E-Bodas are reshaping Kenya's transport labor market

Can electric vehicles transform ‘gig work’ in emerging markets? The World Bank studied a Kenyan startup's bold experiment to find out. Our research, Electric Vehicle and Labor Market Transformation, reveals surprising insights and important considerations or policymakers, investors, and development partners working to develop the informal transport labor market.

The Boda Boda (motorcycle taxi) industry is fraught with multiple challenges—safety risks, lack of regulations, and poor working conditions.  Yet in the absence of a reliable public transport system, two million bodas have rushed to fill the urban mobility vacuum in Kenya. Given the industry's scale, there have been growing efforts to reform it through innovative business models.

New business models that impact driver welfare

The research began with a straightforward question. Conventional wisdom suggests that improving driver welfare in the gig economy requires formalization of employment status and higher wages. What if technology—specifically electric vehicles—could unlock new business models that achieve these goals differently?

A Kenyan startup partnered with a major ride-hailing platform to pilot an innovative approach: combining gig-worker access to electric motorcycles (called e-bodas) with employment benefits. Initially, as part of the startup’s business model, drivers received monthly salaries, medical insurance, and housing allowances as "employees" when they met corporate targets. In late 2024, the model shifted. Drivers could work under a lease-to-own arrangement, meeting weekly trip and hour thresholds to qualify for daily e-motorcycle leasing fees and eventually leading to motorcycle ownership for the drivers.

Electric vehicles made this possible. Lower operating costs improved driver economics, while battery swapping stations enabled the company to conduct real-time tracking of usage and to ensure payment enforcement. Previously, these benefits and mechanisms weren’t possible with traditional motorcycles.

 The data reveals significant behavioral changes

While it was a limited, initial study, researchers conducted rigorous field research over an eight-week period, combining GPS telemetry, platform data, and extensive driver surveys. Using advanced causal inference methods, the analysis identified substantial driver behavior changes following the transition, driven in part by stronger earnings potential and clear incentives toward vehicle ownership on the part of the drivers:

• Productivity improved 37%, reflecting behavioral adjustments aimed at maximizing earnings per hour rather than merely extending work time.
• Energy efficiency doubled, consistent with drivers treating vehicles as assets rather than short-term rentals, leading to more cost-conscious driving behavior.
• Increased geographic dispersion and availability of the service, allowing drivers to take motorcycles home.

Location at Start of Day, Before and After Transition

However, removing earnings constraints also led to unintended negative behavioral changes.

* ATT: Average Treatment Effect on the Treated, CI: Confidence Interval

• Working hours increased 40% (3.5 additional hours daily), as drivers responded to higher  returns for labor and greater confidence that additional effort translated directly into earnings.

* ATT: Average Treatment Effect on the Treated, CI: Confidence Interval

• Distance traveled rose by 70km per day, as drivers remained active longer and accepted more trips to accelerate income accumulation.

* ATT: Average Treatment Effect on the Treated, CI: Confidence Interval

• Average speeds increased by 4.6 km/h, while supporting faster trip turnover and higher daily earnings, it poses a higher safety risk that needs to be managed.

Overall, drivers worked longer but more efficiently, as effort translated directly into earnings. The prospect of ownership promoted higher utilization and more cost-conscious behavior, leading to increased job satisfaction.

Implications for policy and practice

• Governments: The study results highlight that business model design matters just as much as formalization of employment. While policymakers traditionally focus on creating public entities to regulate informal transport, well-designed private models can also help to improve driver welfare and support the acceleration of EV adoption. However, potentially increased speeds and longer working hours require attention by regulators to ensure road safety and to protect labor. Additionally, charging infrastructure costs may function as an unintended “tax” on drivers and should be recognized and supported in policy design. The realities of infrastructure provisioning should not be considered merely as technical operating costs but as welfare-relevant factors requiring policy consideration and support, potentially through subsidies, regulation, or public provisioning.
• Private sector: Firm-level metrics may not account for the full picture. Earnings and trip volumes do not capture financial stress on the drivers, their autonomy, or long-term security, which translates to their commitments to a firm. Combining platform data with GPS telemetry and driver surveys reveals how business models truly affect and impact employee welfare. The prospect of motorcycle ownership, even under more strenuous conditions, emerged as a powerful driver of employee retention and satisfaction. This suggests that asset-building pathways, not just income maximization, should be central to business model design in the gig economy.
• Development partners: Traditional descriptive studies may not account for the full understanding of the impact of business model shifts and require more rigorous measurement frameworks. The methods demonstrated in this research could form the basis for future results-based financing approaches, helping development partners direct resources toward models that genuinely improve welfare.

Looking ahead

The success of e-mobility in informal transportation hinges upon more than conversion of vehicles and charging infrastructure. Business models must thoughtfully align incentives across firms, drivers, and policymakers. When designed well, EV-based approaches can unlock productivity gains and create new pathways to asset ownership for workers historically excluded from such opportunities.

“Regulatory frameworks should not only focus on registration and licensing but must also take into account the wider operational and economic environment within which riders operate.” - Sharon Biwott, Principal Officer-Department of Licensing, Directorate of Registration and Licensing of National Transport and Safety Authority (NTSA)

Yet these models also introduce new costs, risks, and regulatory challenges that require active management. As governments, private operators, and development partners expand their engagement in this space, a deeper understanding of how business models shape welfare and market outcomes is essential. Only then can the transition to electric mobility deliver benefits that are both inclusive and sustainable.

Read the full report