A prescriptive framework to support express delivery supply chain expansions in highly urbanized environments
Industrial Management & Data Systems
ISSN: 0263-5577
Article publication date: 6 June 2022
Issue publication date: 21 June 2022
Abstract
Purpose
With the proliferation of e-commerce companies, express delivery companies must increasingly maintain the efficient expansion of their networks in accordance with growing demands and lower margins in a highly uncertain environment. This paper provides a framework for leveraging demand data to determine sustainable network expansion to fulfill the increasing needs of startups in the express delivery industry.
Design/methodology/approach
While the literature points out several hub assignment methods, the authors propose an alternative spherical-clustering algorithm for densely urbanized population environments to strengthen the accuracy and robustness of current models. The authors complement this approach with straightforward mathematical optimization and simulation models to generate and test designs that effectively align environmentally sustainable solutions.
Findings
To examine the effects of different degrees of demand variability, the authors analyzed this approach's performance by solving a real-world case study from an express delivery company's primary market. The authors structured a four-stage implementation framework to facilitate practitioners applying the proposed model.
Originality/value
Previous investigations explored driving distances on a spherical surface for facility location. The work considers densely urbanized population and traffic data to simultaneously capture demand patterns and other road dynamics. The inclusion of different population densities and sustainability data in current models is lacking; this paper bridges this gap by posing a novel framework that increases the accuracy of spherical-clustering methods.
Keywords
Acknowledgements
The authors would like to thank the subject matter experts and anonymous reviewers for their insightful guidance and suggestions. This research was supported in part by ODU-VMASC Internal Research and Development Project 300770-010: Exploring Additional Applications of Supply Chain Management, AI, and Cybersecurity.
Citation
Diaz, R., Phan, C., Golenbock, D. and Sanford, B. (2022), "A prescriptive framework to support express delivery supply chain expansions in highly urbanized environments", Industrial Management & Data Systems, Vol. 122 No. 7, pp. 1707-1737. https://doi.org/10.1108/IMDS-02-2022-0076
Publisher
:Emerald Publishing Limited
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