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Purpose This study systematically reviews and synthesizes existing literature on gig work to identify its key enablers and barriers. With the rise of algorithmically managed digital platforms, gig work faces unique challenges. The review aims to offer insights and guide future research on this evolving labour market segment. Design/methodology/approach Using Urie Bronfenbrenner’s Ecological Systems framework, this study systematically reviews 83 research articles from leading journals over the past two decades. The framework helps organize and analyse the factors influencing gig work at various levels. Findings The review identifies upskilling opportunities and peer-to-peer networks facilitated by digital technologies as key enablers, while gaps in worker protections and regulatory oversight are significant barriers. Gaps in current research, particularly on the long-term impacts of gig work, are also highlighted. Practical implications The findings inform policymakers, platform managers and gig workers, providing strategies to address the evolving challenges of gig work. Policymakers can craft balanced regulations, while platforms can improve worker satisfaction and performance. Originality/value This study offers a novel contribution by applying Bronfenbrenner’s framework to synthesize gig work research. It provides a structured analysis of enablers and barriers and lays the foundation for future research in this field.

Platform-based gig work is rapidly growing in India and has become a significant component of the economy. Existing labour force surveys are unable to accurately capture this new and emerging form of work. This paper discusses conceptual and definitional issues related to gig work in labour statistics and critically reviews existing studies and estimates of India’s gig workforce. Drawing on recent experiences of several countries, the paper documents conceptual and practical lessons for updating and enhancing India’s labour force surveys for better data collection on gig workers. In doing so, the paper offers an approach to help quantify the size of the gig workforce and provide insights into the diverse and heterogeneous nature of gig work that would enable policymakers to design and implement targeted policies and programmes to improve the well-being of these workers.

Existing research has shown that people experience third-party evaluations as a form of control because they try to align their behavior with evaluations’ criteria to secure more favorable resources, recognition, and opportunities from external audiences. Much of this research has focused on evaluations with transparent criteria, but increasingly, algorithmic evaluation systems are not transparent. Drawing on over three years of interviews, archival data, and observations as a registered user on a labor platform, I studied how freelance workers contend with an opaque third-party evaluation algorithm—and with what consequences. My findings show the platform implemented an opaque evaluation algorithm to meaningfully differentiate between freelancers’ rating scores. Freelancers experienced this evaluation as a form of control but could not align their actions with its criteria because they could not clearly identify those criteria. I found freelancers had divergent responses to this situation: some experimented with ways to improve their rating scores, and others constrained their activity on the platform. Their reactivity differed based not only on their general success on the platform—whether they were high or low performers—but also on how much they depended on the platform for work and whether they experienced setbacks in the form of decreased evaluation scores. These workers experienced what I call an “invisible cage”: a form of control in which the criteria for success and changes to those criteria are unpredictable. For gig workers who rely on labor platforms, this form of control increasingly determines their access to clients and projects while undermining their ability to understand and respond to factors that determine their success.

Many workers have been drawn to the gig economy by the promise of flexible, autonomous work, but scholars have highlighted how independent working arrangements also come with the drawbacks of precarity. Digital platforms appear to provide an alternative to certain aspects of precarity by helping workers find work consistently and securely. However, these platforms also introduce their own demands and constraints. Drawing on 20 interviews with online freelancers, 19 interviews with corresponding clients and a first-hand walkthrough of the Upwork platform, we identify critical literacies (what we call gig literacies), which are emerging around online freelancing. We find that gig workers must adapt their skills and work strategies in order to leverage platforms creatively and productively, and as a component of their ‘personal holding environment’. This involves not only using the resources provided by the platform effectively, but also negotiating or working around its imposed structures and control mechanisms.

Building on an emerging literature concerning algorithmic management, this article analyzes the processes by which food delivery platforms control workers and uncovers variation in the extent to which such platforms constrain the freedoms—over schedules and activities—associated with gig work. Drawing on in-depth interviews with 55 respondents working on food delivery platforms, as well as a survey of 955 platform food delivery workers, we find that although all of the food delivery platforms use algorithmic management to assign and evaluate work, there is significant cross-platform variation. Instacart, the largest grocery delivery platform, exerts a type of control we call “algorithmic despotism,” regulating the time and activities of workers more stringently than other platform delivery companies. We conclude with a discussion of the implications of the spectrum of algorithmic control for the future of work.

