b, December 19). Will Uber Cut Rates in January 2017?. The
Rideshare Guy. Retrieved from
Campbell, H. (2017a, July 12). How to Calculate Uber’s Percentage in an Upfront Fare
World. The Rideshare Guy. Retrieved from
Campbell, H. (2017b, March 29). How to Fix Uber and Lyft’s Rating System. The
Rideshare Guy. Retrieved from
Campbell, H. (2017c, September 4). Is Surge Gone for Good? The Rideshare Guy.
Retrieved from
Chen, L., Mislove, A., & Wilson, C. (2015) Peeking Beneath the Hood of Uber. Working
Collier, R., Dubal, V. B., & Carter, C. (2017). Disrupting Regulation and Regulating
Disruption: The Politics of Uber in the United States. Working Paper
De Stefano, V. (2015). The Rise of the “Just-In-Time Workforce”: On-Demand Work,
Crowdwork, and Labor Protection in the “Gig-Economy”. Comparative Labor Law
& Policy Journal 37, 471-503.
Dubal, V.B. (2017a). The Drive to Precarity: A Political History of Work, Regulation, and
Labor Advocacy in San Francisco’s Taxi and Uber Economies. Berkeley Journal
of Employment and Labor Law, 38, 132-4.
Dubal, V. B. (2017b). Wage Slave or Entrepreneur?: Contesting the Dualism of Legal
Worker Identities. California Law Review, 105, 65:123.
Dubal, V.B. (forthcoming). Winning the Battle, Losing the War?: Assessing the Impact of
Misclassification Litigation on Workers in the Gig Economy . Wisconsin Law
Review. On file with Author.
Evans, D. S. (2003). The Antitrust Economics of Multi-Sided Platform Markets. Yale
Journal on Regulation, 20(2), 325-381.
Evans, D. S., & Noel, D. (2007). Defining Markets that Involve Multi-Sided Platform
Businesses: An Empirical Framework With an Application to Google’s Purchase
of DoubleClick. Retrieved from
Eidelson, J. (2017). It’s a New Game for Uber Drivers if New York Passes This Law.
Bloomberg Businessweek. Retrieved from
Farhang, Sean (2011). The Litigation State: Public Regulation and Private Lawsuits in
the U.S. New Jersey: Princeton University Press.
Feuer A. (2016, February 19). Uber Drivers Against the App. The New York Times.
Retrieved from
Gleason, C., & Lambert, S. J. (2014). Uncertainty by the Hour. Open Society
Foundations’ Future of Work Project. Retrieved from
Goncharova, Masha (2017, January 12). Ride-Hailing Drivers are Slaves to the Surge.
The New York Times. Retrieved from
Griswold A. (2014, September 12). Uber Just Caved on a Big Policy Change After Its
Drivers Threatened to Strike. Slate. Retrieved from
Grossman, N. & Woyke, E. (2015, November 12-13). Serving Workers in the Gig
Economy: Emerging Resources for the On-Demand Workforce. Paper presented
at Next: Economy What’s the Future of Work?, San Francisco, CA.
Hacker, Jacob (2006) The Great Risk Shift: the Assault on American Jobs, Families,
Health Care, and RetirementAnd How You Can Fight Back. Oxford University
Hall, J. & Krueger, A. (2017). An Analysis of the Labor Market for Uber’s Driver-Partners
in the United States. ILR Review, 1-28.
Hill, S. (2015). Raw Deal: How the “Uber Economy” and Runaway Capitalism are
Screwing American Workers. New York: St. Martin’s Press.
Hook, L. (2016, February 7). Uber Drivers’ Super Bowl Protest Fizzles. Financial Times.
Retrieved from
Horowitz, S. (2016, May 10). Freelancers Union Looks to Bring Portable Benefits to On-
Demand Workers Nationwide. Freelancers Union. Retrieved from
Huws, U. (2003). The Making of a Cibertariat: Virtual Work in a Real World. New York:
The Monthly Review Press.
Irani, L. (2015, January 15). Justice for “Data Janitors”. Public Books. Retrieved from
JP Morgan Chase Institute. (2016). Paychecks, Paydays, and the Online Platform
Economy: Big Data on Income Volatility. Retrieved from
Kaplan, E., Gleason, C., DeWitt, C., & Sjoquist, D. (2015, November 12-13). Workplace
Monitoring, Algorithmic Scheduling, and the Quest for a Fair Workweek. Paper
presented at Next: Economy What’s the Future of Work?, San Francisco, CA.
