An Adaptive Decision Support System for Last Mile Logistics in E-Commerce

Abstract

Last mile logistics represent one of the most important challenging issues in online grocery shopping. Online customers are expecting high logistical services, demanding convenience, high reliable and on-time delivery services. As such, online retailers have to respond to these expectations by providing convenient logistical services while keeping this process cost efficient as much as possible. This research aims to design an e-commerce logistical decision support system for online grocery shopping in Jordan as a case study from the developing countries. Online grocery retailers are supposed to use this model in order to select the most suitable delivery operating system in the future. To implement and evaluate this model, one of the available routing and scheduling online solutions (i.e. “My Route Online”) is used to identify, analyse, and compare the cost efficiencies of the available alternative delivery solutions. The system is tested using real data over three different delivery alternatives (i.e. home delivery, delivery point and pickup point) in order to evaluate and compare their cost efficiencies. The findings from the experiments show that there are significant differences amongst the three delivery alternatives on the basis of three KPIs: cost, distance and time. The findings also indicate that the time indicator has more powerful change effect on cost than distance for all delivery alternatives. According to the level of investments online grocery retailers are willing to offer, customer preferences, and the experimental results, it is concluded that pickup point solution is the best logistical strategy for online grocery retailers to start with.