Problem definition: We use the guaranteed service (GS) framework to investigate how to coordinate a multiechelon supply chain when two self-interested parties control different parts of the supply chain. For purposes of supply chain planning, we assume that each stage in a supply chain operates with a local base-stock policy and can provide guaranteed service to its customers, as long as the customer demand falls within certain bounds. Academic/practical relevance: The GS framework for supply chain inventory optimization has been deployed successfully in multiple industrial contexts with centralized control. In this paper, we show how to apply this framework to achieve coordination in a decentralized setting in which two parties control different parts of the supply chain. Methodology: The primary methodology is the analysis of a multiechelon supply chain under the assumptions of the GS model. Results: We find that the GS framework is naturally well suited for this decentralized decision making, and we propose a specific contract structure that facilitates such relationships. This contract is incentive compatible and has several other desirable properties. Under assumptions of complete and incomplete information, a reasonable negotiation process should lead the parties to contract terms that coordinate the supply chain. The contract is simpler than contracts proposed for coordination in the stochastic service (SS) framework. We also highlight the role of markup on the holding costs and some of the difficulties that this might cause in coordinating a decentralized supply chain. Managerial implications: The value from the paper is to show that a simple contract coordinates the chain when both parties plan with a GS model and framework; hence, we provide more evidence for the utility of this model. Furthermore, the simple coordinating contract matches reasonably well with practice; we observe that the most common contract terms include a per-unit wholesale price (possibly with a minimum order quantity and/or quantity discounts), along with a service time from order placement until delivery or until ready to ship. We also observe that firms need to pay a higher price if they want better service. What may differ from practice is the contract provision of a demand bound; our contract specifies that the supplier will provide GS as long as the buyer’s order are within the agreed on demand bound. This provision is essential so that each party can apply the GS framework for planning their supply chain. Of course, contracts have many other provisions for handling exceptions. Nevertheless, our research provides some validation for the GS model and the contracting practices we observe in practice.
MULTI-CHANNEL SUPPLY CHAIN OPTIMISATION IN CYBER-PHYSICAL ENVIRONMENT UNDER QUANTITY DISCOUNTS
