This study seeks to assess the Croatia WhatsApp Number List of adoption of electric and hybrid cars by potential buyers based on the variables that impact this decision and the size of said impact. The literature, which previously dealt with this subject, shows that classic variables such as price and financial profits play an important role at the time of decision-making. The literature also shows that the attitude towards the adoption of this type of vehicle can vary from one person to another depending on their predispositions relating to the environment and reputation. The study was carried out in Spain and the data was obtained via a questionnaire from a sample selected using a non-probability sampling method. More details on the publication.

To carry out the analysis and therefore verify the conclusions of other investigations, this study used a behavior model made up of the variables below: Reliability: a priori one of the big criticisms of electric and autonomous cars when confronted with internal combustion cars. In this paper , reliability is explained by 3 variables Charging time, a big difference between internal combustion cars and electric and hybrid cars (5 minutes to fill the tank against 15 minutes to 8 hours depending on the battery – Hidrue et al., 2011) Available infrastructure, i.e. the number of charging stations to use them (often reported as insufficient in various studies).

Analysis methodology

Prices of electric and hybrid cars: often judged to be higher than their internal combustion equivalent Financial aid / benefits such as subsidies, tax reduction or even the price of electricity Level of concern for the environment: environmental protection would help develop a positive attitude towards cars although this remains a subject of debate in the literature in terms of the magnitude of its impact A structural equation model (SEM) in order to determine the statistical significance of the impacts of the model variables (therefore test the hypotheses) despite the lack of non-linearity analysis of the SEM. The artificial neural network (ANN) model which allows them to more robustly estimate the influence


The results of the study prove that range, charging time and infrastructure significantly (statistically) affect the perceived reliability of electric and hybrid cars. Reach is the aspect that most affects the perception of reliability of potential buyers. The study also shows that reliability and financial benefits are the main sources of consumer concern since an increase in perceived reliability or profits, ceteris paribus , has the most important impact on attitude towards cars. electric and hybrid. The less determining factors but still significant are social reputation and environmental concern. The attitude of consumers is more strongly encouraged by the economic and useful character of vehicles than by an environmental or social interest.

Study results 

With this model, the authors wanted to focus on the true magnitude of the impacts of the model variables and not really their significance (objective of the SEM model). This model generally consists of a layer of neurons with statistically significant parameters ( input layer ), a layer of as many neurons as dependent variables ( output layer ) and several hidden layers of neurons. Two models are studied, model A to study reliability and model B to study attitude towards electric and hybrid cars. Each model contains a single hidden layer to take into account possible continuous functions. Thanks to simulation software, model A contains 2 neurons in its hidden layer and model B contains 3 neurons.

The ANN model is, as mentioned before, capable of measuring the magnitudes of impacts more precisely than the SEM model. With the ANN the models are able to explain around 91% of the variance of model A (against 30% of the SEM model) as well as around 94% of the variance of model B (against 70% of the SEM model) . This means that the magnitude of the parameter effects found via the ANN is more robust than the SEM model. Researchers have again found that range, recharge time, and number of charging stations have a negative effect on perceived reliability. Now, in this case, the range and recharge time many charging stations contribute almost equally to the perceived reliability.

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