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Solidarity across boundaries: a new practice of collectivity among workers in the app-based transport sector in Indonesia

Taylor & Francis
Globalizations
Authors:
  • Solidar Suisse

Abstract

This article discusses new practices of collectivity among drivers in the app-based transport sector in Indonesia, with a case study of motorbike taxi drivers in the country's two major platform companies Go-Jek and Grab. It describes the emergence of transport-related digital platforms and replacement of indigenous transport. The author analyses the labour process and labour control in app-based transport and how drivers resist such algorithmic control. It also highlights the current three models of drivers' organizing (community, association and union), and argues that drivers' practices of collectivity offer invaluable lessons and insights into the development of a new strategy of labour solidarity, relevant for the broader labour movement.
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Globalizations
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Solidarity across boundaries: a new practice of
collectivity among workers in the app-based
transport sector in Indonesia
Fahmi Panimbang
To cite this article: Fahmi Panimbang (2021): Solidarity across boundaries: a new practice of
collectivity among workers in the app-based transport sector in Indonesia, Globalizations, DOI:
10.1080/14747731.2021.1884789
To link to this article: https://doi.org/10.1080/14747731.2021.1884789
Published online: 26 Feb 2021.
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Solidarity across boundaries: a new practice of collectivity among
workers in the app-based transport sector in Indonesia
Fahmi Panimbang
Lembaga Informasi Perburuhan Sedane (LIPS)/Sedane Labour Resource Centre, Bogor, Indonesia
ABSTRACT
This article discusses new practices of collectivity among drivers in the app-
based transport sector in Indonesia, with a case study of motorbike taxi
drivers in the countrys two major platform companies Go-Jek and Grab. It
describes the emergence of transport-related digital platforms and
replacement of indigenous transport. The author analyses the labour process
and labour control in app-based transport and how drivers resist such
algorithmic control. It also highlights the current three models of drivers
organizing (community, association and union), and argues that drivers
practices of collectivity oer invaluable lessons and insights into the
development of a new strategy of labour solidarity, relevant for the broader
labour movement.
KEYWORDS
App-based transport
workers; labour control;
digital platform; algorithmic
resistance; labour solidarity;
collectivity
Introduction
Popular known by many terms (platform, digital, collaborative, sharing, gig economy, etc.), entirely
new business models have emerged in recent years, whereby online platforms use digital technol-
ogies to connect dierent and unassociated groups of users in order to facilitate transactions for the
exchange of goods and services. This model of a digital economy has grown rapidly and globally in
recent years, and takes place at the nexus of two intersecting social phenomena: rst, the prevalence
of digital communications networks in society, and second, the growth of precarious and contin-
gent labour worldwide. Globally, the digital economy has grown faster than Facebook, Google, and
Yahoo combined (Liem, 2015), and the number of precarious workers in this sector of the platform
economy has increased rapidly in many countries.
Since the beginning of 2015, several millions of precarious workers have been working in the
emerging app-based transportation sector in Indonesia, and the countrys digital sector is growing
rapidly due to its huge market. In 2018 alone, there were at least 1807 start-ups active in Indonesia,
the largest number in the ASEAN countries and the sixth largest number worldwide (Adiningsih
et al., 2019). Indonesia has been the target of many new platform companies that adopted a strategic
approach to the countrys vast market, including the growing number of millennials who represent
a large proportion of Indonesias consumer market. With a population of over 267 million and a
workforce of 131.01 million in 2018, the Indonesian population is largely dominated by millennials
(aged between 0 and 34), who account for 33.75 per cent of the total population. There are more
than seven million unemployed persons in the population and over ten million with semi-
© 2021 Informa UK Limited, trading as Taylor & Francis Group
CONTACT Fahmi Panimbang fahmi.panimbang@gmail.com
GLOBALIZATIONS
https://doi.org/10.1080/14747731.2021.1884789
employment status. In addition, the National Development Planning Agency (Bappenas) has pro-
jected Indonesias population to increase to up to 297 million until 2040, of which 64 per cent will
be of working age (Adiningsih et al., 2019). Needless to say, this segment of people has been the
main target of players seeking to gain major market shares in the growing platform economy, in
which mobility and transportation play a signicant role.
This article sheds light on workersorganizing and new practices of collectivity in major
digital platforms in Indonesia (Go-Jek and Grab) amid the rise of the app-based transport sec-
tor in the country. It discusses the question of how app-based workers respond to the growing
dominance of the platform companies and how they organize to deal with the emerging pro-
blems in the workplace; which factors inuenced the solidarity building practices; and what are
the lessons learnt from workersnew practices of collectivity. I argue that driverspractices of
collectivity oer insights into the development of a new organizing strategy for the labour
movement.
The article is structured as follows. In section two the research methodology is described, fol-
lowed by a discussion (in section three) of the emergence of app-based transport and its forceful
replacement of indigenous transport with digitalization. Section four highlights the labour process
and labour control in the app-based transport sector and how drivers resist such algorithmic labour
control. Section ve examines the three models of driver organizing in the app-based transport, and
analyses the driversnew practices of collectivity. The last section concludes with some key points
that the article presents.
