درخت حوزه‌های تخصصی

The purpose of this research is selecting the Most Effective Strategic Capability for Sustainable Development under Risk and Uncertainty in the Oil Industry by Rough Set Theory. The research methodology is qualitative and quantitative. The target population in the qualitative section included 14 industrial management specialists at the university level and in the quantitative section 32 senior managers in companies active in the Oil Industry. In this research, were used Meta-synthesis and Delphi analysis methods were used to identify the components and propositions of the research and in a small part, the analytical approaches of Ruff collection. The results showed that among the 15 final statements of risk and uncertainty in the Oil Industry, the risk of change in domestic law relative to political / economic diplomacy in the development of infrastructure for the Oil Industry X5 as the most important risk statement and uncertainty in the field. Political and legal risks that have been identified as a measure of the strategic viability of sustainable development. Finally, it was found that, despite the most probable risks selected in this study, namely the risk of changes in domestic law to political / economic diplomacy in the development of infrastructure of the Oil Industry "X5" Existence of sanctions of the world powers "X1" Strategic capabilities of sustainable economic development is the most important feature that should be considered in the country's inflationary conditions.

China has become the world’s high-growth and second largest economy since its socialist- orientation opening-up reforms in the early 1980s. Due also to its geographical, cultural and historical attractions, the country has become the world’s fourth largest tourism destination and tenth largest tourism earner in 2018 according to the World Tourist Organization. The important role played by tourism in the Chinese economy has been officially recognized by China’s National Development and Reform Commission as a strategic pillar industry development priority. In spite of these, rigorous policy-related studies on China’s tourism have been limited. The paper is a serious econometric study to investigate the determination of China’s tourism and its contribution to the country during the period 1996-2018 for credible data-based policy analysis.  Significantly, the study is carried out appropriately from an economic integration (globalization) growth framework, which is also the expenditure (as opposed to production or income) perspective of the United Nations System of National Accounts 1998/2003. Specifically, a multi-simultaneous equation model of endogenous growth and China’s tourism determination is developed. The model innovatively incorporates gravity theory and classical consumer demand contributors, Ironmonger-Lancaster new commodity attributes and Johansen policy impact add- and sub-factors (i.e., reforms and crises) explicitly in its economic integration structure. The model is then estimated by system methods with official economic and tourism 1996-2018 data from the World Tourism Organization and international databases. The research will contribute to advances in the literature and the findings provide useful insights and appropriate and much needed evidence-based inputs on the determination and contributors of tourism to China’s growth. Recommendations will be provided to key stake-holders such as tourism policy-makers, academic researchers, business analysts and tourism operators for national strategic policy analysis and practical implementation. JEL Classification: C54, F15, F62, Z32, Z38

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.

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.