Asymmetric Demand Information Research Articles

Collaborative supply chain planning under dynamic lot sizing costs with capacity decision

Studies show that supply chain cooperation improves supply chain performance. However, it remains a challenge to develop and implement the realistic supply chain cooperation scheme. We investigate a two-echelon supply chain planning problem with capacity acquisition decision under asymmetric cost and demand information. A simple negotiation-based coordination mechanism is developed to synchronize production/order strategies of a supplier and a buyer. The coordination scheme shows how the supplier and the buyer modify their production and order policy in order to find a joint economic lot sizing plan, which saves the overall supply chain cost. The allocation of the cooperation benefit is determined by negotiation. Due to the complexity of the multiple periods, multiple level supply chain lot sizing with capacity decision, a heuristic algorithm is developed to find coordination solutions. Finally, the results of the numerical study indicate the performance of supply chain coordination scheme.

Contracting with Asymmetric Demand Information in Supply Chains

When a retailer holds no private information, a powerful supplier can use several contract types to extract for herself the first-best channel profit, leaving the retailer nothing but his reservation profit. In the case where the retailer holds private information on the probability distribution of market demand, most well analyzed contracts do not allow the supplier to achieve for herself the first-best channel profit. In equilibrium, the retailer is able to extract an information rent above his reservation profit, and the overall channel may deviate from its first-best solution. This paper shows that using judicially designed wholesale price contracts involving a buyback policy, a supplier can theoretically avoid paying any information rent to the privately informed retailer, and, at the same time, can extract all the first-best channel profit.

Commitment-penalty contracts in drop-shipping supply chains with asymmetric demand information

We study a drop-shipping supply chain in which the retailer receives a customer’s order and the supplier fills it. In such a chain, the supplier keeps inventory and bears inventory risks; the retailer focuses on marketing and customer acquisition, and forwards the orders to the supplier. The retailer usually has better customer demand information, and may send an over-estimated demand forecast to maximize her own interest, which may result in overstock for the supplier. On the other hand, since the retailer does not own inventory, the main concern of the retailer is that the acquired orders may not be fulfilled because of the supplier’s shortage of stock. To cope with these challenges, we propose a menu of commitment-penalty contracts that can provide greater certainty of demand as well as greater certainty of supply. We focus our study in the asymmetric demand information case and we show that the supplier can obtain the retailer’s demand information by offering a menu of commitment-penalty contracts. Under this mechanism, we find the solution that maximizes the supplier’s expected profit.

Mechanism Design for Capacity Planning Under Dynamic Evolutions of Asymmetric Demand Forecasts

This paper investigates the role of time in forecast information sharing and decision making under uncertainty. To do so, we provide a general framework to model the evolutions of forecasts generated by multiple decision makers who forecast demand for the same product. We also model the evolutions of forecasts when decision makers have asymmetric demand information and refer to it as the Martingale Model of Asymmetric Forecast Evolutions. This model helps us study mechanism design problems in a dynamic environment. In particular, we consider a supplier's (principal's) problem of eliciting credible forecast information from a manufacturer (agent) when both firms obtain asymmetric demand information for the end product over multiple periods. The supplier uses demand information to better plan for a capacity investment decision. When the supplier postpones building capacity and screening the manufacturer's private information, the supplier and the manufacturer can obtain more information and update their forecasts. This delay, however, may increase (respectively, decrease) the degree of information asymmetry between the two firms, resulting in a higher (respectively, lower) cost of screening. The capacity building cost may also increase because of a tighter deadline for building capacity. Considering all such trade-offs, the supplier has to determine (i) when to stop obtaining new demand information and build capacity, (ii) whether to offer a screening contract to credibly elicit private forecast information or to determine the capacity level without information sharing, (iii) how much capacity to build, and (iv) how to design the overall mechanism so that both firms benefit from this mechanism. This paper provides an answer to these questions. In doing so, we develop a new solution approach for a class of dynamic mechanism design problems. In addition, this paper provides a framework to quantify the option value of time for a strategic investment decision under the dynamic evolutions of asymmetric forecasts. This paper was accepted by Yossi Aviv, operations management.

Mechanism Design for Capacity Planning Under Dynamic Evolutions of Asymmetric Demand Forecasts

This paper provides a general framework to model the evolutions of forecasts generated by multiple decision makers who forecast demand for the same product. We also model the evolutions of forecasts when decision makers have asymmetric demand information and refer to it as the Martingale Model of Asymmetric Forecast Evolutions (MMAFE). This model helps us to study mechanism design problems in a dynamic environment. In particular, we consider a supplier's (principal's) problem of eliciting credible forecast information from a manufacturer (agent) when both firms obtain asymmetric demand information for the end product over multiple periods. The supplier uses demand information to better plan for a capacity investment decision. When the supplier postpones building capacity and screening the manufacturer's private information, the supplier and the manufacturer can obtain more information and update their forecasts. This delay, however, may increase (resp., or decrease) the degree of information asymmetry between the two firms, resulting in a higher (resp., or lower) cost of screening. The capacity building cost may also increase because of a tighter deadline for building capacity. Considering all such trade-offs, the supplier has to determine (i) when to stop obtaining new demand information and build capacity, (ii) whether to offer a screening contract to credibly elicit private forecast information or to determine the capacity level without information sharing, (iii) how much capacity to build, and (iv) how to design the overall mechanism so that both firms benefit from this mechanism. This paper provides an answer to these questions. It also provides a framework to quantify the option value of time for a strategic investment decision under the dynamic evolutions of asymmetric forecasts.

