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Risks mean cases of uncertainty of project, the impact of which is realized as a threat (negative aspect) and/or opportunity (positive aspect). The traditional viewpoint on risk is a negative viewpoint that implies damages, loss and harmful consequences. Judgments such as this on risk merely emphasize on risks management and pay less attention to opportunities management. It is clear that some uncertainties might be profitable for the project as in many cases, it could be the source of loss. In a developed attitude, focus is made on a common process that could address the integrated management of both opportunities and risks to aim at maximizing the positive effectsopportunities-, and minimizing negative effects- risks-. Therefore, existence of causal-effect relations between risks, relationship, effects of risks and opportunities on each other and variety of strategies in facing risks gives no alternative for risk management team than taking integrated management of risks and opportunities. In another word, reaction to risks, with respect to risks and/or relevant opportunities, separately, will be never effective. In this paper, for the purpose of integrated management of risks and opportunities, the stages of quality analysis and reactions to risk are combined. The method which is used for reaction towards risk is a procedure based on dynamic system. Dynamic system is highly important among uncertainties due to considering the type and intensity of effects. By using dynamic system and attention to the relationship between uncertainties (risks/ opportunities), reaction to risk and decision making on employing suitable strategies to face risks will be more precise and accurate.

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Risk allocation is the definition and division of responsibility associated with a possible future loss or gain arising from an identified risk. Quantitative approaches to risk allocation have been developed to overcome the limitations of qualitative approaches, especially the issue of the amount of risk to be borne by each party. This paper presents a cooperative-bargaining game model for quantitative risk allocation that extends the previous existing system dynamics SD-based model. The behavior of contracting parties in the quantitative risk allocation process is modeled as the players’ behavior in a game. The proposed model accounts for both the client costs and the contractor costs to perform the quantitative risk allocation process. To evaluate the performance of the proposed model, it has been employed in a pipeline project. Quantitative risk allocation is performed for the inflation as one of the most important identified risks. It is shown that using the proposed cooperative-bargaining game model, both the client and contractor costs are decreased in comparison to the previous SD-based risk allocation approach.

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Construction industries are the most dangerous worksites with high risk of occupational accident and bodily injuries, which ranges from mild to very severe cases. The aim of this study was to explore the causal factors of accident severity rate (ASR), in 13 of the biggest Iranian construction industries. In this analytical cross-sectional study, the data of registered accidents from 2009 until 2013 were obtained from an official database. Data of HSE risk management systems and HSE training were also gathered from comprehensive accident investigation reports. Data analysis and regression modeling were done using SPSS statistical software (version 22). The mean and SD of ASR of studied construction worksites was 257.52±1098.95. The results show that the system associated with HSE and HSE risk management established only 41.8 and 18.4%, respectively. The results of multiple linear regression indicated that some individual and organizational factors (IOFs), HSE training factors (HTFs), and Risk Management System factors (RMSFs) were significantly associated with ASR (p<0.05). The study revealed the causal factors of ASR. Hence, these findings can be applied in the design and implementation of a comprehensive HSE risk management system to reduce ASR.