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Digital labor markets are structured around tasks and not around fixed- or long-term employment contracts. We study the consequences of the granularization of work for digital micro workers. To address this question, we combine interview data from active online micro workers and online data on open projects scraped from Amazon's Mechanical Turk platform to study how the digital micro workers choose which tasks they work on. We find evidence for preferential attachment: workers prefer to attach themselves to experienced employers who are known to offer high quality projects. In addition, workers also clearly prefer long series of repeatable tasks over one-off tasks, even when one-off tasks pay considerably more. We thus see a re-emergence of certain types of organizational structure.

The global workforce is urged to constantly reskill, as technological change favours particular new skills while making others redundant. But which skills are most marketable and have a sustainable demand? We propose a model for skill evaluation that attaches a market value to a set of 962 digital skills based on near real-time online labour market data. We demonstrate that the value of a specific skill is strongly determined by complementarity - that is with how many other high-value skills a competency can be combined. Most importantly, we show that the value of a skill is relative, as it depends on the capacities it is combined with. For most skills, their value is highest when used in combination with skills of the same type. We illustrate our model with a set of AI skills that are particularly valuable because of their strong complementarities, and also because of the significant increase in their demand in recent years. Finally, we contrast our skill premia with automation probabilities and find that some skills are very susceptible to automation despite their high market value. The model and metrics of our work can inform the policy and practice of digital re-skilling to reduce labour market mismatches. In cooperation with online platforms and education providers, researchers and policy makers should consider using this blueprint to provide learners with personalised skill recommendations that complement their existing capacities and fit their occupational background., Comment: 40 pages, 8 figures, 3 tables

The Online Labour Index (OLI) was launched in 2016 to measure the global utilisation of online freelance work at scale. Five years after its creation, the OLI has become a point of reference for scholars and policy experts investigating the online gig economy. As the market for online freelancing work matures, a high volume of data and new analytical tools allow us to revisit half a decade of online freelance monitoring and extend the index's scope to more dimensions of the global online freelancing market. In addition to measuring the utilisation of online labour across countries and occupations by tracking the number of projects and tasks posted on major English-language platforms, the new Online Labour Index 2020 (OLI 2020) also tracks Spanish- and Russian-language platforms, reveals changes over time in the geography of labour supply, and estimates female participation in the online gig economy. The rising popularity of software and tech work and the concentration of freelancers on the Indian subcontinent are examples of the insights that the OLI 2020 provides. The OLI 2020 delivers a more detailed picture of the world of online freelancing via an interactive online visualisation updated daily. It provides easy access to downloadable open data for policymakers, labour market researchers, and the general public (www.onlinelabourobservatory.org)., Comment: 10 pages, 5 figures

This study combines market-level data about changes in jobs offered via online labor platforms and interviews with online freelance workers to highlight how freelancers are responding to the novel coronavirus’s presence. We pursue this work recognizing that as the scope and breadth of the COVID-19 pandemic continues to grow, the implications to workers and labor markets are profound. Our focus on online labor markets and workers reflects our enduring interest in knowledge work, with a particular attention to precarious work. Market data show the dramatic shifts in work availability (supply) and the changes in worker availability (demand) as the United States’ economy struggles with the initial burst of effects of a pandemic. Interview data reveal that freelance workers are aware of these shifts. These changes to already- precarious and market-driven work arrangements are magnified by the realities of balancing family members’ changes in job status, working around children who are home from school, and re-organizing work and lives to account for the rapid onset and confusion of stay-at-home requirements and the uncertainty that is the core of the pandemic. Findings suggest work flexibility, which seems central to freelancer’s motivation to pursue such work, is diminishing and instead freelancers are being driven by desperation rooted in the acknowledged precarity of their situation, magnified by the constellation of events reshaping their working arrangements. We further observe that these effects vary by occupation and are more keenly experienced by women freelancers, both of which warrant additional attention.

Information and communication technologies have long been predicted to make cities as hubs of economic organisation obsolete and spread economic opportunities to rural areas. However, the actual trend in the 21st century has been the opposite. Knowledge spillovers have fuelled urbanisation and pulled job-seekers into large cities, increasing the gap to deprived rural areas. We argue that new assemblages of technologies and social practices, so-called ’online labour platforms’, have recently started to counter this trend. By providing effective formal and informal mechanisms of enforcing cooperation, these platforms for project-based remote knowledge work enable users to hire and find work across distance. In analysing data from a leading online labour platform in more than 3,000 urban and rural counties in the United States, we find that rural workers made disproportionate use of the online labour market. Rural counties also supplied, on average, higher skilled online work than urban areas did. However, many of the most deprived regions of the country did not participate in the online labour market at all. Our findings highlight the potentials and limitations of such platforms for regional economic development.

Gig economy platforms seem to provide extreme temporal flexibility to workers, giving them full control over how to spend each hour and minute of the day. What constraints do workers face when attempting to exercise this flexibility? We use 30 worker interviews and other data to compare three online piecework platforms with different histories and worker demographics: Mechanical Turk, MobileWorks, and CloudFactory. We find that structural constraints (availability of work and degree of worker dependence on the work) as well as cultural‐cognitive constraints (procrastination and presenteeism) limit worker control over scheduling in practice. The severity of these constraints varies significantly between platforms, the formally freest platform presenting the greatest structural and cultural‐cognitive constraints. We also find that workers have developed informal practices, tools, and communities to address these constraints. We conclude that focusing on outcomes rather than on worker control is a more fruitful way to assess flexible working arrangements.