A new paper by Niemeijer and Buijs analyzes the carbon emission impact of pickup points in last-mile parcel delivery. Pickup points offer customers and delivery companies an alternative to attended home delivery. The delivery company can drop a parcel off at the pickup point, such as a service desk in a grocery store or a parcel locker, where the customer collects the parcel.
Because of the potential efficiency gains for the delivery vehicle, pickup points are often presented as a sustainable alternative to home delivery. However, the efficiency gains for the delivery vehicle need to be weighed against customers traveling to the pickup point by car. The mathematical analysis presented in this paper integrates continuous approximation techniques to assess the potential for improved delivery route efficiency with multinomial logistic regression for estimating the travel distance and mode choice of customers collecting their parcels.
The rationale is that introducing pickup points helps improve the efficiency of delivery routes because fewer customer homes have to be visited, and more parcels are successfully delivered at the first attempt. One of the aspects complicating the assessment of pickup points is that it involves customer travel behavior and that the carbon emissions from customer travel are challenging to model accurately.
The results challenge the suggestion that pickup points are a universally sustainable alternative to home delivery. The potential for a net positive carbon emission impact is most significant when pickup points are established in urban settings. At the same time, in rural settings, the carbon emission benefits derived from improved delivery route efficiency are quickly offset by the carbon footprint associated with customer travel.
These assumptions imply that the conditions under which pickup points can have a positive net carbon emission impact may be slightly more extensive than indicated in our analysis. This opens highly interesting areas for future research, both in obtaining new empirical data about which customers choose to self-collect parcels at pickup points and in developing more complex mathematical models allowing for non-uniformly distributed customers and adoption rates.