Methodology
The research focuses on worker/driver organizing strategies in app-based motorbike taxi services
in Indonesia in two major companies: Go-Jek and Grab. I use driverand workerinterchange-
ably throughout the article to refer to those who work as drivers in the transportation industry,
including app-based transportation. My analysis draws on data collected through structured and
semi-structured interviews and focus group discussions (FGD) with (1) conventional (indigen-
ous) transport drivers; (2) app-based transportation drivers; (3) app-based driver communities,
associations, and unions; (4) union representatives; and (5) researchers and activists from non-
governmental organizations (NGO). All interviews were conducted during two rounds of eld-
work between October and December 2019 and January and February 2020, mainly in Jakarta,
Bekasi, Cikarang, Depok, and Bogor, where the largest number of app-based transport workers
are concentrated, but also in the provincial capitals of Serang (Banten), and Bandung (West
Java). These cities account for more than 50 per cent of total app-based transportation workers
in the country.
The selection of drivers and driver organizations for interviews and focus group discussions took
into account the active organizing work of drivers at the time this research was conducted and con-
sidered the signicant number of factory workers in industrial areas who took up part-time jobs as
app-based drivers. This selection is useful to understand how established unions respond to and
connect with emerging issues of app-based workers and the needs involved in their organizing
drives. I interviewed a total of 44 drivers and driver communities (40 men and 4 women), 12 driver
community organizers (10 men and 2 women), 6 conventional transport drivers (all male); and 8
labour unionsactivists (7 men and 1 woman). I also discussed with 5 NGO activists (4 men and 1
woman), and 4 researchers (3 men and 1 woman).
2F. PANIMBANG
The emergence of app-based transport and its market domination
Popularity of motorbikes taxi (ojek) prior to digitalization
Poor public transport in Indonesia is one of the problems that triggered the increasing use of pri-
vate vehicles such as motorbikes. The number of vehicles in the country has increased while in gen-
eral its roads are hardly widened, which caused an ever-increasing road trac and, consequently,
notorious trac congestion. The sale of motorbikes and other vehicles has increased dramatically
from 13.2 million units in 1995121.4 million units in 2015 (Katadata, 2017). This has worsened the
clogged trac in many cities on Java, especially Greater Jakarta. Notably, more than half of the
entire Indonesian population lives on the island of Java, and the island has one of the highest popu-
lation densities in the world.
Due to the limited availability of jobs in the countrys market, there is a large proportion of
low-income and/or unskilled people working as drivers in the informal transport sector. Such an
informal sector exists, especially in urban areas, in part because the capacity of formal public
transport services in the greater Jakarta area is still insucient to meet the ever-increasing popu-
lation demand for travel and commute. This informal transport exists with its own rationality,
that is to provide services to commuters and to earn income for drivers and their families. This
paratransit
1
is one of the unique features of Indonesian transport, where these types of informal
transportation are academically referred to as indigenous transport(Cervero, 2000). Motorbike
taxis or known locally as Ojek are the most popular form of indigenous transportation across
Indonesia. In many small to medium size towns, especially on the outer islands of the Indone-
sian archipelago, the two-wheeler ojeks are even becoming the predominant means of public
transport.
Ojek is an unlicensed motorbike taxi that operates randomly in most areas of Indonesia, from
large cities where jammed trac commonly inhibits other forms of transportation, to rural areas
inaccessible to four-wheeled vehicles. Ojek usually carries a passenger, who is seated behind the
motorbike driver who is mostly male. Many people in Indonesia choose ojek over taxi cars,
which are safer, but more expensive and slower due to trac congestion. Despite coming with a
high-risk of accidents, ojek is still the most popular and ubiquitous form of informal transport.
As an unocial means of transportation, self-employed ojek drivers do not need to obtain permits
or licenses, so anyone can become an ojek driver even without a drivers license (Kusno, 2016). As
Kusno (2016) points out, ojek has been the prime symbol of privatelower-class grassroots trans-
port that has lled the gap in the countrys poor public transportation system.
Ojeksrapid growth over the past few decades has been largely driven by the widespread avail-
ability of cheap domestic motorbikes from Japanese brands and even cheaper motorbikes recently
imported from China. Easy credit arrangements for the purchase of motorbikes and the ease with
which drivers licences can be obtained have also been a major contributor to motorbike sales in the
country, which has increased from 8.1 million motorbikes in 1994 to 12.6 million units in 1998 and
47.7 million units in 2008, and rocketed to 98.9 million units in 2015 (Katadata, 2017).
Although the ojek is generally unlicensed, sometimes the ojek ranks or opang
2
in given neigh-
bourhoods are self-regulated and managed by its own community of drivers. Self-regulation
aims, among other issues, to limit the number of ojek operations in the neighbourhood and to
assure members regularly receive orders or fares. Some ojek ranks issue their own permit called
opang card, the cost of which varies between US$ 50-1000,
3
depending on the potential incomes
and the number of passengers per day in the area (interview with indigenous transport drivers,
GLOBALIZATIONS 3
November 2019). However, ojek is still considered as an unocialentity, counted as outside the
legal status of the transportation authority. There are no ocial data on ojek.
There is little documentation on the history of ojek in the greater Jakarta area but it seems to
have developed massively since the Asian nancial crisis in 1997/1998, particularly when pedicabs
(cycle-rickshaws or three-wheeled pedal-powered bike with a passenger seat, locally known as
becak) were nally banned from operations in Jakarta in November 1999 (Kusno, 2016; The Jakarta
Post, 21 November 1999), when the Jakarta government conscated more than 100,000 pedicabs
and an estimated 40,000 were thrown into the Java Sea (Cervero, 2000). The nancial crisis that
hit the country had left several million people unemployed and made motorbike taxi services a
new means for people to earn a living. Many ojek drivers in the greater Jakarta area chose the pro-
fession after being laid-ofrom their jobs after the 1998 riots following the nancial crisis, as there
were not enough jobs available in the cities. Unfortunately, the period of the nancial crisis in 1997/
1998
4
became a historic moment of the emergence of ojek, as well as late 1999 in relation to the
complete extinction of pedicabs from the greater Jakarta area. These are unwritten episodes of
Indonesias working-class history (Kusno, 2016).
