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A Mechanism Design Approach for Decentralized Supply Chain Formation

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Abstract

In this chapter, we describe a category of supply chain formation problems where the supply chain planner or the Central Design Authority (CDA) is faced with the decision of choosing a partner or service provider for each supply chain stage so as to meet delivery targets and schedules at minimum cost. We first look into the case, where the CDA has access to all the relevant information required to solve this problem. Such a supply chain formation problem with complete information becomes a plain optimization problem in a centralized framework. Since it is quite impractical for the CDA to have access to all the information, we next consider the incomplete information case. In this setting, the individual managers of the supply chain stages are not loyal to the CDA but are rational, intelligent, and autonomous entities always pursuing maximization of their individual payoffs and not necessarily revealing their true private values. The supply chain formation problem now becomes a mechanism design problem followed by an optimization problem. Our specific contribution is to show that Vickrey–Clarke–Groves (VCG) mechanisms provide a natural and compelling model for such problems. We propose a decentralized framework to solve the underlying mechanism design problem. We illustrate our approach with the help of an example of forming a three stage distribution process for a typical automotive supply chain.

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Notes

  1. 1.

    We will keep using the terms cycle time, lead time, and delivery time interchangeably.

  2. 2.

    In most of the practical cases, getting values of the coefficients a i0, a i1, a i2 is not an easy task for the stage manager.

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Correspondence to Dinesh Garg .

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Garg, D., Narahari, Y., Foster, E., Kulkarni, D., Tew, J.D. (2011). A Mechanism Design Approach for Decentralized Supply Chain Formation. In: Kempf, K., Keskinocak, P., Uzsoy, R. (eds) Planning Production and Inventories in the Extended Enterprise. International Series in Operations Research & Management Science, vol 152. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-8191-2_7

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