Ghana’s EV Shift Hinges on Drivers’ Minds, Not Just Their Wallets

Ghana’s urban transport system runs on imported fuel, and that dependency is now at the center of a national debate about energy and climate. According to figures cited in a new study, roughly 70 percent of Ghana’s transport fuel is imported, while transport is reported to contribute about 45 percent of the country’s carbon dioxide emissions. Electric vehicles have been proposed as one route out of this bind, promising progress toward Sustainable Development Goal 7 on affordable and clean energy and Goal 13 on climate action. Yet a fundamental question has gone unanswered for one of the most important groups in the equation: what actually makes the commercial drivers and vehicle owners who keep Ghana’s cities moving willing to switch to electric?

That question is what motivated researchers Ebenezer Arthur Duncan of the University of Professional Studies in Accra and Samuel Affran of the University of Education Winneba to survey 800 commercial drivers and private car owners across four of Ghana’s busiest urban corridors: Accra, Tema, Kumasi, and Takoradi. Their study, published in Frontiers in Sustainable Energy Policy, applied Social Cognitive Theory, a framework developed by psychologist Albert Bandura that holds that behavior emerges from the interplay of personal factors, environmental conditions, and behavior itself. In this setup, tax incentives such as import duty exemptions and VAT waivers on electric vehicles were treated as environmental factors, while environmental awareness, meaning knowledge and concern about the ecological consequences of transport choices, was treated as a personal factor.

The technical machinery behind the analysis was partial least squares structural equation modeling, or PLS-SEM, a statistical technique well suited to behavioral research with non-normal data and complex models. The team recruited participants through established transport union hubs, including the Ghana Private Road Transport Union and PROTOA, using a multi-stage purposive-convenience sampling approach. Quotas were set by city to reflect relative commercial activity: 280 participants from Accra, 160 from Tema, 200 from Kumasi, and 160 from Takoradi, split evenly between 400 commercial drivers and 400 vehicle owners. A power analysis indicated a minimum sample of 647 for detecting small effects, so the obtained 800 comfortably exceeded that threshold. Questionnaires were administered face-to-face between January and March 2025, with 899 distributed and 800 valid responses, yielding an 89 percent response rate.

The instrument contained 25 reflective items on five-point Likert scales, adapted from established scales for tax incentives, environmental awareness, adoption intention, sustainable energy consumption, and perceived greenhouse gas emissions. Illustrative items included statements such as government tax exemptions reduce the cost of owning an electric vehicle, human activities are causing serious damage to the environment, and transport activities contribute to greenhouse gas emissions. The instrument was contextualized to Ghana’s transport setting, reviewed by two transport scholars and two sustainability scholars, and piloted with 40 drivers and owners in December 2024 before the main survey. Reliability and validity checks were rigorous: indicator loadings ranged from 0.730 to 0.883, Cronbach’s alpha values spanned 0.843 to 0.902, and average variance extracted exceeded 0.5 for all constructs. Heterotrait-monotrait ratios, all below the conservative 0.85 threshold, confirmed that the constructs were statistically distinct.

The headline result is that both tax incentives and environmental awareness were positively associated with stronger intentions to adopt electric vehicles. Drivers who reported higher perceived tax benefits also reported more sustainable energy consumption practices, such as reducing vehicle idling to save energy. But the most striking finding concerns perceived greenhouse gas emissions. Contrary to what the researchers hypothesized, both tax incentives and environmental awareness were positively associated with higher perceived emissions, not lower. The perceived emissions construct captured beliefs about emissions rather than metered data, so the pattern cannot be interpreted as evidence that incentives or awareness actually increase emissions. Instead, the authors point to a perception-based rebound effect, in which perceived cost reduction from incentives is associated with higher perceived driving intensity, and to an awareness-action gap, in which heightened concern is linked to higher perceived emissions when alternatives remain limited.