Purpose High-quality employee motivation can contribute to an organization’s long-term success by supporting employees’ well-being and performance. Nevertheless, there is a paucity of research concerning how organizations motivate workers in non-traditional work contexts. In the algocratic context of the gig-economy, the purpose of this paper is to understand the role that technology can play in motivating workers. Design/methodology/approach Drawing on the self-determination theory, job-characteristic theory and enterprise social media research, this conceptual paper explores how the architecture of the digital labor platforms underlying the gig-economy (and the characteristics of jobs mediated through these IT artifacts) can impact key antecedents of self-motivation. Findings Combining theory and empirical evidence, this paper develops a mid-range theory demonstrating how organizations can support the self-motivation of gig-workers through the thoughtful design of their digital labor platforms and the integration of two social media tools (namely, social networking and social badging). Research limitations/implications This paper answers calls for psychologically-based research exploring the consequences of gig-work as well as research studying the impacts of advanced technologies in interaction with work contexts on motivation. In theorizing around a large set of social-contextual variables operating at different levels of analysis, this paper demonstrates that individual-level motivation can be influenced by both task-based and organizational-level factors, in addition to individual-level factors. Originality/value The proposed theory provides novel insight into how gig-organizations can leverage widely accessible social media technology to motivate platform workers in the absence of human supervision and support. Theoretical and practical implications are discussed.

PurposeThrough focusing on gig workers registered in three crowdsourcing platforms, the authors investigate how individual and collaborative job crafting may be positively related to the meaningful work and affective commitment those gig workers develop towards the crowdsourcing platforms they register in.Design/methodology/approachThe authors employed a quantitative research method in which they focused on date from surveys completed by 327 gig workers. They tested the hypotheses using SmartPLS 3, which is more suitable when dealing with complex models, non-normal data, small samples and higher-order constructs.FindingsThe results showed that the proactive behaviour embedded within both individual and collaborative job crafting may lead to a sense of meaningfulness for gig workers and subsequently, their affective commitment towards the crowdsourcing platforms they register in. Specifically, the more gig workers undertake individual (H1) and collaborative (H2) job crafting behaviour, the greater the sense of meaningfulness they develop. Moreover, meaningfulness for gig workers positively affects their affective commitment towards the crowdsourcing platforms they register with (H3).Originality/valueTo the best of the authors' knowledge, this study is the first of its kind in the context of France and the European Union to focus on job crafting and its effect on both meaningful work and the affective commitment of non-traditional workers. This paper contributes by filling a gap in human resource (HR) management, in which empirical studies that address gig work have been limited so far.

While social distancing measures are essential in limiting the impact of a pandemic, such measures are often less feasible for low-income groups such as precarious workers who continue to travel on public transit and are less able to practice social distancing measures. In this paper, based on in-depth remote interviews conducted from April 2020 through June 2020, with more than 130 gig and precarious workers in New York City, we find that precarious workers experience three main hurdles in regard to accessing unemployment assistance that can be broadly categorized as knowledge, sociological, and temporal/financial barriers. Drawing on worker interview responses, we have named these responses: (1) Didn't Know, (2) Didn't Want, and (3) Can't Wait. These challenges have led workers to turn to gig and precarious work, further highlighting the inequities of the pandemic. As a result, for some workers, so-called \"side hustles\" have become their primary social safety net.

This book provides aspiring and seasoned lawyers seeking independence and flexibility a comprehensive guide to launching and sustaining a successful freelance law practice.Authored by a seasoned legal freelancer, this book delves into the nuts and bolts of navigating the landscape of self-employment in the legal field.

We advance the concept of platformic management, and the ways in which platforms help to structure project-based or “gig” work. We do so knowing that the popular press and a substantial number of the scholarly publications characterize the “rise of the gig economy” as advancing worker autonomy and flexibility, focusing attention to online digital labor platforms such as Uber and Amazon’s Mechanical Turk. Scholars have conceptualized the procedures of control exercised by these platforms as exerting “algorithmic management,” reflecting the use of extensive data collection to feed algorithms that structure work. In this paper, we broaden the attention to algorithmic management and gig-working control in two ways. First, we characterize the managerial functions of Upwork, an online platform that facilitates knowledge-intensive freelance labor - to advance discourse beyond ride-sharing and room-renting labor. Second, we advance the concept of platformic management as a means to convey a broader and sociotechnical premise of these platforms’ functions in structuring work. We draw on data collected from Upwork forum discussions, interviews with gig workers who use Upwork, and a walkthrough analysis of the Upwork platform to develop our analysis. Our findings lead us to articulate platformic management -- extending beyond algorithms -- and to present the platform as a “boundary resource” to illustrate the paradoxical affordances of Upwork and similar labor platforms. That is, the platform (1) enables the autonomy desired by gig workers, while (2) also serving as a means of control that helps maintain the viability of transactions and protects the platform from disintermediation.