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Structural Estimation of Driver Attrition in a Last-Mile Delivery Platform
Lina Wang1, Scott Webster2, Elliot Rabinovich2
1Georgia Southern University; 2Arizona State University
In this paper, we consider the question of how to better manage turnover among independent drivers who transport parcels for last-mile delivery platforms. We collaborate with a last-mile delivery platform to build a structural model that enables us to estimate the effects of key predictors of drivers' decisions to continue or leave the platform. For this estimation, we apply a dynamic discrete-choice framework in a two-step procedure that accounts for unobserved heterogeneity among drivers.
The driver-aide problem: coordinated logistics for last-mile delivery
S. Raghavan1, Rui Zhang2
1University of Maryland, College Park, MD 20742, USA; 2University of Colorado, Boulder, CO 80309, USA
We introduce the `Driver-Aide (DA) Problem', a new mode of service operations in last-mile delivery. The use of a DA can shorten route durations, allowing larger delivery volumes without the need for additional vehicles. However, it is challenging to determine the best way to use a DA (as there are two different ways to use a DA) and evaluate the tradeoffs involved. We develop an optimization-based solution framework and conduct an economic analysis using data provided by an industrial partner.
Private vs. pooled transportation: customer preference, environmental effect and congestion management
Kashish Arora1, Fanyin Zheng2, Karan Girota1
1Cornell University; 2Columbia University
In this work, we build a structural model to study customers’ preferences on prices and service features when choosing between private taxis and a scheduled shuttle service.
