Logistics Optimization for Urban Households: Data Quality And Bias | Post-Pandemic Lessons

Policy Brief 4.9

Logistics Optimization for Urban Households: Data Quality And Bias | Post-Pandemic Lessons

Pages

Harvard

Style

~ 5–10 mins

Reading Time

IoT Finance Telemedicine

Abstract

This policy brief investigates “Logistics Optimization for Urban Households: Data Quality And Bias | Post-Pandemic Lessons” using a agent-based simulation. Through a human-centered lens, the analysis integrates multi-source data to derive an actionable roadmap for researchers and practitioners.

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Logistics Optimization for Urban Households: Data Quality And Bias | Post-Pandemic Lessons

ABSTRACT

Logistics Optimization for Urban Households: Data Quality And Bias | Post-Pandemic Lessons is unpacked across themes: security, ethics, change enablement, and interoperability. Limitations and future research paths are noted.

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