A Framework for Life-Cycle Integrated Decision-Making in Buildings

Thesis Abstract

The rapid transformation of building delivery and operation demands a systematic framework that integrates life-cycle thinking across design, construction, operation, and end-of-life stages to optimize economic, environmental, and social outcomes. Despite advances in sustainability and facilities management, practitioners lack a cohesive decision- making framework that harmonizes multi-criteria assessment, stakeholder preferences, and temporal trade-offs within real-world project constraints. This study proposes a Life-Cycle Integrated Decision-Making (LCID-M) framework for buildings, anchored in value-based and systems thinking, to support transparent, auditable, and reproducible decision processes from concept through decommissioning. The aim is to develop, validate, and demonstrate a structured approach that enables simultaneous optimization of cost, embodied and operational energy, carbon footprint, occupant comfort, and resilience, while accommodating policy requirements and market dynamics. The specific objectives are to (1) review and synthesize theoretical foundations from life-cycle assessment (LCA), value-at-risk analysis, and decision theory to identify gaps in current building decision models; (2) articulate a conceptual framework that integrates design-phase parametric modeling, procurement strategies, construction sequencing, facilities management data, and end-of-life scenarios; (3) operationalize the framework into a computational model that couples parametric building information modeling (BIM) with a multi-criteria decision analysis (MCDA) module and a life-cycle cost analysis (LCCA) component; (4) calibrate and validate the model using empirical data from 20 recently completed office buildings across three climates, including energy performance, embodied carbon, maintenance costs, and user satisfaction metrics; (5) test scenario-based decision outcomes under varying policy conditions and market prices to assess robustness and transferability; and (6) provide policy and practice recommendations to advance adoption of LCID-M within industry and regulation. A mixed-methods methodology is employed. The research design combines explanatory sequential design first implementing a qualitative phase to elicit stakeholder preferences and decision criteria from semi-structured interviews with 40 professionals (architects, engineers, facilities managers, and sponsors) and 12 focus groups, followed by a quantitative phase applying a computational LCID-M model. Population includes stakeholders in a metropolitan region with high-rise and mid-rise buildings. Data collection instruments comprise a validated MCDA survey capturing criteria weights, a BIM-embedded data extractor for lifecycle inputs, and energy, cost, and maintenance datasets, complemented by post-occupancy evaluation (POE) data. Instrument validity and reliability are established through expert review, pilot testing with 5 pilot buildings, and Cronbach’s alpha assessments (>0.7) for scales. The data analysis integrates regression analysis to identify determinants of life-cycle performance, Monte Carlo simulation to address parameter uncertainty, and multi-objective optimization (non-dominated sorting genetic algorithm II, NSGA-II) to derive trade-off frontiers. The theoretical backbone draws on multi-criteria decision theory, as well as the theory of value-based decision making and dynamic life-cycle assessment, with references to the Integrated Design Process (IDP) framework and the Circular Economy paradigm. Key expected findings include (i) a validated LCID-M framework comprising an integrated data architecture, a decision-support MCDA module, and a life-cycle cost and environmental impact simulator; (ii) quantified weights for decision criteria representing diverse stakeholder priorities; (iii) optimized design and operational configurations that reduce life-cycle cost by 8–15% and operational energy by 12–22% relative to baselines, while reducing embodied carbon by 10–25%; (iv) robust decision guidelines for policy makers and industry practitioners to embed LCID-M into procurement and asset management processes; and (v) demonstration cases illustrating how early design choices constrain or enable favorable end-of-life pathways. The study contributes to knowledge by bridging fragmented life-cycle tools into an operational framework that supports transparent, evidence-based, value-aligned decisions across the building life cycle, aligns with sustainable construction and urban resilience agendas, and provides a replicable modeling approach for diverse climatic and market contexts. The main conclusion posits that integrating lifecycle cost, environmental performance, and stakeholder preferences within a coherent MCDA-enabled framework yields superior long-term outcomes compared with conventional design and management practices. Recommendations include institutionalizing LCID-M in early-phase project briefs, standardizing data exchange protocols between BIM, LCA, and FM systems, and developing policy incentives to encourage adoption of life-cycle integrated decision-making across public and private sectors.