| Issue |
E3S Web of Conf.
Volume 465, 2023
8th International Conference on Industrial, Mechanical, Electrical and Chemical Engineering (ICIMECE 2023)
|
|
|---|---|---|
| Article Number | 02035 | |
| Number of page(s) | 5 | |
| Section | Symposium on Electrical, Information Technology, and Industrial Engineering | |
| DOI | https://doi.org/10.1051/e3sconf/202346502035 | |
| Published online | 18 December 2023 | |
Factors Influencing Electric Motorcycle Adoption: A Logit Model Analysis
1 Universitas Sebelas Maret, Industrial Engineering Department, Faculty of Engineering, Surakarta, Indonesia
2 Constructor University, School of Business, Social & Decision Sciences, Bremen, Germany
* Corresponding author: yuniaristanto@ft.uns.ac.id
This research investigates the factors influencing the adoption of electric motorcycles in Indonesia. The background of the study lies in the growing interest in sustainable transportation and the potential of electric motorcycles as an eco-friendly alternative. The objective is to understand the impact of travel behavior and knowledge levels on the choice of motorcycles. The research utilizes a logit model to analyze the relationship between independent variables (knowledge levels and travel behavior) and the dependent variable (choice of motorcycles). The findings reveal that travel behavior, such as the usual commute mode and the number of weekend trips for hybrid electric motorcycles, significantly influence adoption. Additionally, knowledge factors like maintenance and charging costs play an essential role. These findings contribute to a better understanding of the decision-making process behind adopting electric motorcycles and provide insights for policymakers and manufacturers to promote the adoption of electric motorcycles in Indonesia.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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