درخت حوزه‌های تخصصی

The agricultural sector in developing countries plays an important role in promoting national development and rational policy making and strategic planning to advance the sustainable development of this sector are of main concerns of the relevant institutional actors. In this regard, the current research was conducted with the aim of identifying scenarios of sustainable agricultural development in the catchment area of Zayandeh River in Isfahan province. The present research was applied, of descriptive-survey type. The statistical population was experts related to agricultural development in the province. To collect data, library sources, questionnaires and interviews were used. Delphi method and interviews with elites and executives were used to identify the primary components and drivers effective on the sustainable development of agriculture in the Zayandeh River watershed of Isfahan province. The snowball technique was used to select the experts. Finally, 8 key drivers were identified and separated in order to explain the research variables in a strategic format. Based on this, in the section related to the expression of research priorities in two direct and indirect modes, these 8 key factors have been repeated in different priorities. Questionnaires were distributed among 25 experts. In this study, five plausible scenarios were identified for forecasting the future of sustainable agricultural development by considering potential outcomes based on key factors and their similarities or differences across the categories of favorable, static, and critical scenarios. Based on their total scores, which range from 85 to 109, two scenarios were identified as the most likely: one favorable scenario and one critical scenario.

The investment decisions of managers of investment funds (especially equity investment funds) have an impression on the returns of individuals who have deposited their capital in these funds. Therefore, the issue of evaluating the performance of investment funds and their managers is imperative for investors. The research aims to investigate the effect of cross-sectional alpha dispersion on investors' evaluation of the performance of investment funds. We extract data regarding 31 equity investment funds from 2012 till 2022 and calculate the interquartile ratio of Jensen's alpha called "IQR" and "Performance-Flow Sensitivity" along with control variables. Then, the hypothesis test model was fitted using the multivariate regression analysis using the Generalized Least Squares method. Empirical findings show a negative and significant connection between the alpha dispersion of investment funds and performance-flow sensitivity. Based on the results, one credit increase in the standard deviation of alpha dispersion leads to a decrease of about 0.4% in the ratio of performance-flow sensitivity. Environments with high alpha dispersion of investment funds will targeted by unskilled managers to introduce themselves as successful and skilled managers to investors and mislead them. Therefore, when the alpha of investment funds has a higher dispersion, the type I error possibility investors will face increases. Individuals may consider an inefficient manager to be competent and skilled. We will provide some suggestions in this regard.

In order to survive and compete with other financial institutions, banks, and financial institutions are required always to evaluate the efficiency of their branches. In this paper, we evaluate and analyze the efficiency of bank branches in the five last years (from 2018 to 2022). To calculate and present the branch efficiency score, we have considered an undesirable component called Nonperforming Loans (NPL) as an undesirable output in evaluating the efficiency of Tose'e Ta'avon Bank branches. Due to the high inflation in Iran, the increase in the NPL of loans causes a decrease in the banks' deposits and profitability, and ultimately, it causes a considerable decrease in inefficiency. In addition, in extreme cases, it may even cause the bank to go bankrupt. Therefore, to calculate the efficiency of the Tose'e Ta'avon Bank branches using the data envelopment analysis method, we have considered operating costs and non-operating costs as two inputs, total deposits, total loans, and also two categories of revenue (Revenue from Jointly Funded Assets and Fee-based incomes as four desirable outputs and based on Islamic banking methods with Nonperforming loans as an undesirable output. In this paper, to deal with undesirable output issues, we use a direct approach that is more suitable to deal with NPLs since it is more convenient and evident to incorporate undesirable outputs directly into the DEA model. We used the dynamic cross-efficiency technique of DEA with undesirable outputs (DEA-UO) to obtain the efficiency of the branches over five years.