FUZZY AHP

Abstract: One of the basic priorities of any country is to designate appropriate financial strategy to reach an optimized education system to to tenure different jobs. The goal of this research is to determine criteria of importance and skills and knowledge ranking needed by Accounting graduates in order to achieve future financial success. To have access to the research goal, accounting education skills related variables recognized and categorized into 7 principal components (strategic management, analyzing skills, leadership skills, increasing capabilities skills, general skills of Accounting, communication skills and personality skills) are selected and the fuzzy AHP is utilized to data analysis. Research results show that strategic management is placed as the first priority and communication skills is considered as the last one according to professionals' points of view.

INTRODUCTION: Iran has always been prone to natural disasters, such as hurricanes and earthquakes, which are followed by heavy financial and bodily harms. In this regard, it is crucial to have disaster management in the schools of Iran to protect the significant number of young people studying in schools. Therefore, school principals must be constantly prepared for disasters and develop disaster management plans. METHODS: The present study aimed to identify and prioritize the factors that affect the natural disaster preparedness of schools using the fuzzy analytic hierarchy process (FAHP) method. Moreover, another objective of this research was to rank the elementary schools in District 6 of Mashhad regarding their disaster preparedness with the fuzzy technique for order preference by similarity to ideal solution (FTOPSIS). In this research, first, the criteria and sub-criteria for disaster preparedness were obtained using the Delphi method and according to the opinions of experts. Afterward, the collected criteria and sub-criteria were ranked using the FAHP method. The statistical population of this research consisted of experts, including principals and experts in the studied schools (schools in District 6 of Mashhad) who were familiar with disaster management issues. In total, 10 experts were selected as the sample using the purposive sampling method. FINDINGS: Based on the results, the most important disaster preparedness factors in schools were building retrofit, adherence to basic standards, and committee formation, in that order. CONCLUSION: Finally, the elementary schools of District 6 of Mashhad were ranked in terms of disaster preparedness using the obtained model and the FTOPSIS. This ranking can help the managers in making decisions to prioritize the conduction of building retrofit of the schools in the studied area.

Nowadays, most of Businesses have faced a great challenge for entering a new market. The existence conditions have forced the managers to apply the innovative methods for simultaneous analyzing of various factors for arrival to special markets. This paper prioritizes a few target markets using two methods. First, the problem is solved by the combined method of hierarchical analysis and Monte Carlo simulation, and then by the method of fuzzy hierarchical analysis and finally the results of both methods are compared. The considered problem in this study relates to a factory of prefabricated building components that is looking for establishing the sale agencies in appropriate towns in order to introduce and distribute the new products. In order to prioritize cities, desired criteria are determined through interviews with experts and investigating the previous studies. The research findings have shown that based on the four main criteria and seven related sub-criteria, the prioritization of selected cities as markets has been A-D-C-B respectively. In the end, it is concluded that based on the findings of this study, managers and stakeholders should pay attention to these priorities in choosing the target market. In this research, for the first time, the combined Monte Carlo technique and hierarchical analysis have been used to select the market. Market selection is one of the issues that has always been a concern of managers and has been associated with a lot of risk. Using Monte Carlo simulation algorithm and hierarchical analysis, by considering different decision intervals, greatly reduces the risk of selection, so this technique is recommended to managers of organizations as a practical method in market selection.