# A Fuzzy-Based Decision Support Model for Risk Maturity Evaluation of Construction Organizations
## 5 Conclusions  
This paper presented a novel decision support model for evaluating the risk management maturity level of construction organizations. The developed model can assist construction organizations to have a clear view of their capabilities and weaknesses in risk management processes and help these organizations in having a better understanding of the areas that need improvements.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Attributes**} & \multicolumn{2}{c}{**Attributes’ Importance**} & \multicolumn{2}{c}{**Degree of Implementation**} & \multicolumn{2}{c}{**Attributes’**} \\ \cline{2-6}  & **Weights (ANP)** & **Rank** & **Fuzzy Number** & **Crisp Number** & **Maturity Score** \\ \hline APR & 18.33 & 3 & (0.075, 0.408, 0.655) & 0.379 & 6.95 \\ \hline AID & 18.55 & 2 & (0.107, 0.453, 0.696) & 0.419 & 7.77 \\ \hline AAR & 13.42 & 5 & (0.071, 0.282, 0.528) & 0.294 & 3.94 \\ \hline ARR & 19.54 & 1 & (0.064, 0.396, 0.639) & 0.366 & 7.15 \\ \hline AIRR & 16.83 & 4 & (0.092, 0.471, 0.703) & 0.422 & 7.10 \\ \hline AMR & 13.33 & 6 & (0.05, 0.335, 0.582) & 0.322 & 4.29 \\ \hline \multicolumn{6}{c}{Industrial partner risk maturity score} & \multicolumn{2}{c}{37.2} \\ \hline \hline \end{tabular}
\end{table}
Table 12: Risk maturity score of industrial partner’s organization.  
Figure 7: Degree of implementation for each attribute.  
Unlike the existing risk maturity models reported in the literature, the developed model considered different relative weights for the responses provided by different individuals. It accounted for the authority level of the participants and their level of involvement in the risk management processes. This unique aspect of the developed model allows construction organizations to assign a higher weight to the responses provided by individuals who are at portfolio or program levels of the organization and have an adequate knowledge of risk management which in turn leads to a more accurate and reliable evaluation of the risk maturity level of the organization. Moreover, the developed model is capable of accounting for the interdependency between the risk maturity attributes and for the subjectivity and imprecision in the responses of the participants involved in the development of the model.  
The developed model is limited to the use of trapezoidal membership function in representing the subjectivity associated with the individual responses. The model validation was also limited to the use of one case example. A sensitivity analysis needs to be conducted in future work in order to investigate the impact of the organization risk maturity level on managing risk.  
Conceptualization, M.A.R. and O.M.; methodology, M.A.R. and O.M.; software, M.A.R.; validation, M.A.R. and O.M.; formal analysis, O.M.; investigation, M.A.R. and O.M.; resources, M.A.R. and O.M.; data curation, M.A.R. and O.M.; writing--original draft preparation, M.A.R.; writing--review, restructuring, organization and editing, O.M.; visualization, M.A.R.; supervision, O.M.; project administration, M.A.R.; funding acquisition, O.M. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the Mitacs under Grant IT14277.  
The authors would like to acknowledge the support provided by the members of the industrial partner in responding to the questionnaire.  
The authors declare no conflict of interest.