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The aim of the paper is to find out whether euro is a convenient substitution for U.S. dollar as an anchor currency for Iranian rial and whether this replacement would affect Iran's international trade positively. We explore these effects via Optimum Currency Area (OCA) theories using generalized least square from 2000 to 2018. Based on OCA index, euro would be a good substitution for U.S. dollar as an anchor for Iranian rial. In addition, gravity model and Generalized Method of Moments estimation confirm that substitution of U.S. dollar by euro would improve bilateral trade between Iran and its major trade partners especially the European Economic and Monetary Union (EMU). Furthermore, we confirm that a basket containing main currencies (euro, U.S. dollar, yuan, Russian rubble) would be more efficient than a single currency anchor however euro should be prominent in the basket. Such a change of anchor could positively contribute to reduction of transaction costs, diversification of external risk, rise of mutual trade exchanges between Iran and the EMU or the EU and consequent economic growth of trade partners. The paper contributes to the existing literature by comprehensive methodological approach how to identify an appropriate anchor currency. [ABSTRACT FROM AUTHOR]

Value engineering is an appropriate policy for creating and improving value, which reduces unnecessary costs and maintains core functionality. Despite the mentioned benefits, this approach has so far received little attention in the area of supply chain management. Although this approach is highly structured, limitations such as overemphasizing the cost criterion and failure to meet other criteria, utilizing team members' votes to rank solutions, ignoring inherent uncertainty and ultimately disagreement between value engineering team members have reduced the effectiveness of this approach. The present study aims to provide a coherent framework for utilizing a value engineering approach to supply chain cost management and overcome the aforementioned limitations by utilizing gray multi-criteria decision-making. In this regard, in the first phase, the initial list of improvement solutions is determined, the criteria extracted from the literature are localized using value engineering team members' opinion. These criteria are weighted using the gray stepwise weight assessment ratio analysis (SWARA-Gray) method. Then, the score of each solution is calculated by the value engineering team based on the list of criteria as a gray number. The scores are aggregated using the gray evaluation based on distance from average solution (EDAS-Gray) method, and the solutions are prioritized. Finally, the application of the proposed framework is investigated in a real case study in a power plant in Iran. The results of the research show that the final rankings of the solutions rarely changed for different methods; so the model used in this study has acceptable stability. [ABSTRACT FROM AUTHOR]