The study of new energy vehicle choice in China from the perspective of complex neural network
China has become the world’s largest market for the production and sales of new energy vehicles. In the Internet era, online review data is becoming more and more important, and it is a great challenge for new energy vehicle manufacturers and consumers to quickly obtain and find out the effective in...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-09-01
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| Series: | Frontiers in Physics |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fphy.2022.1015103/full |
| _version_ | 1798001673737601024 |
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| author | Hui Liu Hui Liu Lei Feng Lei Feng |
| author_facet | Hui Liu Hui Liu Lei Feng Lei Feng |
| author_sort | Hui Liu |
| collection | DOAJ |
| description | China has become the world’s largest market for the production and sales of new energy vehicles. In the Internet era, online review data is becoming more and more important, and it is a great challenge for new energy vehicle manufacturers and consumers to quickly obtain and find out the effective information in the review data. In view of the above understanding, this study uses the Bert-wwm-ext model structure, data mining, and deep learning to study the new energy vehicle selection, and also analyzes the positioning of domestic and foreign new energy vehicle brands and their brand development from the perspective of complex networks. The research results found that: 1) Consumers pay more and more attention to the quality of new energy vehicles. 2) The comparative analysis of BEV and PHEV reveals that consumers’ evaluation of both types of vehicles is roughly comparable, but the difference in satisfaction with the endurance of both types of vehicles is very obvious. 3) Most of the brands of new energy vehicles are concentrated in the price range of RMB80,000 to RMB350,000, and within this range, consumers’ evaluation is positively correlated with the price of the vehicle. Among the new energy vehicle brands over RMB350,000, consumer evaluation does not rise with the price of the vehicle. 4) The head effect of Chinese brands is significant, Foreign brands have formed strong brands with high brand premiums. |
| first_indexed | 2024-04-11T11:40:13Z |
| format | Article |
| id | doaj.art-7e9a943be4df469fa7677f48912b0633 |
| institution | Directory Open Access Journal |
| issn | 2296-424X |
| language | English |
| last_indexed | 2024-04-11T11:40:13Z |
| publishDate | 2022-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Physics |
| spelling | doaj.art-7e9a943be4df469fa7677f48912b06332022-12-22T04:25:51ZengFrontiers Media S.A.Frontiers in Physics2296-424X2022-09-011010.3389/fphy.2022.10151031015103The study of new energy vehicle choice in China from the perspective of complex neural networkHui Liu0Hui Liu1Lei Feng2Lei Feng3Faculty of Applied Economics, University of Chinese Academy of Social Sciences, Beijing, ChinaCenter for Brand Leadership, University of Chinese Academy of Social Sciences, Beijing, ChinaCenter for Brand Leadership, University of Chinese Academy of Social Sciences, Beijing, ChinaFaculty of Economics, University of Chinese Academy of Social Sciences, Beijing, ChinaChina has become the world’s largest market for the production and sales of new energy vehicles. In the Internet era, online review data is becoming more and more important, and it is a great challenge for new energy vehicle manufacturers and consumers to quickly obtain and find out the effective information in the review data. In view of the above understanding, this study uses the Bert-wwm-ext model structure, data mining, and deep learning to study the new energy vehicle selection, and also analyzes the positioning of domestic and foreign new energy vehicle brands and their brand development from the perspective of complex networks. The research results found that: 1) Consumers pay more and more attention to the quality of new energy vehicles. 2) The comparative analysis of BEV and PHEV reveals that consumers’ evaluation of both types of vehicles is roughly comparable, but the difference in satisfaction with the endurance of both types of vehicles is very obvious. 3) Most of the brands of new energy vehicles are concentrated in the price range of RMB80,000 to RMB350,000, and within this range, consumers’ evaluation is positively correlated with the price of the vehicle. Among the new energy vehicle brands over RMB350,000, consumer evaluation does not rise with the price of the vehicle. 4) The head effect of Chinese brands is significant, Foreign brands have formed strong brands with high brand premiums.https://www.frontiersin.org/articles/10.3389/fphy.2022.1015103/fullcomplex networksnew energy vehiclesdata miningdeep learningnatural language processing |
| spellingShingle | Hui Liu Hui Liu Lei Feng Lei Feng The study of new energy vehicle choice in China from the perspective of complex neural network Frontiers in Physics complex networks new energy vehicles data mining deep learning natural language processing |
| title | The study of new energy vehicle choice in China from the perspective of complex neural network |
| title_full | The study of new energy vehicle choice in China from the perspective of complex neural network |
| title_fullStr | The study of new energy vehicle choice in China from the perspective of complex neural network |
| title_full_unstemmed | The study of new energy vehicle choice in China from the perspective of complex neural network |
| title_short | The study of new energy vehicle choice in China from the perspective of complex neural network |
| title_sort | study of new energy vehicle choice in china from the perspective of complex neural network |
| topic | complex networks new energy vehicles data mining deep learning natural language processing |
| url | https://www.frontiersin.org/articles/10.3389/fphy.2022.1015103/full |
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