To improve the performance of the supply chain with one supplier and multiple retailers under deterministic price-sensitive customer demand, an optimal strategy is proposed based on knowledge discovery. First the decentralized system in which the supplier and the retailers are independent, profit-maximizing participants with the supplier acting as a Stackelberg game leader is studied. Numerical examples illustrate the importance of the coordination. The conventional quantity discount mechanism needs to be modified to coordinate the supply chain, so a revenue-sharing contract is proposed to coordinate such supply chain. Lastly, a special decision under certain demand rates is studied. The pricing and replenishment policies can be decided sequentially, which yields much less loss comparing with optimal decision when the demand rates are sufficiently large.
We consider a distribution system with one supplier and two retailers. For the two retailers, they face different demand and are both risk averse. We study a single period model which the supplier has ample goods and the retailers order goods separately. Market search is measured as the fraction of customers who unsatisfied with their ＂local＂ retailer due to stock-out, and search for the goods at the other retailer before leaving the system. We investigate how the retailers game for order quantity in a Conditional Value-at-Risk framework and study how risk averse degree, market search level, holding cost and backorder cost influence the optimal order strategies. Furthermore, we use uniform distribution to illustrate these results and obtain Nash equilibrium of order strategies.
This paper studies a single-season two-period supply chain with market signal and remanufacturing between two periods. The decider has two opportunities in period 2 after observing market signal which updates the demand forecast. One is to manufacture a normal product, the other is to remanufacture the left-over inventory of the first period. We consider the centralized and decentralized system. In the centralized system, we derive the optimal ordering policy. In the decentralized system, we show that the revenue-sharing contracts can be amended simply to coordinate our supply chain with remanufacturing. Finally, we analyze the effect of market signal and remanufacturing in the supply chain through numerical examples. We can find the monotonicity behaviors of the optimal first-period order quantity and the optimal expected profit with respect to the quality of information. With remanufacturing in the system, the expected profit increases.
We extend the classical newsvendor problem by introducing a downside risk constraint from the perspective of inventory control. At the beginning of a replenishment period the newsvendor will place an order, then he will review the inventory level at the end of the period. If the inventory level is positive then he will bear the holding cost and if the inventory level is negative then he will bear the backorder cost. The optimal order quantity has a simple form. We analyze the form of the optimal order quantity when we restrict that the probability that the cost level is larger than or equal to a fixed cost constant is less than a fixed value of probability. At last, we analyze the case that the fixed cost constant is equal to the expected cost.
This paper analyzes an electronic procurement （e-procurement） process between a manufacturer and N-supplier in the e-market. We proof that using the general contract based on auction theory, i. e. the wholesale price contract, would not achieve the coordination of channel composed of the manufacturer and the winning supplier. The paper designs a contract mechanism, i.e. the side payment price-restricted contract based on auction theory, which not only ensures Pareto optimal solutions for both, but also coordinates the supply chain. A numerical experiment is provided to compare the performance of different auction mechanisms and to reinforce key managerial insights generated through analysis.
