Nairobi motorcycle transit comparison dataset: Fuel vs. electric vehicle performance tracking (2023)

This dataset, titled "Nairobi Motorcycle Transit Comparison Dataset," was compiled to document a simulated transition of motorcycle taxis (boda bodas) in Nairobi, Kenya, from internal combustion engine (ICE) to electric motorcycles. The data collection spanned two distinct phases. The baseline phase, conducted from November 13-26, 2023, involved 120 ICE motorcycles. The transition phase, occurring from December 10-21, 2023, included 110 ICE motorcycles as a control group and 9 electric motorcycles as a treatment group. Data were gathered in Nairobi, a major urban center in East Africa, providing a geographically specific context for the data collection. Recognising the limited availability of data on such transitions in African cities, including historical insights from Kenyan urban transport systems [3,5,6], this dataset provides a unique resource for researchers and policymakers. The data collection process utilised multiple instruments and methods. Trip-level data were recorded using GPS tracking devices installed on each motorcycle, capturing location, speed, and distance at 10-second intervals. Financial data, such as revenue, maintenance costs, fuel costs (for ICE motorcycles), and electricity usage (for electric motorcycles), were collected via daily phone-based surveys administered to riders. Energy consumption for the electric motorcycles was measured using wall-plug meters connected to each battery charger. These methods ensured comprehensive tracking of both operational and economic metrics across the two motorcycle types. The dataset is organised into two primary directories: trip_data and daily_data. The trip_data directory contains CSV files with detailed trip-level metrics, including start and end times, distances travelled, and average speeds. The daily_data directory provides aggregated daily summaries in CSV format, encompassing total distance, revenue, and costs. To safeguard rider privacy, location data for the first and last trips of each day are excluded. The dataset is hosted on Mendeley, with a publicly accessible URL provided below, ensuring availability for researchers, editors, and reviewers. This dataset holds substantial reuse potential for various research domains. It offers a valuable resource for investigating urban mobility patterns, the adoption of e-mobility in developing cities, energy demand forecasting, and transportation economics. Researchers can leverage the data to explore operational differences between ICE and electric motorcycles, evaluate economic impacts on riders, or model energy consumption trends.