A Strategic Framework for Post-Disaster Estate Asset Recovery and Valuation

Thesis Abstract

This study addresses the persistent challenge of estimating, recovering, and valuing estate assets in the aftermath of natural and anthropogenic disasters, where disruption of land records, ownership conflicts, and damaged asset registries impede rapid reconstruction and financial restitution. The aim is to develop a strategic framework that integrates asset recovery processes with reliable valuation mechanisms to enhance post-disaster resilience and inform governance, private sector, and community stakeholder decisions. Specific objectives are (1) to map current post-disaster asset recovery workflows across municipal, cadastral, and financial institutions; (2) to identify cognitive, legal, and operational barriers to timely asset recovery and accurate valuation; (3) to design a standardized valuation model that accommodates disaster-induced asset degradation, obsolescence, and uncertainty; (4) to test the framework through a multi-site empirical evaluation in three metropolitan regions experiencing recent flood, earthquake, and windstorm events; and (5) to produce policy and practice recommendations that bridge public administration, professional estate management, and disaster risk reduction. The study employs a mixed-methods research design combining quantitative and qualitative strands. The population encompasses asset registries, property appraisers, survey respondents from 12 municipal departments of works, 8 cadastre offices, 6 loss-adjustment firms, and 9 major real estate firms involved in post-disaster recovery. A stratified random sample selects 360 property records with post-disaster claims and 180 professionals for surveys, complemented by 36 in-depth interviews and 8 focus groups with stakeholders across the governance, valuation, and rebuilding domains. Data collection instruments include a structured survey measuring readiness, data quality, and valuation accuracy; semi-structured interview guides exploring legal constraints, information systems interoperability, and risk perception; and archival data from cadastral databases and disaster response logs. Validity and reliability are ensured through pilot testing (n=40), content validity via expert panels including survey design and estate valuation specialists, and triangulation across documentary evidence, survey results, and interview narratives. The analytical approach integrates descriptive statistics, multiple regression to identify determinants of valuation accuracy, and variance analysis to compare recovery performance across sites. A comprehensive valuation framework is specified using a hedonic pricing model adjusted for disaster-induced depreciation and uncertainty, supplemented by a Bayesian updating procedure to incorporate new information as recovery progresses. The study also employs thematic analysis for qualitative data to extract patterns related to governance capacity, information system interoperability, and community engagement. Ethical considerations include informed consent, data anonymization, and coordination with municipal authorities to safeguard confidential asset information. Expected findings indicate that (i) fragmented data governance and inconsistent land records significantly reduce the speed and accuracy of asset recovery and valuation; (ii) a standardized valuation framework that integrates post-disaster depreciation factors and uncertainty quantification improves decision-making for insurers, lenders, and government agencies; (iii) interagency collaboration and interoperable information systems substantially enhance recovery timelines by up to 28% and valuation accuracy by 15%–22%; and (iv) a Bayesian updating mechanism that revises asset values as new field data becomes available reduces mispricing risks in insurance settlements and compensation schemes. The study is anticipated to demonstrate that the proposed strategic framework—comprising data governance guidelines, a harmonized valuation model, interoperability protocols, and decision-support tools—significantly strengthens post-disaster estate management capacities and resilience. Contributions to knowledge include (a) a theoretically informed, practice-ready framework integrating asset recovery and valuation in post-disaster contexts; (b) empirical evidence on the determinants of valuation accuracy under catastrophic conditions; (c) a validated hedonic-Bayesian valuation model adapted for disaster scenarios; and (d) policy recommendations for legal harmonization, data standardization, and capacity building in estate management institutions. The study concludes with implications for national disaster risk reduction strategies, insurance and compensation mechanisms, and urban planning practices, advocating for mandatory data interoperability, standardized post-disaster valuation protocols, and investment in cadastral modernization to safeguard asset recovery outcomes in future disasters. Recommendations include institutionalize cross-department data sharing, develop a governed valuation toolkit with transparent depreciation and uncertainty parameters, implement routine post-disaster audits of asset registries, and establish capacity-building programs for practitioners in valuation and asset recovery under crisis conditions.