Katz, L. & Krueger, A. (2016). The Rise and Nature of Alternative Work Arrangements in
the United States, 1995-2015. NBER Working Paper No. 22667. Retrieved from
Kenney, M. & Zysman, J. (2016). What Is the Future of Work? Understanding the
Platform Economy and Computation-Intensive Automation. Paper prepared for
the Seminar on the Politics of Work and Welfare in the Platform Economy at the
Radcliffe Institute, Cambridge, MA.
Kokalitcheva, K. (2016, August 24). Uber’s Latest Perk for Drivers Is a Fancy Savings
Management Service. Fortune. Retrieved from
Kosoff, M. (2014, October 22). Uber Drivers Across the Country are Protesting Today
Here’s Why. Business Insider. Retrieved from
Krisher, T. & Skidmore S. S. (2017, March 1). Drivers rebel against Uber’s Price-Cutting
Quest for Growth. The Seattle Times. Retrieved from
Lambert, S. J., Fugiel, P. J., & Henly, J. R. (2014). Precarious Work Scheduling among
Early-Career Employees in the US: A National Snapshot. Retrieved from EINet,
The University of Chicago
Lawler, R. (2013, June 12). Uber Confirms UberX Price Cuts in San Francisco to Target
Rivals Lyft and SideCar. Retrieved from
Lee, Min Kyung, Daniel Kusbit, Evan Metsky, and Laura Dabbish. (2015). "Working with
Machines: The Impact of Algorithmic and Data-Driven Management on Human
Workers." In Proceedings of the 33rd Annual ACM Conference on Human
Factors in Computing Systems.
Leung, M. (2016). Learning to Hire? Hiring as a Dynamic Experiential Process in an
Online Market for Contract Labor. IRLE Working Paper No. 113-16. Retrieved
Lobel, Orly (2016). The Law of the Platform. Minnesota Law Review, 101(1), 87-166.
Lomas, N. (2016, October 28). Uber Loses Employment Tribunal in the UK. Tech
Crunch. Retrieved from
Middleton, J. (1996). Contingent Workers in a Changing Economy: Endure, Adapt, or
Organize?. N.Y.U. Review of Law and Social Change, 22, 557-621.
Mukherjee R. (2017, July 14). Uber Drivers are Employees, Says South Africa’s Labour
Commission. Medianama. Retrieved from
Munoz, E. (2016, February 10). Uber is Using its US Customer Service Reps to Deliver
its Anti-Union Message. Quartz. Retrieved from
Perea, C. (2017, May 24). Uber Makes Big Changes to Commission and Upfront Pricing.
The Rideshare Guy. Retrieved from
Pew Research Center (2016). Shared, Collaborative and On Demand: The New Digital
Economy. Retrieved from
Rosenblat, A. & Stark, L. (2016). Algorithmic Labor and Information Asymmetries: A
Case Study of Uber’s Drivers. International Journal of Communication, 10, 3758-
Said, C. (2016, February 4). Will Protesting Uber Drivers Disrupt Super Bowl Transit?
The San Francisco Chronicle. Retrieved from
Schaller, B. (2016). Appendix B: Taxi, Sedan, and Limousine Industries and
Regulations. In National Research Council (U.S.). Transportation Research
Board, Special Report 319: Between Public and Private Mobility, Examining the
Rise of Technology-Enables Transportation Services.
Standing, G. (2011). The Precariat: The New Dangerous Class. London: Bloomsbury
Torpey, E. & Hogan, A (2016, May). Working in a Gig Economy. Retrieved from
Uber Newsroom (2015, November 3). Uber and the American Worker: Remarks From
David Plouffe. Retrieved from
Walker, A. (2017, April 5). Competition from Uber and Lyft puts yellow taxi medallion
value at its lowest of the century. Curbed: New York. Retrieved from
Walker, E. T. (2014). Grassroots for Hire: Public affairs consultants in American
democracy. Cambridge: Cambridge University Press.
Weil, D. (2014). The Fissured Workplace: Why Work Became So Bad for So Many and
What Can Be Done to Improve It. Cambridge, MA: Harvard University Press.
