علیرضا پاکدین امیری

The purpose of this paper is to investigate the effective factors on corporate entrepreneurship barriers in Ministry of Interior to understand the challenges facing corporate entrepreneurship. The population and sample were 532 and 213 respectively. The method of sampling is random and grouped sampling. The data are collected by using tools like the documents, interviews and questionnaires in the form of non-experimental research. The reliability coefficient obtained is 0.8744 and, at the end, explains the barriers of corporate entrepreneurship. The results represents that among three main variables of the model including internal, environmental and synthetic barriers, synthetic variables are the most important ones in this process. Also, due to internal barriers, two variables containing human resource management and structural variables are of high priority. In the field of environmental barriers, information technology and in synthetic barriers, information and communication variables are the most important.

The target of this research is recognizing and ranking of effective individual behavior factors on driving violations reducing by TAPSIS algorithm. So, we have been comprehensive review about relative topical literature to behavior al factors. We collect required data with using of proofs and documents consult, interview and questioner in form of metrical no experimental research method for priority allocation by using TAPSIS algorithm. Research consequences show that introverted personality, educations remembrance show that introverted personality, educations remembrance, intelligential ability, motivation, experiment and positive maintenance have high priority.

The object of this research is to present a prediction model of price index in Tehran stock exchange using artificial neural networks. For this reason, the industry index, financial index and the annual TEDIX index were introduced as (independent) input variables. The MLP plan accompanied with post-processing algorithm and multi-factor model have been used to evaluate neural network model. The results suggest that the proposed neural networks model is potent of predicting price index in Tehran stock exchange. In the closing part,conclusion has been drawn and applicable suggestions and also directions have been given concerning pursuing and following up similar researches.

The goal of this research was prioritize effective financial factors on price stock in Tehran stock exchange with using TOPSIS method. Based on, it was reviewed literature and interviews and specially questionnaire obtain, effective financial factors to analysis with emphasize on TOPSIS technique. The results shown in the entire ratio price to income, historical event share, EPS and return on assets factors were most effect on price index. Finally, it is presented concluding, discussion, implications for managers, and directions for further research.The goal of this research was prioritize effective financial factors on price stock in Tehran stock exchange with using TOPSIS method. Based on, it was reviewed literature and interviews and specially questionnaire obtain, effective financial factors to analysis with emphasize on TOPSIS technique. The results shown in the entire ratio price to income, historical event share, EPS and return on assets factors were most effect on price index. Finally, it is presented concluding, discussion, implications for managers, and directions for further research.