A Resilience-Based Framework for Post-Occupancy Evaluation in Green Buildings

Thesis Abstract

Post-occupancy evaluation (POE) in green buildings has often focused on biophysical performance, with limited integration of resilience concepts to address post-occupancy realities under evolving climatic, social, and operational stresses. This study develops a resilience-based framework for POE to systematically assess, diagnose, and enhance the long-term adaptive capacity of green buildings. The aim is to (i) operationalize resilience in the POE context, (ii) identify determinants of performance variability across time and occupants, and (iii) propose actionable strategies for design, operation, and policy to sustain green building performance. Specific objectives include (1) conceptualising a resilience-based POE model integrating physical, behavioral, and climatic dimensions; (2) mapping relevant indicators across structural, operational, and social subsystems; (3) validating the framework through empirical POE data from a sample of certified green buildings; (4) examining the interaction between occupant behavior, building management practices, and system resilience; and (5) delivering a practical toolkit for practitioners to monitor, predict, and mitigate performance degradation under disturbance events. A mixed-methods research design will be employed, combining quantitative survey data, building performance metrics, and qualitative interviews. The population comprises green-certified office buildings in a metropolitan region with high adoption of energy efficiency and low-carbon strategies. A stratified random sample of 30 buildings will be selected, with at least 15 providing at least one year of post-occupancy performance data. Within each building, a representative sample of occupants (n ? 20–30 per site) and building managers (n ? 5 per site) will be surveyed and interviewed. Data collection instruments include a resilience-oriented POE questionnaire adapted from established occupant comfort and satisfaction scales, building management records, energy and indoor environmental quality (IEQ) performance data, and semi-structured interview guides. Instrument validity and reliability will be ensured through content validity with a panel of experts and pilot testing (Cronbach’s alpha targets ?0.80 for multi-item scales). Quantitative data will be analyzed using structural equation modeling to test the relationships among physical performance, resilience indicators, and occupant outcomes; regression analysis will identify predictors of post-occupancy resilience; and time-series analyses will examine performance trajectories under disturbances. Qualitative data will be analyzed using thematic analysis to uncover salient resilience mechanisms, with triangulation against quantitative findings. The analytical framework will be anchored in organizational resilience theory and the socio-technical systems perspective, incorporating concepts from the Theory of Planned Behavior to interpret occupant interactions, and the Multi-Level Perspective on sustainability transitions to contextualize scale effects. A conceptual model will be iteratively refined through empirical results. Key expected findings include (i) a validated resilience-based POE model that links structural and environmental performance with occupant behavior and management practices; (ii) identification of critical resilience indicators such as adaptive maintenance capacity, sensor-data reliability, occupant cognitive load, and operational redundancy; (iii) quantified relationships showing that proactive management practices and real-time feedback loops significantly elevate resilience scores and reduce performance volatility during disturbances such as heat waves or unexpected occupancy surges; and (iv) evidence that occupancy patterns and retrofit readiness moderate resilience outcomes, informing prioritization of retrofit investments. The study’s contribution to knowledge lies in integrating resilience theory with POE to produce a practical framework and toolkit that enables continuous learning and adaptive optimization of green buildings. It advances methodological combine of SEM, time-series, and thematic analysis within a POE context and extends understanding of how social and organizational dimensions interact with technical systems to sustain environmental performance. Policy implications include guidance for post-occupancy monitoring requirements, performance-based maintenance regimes, and occupant-oriented strategies that reinforce resilience in green buildings. The main conclusion is that resilience-centered POE provides a robust, integrative approach to maintaining and enhancing green building performance in the face of dynamic disturbances. Practical recommendations include implementing a resilience dashboard for ongoing monitoring, establishing adaptive maintenance protocols, integrating occupant feedback mechanisms into building management systems, and prioritizing retrofit plans that improve system redundancy and data reliability. Further research could explore cross-cultural validations, longer longitudinal studies to capture seasonality and aging effects, and the extension of the framework to other building typologies such as mixed-use developments and high-rise residential towers.