Supply Chain Network Competition: Retailers Risk Attitude Approach

In this paper a supply chain network equilibrium model is developed through a mixed integer linear programming problem. Demand uncertainty and retailers’ risk averseness are simultaneously considered in the model formulation. According to the nature of the supply chain network, the relationship between the network and the final customer is allowed in the last echelon of the network. Therefore, the demand uncertainty affects the retailers in the last tire of the network. Some retailers are risk averse and some others are risk natural so the model is sensitive to the retailers risk averseness. Thus the Conditional Value at Risk (CVaR) method is employed through the datadriven approach in order to address this sensitivity in the robust manner. Numerical results show that the proposed model is efficient for supply chain network competition in compliance with retailers risk attitude. Finally, the model outputs and its results are illustrated through a numerical example.