Unleashing the Factors Inducing the Adoption of Electric Vehicles (EVs) in Bangladesh: A PLS-SEM Approach
Year: 2025
Type: article
Study design: Observational Study
Abstract: Global Electric Vehicle (EV) market growth has garnered attention as an avenue to curb the discharge of greenhouse gases and confront the effects of climate change. Policymakers, industry stakeholders and researchers must comprehend the factors influencing EV adoption. This study investigates the components affecting the introduction of electric vehicles in Bangladesh due to its prominence. The study examines how affordability, insufficient infrastructure and after-sales service affect electric vehicle initiation in Bangladesh through a comprehensive survey of a diverse group. These factors significantly influence EV adoption trends in Bangladesh and the study employs descriptive and inferential statistics to assess their impact. Valid data were analyzed using SmartPLS 4. The study reveals that affordability and infrastructure act as impediments to Bangladesh's adoption of electric vehicles, underscoring the pivotal role of cost in consumer decision-making. To boost EV adoption in the country, there's a need for financial incentives and reduced upfront costs for EVs. Conversely, the study indicates that after-sales service does not significantly affect electric vehicle adoption in Bangladesh. Given these results, policymakers and industry stakeholders should prioritize affordability to accelerate EV adoption and enhance infrastructure and after-sales services to improve the EV ownership experience. These insights can aid policymakers and stakeholders in promoting sustainable transportation and EV adoption in Bangladesh, ultimately contributing to climate change mitigation and global air quality improvement. Additionally, the conclusions derived can serve as a foundation for further investigation, exploring socio-economic, political and macroeconomic variables in greater depth.
Authors: S M Masudur Rahman, Sadman Kabir, Md Johir Rayhan, Abu Naser Mohammad Saif, Nayan Miah, Abdullah Al Mamun
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4408948429