Along with the proliferation of electric vehicles (EVs), optimizing the use of EV charging space can significantly alleviate the growing load on intelligent transportation systems. As the foundation to achieve such an optimization, a spatiotemporal method for EV charging demand prediction in urban areas is required. Although several solutions have been proposed by using data-driven deep learning methods, it can be that these performance-oriented approaches may struggle to correctly understand the underlying factors influencing charging demand, particularly charging prices. A representative case that highlights the challenge faced by existing methods is their potential misinterpretation of high prices during peak times, leading to an incorrect assumption that higher prices correspond to increased demand. To address the challenges associated with training an accurate and reliable prediction model for EV charging demand, this paper proposes a novel approach called PAG, which leverages the integration of graph and temporal attention mechanisms for effective feature extraction and introduces physics-informed meta-learning in the pre-training step to facilitate prior knowledge learning. Evaluation results on a dataset of 18,061 EV charging piles in Shenzhen, China, show that the proposed approach can achieve state-of-the-art forecasting performance and the ability to understand the adaptive changes in charging demands caused by price fluctuations.

How can entrepreneurs protect their wellbeing during a crisis? Does engaging agility (namely, opportunity agility and planning agility) in response to adversity help entrepreneurs safeguard their wellbeing? Activated by adversity, agility may function as a specific resilience mechanism enabling positive adaption to crisis. We studied 3162 entrepreneurs from 20 countries during the COVID-19 pandemic and found that more severe national lockdowns enhanced firm-level adversity for entrepreneurs and diminished their wellbeing. Moreover, entrepreneurs who combined opportunity agility with planning agility experienced higher wellbeing but planning agility alone lowered wellbeing. Entrepreneur agility offers a new agentic perspective to research on entrepreneur wellbeing.

This study explores the extent to which changes in transport infrastructure counterbalance pre-existing geographical friction and foster innovation collaboration, using the Chinese high-speed rail (HSR) construction as a quasi-natural experiment. Using a comprehensive dataset of city-pair co-patents from 2005 to 2018, we show that HSR connections significantly increase intercity co-patents, patent quality and collaborative partnerships, and such effects are strongest for city-pairs within 250 km and decrease for longer distances. Moreover, the HSR effect is stronger for cities in similar institutional settings, indicating a negative moderating effect of institutional distance. Various robustness methods are used to confirm the validity of our findings.