A prescriptive framework to support express delivery supply chain expansions in highly urbanized environments
Industrial Management & Data Systems
; 122(7):1707-1737, 2022.
Article
in English
| ProQuest Central | ID: covidwho-1901376
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.
Business And Economics--Computer Applications; Last-mile; Multi-period hub assignment optimization; Spherical-clustering algorithms; Simulation; Research; Integer programming; Traffic information; Sustainability; Competitive advantage; Population density; Demand; Optimization; Data analysis; Operations management; Clustering; COVID-19; Mathematical programming; Accuracy; Network management systems; Startups; Pandemics; Algorithms; Supply chains; Methods; Electronic commerce; Robustness (mathematics); Logistics; United States--US; 45411:Electronic Shopping and Mail-Order Houses
Full text:
Available
Collection:
Databases of international organizations
Database:
ProQuest Central
Language:
English
Journal:
Industrial Management & Data Systems
Year:
2022
Document Type:
Article
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