Economy-wide impacts of road transport electrification in the EU.

While electrification of road transport is a key component of decarbonisation, the implications for the broader economy and related jobs remain underexplored. We quantify these impacts in the EU in a global Computable General Equilibrium (CGE) model, combining techno-economic assumptions about electric vehicles with deployment scenarios derived by energy models. We augment input-output tables underlying the JRC-GEM-E3 model with an explicit representation of vehicle manufacturing and upgrade the modelling of vehicle purchase and operation. Our findings illustrate that greater road transport electrification reduces the overall costs of climate mitigation, primarily driven by lower fuel costs for electric vehicles and a faster decline of battery costs. Transport electrification alters supply-chains and leads to structural shifts in employment from traditional vehicle manufacturing towards battery production, electricity supply and related investments. Finally, we expand the set of labour market indicators to cover skills and occupations, to refine the socio-economic assessments of climate policy.

An acceptance divergence? Media, citizens and policy perspectives on autonomous cars in the European Union.

Do citizens, media and policymakers share the same view on autonomous cars? In the present paper, we analyse data from media articles, a Eurobarometer survey, and policy documents, to understand the perspective of different stakeholders when it comes to autonomous cars. We find significant differences between the groups, with a predominance of negative sentiments in news articles and a majority of citizens being wary of autonomous cars, while the political narrative mostly carries a positive tone. The findings highlight a dichotomous perspective about this potentially disruptive technology. This may represent a problem as the benefits of adopting autonomous cars will only come to surface if all actors are engaged and see the advantages they can bring to people's daily lives. We conclude by encouraging policymakers to promote initiatives to engage citizens in the transformation of road transport and other stakeholders to be advertised the positive implications of autonomous vehicles.

How will vehicle automation and electrification affect the automotive maintenance, repair sector?

Automation and electrification in road transport are trends that will influence several economic sectors of the European economy. The automotive maintenance and repair (M&R) sector will experience the effects of such transitions in the long term. This paper assesses the research in the road transport to derive the factors that may influence the M&R demand based on Battery Electric Vehicles (BEVs) and Autonomous Vehicles (AVs) uptake. Starting from current scientific research and grounded on interviews with experts, the paper reviews major drivers influencing M&R demand and provides indications on possible future effects. While for BEVs, previous work has been conducted to estimate the M&R cost variations, the research addressing the impacts of AVs deployment on the M&R sector is at its incipient stage, hence the views of experts were paramount to shed light on this topic. We identified a scientific consensus that BEVs have less M&R requirements compared with Conventional Vehicles (CVs). For AVs, our analysis and expert views identify some important factors influencing M&R requirements: hardware components, software that enables autonomy, the rise in vehicle kilometres travelled leading to higher wear and tear of replaceable parts, the need for adequate cleaning services, especially for fleets and shared vehicles. Further work should look at the impact of regulations and the non-insurable risks linked to M&R requirements.

The missing path to gain customers loyalty in pharmacy retail: The role of the store in developing satisfaction and trust.

BACKGROUND: An evolution led to community pharmacies experiencing increased competition both between themselves and with new entrants in the sector, for example, grocery retailers. Applying certain retail marketing strategies aimed at developing store loyalty may be an appropriate strategic path for pharmacies wanting to compete in this new arena. OBJECTIVES: This study aimed to develop and test a two-step model to identify the determinants of store loyalty for community pharmacies in Italy. METHODS: Based on the retail literature, qualitative research was conducted to identify key variables determining loyalty to community pharmacies. The model was then tested by means of a phone survey. A total of 735 usable questionnaires was collected. RESULTS: The study highlights the key role of the relationship between pharmacists and their customers in the loyalty-building path; trust in pharmacists is the first driver of satisfaction and a direct and indirect (through satisfaction) driver of trust in pharmacies, which leads to store loyalty. Retail-level levers, such as the store environment, assortment, and communication, influence trust in pharmacies. CONCLUSIONS: This model is a first step toward investigating loyalty-building by applying the retail management literature's concepts to the community pharmacy sector.

Large cryptic genomic rearrangements with apparently normal karyotypes detected by array-CGH.

BACKGROUND: Conventional karyotyping (550 bands resolution) is able to identify chromosomal aberrations >5-10 Mb, which represent a known cause of intellectual disability/developmental delay (ID/DD) and/or multiple congenital anomalies (MCA). Array-Comparative Genomic Hybridization (array-CGH) has increased the diagnostic yield of 15-20%. RESULTS: In a cohort of 700 ID/DD cases with or without MCA, including 15 prenatal diagnoses, we identified a subgroup of seven patients with a normal karyotype and a large complex rearrangement detected by array-CGH (at least 6, and up to 18 Mb). FISH analysis could be performed on six cases and showed that rearrangements were translocation derivatives, indistinguishable from a normal karyotype as they involved a similar band pattern and size. Five were inherited from a parent with a balanced translocation, whereas two were apparently de novo. Genes spanning the rearrangements could be associated with some phenotypic features in three cases (case 3: DOCK8; case 4: GATA3, AKR1C4; case 6: AS/PWS deletion, CHRNA7), and in two, likely disease genes were present (case 5: NR2F2, TP63, IGF1R; case 7: CDON). Three of our cases were prenatal diagnoses with an apparently normal karyotype. CONCLUSIONS: Large complex rearrangements of up to 18 Mb, involving chromosomal regions with similar size and band appearance may be overlooked by conventional karyotyping. Array-CGH allows a precise chromosomal diagnosis and recurrence risk definition, further confirming this analysis as a first tier approach to clarify molecular bases of ID/DD and/or MCA. In prenatal tests, array-CGH is confirmed as an important tool to avoid false negative results due to karyotype intrinsic limit of detection.