Evolution of Labour Supply in Ridesourcing

TL;DR

This paper develops a dynamic model to analyze how gig workers' individual decisions influence the evolution of supply in ridesourcing, revealing complex non-linear supply patterns and implications for market regulation.

Contribution

It introduces a novel dynamic model capturing gig workers' decision processes and examines how market properties affect supply evolution in ridesourcing.

Findings

Labour supply can be non-linear with multiple transitions.

Market regulation like supply caps and fee regulation can improve service stability.

Significant variations in income and service levels over time.

Abstract

Contrary to traditional transit services, supply in ridesourcing systems emerges from individual labour decisions of gig workers. The effect of decentralisation in supply on the evolution of on-demand transit services is largely unknown. To this end, we propose a dynamic model comprising of the subsequent supply-side processes: (i) initial exposure to information about the platform, (ii) a long-term registration decision, and (iii) daily participation decisions, subject to day-to-day learning based on within-day matching outcomes. We construct a series of experiments to study the effect of supply market properties and pricing strategies. We find that labour supply in ridesourcing may be non-linear and undergo several transitions, inducing significant variations in income levels and level of service over time. Our results provide indications that the ridesourcing market may benefit from a cap in supply and regulation of the commission fee.