EXAMINING INDIRECT NETWORK EFFECTS IN THE ELECTRIC VEHICLE MARKET SYSTEM

Abstract

Reduction in transportation carbon emissions is a crucial enabler to a net-zero future. As decarbonization efforts increase, many states and the federal government are considering methods to catalyze transportation electrification. This study examines California’s light-duty vehicle (LDV) market's electrification, focusing on capturing EV market behavior that entails: (1) the influence of socioeconomic and demographic variables on the market, (2) the indirect network between electric vehicle (EV) adoption and EV charging infrastructure (EVCS), and (3) adoption and deployment forecast scenarios. The study uses panel data of EV, EVCS, and socioeconomic variables to perform (1) regression analyses and (2) bass diffusion modeling. This study found that median household income and share of owner-occupied housing were most significant to EV adoption and EVCS deployment. The presence of positive bidirectional network effects was verified, with stronger network impacts observed from EVCS than that observed from EVs. The rate of EV and EVCS diffusion until market saturation depends on the current adoption and size of the addressable market.