Managing contingencies in supply chains

Zhengping Wu, Purdue University

Abstract

In this work, we study contingency related issues arising from both the demand side and the supply side. On the demand side, we model demand surges as the primary source of contingency. We analyze demand postponement as a strategy to handle potential demand surges. Under demand postponement, a fraction of the demands from the “regular” period are postponed and satisfied during a “postponement” period. This permits capacity to be procured to satisfy the postponed demands. A reimbursement per unit is paid to customers whose demands are postponed. The basic idea is that by preempting stock-outs through demand postponement, we can reduce overall stock-out costs. We analytically solve the problem of determining the optimal regular and postponement period capacities, and the demand splitting rule. We then consider the decentralized version of the demand postponement problem, in which the postponement cost is the customers' private information that is not known to the supplier. We show that the agency effect is equivalent to a larger postponement cost, with the increment being the “information cost”. We also model details of customer response to demand postponement and study using price discount to induce customers to agree to demand postponement. We explicitly consider heterogeneous customers with differing preferences. We characterize the optimal discount scheme the supplier should offer in order to maximize her expected profit. On the supply side, we consider a two-tier supply chain consisting of a monopolist supplier and multiple buyers. Suppose the supplier experiences a disruption in supply and actions (with associated costs) are required to restore the supply. During the disruption phase, buyers do not have access to supply and thus experience stock-outs. Buyers incur a back-order cost, which we model as private information not known to the supplier. We obtain insights into issues of how fast to restore the system and what costs to charge each party in the system.

Degree

Ph.D.

Advisors

Iyer, Purdue University.

Subject Area

Management

COinS