Prioritising indicators of success in 'Build Back Better' post-disaster frameworks : a thesis submitted in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Construction at Massey University, Albany, New Zealand

Abstract

This study explores the challenges and significance of indicator selection for key decision-makers in post-disaster response, recovery, and reconstruction efforts. When a community is overwhelmed in the aftermath of a disaster - various entities, including aid organisations, local authorities, and national agencies, are mobilised to provide emergency response and support in the subsequent response and recovery phases. These decision-makers rely on choosing appropriate indicators to evaluate the effectiveness of their interventions, track progress, and decide on appropriate actions and activities. Guided by the principle of "Build Back Better," which advocates for a comprehensive and holistic approach to resilience, practitioners need to comprehend the intricate relationships and dependencies among indicators to make informed decisions regarding their selection. This aspect has been identified as a significant weakness in the implementation process for all stakeholders. Employing a novel methodology, this thesis utilises the Hierarchical Decomposition Algorithm to analyse the priority of and the relationship between indicators proposed by the 2016 ‘Build Back Better Framework’, a synthesised framework reflecting a unified approach in disaster management. Empirical evidence from forty case studies examining key decision makers experiences of implementing disaster response efforts validates these findings. The study concludes with a rational process and workflow for determining indicator selection which considers the diverse nature of response and recovery in the pursuit to effectively build back better.