Coercive replacement of the conventional motorbike taxis (ojek) by the app-based
motorbike taxis (ojol)
Since the beginning of 2015, ojek drivers in Indonesia went increasingly online with app-based ser-
vices, gradually outnumbering the entire conventional ojek. Since then, the era of digital platforms
began in this ride-hailing sector. In the app-based transportation industry in Indonesia, Go-Jek and
Grab are the two leading companies that have been in business for nearly a decade. Go-Jek is an
Indonesian company founded in 2010. It began by oering an online motorbike taxi booking ser-
vice,
5
now called Go-Ride, and later expanded its scope to oer a range of dierent services. After
the app launched in January 2015, it was downloaded by 10 million users and then rose to more
than 35 million users in early 2017 (Ford & Honan, 2017). In Indonesia alone, there were over
2.5 million drivers actively working for Go-Jek in 2019, providing services in more than 167 cities
and districts (Adiningsih et al., 2019). Go-Jek also operates in Viet Nam, Thailand, Singapore and
the Philippines.
The second major player, Grab, is a Singapore-based company founded in Malaysia in 2012,
which entered the Indonesian market when it launched the GrabTaxi service in Jakarta in June
2014, followed by GrabBike and GrabCar in 2015 (Ford & Honan, 2017). Grab operates in 100 cities
in Indonesia, and in many cities in other Southeast Asian countries. The number of Grab-bike and
Grab-car drivers surpassed 2 million when it acquired the Indonesian operations of Uber in early
2018. In 2019 Grab employed more than 9 million drivers throughout Southeast Asia, oering 14
dierent types of on-demand services (Jayani, 2019). Both Go-Jek and Grab are Southeast Asias
ride-hailing giants and increasingly expand to other on-demand services, including food delivery
services, convenience goods, and urban logistics.
Go-Jek and Grab have eliminated many competitors. They have been battling it out with each
other to see who is capable of monopolizing the market, and more recently, they are reportedly dis-
cussing a merger deal (Eloksari, 2020). The two companies display an ingrained desire to monop-
olize the on-demand market, and also exhibit anticompetitive structures. One of the reasons for this
is that the massive acquisition of proprietary digital metadata can provide a very signicant com-
petitive advantage to a single operator, since the greater the number of interactions that occur
through the application platform, the better the algorithm that governs the transactions and the
4F. PANIMBANG
underlying services (Smorto, 2018), and it certainly controls the workers. This tendency towards
monopoly, like the practice of capital and investment in general, has had a number of consequences
and raised several problems.
Venture capital investments are the main drivers behind the rise of digital platform companies
like Go-Jek and Grab, which are able to leverage vast resources and aggressively oer their services
to consumers. One tactic employed by these companies is the price wars with their competitors.
App-based transport companies, all of them well-endowed with nancial investment, can subsidize
costs and oer a much lower price to consumers than indigenous transport drivers. When an app-
based means of transportation has secured a dominant position in the market, it becomes the sole
point of access for drivers and passengers. This clearly increases the danger of an imbalance in bar-
gaining power in favour of app-based transport companies against their workers. In the long run,
consumers are at risk of facing much higher rates and workers of experiencing exploitation due to
the societys dependence on app-based transport. Notably, application-based transport services in
Jakarta are now superior to and cheaper than others. Also, research indicates that commuter train
users in Jakarta are becoming dependent on app-based transport services, and the use of appli-
cation-based transport exceeds the proportion of public transport (Bus Rapid Transit and micro-
bus) at many commuter train stations (Saan & Rizki, 2018). On the other hand, several studies
nd that the business practices of app-based transport have not reduced the number of motorized
vehicles owners and the number of trips taken, and even vehicle miles travelled (VMT) increased
due to the availability of this inexpensive, accessible service. In a nutshell, digital platform compa-
nies such as Go-Jek and Grab are achieving dominance and commercial success at the expense of
labour and the environment (Davidson & Infranca, 2018; Nastiti, 2017; Retamal & Dominish, 2017;
Saan & Rizki, 2018), and potentially even consumers. This, in turn, has the potential to negatively
aect the long-term ability of cities to provide essential public transport services.
Behind the current popularity of Go-Jek and Grab is a history of clashes between indigenous and
app-based drivers, which were the result of erce opposition by indigenous transport companies to
application-based transport services, resulting in protests and violence (Ford & Honan, 2019;
Panimbang et al., 2020). Indeed, app-based transport services have actively worked to displace
the indigenous sector by actively recruiting indigenous transport drivers. Clashes between drivers
in various cities have made headlines and generated controversies in public debate. The govern-
ment was indecisive and slow to respond to protests and conicts from drivers. Between late
2015 and early 2016, the government issued a ban against app-based transport, which was later
retracted following massive protests by app-based drivers (Makki, 2015).
When these horizontal conicts receded, companies began hiring thousands of new drivers
again, deepening the many unresolved horizontal conicts. Go-Jek, for example, moved to recruit
indigenous transport drivers in August 2015, enlisting tens of thousands, and converting them into
Go-Jek workers. At that time, Go-Jek was recruiting thousands of drivers per day (Aulia, 2015).
