محمود مدیری

There are many opportunities and threats in the decision-making environment for managers, and an organization must use research and information systems to change, monitor, and anticipate this environment. Futurism reflects how tomorrow reality gives birth to tomorrow's reality is. The purpose of this research; Analyzing the role of futures studies in the existing patterns of critical factors of multi-criteria decision-making techniques in operations research using the philosophical assumptions of the classical and critical paradigms and finally determining the appropriate strategy based on these components, to increase success and life expectancy. The present study intends to formulate exploratory scenarios of this knowledge by using the critical uncertainty approach. To develop credible scenarios of knowledge of decision techniques, the opinions of 15 experts in this field were collected using the fuzzy Delphi approach and through the critical uncertainty questionnaire. After extracting the most important uncertainties, plausible scenarios of decision-making techniques were determined with the help of experts. According to the results obtained from the opinion of experts from the critical uncertainty questionnaire, four research uncertainties were identified, identified and the scenario design criteria were used. Each of the four cases, which includes low attention to social issues versus high attention to social issues, low attention to ethical models versus high attention to ethical models, low attention to soft approaches versus high attention to soft approaches, Low attention to complex issues versus high attention to complex issues indicates a specific dual situation in the future. Each of these dual situations indicates uncertainty about the future of multi-criteria decision making. Based on these uncertainties, three scenarios were identified. These scenarios include Achilles heel, phoenix, and heel. Also, semi-structured interviews with the theme analysis approach were used, and the philosophy of past and future approaches in this field was reviewed and critiqued.

Though financial services outsourcing has been increasing during the last decades, most outsourcing projects have failed due to qualitative criteria used in decision-making as well as being unaware of differences in environmental circumstances. This study aims at designing a model of deciding on outsourcing in state banks. The data of this applied, developmental research was collected, using descriptive-survey method and two instruments, namely, interview and quantitative were used in qualitative and quantitative sections, respectively. The sample of the study comprises of banking experts working in six state banks and the Central Bank of Iran. The initial model was derived, based on an analysis of the aspects of variables as well as the indices obtained from the theoretical principles and previous studies. The final research model, which consists of 6 factors and 22 subfactors was developed, using the Fuzzy Delphi Method and in triple consultation with 20 banking experts. The criteria were weighted, and the relationship between the criteria was examined, using F-DEMATEL method and ANP. The results of the study indicate that the following are the most significant criteria driving the decisions made by state banks on activities outsourcing: reliance on service providers, cost, the rapid delivery of services by the contractors, gaining competitive advantage, the existence of multiple contractors, improved control and overseeing.

Improving the competitiveness of businesses through investment in industrial parks is one of the challenges that managers face for economic development. This study has been done with the aim of identifying, determining relationships and providing a structural model of investment to competitive advantage in industrial parks. The data have been analyzed in two parts, qualitative and quantitative. In the qualitative part, the variables of the model were extracted using the method of content analysis and coding and confirmed by the fuzzy Delphi method, and in the quantitative part, the hierarchical structure model was presented. The statistical population of the research is 25 experts who were selected by non-probability purposeful and snowball sampling and answered the pairwise comparison questionnaire. The findings of the qualitative section showed that the model has eight variables including "infrastructure investment", "motivational investment", "economical investment", "institutional investment", "environmental investment", "support investment", "Political investment" and "competitiveness". The findings of the quantitative section showed that the structural model has six levels, that "political investment" and "infrastructure investment" have the most influence in the model and are in the first priority. We conclude that in order to competitive advantage, managers should pay more attention to technical and informational infrastructure, as well as appropriate policies and providing regulations.

The increase in non-performing loans considerably reduces profit in the banking systems. To solve these problems, factors influencing the collection of non-performing loans have to be examined in a hopeful attempt to reduce it to an ac-ceptable level. The present study is conducted to analyze and study factors influ-encing the collection of non-performing loans in Shahr Bank. This research is an applied study regarding its goal. It was conducted in two sections, namely the qualitative and quantitative sections. In the qualitative sections, the factors influ-encing the collection of receivables were identified using the theoretical literature and interviews with senior managers of Shahr Bank through the encoding process. In the quantitative section, data was collected by surveying the opinions of 12 experts, including senior managers of Shahr Bank in 2020 using a questionnaire. Thereafter, the factors were selected using the fuzzy Delphi technique and the relationships between them were determined using the fuzzy DEMATEL method. Finally, the factors were weighted and prioritized using the fuzzy ANP method. The research findings showed that non-performing loans can be collected through six types of factors including organizational, regulatory, customer, banking, envi-ronmental, and operational factors. The environmental factor is the most influential factor, while the operational factor is the most influenced and most important factor. In addition, behavioural, contextual, and structural sub-factors have the highest level of importance in the collection of non-performing loans in the order mentioned. These findings can help bank managers make decisions to improve the collection of receivables.