Evaluation of Efficiency in Logistics Company: An Analysis of Last-Mile Delivery

Isti Surjandari, Rahajeng Rindrasari, Arian Dhini

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


Major developments in the e-commerce business have an impact on supporting industries, such as the logistics industry. Logistics service providers for e-commerce consumers must focus on the quality of their services. Service quality is determined by meeting customer expectations, including on-time delivery, parcel security, and customer service. In the process of sending parcels, one thing that affects the timeliness of delivery is the last-mile delivery stage. Due to a large number of last-mile stations and the geographic dispersion of their locations throughout Indonesia, the service quality between stations becomes inhomogeneous. The performance of the last-mile station can be measured by comparing the relative efficiency between stations. In this study, the initial stage of the efficiency analysis of the last-mile delivery station is by conducting a cluster analysis that divides the station into two groups, namely the Leader and Majority clusters, which aim to group homogeneous DMUs. Efficiency analysis with DEA is given for each cluster. The result shows that 94 of the 133 stations are relatively efficient for the Leader cluster stations, and 136 of the 466 stations are relatively efficient for the Majority cluster stations. A decision tree method is used for classification modeling to determine the characteristics of a relatively efficient station. Total daily delivery becomes the initial variable that determines the station to enter the Leader or Majority cluster. The second criterion is the variable number and quantity of goods delivered on time.

Original languageEnglish
Pages (from-to)649-657
Number of pages9
Issue number2
Publication statusPublished - Jun 2023


  • cluster analysis
  • data envelopment analysis
  • decision tree
  • last-mile delivery


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