Authors:
Iñaki Cejudo
;
Laura Rabadán
;
Eider Irigoyen
and
Harbil Arregui
Affiliation:
Intelligent Systems for Mobility and Logistics, Vicomtech Foundation, Basque Research and Technology Alliance (BRTA), Mikeletegi 57, Donostia, Spain
Keyword(s):
Depot Clustering, Delivery Logistics, Socio-Economic Indicators, Urban Network, Decision Support Systems.
Abstract:
People’s lifestyles have evolved in recent years, making home deliveries a necessity for various types of services. Moreover, with the growth of big data and Artificial Intelligence, predicting the performance and customer demand of new businesses is a key aspect of logistics and last-mile delivery planning. By using examples and predictions as a foundation for goods delivery services, initial over-sizing costs can be signifi-cantly reduced. In this paper, we analyze and compare operational zone similarities for food and parcel delivery services in Spain, considering socio-economic indicators and urban network features. The study leverages motorbike delivery metrics to complement the analysis. The results demonstrate how similar depots can be clustered, providing a foundational performance scenario for decision-making when planning the launch of a new service.