Predictive analysis of electric vehicle prices across various car brands in Germany
Diverse factors influencing electric vehicle (EV) pricing pose significant challenges for manufacturers, consumers, and policymakers. Hence, manufacturers need help to develop competitive pricing strategies, promote market growth, and consumer confidence. Bridging this knowledge gap is essential for...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English English |
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Springer Science and Business Media B.V.
2025
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| Online Access: | http://umpir.ump.edu.my/id/eprint/43826/ http://umpir.ump.edu.my/id/eprint/43826/1/Predictive%20analysis%20of%20electric%20vehicle%20prices.pdf http://umpir.ump.edu.my/id/eprint/43826/2/Predictive%20analysis%20of%20electric%20vehicle%20prices%20across%20various%20car%20brands%20in%20Germany_ABS.pdf |
| _version_ | 1848826968281186304 |
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| author | Lee, Zhi Lin Nur Haizum, Abd Rahman Chong, Jim |
| author_facet | Lee, Zhi Lin Nur Haizum, Abd Rahman Chong, Jim |
| author_sort | Lee, Zhi Lin |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | Diverse factors influencing electric vehicle (EV) pricing pose significant challenges for manufacturers, consumers, and policymakers. Hence, manufacturers need help to develop competitive pricing strategies, promote market growth, and consumer confidence. Bridging this knowledge gap is essential for fostering a more transparent and effective EV market, necessitating comprehensive research to identify pricing influencers and provide actionable insights for stakeholders. This project utilizes a data science methodology to investigate factors influencing EV prices, predict new EV prices using machine learning techniques, linear regression, and support vector regression (SVR), and assess prediction accuracy through magnitude error. Data for analysis are sourced from Germany, Cheapest Electric Cars 2023 dataset. The results show significant correlations between EV prices and technological features; TopSpeed and Useable batteries show a positive correlation of 0.78 with prices in Germany, indicating that improvements in these features drive up EV costs. In prediction, linear regression is much more reliable than SVR in predicting EV prices. These findings are expected to give stakeholders actionable insights to comprehend market dynamics and enhance pricing strategies within the EV industry. |
| first_indexed | 2025-11-15T03:53:15Z |
| format | Article |
| id | ump-43826 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-15T03:53:15Z |
| publishDate | 2025 |
| publisher | Springer Science and Business Media B.V. |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-438262025-03-03T01:54:15Z http://umpir.ump.edu.my/id/eprint/43826/ Predictive analysis of electric vehicle prices across various car brands in Germany Lee, Zhi Lin Nur Haizum, Abd Rahman Chong, Jim Q Science (General) QA Mathematics Diverse factors influencing electric vehicle (EV) pricing pose significant challenges for manufacturers, consumers, and policymakers. Hence, manufacturers need help to develop competitive pricing strategies, promote market growth, and consumer confidence. Bridging this knowledge gap is essential for fostering a more transparent and effective EV market, necessitating comprehensive research to identify pricing influencers and provide actionable insights for stakeholders. This project utilizes a data science methodology to investigate factors influencing EV prices, predict new EV prices using machine learning techniques, linear regression, and support vector regression (SVR), and assess prediction accuracy through magnitude error. Data for analysis are sourced from Germany, Cheapest Electric Cars 2023 dataset. The results show significant correlations between EV prices and technological features; TopSpeed and Useable batteries show a positive correlation of 0.78 with prices in Germany, indicating that improvements in these features drive up EV costs. In prediction, linear regression is much more reliable than SVR in predicting EV prices. These findings are expected to give stakeholders actionable insights to comprehend market dynamics and enhance pricing strategies within the EV industry. Springer Science and Business Media B.V. 2025 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/43826/1/Predictive%20analysis%20of%20electric%20vehicle%20prices.pdf pdf en http://umpir.ump.edu.my/id/eprint/43826/2/Predictive%20analysis%20of%20electric%20vehicle%20prices%20across%20various%20car%20brands%20in%20Germany_ABS.pdf Lee, Zhi Lin and Nur Haizum, Abd Rahman and Chong, Jim (2025) Predictive analysis of electric vehicle prices across various car brands in Germany. Quality and Quantity. pp. 1-15. ISSN 0033-5177. (Published) https://doi.org/10.1007/s11135-025-02055-4 https://doi.org/10.1007/s11135-025-02055-4 |
| spellingShingle | Q Science (General) QA Mathematics Lee, Zhi Lin Nur Haizum, Abd Rahman Chong, Jim Predictive analysis of electric vehicle prices across various car brands in Germany |
| title | Predictive analysis of electric vehicle prices across various car brands in Germany |
| title_full | Predictive analysis of electric vehicle prices across various car brands in Germany |
| title_fullStr | Predictive analysis of electric vehicle prices across various car brands in Germany |
| title_full_unstemmed | Predictive analysis of electric vehicle prices across various car brands in Germany |
| title_short | Predictive analysis of electric vehicle prices across various car brands in Germany |
| title_sort | predictive analysis of electric vehicle prices across various car brands in germany |
| topic | Q Science (General) QA Mathematics |
| url | http://umpir.ump.edu.my/id/eprint/43826/ http://umpir.ump.edu.my/id/eprint/43826/ http://umpir.ump.edu.my/id/eprint/43826/ http://umpir.ump.edu.my/id/eprint/43826/1/Predictive%20analysis%20of%20electric%20vehicle%20prices.pdf http://umpir.ump.edu.my/id/eprint/43826/2/Predictive%20analysis%20of%20electric%20vehicle%20prices%20across%20various%20car%20brands%20in%20Germany_ABS.pdf |