Havran, O. orcid.org/0009-0003-6367-1848, Watling, D. orcid.org/0000-0002-6193-9121, Chen, H. orcid.org/0000-0003-0753-7735 et al. (4 more authors) (2025) Electrifying urban mobility: Unveiling expert insights on electric quadricycles through topic modelling and sentiment analysis. Sustainable Futures, 10. 101540. ISSN: 2666-1888
Abstract
Electric quadricycles offer significant potential for enhancing sustainable urban mobility due to their compact design and efficiency. To effectively shape this sustainable future, it is vital to understand the associated trends and challenges. Accordingly, this study analysed expert reviews of 13 heavy and light electric quadricycles by implementing an advanced topic modelling approach to identify dominant themes and examined sentiment polarity across reviews using artificial intelligence. The study revealed eight key topics: design and technology, driving experience, urban mobility and acceptance, performance, battery and efficiency, pricing options, market and production, and classification and regulations. Additionally, the assessment quantified experts' positive and negative perceptions of specific elements within these topics. The findings indicate that (1) the majority of discussions focused on design and technology, (2) experts frequently appreciated spacious interiors, innovative swappable battery solutions, and agile and playful driving characteristics, (3) negative sentiments primarily pertained to safety, comfort, purchase price, and build quality, and (4) overall, experts held optimistic views regarding the role of electric quadricycles in urban mobility. These insights support a data-driven and user-centred approach to electric quadricycle design, assisting manufacturers and policymakers in advocating for electric quadricycles as practical solutions for sustainable urban mobility of the future.
Metadata
| Item Type: | Article |
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| Authors/Creators: |
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| Copyright, Publisher and Additional Information: | © 2025 Published by Elsevier Ltd. This is an open access article under the terms of the Creative Commons Attribution License (CC-BY-NC-ND 4.0). |
| Keywords: | Urban mobility, Artificial intelligence, Electric quadricycles, Topic modelling, Sentiment Analysis |
| Dates: |
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| Institution: | The University of Leeds |
| Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) |
| Date Deposited: | 26 Nov 2025 09:37 |
| Last Modified: | 26 Nov 2025 09:37 |
| Status: | Published |
| Publisher: | Elsevier |
| Identification Number: | 10.1016/j.sftr.2025.101540 |
| Related URLs: | |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:234870 |

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