Data Quality And Bias in Logistics Optimization for Pharmaceutical Firms: A time-series forecasting

Policy Brief 4.6

Data Quality And Bias in Logistics Optimization for Pharmaceutical Firms: A time-series forecasting

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Harvard

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~ 12–19 mins

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AR/VR IoT Epidemiology

Abstract

This policy brief investigates “Data Quality And Bias in Logistics Optimization for Pharmaceutical Firms: A time-series forecasting” using a survey-based structural equation modeling. Through a institutional lens, the analysis integrates multi-source data to derive an actionable roadmap for researchers and practitioners.

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Data Quality And Bias in Logistics Optimization for Pharmaceutical Firms: A time-series forecasting

ABSTRACT

Data Quality And Bias in Logistics Optimization for Pharmaceutical Firms: A time-series forecasting is unpacked across themes: interoperability, costs, scalability, and KPIs. Limitations and future research paths are noted.

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