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This work examines the intersection between traditional human resource management and the novel employment arrangements of the expanding gig economy. While there is a substantial multidisciplinary literature on the digital platform labor phenomenon, it has been largely centered on the experiences of gig workers. As digital labor platforms continue to grow and specialize, more managers, executives, and human resource practitioners will need to make decisions about whether and how to utilize gig workers. Here the authors explore and interrogate the unique features of human resource management (HRM) activities in the context of digital labor platforms. The authors discuss challenges and opportunities regarding (1) HRM in organizations that outsource labor needs to external labor platforms, (2) HRM functions within digital labor platform firms, and (3) HRM policies and practices for organizations that develop their own spin-off digital labor platform. To foster a more nuanced understanding of work in the gig economy, the authors identify common themes across these contexts, highlight knowledge gaps, offer recommendations for future research, and outline pathways for collecting empirical data on HRM in the gig economy.

While digital labour platforms are being increasingly studied across the Global South, the existing literature does not conceptualise the theoretical link between such platforms and socio-economic development. This paper theorises such a link drawing on the notion of institutional voids defined, as in Khanna and Palepu (2010), as “the absence of intermediaries to efficiently connect buyers and sellers” in an economy. We frame digital labour platforms as means to fill institutional voids, seeking to create “development” in the form of earning opportunities in contexts of deprivation.

We draw on an interpretive case study of an online work training project in a deprived region of Pakistan, where members of marginalised communities were trained to become freelancers for global digital labour platforms. We use the notion of market-enabling institutions aimed at filling institutional voids as a lens to study the project's declared goals, examining the extent to which these were met in practice for the workers who participated in the training.

Our analysis reveals three types of market-enabling institutions–credibility enhancers, aggregators and distributors, and transaction facilitators–through which digital labour platforms seek to fill institutional voids. However, workers' narratives reveal that institutional voids are only partially filled by these platforms, and their perpetuation results in diverse forms of power asymmetries leveraged by clients and owners of the platforms. We also observe the formation of solidarity networks among workers, networks that are intra-familial and societal rather than characterised by formal unionisation.

The paper offers a novel perspective to theorise the link between digital labour and socio-economic development. Applying such a perspective in a Global South context, it also finds the limits of the digital platforms' institutional void-filling potential, highlighting the emergence of power asymmetries and the emerging formation of worker solidarity networks.

This paper aims to explore the prevalence of undeclared activities conducted on digital labour platforms, and then to discuss what policies are likely to be more effective in order to prevent the growth of the informal activities on these platforms.

To depict the profile of the digital worker conducting undeclared activities, the sectors where undeclared activities are more prevalent and the effectiveness of deterrent policies, data are reported from 2019 Special Eurobarometer survey covering the European Union member states and the UK.

The finding is that 13% of undeclared activities are conducted on digital labour platforms. This practice is more common amongst men, those married or remarried, those living in small/middle towns, in sectors such as repairs/renovations, selling goods/services, assistance for dependant persons, gardening and help moving house. The higher the perceived sanction, the lower the likelihood of undertaking undeclared activities on digital labour platforms. Intriguing, a higher risk of detection is associated with a higher likelihood to use digital labour platform for undeclared activities.

The attitudes toward risk can be interpreted closer to the gaming context, and not to the working environment, looking at platform workers as being involved in a state versus individual game. Policy makers should consider improving the correspondence of laws and regulations between countries and offering operational assistance for suppliers and consumers.

This is the first paper to explore the prevalence of undeclared activities conducted on digital labour platforms and to outline the policy measures required to reduce this practice.

This paper aims to explore the implications of algorithmic management on careers and employment relationships in the Nigerian gig economy. Specifically, drawing on labour process theory (LPT), this study provides an understanding of the production relations beyond the “traditional standard” to “nonstandard” forms of employment in a gig economy mediated by digital platforms or digital forms of work, especially on ride-hailing platforms (Uber and Bolt).

This study adopted the interpretive qualitative approach and a semi-structured interview of 49 participants, including 46 platform drivers and 3 platform managers from Uber and Bolt.