Companies were hiring drivers up to the age of 55. Drivers had to have their own motorbikes,
but initially received basic training, skills, orientation, as well as two helmets, a jacket, and a smart-
phone that had to be paid in instalments a daily amount was debited from the driversdigital
wallet in the apps on a daily basis (FGD with drivers organizations, October 2019; see also Ford
& Honan, 2017).
App-based transport companies compete with each other to recruit drivers, providing incentives
to migrate from a competing company, and even oering much more incentives to those brokers
who could convince as many drivers as possible to migrate to their platform. This competition in
recruiting drivers is especially evident with regard to motorbike taxi services (interview with app-
GLOBALIZATIONS 5
based drivers, November 2019). Recently, more indigenous transport drivers have joined the app-
based transport sector, especially as companies continue to target them specically for recruitment.
Having to deal with requirements when trying to join these platforms, companies make these
requirements much easier for indigenous transport drivers of any opang. In areas that have experi-
enced high levels of horizontal conict, popularly known as red zones, these companies reimburse
drivers for their opang cardor opang permitand help them obtain a driving license, vehicle docu-
ments, etc. In short, red-zoneopang drivers are warmly welcomed by platform companies to their
business (Interview with former ojek/opang driver, October 2019).
Labour process and labour control in the app-based transport
Algorithmic labour control
Studies on algorithmic labour control in the digital economy analyse how app-based companies
such as Go-Jek and Grab leverage their signicant control over how workers behave on the job
(Gandini, 2019; Nastiti, 2017; Rosenblat, 2018). Using labour process theory, Gandini (2019) ana-
lyses labour control in the gig economy and argues that transformation of labour power into a com-
modity is now mediated by a digital platform where feedback, ranking, and a rating system serve
purposes of managerialization and monitoring of workers. Rosenblat (2018) also analyses how
Uber uses its algorithms to control its workers: instead of monitoring its hundreds of thousands
of workers with human supervisors, Uber has built an app-based transport system with a set of
algorithms that act as a virtual automated manager. This algorithmic labour control was developed
by Uber in the Silicon Valley in the USA, but was very quickly copied by other companies like Go-
Jek and Grab in Southeast Asia and elsewhere that use the same system for such algorithmic labour
control (Nastiti, 2017). As I will elaborate in more detail, app-based drivers in Indonesia are chal-
lenging this algorithmic labour control by, in part, generating algorithm bugs and errors on their
smartphones.
Labour control is based on algorithmic analysis. Once drivers activate their apps, they are con-
stantly monitored and analysed. Nastiti (2017) meticulously identies the methods of labour con-
trol by algorithmic management in the case of Go-Jek. Methods include mechanisms to earn points,
bonuses, ratings, and suspension or deactivation. These methods constitute a carrot and stick: dri-
vers get a bonus if they can accumulate a lot of points, but they are penalized if caught failing.
Nonetheless, disincentives are disproportionately higher than incentives. The system serves as
another strategy for evaluating drivers. If their average rating falls below four stars, drivers are auto-
matically suspended. They are also suspended if they refuse orders.
Not many drivers understand what algorithms are and how they work, but for the most part they
understand that their performance is being controlled and monitored by the apps. They know that
the application on their smartphones controls how they behave in responding orders. Algorithms
sometimes privilege indebted drivers, who still have to pay the company for their jacket and helmet
in instalments that are deducted from the driversaccounts every day. These drivers receive a noti-
cation about locations with passengers requesting a ride. These notications are no longer available
once payment has been settled (interview with driver association, January 2020).
Drivers know that they are in a vulnerable position and always feel compelled to receive a ve-
starrating and positive comments from customers. One bad comment from a customer can ruin
an overall good performance for the last month or two, forcing drivers to keep moving and search-
ing for passengers proactively. When an order comes in, they cannot easily refuse it. The app
6F. PANIMBANG
system managed by algorithms compels drivers to stay active and search for orders. Otherwise, they
risk deactivation from the app or suspension of their account (FGD with drivers, October-Decem-
ber 2019). This form of labour process and labour control bring about negative consequences.
These consequences include the increasing number of road fatalities such as in Cikarang, one of
the busiest industrial areas of Bekasi regency in West Java province, with at least ve trac acci-
dents and fatalities involving app-based drivers occurring each month (FGD with drivers associ-
ation, January 2020). Despite this fact, the company does not provide any assistance to such
occupational accidents and road fatalities. Insurance against accidents has been provided just in
the last few years in response to the driversdemand although they still have to pay the insurance
premium, Go-Jek using a government insurance scheme (BPJS) and Grab providing a private
insurance with a reimbursement of maximum IDR 25 million (US$ 1800). Indonesia is among
nine Asian countries that account for roughly half a million road fatalities annually, a major con-
tributor to the growth of global trac accidents (Jiang & Zhang, 2018). The road accidents and
fatalities in Indonesian cities have increased, and they are among the highest among the ASEAN
countries, and motorbike trac accident is the major contributor (Antara, 2017; Dananjaya, 2019).
