درخت حوزه‌های تخصصی

In today's rapidly advancing electronics industry, the widespread use of electrical and electronic equipment has made sustainable management of end-of-life (EOL) equipment a pressing need. A global system is required to facilitate informed decision-making regarding e-waste. Manufacturers must therefore devise strategies for effectively managing products during the EOL phase. This article introduces a novel framework for managing e-waste during the EOL phase to identify the most appropriate EOL options to minimize e-waste. The proposed framework harnesses the power of Twitter as a data source, utilizing data mining techniques to extract consumer opinions on e-waste. The article also outlines the development of a Fuzzy Analytic Hierarchy Process method and a multi-objective mathematical framework, enabling efficient decision-making in EOL processes based on e-waste information obtained from Twitter data. The study's findings have the potential to assist equipment manufacturers in identifying flaws in electrical and electronic equipment by analyzing customer opinions shared on social media platforms. Furthermore, by analyzing consumer sentiment towards e-waste, manufacturers can gain a deeper understanding of customer perspectives and develop appropriate strategic plans for selecting suitable EOL processes for returned products. This study underscores the significance of social media data in addressing e-waste management challenges, showcasing the profound impact of customer opinions.

This paper examines the non-linear relationship between CO2 emissions and economic development using an innovative dynamic panel threshold technique. The sample consists of 35 developed countries over the period 2003-2010. The empirical results indicate that there is a threshold effect in the relationship between economic growth and pollutant emissions as suggested by the environmental Kuznets curve (EKC). In particular, at the early stage of economic development below the estimated threshold value, more growth deteriorates the environmental problems. However, after this threshold value further growth serves as a solution to the environmental problems. Accordingly, promoting economic growth and becoming rich in the long run, is necessary to solve the environmental problems arising from greenhouse gas (GHG) emissions. In the short run and in the early stage of economic growth, focus on investments in environmentally friendly technology and on the use of renewable energy is necessary for mitigating the pollution effects of economic progress.

Financial sanctions have many economic consequences for the oil exporting economies. The sanctioned economy adopts economic policies to deal with it. This paper examines the relationship between financial sanctions, oil revenues and monetary and fiscal policies in Iran and explicates how financial sanctions have affected Iran's access to oil revenues. It also examines the role of fiscal and monetary policies in financial stability and resilience in Iran's economy. To this end, we employed a DSGE model with the new Keynesian approach. The results indicate that the interest rate, consumption, imports and inflation have a positive reaction to the oil revenue shock resulting from financial sanctions. However, the production, export, private sector investment and oil sales indicate a negative reaction to the oil revenues’ shock. Regarding the monetary policy shock, the reaction of production and consumption to the shock is positive. However, the reaction of oil sales and interest rate to this shock is negative. In terms of financial policy shock, production, consumption, investment and export indicated a positive reaction to this shock. However, the interest rate, imports and oil sales indicated a negative reaction to the fiscal policy shock. Monetary and fiscal policy shocks increase the effect of financial sanctions for a short period, while monetary policy shock has reduced the effect of financial sanctions for three periods. Therefore, monetary policy has been more effective than fiscal policy in reducing the effect of financial sanctions.

Special attention to the relative advantages of the economy is the best way toward economic development of the country. The chemical sector, due to the country's advantage, owing to its considerable natural oil and gas resources, high variety of products, technology and market, has a significant charm and scope for technological innovation and development. Nowadays, the country's political and economic status has created opportunities for chemicals, but Existing policies have merely increased scientific research articles and in practice it has not cause to technological innovation (Patent). The first step in the policies for this sector, understanding the factors that influence firms to technology innovation. Therefore, the purpose of this study is to analyze of factors affecting the management of technological innovation in the chemical industry to provide solutions. In this paper, the factors, were investigated by using verification factor analysis and structural equations. Then, the relative importance of each factor was determined based on the Fuzzy BWM method. The results of the present study indicated that, R&D ability, R&D efforts, Sustainable Profitability With the most votes and low-risk chemical synthesis, less chemical waste science and technology diplomacy were ranked last.

In this paper, trade relationship between Iran and its main trading partners based on Heckscher-Ohlin-Vanek (H-O-V) theory is studied in order to evaluate the development of trade relationship in export factor intensity framework. Considering several production factors such as labor, physical capital, knowledge capital, R&D expenditures, productivity and energy as countries export factor content from 1990 to 2020 is the innovation of the study. Regarding the role of R&D expenditures in trade expansion, it seems there is an allocation gap of this resource between developed and developing countries in order to benefit from the identical distribution, while the empirical findings available in the trade literature implies also unpredictable impact of the R&D expenditure variable on trade flows. Therefore, the analysis of this variable effect on trade flows is not limited to a parametric relationship. Nevertheless, other factors such as labor and capital have distinct and parametric effects on trade relations, so that a semiparametric method has been applied to the model of Iran’s export supply in relation with its trading partners. The empirical results showed that productivity, human capital, and knowledge capital, which are the main trade factor content, have the most impacts on Iran export flows and its trading partners. Additionally, the nonparametric part of the model implies that a higher percentage of R&D expenditures affects significantly Iran’s export flows in a higher rate.