DOI: 10.14457/tu.the.2018.870
title: Supply chain coordination using wholesale price

description: In decentralized supply chain structures, each member aims to maximize their profit. Therefore, the supply chain performance suffers in the decentralized structure. The lack of supply chain coordination makes supply chain have low performance. Therefore, we want to improve the performance of supply chain by using the new supply chain coordination technique. Wholesale price is selected to coordinate the supply chain. A manufacturer can motivate retailers by offering wholesale price discounts to retailers to change ordering decisions.In this dissertation, multiple period coordination is proposed for a two-stage supply chain that consists of a manufacturer and retailers. The study was separated into two parts. First, the coordination between a single manufacturer and a single retailer with a single product was studied. The objective of the coordination is to minimize the total supply chain cost. In the second study, the problem was extended to multiple retailers and multiple products. A bi-level model was developed with the objective to maximize the manufacturer profit while the retailers also gain from the coordination. In the first study, a two-level supply chain network with a single manufacturer supplying a single product to a single retailer. The manufacturer and retailer are owned by different companies. The retailer faces varying demand. The multiple ownership of companies in a supply chain creates operational problems, resulting in lower efficiency and higher total costs. In this paper, a coordination technique is proposed to restore the efficiency of a decentralized supply chain. This research aims to find the optimal pre-announced multi-period wholesale prices that can help the retailer’s decentralized decisions to be the same as the retailer’s centralized decisions with the minimum total cost of supply chain in a multiple time period planning horizon. We propose a procedure to determine the set of optimal wholesale prices in each period to pre-announce to the retailer and induce the retailer’s centralized order decisions using complementary slackness conditions. This study also analyzes the impact of parameters on optimal decisions and supply chain profit. The results show coordination benefits for a supply chain when the setup cost or reorder cost is high, but the average demand is low. Finally the performance of the proposed coordination method is compared with the performance of the “Every Day Low Price” wholesale price policy.In the second study, a two-level decentralized supply chain that consists of a single manufacturer and multiple retailers. The manufacturer produces and distributes multiple products to multiple retailers. The retailers face time-varying demands. A multi-product multi-period wholesale price coordination technique is proposed to restore the efficiency of the decentralized supply chain. A nonlinear bi-level programming model is developed to coordinate the supply chain. The manufacturer uses the optimal multi-period wholesale prices solved from the proposed coordination model as the incentive to change retailers’ decisions, thereby improving the supply chain performance. Due to the complexity, the nonlinear bi-level model is transformed into an equivalent mixed-integer linear programming model and solved for the optimal solution. The numerical experiments show that the wholesale prices determined by the model can induce the centralized decisions in most cases. The multi-period wholesale price mechanism can adjust profit sharing among members. The discount on wholesale prices are mainly given to avoid the overtime cost. The benefits of using the model over the decentralized model is high when a production setup cost, the marginal cost of addition a product to order or the cost of placing an order is low and manufacturer’s holding cost is high. Also, we found that, as the total demand increases, the manufacturer should increase the number of discount period and the summation of discount to spread out the production time.