Other negative consequences that labour control on digital platforms bring are the increasing
number of occupational diseases, with mostly lung and respiratory-related diseases, haemorrhoids,
back-pain, and exhaustion-related illnesses that lead to other health issues. Certain polluted areas
clearly contribute to the serious lung and respiratory diseases suered by some drivers, which
should be taken into consideration when considering to limit the driversworking hours. Labour
activists of an industrial union in Bekasi in West Java province, worry that at least 30 per cent of
their union members are taking side-jobs as app-based drivers. One of the union members had died
in early 2019, one year after the person joined an app-based transport service. It was observed by
many of his friends, that he was struggling to drive long hours and consumed food supplements to
stay awake and strong, in order to earn points, bonuses, and eventually additional income (inter-
view with union leaders, October 2019). He had the freedom and exibility to work for a digital
platform, but the algorithmic management that propelled him to work longer hours and kept
his performance high, could possibly take the blame for his death. App-based drivers like him
are among those in the gig economy adapting to work for a faceless boss.
Furthermore, companiesdriversdata generated through algorithms are also used to control
taris and rates as well as monitor driversbehaviour in the workplace context. As companies
keep expanding their services, promotional prices and taricuts for passengers are advertised
on a massive scale. Low-priced sales campaignsare at the expense of drivers whose rates are
cut from time to time (Nastiti, 2017). There is no opportunity for drivers to negotiate fares and
rates with the companies, which constantly announce dierent rates and change policies via
short messages or through apps sent unilaterally to drivers. In order to have full control over dri-
vers, app-based transport companies have hired many more drivers, gradually increasing compe-
tition between them and weakening their bargaining power. On the other hand, since December
2019, the new apps algorithms assign only one driver to carry out two food delivery orders in
one go, with drivers being paid much lower rates for the second order, instead of receiving two
fares (FGD with community members, January 2020).
These algorithmic practices reect how technology is constantly changing not only the way we
dene work, but also how it is organized and used to control and monitor workers. For the
moment, app-based transport companies such as Go-Jek and Grab have succeeded in bringing
the world of algorithms into the context of employment, which has a host of implications for
how workers are treated and protected. While regulators and legislators are still sluggishly moving
GLOBALIZATIONS 7
to catch up, the app-based transport companies are rapidly using data-driven algorithms to reshape
the norms of employment and rewrite the rules of work (Gandini, 2019; Nastiti, 2017; Rosenblat,
2018).
Driversalgorithmic resistance
A lot of workers in app-based transport understand that power is a relational concept, that is, that
workersability to realize their own interests may depend, in part, on their capacity to counter the
power of their employers. In the beginning, when platform rms needed to recruit drivers, drivers
structural power was relatively strong. The drivers as a collective are located in the strategic points
in the production or distribution process of the overall transportation business, thus they have a
certain structural power within the company. However, this structural power should be exerted col-
lectively (Luce, 2014) as it was realized by many Indonesian workers in many industrial areas
during labour strikes since 1998 and the subsequent collective actions that include the historic gen-
eral strikes in 20122013 (Caraway & Ford, 2020; Juliawan, 2011; Mufakhir, 2014; Mufakhir, 2017;
Panimbang & Mufakhir, 2018).
Platform drivers increasingly realized that the honeymoonis over; no more bonuses and money
they can easily get from the platform company. Many have experienced suspension without
reasons. Drivers do not get any orders for the whole day or week. They observe that orders are
given to newly recruited drivers. Competition between app-based drivers to receive orders has
started, and they hope this will not lead to horizontal conict. As a collective, drivers know that
they could do a collective o-bid(turning-othe apps) en masse to disrupt the production or
transaction. To some degree, there are collective repertoires that stimulated the drivers during
recent mobilizations and protests (Panimbang et al., 2020). But that is exactly the purpose of
expanding recruitment of drivers by the company: an excess supply of drivers would weaken
their bargaining power, eventually avoiding possible structural disruption by the workers.
Many drivers resist complying with exploitative control and rule by the algorithm by using fake
GPSbugs (popularly named as tuyul)
6
to work around the workow system. This method allows
drivers to be seen on the application map at a desirable location closer to potential passengers, so
they can receive orders from customers without having to make the eort of getting to the custo-
mer, even though in reality they might be taking a rest at a dierent location (such as at home if this
is not that far away, or at a community secretariat to charge their phone). Drivers claim this is not
wrong because the bookings and trips are real, and trip orders are completed as normal.
Given the increasingly pervasive yet anonymous control by algorithms, drivers have also
employed a variety of resistance tactics to improve their subsistence income. Instead of more
open forms of collective protest against app-based companies, drivers have taken advantage of
some loopholes in the apps. These tactics have included negotiating with costumers about their
orders. For example, a driver asks a customer to cancel an order from the app, when in reality
the trip is still performed at the same price as shown on the app. This means the driver saves 20
per cent the amount of the deduction from his earnings.
Another tactic involves food delivery service, where drivers take advantage of promo and price
discounts that are available. For example, if a customer orders food from Gofood (Go-Jek) and
there are special oers or discounts available for the same item at Grabfood (Grab), the driver
uses his/her Grab account to purchase the item. This means that the discounts provide the driver
with additional income, sometimes up to 50 per cent of the price. These kinds of tactics are regu-
larly shared and discussed by driver communities, as well as other tactics and strategies (interview
8F. PANIMBANG
with a driver community, October 2019). These means of everyday resistance clearly show that dri-
vers regularly attempt to circumvent their faceless bosses.
One of the most interesting types of algorithmic resistance to faceless bosses (of algorithms) is
the use of multiple communities of drivers who have capacities and skills in digital technologies.
The group of drivers are popularly known as IT jalanan,
7
which means street programmer.
The name street programmeris comparable to the street-books-and-libraryactivism popularized
by activists in several cities and towns, rst initiated in Bandung, West Java. Later this spread to the
greater Jakarta area and elsewhere in the eort to foster a spirit of youth resistance to social injus-
tice. These street programmers,orITjalanan, are self-taught persons, some of whom were mem-
bers of industrial labour unions.
