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This article evaluates the job quality of work in the remote gig economy. Such work consists of the remote provision of a wide variety of digital services mediated by online labour platforms. Focusing on workers in Southeast Asia and Sub-Saharan Africa, the article draws on semi-structured interviews in six countries ( N = 107) and a cross-regional survey ( N = 679) to detail the manner in which remote gig work is shaped by platform-based algorithmic control. Despite varying country contexts and types of work, we show that algorithmic control is central to the operation of online labour platforms. Algorithmic management techniques tend to offer workers high levels of flexibility, autonomy, task variety and complexity. However, these mechanisms of control can also result in low pay, social isolation, working unsocial and irregular hours, overwork, sleep deprivation and exhaustion.

The advent of online platforms has been considered to be one of the most significant economic changes of the last decade, with their emergence reflecting a longer trend of increasing contingent work, labor market flexibility, and outsourcing work to independent contractors. In this article, we conceptualize the so-called gig economy along four dimensions, namely, online intermediation, independent contractors, paid tasks, and personal services. Using this framework, it is possible to derive both a narrow definition of the gig economy, as ex ante specified, paid tasks carried out by independent contractors mediated by online platforms, and broader definitions that include offline alongside online intermediation, employees alongside independent contractors, unpaid tasks alongside paid tasks, and asset sharing alongside performing gigs. The four dimensions also span four key regulatory questions: How should online platforms be classified and regulated; how should gig workers be classified and regulated; what should count as paid and unpaid work; and should we treat earnings from performing gigs differently than earnings from sharing assets? We conclude that the positions taken on these regulatory issues are essentially contingent upon political choices and will determine how the gig economy evolves in the future.

Ecuador is home to approximately 556,000 immigrants, mostly from Venezuela (65%) and Colombia (25%), many of whom have an irregular immigration status. In Ecuador, an immigrant without a visa cannot work, which creates a scenario that favours abuse by employers and hinders immigrants' ability to organize and negotiate their rights. Part of this population has found the platform economy to be a flexible way to find work and earn an income quickly. However, this has also given rise to new forms of exploitation. The objective of this article is to analyse the relationship between the development of the platform economy in Ecuador and the labour conditions of the migrant population that has entered the country in recent years. We used a qualitative methodology based on direct observation, semi-structured interviews (46) and in-depth interviews (10). The main results of this research show that the development of the platform economy and the lack of adequate legislation have produced new forms of disguised exploitation, particularly of immigrant workers. These new forms of exploitation operate through a black market of profile and vehicle subcontracting which, in their interaction with the algorithmic management systems of these applications, end up worsening the already precarious working conditions of the migrant population that uses these applications as a means of survival. The article concludes with a brief analysis of these working conditions in relation to the five principles of fair work.

Purpose
A quarterly series of gig economy activity in the regions of the UK is constructed. Patterns of regional linkages are identified and the implications of spatial patterns for policymakers, businesses, workers and institutions are highlighted.


Design/methodology/approach
The Labour Force Survey data on main job self-employment in key gig economy sectors are used to construct the series. These are then analysed using vector autoregression techniques to identify patterns in the data and provide provisional forecasts.


Findings
The incidence of gig economy activity is greatest in the London region, characterised by high population density and a concentration of service sectors in which gig economy work, particularly of a highly skilled nature, takes place. Growth of gig economy activity in other regions has been more modest. In London, the percentage of workers in the gig economy is expected to rise to around 6.5 per cent over the next few years, while in other regions, the percentage is expected to settle at between 3 and 4.5 per cent.


Originality/value
These are the first regional estimates to be provided of the extent of gig economy activity. This is important in the context of discussions about the future of work, not least because regional disparities imply the need for policies addressing insecurity to have a spatial dimension.

