Fangruo Chen

Information Sharing and Supply Chain Coordination

Publisher Summary This chapter discusses the information pertaining to the downstream part of the supply chain and then reviews the upstream information. The chapter discusses the papers that investigate the consequences of imperfect transmission of information. All the papers adopt the perspective of a central planner whose goal is to optimize the performance of the entire supply chain. The chapter addresses the incentive issues in information sharing. Supply chains are composed of independent firms with private information. Information sharing in supply chains with independent players is tricky. When a player has superior information, two things may happen. He may withhold it to gain strategic advantage or he may reveal it to gain cooperation from others. If the former, the less informed players try to provide incentives for him to reveal his private information, then it is termed “screening.”

Salesforce Incentives, Market Information, and Production/Inventory Planning

Salespeople are the eyes and ears of the firms they serve. They possess market knowledge that is critical for a wide range of decisions. A key question is how a firm can provide incentives to its salesforce so that it is in their interest to truthfully disclose their information about the market and to work hard. Many people have considered this question and provided solutions. Perhaps the most well-known solution is due to Gonik (1978), who proposed and implemented a clever scheme designed to elicit market information and encourage hard work. The purpose of this paper is to study Goniks scheme and compare it with a menu of linear contracts--a solution often used in the agency literature--in a model where the market information possessed by the salesforce is important for the firms production and inventory-planning decisions.

Optimal Policies for Multiechelon Inventory Problems with Markov-Modulated Demand

This paper considers a multistage serial inventory system with Markov-modulated demand. Random demand arises at Stage 1, Stage 1 orders from Stage 2, etc., and Stage N orders from an outside supplier with unlimited stock. The demand distribution in each period is determined by the current state of an exogenous Markov chain. Excess demand is backlogged. Linear holding costs are incurred at every stage, and linear backorder costs are incurred at Stage 1. The ordering costs are also linear. The objective is to minimize the long-run average costs in the system. The paper shows that the optimal policy is an echelon base-stock policy with state-dependent order-up-to levels. An efficient algorithm is also provided for determining the optimal base-stock levels. The results can be extended to serial systems in which there is a fixed ordering cost at stage N and to assembly systems with linear ordering costs.

Optimal Policies for Multi-Echelon Inventory Problems with Batch Ordering

In many production/distribution systems, materials flow from one stage to another in fixed lot sizes. For example, a retailer orders a full truckload from a manufacturer to qualify for a quantity discount; a factory has a material handling system that moves full containers of parts from one production stage to the next. In this paper, we derive optimal policies for multi-stage serial and assembly systems where materials flow in fixed batches. The optimal policies have a simple structure, and their parameters can be easily determined. This research extends the multi-echelon inventory theory in several ways. It generalizes the Clark-Scarf model by allowing batch transfers of inventories. Rosling (1989) shows that assembly systems can be interpreted as serial systems under the assumption that there are no setup costs. We show that the series interpretation still holds when materials flow in fixed batches which satisfy a certain regularity condition. Finally, Veinott (1965) identifies an optimal policy for a single-location inventory system with batch ordering. This paper generalizes his result to multi-echelon settings.

Auctioning Supply Contracts

This paper studies a procurement problem with one buyer and multiple potential suppliers who hold private information about their own production costs. Both the purchase quantity and the price need to be determined. An optimal procurement strategy for the buyer requires the buyer to first design a supply contract that specifies a payment for each possible purchase quantity and then invites the suppliers to bid for this contract. The auction can be conducted in many formats such as the English auction, the Dutch auction, the first-priced, sealed-bid auction, and the Vickrey auction. The winner is the supplier with the highest bid, and is given the decision right for the quantity produced and delivered. Applying this theory to a newsvendor model with supply-side competition, this paper establishes a connection between the above optimal procurement strategy and a common practice in the retail industry, namely, the use of slotting allowances and vendor-managed inventory. Also discussed in the newsvendor context are the role of well-known supply contracts such as returns contracts and revenue-sharing contracts in procurement auctions, the scenarios where the buyer and suppliers may possess asymmetric information about the demand distribution, and how the cost of supply-demand mismatch is affected by supply-side competition. Finally, this paper compares the optimal procurement strategy with a simpler but suboptimal strategy where the buyer first determines a purchase quantity and then seeks the lowest-cost supplier for the quantity in an auction.