Since they work in a clandestine manner, the community of street programmers in several
cities work and coordinate eorts mostly web-based or online. They share new information
and tricks related to the new versions of apps from platform companies. Their main goal is to
create algorithm bugs in the driversapplication to change the algorithm. This is mainly intended
to reduce the driversworkload imposed on the drivers by the algorithm. Street programmers
argue that the labour process and labour control emanating from the ranking and rating system
has propelled drivers to work extremely hard and for longer hours. They challenge and resist the
algorithmic pressure by helping fellow drivers modify and tweak the appsalgorithm. Interest-
ingly, the group of street programmers perceive their resistance to be part of the class struggle
against corporate greed (FGD with drivers community leaders, November 2019). While algor-
ithms seek to maximize the amount of labour extracted from drivers, an additional app is used
to reduce their use of labour power. The drivers have consistently sought to discreetly circumvent
these rules underlying faceless managerial assertions of control, asserting their own control over
the use of their labour power.
App-based driversorganizing and a new practice of collectivity
Three organizing strategies
Not many established labour unions in the existing sectors have adequately responded to the need
of organizing of the unorganized drivers in the newly emerged app-based transport sector. Labour
unions have been pre-occupied with their own continuing challenges, including the recent
unfavourable Omnibus Law on job creation promoting more investment and business, on the
one hand, and reducing protection through labour rights on the other. Organizing this new terrain
of the gig economy has yet to become a priority for most labour unions in Indonesia (FGD with
driver organizers, December 2019).
In general, as Ford and Honan (2019) point out, there are currently three organizing strategies:
community, association, and union models (see also Panimbang et al., 2020). The rst organizing
model is based on the driver community, which is the most popular model of organization among
the app-based drivers. These driver communities are small, informal, and run exibly. They operate
at the grassroots level, with members mostly from the neighbourhood. Driver community organiz-
ing strategies are mostly ad hoc, focusing on mutual support in dealing with workplace problems
and issues such as suspension of driver accounts and sharing ideas for new tactics to earn higher
incomes. Many driver communities provide social services, and more importantly, deal with mem-
bers emergency and non-work-related issues like providing support when drivers or their family
members are sick.
GLOBALIZATIONS 9
There is no ocial data on the number of driver communities that exist, but it is estimated that
over 5000 communities have been established in the greater Jakarta area alone, with each commu-
nity having between 10 and 100 members or even more (interview with researchers and driver
association leaders, January 2020). A survey conducted in 2018 found that not more than 27 per
cent of app-based drivers in several big cities have joined a community (Instran, 2018), showing
that many more drivers are still unorganized. Some driver communities are aliated to an associ-
ation of driver communities, a broader scale of organization at district or city level.
The second model is the drivers association. It is a broader form of driverscommunity organ-
ization with members from dierent communities, but individual drivers can also be included as
members. Many of these drivers associations are informal in institutional terms and work exibly,
but some are registered with a social/mass organizational status in order to operate formally, and
have a more formal organizational structure. Several larger associations have slightly more complex
organizational structures, covering more locations in dierent provinces, and some are almost
nation-wide. Some of these drivers associations, especially those who have access to authorities
such as the Ministry of Transportation, have been able to get involved in decision-making on
app-based transport regulations. Both driver communities and drivers ´associations are the most
active actors in the past mobilizations to protest against governments and platform companies
demanding regulations and legal protection (Panimbang et al., 2020).
The third model is the app-based driversunion. The initiative to form driversunions comes
mainly from the existing federation of factory unions in the manufacturing sector, or from trans-
port and dockworkersunions. However, this organizing initiative to incorporate the app-based
drivers into the existing labour union structure faces formidable challenges, besides the fact that
unions are not popular among the drivers. The app-based driversunions are relatively small
and mostly inactive, and not one single union has been involved in recent policy-making processes
presided over by the Ministry of Transportation. One possible reason for the unpopularity of dri-
versunions therefore its lack of membership is their organizational structure and function,
which are viewed as inexible and rigid, as these have been adopted from the traditional trade
unionsstructure despite the nature of the platform economy which is fundamentally dierent.
For example, the driverśunions set up a plant-level union structure for Go-Jek and Grab separately
(similar with a factory or workplace union structure) despite the fact that drivers for both compa-
nies are inseparably gathered at the same base-campor roadside areas. In the following section, I
will analyse how the rst two models (community and association), in contrast to the union model,
can bring about a new practice of collectivity among their members.
A new practice of collectivity
By proposing the term a new practice of collectivity, I aim to highlight the peculiar act of collec-
tivity among the app-based drivers through spatial interaction that is not extensively practised by
any labour union in Indonesia. Both driver community and associations organizational structures
and functions are very exible and more informal, which makes it easier for drivers to establish
connections and network with dierent driver organizations across the country. An essential factor
that enables this new practice of collectivity is its type of digital work. Communication and coordi-
nation between members take place consistently via the communication channel as well as through
daily personal meetings at driversrest areas.
