Publication Type

Working Paper

Version

publishedVersion

Publication Date

1-2018

Abstract

The Last-Mile Problem refers to the provision of travel service from the nearest public transportation node to the final destination. The Last-Mile Transportation System (LMTS), which has recently emerged, provides on-demand shared last-mile transportation service. While it is natural that in the last-mile supply chain, a high-value parcel should be charged a higher price and deserves service priority compared to a low-value parcel, it is not straightforward to identify an obvious pricing and service priority for an LMTS that serves passengers. In an LMTS, a special-type passenger who has a higher valuation of service usually has a lower waiting time disutility; i.e., the valuation of service and the waiting time disutility rate are negatively correlated. In this paper, we consider two fairness guarantees — price discount and service priority — applied to special-type passengers with higher service valuation but lower waiting time disutility. We propose models to analyze pricing and service priority policies. We prove that the LMTS is more profitable if a smaller price discount and no service priority are given to special-type passengers, and this is also the case for the social welfare maximization objective. We implement the models in a set of numerical experiments using real public transport data. Based on both the theoretical analysis and the numerical experiments, we find that enforcing fairness guarantees in the LMTS is critical.

Keywords

Shared Transportation, Last-Mile, Fairness, Price Discount, Service Priority

Discipline

Systems Architecture

Research Areas

Intelligent Systems and Optimization

Download

Share

COinS