درخت حوزه‌های تخصصی

The pursuit of sustainable development requires balancing the objectives of FDI, Trade, economic growth and environmental protection. Achieving a balance between these often-conflicting priorities is difficult enough at the national level, where competing interests are at least grounded in a common environmental, social and economic context. At the international level, where different countries have vastly different circumstances and priorities, it is significantly harder. One of the many ways in which this challenge manifests itself in the real world is in the conflict between the desire to promote trade by reducing non-tariff barriers and the desire to protect the environment and health through the use of technical regulations and standards.   As competition becomes more global, people are concerned that relatively lenient environmental regulation and lax enforcement in developing countries give them a comparative advantage in pollution intensive goods. Lowering trade barrier may encourage a relocation of polluting industries from countries with strict environmental policy to those with lenient policy. These shifts may increase global pollution, as countries become reluctant to tighten environmental regulations due of their concerns over comparative advantage in international trade. Therefore, trade and FDI may encourage a relocation of polluting industries from countries with strict environmental policy to those with less stringent policy. We call this a pollution haven effect. The pattern of trade depends on which of these effects is stronger. The aim of this paper is to test the validation of the hypothesis of the pollution haven effect on water created by the different industries in the selected countries of Europe and Asia.   Overall, our results show that trade liberalization decreases the BOD emission crated by chemical, food, metal, paper and pulp, textile, wood and other industries but it increases this emission crated by clay and glass industry in the selected EU-Asian countries. JEL Classification : Q51, Q56.

This paper examines the credit risk in the Iranian banks during 2008 to 2018 through the Z-score (Accounting based data) and the KMV-Merton (Market based information) models. In the Merton model, equity is equal to call option on underlying value of the bank’s asset. The market value of assets is estimated by share price. The value of assets is then compared to the value of liabilities. Therefore, default when occurs that the market value of assets is less than the book value of debts. so, value of equity becomes negative. In the Z-score model, Return on Assets and Equity to Assets as the numerator and standard deviation of ROA as the denominator are applied. If the mentioned ratios of numerator increase and the denominator decrease, the probability of default decline. As well as, Independent variables are divided into five groups: leverage, management efficiency, profitability quality, financial health, and liquidity. As a result, capital adequacy and profitability have a greater impact on both models. Also, the ANOVA table proves the validity of two models. The value of ROC test in both models is above average (0.5) which are efficient and their efficiency is 99.48% and 92.68%, respectively. Also, in terms of Voung’s test, the KMV is more efficient than the Z-score.

Competitive advantages play a unique role in organizations' successes or failures because of customers' very speedy accessibility to suppliers and manufacturers. Indeed, this is competitive advantages which can make firms and organizations survive and grow in today's increasing competitive field attaining by creating and or improving their capabilities. The main goal of the study is to design a grounded theory model extracted from the transnational capabilities, but this required to explore the transnational capabilities aiming for the international markets entry. The statistical population of this qualitative research included experts and managers working in the steel pipe manufacturing companies of Iranian gas and oil industry. The data collected via interviews. The validity assured by counseling with the elites and university professors and the reliability verified by the Delphi technique. The findings revealed 496 open, 44 axial and 9 selective codes including: 1) Marketing, 2) Managerial, 3) Human Resources, 4) Financial, 5) Manufacturing, 6) Quality & Standards, 7) Research & Development 8) Logistics and 9) Interactions and counseling with the government. Finally, a new model extracted and represented from analysis of the axial coding process of the grounded theory. The model precisely clarified relationships among the components including casual conditions, context, actions/interactions (strategies), intervening conditions and consequences. Recognition of the relationships of the components will help better understanding of the capabilities. This will lead to attain the competitive advantages needed for successful entry into the international markets.