Interaction of consumer preferences and climate policies in the global transition to low-carbon vehicles

Burgeoning demands for mobility and private vehicle ownership undermine global efforts to reduce energy-related greenhouse gas emissions. Advanced vehicles powered by low-carbon sources of electricity or hydrogen offer an alternative to conventional fossil-fuelled technologies. Yet, despite ambitious pledges and investments by governments and automakers, it is by no means clear that these vehicles will ultimately reach mass-market consumers. Here, we develop state-of-the-art representations of consumer preferences in multiple, global energy- economy models, specifically focusing on the non-financial preferences of individuals. We employ these enhanced model formulations to analyse the potential for a low-carbon vehicle revolution up to mid-century. Our analysis shows that a diverse set of measures targeting vehicle buyers is necessary for driving widespread adoption of clean technologies. Carbon pricing alone is insufficient for bringing low-carbon vehicles to mass market, though it can certainly play a supporting role in ensuring a decarbonised energy supply

A scalable preference model for autonomous decision-making

Emerging domains such as smart electric grids require decisions to be made autonomously, based on the observed behaviors of large numbers of connected consumers. Existing approaches either lack the flexibility to capture nuanced, individualized preference profiles, or scale poorly with the size of the dataset. We propose a preference model that combines flexible Bayesian nonparametric priors-providing state-of-the-art predictive power-with well-justified structural assumptions that allow a scalable implementation. The Gaussian process scalable preference model via Kronecker factorization (GaSPK) model provides accurate choice predictions and principled uncertainty estimates as input to decision-making tasks. In consumer choice settings where alternatives are described by few key attributes, inference in our model is highly efficient and scalable to tens of thousands of choices

Temporal discounting of gains and losses of time: An experimental investigation

This paper investigates “asymmetries” between non-monetary gains and losses in intertemporal choice. We considered gains and losses of spare/working time with respect to a reference duration defined in a working contract. Specifically, we elicited a behavioral model of intertemporal choice that accounts for a gain/loss-dependent discounting function and a reference-dependent utility. Additionally, we did not impose preference for the present (positive discounting) and allowed for both decreasing and increasing impatience. While our results are standard regarding the discount of money (our baseline treatment), our subjects heavily discounted gains of time. More patience was observed for losses of time and a sizable portion of subjects even exhibited negative discounting, i.e. prefer to expedite losses of time. Our econometric estimations also reveal a much larger heterogeneity of behavior in terms of both utility and discounting for gains and losses of spare time as compared to money

Physician-patient communication and patient-reported outcomes in the actinic keratosis treatment adherence initiative (AK-TRAIN): a multicenter, prospective, real-life study of treatment satisfaction, quality of life and adherence to topical field-directed therapy for the treatment of actinic keratosis in Italy

Background: Patients with multiple actinic keratoses (AKs) should be treated with field-directed therapy. Such treatments challenge patients’ adherence due to out-of-pocket costs, length of treatment and severity of local skin reactions (LSRs). Effective physician–patient communication (PPC) may buffer therapy-related distress, thus improving quality of life, treatment satisfaction and adherence. Objectives: We evaluated the interplay between PPC, LSR intensity (safety) and lesion clearance rates (effectiveness) on treatment satisfaction, quality of life and treatment adherence among patients with multiple AKs receiving topical field-directed therapies. Methods: In this observational, multicentre, longitudinal, cohort study, we included 1136 adult patients with discrete, clinically detectable, visible, multiple (three or more lesions in a 25 cm 2 area), Grade I/II AKs, for whom the attending dermatologist has prescribed treatment with a topical field-directed therapy. We matched self-reported data and medical information recorded by dermatologists in standard clinical forms. Patients were followed up at two time points (T1: 8 days; T2: 25–30 days). Results: Most patients were elderly, married, men with poor socio-economic status and multiple lesions of the scalp or face. The majority (n = 961) had a prescription of ingenol mebutate (IMB) and 175 received either diclofenac 3% in hyaluronic acid (DHA) or imiquimod 5% (IMQ). Clearance rate at 1 month was 84%. Most patients felt very supported (n = 819, 73%) and rated dermatologist's explanations very clear (n = 608, 54%). Treatment satisfaction (effectiveness and convenience scales) increased along the follow-up, especially for those on IMB (Δ pre-post = −4.00; other: Δ pre-post = −0.25; interaction P < 0.001). Communication clarity was associated with higher treatment satisfaction scores (β = 0.4–0.6, P < 0.01) and lower risk of non-adherence among IMB patients (risk difference: 16%, P < 0.01). Conclusion: Communication clarity was associated with patient-reported outcomes and adherence beyond AK-related clinical parameters. Our study questions the current episodic approach to AK management and provides the rationale to develop chronic care models fostering patients’ engagement and treatment alliance