One of the key players in this new practice of collectivity is the voluntary group of drivers known
as the Rapid Response Team or popularly known as URC (unit reaksi cepat). URC is a task force of
10 F. PANIMBANG
drivers who take turns providing assistance whenever necessary, such as in a trac accident. It con-
sists of several delegates, between two to four members from each driver community. URCs exist in
most of the cities or regions in the country. Although the URC teams operate only at district/city
level, they are easy to connect with on a large scale with almost every other URC team across the
country. This connection uses a communication platform, especially the most popular and acces-
sible chat platform like WhatsApp, through which drivers exchange information with each other,
and are often in contact with their co-workers almost all day and night without interruption. This
constant contact is necessary as many drivers have to stop by at a certain area to charge phones or to
have a rest after taking a long trip order. Some others may want their location to be monitored by
other community members in case of emergencies or crimes. This practice of mutual support is
seen as very helpful for the drivers (FGD with driver community leaders, October 2019).
Another important practice of these driver organizations is the building of networks and alli-
ances. In networking, they use community labels and badges as symbols of networking and
reach out. That is one of the reasons why they highlight the spirit of collectivity and solidarity
on their communitys logos and mottos, printed on banners, badges, and stickers. Solidarity (soli-
daritas) and collectivity (kebersamaan) are among the most popular words written in the names of
their communities. These stickers and badges are used for an exchange with each others driver
communities when visiting. The number of stickers from various communities symbolize and
demonstrate the networking capacity of a community; the more stickers they have on their own
banner or base-camp wall, the greater the network and friendships they have established. With
this networking practice, driver communities/associations including female driver groups that
actively participating in association events such as anniversaries or social services (Panimbang
et al., 2020)play an important role in the construction of an alternative social relation, in
which they normalize mobility and movement of drivers, and they consider every place as a com-
mon space. More importantly, they treat other co-workers/drivers anywhere like family.
For example, when a driver from a community in one area has a problem or accident somewhere
far away, a community that is close to the accident point must provide help. This would be com-
municated through WhatsApp by community leaders. All drivers seem to support an agreed tacit
principle: you should help other fellow-drivers if you want to be treated the same. Another
example of solidarity practice among the workers is mutual aid during the diculties aected by
the Covid-19 pandemic when transport activity was mostly stopped: some driver associations col-
lected donations from their members who had other jobs in addition to app-based transport, to be
distributed to other members who relied exclusively on ride-hailing work (interview with commu-
nity and association leaders, May 2020). Such solidarity in practice, along with the collectivity and
bonds of friendship, is genuinely implemented among the drivers in many places.
Many communities are able to collect membership dues between IDR 10,00030,000 (US$ 0.80
2.20) on a regular basis (usually every month), which are used for collective purposes or to support
members in need. Others collect money from members occasionally, especially when it is needed
for collective purposes like to have base-camp awnings to provide shade or to cover electricity costs
for charging their phones. Although this capacity is small, it has great potential for driver commu-
nities to be able to mobilize resources.
It should be noted that both the driver community and the association become a hotspot for the
mobilization of drivers, and they are seen as strategic actors by the state authorities and the plat-
form companies, who have an interest in detecting and preventing any possible disruptions by dri-
vers. Several key communities and associations, especially the URC team, are tightly monitored by
the police and the platform company, as they played an important role in the past protest
GLOBALIZATIONS 11
mobilizations that took place between 2015 and 2018. Therefore, although with some limitations as
suggested by Ford and Honan (2019), from my point of view, driver communities and associations
are potential agents in platform workers organizing. They demonstrated collective action during a
number of protest mobilization, and explore strategies to improve their working conditions as
shown by several associations that have been involved in a number of regulatory discussions
with the Ministry of Transportation (interview with driver association, January 2020).
I would argue that the practice of collectivity among app-based drivers is, to some extent, an
invaluable lesson for the established labour unions in Indonesia and elsewhere, which have been
constrained by the formality and inexibility of their organizational structure. It provides insights
into the development of a new strategy for labour solidarity building within a broader labour move-
ment. On the other hand, the labour movement should also reect on how to start embracing these
precarious platform workers who are excluded from protection of their labour rights, and grappling
with their concerns more systematically. Drivers are also part of working people continuously
reproduced by social, political and economic processes of capitalism.
Conclusion
This article has demonstrated that the rise of app-based transportation business in Indonesia, as
practised by Go-Jek and Grab, is not without its consequences. These consequences include the
forced replacement of the indigenous transport service by digital platforms that threaten the
livelihoods of workers. This applies not only to the indigenous transport drivers, who have
gradually been ousted from the sector, but also to many app-based drivers, who are increas-
ingly exploited. Labour process and algorithmic labour control in Go-Jek and Grab prove
that the platform companies leverage signicant control over how workers behave on the
job. Against this algorithmic labour control, some drivers in Indonesia are challenging the plat-
form companies by creating algorithm bugs and errors in the driversphone to express their
resistance.
There are three models of organizing in place: community, association and union models. The
rst two models are the most popular and attractive for the workers, so they have more members
and are able to mobilize resources. In contrast to the union model, both driverscommunities and
associations have exible and informal organizational structures that allow them to easily connect
with other driversorganizations across the country. They display a new practice of collectivity
among the drivers, which is an invaluable lesson for the established labour unions. The driver com-
munities and associations play a signicant role in constructing an alternative social relation. They
normalize the mobility and movement of drivers across territories, and consider every place as a
common space.
I argue that despite legal and practical obstacles, driver communities and associations are poten-
tial agents in future organizing of platform workers, who are capable of engaging in collective
action and exploring strategies to improve their working conditions. Solidarity-building in actual
practice as well as the common practice of providing mutual help among drivers have become well-
established in most driver communities, clearly demonstrating the great potential of drivers. With-
out doubt, there are great challenges ahead, and one of the most important is the fact that the
majority of app-based drivers misrecognize their employment relation as workers vis-à-vis employ-
ers, who are entitled to labour rights as stipulated in the Labour Act. Recognizing these entitlements
to labour rights, among other things, is a rst step in building more power and legitimacy for dri-
versfuture collective actions.