Ordering and pricing decisions in a two-echelon supply chain with asymmetric demand information

Abstract This article examines coordinated decisions in a decentralized supply chain that consists of one supplier and one retailer, and faces random demand of a single product with a short life cycle. We consider a setting where the retailer has accurate demand information while the supplier does not. Such a problem with asymmetric demand information can be viewed as an extension of the newsboy problem in which both the supplier and the retailer possess the same demand information. Combining the mechanism of sharing demand information and that of quantity discount and return policy enables us to develop three coordinated models in contrast with the basic and uncoordinated model. We are able to show the ordinal relationship among the retailer’s optimal order quantities in these four models under a general form of random demand, and compare the supply chain profits and conduct sensitivity analysis analytically in four models under uniform random demand. We also provide numerical results under normal random demand that bear a resemblance to those under uniform random demand.

A comparison of different quantity discount pricing policies in a two-echelon channel with stochastic and asymmetric demand information

In this paper, we study quantity discount pricing policies in a channel of one manufacturer and one retailer. The paper assumes that the channel faces a stochastic price-sensitive demand but the retailer can privately observe the realization of an uncertain demand parameter. The problem is analyzed as a Stackelberg game in which the manufacturer declares quantity discount pricing schemes to the retailer and then the retailer follows by selecting the retail price and associated quantity. Proposed in the paper are four quantity-discount pricing policies: “regular quantity discount”; “fixed percentage discount”; “incremental volume discount” and “fixed marginal-profit-rate discount”. Optimal solutions are derived, and numerical examples are presented to illustrate the efficiency of each discount policy.

Asymmetric Demand Information and Foreign Direct Investment*

AbstractWe examine the FDI versus exports decision of firms competing in an oligopolistic (quantity‐setting) market under demand uncertainty and asymmetric information. Compared to a firm that chooses to export, a firm that chooses to set up a plant in the host market has superior information about local market demand. In addition to the well‐known tension between the fixed set‐up costs of investment, the additional variable costs of exports and oligopoly sizes, the incentive to invest abroad is explained by the strategic learning effect. FDI may be observed even if trade costs are zero. The analysis is robust to price competition and to the possibility that a foreign firm can engage in both FDI and exports.

Quantity discounts in single-period supply contracts with asymmetric demand information

We investigate how a supplier can use a quantity discount schedule to influence the stocking decisions of a downstream buyer that faces a single period of stochastic demand. In contrast to much of the work that has been done on single-period supply contracts, we assume that there are no interactions between the supplier and the buyer after demand information is revealed and that the buyer has better information about the distribution of demand than does the supplier. We characterize the structure of the optimal discount schedule for both all-unit and incremental discounts and show that the supplier can earn larger profits with an all-unit discount.

A stochastic and asymmetric-information framework for a dominant-manufacturer supply chain

Consider a dominant manufacturer wholesaling a product to a retailer, who in turn retails it to the consumers at $ p/unit. The retail-market demand volume varies with p according to a given demand curve. This basic system is commonly modeled as a manufacturer-Stackelberg ([mS]) game under a “deterministic and symmetric-information” (“det-sym-i”) framework. We first explain the logical flaws of this framework, which are (i) the dominant manufacturer-leader will have a lower profit than the retailer under an iso-elastic demand curve; (ii) in some situations the system’s “correct solution” can be hyper-sensitive to minute changes in the demand curve; (iii) applying volume discounting while keeping the original [mS] profit-maximizing objective leads to an implausible degenerate solution in which the manufacturer has dictatorial power over the channel. We then present an extension of the “stochastic and asymmetric-information” (“sto-asy-i”) framework proposed in Lau and Lau [Lau, A., Lau, H.-S., 2005. Some two-echelon supply-chain games: Improving from deterministic–symmetric-information to stochastic-asymmetric-information models. European Journal of Operational Research 161 (1), 203–223], coupled with the notion that a profit-maximizing dominant manufacturer may implement not only [mS] but also “[pm]”—i.e., using a manufacturer-imposed maximum retail price. We show that this new framework resolves all the logical flaws stated above. Along the way, we also present a procedure for the dominant manufacturer to design a profit-maximizing volume-discount scheme using stochastic and asymmetric demand information. Using our sto-asy-i framework to resolve the logical flaws of the det-sym-i framework also reveals two noteworthy points: (i) the attractiveness of the perfectly legal but overlooked channel-coordination mechanism [pm]; and (ii) volume discounting as a means for the dominant manufacturer to benefit from information known only to the retailer.

Quantity Discounts in Single Period Supply Contracts with Asymmetric Demand Information

We investigate how supplier can use a quantity discount schedule to influence the stocking decisions of a downstream buyer that faces a single period of stochastic demand. In contrast to much of the work that has been done on single-period supply contracts, we assume that there are no interactions between the supplier and the buyer after demand information is revealed and that the buyer has better information about the distribution of demand than does the supplier. We characterize the structure of the optimal discount schedule for both all-unit and incremental discounts and show that the supplier can earn larger profits with an all-unit discount.

Asymmetric Demand Information in Uniform and Discriminatory Call Auctions: An Experimental Analysis Motivated by Electricity Markets

We study experimental multi-unit uniform and discriminatory auctions with demand uncertainty, motivated by the ongoing debate about market design in the electricity industry. We study the effect of asymmetric demand-information in the two auction institutions. In our treatment condition some sellers have less information than in our baseline conditions. In both conditions transaction prices and price volatility are not significantly different under the two auction institutions. However, under asymmetric information discriminatory auctions are significantly less efficient. These results are not in line with typical arguments made in favor of discriminatory pricing in electricity industries; namely, lower prices and less volatility.