درخت حوزه‌های تخصصی

This research deals with integrating RE and CBC in the product design process. RE improves the product value based on evaluate the competition products, whereas CBC aims to use a process approach to define activities and prelates those activities to products or customers using the product’s Characteristics. Integrating RE and CBC together leads to the improvement of product value, an increase of customer satisfaction, and support of competitive advantage. In this study first, a conceptual model of integration of these two approaches is provided and then the implementation procedures in product design cycle are explained, and finally, the results got from implementing it in an Electronic Industries company are discussed.

Polling system is not trusted everywhere around the world it is very important in this modern world to replace the traditional polling system with the new technology. Some countries like United States, Japan, and India suffer from corrupted polling system. Major issues are faced by current polling systems like system hacking, vote rigging, vote manipulation, distributed denial of service attack, and online polling booth capturing. This paper will lead to the problems faced by the traditional polling system and how the new technology will provide the solution to that problem. Also, our purpose is to check the feasibility of the system by recording the transaction fees and evaluate the right way to spend the amount of gas in the transaction. This will highlight blockchain frameworks including blockchain as a service and polling system which is on blockchain that addresses all constraint introducing ethereum which is a blockchain-based distributed computing platform. Ethereum is open source, and publicly available with a system featuring smart contracts. It provides the cryptocurrency wallets that let you make cheap, instant payments with gas in the form of ethers. The ethereum community is the most active and largest blockchain community in the world. There is no centralized organization that controls ethereum.

During the COVID-19 pandemic, the usage of e-learning systems became the main challenge for many universities. E-learning has risen as cutting-edge method for promoting learning delivery. To ensure productive use, it is important to continue using e-learning. Numerous studies have shown that continued usage by the user is the indicator of success in e-learning, and in recent years, research on continued use of e-learning is being explored at a higher level than before. However, to date, there have been no attempts to systematically analyse these studies in order to provide researchers and practitioners with a picture of the current state of continued usage of e-learning. The aim of this research is to provide an in-depth look at the theory of continued use information systems in e-learning context. In this study, we used a systematic review approach to collect, evaluate, and synthesize data on the accuracy and value of previous articles published in digital databases between 2009 and 2019 that were based on this research area. To include all relevant research papers that were written during this period time, we used a Systematic Literature Review (SLR) approach to collect and review studies by following a predefined review process that included both automated and manual search strategies. We listed 87 primary studies from the review study that presented research on the continued use of e-learning. These studies were analysed using a comprehensive mapping method that collected relevant information to address a series of research questions. We summarized and analysed the published articles, which covered a wide range of research subjects, including the majority of factors that affect e-learning use. While research on the continued use of e-learning is growing and providing a promising new field of research, the systematic review found that a clearer understanding of the environment and path is not well reported. This research will contribute to a better understanding of the factors that affect e-learning use over time

Today, health tourism is a growing phenomenon, especially in developing countries, which has been greatly affected by the Covid 19 crisis. After overcoming this crisis and re-competing in this industry, our country also needs to develop capabilities. Take your marketing step and move towards being financially agile. Agility, or the ability to adapt quickly and in a timely manner to changing international markets at low cost and high added value, is therefore cost-effective. The present study was conducted with the exploratory mixed research method and the purpose of designing and validating the agile financial marketing capability model in the health tourism industry in Iran. The statistical population includes health tourism industry experts and prominent professors in the field of finance who have worked in medical centers that provide health tourism services. The research findings led to the identification of 14 main concepts that were presented in the form of a paradigm model and the central category of agile financial marketing capabilities (specialized and structural capabilities) was empirically examined with real data and confirmed.

One of the most critical indicators of one-factor productivity is the labor productivity index. This index has various and broad applications in the dimensions of economic policy. On the one hand, the labor productivity index determines per capita income levels and living standards. On the other hand, efficiency combined with other factors such as capital stock can make technical changes. The issue of how monetary and exchange rate variables affect labor productivity has been of particular importance in recent international studies. Due to the importance of the issue, this study investigates the asymmetric effect of exchange rate and bank facility rates on labor productivity in Iran in 1971-2018. The results of model estimation by self-explanatory method with nonlinear autoregressive distributed lag (NARDL) indicate that in the short and long run, the effect of free-market exchange rates and bank lending rates on labor productivity is asymmetric so that reductions in exchange rates have a significant direct effect on labor productivity and increases are not significant. In addition, increases in bank lending rates have a direct effect and reductions have an adverse effect on labor productivity.

