Determinants of Electric Cars Purchase Intention in Poland: Personal Attitudes v. Economic Arguments

• Published in: Energies (Basel) 2022-05, Vol.15 (9), p.3078
• Main Authors: Sobiech-Grabka, Katarzyna, Stankowska, Anna, Jerzak, Krzysztof
• Format: Article
• Language: English
• Subjects: Automobile industry; Carbon; Cities; consumer decision making; consumers preferences; Cost control; COVID-19; Decision making; e-mobility; Electric vehicles; electric vehicles market and policy; Emissions; Energy consumption; Fossil fuels; Fuel cells; Learning algorithms; Literature reviews; Machine learning; Mobility; Pollutants; Pollution; Public transportation; purchase intention
• ISSN: 1996-1073; 1996-1073
• DOI: 10.3390/en15093078

Urban e-mobility, seen as a part of complex and multidimensional European Green Deal plan, is essential for cities. However, it cannot be implemented without a common social commitment accompanied by a shared, strong belief in its advantages. Even if urban authorities and central governments would encourage their citizens to buy or share an electric vehicle (EV), the shift to EV will not be significant without people convinced that the idea of becoming zero-emission is economically viable and rational to them privately. This is especially true and important in countries like Poland—which is classified as an “EV readiness straggler”. The main purpose of this study is to develop a robust forecasting model with the aid of advanced machine learning methods. Based on the survey conducted, we identified factors useful for predicting consumer behaviour in terms of willingness to purchase an EV. The proposed machine-learning tool (specifically, the Random Forest algorithm) will allow automotive companies to more effectively target factors supporting the promulgation of urban individual e-mobility.