While online platforms were initially applauded for improving services in a range of sectors, they are currently being criticized for ignoring laws and regulations. We analyse the evolution of Helpling – the largest domestic cleaning platform company in Europe – by focusing on the ways that Helpling has adapted its platform to regulations in five national contexts (France, Germany, Ireland, the Netherlands and the United Kingdom). Using data on changing Terms and Conditions, we show that Helpling initially tried to introduce a single business model across Europe, but quickly started to adapt to national regulatory contexts. Informed by arguments on ‘varieties of capitalism’ in Europe, we base our case study on a comparison of the different national trajectories pursued by Helpling.

In the past decade, the widespread use of smartphones, app software, and broadband internet access has led to the rise of internet platforms, particularly online marketplaces that connect job requesters with workers in various sectors. These platforms, commonly known as the gig economy, have become a significant part of the labor market. One distinguishing feature of gig economy platforms is that they classify their workers as independent contractors. Although gig platforms have been seen as operating in a regulatory gray area, the physical nature of onsite gig transactions and their presence within specific legal jurisdictions make regulatory issues more pertinent in the onsite gig economy. Moreover, different countries face distinct regulatory challenges related to gig economy platforms, even when dealing with the same platform. This thesis focuses on the institutional conditions that shape gig economy platforms during their stages of development, including creation, internationalization, and adaptation. The central research question is how national institutions impact onsite gig economy platforms. Chapter 2 of the thesis defines the gig economy based on four dimensions: online vs. offline intermediation, independent contractor vs. platform employee, paid vs. unpaid labor, and provision of services vs. goods. Each dimension raises regulatory questions regarding the classification of platforms and workers. Chapter 3 explores how national institutions influence the founding and international expansion of gig economy platforms. The findings indicate that while national institutions have limited effects during the founding stage, they play a crucial role in the internationalization process. Geographical conditions, particularly larger populations and capital city status, affect the likelihood of hosting newly founded platforms but do not predict higher rates of internationalization. Chapter 4 focuses on how national institutions respond to gig platforms following their international expansion. Using Uber as a case study, the chapter examines how institutional actors, such as the police and local authorities in different countries, reacted to Uber's service with unlicensed drivers. The results show varied responses, including bans and tailored regulations, particularly in countries with well-functioning legal institutions. Chapter 5 investigates how gig platforms adapt to negative institutional reactions to ensure their survival and success. Using Helpling.com, a major cleaning platform in Europe, as a case study, the chapter analyzes the evolution of its employment relationship with gig workers across five European countries. The findings reveal that Helpling had to adapt its business model to comply with each country's regulatory context, with more significant changes occurring in countries with stricter labor market regulations. The main conclusion of the thesis is that gig platforms are not operating in a regulatory void but are significantly influenced by prevailing institutions. The existence of certain institutions can facilitate or hinder platform operations and evolution. Home country institutions supporting innovation and labor flexibility promote platform internationalization. However, a well-functioning justice system leads to more negative institutional reactions against new platforms. The findings also highlight that stringent labor market institutions and sectoral regulations prompt gig platforms to adjust their business models to provide gig workers with more autonomy and reduce institutional frictions.