Market Segmentation, Advanced Demand Information, and Supply Chain Performance

A monopolist sells a single product to a market where the customers may be enticed to accept a delay as to when their orders are shipped. The enticement is a discounted price for the product. The market consists of several segments with different degrees of aversion to delays. The firm offers a price schedule under which the customers each self-select the price they pay and when their orders are to be shipped. When a customer agrees to wait, the firm gains advanced demand information that can be used to reduce its supply chain costs. This article shows how an optimal pricing-replenishment strategy that balances the costs due to discounted prices and the benefits due to advanced demand information can be determined.

One-Warehouse Multiretailer Systems with Centralized Stock Information

We consider a distribution system with a central warehouse and multiple retailers. The warehouse orders from an outside supplier and replenishes the retailers which in turn satisfy customer demand. The retailers are nonidentical, and their demand processes are independent compound Poisson. There are economies of scale in inventory replenishment, which is controlled by an echelon-stock, batch-transfer policy. For the special case with simple Poisson demand, we develop an exact method for computing the long-run average holding and backorder costs of the system. Based on this exact method, we provide approximations for compound Poisson demand. Numerical examples are used to illustrate the accuracy of the approximations. We also present a numerical comparison between the average costs of a heuristic, echelon-stock policy and an existing lower bound on the average costs of all feasible policies.

Quantifying the Value of Leadtime Information in a Single-Location Inventory System

This article studies a single-location inventory model with random leadtimes. Inventory is replenished by a single supplier who, at the time a replenishment order is received, knows exactly when the order will be delivered. In other words, the supplier knows the leadtime for every replenishment order. Suppose the single-location inventory system is managed by a retailer. The objective of this article is to quantify the value of the information about leadtimes to the retailer. This is achieved by considering and comparing the performances of two scenarios whether or not the supplier shares his leadtime information with the retailer. Numerical evidence suggests that the value of leadtime information can be significant.

Near-Optimal Pricing and Replenishment Strategies for a Retail/Distribution System

This paper integrates pricing and replenishment decisions for the following prototypical two-echelon distribution system with deterministic demands. A supplier distributes a single product to multiple retailers, who in turn sell it to consumers. The retailers serve geographically dispersed, heterogeneous markets. The demand in each retail market arrives continuously at a constant rate, which is a general decreasing function of the retail price in the market. The supplier replenishes its inventory through orders (purchases, production runs) from a source with ample capacity. The retailers replenish their inventories from the supplier. We develop efficient algorithms to determine optimal pricing and replenishment strategies for the following three channel structures. The first is the vertically integrated channel, where the system-wide pricing and replenishment strategies are determined by a central planner whose objective is to maximize the system-wide profits. The second structure is that of a vertically integrated channel in which pricing and operational decisions are made sequentially by separate functional departments. The third channel structure is decentralized, i.e., the supplier and the retailers are independent, profit-maximizing firms with the supplier acting as a Stackelberg game leader. We apply our algorithms to a set of numerical examples to quantify the supply chain inefficiencies due to functional segregation or uncoordinated decision making in a decentralized channel. We also gain insight into systematic differences in the associated pricing and operational patterns.

Sales-Force Incentives and Inventory Management

This article studies the problem of sales-force compensation by considering the impact of sales-force behavior on a firms production and inventory system. The sales forces compensation package affects how the salespeople are going to exert their effort, which in turn determines the sales pattern for the firms product and ultimately drives the performance of the firms production and inventory system. In general, a smooth demand process facilitates production/inventory planning. Therefore, it is beneficial for a firm to induce its salespeople to exert effort in a way that actually smoothes the demand process. The article proposes a compensation package to induce such behavior. It evaluates and compensates the sales force on a moving-time-window basis, where the length of the time window is determined by the production lead time. Numerical examples show that the proposed package is beneficial to the firm relative to a widely used compensation plan based on annual quotas.