Competition in the Supply Option Market

This paper develops a multiattribute competition model for procurement of short life-cycle products. In such an environment, the buyer installs dedicated production capacity at the suppliers before demand is realized. Final production orders are decided after demand materializes. Of course, the buyer is reluctant to bear all the capacity and inventory risk, and thus signs flexible contracts with several suppliers. We model the suppliers' offers as option contracts, where each supplier charges a reservation price per unit of capacity and an execution price per unit of delivered supply. These two parameters illustrate the trade-off between total price and flexibility of a contract, which are both important to the buyer. We model the interaction between suppliers and the buyer as a game in which the suppliers are the leaders and the buyer is the follower. Specifically, suppliers compete to provide supply capacity to the buyer, and the buyer optimizes its expected profit by selecting one or more suppliers. We characterize the suppliers' equilibria in pure strategies for a class of customer demand distributions. In particular, we show that this type of interaction gives rise to cluster competition. That is, in equilibrium suppliers tend to be clustered in small groups of two or three suppliers each, such that within the same group all suppliers use similar technologies and offer the same type of contract. Finally, we show that in equilibrium, supply chain inefficiencies—i.e., the loss of profit due to competition—are at most 25% of the profit of a centralized supply chain.United States. Office of Naval Research (contract N00014-95-1-0232)United States. Office of Naval Research (contract N00014-01-1-0146)National Science Foundation (U.S.) (contract DMI-0085683)National Science Foundation (U.S.) (DMI-0245352)National Science Foundation (U.S.) (CMMI-0758069)Massachusetts Institute of Technology. Center for Digital BusinessUniversity of Navarra. IESE Business School (CIIL International Center for Logistics Research

Portfolio strategies in supply contracts

Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2004.Includes bibliographical references (p. 235-239).Traditionally, industrial buyers have focused on long-term contracts for many of their purchasing needs. Recently, however, some high-tech manufacturers have started looking at more flexible contracts for non-strategic components, which enables them to buy from a variety of suppliers and the spot market. We study this type of strategies in a general framework for supply contracts, in which portfolios of contracts can be analyzed and optimized. We examine a multi-period model where expected profit is optimized, and a single-period model where a mean-variance objective is considered. In addition, we investigate what the consequences of such purchasing behavior might be. For this purpose, we study the game where suppliers compete on price and flexibility for the buyer's orders. We characterize the suppliers' Nash equilibria in pure strategies and show that, when demand is log-concave, there exists one or multiple equilibria, and that in any of these, suppliers bid in clusters against other suppliers with similar technologies.by Victor Martínez-de-Albéniz.Ph.D

Optimal Procurement Design in the Presence of Supply Risk

This paper analyzes optimal auction design when delivery of supply is uncertain. We consider a buyer facing multiple potential suppliers, each having an associated (exogenous) reliability that quantifies its risk of supply failure. We design optimal mechanisms that depend on the buyer's level of information regarding the suppliers' cost of production and reliability. When supplier reliability is known, we find that the optimal allocation resembles the allocation under full information, but with inflated production costs. When it is unknown, the same result is true when cost and reliability of a supplier are independent. Furthermore, the buyer does not have to pay any rent for information on suppliers' reliability. Moreover, we assess the benefits of the optimal mechanism compared to traditional auctions that ignore supply risk.auctions, supply risk, information asymmetry

Dynamic speed optimization in supply chains with stochastic demand

In this paper, we analyze how to continuously adjust the speed in a supply chain with stochastic demand. For each unit (e.g., truckload, shipping container) in the chain, one must decide at which speed it should be moved downstream, given the state of the system, to minimize total supply chain costs. We decompose the problem into a set of one-dimensional subproblems that can be easily solved and characterize the optimal variable speed policy: under some assumptions, we show that it is optimal to set a speed that is first increasing in the distance to the market, and then decreasing. As a result, at optimality a given unit will experience an accelerating speed and then it will be slowed down, unless a demand occurs, in which case, the speed will be adjusted upward. We finally provide a transportation case study where we estimate the benefits of a variable-speed compared to a fixed-speed policy and show them to be significant both financially and from a CO2-emissions perspective

A characterization of optimal base-stock levels for a multistage serial supply chain

In this article, we present a multistage model to optimize inventory control decisions under stochastic demand and continuous review. We first formulate the general problem for continuous stages and use a decomposition solution approach: since it is never optimal to let orders cross, the general problem can be broken into a set of single-unit subproblems that can be solved in a sequential fashion. These subproblems are optimal control problems for which a differential equation must be solved. This can be done easily by recursively identifying coefficients and performing a line search. The methodology is then extended to a discrete number of stages and allows us to compute the optimal solution in an efficient manner, with a competitive complexity

Myopic Inventory Policies Using Individual Customer Arrival Information

In this paper, we investigate the optimality of myopic inventory replenishment policies in a periodic-review single-echelon system, with nonstationary, correlated, stochastic demand and cost, and nonincreasing stochastic prices. Using the single-unit decomposition approach, we provide certain general conditions on the demand and cost processes under which a myopic policy is optimal. Under these conditions, the optimal policy is a myopic state-dependent base-stock policy, which can be expressed in closed form as a base-probability policy. Specifically, the order associated with a given customer should be placed if and only if its arrival probability within the leadtime is higher than a threshold. Our results generalize earlier conditions for the optimality of myopic policies. Namely, we show that myopic policies can be optimal even when the demand is correlated or stochastically decreasing.state-dependent base-stock policies, single-unit decomposition approach