Light duty electrification requires DC charging stations to take over the current role of petroleum stations. However, charging and fueling systems differ substantially in technology, user behavior, and business models. This study analyzes thousands of reviews for petroleum stations and DC charging stations. Using a mixed-methods approach combining quantitative rating, sentiment analysis, and Large Language Model (LLM)-assisted topical classification, factors that shape user experience are identified. Charging and fueling are perceived as fundamentally different activities. Fueling reviews are dominated by fuel price and staff interaction, while charging reviews emphasize equipment reliability, location convenience, and access to nearby amenities. Manufacturer-owned charging networks are perceived more positively than open networks. Open networks suffer from small station sizes and higher outage rates which reduce effective capacity and generate negative feedback. Across networks, proximity to amenities strongly influences perceived convenience and satisfaction. These findings identify actionable pathways for improving charging experiences and perceptions.
Despite advances in transport technology, ownership of alternative fuel vehicles (AFVs) remains markedly lower than that of conventional vehicles. While prior work has highlighted the influence of the built environment on AFV ownership, the social mechanisms underlying this relationship are less well understood, particularly the mediating role of social trust. This study investigates the direct and indirect associations between the perceived neighbourhood environment and intention to purchase AFVs, with trust in public institutions and neighbours as mediators. Our findings show that neighbourhoods characterised by good physical activity infrastructure, greater accessibility, and perceived safety are associated with higher levels of trust in public institutions, which in turn increases individuals’ intention to purchase AFVs. The results emphasise the relevance of land-use policies for promoting environmentally sustainable cities and underscore the modest but significant role of social mechanisms in linking land-use policy to AFV ownership.
This study conducts a meta-analysis of 152 primary estimates to examine how social influences affect electric vehicle (EV) adoption. We distinguish between informational influences (social interaction and neighborhood effect) and normative influences (social norm and social symbolism). The results confirm a significant overall effect of social influences on EV adoption, with normative influences outweighing informational ones. Over time, the dominant normative driver shifts from social symbolism to social norm. Cross-sectionally, social norm is more influential in collectivistic cultures and for conservative innovations, whereas informational social interaction is more influential in individualistic cultures and for radical innovations. Based on these findings, we recommend celebrity endorsements to amplify social symbolism in early market stages, and green labelling to reinforce social norm in mature markets. Community-based campaigns that foster social interaction are suggested for individualistic regions and radical innovations, while broad publicity emphasizing social norm is suggested for collectivistic regions and conservative innovations.
The inclusion of the maritime sector in the EU Emissions Trading System (EU ETS) exposes shipowners to dual compliance risks: carbon price volatility and unexpected excess emissions from emission-reduction equipment failures. We propose a novel risk management framework integrating an EUA Price Call Option (EPCO) and a Carbon Emission Equipment Loss Insurance (CEELI). We develop a rigorous pricing model that incorporates the joint stochastic dynamics of carbon prices and EUR/USD exchange rates, alongside the “bathtub” reliability curve of abatement technologies. A case study demonstrates that the framework successfully translates operational risks into transparent, budgetable upfront premiums, providing a “cost of certainty” for operators. Furthermore, scenario analyses reveal a dynamic operational-financial interaction mechanism: EPCO adoption is driven by EEA voyage exposure and cost pass-through capacity, whereas CEELI acts as a strategic financial enabler for fleet retrofitting. We provide a highly adaptable financial toolkit for shipping operators navigating the EU ETS transition.
Despite the inherent complexity of urban mobility, conventional methodologies often oversimplify the associations between transit demand and built environment, leaving nonlinearity and behavioral asymmetries obscured. This study integrates computer vision and explainable artificial intelligence (XGBoost-SHAP) to decode how the micro-scale built environment affects multidimensional bus ridership. Six environmental visual proxies were extracted through semantic segmentation from 3,736 street view imagery, and subsequently analyzed alongside 8.6 million ridership records over one month across 934 bus stops in Shenzhen, China. Four models distinguish temporal-behavioral patterns (weekday peak vs. weekend off-peak, boarding vs. alighting). The results reveal behavioral heterogeneity: stronger correlations were observed in boarding than alighting demand, while weekend discretionary trips exhibit greater sensitivity to micro-environmental quality than weekday mandatory trips. By quantifying nonlinear threshold effects and diminishing marginal utilities, this study develops a spatial screening matrix that supports planners in flagging environmental mismatches and advancing transit-demand-oriented, data-driven transportation planning.
