جستجوی مقالات مرتبط با کلیدواژه « بورس اوراق بهادار تهران » در نشریات گروه « صنایع »

Performance evaluation is one of the most significant issues in management taken into consideration by a number of academics and researchers who have developed various parametric and non-parametric methods used for performance measurement and evaluation. Among these models, Data Envelopment Analysis (DEA) is regarded as one of the most widely used models for performance evaluation. DEA is a powerful mathematical tool and a non-parametric technique to measure the relative efficiency of a group of homogeneous Decision-Making Units (DMUs). This approach carried out an evaluation by assigning weights to the inputs and outputs of each decision-making unit. The difference in the input and output weights in this technique is one of the objections to this method that threatens the assessment of the underlying basis. In this study, a model was presented to find a solution to this problem. The proposed model is a one-phase linear model and has less computational complexity than other models. To validate this model, the numerical exam of Kao & Hung (2005) was implemented and the results of the presented model were compared with those of other models; in addition, the Spearman correlation coefficient was calculated. The results showed that the proposed model had a more significant correlation coefficient than other models, had a more resolution than other models, and eliminated the shortcomings of Classic base models. After the validation of the model, the pharmaceutical companies in Tehran Stock Exchange were evaluated by means of the proposed model and CCR model. The indices of the study were obtained from previous studies and the opinions of experts were taken into account to confirm these indices. The data used in the present study and the actual values of these indices were obtained from ``codal.ir website'' according to each company's financial status. Moreover, sensitivity analysis was performed on the outputs of these companies. The results showed that Alborz Pharmaceutical and Shafa Pharmaceutical Investment companies were the most effective units in both models, and Farabi Pharmaceutical Company was the most inefficient one. Besides, the results indicated that the units under study showed more sensitivity than the first output.

Organizational agility is one of new paradigms in the field of organizations management which has been presented to reward the environmental changes and satisfying the customer needs. One of the numerous factors affecting the organizational agility is to apply the Information Technology (IT). This study investigates the relationship between the IT penetration coefficient and organizational agility. This study is of type the applied research in terms of objective and it also uses survey-descriptive and correlation method in terms of nature and method. Closed questionnaire was used for examining the variables. Population is the companies accepted in Tehran Stock Exchange in 2013-14. The questionnaire and structural equation modeling were used for analyzing the obtained data and testing the hypothesis, respectively. The results obtained from data analysis indicate that the technology acceptance combination model and organization agility model are both powerful models for anticipating the organization agility and the attitude towards the use of IT has the most effect on the organization agility.

Organizational agility is one of new paradigms in the field of organizations management which has been presented to reward the environmental changes and satisfying the customer needs. One of the numerous factors affecting the organizational agility is to apply the Information Technology (IT). This study investigates the relationship between the IT penetration coefficient and organizational agility. This study is of type the applied research in terms of objective and it also uses survey-descriptive and correlation method in terms of nature and method. Closed questionnaire was used for examining the variables. Population is the companies accepted in Tehran Stock Exchange in 2013-14. The questionnaire and structural equation modeling were used for analyzing the obtained data and testing the hypothesis, respectively. The results obtained from data analysis indicate that the technology acceptance combination model and organization agility model are both powerful models for anticipating the organization agility and the attitude towards the use of IT has the most effect on the organization agility.

In today highly competitive and changing business environment, systematic analysis of performance of the organization for determining the rate of success, detecting the deviations and their causes and exploring new ideas or finding the modification solutions, has been the principal concern of managers and organizations. The evaluation of the financial efficiency and using the financial indicators are one of the most common approaches in this way. Given the importance and urgency of this issue, in this study financial efficiency of the pharmaceutical companies listed in Tehran Stock Exchange that are working in the field of production of pharmaceutical products has been assessed and evaluated. Therefore, and in order to overcome limitations of financial ratios in this study to assess the financial efficiency of statistical sample of firms through using financial ratios, has been used the integrated approach of Data Envelopment Analysis and Balanced Scorecard (DEA-BSC).
Based on this approach and to overcome the challenges in selecting optimum combination of financial ratios, the Balanced Scorecard approach has been applied. For this purpose, the four key perspectives (financial, stakeholders, processes and growth) are considered as the basis for an explanation of the proposed financial ratios. In order to choose the right financial ratios, a panel of industry experts (experts in the field of financial and pharmaceutical fields) formed and through monitoring their specialized comments, in each perspective three ratios were selected as an indicator of financial performance measurement and then were weighted. This process will cause the appropriate influence of each indicator according to its importance in the statistical sample companies. In addition, the suitable type of data envelopment analysis approach that is consistent with the nature of the study have been selected and used. Finally, by doing the mathematical calculations and solving the relevant equations through using the operations research software (GAMS), the financial performance of each company of the statistical sample of the research was estimated and according to this basis the companies were ranked.

Generally speaking Technical Analysis Rules are a set of methods which concentrate on prices trends in order to predict the prices trend in the future. It must be mentioned that Technical Analysis Rules are many and varied and in order to make effective outcome, one must select the most useful methods which are depends on the market situation. In this paper, the profitability of 46 popular technical trading rules such as “moving average”, “trading range breakout”, “Bollinger bands”, “stochastic”, “RSI” and “MACD” in 22 company in Tehran Stock Exchange (TSE) from 1995-2005 have been evaluated. The small nature, short-selling constraints, lack of analyst coverage, and loose insider trading regulation suggest that the TSE equity market may be has less efficient. This cause that technical analysis has more potential to be profitable. To overcome the shortfalls of the t-test methodology within our test sample, the significance of the technical trading rules have been analyzed by using the bootstrap methodology with Random Walk null models. The numerical results indicate that technical trading rules have predictive ability in the mentioned companies. This result rejects the null hypothesis that the returns to be earned from applying trading rules values are equal to those achieved from a naive buy and hold strategy. This research also illustrates that among all 46 Technical Analysis Rules, “moving average” and “stochastic” are the most effective trading rules.