This study addresses the theoretical underpinnings of the LPT as it relates to algorithmic management and control in the digital platform economy. The study revealed that, despite the ultra-precarious working conditions and persistent uncertainty in employment relations under algorithmic management, the underlying key factors that motivate workers to engage in digital platform work include higher job flexibility and autonomy, as well as having a source of income. This study captured the human-digital interface and labour processes related to digital platform work in Nigeria. Findings of this study also revealed that algorithmic management enables a transactional exchange between platform providers and drivers, while relational exchanges occur between drivers and customers/passengers. Finally, this study highlighted the perceived impact of algorithmic management on the attitude and performance of workers.

The research presents an interesting case study to investigate the influence of algorithmic management and labour processes on employment relationships in the largest emerging economy in Africa.

This study aims to conduct a systematic literature review and bibliometric analysis on the topic of digital labour. The study also identifies the future research directions for the topic.

In total, 118 research papers were identified and reviewed from 11 established research databases and A*, A and B category journals from the ABDC journal list. The papers covered a timespan between 2006 and 2023. Bibliometric analysis was conducted to identify key research hotspots.

The emergent themes and associated sub-themes related to digital labour were identified from the literature. The paper found three significant themes that include digital labour platform, gig economy and productivity. This study also acts as a platform to initiate further research in this field for academicians, scholars, industry practitioners and policymakers. The future research scope in the topic is also presented.

The present study is unique in its nature as it approaches the topic of digital labour from all relevant perspectives.

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.

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.

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).

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.

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.

The paper brings Foucauldian analysis of neoliberal governmentality in the discussion on the new forms of labour control within digital labour platforms. The aim of the paper is to reveal the effect of control mechanisms employed by platforms on “entrepreneurial self” within the context of work relations.

Drawing on in-depth interviews, conducted with workers under different service categories, the author undertook an extended case study of Armut.com, a digital labour platform operating in Turkey.

The study finds that competitive mechanisms employed by the platform have a considerable effect on worker self-commercialisation and self-rationalisation. This is dependent on different control mechanisms employed by the platform, based on different platform working models.

The research brings the worker subjectivities to the discussion of control within the scope of digital labour platforms. By undertaking a rare empirical study on this issue, it contributes to the theory of entrepreneurial self within the scope of work relations.

The paper argues that the classical Marxist theory of capitalist accumulation is inadequate to understand new forms of capitalism and their accumulation processes determined by “platforms” and “big data”. Big data platforms are shaping the processes of production, labour, the price of products and market conditions. “Digital platforms” and “big data” have become an integral part of the processes of production, distribution and exchange relations. These twin pillars are central to the capitalist accumulation processes. The article argues that the classical Marxist theory of capitalist accumulation is inadequate to understand new forms of capitalism and their accumulation processes determined by “platforms” and “big data”.

As a conceptual paper, this paper follows critical methodological lineages and traditions based on non-linear historical narratives around the conceptualisation, construction and transition of the “Marxist theory of capital accumulation” in the age of platform economy. This paper follows a discourse analysis (Fairclough, 2003) to locate the way in which an artificial intelligence (AI)-led platform economy helps identify and conceptualise new forms of capitalist accumulation. It engages with Jørgensen and Phillips' (2002) contextual and empirical discursive traditions to undertake a qualitative comparative analysis by exploring a broad range of complex factors with case studies and examples from leading firms within the platform economy. Finally, it adopts two steps of “Theory Synthesis and Theory Adaptation” as outlined by Jaakkola (2020) to synthesise, adopt and expand the Marxist theory of capital accumulation under platform capitalism.

This article identifies new trends and forms of data driven capitalist accumulation processes within the platform capitalism. The findings suggest that an AI led platform economy creates new forms of capitalist accumulation. The article helps to develop theoretical understanding and conceptual frameworks to understand and explain these new forms of capital accumulation.

This study builds upon the limited theorisation on the AI and new capitalist accumulation processes. This article identifies new trends and forms of data driven capitalist accumulation processes within platform capitalism. The article helps to understand digital and platform capitalisms in the lens of digital labour and expands the theory of capitalist accumulation and its new forms in the age of datafication. While critiquing the Marxist theory of capitalist accumulation, the article offers alternative approaches for the future.