Abstract
The shift in the automotive landscape has led to inconsistent consumer behavior, challenging forecasting the market’s future. This work aims to develop a model utilizing system dynamics to predict how the market will behave and how the attractiveness of electrical, conventional, and hydrogen vehicles will fluctuate. Variables, such as fuel price per km, the average electric vehicle range, and the average hydrogen tank capacity, are considered in the model. Data were collected using various techniques such as experts’ opinions, surveys, governmental entities, and web scraping. This study employs a system dynamics (SD) model, which facilitates scenario analysis to explore complex, dynamic interactions and provides insights beyond what traditional methods like regression or time series can offer. The results revealed an anticipated rise in the annual percentage of electric vehicle purchases relative to conventional vehicles. (The CV share dropped from 56.4% to 31.5%, whereas the EV share increased from 43.4% to 68.5% in ten years from 2022.) This growth was brought on by higher gasoline costs, technology developments that enable faster charging, longer electric automobile ranges, and lower electric vehicle prices. However, there would be no significant increase in hydrogen fuel cell automobiles due to the lack of infrastructure and government support.
Original language | English |
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Number of pages | 26 |
Journal | Arabian Journal for Science and Engineering |
Early online date | 14 Feb 2025 |
DOIs | |
Publication status | E-pub ahead of print - 14 Feb 2025 |
Bibliographical note
Copyright © King Fahd University of Petroleum & Minerals 2025. This version of the article has been accepted for publication, after peer review and is subject to Springer Nature’s AM terms of use [ https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms ] but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/s13369-025-09984-0Keywords
- Automotive market prediction
- Consumer behavior
- Electric vehicles (EVs)
- Sustainable transportation
- System dynamics modeling