Environmental awareness emerged as the stronger predictor overall. Its effect on adoption intention was medium in size, with a beta of 0.470 and an effect size of 0.207, while tax incentives had a smaller effect, with a beta of 0.210 and an effect size of 0.040. Tax incentives and environmental awareness jointly explained 38.7 percent of the variance in adoption intention, 30.1 percent of the variance in sustainable energy consumption, and 46.1 percent of the variance in perceived greenhouse gas emissions. Predictive relevance, assessed through Q-squared values, was confirmed for all three outcomes. Model fit was marginally acceptable, with a standardized root mean square residual of 0.079 and a normed fit index of 0.857, and 60 to 70 percent of the variance in outcomes remained unexplained, a reminder that infrastructure, grid carbon intensity, and other unmeasured factors matter enormously.

The moderation results add a layer of nuance that could reshape how policymakers sequence interventions. Environmental awareness strengthened the link between tax incentives and adoption intention: the effect of incentives on adoption rose from a beta of 0.158 at low awareness to 0.262 at high awareness, supporting the idea that awareness amplifies the pull of fiscal measures. But awareness dampened the links between incentives and both sustainable energy consumption and perceived emissions. In other words, drivers with high environmental awareness relied less on incentives to conserve energy, suggesting that awareness campaigns may reduce dependence on fiscal measures for conservation behavior. The moderation effects themselves were very small to small in magnitude, so the authors caution against overstating their practical importance.

The demographic profile of the sample reveals who Ghana’s commercial vehicle sector actually is: predominantly male at 90 percent, middle-aged, with moderate education and income levels. Other commercial vehicles constituted the majority at 56.25 percent, followed by taxis at 18.75 percent, buses at 15 percent, and trucks at 10 percent. Driving tenure varied widely, with 30 percent of respondents having more than 15 years of experience. This profile matters because it suggests that any transition strategy must account for a workforce that is experienced, unionized, and operating within tight economic margins, where fuel costs and vehicle prices are salient daily concerns rather than abstract policy variables.

The authors are careful to draw boundaries around what their findings can and cannot support. The cross-sectional design precludes causal inference, and the language throughout is associational rather than explanatory. The purposive-convenience sampling at union hubs is a non-probability method, so the findings are analytically transferable to similar urban contexts with nascent electric vehicle markets, fuel import dependence, limited charging infrastructure, and unionized transport operations, but they cannot be statistically generalized to all of Ghana or to rural areas. Self-efficacy and observational learning, core concepts in Social Cognitive Theory, were treated as background rather than directly measured, which limits claims to an SCT-informed examination rather than a full test of the theory. The study also did not test whether adoption intention actually leads to lower emissions or higher sustainable consumption, leaving mediation for future research with longitudinal and metered data.

For Ghana’s policymakers, the study suggests a sequenced approach rather than a single lever. Union-based awareness programs in the four cities could be evaluated before scaling fiscal incentives, and linking incentives to usage data for commercial fleets could help verify whether intentions translate into actual behavior. Directing electric vehicle-related tax revenue toward solar charging infrastructure at union hubs is proposed for further evaluation. The authors also suggest monitoring for perception-based rebound, with the recognition that the data cannot support claims about actual emissions. What emerges is a picture of a transition that depends as much on drivers’ minds as on their wallets, where awareness and incentives interact in complex ways, and where the gap between intending to go electric and actually cutting emissions remains a challenge that only metered data and grid reform can close.

Subject of Research: Electric vehicle adoption intentions among commercial drivers and vehicle owners in Ghana's urban transport corridors

Article Title: Accelerating Ghana’s sustainable transport transition: the role of electric vehicles in achieving SDG 7 and SDG 13

Article References: Duncan, E. A., & Affran, S. (2026). Accelerating Ghana’s sustainable transport transition: the role of electric vehicles in achieving SDG 7 and SDG 13. Frontiers in Sustainable Energy Policy, 5, Article 1930955. https://doi.org/10.3389/fsuep.2026.1930955

Image Credits: AI Generated

DOI: 10.3389/fsuep.2026.1930955

Keywords: electric vehicles, Ghana, SDG 7, SDG 13, tax incentives, environmental awareness, sustainable energy consumption, greenhouse gas emissions, Social Cognitive Theory, PLS-SEM, commercial drivers, transport policy