| dc.description.abstract | This study is an examination of human resource management (HRM) in the platform-driven
gig economy. More specifically, this research aims to answer the following question:
How do different actors in the algorithm-driven platform economy influence HRM perceptions
of gig workers?
A qualitative method is used to collect and analyse non-numerical data from interviews with
gig workers in the food delivery sector. The research scope is narrowed down to Europe, and
the participants interviewed are residents in the Netherlands, Norway and Germany. The gig
workers interviewed have worked for Uber Eats, Foodora and Deliveroo.
Human research management can contribute greatly to a firm’s performance and competitive
advantage. However, past research on HRM has mainly been conducted in more traditional
sectors, which are not based on algorithms and technology. Furthermore, an increasing number
of companies use automated, less human-based approaches in managing their workforce. This
study thus aims to understand which actors affect the gig worker’s perception of HRM and how
they do so.
The results of this research found differences in the perceptions of riders across gig companies,
depending not only on the company they work at but also on the country they are working in.
The main finding of the research is that seven key actors play major influencing roles in
developing HRM perceptions of the riders. The actors are the companies, merchants,
customers, fellow riders, tax offices, trade unions and the riders themselves. The strongest
factors influencing HRM perceptions are money, flexibility, rewards, customer tips, the
unpredictability of waiting time, solidarity with other riders, employee support from trade
unions and self-motivation of the riders.
Thus, the research provides interesting and relevant primary evidence showing that multiple
actors influence the positive and negative perceptions for riders working in the food delivery
sector in the platform economy. | en_US |
