MODERN RESEARCHES IN DECISION MAKING
Year:2022 | Volume:6 | Issue:4|Papers Count:4

Today, the need to use efficiency measurement systems in the modern banking industry has become increasingly apparent. Therefore, the efficiency of banks needs to be forecasted so that future economic growth can be monitored in future decisions. This paper designs a new integrated model based on the Stochastic Data Envelopment Analysis (SDEA) model and the Principal Component Analysis (PCA) method in a dynamic environment to forecast the efficiency of branches in the modern banking industry by considering variable returns to scale for them. In order to deal with the uncertainty in efficiency forecasting, the inputs and outputs of the branches are designed as triangular fuzzy stochastic variables with normal distribution. In this study, Monte Carlo (MC) simulation and meta-heuristic algorithms have been used to solve the proposed model. Finally, in order to evaluate the performance and accuracy of the proposed integrated model, a case study based on modern banking indicators has been presented to forecast the efficiency of the future financial period of the branches and the results have been analyzed.

Today, social media has become a place for users to comment on various topics, including consumer products, and these comments have become a valuable resource for sentiments analyzing and extracting customer expectations of products. This subject provides companies with a good opportunity to redesign their products based on user feedback. In this study, to provide recommendations to the design units of detergent products, we used sentiment analysis of customers and consumers of this products on social media. More than 4200 tweets were extracted from Twitter in 2019 based on the research topic and refined and tagged during the pre-processing of the texts. Afterwards, we analyzed the emotions using fuzzy logic and topic modeling. We have used topic modeling to find the features mentioned in the comments for a better approach in the design units, and fuzzy logic to obtain the degree of polarity of ideas into 5 categories: very positive, positive, neutral, negative and very negative. We used confusion matrix for evaluating research model and an accuracy of 86. 15 % has been recorded. In this research Python libraries are used for data gathering, cleansing and analysis.

The management of production and distribution of electricity is one of the most important issues in developing countries and it is the framework for development. Because of limitations and different technologies and existence of so many factors on electricity management, consideration such problem as a single level approach is not reasonable. So, in this paper a bi-level follower leader approach is considered in which the follower is the company of Iran management network electricity and the leaders are some operation companies. Based on the accomplished researches, this paper is the first bi level attempt in the field of production and transmission management of electricity and it is localized with the special specifications in Iran. The objective function is minimizing the emission cost of greenhouse effect and distribution costs and consumed fuels and startup for follower and leader respectively. Because of high complexity of presented model, a Simulated Annealing is used for solving the problem. The results of current study could be used for improvement of Iran management network.

Investigating dynamic relationships among effective variables for sustainable industrial development can help to understand the industrial ecosystem's behavioral responses to development policies. The purpose of this study is to develop a system dynamics model for sustainable development and development policy evaluation model in Aras free zone. In this paper, system dynamics modeling framework has been used to understand the interactions among social, economic, and environmental components. In the next step, the robustness of the model is examined using time series data between 2008 and 2018. Thereafter, sensitivity analysis has been conducted to evaluate the influence of the possible changes in the key drivers through simulation technique on policy efficiency in Aras economic region. The simulation results show that the development in the manufacturing industry based on the advice from the "Development in Aras economic zone" Scheme has led to the situation where the carrying capacity has been failed, hence the sustainability goals are unattainable. the results show that the service section has the least destructionto the environment. Developing industrial development strategies by considering its environmental and social dimensions and directing investments to the service sector can be considered as solutions to achieve the goals of sustainable development of the Aras Free Zone.