The Gig Economy: Current Issues, the Debate, and the New Avenues of Research

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Abstract

In the context of the debate on platform economy, on the one hand, and the gig economy, on the other, this paper delineates the conceptual boundaries of both concepts to query the gig economy research included in the Web of Science database. The initial search, cutoff date February 2020, targeting “gig economy” returned a sample of 378 papers dealing with the topic. The subsequent analysis, employing the science mapping method and relating software (SciMAT), allowed to query the body of research dealing with gig economy in detail. The value added by this paper is fourfold. First, the broad literature on gig economy is mapped and the nascent synergies relating both to research opportunities and economic implications are identified and highlighted. Second, the findings reveal that while research on gig economy proliferates, the distinction between “platform” and “gig” economy frequently remains blurred in the analysis. This paper elaborates on this issue. Third, it is highlighted that the discussion on gig economy is largely dispersed and a clearer research agenda is needed to streamline the discussion to improve its exploratory and explanatory potential. This paper suggests ways of navigating this issue. Fourth, by mapping the existing research on gig economy and highlighting its caveats, the way toward a comprehensive research agenda in the field is highlighted.

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Most cited references 77

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An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application to the Fuzzy Sets Theory field

F Herrera, E Herrera-Viedma, M.J. Cobo … (2011)

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Science Mapping: A Systematic Review of the Literature

Chaomei Chen (2017)

We present a systematic review of the literature concerning major aspects of science mapping to serve two primary purposes: First, to demonstrate the use of a science mapping approach to perform the review so that researchers may apply the procedure to the review of a scientific domain of their own interest, and second, to identify major areas of research activities concerning science mapping, intellectual milestones in the development of key specialties, evolutionary stages of major specialties involved, and the dynamics of transitions from one specialty to another. We first introduce a theoretical framework of the evolution of a scientific specialty. Then we demonstrate a generic search strategy that can be used to construct a representative dataset of bibliographic records of a domain of research. Next, progressively synthesized co-citation networks are constructed and visualized to aid visual analytic studies of the domain’s structural and dynamic patterns and trends. Finally, trajectories of citations made by particular types of authors and articles are presented to illustrate the predictive potential of the analytic approach. The evolution of the science mapping research involves the development of a number of interrelated specialties. Four major specialties are discussed in detail in terms of four evolutionary stages: conceptualization, tool construction, application, and codification. Underlying connections between major specialties are also explored. The predictive analysis demonstrates citations trajectories of potentially transformative contributions. The systematic review is primarily guided by citation patterns in the dataset retrieved from the literature. The scope of the data is limited by the source of the retrieval, i.e. the Web of Science, and the composite query used. An iterative query refinement is possible if one would like to improve the data quality, although the current approach serves our purpose adequately. More in-depth analyses of each specialty would be more revealing by incorporating additional methods such as citation context analysis and studies of other aspects of scholarly publications. The underlying analytic process of science mapping serves many practical needs, notably bibliometric mapping, knowledge domain visualization, and visualization of scientific literature. In order to master such a complex process of science mapping, researchers often need to develop a diverse set of skills and knowledge that may span multiple disciplines. The approach demonstrated in this article provides a generic method for conducting a systematic review. Incorporating the evolutionary stages of a specialty into the visual analytic study of a research domain is innovative. It provides a systematic methodology for researchers to achieve a good understanding of how scientific fields evolve, to recognize potentially insightful patterns from visually encoded signs, and to synthesize various information so as to capture the state of the art of the domain.

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Good Gig, Bad Gig: Autonomy and Algorithmic Control in the Global Gig Economy

Alex Wood, Mark Graham, Vili Lehdonvirta … (2018)

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.