درخت حوزه‌های تخصصی

In order to survive in the modern world, organizations must be equipped with the mechanisms that not only maintain their competitive advantage, but also result in their progress and improvement. Prediction of banks’ performances is an important issue, and a poor performance in banks may primarily lead to their bankruptcy, thereby affecting national economics. The bank performance prediction model uses scientific and systematic approaches to diagnose the financial operations of institutes. According to a precise and strict evaluation, the model can detect the weakness of institutions in advance and provide early warning signals to related financial governments. In the present study, we have used three data mining models to predict the future performance of the banks accepted in Tehran Stock Exchange (TSE) and Iran Fara Bourse. Initially, 53 financial ratios were selected and, consequently, reduced to 28 using the fuzzy Delphi technique. The statistical population included 18 banks listed on TSE and Iran Fara Bourse, which   provided their financial statements during the period of 2011 to 2017. Data were collected from the Codal site based on 28 financial ratios using C4.5 decision tree, AdaBoost, and Naïve Bayes algorithm. According to the findings, the Naïve Bayes algorithm was the optimal predictive model with the accuracy of 88.89%.

One of the main causes of firms’ ineffectiveness is the absence or insufficiency of appropriate investment methods. This deficiency could also be attributed to an unfortunate selecting of an inappropriate investment methods which may ultimately endanger the firms’ prospect of survival. According to the firm life cycle theory, various firms demonstrate diverse behavior when provided with an investment opportunity. These responses are largely in accordance with the stage of the life cycle in which the firm resides in at that moment. In this research, the selection of the investment method appropriate for a firm has been studied following the premises of the life cycle theory. The target populations of this study were companies admitted to Tehran Stock Exchange. Systematic removal method was adopted to recruit a sample of 118 firms. The study period was 8 years (2011-2018).  Findings suggest that firms choose to invest in operational properties when they are at the stage of growth, maturity and decline. In other words, the capital under the companies’ authority and control were employed for the firms’ mainstream activities. However, such a link was not found at the introduction stage of their life cycle. This relation has been illustrated in various industries.

The Stock Exchange is a private sector savings and liquidity fund to fund long-term investment projects. The indicators of this market are influenced by several factors, one of which are economic variables. Banks are also one of the most important investors in the financial market. In this study, the effect of exchange rate, bank interest rate, liquidity and inflation rate on stock price index using time series data of 1978-1988 and using equation system model of four equations of the stock price index, inflation rate, profit rate Deposits, and facility interest rates were estimated using the three-stage least squares method. The results showed that the effect of the exchange rate, deposit interest rate and positive liquidity volume and the effect of inflation rate on stock price index was negative. Other equations have been estimated because of the relationship between the bank interest rate and inflation rate, and the results show that both deposit interest rate and facility interest rate have a positive relationship with the inflation rate

Strategic management accounting, including systems and processes in the modern era, is characterized by changes in the competitive environment that, Can be achieved through the participation of companies in the management accounting system, Assist financial managers to make decisions in the value chain and develop green accounting functions. Unfortunately, though, over time, strategic management accounting techniques are still unknown to corporate executives, especially in environmental processes, leading to a decline in corporate participation in strategic decision making. The Purpose of this research is Capacity Building Green Accounting Consequences Based on Explanation of Strategic Management Accounting Techniques by analysis of CARD and developed the theory of Rough (ERST). The methodology of this research is developmental, applied and hybrid and two groups of target population participated in this research. In the first part of 15 experts in the field of accounting at the university level an In the second part, 35 executives participated matrix Tehran Stock Exchange through a questionnaire that both the target population, sampling was homogenous. In this research, in the qualitative part, the components and indices related to the research variables were selected based on content analysis and cross-analysis and then based on Delphi analysis and hierarchical analysis in order to achieve theoretical adequacy. Then, in the quantitative section, through the analysis of the Rough Complex analysis, the decision tree determined the most effective green accounting function/outcome and strategic management accounting technique, and finally, the product life cycle costing technique is the most effective strategic management accounting technique for enhancing green accounting functions. In fact, the results showed that product cycle costing technique is a factor for enhancing the cost savings of recycling and waste recycling costs and increasing the competitiveness of the company as a component of green accounting competitive Consequences.