The Value of Last-mile Delivery in Online Retail

40 Pages Posted: 31 Oct 2023

See all articles by Zhikun Lu

Zhikun Lu

Emory University - Goizueta Business School

Ruomeng Cui

Emory University - Goizueta Business School

Tianshu Sun

Cheung Kong Graduate School of Business; University of Southern California - Marshall School of Business

Lixia Wu

Alibaba Group

Date Written: October 2, 2023

Abstract

Last-mile delivery refers to the final leg of shipment in which packages are moved from a local transportation hub to end-customers. It is known to be the most expensive part of delivery, due to operations complexity and lack of economy of scale. Given the growing importance of last-mile delivery in online retail, companies need to decide whether to outsource this service to customers through pickup stations where they can collect packages or to offer home delivery. In this paper, we study the economic value of last-mile delivery. We conducted a quasi-experiment in collaboration with Cainiao, Alibaba's logistics subsidiary, in which home delivery service was rolled out to some pickup stations sequentially in 2021. This allowed us to comprehensively evaluate the causal impact of last-mile delivery. Using a staggered difference-in-differences identification, we found that last-mile delivery significantly increases sales and customer spending on Alibaba's retail platform. Last-mile home delivery relies heavily on physical labor and thus has capacity constraints. To optimally prioritize that capacity, we used an uplift model with causal machine learning to target the most responsive customers. Specifically, we proposed a novel capacity- and fairness-aware uplift model that builds in capacity and fairness constraints to optimize the targeting policy, thereby maximizing profits without compromising social equity. Our findings suggest that online retailers should carefully weigh the costs and benefits of last-mile delivery and tailor their logistic strategies.

Keywords: last-mile delivery, experiment, uplift model, causal machine learning, capacity-aware, fairness

Suggested Citation

Lu, Zhikun and Cui, Ruomeng and Sun, Tianshu and Wu, Lixia, The Value of Last-mile Delivery in Online Retail (October 2, 2023). Available at SSRN: https://ssrn.com/abstract=4590356 or http://dx.doi.org/10.2139/ssrn.4590356

Zhikun Lu

Emory University - Goizueta Business School ( email )

1300 Clifton Road
Atlanta, GA 30322-2722
United States

Ruomeng Cui (Contact Author)

Emory University - Goizueta Business School ( email )

1300 Clifton Road
Atlanta, GA 30322
United States

HOME PAGE: http://www.ruomengcui.com

Tianshu Sun

Cheung Kong Graduate School of Business ( email )

1017, Oriental Plaza 1
No.1 Dong Chang'an Street
Beijing
China

University of Southern California - Marshall School of Business ( email )

3670 Trousdale Parkway
Bridge Hall 310B
Los Angeles, CA 90089
United States

Lixia Wu

Alibaba Group ( email )

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
179
Abstract Views
497
Rank
286,629
PlumX Metrics