This study develops a multiple-round compromising mechanism to achieve coordination of a supply chain with a single supplier and multiple retailers. Typically, the availability of global information and its possibility to be used to maximize the profit of the entire supply chain, which may result in unfavorable allocations of profits to some members in the chain, are unrealistically assumed. Accordingly, this study differs from the existing ones because the proposed multiple-round negotiation process ensures that each member can have a sufficient profit gain under a restrictive private information environment, which is often a more realistic business case. This study contributes to the literature by proposing a feasible coordination mechanism which is able to provide flexible negotiation cushions for both the single supplier and the retailers under the condition that every member is self-interested, i.e., concerned primarily with their own profit, and is willing to share only a little information. Since such coordination ensures more profitability for the members in the supply chain, it can remain for a significantly longer period and thus is able to maintain a long-term, steady win–win situation. The objective function and the cost structure of each member are regarded as restricted private information and hence would not be shared with any other members of the supply chain. However, the offer of quantity discounts from the supplier and the pre-sale contract of each supplier–retailer pair are transparent within the supply chain. Each member in the supply chain focuses on their own profits and finds an acceptable negotiation quantity, along with possible discounts after several rounds of coordination. The numerical illustration suggests that the supplier should conservatively contemplate its planned capacity to approximate the original predicted market demand and then realistically conclude contract agreements with reasonable ranges of order amount to prevent both sides of the supply chain to be in an unfair situation of being individually exposed to market risk.
All Science Journal Classification (ASJC) codes
- Computer Science(all)