Houmin Yan

Coordination of Supply Chains with Risk-Averse Agents

The extant supply chain management literature has not addressed the issue of coordination in supply chains involving risk-averse agents. We take up this issue and begin with defining a coordinating contract as one that results in a Pareto-optimal solution acceptable to each agent. Our definition generalizes the standard one in the risk-neutral case. We then develop coordinating contracts in three specific cases: (i) the supplier is risk neutral and the retailer maximizes his expected profit subject to a downside risk constraint; (ii) the supplier and the retailer each maximizes his own mean-variance trade-off; and (iii) the supplier and the retailer each maximizes his own expected utility. Moreover, in case (iii), we show that our contract yields the Nash Bargaining solution. In each case, we show how we can find the set of Pareto-optimal solutions, and then design a contract to achieve the solutions. We also exhibit a case in which we obtain Pareto-optimal sharing rules explicitly, and outline a procedure to obtain Pareto-optimal solutions.

Mean-variance analysis of a single supplier and retailer supply chain under a returns policy

Abstract In the literature, most of the supply chain coordinating policies target at improving the supply chain’s efficiency in terms of expected cost reduction or expected profit improvement. However, optimizing the expected performance alone cannot guarantee that the realized performance measure will fall within a small neighborhood of its expected value when the corresponding variance is high. Moreover, it ignores the risk aversion of supply chain members which may affect the achievability of channel coordination. As a result, we carry out in this paper a mean–variance (MV) analysis of supply chains under a returns policy. We first propose an MV formulation for a single supplier single retailer supply chain with a newsvendor type of product. The objective of each supply chain decision maker is to maximize the expected profit such that the standard deviation of profit is under the decision maker’s control. We study both the cases with centralized and decentralized supply chains. We illustrate how a returns policy can be applied for managing the supply chains to address the issues such as channel coordination and risk control. Extensive numerical studies are conducted and managerial findings are proposed.

Optimal returns policy for supply chain with e-marketplace

Abstract We study in this paper a supply chain which is integrated by a returns policy. In the past, owing to a lack of sales channels, the returned products would worth very little. Now, with the advance of the e-commerce, the returned products can be sold with a higher price on the e-marketplace. In light of this, we first investigate the optimal returns policy under the existence of the e-marketplace. Through a mean–variance analysis, we further study the risk issue associated with the optimal policy. Extensive simulations are then carried out and the managerial insights are discussed.

Optimal two-stage ordering policy with Bayesian information updating

We investigate in this paper an optimal two-stage ordering policy for seasonal products. Before the selling season, a retailer can place orders for a seasonal product from her supplier at two distinct stages satisfying the lead-time requirement. Market information is collected at the first stage and is used to update the demand forecast at the second stage by using Bayesian approach. The ordering cost at the first stage is known but the ordering cost at the second stage is uncertain. A two-stage dynamic optimization problem is formulated and an optimal policy is derived using dynamic programming. The optimal ordering policy exhibits nice structural properties and can easily be implemented by a computer program. The detailed implementation scheme is proposed. The service level and profit uncertainty level under the optimal policy are discussed. Extensive numerical analyses are carried out to study the performance of the optimal policy.

Mean–Variance Analysis for the Newsvendor Problem

The newsvendor problem is a fundamental building block for inventory management with a stochastic demand. The classical newsvendor problem focuses on a sole objective of either minimizing the expected cost or maximizing the expected profit. However, the performance measure with expected value alone is insufficient, and it ignores the risk preferences of the decision makers. As a result, we carry out a mean-variance analysis of the newsvendor problem. We construct analytical models and reveal the problems structural properties. We propose the solution schemes which help to identify the optimal solutions. Interesting findings regarding the efficient frontier, the case with a stockout penalty cost, and the safety-first objective are discussed.

Quantity Flexibility Contracts: Optimal Decisions with Information Updates*

We study single and multiperiod quantity flexibility contracts involving one demand forecast update in each period and a spot market. We obtain the optimal order quantity at the beginning of a period and order quantities on contract and from the spot market at the then prevailing price after the forecast revision and before the demand materialization. The amount that can be purchased on contract is bounded by a given flexibility limit. We discuss the impact of the forecast quality and the level of flexibility on the optimal decisions and managerial insights behind the results.

Inventory Models with Fixed Costs, Forecast Updates, and Two Delivery Modes

This paper is concerned with a periodic review inventory system with fast and slow delivery modes, fixed ordering cost, and regular demand forecast updates. At the beginning of each period, on-hand inventory and demand information are updated. At the same time, decisions on how much to order using fast and slow delivery modes are made. Fast and slow orders are delivered at the end of the current period and at the end of the next period, respectively. A forecast-update-dependent ( s,S)-type policy is shown to be optimal. Also shown are some monotonicity properties of the policy parameters with respect to the costs and information updates.

A newsvendor pricing game

This paper considers a horizontal market of multiple firms that face stochastic price-dependent demand. The firms make joint pricing/inventory decisions and use price to compete for market demand. With fairly general demand models that are price-dependent, stochastic, and substitutable among firms, we prove the existence and uniqueness of the pure-strategy Nash equilibrium. The market at the equilibrium exhibits a bias toward under-pricing caused by competition; specifically, raising prices at any equilibrium of the game increases the total system profit, and at any joint-optimal set of pricing levels each self-interested firm has an incentive to lower its price. This result closely parallels that obtained in the inventory competition games in which prices are fixed and the bias is toward overstocking.

A numerical method in optimal production and setup scheduling of stochastic manufacturing systems

In this paper, we consider optimal production and setup scheduling in a failure-prone manufacturing system consisting of a single machine. The system can produce several types-of products, but at any given time it can only produce one type of product. A setup is required if production is to be switched from one type of product to another. The decision variables are a sequence of setups and a production plan. The objective of the problem is to minimize the cost of setup, production, and surplus. An approximate optimality condition is given together with a computational algorithm for solving the optimal control problem.

The newsvendor problem with pricing: Extensions

Abstract The newsvendor problem with pricing decision provides an important vehicle for examining how operational problems interacts with marketing issues to influence decision-making at the firm level. This paper considers the newsvendor problem with pricing and its extensions. We try to answer two questions: (1) how to model the price-dependent stochastic demand and (2) how to derive the combined pricing and inventory solutions. We identify a class of demand functions which can result in well behaved profit functions. A demand function can be divided into two parts: the mean demand and random demand. If the part of mean demand has increasing price elasticity (IPE) and the part of random demand has generalized strict increasing failure rate (GSIFR), then the expected profit of the newsvendor is unimodal or quasi-concave. This appears generalizing the existent models in the literature.