The project portfolio is to transfer the strategic needs of the organization to projects and operational activities. If portfolio risk occurs, it can affect the portfolio success metrics and overshadow the achievement of the organization's strategic goals. Despite the important role of portfolio risk management in the success of an organization, no proper analysis of project portfolio risks has been provided yet. The purpose of this study is to investigate the importance of portfolio risks and, selection of the best portfolio risk management strategy using multi-criteria decision-making methods. Due to the ignorance of portfolio level risks, the first step of this research is to identify and select important portfolio risks of projects based on previous studies in this field. The importance of risks in different portfolio management strategies was then assessed using a questionnaire from a group of elites. In this study, the CRITIC method, which is a multi-criteria decision-making method has been used to determine the weight of each risk, during which the importance of each risk is calculated without direct questions from experts, and only using the scores given to each risk in different strategies. After that, different portfolio risk management strategies will be identified and, the best risk management response will be calculated and selected.

Multiple Criteria Decision Analysis (MCDA) has been widely investigated and successfully applied to many fields,owing to its great capability of modeling the process of actual decision-making problems and establishing proper evaluation and assessment mechanisms. With the development of management and economics, real-world decision-making problem are becoming diversified and complicated to an increasing extent, especially within a changeable and unpredictable enviroment. Multi-criteria is a decision-making technique that explicitly evaluates numerous contradictory criteria. TOPSIS is a well-known multi-criteria decision-making process. The goal of this research is to use TOPSIS to solve MCDM problems in a Pythagorean fuzzy environment. The distance between two Pythagorean fuzzy numbers is utilized to create the model using the spherical distance measure. To construct a ranking order of alternatives and determine the best one,the revised index approach is utilized. Finally, we look at a set of MCDM problems to show how the proposed method and approach work in practice. In addition, it shows comparative data from the relative closeness and updated index methods.

An enterprise resource planning (ERP) software is needed for industries and companies that want to develop in future. Many of the manufactures and companies have a problem with ERP software selection. An inappropriate selection process can affect both the implementation and the performance of the company significantly. Although several models are proposed to solve this problem many of them did not consider uncertainty as an effective environmental factor. In the current paper a new model is designed. This model is based on balanced score card (BSC) and in addition, uncertainty is considered. This paper used three-parameter interval grey numbers concept that derived from Grey-theory in order to reduce uncertainty. Beside, hybrid model for weighting based on Shapley and Entropy methods are used. This combination approach is also because of reducing uncertainty. And at the end, a new method named projection attribute function method is used for ranking. There is a case study at the end of this paper that shows how this model works.

Landslide hazards are relatively frequent in the mountainous region of Northern Iran. This paper aimed to utilize the potential application of a GIS-based multi-criteria decision-making model (MCDM) to evaluate and landslide susceptibility mapping in the Arabdagh forests, Golestan Province, northern Iran. A ground truth landslide map was prepared using aerial photographs and high-resolution satellite images interpretation, and field surveys. The landslide influencing factors maps were produced and used as thematic layers in the analysis (criteria and sub criteria). The landslide susceptibility map of the study area was produced by weighted linear combination (WLC) model based on AHP weights of factors. The resulting landslide susceptibility map was classified into five relative susceptibility zones according to the natural break method: very low, low, moderate, high, and very high with an area of 5.1%, 26.1%, 31.7%, 24.4%, and 12.8% of the total study area, respectively. The validation of the susceptibility map was performed using receiver operating characteristics (ROC) and area under the curve (AUC). The validation results showed the area under the curve of 0.852 (85.2%) with a standard error of 0.036. The susceptibility risk rate in the areas where are mainly shrub and herb lands is high and very high.

Financial decision-making is a principal part of any decisions; hence, great efforts are made to improve the methods to assess and analyze the stocks in financial markets as an important part of the financial decisions. This paper addresses the stock selection by discovering the investor's utility function. Investors in the Stock Exchange consider diverse criteria to buy securities and bonds. Due to the criteria development in stock selection, understanding the investor's behavior by a consultant is a prominent issue. Recognizing an exclusive utility function, according to the characteristics of the investors, facilitates acquiring each share's value for the decision-maker (DM). In this study, UTASTAR method is used to estimate the marginal value function by using 3 appropriate criteria (risk, return, and liquidity) and, finally, fit the total utility function. It provides an opportunity to make a rational decision adjustable to the investor's mentality that considers their ranking, prioritization, selection, or classification. The ranking of the options is as compatible as possible to the original one. The method is applied to an example from Iran Stock Exchange.

Aim&Background: with increasing the unreliability in the competitive and dynamic environment of the market, caring the supply chain resilience is important. whose start point is selection of resilient suppliers. Steel makers as one of the most important and vital industries of the country due to market disturbance and increase of currency price have have encountered raw materials supply problem specially iron ore supply. The aim of this research is to identify criteria of the resilient suppliers in the steel industry of Chaharmahal and Bakhtiari and rank it. method: This research is of applicative kind which has been done by qualitative and quantitative method. During the aimed sampling, 10 of the experts acquainted with the research has been selected. In the qualitative section, Criteria affect the resilient supplier selection using theme analysis and during interview with experts has been identified. Then in the quantitative section weight of criteria was calculated using hierarchical analysis and the ranking of the 3 raw material supplier companies has been done using new MARCOS multi-criterion decision making method. Findings: In the qualitative section six criteria including information technology, delivery, safety, enviromental and social issues, quality, flexibility and agility using theme analysis and during interview with experts has been identified. After criteria weights were determined agility has been identified as the most important criterion. Ranking of suppliers was done using MARCOS method and it is showed that the acquired results using MARCOS method is compatible with the results of VIKOR, TOPSIS, COPRAS, and QULAIFLEX methods. Also it was showed that MARCOS method is sensible to probable changes in decision making criteria importance and method stability in supplier selection at the various circumstances of suppliers has been showed. Conclusion: Criteria which is determined in this research is compatible with criteria which was determined in previous researches. Also MARCOS method is simple, effective and stable for ranking the suppliers at the dynamic circumstances.