Component Procurement for an Assembly Supply Chain with Random Capacities and Random Demand

Abstract

In a decentralized assembly supply chain, one assembler assembles a set of n components, each produced by a different supplier, into a final product to meet an uncertain market demand. Each supplier faces an uncertain production capacity such that only the lesser of the planned production quantity and the realized capacity can be delivered to the assembler. We assume that the suppliers' random capacities and the random demand follow an arbitrary continuous multivariate distribution. We formulate the problem as a two-stage Stackelberg game. In the base model, the assembler and the suppliers adopt a so-called vendor-managed-consigned-inventory (VMCI) contract. We analytically characterize the equilibrium of this game, based on which we obtain several managerial insights. Particularly, we show that a reduction in one supplier's production cost or capacity uncertainty, or an increase in the component salvage value, might sometimes hurt this particular supplier's profitability. Furthermore, we demonstrate that when the suppliers' capacities become more positively correlated, the assembler is always better off, but the suppliers might be better or worse off. Later, in the article, we also solve the game under a wholesale price contract. We find that the assembler always prefers the VMCI contract, and the suppliers always prefer the wholesale price contract. In addition, we illustrate that the VMCI contract is more efficient than the wholesale price contract for this decentralized assembly supply chain.

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