... But during high demand, gig platforms keep track of workers' productivity by promoting incentives systems based on their reputation and ranking, and discouraging switching jobs within the gig sector (Ray et al., 2019). Many gig platforms like ridesharing and food delivery platforms fix a minimum amount of login period and specify the number of deliveries to incentivize their gig workers based on algorithm system (Wu and Zheng, 2020;Collier et al., 2017). Yet gig platforms often intervene with bonuses and incentives of these gig workers and regulate the work floor by strict control over the terms and conditions of receiving these incentives (Parwez and Ranjan, 2021;Krijger, 2019;Butschek et al., 2019;Adams et al., 2018). ...
... The matching of algorithms with clients depends on the competition faced by these platforms, which reduces gig workers' hourly pay wages, thus reducing their earnings unambiguously (Schwellnus et al., 2019;Ostoj, 2019). The regulations addressing high competition and the gig workers' rights are almost absent in most legislative decisions (Collier et al., 2017). Many studies reveal that gig platforms try to develop new forms of algorithmic shortlisting of gig workers to ease the roles of recruiters during fierce competition (Williams et al., 2021). ...
... An identity proof and a copy of the registered license is required to be deposited along with onboarding fees (Van Doorn et al., 2020;Heeks, 2017;Hunt et al., 2018). The platforms exercise strict control over the conditions of work of gig workers after checking their background and other details like experience, qualifications and knowledge (Collier et al., 2017;Norlander et al., 2021;Donovan et al., 2016). This is a part of their training regime. ...
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Purpose The alternative arrangements to traditional employment have become a promising area in the gig economy with the technological advancements dominating every work. The purpose of this paper is to explore the barriers to the entry of gig workers in gig platforms pertaining to the food delivery sector. It proposes a framework using interpretive structural modelling (ISM) for which systematic literature review is done to extract the variables. This analysis helps to examine the relationship between the entry barriers to gig platforms. The study further proposes strategies to reduce the entry barriers in gig sector which would help to enhance productivity and generate employment opportunities. Design/methodology/approach The study uses interpretive structural model (ISM) to ascertain the relationship between various entry barriers of the gig workers to the gig platforms. It also validates the relationship and understand the reasons of their association along with MICMAC analysis. The model was designed by consulting the gig workers and the experts allied to food delivery gig platforms namely Zomato and Swiggy. Findings It was observed that high competition, longer login hours and late-night deliveries are the significant barriers with high driving power and low dependence power. Poor payment structures and strict terms and conditions for receiving the incentives are interdependent on each other and have moderate driving and dependence power. The expenses borne by the gig workers, such as Internet, fuel and vehicle maintenance expenses have high dependence power and low driving power. Hence, they are relatively less significant than other barriers. Research limitations/implications The study is confined to food delivery sector of India, without considering other important sectors of gig economy for generalizing the framework. As the study is based on forming an ISM framework through literature review only, it does not consider other research methods for analysing the entry barriers to the gig platforms. Practical implications The study attempts to dig out the low entry barriers for gig workers in food delivery platforms as there is a dearth of analysis of these factors. This study would weave them using ISM framework to help the gig platforms overcome these barriers at various levels, thus adding to the body of literature. Originality/value The study discusses the need for understanding relationship between the entry barriers in the form of ISM model to identify the dependent and driving factors of the same.
... Similar to teleworking, extant studies state that there is a gap with regard to how individuals perceive gig employment opportunities and how these opportunities affect them (Gleim et al., 2019). The discussion around gig work emphasises different variants of gig jobs and their positive aspects, such as schedule flexibility and higher levels of compensation (Hall & Krueger, 2018), while it criticises the eroded employment standards and lack of regulation associated with this type of work arrangement (Collier et al., 2017;Racabi, 2021). ...
Researchers and practitioners are becoming increasingly concerned with the consequences of modern work arrangements for our understanding of work. This article, alongside the four papers which are included in the special issue, explores the implications of new ways of working for employees. We conceptualise new ways of working as an ongoing transformative process, characterised by unprecedented spread, speed and depth of transformation, and highlight four major changes in work which impact employees’ experiences. We critically evaluate the implications of each change for employees’ attitudes, performance and wellbeing, and suggest areas where more research is needed to deepen our knowledge about how modern work arrangements affect employees.
