Gad Allon, Operations, Information and Decisions, The Wharton School
Abstract: The gig economy is rapidly integrating electric vehicles (EVs) into its infrastructure, particularly within ride-hailing services such as Uber and Lyft. Algorithms play a crucial role in this ecosystem, determining customer pricing, driver compensation, and matching drivers with customers. While these algorithms have enabled efficient matching of supply and demand, they also face criticisms, including a lack of transparency, potential bias, and inefficiency. This study investigates the decision-making processes of EV drivers within the gig economy, focusing on how charging infrastructure and fleet size impact driver behavior. The power dynamics of algorithms are scrutinized, particularly in terms of how they influence driver earnings and operational efficiency. Leveraging insights from recent research on EV fleet and charging infrastructure planning, we aim to understand the complexities of EV integration in gig economy services.