The slow uptake of electric cars in Italy and Slovenia. Evidence from a stated-preference survey and the role of knowledge and environmental awareness
Introduction
Battery electric cars (from now on, we will use the widely adopted acronym BEV, Battery Electric Vehicles, though we will refer only to cars) are slowly gaining popularity in many European countries, but at different rates. According to ACEA (2020), BEVs reached in 2019 a 2.3% average market share in the EU + EFTA countries. The small group of countries which leads the way include Norway (42.4%), the Netherlands (13.9%) and Iceland (7.8%), followed by a group of countries with above average uptake levels including, in decreasing order, Sweden, Switzerland, Portugal, Ireland, Austria, and Denmark, with a BEV market share ranging from 4.4% to 2.5%. A third group of countries with slightly below average BEV uptake comprises France, Germany, Finland, United Kingdom, Belgium, Hungary, with a BEV market share going from 1.9% to 1.0%. Finally, there is a group of countries still in the initial phase of BEV uptake (below 1% market share). They are, in decreasing order, Romania, Spain, Slovenia (0.7%), Italy (0.6%), Latvia, Bulgaria, Lithuania, Czech Republic, Poland, Estonia, Greece and Slovakia.
Since a growing number of papers finds that BEVs have the potential to decrease CO2 emissions and to improve air quality at the local level (e.g., Cox and Bauer, 2018 with reference to Switzerland; Knobloch et al., 2020 for 59 world regions), it is worthwhile to examine why some countries are lagging behind in the adoption of BEVs and which policy could be enacted to spur their uptake.
CO2 emissions for a given car are the result of a detailed estimate of the lifecycle emissions associated with the manufacturing, maintenance and end-of-life of the glider, the powertrain (motors, power batteries, electrical converters, charging components, fuel cells, etc.), the energy storage components, the supply of energy carriers used for vehicle operation and the direct emissions from vehicle operation. Although, to the best of our knowledge, no life cycle analysis comparing propulsion systems has been recently performed for Italy and Slovenia (the most recent studies for Italy are Donateo et al., 2015, Rusich and Danielis, 2015), it is quite likely that BEVs will help reduce their overall CO2 emissions. In fact, according to an estimate by Moro and Lonza (2018), Italy has a carbon intensity of gross electricity production (with upstream) of 427 gCO2e/kWh and Slovenia of 329 gCO2e/kWh (having a larger nuclear energy share). This translates, in their calculations, in an estimate for electric vehicle use of 60–80 gCO2e/km for Italy and of 48–60 gCO2e/km for Slovenia, vs. an estimated European average of 145 gCO2e/km for diesel cars and of 178 gCO2e/km for petrol cars.
Moreover, especially Italian cities suffer from unhealthy air quality. In the 2019 report on Air quality in Europe prepared by the European Environment Agency (henceforth EEA) (2019), Italy shows worrying concentration levels of NOx, O3, PM10 and PM2.5, frequently exceeding the recommended limits set by Directive 2008/50/EC for the protection of human health. EEA estimates that in Italy there were a total of 1,183 years of life lost per 105 inhabitants (908 due to PM2.5, 227 due to NOx, and 48 due to O3 exposure) against a EU28 average of 930. Slovenia also fares worse than the EU28 average, with a total of 996 years of life lost per 105 inhabitants (916 due to PM2.5, 39 due to NOx, and 41 due to O3 exposure). Estimating the potential local air pollution reduction from substituting internal combustion engine vehicles (ICEVs) with BEVs is also problematic. Cox and Bauer (2018) argue that life cycle assessments of particulate matter and photochemical oxidant formation are similar for all powertrain types. However, due to their lack of direct exhaust emissions, BEVs have the potential to reduce air pollution in densely populated areas, transferring their air emissions to the regions where vehicles and their components are manufactured. In any case, it is commonly accepted that the environmental performance of BEVs requires low CO2 electricity generation technologies and a high efficiency of the energy chain from electricity generation to the wheel.