... Inoltre, la diffusione del management algoritmico potrebbe preludere a un ulteriore frammentazione dei processi produttivi e a una conseguente crescita della già ampia quota di lavoro non-standard 3 . I rischi sociali che hanno caratterizzato il diffondersi delle piattaforme digitali sono venuti alla ribalta con il proliferare di mobilitazioni (Collier et al. 2017) e di cause di lavoro intentate, allo scopo di vedersi riconosciuti diritti e tutele, dagli stessi lavoratori delle piattaforme (De Stefano 2015;Donini 2020). Ciò ha parallelamente accresciuto l'interesse della ricerca scientifica sul tema. ...
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This article contributes to the growing empirical literature on the platform economy. By relying on an original European online survey on platform and non-standard work, it provides evidence on the socio-demographic and occupational characteristics of platform workers in France, Germany, Italy, the Netherlands, Poland, Portugal, Romania, Slovakia, Spain, and Sweden. The article aims to profile European platform workers by comparing their socio-demographic characteristics with those of non-standard workers. Further, it explores how and to which extent working on a labour platform can increase the individual perception of socio-economic vulnerability.
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Introducción: La economía de plataformas ha invadido las relaciones sociales de todo orden. Producto de la revolución informacional, la inteligencia artificial y el big data[1], las plataformas constituyen un signo de época que atraviesa y profundiza el conjunto de las relaciones mercantiles preexistentes, a la vez que mercantiliza una serie de actividades que, hasta su llegada, se encontraban ajenas a la lógica extractiva de datos. Las consecuencias de esta irrupción para el mundo del trabajo son múltiples y profundas. Objetivos: Aquí nos proponemos analizar las prácticas de control y las condiciones de trabajo en UBER, una empresa que constituye un paradigma de las nuevas lógicas de gestión del trabajo a través de plataformas digitales. Metodología: El estudio es de carácter cualitativo, se basa en diez entrevistas en profundidad realizadas durante los años 2019 y 2020 a personas que conducen para UBER, en las cuales se indagó, entre otras dimensiones, sobre condiciones de trabajo, mecanismos de control y sentidos del trabajo. Asimismo, se realizó el seguimiento periódico de dos foros de conductores y pasajeros. Resultados: A lo largo del escrito se observa una multiplicidad de prácticas cotidianas desarrolladas por la empresa Uber para incidir en los comportamientos y controlar la actividad de las personas conductoras. Se verifica la capacidad de la plataforma para gestionar algorítmicamente el trabajo de modo masivo y personalizado, con efectos significativos sobre las condiciones de trabajo. [Continúa leyendo en el artículo]
The article discusses the idea and proposes digital framework models for creating platform for higher and professional education based on Education as a Service (EaaS) model. The prerequisites for creating such a new type of educational approach, which could, through the digital integration of existing educational services, create a single ecosystem for obtaining competencies on an individual request are described in the paper. The basic principles for the development of a digital platform that implements the ecosystem of the EaaS model are discussed in the paper: principle of competency-based learning, principle of service-oriented education, principle of open recourses, principle of student-centered education and principle of academia-business partnerships. The architecture of the system functionally grouped at four levels, which form the frame of the EaaS model: pedagogical level, organizational level, competence level, technological level. The main components of its architecture are described in the paper.KeywordsEducation as a serviceCompetence-based educationEducation ecosystemEducation digital platform
The digital revolution is bringing new competition to education compared to classical universities, especially in the form of more accessible online education. At the same time, interest is growing in the mobility of educational services, which is designed to bridge the gap between businesses that require new competencies, the inertia of universities in providing them within the framework of classical programs, and the student’s desire to instantly receive services to master new competencies. All this is accompanied by the development of a competency-based approach to education, which allows structuring the needs of society and clearly formulating the demand of society for the training of professionals. This need has already been formulated in the form of European standards and professional frameworks that create a regulatory framework for the implementation of new approaches to education. The paper describes the initial results of the study, the aim of which was to create a fundamental feasibility model for a cloud-based service-oriented education platform for the next generation of an educational institution. This article presents the Service Delivery Model, which provides a description of the main functions of the proposed digital educational platform.
