An e-delivery system based on pick-up points: demand forecast, system design and scenario assessment

In recent years, e-commerce experienced significant growth, also pushed by restrictions imposed during the COVID-19 pandemic. This rapid growth has had significant both positive (e.g., economic growth) and negative (e.g., congestion and pollution) impacts on cities. In fact, in many cases, small, sprawled and failed deliveries, resulting in additional trips for carriers, are a problem to tackle in terms of both operational (internal) costs and external costs. Focusing on such a problem, this paper reviews the current literature and points out the need to overcome the current literature lacks that limit the exploitation of new ways of receiving e-purchases in a sustainable way. The current methodologies were developed mainly to simulate some aspects of e-delivering and are not able to forecast the end consumers' choice as well as the impacts due to the different measures that are implemented at urban scale which affect the e-delivery operations. Therefore, considering the limited literature analyses regarding such a delivery system, the paper proposes an assessment methodology which included an advanced behavioral modeling system able to forecast the end consumers' demand, and an optimization model for designing the pick-up system in terms of the number, location and size of the pick-up points, taking the availability of end consumers to collect their e-purchases into consideration. The approach has been applied to a real case study, and satisfactory results have been obtained. The findings of this study can contribute to the development of more sustainable urban freight transport, one of the most significant challenges facing city decision makers and authorities.