A Bayesian Incentive Compatible Mechanism for Decentralized Supply Chain Formation

In this paper, we consider a decentralized supply chain forma-tion problem for linear, multi-echelon supply chains when the man-agers of the individual echelons are autonomous, rational, and in-telligent. At each echelon, there is a choice of service providers and the specific problem we solve is that of determining a cost-optimal mix of service providers so as to achieve a desired level of end-to-end delivery performance. The problem can be broken up into two sub-problems following a mechanism design approach: (1) Design of an incentive compatible mechanism to elicit the true cost functions from the echelon managers; (2) Formulation and so-lution of an appropriate optimization problem using the true cost information. In this paper, we propose a novel Bayesian incen-tive compatible mechanism for eliciting the true cost functions. This improves upon existing solutions in the literature which are all based on the classical Vickrey-Clarke-Groves mechanisms, re-quiring significant incentives to be paid to the echelon managers for achieving dominant strategy incentive compatibility. The pro-posed solution, which we call SCF-BIC (Supply Chain Formation with Bayesian Incentive Compatibility), significantly reduces the cost of supply chain formation. We illustrate the efficacy of the proposed methodology using the example of a three echelon man-ufacturing supply chain. Keywords Supply chain planner (central design authority) (CDA), mean vari-ance allocation, mechanism design, Groves mechanism, dAGVA (d’Aspremont and Grard-Verat) mechanism, SCF-DSIC (Suppl