مطالب

Agility of the supply chain is one of the main challenges in organizations which acting in a dynamic and complex environment, which they have to be able to answer to customers quickly. But the agility of supply chain is influenced by different agents. Using the model based on agent, this study has tried to simulate the agility of supply chain in an institute of higher education. There are three impressive elements are used in this model called as: smooth, offender and fault case, which those are also categorized in two groups impressive and impressible. There is a model is designed by using NETLOGO software which examines the impression and impressibility on each other. After executing the model at the case studied university at point of Time-769, the organization’s improvement will be possible in the best estate. All offender elements are reduced at this point.

Thisstudy provided a comprehensive model for identifying and explaining factors affecting burnout of faculty members. In this study, a descriptive-exploratory method with in-depth interviews were used. It was an applied, quantitative and non-experimental research. The instrument was a researcher-made questionnaire whose items were identified based on the review of secondary sources  as well as semi-structured and structured interviews. Structural equation modeling was used to analyze findings. The results showed that all identified factors included emotional exhaustion, decrease in success, depersonalization, organizational factors, demographic factors, individual factors, organizational indifference, quality of working life, organizational commitment, occupational performance and flattening had an effect on burnout. The results showed that among the identified factors, emotional exhaustion had the most effect on the burnout of faculty members.

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.

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.