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Purpose Identifying and prioritizing the risks are considered as critical issues in risk management; otherwise, non-considering the risks will lead to the problems such as delays in project implementation, increased costs, loss of reputation, loss of clients, reduced revenue and liquidity and even bankruptcy. The paper aims to discuss these issues. Design/methodology/approach In this paper, the factors influencing the organization risk tolerance level were identified. Then, the factors increasing and decreasing the risk tolerance level were determined by a decision-making model. Finally, a comprehensive model was considered for risk measuring and preparing a risk failure structure chart, in order to determine the factors influencing it as well as the measurement criteria and then they were ranked using the taxonomy method. In this study, the size of the statistical population was 130 (six small and medium manufacturer and service provider companies). Based on Cochran’s sample size formula, 97 questionnaires containing 30 questions were randomly distributed among the population. Validity and reliability of the questionnaire were confirmed. The data were analyzed by SPSS 22. Findings Given the hypotheses of this study, the first hypothesis was rejected and the other hypotheses were accepted. The final ranking was done using the taxonomy method; the personality of the project manager was ranked at first; income, credit and capital were ranked second and the number of personnel was ranked third. Moreover, the TOPSIS method was used for ranking to compare the results. Originality/value In this research, the identification and ranking of these factors have taken place in several small- and medium-sized organizations; in addition, the rankings are conducted using the taxonomy decision-making method.

Due to the increasing demand for metals, the extractable grade of metal deposits has been decreasing and caused an increase in the amount of tailings. Increase in the volume of tailings requires proper attention to tailings disposal, the establishment of tailings dams, water consumption and prevention of environmental and groundwater pollution. Since tailings disposal consists of many stages such as discharge, thickening technology and location, and transportation, selection of the best disposal method is a complicated task. Nowadays, decision-making methods are widely used and they are very reliable and efficient. Therefore, a model based on fuzzy analytic hierarchy process (AHP) has been developed in this study to optimize tailings disposal method selection. In the model, 21 criteria and a wide range of alternatives have been introduced. The model has been applied to the Sangan Iron Ore Project (SIOP). The concentrator plant of SIOP will produce 75 million tons of tailings during the mine lifetime. Since the current disposal method wastes 1.5 million cubic metres of water annually and the project is located in a dry region, the proposed model has been used to investigate other options and the results show the filtered technique is the best alternative.