The escalating complexity of B2C e-commerce logistics, particularly in the critical area of last-mile delivery, along with the prevalent consumer preference for home delivery, highlights a major challenge: the need to reduce incidents during the delivery process. These incidents not only reduce the perceived quality of service but also increase distribution costs and emissions. This paper presents a novel initiative to address the challenge of delivery failures by allowing users to generate and send location statistics to the delivery company, contingent upon their explicit consent. In this way, users can define a list of preferred personal locations for tracking, ensuring enhanced coordination between customers and delivery companies. Through this collaborative approach, users have agency over their data, contributing to a more efficient and customer-centric e-commerce logistics ecosystem while mitigating incidents, reducing costs, and minimizing environmental impact.

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Characterizing E-Commerce Users to Improve Last-Mile Parcel Delivery: A Mobile App-Based Approach

  • Juan-Carlos Cortés-Muñoz,
  • Alicia Robles-Velasco,
  • Luis Onieva,
  • Alejandro Escudero-Santana

摘要

The escalating complexity of B2C e-commerce logistics, particularly in the critical area of last-mile delivery, along with the prevalent consumer preference for home delivery, highlights a major challenge: the need to reduce incidents during the delivery process. These incidents not only reduce the perceived quality of service but also increase distribution costs and emissions. This paper presents a novel initiative to address the challenge of delivery failures by allowing users to generate and send location statistics to the delivery company, contingent upon their explicit consent. In this way, users can define a list of preferred personal locations for tracking, ensuring enhanced coordination between customers and delivery companies. Through this collaborative approach, users have agency over their data, contributing to a more efficient and customer-centric e-commerce logistics ecosystem while mitigating incidents, reducing costs, and minimizing environmental impact.