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.
