Robust Workforce Management with Crowdsourced Delivery

Revolutionize Workforce Management of Crowdsourced Delivery Platforms The surge in online shopping is driving e-retailers to revamp their logistics for efficient, cost-effective deliveries. Many are embracing crowdsourced delivery, where independent couriers use personal vehicles for swift shipments. Major players like Amazon and Walmart have pioneered this shift in delivery methods. To tackle uncertainties in this model, platforms are blending ad hoc couriers with prehired couriers. This hybrid approach ensures reliability in customer service while managing costs effectively. However, balancing this mix poses challenges, as future demands are still being determined. This study proposes a robust satisficing framework to optimize workforce management in delivery platforms. This innovative method aims to enhance cost-effectiveness and service quality by addressing uncertainties in ad hoc couriers’ availability and behavior. It offers a strategic tool for platforms to navigate workforce resources efficiently amidst fluctuating demands and cost constraints.

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Institutions

Publication Details

Journal
Operations Research
Published
2024-11-04
DOI
https://doi.org/10.1287/opre.2023.0125
Citations
2
Primary Topic
Scheduling and Optimization Algorithms
Type
article
Field-Weighted Citation Impact
0.70
Controls
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article

Robust Workforce Management with Crowdsourced Delivery

Chun Cheng, Yue Zhao, Melvyn Sim
2 citations
Operations Research
Scheduling and Optimization Algorithms
0.70
article

Robust Workforce Management with Crowdsourced Delivery

Chun Cheng, Yue Zhao, Melvyn Sim
article en
2 citations

Abstract

Revolutionize Workforce Management of Crowdsourced Delivery Platforms The surge in online shopping is driving e-retailers to revamp their logistics for efficient, cost-effective deliveries. Many are embracing crowdsourced delivery, where independent couriers use personal vehicles for swift shipments. Major players like Amazon and Walmart have pioneered this shift in delivery methods. To tackle uncertainties in this model, platforms are blending ad hoc couriers with prehired couriers. This hybrid approach ensures reliability in customer service while managing costs effectively. However, balancing this mix poses challenges, as future demands are still being determined. This study proposes a robust satisficing framework to optimize workforce management in delivery platforms. This innovative method aims to enhance cost-effectiveness and service quality by addressing uncertainties in ad hoc couriers’ availability and behavior. It offers a strategic tool for platforms to navigate workforce resources efficiently amidst fluctuating demands and cost constraints.

Operations ResearchVol. 73(2)
National University of Singapore (SG), Dalian University of Technology (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 25%
Scheduling and Optimization Algorithms
0.70
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Robust Workforce Management with Crowdsourced Delivery — Chun Cheng, Yue Zhao, et al. · Operations Research (2024) | TGRS Research Map | TGRS