The objective of this study is to identify techniques for predicting the outcome of a negotiation and then apply them to the current negotiations over the legal status of the Caspian Sea, which has been in dispute since the collapse of the Soviet Union. The five coastal states -Azerbaijan, Iran, Kazakhstan, Russia, and Turkmenistan-entered negotiations in 1993, but have not yet agreed on who owns the waters or the oil and natural gas beneath them. We identify the five well-defined options for resolving the dispute and then discuss the states' preferences regarding these options. We apply some well-known social choice rules to find the "socially optimal" resolution. Then we review several versions of Fallback Bargaining, which aims to minimize the maximum dissatisfaction of the bargainers, and apply them to the dispute. Finally, we represent the dispute in financial terms and apply several well-known bankruptcy procedures, which are fair division methods for settling monetary claims. We end with some suggestions on how the value of the Caspian seabed resources could be allocated among the five Caspian states.
Supply chain members coordinate with each other in order to obtain more profit. The major mechanisms for coordination among supply chain echelons are pricing, inventory management, and ordering decisions. Regarding to these mechanisms, supply chain participants have conflicts of interest. This paper concerns coordination of enterprise decisions including pricing, advertising, ordering, and inventory decisions in a multi-echelon supply chain consisting of multiple suppliers, one manufacturer, and multiple retailers. In the current study, a novel inventory model is presented for both the manufacturer, and the retailers who are able to determine the number of orders for each product. Moreover, each supply chain member has equal power and make their decisions simultaneously. The proposed model considers the relationships among three echelon supply chain members based on a non-cooperative Nash game with pricing and inventory decisions. An iterative solution algorithm is proposed to find Nash equilibrium point of the game. Several numerical examples are presented to study the application of the model as well as the effectiveness of the algorithm. Finally, a comprehensive sensitivity analysis is performed and some important managerial insights are highlighted.2010 Mathematics Subject Classification. Primary: 91A10, 90B60, 90B05.
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