درخت حوزه‌های تخصصی

One of the most important applications of data envelopment analysis tech-nique is measuring the efficiency of bank branches. Performance measure-ment in the banking industry is important for several groups, including bank managers, customers, investors, and shareholders. The purpose of this study is to examine and design a mixed structure to measure the efficiency of branches of Iranian banks according to their policies. In order to obtain the efficiency of the structure divisions proposed in this study, a slack-based NDEA model was selected to solve its mathematical model. The study sam-ple consists of 31 branches of a large commercial bank in Iran. The ad-vantage of this research to previous studies is that the result will be more realistic considering the inputs and outputs consistent with Iran's banking conditions.

One of the main concerns of investors is the evaluation of the return on investment, which is conducted using various models such as the CAPM (single-factor model), Fama-French three/five-factor models, and Roy and Shijin’s six-factor model and other models known as multi-factor models. Despite the widespread use of these models, their major drawbacks include sensitivity to unexpected changes, sudden shocks, high turbulence of price bubble, and so on. To eliminate such negatives, the multi-factor model using the penalty function method is used, in which, instead of averaging, the optimization and avoidance of the effects of abnormal changes and other factors affecting the capital market are considered. In order to evaluate stock returns, it is possible to select effective factors, to simulate and develop a model appropriate to the conditions governing the capital market in Iran. In the present study, by forming portfolios of investments and identifying and refining effective factors, the classification and estimation of the hybrid model of penalty and multi-factor (P & PCA) functions were performed based on the functional data during 2007-2017. The results of this study indicated that the extensive use of the simulation algorithm for the penalty function in the form of P & PCA estimation method improves the efficiency of multi-factor methods in stock return evaluation, and that the use of the hybrid algorithm of penalty and multi-factor functions, compared to the exclusive use of multi-factor models, brings a higher accuracy in estimating stock returns.

The emergence of new issues and complexity of them, involve formulating and implementing intelligent policies in government. Therefore, the concept of ”policy capacity” has been emerged in different dimensions of governance. Promoting the policy-making capacity of government, means the ability of government in identification of issues, formulating of high quality and convenience policies and coordinating of policymaking process. In this regards, This Research is going to design a model to explore the different elements of policymaking capacity in government. Therefore, drawing upon mixed method design, in the first step by using semi-structured interview, many data was collect and in a recursive way, the core categories of policymaking capacity extracted and named. According to model, the institutional factors, policy-making infrastructure, policymaking capability, and interaction with environment, recognized as a causal condition for policymaking capacity. In addition, in our grounded theory model, the category of good policymaking considered as a strategy for core category (policymaking capacity). In addition, the intervening variables and contextual conditions in implementing good policymaking strategy in government extracted and named. The categories of organizational and managerial capacity along with extra role capacity of policy maker constitute the intervening condition of government. Contextual conditions that influence in good policymaking strategy were named in five categories of international, social, political, economic, and technological conditions. Finally, the consequences of implementing good policy making in government were named in three categories of governmental consequence, national consequence and policy maker consequence. In the second phase of the research, all parts of the policy making capacity theory, using structural equation model were tested in AMOS graph 18. Research Results Show Significance of Measurement and Structural Models at the 0.95 Confidence Level .

This study aimed to investigate the impact of authentic leadership on psychological well-being and job satisfaction with mediating role of psychological capital among employees at Ministry of Sports and Youths. This was causal-applied study. The population consisted of all employees and managers at Ministry of Sports and Youth in 2018 (N= 831). The research tools included Avolio et al. Authentic Leadership Questionnaire, Luthans’s Psychological Capital Scale, Minnesota’s Job Satisfaction Standard Questionnaire, and Ryff's Psychological Well-being questionnaire. The collected data were analyzed using partial least square (Smart PLS) and SPSS. Also, Sobel test and VAF were used to measure the impact and t–value of psychological capital. The findings showed that the authentic leadership impacted directly and indirectly on psychological well-being and job satisfaction of staff at Ministry of Sports and Youth with mediating role of psychological capital.

One of the most important effective factors in the economic growth is the increased efficiency of manufacturing sectors. Thus, it is necessary to review and measure the efficiency of business units from a variety of dimensions to plan the increase of efficiency in future courses. One of these dimensions is the economics to scale (ES) referring to the concept of enhanced earnings due to the increased manufacturing unit, which may be of an increasing, fixed or decreasing trend. ES can be measured through economic production functions. This paper has applied Translog production function to measure corporates' ES. Therefore, data of 105 manufacturing corporates have been collected during 2008-2017. With regard to linearity between independent variables, the elastic net regression method has been used. Results indicate that some industries are of increasing economics to scale trend and some have a decreasing ES. Results can be applied in order to plan and determine the appropriate production level in the management accounting of corporates.

Banks are the financial institutions that collect assets from various sources and allocate them to the sectors that require liquidity. Therefore, banks are an inherent element in the system of every country. As private banks enter financial markets, the demand for diverse banking services increases dramatically. Banks seek to use various techniques to improve their performance in attracting customers to increase their market share and profitability. In this regard, assessing the performance of banks is of utmost importance and has become a major activity of bank managers. With the constant changes in the modern world and incessant attempts of competitors to increase their market share by gaining competitive advantage, special attention should be paid to ambidexterity as a key strategy to increase competitive advantage and achieve high performance in dynamic business environments. The present study aimed to identify the ambidextrous factors affecting the performance of banks and present a model to assess the performance of an ambidextrous bank using an agent-based modeling approach. The main objective of the research is to achieve an applied model for managing the performance of the banking industry. The simulation model is processed using the agent-based modeling approach in AnyLogic software environment.

Investment decision making is one of the key issues in financial management. Selecting the appropriate tools and techniques that can make optimal portfolio is one of the main objectives of the investment world. This study tries to optimize the decision making in stock selection or the optimization of the portfolio by means of the artificial colony of honey bee algorithm. To determine the effectiveness of the algorithm, its sharp criteria was calculated and compared with the portfolio made up of genes and ant colony algorithms. The sample consisted of active firms listed on the Tehran Stock Exchange from 2005 to 2015. The sample selected by the systematic removal method. The findings show that artificial bee colony algorithm functions better than the genetic and ant colony algorithms in terms of portfolio formation

The purpose of this study is to investigate and identify the periods of formation and bursting of speculative bubbles in Iran's capital market by creating a state space model and two-mode switching regime (mode 1 is bubble growth and burst stage and mode 2 is the time of bubble loss) during the period from April 2011 to March 2018. The Oxmetrics 7 software is used to investigate the existence of multiple bubbles and research objective. The results of the study of the state space switches confirm the bubble of the capital market in Iran during four periods in the research domain. The life span of the first speculative bubble is 2 months from October to November 2011, the second is 8 months from March to October 2013, the third is 3 months from December 2015 to February 2016, and the fourth period of bubble is 5 months from August to December 2017. Therefore, the result of the research stipulates that the stock index of the Iranian capital market in the realm of research time period has had 18 months of bubbles and has spent 66 months in balance.