Preferences for electric vehicles under uncertain charging prices: An eye-tracking study

Abstract

Fluctuating operating costs (OC) create uncertainty around the benefits of electric vehicles (EVs). This study is the first to explore how uncertain OC impacts EV preferences using an extended decision field theory (DFT). We examine Singaporean ride-hailing drivers’ EV rental choices under uncertain OC, finding that extended DFT outperforms prospect theory. Incorporating eye-tracking data further improves DFT’s explanatory power, leading to two insights. First, younger, frequent, long-distance drivers are more inclined to adopt EVs and are more affected by uncertainty in OC. For example, for drivers with a daily OC of $25, a 20% chance of a $12.5 increase in OC reduces EV preference by 1.5%. Second, providing drivers with clear information on predictable OC increases is more effective than leaving them uncertain; for instance, a guaranteed $5 increase in daily OC is preferable to letting drivers guess about a random increase between $2.5 and $8.5.