Penelitian ini mengkaji tentang pelaksanaan hak jaminan kesehatan pengemudi transportasi daring di Kediri pada masa pandemi Corona Virus Disease 2019. Tujuan penelitian ini adalah untuk mengetahui bentuk pelindungan atas hak jaminan kesehatan untuk pengemudi transportasi daring. Penelitian ini menggunakan metode penelitian hukum empiris. Berdasarkan hasil penelitian yang dilakukan pada periode Juli - September 2020 di Kediri, menunjukkan bahwa karena pola hubungan hukum antara pengemudi transportasi daring dan pemilik aplikasi ride sharing bukanlah sepenuhnya hubungan kerja, mereka tidak mendapatkan hak jaminan kesehatan seperti pekerja pada umumnya. Sebagian pengemudi transportasi daring kemudian memilih mendaftar program jaminan kesehatan dari pemerintah yakni BPJS dalam skema Pekerja Mandiri atau skema Bukan Penerima Upah. Hal ini tentu saja tidak ideal karena tanggung jawab untuk memberikan hak atas jaminan kesehatan ada pada pemerintah dan pengemudi transportasi daring itu sendiri. Pemilik aplikasi ride sharing sebagai pihak yang juga mendapat keuntungan dari pekerjaan yang dilakukan oleh pengemudi transportasi daring tidak dibebani oleh tanggung jawab ini.
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La frontera líquida entre lo personal y lo laboral ya no es debida, exclusivamente, a la utilización por parte de la empresa de medios de control tradicionales, sino a la mejora de las tecnologías y al desarrollo de nuevas aplicaciones, intensificando la capacidad del/la empleador/a de impartir órdenes e instrucciones, permitiendo, por ejemplo, que las personas puedan trabajar desde cualquier lugar y estén permanente localizadas y controladas, lo que viene denominándose empleado 3.01 . Hasta el momento, con los medios tecnológicos de que disponíamos en el siglo XX, los problemas más frecuentes que se han generado en este ámbito de manera previa a la introducción de la nueva normativa de protección de datos (Reglamento europeo y nueva Ley Orgánica de Protección de Datos) han sido los relevantes al uso y control de los medios informáticos de la empresa, el control a través del sistema Global Position System (en adelante, GPS) y el uso de la empresa de los datos personales del/la trabajador/a; los problemas se han planteado, no tanto por la incorporación de tales tecnologías como, por la conectividad de las mismas2 . Pero, están surgiendo nuevas problemáticas en este futuro del trabajo que ya está aquí, que nos deben llevar a profundizar en la normativa interna e internacional, en especial en materia de tiempo de trabajo, su control y el derecho a la intimidad de la persona trabajadora, con objeto de comprobar si la nueva normativa puede adaptarse a ellos o resulta insuficiente, en cuyo caso, debemos realizar nuevos planteamientos legales con urgencia. Porque no olvidemos, como señala Montoya Melgar que “(…) todo el Derecho del Trabajo no es otra cosa que un sistema de progresiva contención del poder empresarial”3 y, creemos, que debe seguir siéndolo para el libre desarrollo de la dignidad humana, como derecho universal de las personas.
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El acelerado desarrollo de las TIC ha propiciado el surgimiento de nuevos modelos de negocios digitalizados con evidentes déficits de trabajo decente. A este nuevo paradigma tecnológico, que ha emergido como excusa perfecta para eludir la legislación social, se une la perpetuación, a escala global, de las tradicionales bolsas de economía sumergida y determinados estereotipos de género que invisibilizan a grandes contingentes de personas trabajadoras que no pueden aspirar a los derechos sociales legalmente establecidos, como sucede en el ámbito del trabajo de cuidados. La conjunción de esas tendencias desreguladoras y la sucesión de crisis económicas típicas del modelo de producción capitalista, con su inevitable secuela de desempleo masivo y precarización de las condiciones de trabajo, han ido conduciendo a un paulatino aumento del riesgo de exclusión social de grandes capas de la población trabajadora para las que el hecho de trabajar ya no les garantiza salir de la pobreza.
