درخت حوزه‌های تخصصی

This study was carried out aimed to identify and prioritize the factors affecting the acceptance of electronic services from the perspective of the Iranian citizens. The present study is considered as an applied-developmental research in terms of purpose and qualitative and quantitative research in terms of method. Library studies, interviews, and questionnaires were used to collect data. The questionnaire had face validity and Cronbach's alpha and composite reliability were used to estimate its reliability. The statistical population related to the qualitative study, included professors in the field of e-government and active executive experts working in the Ministry of Communications and Information Technology, the Administrative and Employment Organization, and the Management and Planning Organization are 17 people who were selected using targeted snowball sampling. The statistical population related to the quantitative study, included the Iranian citizens, 384 people were selected from the infinite population according to Morgan's table and were examined according to the infinite statistical population. LISREL software, SPSS and one-sample t-test were used to analyze the data. According to the results, the factor of citizens 'efficiency, perceived usefulness, perceived ease have the greatest impact on the acceptance of electronic services from the citizens' point of view, respectively.

Identification of persistence component of inflation and prediction about future inflation structure is a crucial ingredient of an inflation targeting strategies or other related monetary policies. Monetary policy makers perform this task by extracting the measure known as “core inflation”. This measure is a good indicator for tracking trend of inflation and forecasting future inflation. Measures of core inflation was developed by using wavelet methods in our research. The maximum overlap discrete wavelet transformation (MOWT) and multi resolution analysis (MRA) methods are performed for extracting core inflation in period 1381(1)-1400(3) in Iran by monthly data. Using this methods is relatively new in the literature and are ideally appropriated for this task. The best wavelet in each wavelet families choose in accordance with Shannon entropy and logarithm of energy. On the other hand the properties of wavelet-based core inflation measure was evaluated by some tests. The results reveal that our new measure is more superior to the traditional approaches that used in previous studies in Iran.       

Value at Risk model based on a switching regime approach was used in this study to optimize portfolios consisting of industry index (petroleum products, investment, chemical products, and metal products). For this purpose, the VaR of returns on index should first be extracted through parametric models of the (GARCH) family in each of the above industries by using regime transitions. After the risk of return on index is obtained for each industry, the optimal portfolio is created in the next step based on VaR minimization, and the optimal value of each industry is determined in the portfolio. According to the results, (MRS-FIEGARCH) model had no superiority in VaR estimation over the other parametric models of the GARCH family. In fact (MS-EGARCH-t) was introduced as the optimal model. Among the designated industries, returns on indices followed regime transitions only in chemical products and investment by showing asymmetric reactions to external shocks. Moreover, the optimal weights were on the rise in the industries where VaR decreased over time, whereas the optimal weight of the portfolio decreased in the industries where VaR increased over time. The higher share of an optimal portfolio belonged to the industries where stock returns had lower rates of VaR. The risk-return-ratio was employed to show that the optimal portfolio with a risk rate was measured by considering the switching regime was superior over the optimal portfolio with a risk rate extracted without considering the switching effects. To create an optimal portfolio, it is then recommended to make investments in the industries characterized by higher stability in prices and lower fluctuations in stock returns in the long run. This approach can be employed to obtain the best results from optimal portfolio preparation in the worst-case scenario of the market fluctuations.