From Co-Location Patterns to an Informal Social Network of Gig Economy Workers

Gustavo Pilatti, Cristian Candia, Alessandra Montini, Flávio L. Pinheiro

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)
29 Downloads (Pure)

Abstract

The labor market has transformed with the advent of the gig economy, characterized by short-term and flexible work arrangements facilitated by online platforms. As this trend becomes increasingly prevalent, it presents unique opportunities and challenges. In this manuscript, we comprehensively characterize the social networks of gig economy workers in each of the 15 cities studied. Our analysis reveals a scaling relationship between networks and the city population. In particular, we note the high level of modularity of the networks, and we argue that it results from the natural specialization of couriers along different areas of the cities. Furthermore, we show that degree and betweenness centrality is positively correlated with income but not with tenure. Our findings shed new light on the social organization of the gig economy workers and provide valuable insights for the management and design of gig economy platforms.
Original languageEnglish
Article number77
Pages (from-to)1-15
Number of pages15
JournalApplied Network Science
Volume8
Issue number1
Early online date9 Nov 2023
DOIs
Publication statusPublished - 1 Dec 2023

Keywords

  • Gig economy
  • GPS data
  • Big Data
  • Co-location social network
  • Complex networks

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