The increase in electric vehicles as a low‐carbon mobility option has driven interest from many workplaces and local governments to offer charging services for employees, customers and visitors. However, the lack of incentives to limit over‐consumption in shared charging resources has led to congestion issues. In this paper, we use high‐frequency data to study two deterrence mechanisms implemented at one of the largest workplace charging programs in the United States. We study both price and nonprice interventions that encourage adoption of workplace norms and charging etiquette for resource sharing in charging stations. To study these mechanisms, we use a dynamic regression discontinuity design to separately identify treatment effects with digital platform data. Our findings provide new evidence that group norms can play an important role in driving behavioral compliance when setting EV access policies. We also find that workplace norms are complements to dynamic pricing policies. We discuss the implications of this data discovery for the effective management of common pool resources in the context of workplace charging and space‐constrained environments. This article met the requirements for a Gold‐Gold JIE data openness badge described at http://jie.click/badges.
Problems of poor network interoperability in electric vehicle (EV) infrastructure, where data about real-time usage or consumption is not easily shared across service providers, has plagued the widespread analysis of energy used for transportation. In this article, we present a high-resolution dataset of real-time EV charging transactions resolved to the nearest second over a one-year period at a multi-site corporate campus. This includes 105 charging stations across 25 different facilities operated by a single firm in the U.S. Department of Energy Workplace Charging Challenge. The high-resolution data has 3,395 real-time transactions and 85 users with both paid and free sessions. The data has been expanded for re-use such as identifying charging behaviour and segmenting user groups by frequency of usage, stage of adoption, and employee type. Potential applications include but are not limited to simulating and parameterizing energy demand models; investigating flexible charge scheduling and optimal power flow problems; characterizing transportation emissions and electric mobility patterns at high temporal resolution; and evaluating characteristics of early adopters and lead user innovation.
We estimate a Ricardian model of Western European agricultural land values using farm-level data. We model the effect of temperature on land values using a flexible specification of daily mean temperature to test if there are temperature threshold effects. Results indicate that there are no temperature thresholds beyond which agricultural land values suddenly drop. The results are robust to alternative model specifications. Adaptation explains why a smooth aggregate response function is compatible with sharply non-linear crop yield functions. With adaptation, the effect of warming on Western European agriculture is likely to be smooth.
Micromobility, such as electric scooters and electric bikes—an estimated US$300 billion global market by 2030—will accelerate electrification efforts and fundamentally change urban mobility patterns. However, the impacts of micromobility adoption on traffic congestion and sustainability remain unclear. Here we leverage advances in mobile geofencing and high-resolution data to study the effects of a policy intervention, which unexpectedly banned the use of scooters during evening hours with remote shutdown, guaranteeing near perfect compliance. We test theories of habit discontinuity to provide statistical identification for whether micromobility users substitute scooters for cars. Evidence from a natural experiment in a major US city shows increases in travel time of 9–11% for daily commuting and 37% for large events. Given the growing popularity of restrictions on the use of micromobility devices globally, cities should expect to see trade-offs between micromobility restrictions designed to promote public safety and increased emissions associated with heightened congestion.
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