Ausgehend von politischen Forderungen, Produktivitätsgewinne, die gegenwärtig durch Digitalisierung und Automatisierung entstehen und mit dem Aufkommen der sogenannten ‹Gig Economy› einhergehen, im Rahmen einer «Maschinensteuer» abzuschöpfen, untersucht der Beitrag am Beispiel des Webdienstes Amazon Mechanical Turk die Erscheinungsweisen und Logiken der digitalen Plattformökonomie. Der Text problematisiert dabei im Anschluss an Karl Marx und Gilles Deleuze / Félix Guattari den Begriff der Maschine und kommt zu dem Schluss, dass für die untersuchte Plattform nicht nur eine weitreichende Reorganisation von Arbeit und Arbeitskraft kennzeichnend ist, sondern die Austauschprozesse, Verkettungen und Vernetzungen zwischen den Elementen einer solchen Maschine etwa dort offenkundig werden, wo sie in den Kontext der gegenwärtig dominanten Supplyside Economics gestellt wird, welche die Verfügbarkeit eines weltweiten Prekariats von Arbeitskräften zum Ziel hat. ; Taking as its starting point political demands to skim off, within the framework of a «machine tax», the productivity gains which presently arise through digitalization and automatization and accompany the rise of the so-called ‹gig economy›, this essay analyzes the modes of appearance and logics of the digital platform economy using the example of the web service Amazon Mechanical Turk. In the process, and with reference to Karl Marx and Gilles Deleuze / Félix Guattari, the text problematizes the concept of the machine and concludes that the platform under consideration here is not only characterized by an extensive reorganization of labor and labor power, but also the exchange processes, the linkages and networks between the elements of such a machine manifest themselves at the point where they are placed within the context of the currently dominant supply-side economics that has as its goal the availability of a worldwide precariat of labor power.

The Gig Economy is increasingly seen to reward hustle, flexibility, autonomy, specialised skills, deep expertise, or in-demand experience and creative abilities along with entrepreneurial work formats that demand skills such as comfort with developing income streams, marketing and connecting yourself to gig offers. The gig economy offers both good and bad jobs and opens new … Continued

This blog is based on an article in the Journal of Social Policy by Tat Chor Au-Yeung, Chris King-Chi Chan, Cham Kit Keith Ming and Wing Yin Anna Tsui. Click here to access the article. The digitisation and platformisation of work pose many challenges to social policy and welfare states, including the issues about workers'… Continue reading The Gig Economy: Delivering Food But Abandoning Welfare? →

PurposeThe purpose of this paper is to provide an investigation of how different types of gig workers engage in the gig economy. Specifically, the authors distinguish between workers who view gig work as primary income (or not) and those workers who view it as a job (or not).Design/methodology/approachIn total, 1,190 Mechanical Turk (MTurk) workers completed surveys across two studies examining whether types of workers differ based on demographic characteristics, utilization of MTurk, why they participate in the gig economy on MTurk (i.e. push and pull factors) and how this impacts life satisfaction.FindingsWorkers relying on MTurk as a primary income had lower incomes and spent more time completing large numbers of work units. This group of workers also reported fewer pull factors (e.g. enjoyment) as a reason for working in the gig economy and had lower levels of self-reported current and predicted future life satisfaction. Individuals who view MTurk as a job were more likely to treat MTurk like a job – engaging in online communities and having a regular work schedule. These workers were more likely to report pull factors (e.g. enjoyment and challenge) and did not differ on life satisfaction.Originality/valueThe current research contributes to our understanding of MTurk, one of the largest online platforms for gig work, as part of the diverse gig economy and highlights potential areas for future research.

In urban gig economies around the world, platform labour is predominantly migrant labour, yet research on the intersection of the gig economy and labour migration remains scant. Our experience with two action research projects, spanning six cities on four continents, has taught us how platform work impacts the structural vulnerability of migrant workers. This leads us to two claims that should recalibrate the gig economy research agenda. First, we argue that platform labour simultaneously degrades working conditions while offering migrants much-needed opportunities to improve their livelihoods. Second, we contend that the reclassification of gig workers as employees is by itself not sufficient to counter the precarisation of migrant gig work. Instead, we need ambitious policies at the intersection of immigration, social welfare, and employment regulation that push back against the digitally mediated commodification of migrant labour worldwide.