Data Analytics Models for Equitable and Behavioural Operations Research: Applications in Healthcare

Abstract

This dissertation explores the intersection of healthcare operations management, equity in resource allocation, and behavioural uncertainty, particularly in the context of the COVID-19 pandemic. It presents a hybrid approach that combines traditional opti- misation models with machine learning techniques to address two critical challenges: equitable vaccine distribution and vaccine hesitancy. The first part introduces a novel equitably bounded multidimensional knapsack model, incorporating different equity con- straints to optimise vaccine allocation under uncertainty. The second part develops a semi-supervised few-shot clustering algorithm to classify vaccine hesitancy on Twitter/X using the 3Cs model (Confidence, Complacency, Convenience). The third part integrates topic modelling with hidden Markov models to analyse the temporal evolution of vaccine- related discourse. Together, these studies offer a comprehensive, data-driven framework for improving healthcare decision-making, balancing methodological rigour, technical feasibility, and social acceptability.