Periodic Reporting for period 1 - www.WORK (How Mirror-Image Effects Shape Online Labour Markets)
Período documentado: 2023-01-01 hasta 2025-06-30
Making the Online Gig Economy Work for Workers:
In today’s world, work is increasingly organized through digital platforms. Millions of people now earn a living by offering services – such as programming, translation, or graphic design—online, often through platforms like Fiverr, Upwork or Truelancer. This shift has created the first truly global labour market, commonly known as the "gig economy." While it offers flexibility and new opportunities, it also comes with risks: many gig workers earn low wages and lack social protections like health insurance or pensions.
This project investigates the vital question: can national governments still protect gig workers in this global, digital market? Or will regulations simply drive the demand for gig work to cheaper, less regulated countries?
To answer this, the project introduces a new idea called mirror-image specialization. It suggests that national education and labour systems shape which skills are common in a country—and as a result, what kinds of gig work people seek or offer online. For example, countries with lots of specialists may seek generalists online, and vice versa. This means that the online gig economy may develop in ways that complement rather than compete with national job markets.
Using large-scale data across platforms and countries, the project explores how these patterns unfold—and how they could enable smarter national regulation without driving away digital jobs.
The project’s findings are expected to break new ground in understanding how digital work is shaped by national institutions, offering practical insights for policy-makers. If successful, this research could show how gig workers might be better protected—without sacrificing the benefits of global digital markets.
In today’s world, work is increasingly organized through digital platforms. Millions of people now earn a living by offering services – such as programming, translation, or graphic design—online, often through platforms like Fiverr, Upwork or Truelancer. This shift has created the first truly global labour market, commonly known as the "gig economy." While it offers flexibility and new opportunities, it also comes with risks: many gig workers earn low wages and lack social protections like health insurance or pensions.
This project investigates the vital question: can national governments still protect gig workers in this global, digital market? Or will regulations simply drive the demand for gig work to cheaper, less regulated countries?
To answer this, the project introduces a new idea called mirror-image specialization. It suggests that national education and labour systems shape which skills are common in a country—and as a result, what kinds of gig work people seek or offer online. For example, countries with lots of specialists may seek generalists online, and vice versa. This means that the online gig economy may develop in ways that complement rather than compete with national job markets.
Using large-scale data across platforms and countries, the project explores how these patterns unfold—and how they could enable smarter national regulation without driving away digital jobs.
The project’s findings are expected to break new ground in understanding how digital work is shaped by national institutions, offering practical insights for policy-makers. If successful, this research could show how gig workers might be better protected—without sacrificing the benefits of global digital markets.
To investigate how digital gig work develops across countries and whether national institutions still shape labour outcomes in the age of global online markets, the project is structured around four objectives. The first objective focuses on those who use gig workers and asks why firms hire online gig workers. Our analyses of large-scale data across multiple platforms shows that firms often use online work to access skills not readily available in their country. For example, countries with many specialists tend to seek generalist gig workers online—and vice versa.
The third objective, focusing on those who offer gig work, shows a similar mirror-image effect: workers tend to offer online the skills that are underutilized in their home country. These findings support the project’s new theory that online and offline labour markets evolve in opposite directions due to national institutional constraints.
The second objective, still ongoing, explores how platforms manage users and match skills, exploring a novel dataset of reviews from over 100 platforms. Preliminary findings suggest that management practices affect user satisfaction differently for workers and clients, highlighting tensions in platform governance. The realisation of the fourth objective will start in project year 3.
Key achievements include the creation of two unique datasets, covering information on gig jobs and gig workers across three major platforms, and capturing user experiences across more than 100 gig platforms. These datasets are enabling dynamic, cross-platform, and longitudinal analyses that go beyond the current state of the art.
In sum, the project has laid the theoretical, empirical, and analytical groundwork for a new understanding of digital labour markets and their regulation, offering hope that national policy can still shape fair outcomes in a globalised world of work.
The third objective, focusing on those who offer gig work, shows a similar mirror-image effect: workers tend to offer online the skills that are underutilized in their home country. These findings support the project’s new theory that online and offline labour markets evolve in opposite directions due to national institutional constraints.
The second objective, still ongoing, explores how platforms manage users and match skills, exploring a novel dataset of reviews from over 100 platforms. Preliminary findings suggest that management practices affect user satisfaction differently for workers and clients, highlighting tensions in platform governance. The realisation of the fourth objective will start in project year 3.
Key achievements include the creation of two unique datasets, covering information on gig jobs and gig workers across three major platforms, and capturing user experiences across more than 100 gig platforms. These datasets are enabling dynamic, cross-platform, and longitudinal analyses that go beyond the current state of the art.
In sum, the project has laid the theoretical, empirical, and analytical groundwork for a new understanding of digital labour markets and their regulation, offering hope that national policy can still shape fair outcomes in a globalised world of work.
This project has made important advances in how we understand digital gig work across the globe. Most research so far has focused on single platforms, specific countries, or only on workers. This project goes far beyond this state-of-the-art by developing a new theory, collecting rich new data, and analysing the online gig economy in a way that captures its complexity over time.
A central innovation is the theory of mirror-image specialization, which shows that the skills in demand and on offer in the gig economy tend to be the opposite of what is available in a country’s traditional labour market. For example, countries with many specialist jobs tend to hire generalists online — and workers with underused skills at home tend to offer those online. This goes against the common belief that the development of gig work is mainly driven by cheap labour or global wage competition.
To test this theory, we built two major datasets:
- One dataset, covering job and worker profiles across three of the largest gig platforms worldwide; and
- one dataset, tracking user satisfaction and management practices across 100 gig platforms.
These datasets allow us to observe gig work over time and across platforms, enabling dynamic, multi-actor analyses far beyond what was previously possible. Our first studies confirm the mirror-image specialization patterns and show that platforms’ design choices also shape user satisfaction differently for workers and clients.
By revealing that national institutions still influence online work, our project may open up new ways for governments to regulate and protect digital workers – without driving jobs to cheaper countries. To fully realise these impacts, continued research, international policy dialogue, and collaboration with platforms will be essential.
These results lay the foundation for a new understanding of how online work is shaped, potentially influencing labour policy, platform design, and academic research worldwide.
A central innovation is the theory of mirror-image specialization, which shows that the skills in demand and on offer in the gig economy tend to be the opposite of what is available in a country’s traditional labour market. For example, countries with many specialist jobs tend to hire generalists online — and workers with underused skills at home tend to offer those online. This goes against the common belief that the development of gig work is mainly driven by cheap labour or global wage competition.
To test this theory, we built two major datasets:
- One dataset, covering job and worker profiles across three of the largest gig platforms worldwide; and
- one dataset, tracking user satisfaction and management practices across 100 gig platforms.
These datasets allow us to observe gig work over time and across platforms, enabling dynamic, multi-actor analyses far beyond what was previously possible. Our first studies confirm the mirror-image specialization patterns and show that platforms’ design choices also shape user satisfaction differently for workers and clients.
By revealing that national institutions still influence online work, our project may open up new ways for governments to regulate and protect digital workers – without driving jobs to cheaper countries. To fully realise these impacts, continued research, international policy dialogue, and collaboration with platforms will be essential.
These results lay the foundation for a new understanding of how online work is shaped, potentially influencing labour policy, platform design, and academic research worldwide.