The catalogue contains study descriptions in various languages. The system searches with your search terms from study descriptions available in the language you have selected. The catalogue does not have ‘All languages’ option as due to linguistic differences this would give incomplete results. See the User Guide for more detailed information.
The Effect of Gig Economy Work: Interviews with Platform Workers, 2020-2021
Creator
Antonucci, L, University of Birmingham
Study number / PID
857105 (UKDA)
10.5255/UKDA-SN-857105 (DOI)
Data access
Restricted
Series
Not available
Abstract
The type of 'gig work,' already familiar to many workers through popular platforms like Uber and Deliveroo, is seen as a potential model for the future of employment. The gig economy blurred the lines between employed and self-employed statuses, with gig workers classified as self-employed, thus missing out on state support available to employed individuals. The project explored how labour market conditions for gig economy workers affected their financial security. It also examined the role of social security provisions in Italy, Sweden, and the UK. The study was initially positioned within broader debates on the increasing precarity of work and the evolving role of the welfare state in European societies. The data collection of this study was conducted between October 2020 and May 2021. 101 platform workers were recruited and invited to take part in in-depth interviews, which lasted from 38 to 119 minutes. Due to Covid-19, all the interviews were conducted remotely, using instruments that maximised participants’ privacy and minimised the risks of data breaches. To guarantee high-quality comparative material, the interviews were conducted by the PI of the project in English in the UK and Sweden, and in Italian and English in Italy, depending on the preference of the participant.Receive a request for a job through your phone, perform the task using your own facilities and get paid. This type of 'gig work' is regarded as the model of work for the future, but it is already experienced by many workers using the popular platforms of Uber and Deliveroo. Gig economy work blurs the division between employed and self-employed work, with gig economy workers being classified as self-employed and therefore being unable to access forms of state support available to employed individuals. This project explores the effects of gig economy workers' labour market conditions on their financial (in)security, and it investigates the role of social security provisions in Italy, Sweden...
Terminology used is generally based on DDI controlled vocabularies: Time Method, Analysis Unit, Sampling Procedure and Mode of Collection, available at CESSDA Vocabulary Service.
Methodology
Data collection period
01/10/2020 - 31/07/2021
Country
United Kingdom, Sweden, Italy
Time dimension
Not available
Analysis unit
Individual
Universe
Not available
Sampling procedure
Not available
Kind of data
Text
Data collection mode
Participants were recruited through digital advertisements, existing apps and, as a last resort, snowballing to maximise the demographic variation of the sample (age and gender) and have participants from a variety of apps. The average age of the workers in this convenience sample was 36, ranging between 18 and 65 years old, and the study used stakeholders and key actors within each country to guarantee the comparability of the qualitative material. To make the study sensitive to gender structural dynamics and address the usual lack of inclusion of experiences of women in platform work research, the study recruited a minimum of 10 female and male participants within each country. This was achieved in part by recruiting participants who worked in platforms with a higher representation of women: beauty (make up, massages etc); cleaning and shopping. The diversity of the applications across the three case studies reflects the different legal and economic contexts within each case study, and the study aimed to have a diversity of apps within each national context , which was reached through the final sample (see the files attached to this data submission).
Funding information
Grant number
ES/S016414/1
Access
Publisher
UK Data Service
Publication year
2024
Terms of data access
The Data Collection is available for download to users registered with the UK Data Service.