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This Article examines both the creation of secure work and its ongoing demise through a critical historical and contemporary case study: over a century of chauffeur work in San Francisco, California. Employing a combination of historical archives and sociological research, I show how chauffeur driving became a site of secure work for much of the twentieth century and how this security unraveled over the course of many years. Since their entrée on the streets in 1909, chauffeur corporations—from the Taxicab Company to Uber—underwent formative re-organizations to shift the liabilities and responsibilities of business onto workers. Counterintuitively, these changes in corporate form were met with decreased regulation and a contracted business-labor bargain. I contend that the transformation of the corporate form, the shrinking bargain, and the rejoinders of the state triangulated to produce worker risk and weaken the relationship between work and security. Part I of this Article describes how militant labor advocacy transformed taxi driving from precarious to secure work in the earliest decades of the twentieth century by compelling municipal regulation and using collective power to shape the business model. Part II explains how by the 1970s, legal decisions to withdraw from the business-labor bargain combined with political and racial discontent among rank-and-file workers set the stage for the complete decline of union power. Part III then tells the post-union story. In the following three decades, even without official bargaining power, worker advocates leveraged municipal regulation to exert minimal control over wages and working conditions. The impact of these tactics, however, was both limited and shaped by the possibilities and constraints of work law. Finally, Part IV turns to the current Uber era and details the course of industry deregulation and labor’s response to the reproduction of risky, early 20th century working conditions. As the “Uber economy” model rapidly expands into other spheres of service work, I maintain that the political history of how chauffeur work went from precarity to security and back may hold important lessons for contemporary labor struggles.
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Platform companies disrupt not only the economic sectors they enter, but also the regulatory regimes that govern those sectors. We examine Uber in the United States as a case of regulating this disruption in different arenas: cities, state legislatures, and judicial venues. We find that the politics of Uber regulation does not conform to existing models of regulation. We describe instead a pattern of “disruptive regulation”, characterized by a challenger-incumbent cleavage, in two steps. First, an existing regulatory regime is not deregulated but successfully disregarded by a new entrant. Second, the politics of subsequently regulating the challenger leads to a dual regulatory regime. In the case of Uber, disruptive regulation takes the form of challenger capture, an elite-driven pattern, in which the challenger has largely prevailed. It is further characterized by the surrogate representation of dispersed actors—customers and drivers—who do not have autonomous power and who rely instead on shifting alignments with the challenger and incumbent. In its surrogate capacity in city and state regulation, Uber has frequently mobilized large numbers of customers and drivers to lobby for policy outcomes that allow it to continue to provide service on terms it finds acceptable. Because drivers have reaped less advantage from these alignments, labor issues have been taken up in judicial venues, again primarily by surrogates (usually plaintiffs’ attorneys) but to date have not been successful.
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In the framework of the so-called “sharing economy”, the number of on-demand companies matching labour supply and demand is on the rise. These schemes may enlarge opportunities for people willing to find a job or to top up their salaries. Despite the upsides of creating new peer marketplaces, these platforms may also be used to circumvent employment regulation, by operating informally in traditionally regulated markets. Literature showed how, by 2009, over 2 million worker accounts had been generated within these frameworks. Productivity may be fostered but, at the same time, a new version of Taylorism is disseminated (i.e. the fragmentation of labour into hyper-temporary jobs – they call them microtasks – on a virtual assembly line), strengthened by globalisation and computerisation. All these intermediaries recruit freelance or casual workers (these continue to be independent contractors even though many indicators seem to reveal a disguised employment relationship). Uncertainty and insecurity are the price for extreme flexibility. A noteworthy volume of business risk is shifted to workers, and potential costs as benefits or unemployment insurance are avoided. Minimum wages are often far from being reached. This paper will present a case study analysis of several “on-demand work” platforms, starting from the Amazon Mechanical Turk, one of the first schemes founded in 2005, which is arguably “employing humans-as-a-service”. It splits a single service in several micro “Human Intelligence Tasks” (such as tagging photographs, writing short descriptions, transcribing podcasts, processing raw data); “Turkers/Providers” (workers) are selected by “Requesters” to rapidly accomplish assignments online, are then rated according to an internal system and are finally paid (also in gaming credits) only if delivery is accepted. After having signed up and worked within some platforms, I comment upon TaskRabbit (thousands people on the service who bid to do simple manual tasks), Handy and Wonolo (personal assistance at a local level), oDesk and Freelancer (online staffing), Uber and Lyft (peer-to-peer ridesharing), Airbnb (hosting service), InnoCentive (engineering solutions), Axiom (legal research or service), BitWine (consultancy). Finally I highlight downsides and upsides of work in these platforms by studying terms of service or participation agreements to which both parties have to agree. I look into several key features such as (i) means of exchange/commodities, (ii) systems of payment, (iii) demographics, (iv) legal issues concerning status and statutory protection of workers, indicators of subordination, treatment of sickness, benefits and overtime, potential dispute resolution, and deprived “moral valence of work” and I discuss potential strategies to address these issues.
