Mechanism design by an informed principal needs to take into account the informational leakage taking place when offering a contract to the agent. In this paper, the problem of contract design by an informed principal under trade credit in supply chain is investigated. More specifically, a supply chain consisting of a risk-neural supplier and a risk-neural retailer is considered. As the core enterprise, the retailer finances the inventory using trade credit from the supplier. By the Revelation Principle, we design the low-information-intensity optimum allocation (LⅡ) with incentive compatibility is designed, to realize the informational leakage to the supplier, and avoid the imitation between different types of retailers. By means of the mechanism way of deriving the equilibrium applied by Tirole, it is found that under the weak monotonic profit assumption, the separating allocation is the LⅡ. It's also shown that to sign the true type to the supplier, the optimal contracts for the retailer with higher ability entails an upward distortion, which causes signaling cost. And the degree of distortion decreases with the increase of the retailer's initial capital. Meanwhile, the contracts have restrictions of the initial capital. Furthermore, the interim-efficient allocation (IE) is presented to analyze the perfect Bayesian equilibrium (PBE) of the game. It can be shown that the LⅡ is the unique PBE for certain supplier's ax ante belief. Otherwise, the set of equilibrium payoffs for the two types of retailers weakly Pareto-dominate the LⅡ. And the (IE) still present the same distorted characteristic as the LⅡ, but has lower restrictions on the retailer's initial capital. Our research will provide some theoretical basis and practical guidance for the mechanism design by an informed principal under trade credit in supply chain.
YAN Ren-xiu, WANG Xian-yu
. Trade Credit Contracts Design by an Informed Principal in Retailer-dominant Supply Chain[J]. Chinese Journal of Management Science, 2017
, 25(11)
: 85
-93
.
DOI: 10.16381/j.cnki.issn1003-207x.2017.11.009
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