## 2 Materials and Methods
### Sensitivity and Uncertainty Analysis  
A sensitivity analysis is conducted to determine the most influential HOE variables on the model outputs while uncertainty analysis is used to assess how much uncertainty is associated with these influential variables. The purpose of these analyses is to determine the HOE-related influence on risk. A Monte Carlo approach is adopted to perform the analysis; a sampling is generated from the probability distributions and the output of the model is determined and represented in different graphs. The number of samples has been fixed to 1000 samples for an acceptable level of confidence. The following steps are performed for the sensitivity and uncertainty analyses. First, the responsive parameters are identified. Second, for each of the responsive human and organizational parameters, a univariate analysis is performed to assess the sensitivity of the target variables to characterize which variables are more sensitive to the organisational response. The quantification of the uncertainty allows for both comparative and absolute risk analysis; when using the comparative approach, it ensures that the point value of the individual risk of the performance solution is below that of the DTS solution even if HOE-related errors are taken into account for both designs. It can be possible, in theory, that the first of the two solutions is more prone to be influenced by human factors than the second, or vice versa. For the performance solution to be approved, it is therefore important to find the upper and lower limits for both the risk values and verify that the upper bound value of the performance solution is below the lower bound solution of the DTS solution. When risk evaluation is conducted in absolute terms, the oscillations of the risk value should never trigger the reference value. The uncertainty analysis allows a deeper understanding of the propagation of HOEs through a risk model for high-rise buildings subject to fire. In the sensitivity analysis, a simple mono-dimensional analysis is conducted based on point values. The HOEs (deficient training, inefficient emergency plan, not comply with instruction, no check rules, deficient maintenance, wrong risk assessment, not obey standard, improper safety organisation) are attributed with a probability distribution built based on a three-point estimation method. In a multivariate analysis, the sensitivity is represented in a tornado graph showing the variables with major impacts on the final risk value. When considering a single parameter, the relative amplitude of the variation of the global risk value is compared to the relative amplitude of the variation of the parameter value (sensitivity). Moreover, the model is used to determine the amplitude of the risk variations in cumulative terms. This in fact can be beneficial for more detailed analysis of the risk in relationship to the entire society. Sensitivity analysis is further conducted on key variables in the SD model to assess model robustness and to explore how uncertainty affects the assessment of different safety systems and reliability of model outputs. Once the sensitive parameters for each HOE variable have been identified in the previous steps, a Monte Carlo simulation is carried out. The linkage of these variables to their parent nodes is the focus of this analysis. The causal loop in the SD model consists of all the variable and their interactions with each other including feedback loops and time delays. Stocks are accumulations in the system used to represent variables that change with time and flows are entities that control these stocks. The behaviour of the HOE variables depends on the parent variables connected to them in the causal loop and delays are to be expected in the response to safety issues due to feedback loops occurring over a period of time. Therefore, if the system is observed on a wider time scale over ten years, oscillations in the final output are possible, generating phases during which the risk could vary greatly with respect to the static value.