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As on-demand labor platforms proliferate the independent contractor business model, plaintiffs' attorneys in the United States have filed dozens of misclassification lawsuits to secure rights and protections for workers. The conventional wisdom is that if these lawsuits are won, then they will reverse the growth of insecure work. This Article challenges this widelyheld assumption. Using empirical research, I examine the trajectories and legacies of three celebrated misclassification lawsuits from earlier moments of transportation "gig work" in California: Tracy v. Yellow Cab Cooperative, Friendly Cab v. NLRB, and Alexander v. FedEx. Against many odds, plaintiff workers secured judicial recognition of employee status in each of these cases. The untold, post-litigation stories, however, were surprisingly grim: workers' economic lives were no more secure-And in some cases more precarious-Then before the lawsuits. While I maintain that such litigation plays an important deterrence role, this Article highlights the significant limitations of misclassification litigation victories in effecting and enforcing the rights of gig workers. Based on this data, I critique the (over) reliance on the private enforcement of employee-status to fight precarity in the on-demand gig economy and suggest lessons for future advocacy.
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Today, whether a worker is legally classified as an "employee" or an "independent contractor" determines whether he or she is entitled to employment and labor law protections. With the proliferation of the on-demand economy the doctrinal definitions and legal analyses of these categories are fiercely contested. While businesses have attempted to confine the definition of employee to limit their financial and legal liabilities and risks, public interest lawyers have worked to broaden the definition, ensuring that more workers are covered and protected by the law. How did U.S. law come to divide workers into these two categories, how have the definitions evolved historically, and how do workers today make sense of them? This Article challenges the duality of worker classification in employment regulation by positioning the employee and the independent contractor in U.S. legal history and in the lives of contemporary workers. Part I situates the debate in work law scholarship. Part II uses historical and legal archives to challenge the prevailing assumptions about the employee and independent contractor classifications in employment and labor law. I argue that the existence of the dualism of worker categories is more recent than previously understood and that contemporary doctrinal tests reflect not bright line legal rules, but evolving political and cultural philosophies about work. Part III investigates the impact of these legal classifications on the ground. Through ethnographic research and analysis, I find that these categories of work have taken on social meaning for workers, often disrupting worker collectivities. The Article concludes that both the doctrinal analyses of the employee category and the lawyering methodologies used to advance the interests of workers must be more attendant to workers' realities.
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.
Uber, the ride-sharing company launched in 2010, has grown at an exponential rate. Using both survey and administrative data, the authors provide the first comprehensive analysis of the labor market for Uber’s driver-partners. Drivers appear to be attracted to the Uber platform largely because of the flexibility it offers, the level of compensation, and the fact that earnings per hour do not vary much based on the number of hours worked. Uber’s driver-partners are more similar in terms of their age and education to the general workforce than to taxi drivers and chauffeurs. Most of Uber’s driver-partners had full- or part-time employment before joining Uber, and many continue in those positions after starting to drive with the Uber platform, which makes the flexibility to set their own hours especially valuable. Drivers often cite the desire to smooth fluctuations in their income as one of their reasons for partnering with Uber.
The so-called “gig-economy” has been growing exponentially in numbers and importance in recent years but its impact on labour rights has been largely overlooked. Forms of work in the “gig-economy” include “crowd work”, and “work-on-demand via apps”, under which the demand and supply of working activities is matched online or via mobile apps. These forms of work can provide a good match of job opportunities and allow flexible working schedules. However, they can also pave the way to a severe commodification of work. This paper discusses the implications of this commodification and advocates the full recognition of activities in the gig-economy as “work”. It shows how the gig-economy is not a separate silo of the economy and that is part of broader phenomena such as casualization and informalisation of work and the spread of non-standard forms of employment. It then addresses the issue of misclassification of the employment status of workers in the gig-economy. Current relevant trends are thus examined, such as the emergence of forms of self-organisation of workers. Finally, some policy proposals are critically analysed, such as the possibility of creating an intermediate category of worker between “employee” and “independent contractor” to classify work in the gig-economy, and other tentative proposals are put forward such extension of fundamental labour rights to all workers irrespective of employment status, and recognition of the role of social partners in this respect, whilst avoiding temptations of hastened deregulation.