Efficiency Analysis of Last Mile Delivery Station

Abstract

∗A large increase in e-commerce business has an impact on supporting industries, one of which is the logistics industry. The quality in logistics services needs to be improved in line with the increasing demand from the market. Improvements in service quality and performance need efforts from all parts of the business process, one of which is the last mile delivery stage, which is the delivery of goods from retail locations to customers. Delivery speed and accuracy are important factors for measuring the performance of the process in the last mile. The performance of the process can be seen by measuring the relative efficiency of the last mile station using the Data Envelopment Analysis (DEA) method which is able to evaluate the relative efficiency level of a DMU (Decision Making Unit), in this case the DMU analyzed is 137 last mile stations in the DKI Jakarta and West Java. The input variables to measure efficiency are the number of couriers, the number of parcels that must be sent, and the cost to pay employees, while the output variables are in terms of delivery speed and customer satisfaction. Of the 139 stations, there are 51 stations (37%) that are relatively efficient (above 95% efficiency), and 88 stations (63%) that are not yet efficient. Station with low efficiency needs to improve its performance based on the benchmark value of each variable in the DEA analysis. CCS CONCEPTS • Mathematics of computing • Probability and statistics • Nonparametric