As electric vehicle (EV) markets mature and governments worldwide consider ending costly financial incentives, there is a lack of empirical evidence on the sustained effectiveness of these incentives once they are reduced or eliminated. Exploiting the sudden pause of the Canada iZEV purchase subsidy program as a natural experiment and using the quasi-experimental controlled interrupted time series approach, this nationwide study estimates the causal impacts of the purchase subsidy on the uptake of zero-emission electric vehicles (ZEVs) over the 7-year period from 2019 to 2025. The results show that after accounting for the pre-pause quadratic growth trend in ZEV adoption, ending the purchase subsidy in the first quarter of 2025 immediately reduced the new ZEV adoption rate by 10.2 percentage points, representing more than half (55%) of the adoption rate that would have been observed in the absence of the subsidy exit. Furthermore, the new ZEV adoption rate grew only linearly over time in the post-subsidy period, losing the quadratic growth enjoyed in the pre-pause period. Our analysis also reveals substantial heterogeneity in the impacts of ending the purchase subsidy across ZEV types (battery EVs vs. plugged-in EVs) and across regions with different population sizes and EV market maturity. These findings help inform the boundaries of subsidy effectiveness, the design of subsidy exit schemes, and the forecasts of policy impacts, thus supporting more efficient allocation of public resources.
The primary trade-off faced in public transport planning and design is between the level of service experienced by users and the costs borne by the operators. It has been shown that these latter weigh more when imposing self-financing policies at the expense of the relevance of users’ costs (their time), inducing smaller than optimal fleets of larger than optimal vehicles. This study analyzes the effects of ignoring user costs (UC) in the strategic design of public transport systems from a structural perspective, with a particular focus on spatial design. The problem is addressed using three simplified networks (cross-shaped, triangular, and Y-shaped), over which traditional line structures are compared: Feeder-Trunk, Hub-and-Spoke, Direct (avoiding transfers), and Exclusive (avoiding transfers and intermediate stops). For each network and line structure, operational variables —frequencies and bus sizes— are optimized under two objectives: minimizing operator cost (OC) and minimizing OC + UC. Four elements stand out in the analysis: transfers, idle capacity, excess distance traveled, and stopped utilization. The main result is that the optimal structure varies with the level and distribution of demand when OC + UC are minimized, but when UC is omitted, the structure that generally dominates is the Exclusive one, always operating with an undersized fleet of oversized buses running at lower frequencies than those of the OC + UC optimum. Differences with what is reported in the literature are discussed, motivating further analysis in more complex networks.
Online professional aviation education holds significant potential to address the global aviation workforce shortage and advance equity for underrepresented learners, yet large-scale empirical evidence on participation, completion, and equity outcomes remains scarce. This study evaluates the International Civil Aviation Organization (ICAO)–the University of Waterloo Aviation Fundamentals Education programme (AVIFUN), a longitudinal online professional education initiative spanning 3,026 learners across 141 countries from 2020 to 2025, with a focus on the equity implications of a structural transition from a long-format 20-hour model to a modular micro-credential architecture in July 2025. Using multivariable binary logistic regression, pre/post comparative analysis with Wilson score confidence intervals, and interaction modeling, the study examines how programme format, gender, Least Developed Country (LDC) status, and ICAO region independently and jointly predict certificate attainment. The micro-credential transition was associated with a near-fivefold increase in LDC participation (from 2.8% to 14.7%) and a rise in female enrolment from 26.1% in 2020 to 46.8% in 2025. These access gains were, however, accompanied by a significant decline in certificate attainment, with micro-credential learner-level certification (76.5% certifying any module) not significantly different from long-format certificate attainment (73.8%; learner-level OR = 1.105, p = 0.619). A 22.6 percentage-point gender completion gap within micro-credentials and significant regional heterogeneity further characterize the equity landscape. Module-level analysis confirms that gender and region did not systematically influence content selection, a positive equity outcome. The findings reveal a fundamental access-completion trade-off in micro-credential delivery and offer actionable design recommendations for second-generation programme architectures to sustain both access equity and completion equity in global aviation professional education.
Game-based approaches are increasingly employed to address complex challenges in logistics and freight transport. While traditionally employed for education and workforce training, they have broader applications and untapped potential. In particular, advances in artificial intelligence (AI) are creating new opportunities to design, personalise, and scale these interventions. Despite this growing interest, a comprehensive understanding of how game-based approaches have evolved, who they target, what functions they serve, and where future opportunities lie remains limited. This study presents a systematic review of 87 studies on game-based interventions in freight transport and logistics, synthesising evidence across five application domains: warehouse operations management, terminal operations management, transport planning and optimisation, reverse logistics, and risk management and resilience. The findings reveal that games are evolving beyond training applications towards behavioural research, decision support, stakeholder engagement, and consumer behaviour change. Target audiences have similarly expanded from students and operational personnel to include managers, planners, consumers, and participants in behavioural research settings. Nevertheless, evidence regarding the long-term effectiveness of these interventions remains scarce, and several logistics challenges remain largely unexplored. Building on evidence-based gaps identified in the literature, this review proposes future research directions and highlights the potential of AI to enable adaptive, personalised, and scalable game-based interventions. By consolidating fragmented knowledge and outlining emerging opportunities, this study provides a foundation for researchers and practitioners seeking to harness game-based approaches to understand and improve logistics and freight transport systems.
Advanced parking information systems (APISs) aim to alleviate urban parking challenges by providing real-time information and reservations. Their effectiveness, however, depends on how drivers respond to these services when they coexist with uncertain current parking options. This decision process is shaped by psychological mechanisms which standard utility-maximizing models often fail to capture. This study addresses this gap by examining drivers’ APIS choices through an anchored generalized random regret minimization (AG-RRM) model, extended within a latent class framework. By introducing the Self-Report Parking Habit Index (SRPHI), we further quantify the strength of ingrained parking routine and its impact on APIS choices. Results from a stated preference survey reveal parking behavior spans a spectrum from asymmetric regret aversion to linear attribute trade-offs. Familiar current parking serves as a reference anchor associated with stronger regret responses when APIS options underperform. We identify two distinct driver segments based on SRPHI scores. Efficiency-oriented drivers (38.8%) respond rationally to quantifiable APIS benefits. Conversely, habitual or anchor-bound drivers (61.2%) represent the majority, exhibiting stronger regret aversion and anchoring-related responses involving current parking. For the anchor-bound majority, the estimated responses suggest that marginal price signals alone may be insufficient to nudge adoption. These insights provide a behavioral foundation for personalized measures and de-anchoring interventions promoting APIS usage. We suggest APIS operators leverage psychological nudges, such visualizing invisible cruising costs, to weaken the perceived surcharge-free advantage of current parking options. By reframing the mental anchor, such non-monetary interventions have the potential to address behavioral inertia and improve parking efficiencies.
