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Aligning electric vehicle (EV) charging with periods of abundant clean energy is essential for decarbonizing transportation. In solar-dominated grids, this requires shifting charging to midday hours – when vehicles are typically parked at workplaces. Yet workplace charging networks operate under institutional constraints such as shared infrastructure, bundled parking and charging services, and limited willingness to require drivers to move vehicles, making time-of-day pricing and active management difficult to implement. In a natural field experiment (n = 629 drivers) across a large workplace charging network, we randomize time-invariant price discounts and environmental nudges that emphasize the environmental benefits of daytime charging. Price discounts modestly increase workplace charging but shift charging toward off-solar periods when charger occupancy is lower, while environmental nudges re-time charging toward solar hours without increasing total demand. A follow-up experiment shows that these timing responses are driven by perceived charger scarcity and congestion under price discounts. Finally, we quantify the abatement costs per ton of CO2 of these shifts.

Many workplaces and other institutions are grappling with how to plan and deploy electric vehicle (EV) charging networks to support their employees and other constituents who drive EVs. We develop a novel approach for designing EV charging networks that is driver-centric: it estimates drivers' charging needs based on their driving and charging habits and determines the optimal number and type of chargers to install to meet those needs. Unlike prior literature, our framework establishes a unique individual profile for each driver based on their observed behaviors and habits. We demonstrate our approach at the University of California San Diego (UCSD) EV network of 439 charging ports using behavioral data derived from 800 EV drivers. We find that using unique driver profiles significantly increases expected network usage and size—in some cases requiring fivefold more workplace charging sessions and a threefold larger network compared to the same analysis based on regionally-averaged driver data. These increases are driven by drivers' tendency to recharge with high battery state-of-charge, which increases network size by 50 alone and implies less value in using high-power chargers. An institution’s goals for supporting drivers, which are important for equity, also significantly affect network size.

Players often fail to coordinate on the efficient equilibrium in laboratory weak-link coordination games. In this paper, we investigate whether such coordination failures can be mitigated by increasing the number of rounds or altering per-period stakes. We find that neither time horizon nor stakes affect equilibrium selection. In contrast to previous findings, players are not more likely to play above the previous period’s minimum choice when the horizon is longer or per-period stakes lower. We also investigate which socio-demographic factors and behavioral traits correlate most strongly with play both in the first round and in subsequent rounds. Cognitive ability as measured by a cognitive reflection test stands out as the characteristic that is most strongly associated with efficient coordination.