مطالب

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.