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One of the most important aspects of investment is determining the “optimal investment portfolio”. To date, scientific research has been conducted to determine the optimal portfolio with “artificial intelligence” and “Fuzzy logic”. However, we determine the optimal portfolio based on Dynamic Stochastic General Equilibrium (DSGE) model. On the other hand, several factors affect returns, which is one of the most important issues in investment decision-makings, and various models have been developed to analyze the return of “capital” and “other assets”. In this regard, some of the most important models include linear and non-linear models, artificial neural network models, Fama–French model, Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) model, and optimal stable model. All of these models are indicative of the use of quantitative methods and models in the investment industry. One of the causes of using these models is developing the financial economy. In fact, the development of financial economy has more increased with the concept of “portfolio optimization”. In fact, the portfolio optimization and diversification concept is the basis of developing and expanding classical finance and financial decision-making. Financial markets, especially the capital market, can have a great deal of relevance to other sectors of the economy. In the present study, we design and calibrate a new Keynesian DSGE model in relation to the optimal investment portfolio and effectiveness of shocks (e.g., productivity and foreign exchange earnings fluctuation) on macroeconomics variables.

The high transparency and ability of consumers to transmit advertising content quickly in the modern age require that organizations consider authenticity and interaction with customers among their top priorities and combine consumer-generated advertising (CGA) with their own marketing strategies in order to respond to these priorities. This study aims to investigate the factors affecting consumers' attitudes and willingness toward consumer-generated advertising and its effect on brand loyalty and attachment. This is an applied study conducted using the descriptive correlational survey method. Its statistical population consists of dairy consumers of Kalleh Company in Mazandaran Province. A total of 460 questionnaires were distributed by stratified random sampling and descriptive and inferential statistics was used for data analysis. Structural equation modeling and Smart PLS2 were used to test the hypotheses. The reliability of the questionnaires was determined by Cronbach's alpha test and composite reliability coefficient. Results showed that brand attachment had a significant positive effect on attitude toward advertising production and willingness to participate in advertising production. Attitude toward advertising production has a significant positive effect on willingness toward CGA as well as on brand loyalty. It was also shown that brand attachment has a significant positive effect on loyalty. The rapid changes in technology and the development of effective advertising in the modern businesses require defining the concept of CGA, which is addressed in the present study. Also, based on the results of this study, brand attachment increases customers’ willingness toward and participation in CGA. An increase in customers' willingness and involvement in advertising production will also increase their loyalty.

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