Development of a risk assessment methodology and safety management model for the building construction industry: case studies from Thailand

The building construction industry is growing all over the world and considered as a labour-intensive industry. It is associated with significant safety risks and losses resulting from major accidents. These critical safety risks are largely due to lack of awareness, which causes poor performance. Furthermore, in construction management projects, risk assessment tools are still widely employed by adopting two traditional parameters, severity of consequence (SC) and probability of occurrence (PO), to analyse the safety risk level. It is not clear, however, whether this analysis can evaluate the safety risk magnitude appropriately, which necessitates the introduction of another parameter, probability of consequence (PC), to improve the risk evaluation. The fuzzy reasoning technique (FRT) is useful for quantifying and dealing effectively with the lack of certainty related to the domain of building construction projects. PC was incorporated into the model which allows safety risks to be assessed correctly. Furthermore, the modified fuzzy analytical hierarchy process (MFAHP) and fuzzy technique for order preference by similarity to ideal solution (FTOPSIS) methods are integrated into a new construction safety risks model for the evaluation of important safety risks. Four specific case studies are employed to illustrate the applicability and performance of the proposed model. This research contributes significantly to construction safety management projects and can be utilised to analyse and manipulate the safety risk level of every possible hazardous event that is identified during the construction period. The proposed model could also be applied in other construction projects to obtain results with greater accuracy and reliability from the evaluation and ranking of safety risks, which would yield data that would be useful in helping the management team to mitigate and control the risks in other construction projects.