In order to evaluate the companies of the cement industry active in the Tehran Stock Exchange (Iran), it is first necessary to identify the indicators of the industry. Note that some of the indicator values provided by the Exchange Organization to the users may have been lost for any reason. All of the existing models for calculating the efficiency of such units calculate the weight of the indicators related to each unit under evaluation independent of the weight of other units. So, in this study, researchers decided to develop a common set of weight models and propose a model that evaluates efficiency in the presence of heterogeneity decision-making units (DMUs) based on the common set of weight models. Finally, the proposed model evaluates 25 cement industry companies in the presence of heterogeneity DMUs of indicators and the results are being analyzed.

In this research, we have tried to investigate the effect of successive news of dis-tributed profits, negative adjustment and late announcement of an adjustment on the market reaction process in Iran. Following the design of the market response evaluation indicators, the transaction information was collected from the Stock Exchange in the five-year period of 2011-2015. The statistical sample consists of 125 companies selected by systematic elimination method and a total of 625 years-firms. To investigate the research hypotheses, linear regression and correlation have been used and for analyzing the data and testing the hypotheses, Eviews software has been used. What is summarized in the overall conclusion of the test of research hypotheses is that the successive news of distributed profits has an effect on the market reaction process;moreover, negative adjustment has a negative impact in the forecast of earnings per share and late announcement of the adjustment of the earnings per share on the market reaction process.Finally, the results indicated that the market's negative reaction to the late negative adjustment of the earnings per share forecasting is not lower than timely negative adjustment of earnings per share forecasting, and the positive reaction of the market to adjust the timely positive or zero forecast of earning per share, compared to adjusting the late positive or zero forecast of earnings per share is also no greater. the results obtained in this study are partly consistent with the documentation referenced in the theoretical framework of the research and financial literature

The accounting software is considered to be of the most critical components of accounting information system, with particular significance as of accounting and financial systems. the most important problems with accounting education systems is that students do not adequately learn the financial software required by the accounting profession, which, in turn, reduces the credibility and position of the accounting profession. That the main objective of accounting software education is to educate skilled and expert accountants to enter the accounting profession, which is considered as of the success factors of country’s economy. In this study, employ data mining techniques to investigate the accuracy, precision, and recall performance measures and to predict the rate of financial software learning based on accounting students’ emotional intelligence (EI), gender and education level. Accordingly, a machine-learning-based multivariate statistical analysis is performed on 100 Iranian accounting students. The results show that emotional intelligence has the most impact on the rate of financial software learning among the variables. Gender and education level were influential. Also, among the five algorithms, the highest precision and recall are achieved by both Decision Tree and XGBoost and are presented as the most appropriate models for the prediction rate of financial software learning.

In the research, pattern explanation of micro and macro variables on return on stock trading strategies has been dealt with. Based on data collected, existence of momentum and contrarian strategies in Tehran Stock Exchange market has been studied. To collect data and make statistical analysis, Excel Spread Sheet software, and statistical SPSS and R software packages have been used. Through usage made of various statistical models, the relationship between variable of return on stock and other variables added has been studied so that based on which stock trading strategy would be predicted, for the next 12 months. To do so, three statistical models of autoregressive time series (with no auxiliary variable), linear regression, and Markov-switching have been applied. Using the model’s fit criteria, these three models have been compared and best of them has been selected. Based on selected model, stock trading strategy for the next 12 months has been predicted. Markov model showed that within next 12 months, using contrarian strategy i.e. selling previous winners and purchasing previous losers can be profitable. According to the research findings, from among micro variables (base volume, trade volume, institutional investment, and free float) and from among macro variables (currency and inflation rates), only three variables of the first (base volume, institutional investment, and free float) are effective on stock trading strategy; and, they can be used as auxiliary variables to predict return on stock and to specify stock trading strategy in future as a result.