Dataset for a Big Data–Driven Green Logistics Model to Improve Last-Mile Delivery Efficiency and Reduce Fossil Fuel Use

This dataset contains empirical data used to validate a Big Data–driven Green Logistics model focused on improving last-mile delivery efficiency and reducing fossil fuel consumption. The data were collected from a light-logistics company operating in three cities in Peru and include historical delivery records, delivery attempt outcomes, routing information, fuel consumption data, and performance indicators. The dataset supports the calculation of key logistics metrics such as delivery efficiency, average delivery time, number of delivery attempts, fuel consumption efficiency, and the Green Logistics Efficiency Index (GLEI). These data enable the replication of the results reported in the associated research article and provide a basis for comparative analysis of sustainable last-mile logistics strategies in similar operational contexts.