12 F. PANIMBANG
Notes
1. Community transport that supplements xed-route transport by providing individualized rides with-
out xed routes or timetables.
2. Opang is a short form of ojek pangkalan, meaning the indigenous motorbike taxi service (ojek) waiting
for a fare at a base/rank (pangkalan).
3. As it becomes a regular income, this amount is mostly managed by the head of the neighbourhood,
which would be distributed to dierent individuals and institutions, often including local gangsters
and authorities (police and military) for legitimacy and protection.
4. This was popularly articulated as krismon, a short form of krisis moneter, meaning monetary crisis.
5. This online motorbike taxi booking service is popularly known as ojol, a short form of ojek online,
which means online motorbike taxi.
6. This is a term used by drivers to denote a fake global positioning system (fake GPS). Literally, tuyul
means a spirit that obtains wealth for its human master. It is a mythical spirit in Malay mythology
in Southeast Asia, especially in Indonesia, Malaysia, Brunei, and Singapore.
7. IT stands for Information and Technology and jalananliterally means street, a popular space for mar-
ginalized people. Here, jalanan refers to a brand of activism advocating marginalized people.
Acknowledgements
I am indebted to Syarif Arin, Sugeng Riyadi, Dina Septi Utami, Abu Mufakhir and other colleagues at LIPS
for their ideas and companion in the eld works, and to the workers I encountered for their supports. I want
to express my gratitude to Andreas Bieler, Joerg Nowak, Michele Ford, Bambang Dahana, Hari Nugroho and
the anonymous referees for their constructive and extensive feedback on earlier draft of this article. My special
gratitude to Melisa Serrano, Thomas Greven and Mirko Herberg for the discussion about this research project
under FES Trade Union in Transformation 4.0. Any errors found in this article are solely my mistakes.
Disclosure statement
No potential conict of interest was reported by the author(s).
Funding
The research was generously supported by the Friedrich-Ebert-Stiftung (FES).
Notes on contributor
Fahmi Panimbang is a labour activist based in Indonesia. His publications include Resistance on the continent
of labour: Strategies and initiatives of labour organizing in Asia (2017).
ORCID
Fahmi Panimbang http://orcid.org/0000-0002-9125-9186
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GLOBALIZATIONS 15
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Cambridge Core - South-East Asian Government, Politics and Policy - Labor and Politics in Indonesia - by Teri L. Caraway
Article
App-based transport has grown rapidly in Indonesia, and now provides work for over a million private commercial drivers. A large proportion of online drivers have joined self-organised community organisations that operate on a mutual aid logic, characterised by horizontal networks and strong social commitment. This mutual aid-based approach, which builds on a long tradition of associational behaviour in Indonesia’s large informal sector, has facilitated high levels of membership and member participation in small, geographically based driver communities. It is less well suited, however, to staging large-scale protests, negotiating with the app-based transport companies or engaging with government. Drawing on extensive qualitative fieldwork, this article argues that mutual aid-based organising has indeed proved an effective way to reach out to this group of non-traditional workers, but is not in itself enough to effect structural change. Ultimately, everyday forms of collectivism must be complemented by large-scale mobilisation, legal challenges and industrial action if drivers are to challenge the power of their pseudo-employers. To date, however, successful integration between driver communities and larger scale organisations has proven difficult in the face of external hostility and internal divisions.
Book
Silicon Valley technology is transforming the way we work, and Uber is leading the charge. An American startup that promised to deliver entrepreneurship for the masses through its technology, Uber instead built a new template for employment using algorithms and Internet platforms. Upending our understanding of work in the digital age, Uberland paints a future where any of us might be managed by a faceless boss. The neutral language of technology masks the powerful influence algorithms have across the New Economy. Uberland chronicles the stories of drivers in more than twenty-five cities in the United States and Canada over four years, shedding light on their working conditions and providing a window into how they feel behind the wheel. The book also explores Uber’s outsized influence around the world: the billion-dollar company is now influencing everything from debates about sexual harassment and transportation regulations to racial equality campaigns and labor rights initiatives. Based on award-winning technology ethnographer Alex Rosenblat’s firsthand experience of riding over 5,000 miles with Uber drivers, daily visits to online forums, and face-to-face discussions with senior Uber employees, Uberland goes beyond the headlines to reveal the complicated politics of popular technologies that are manipulating both workers and consumers.
Book
Cambridge Core - E-Commerce Law - The Cambridge Handbook of the Law of the Sharing Economy - by John J. Infranca / edited by Nestor M. Davidson
Article
What are the distinctive traits that characterize work(ing) through (and for) a digital platform? In the burgeoning debate on the ‘gig economy’, a critical examination that comprehensively addresses this issue beyond specific examples or case studies is currently missing. This article uses labour process theory – an important Marxist approach in the study of relations of production in industrial capitalism – to address this gap. Supported by empirical illustrations from existing research, the article discusses the notions of ‘point of production’, emotional labour and control in the gig economy to argue that labour process theory offers a unique set of tools to expand our understanding of the way in which labour power comes to be transformed into a commodity in a context where the encounter between supply and demand of work is mediated by a digital platform, and where feedback, ranking and rating systems serve purposes of managerialization and monitoring of workers.