Social networking of gig workers in the platform economy

Gig working is a term that describes a new, flexible way of working, where permanent employment is supplemented or replaced by on-demand working that is scheduled online. The contractors, i.e. the gig workers, carry out series of jobs for which they are paid on completion. These typically include assignments in the fields of transport and logistics, events and promotions, all aspects of gastronomy, commercial activities, retail and aviation.

As a new and relevant form of gainful employment, gig working has also taken hold in Switzerland and is spreading, which implies changes in the world of work for both employees and employers. Perspectives on the topic from the point of view of industrial and organisational psychology are aimed at providing innovative food for thought.

This project is the first in Switzerland to explore the informal networking that occurs between gig workers. With Coople Schweiz AG, the largest provider in the country, as industry partner, the communication and networking needs of gig workers are being examined with the aim of strengthening their identification with, and commitment to, the job placement platform.

This involves helping the industry partner to understand gig workers and make them "tangible", and, as a result, develop target group-specific offerings. The project includes the following services, which will be used in the form of social and technology-based renewals going forward:

• Developing a gig worker typology for segmentation purposes and for the development of "gig worker personas" (archetypal users)
• Strengthening user engagement and retention by considering contextual and specific user interests that focus on extended communication, information and networking processes
• Reducing effort and cost and driving quality assurance through an optimisation/redesign of the onboarding process in line with holistic criteria based on occupational psychology
• Developing and implementing a machine-based sentiment analysis methodology to optimise text and data mining activities

Project Dates