Prioritising Non-Systematic Risks to the Operational Sustainability of Smart-Building Technologies in Healthcare Facilities: A Best-Worst Method Study

Healthcare facilities depend on smart-building technologies, yet their institution-specific vulnerabilities are difficult to prioritise. Ten purposively recruited experts from hospitals in Istanbul, Türkiye, weighted eight literature-derived risks. The primary analysis used linear Best-Worst Method (BWM) estimation and arithmetic-mean aggregation. Additional judgement-traceability diagnostics, consistency-based reweighting and selection, Bayesian BWM, group omissions and bootstrap resampling were post hoc exploratory robustness analyses. In the primary analysis, privacy and data breach (0.170), crisis response and recovery failure (0.163), loss of data integrity and transparency (0.158) and device and endpoint security (0.142) carried 63.4% of the weight, but their order and group membership were sensitive to analytical choices and panel composition. Improper data disposal policies ranked last (0.030) in the primary analysis and the reported non-bootstrap sensitivity specifications. Crisis response and recovery failure ranked first or second in analyses that weighted or selected experts according to judgement consistency; privacy and data breach did not rank first in these analyses. Recovery failure fell to seventh when the three experts whose comparison vectors prioritised it were omitted. Questionnaire limitations included a missing comparison row, conflicting selections and duplicate comparisons, and a fixed criterion order. The weights describe expert-perceived priorities and require validation against incident and downtime data before guiding resource allocation.