The rapid classification of building damage states or placards after an earthquake is vital for enabling an efficient emergency response and informed decision-making for rehabilitation and recovery purposes. Traditional methods rely heavily on inspector-led on-site surveys, which are often time-consuming, resource-intensive, and susceptible to human error. This study introduces a machine learning-supported surrogate model designed to streamline the assessment of building damage, focusing on the automated assignment of damage placards within the context of New Zealand's post-earthquake evaluation frameworks. The study evaluates two key safety evaluation protocols—Rapid Building Assessment (RBA) and Detailed Damage Evaluation (DDE)—and integrates corresponding databases derived from the 2010–2011 Canterbury Earthquake Sequence (CES) in Christchurch. Six ML classifiers—Multilayer Perceptron (MLP), Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbours (KNN), Gradient Boosting Classifier (GBC), and Gradient Bagging (GBag)—were rigorously tested across both databases. The results indicate that the RF-based surrogate model outperforms the other classifiers across both RBA and DDE protocols. Two distinct sets of critical predictors have been further identified for each protocol, allowing for the rapid retrieval of essential data for future on-site surveys, while retaining the RF model's predictive accuracy. The developed surrogate model provides a pragmatic tool for practising engineers to rapidly assign placards to damaged structures and for policymakers and building owners to make informed recovery decisions for earthquake-affected buildings
Contemporary organisations operate in rapidly evolving complex and ambiguous environments for which traditional change management approaches are insufficient. Under these conditions, organisations need to demonstrate learning and adaptive capabilities to effectively manage crises. Yet, the swift development and enactment of these capabilities can be particularly challenging for large, operationally diverse, and financially constrained public-sector organisations such as universities. Despite growing need for evidence-based research to guide crisis and change management in the higher education sector, the organisational literature offers limited insights. The combined impact of the 2010 and 2011 Canterbury earthquakes with a well-advanced restructure provided an opportunity to investigate institutional adaptation to and management of a compounded planned change (i.e., restructure) and an unplanned change (i.e., natural disaster response) at a university. Beginning in 2016, individual semi-structured interviews were conducted with 20 middle and senior university managers to capture their perspectives of compounded planned and unplanned change management, covering views of leadership, and of operational, structural, relational, and extra-organisational factors. Data were analysed using reflexive thematic analysis. The analysis coalesced into two overarching themes: Change Management Approaches and Lessons Learned through Change. Change Management Approaches evince institutional adaptation factors, along with barriers and enablers to effective change management, arising from the interplay of, and tensions between, leadership capabilities and a longstanding participatory culture. Lessons Learned through Change encompass business continuity mechanisms, and the learning opportunities seized and missed by leaders. The findings assert the primacy of workforce capabilities to 21st-century organisational success and thriving and substantiate that the calibre and availability of workforce capability is contingent on organisational culture and leadership. Leaders must ensure organisational agility by empowering employees, leveraging and integrating their contributions within and across functional units, and promoting effective two-way communication. The research argues for a hybrid repertoire of versatile dynamic organisational leadership qualities and capabilities to effectively navigate the multidimensional challenges and uncertainties in this sector and 21st-century business conditions. Of overarching significance to this repertoire is purpose-oriented emotionally intelligent leadership that honours the individual and collective dignity, diversity, and intelligence of all employees. This research empirically evidences the co-occurrence of planned and unplanned change in contemporary society, and continuous organisational adaptation and resilience to navigate the persistent volatility during a protracted crisis. Accordingly, the thesis argues that continued bifurcation of planned and unplanned change fields, and strategic and change management leadership theories is untenable, and that an integrated framework of organisational leadership and change management methodologies is required for organisations to effectively respond to and navigate the challenges and volatility of contemporary organisational contexts.