With the goal of improving energy efficiency and reducing CO2 emissions, Italy and Slovenia financed the MUSE project within the priority axis of the INTERREG Programme Italy-Slovenia. The project partners are academic institutions, public administrations and agencies for local development, located in the neighboring regions of the two countries, in particular in the western part of Slovenia and in Friuli Venezia Giulia (FVG), a region located in the northeastern part of Italy. Within the MUSE project, we were able to carry out a stated-preference survey (N = 1,934) aimed at evaluating the preferences of the Italian and Slovenian drivers for BEVs relative to ICEVs. We investigated the importance consumers assign to 7 attributes, 4 of them shared by both propulsion systems (brand\model type, purchase price, fuel\electricity costs, driving range with a full tank\charge) and 3 BEV-specific (time needed to fast charge the battery, fast charging station density, free parking). The aim of the study is to identify both common features and preference differences. Moreover, we explored the role played by two latent variables, which we termed as Environmental awareness and BEV knowledge, in shaping car choice, identifying their socio-economic determinants and country-specificities.
The paper contributes to the literature at least in two ways. First, it provides the first car choice study based on Slovenian stated-choice data and with a focus on BEVs, complementing the qualitative research published by Knez et al. (2014). Second, it performs a cross-country comparison of the car choice preference structure between Italian and Slovenian decision makers in order to identify and calibrate the national policies incentivizing BEV uptake and the development of cross-border mobility plans.
The paper is organized as follows. Section 2 reviews the related literature. Section 3 describes the stated choice experiment and the data collection process. Section 4 presents the modelling framework, whilst Section 5 illustrates the results. Section 6 discusses the results and draws some conclusions.
Section snippets
Related literature
Over the years, many authors have reviewed the abundant literature on BEVs (Rezvani et al., 2015, Coffman et al., 2017, Li et al., 2017, Liao et al., 2017, Kumar and Alok, 2020). They clarified the numerous factors that influence BEV adoption including:
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vehicle technical attributes such as acceleration, driving range, battery degradation, maximum speed;
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economic attributes including purchase price, fuel economy, insurance cost, maintenance and repair costs, warranty;
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infrastructural variables such
Stated choice experiment and data collection
We estimate a hybrid mixed logit model, based on stated preference data collected via internet-based interviews, administered between October and December 2018 on a sample of the Italian (N = 996) and the Slovenian (N = 938) population using a CAWI (Computer Assisted Web Interviewing) questionnaire. SWG, a Trieste-based company specialized in market surveys, was in charge of the task and collected a total of 1,934 interviews. The sample was randomly drawn from the SWG Community that has over
Modelling framework
Following Soto et al. (2018b), we model the measurement equation as an ordered probit.
The categorical response of the indicator , where denotes the indicator, c identifies the country, Italy (IT) vs. Slovenia (SI), and detects the respondents, is defined by a set of threshold parameters to be estimated and by which is the discrete choice response to the proposed statement for each
Results
One of the aims of the paper is to detect whether there are statistically significant differences in the stated choices between Slovenian and Italian respondents. Hence, we introduce country-specific attributes in both the utility functions (eq. (6), (7)) and in the structural equations (eq. (3)). Individuals having lexicographic preferences have been excluded from the dataset. We tested all vehicle, infrastructural and policy attributes and many of the available socio-economic variables
Discussion and conclusions
Italy and Slovenia are neighboring countries that share many similarities but have also some differences. In terms of BEV uptake, their rate of adoption is certainly not comparable with that of the Northern European countries, whereas it is similar to that of other Southern and Eastern European countries. Thanks to an INTERREG research project, we were able to perform a survey on a significant number of respondents (N = 996 for Italy and N = 938 for Slovenia) and to analyze their answers to a
CRediT authorship contribution statement
Lucia Rotaris: Conceptualization, Methodology, Investigation, Supervision, Project administration, Software, Writing - review & editing. Marco Giansoldati: Data curation, Software, Writing - original draft, Writing - review & editing. Mariangela Scorrano: Formal analysis, Software, Writing - original draft, Writing - review & editing.
Acknowledgments
We thank Mikołaj Czajkowski, Head of the Chair of Microeconomics at the University of Warsaw, for his kind and patient support in the application of the MATLAB code he implemented for the estimation of HCMs, and Andrea Parma for his excellent technical assistance.
Financial assistance by the MUSE INTERREG V-A Programme Italy-Slovenia 2014-2010, CCI number 2014TC16RFCB036, is acknowledged.
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