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...inventory-related shortage-related within supply chain. For instance, quick response is a strategy that focuses on reducing lead times for fashion merchandise. Other strategies such as efficient consumer response, continuous replenishment program, and collaborative planning forecasting and replenishment allow manufacturers and retailers to share inventory and demand data in order to reduce the "bullwhip effect" in a distribution channel (Lee et al., 1997). The cornerstone of these techniques is the sharing of information between trading partners within a supply chain because the decisions made at each level have implication across the entire chain. However, credibility is a key factor in the exchange of information because each party may have an incentive to distort its information to influence the receiver's decisions. In addition, the possibility of the party receiving the information to use the information only for its own benefit may give rise to certain disincentives to information sharing. Hence, mechanisms that can diminish such opportunistic behavior while allowing for increased benefits from information sharing are critical to the creation of efficient supply chains.
Prior studies on supply chain information sharing have assumed that information is shared truthfully and thus they do not consider incentives for information distortion. However, we show that when each player in the supply chain makes its decision based on its private information, each has an incentive to share distorted information with others. Many supply chains suffer from information asymmetry issues. Information asymmetry may be a result of different interpretations of the same information or access to different information sets by the manufacturer and the retailer. One example of potential difference in beliefs about the demand can be found in the markets for newly introduced products (Neelamegham and Chintagunta, 1999). Our notion of information asymmetry is different from the traditional notion in which one party is assumed to have superior information. In our context neither party is endowed with superior information, ex ante.
Manufacturers and retailers in some industries use return policies to deal with information asymmetry problems (Kandel, 1996). Recent efforts attempt to address the underlying information asymmetry problems through information sharing. Lee et al. (1997) were the first to propose the sharing of end-consumer demand data within a supply chain to reduce the bullwhip effect caused by information asymmetry. To prevent the receiving party from using the shared information only to its advantage, the parties often enter into price and service-level contracts before sharing information. For instance, major manufacturers (e.g., Proctor and Gamble, Kraft, Pillsbury, etc.) and retailers (e.g., Wal-Mart) negotiate Every Day Low Price (EDLP) contracts (Lee et al. 1997). We show that such negotiated price contracts between manufacturers and retailers, both at the retail and wholesale levels, eliminate the disincentives for information sharing and information distortion in supply chains.
The main results of our study can be summarized as follows. We demonstrate that if both parties share their forecasts truthfully, the manufacturer always benefits; however, the retailer benefits only if the manufacturer sets a lower wholesale price when information is shared compared to when information is not shared. However, we also show that the manufacturer and the retailer, respectively, have an incentive to overstate and understate their forecasts while sharing information. Unless each party can verify the authenticity of the other party's information, these information distortions may reduce the benefit levels or even prohibit information sharing in supply chains. The incentives to distort information are eliminated and both parties benefit from information sharing if the manufacturer and the retailer can agree on their relative profit margins (or equivalently relative profits) prior to information sharing.
The rest of the paper has the following structure. We review the related literature in Section 2. We discuss the model framework in Section 3. In Section 4, we analyze the impact of information sharing and present the results. We illustrate the analysis using a numerical example in Section 5. We offer managerial implications of our theoretical results in Section 6. We conclude the paper in Section 7.
2. Literature review
Several types of information sharing in supply chains have been analyzed in the literature (Tayur et al. 1999). Bourland et al. (1996) derived the benefits of information sharing when the review period of the manufacturer is not synchronized with that of the retailer. Gavirneni et al. (1999) studied the value of information sharing for a finite-capacity supplier facing demands from a single retailer following a (s, S) policy. Lee et al. (2000) studied the benefit of demand information sharing when the underlying demand process faced by the retailer is a AR(1) process. Raghunathan (2001) showed that the results derived by Lee et al. (2000) overestimate the benefit of demand information sharing if the manufacturer uses the entire order history to do its forecast. Chen et al. (2000) quantified the bullwhip effect for a simple two-stage supply chain and demonstrated that centralizing demand information can significantly reduce the increase in variability. Cachon and Fisher (2000) studied the value of sharing data in a model with one supplier, N identical retailers, and stationary stochastic consumer demand. They concluded that accelerating the physical flow of goods through a supply chain is significantly more valuable than exchange of information. Gallego et al. (2000) showed that delay base stock policies can capture a significant portion of the benefits of demand information sharing. Aviv (2001) investigated the value of collaborative forecasting and integrating retailer forecasts into the manufacturer's replenishment process. Gavirneni (2002) showed that the benefit of information sharing to the manufacturer is significant when the wholesale price alternates between high and low levels. All these papers investigated the inventory-related and shortage-related benefits of information sharing.
Li (2002) considered the effects of information sharing on pricing decisions within a supply chain consisting of one manufacturer and multiple competing retailers. He showed that retailers would not voluntarily share their information. He identified conditions under which the manufacturer would be able to buy retailer information. Similar results were also shown by Zhang (2002). Mishra et al. (2006) show how a discount-based contract may enable a manufacturer to induce information sharing under a broader set of conditions. More recently, Li and Zhang (2005) analyzed different information-sharing scenarios with varying degrees of confidentiality of information.
Our paper relates to recent papers with respect to the modeling framework, e.g., Winkler's model of information aggregation, used for information sharing. Yao et al. (2005) discussed information-sharing issues under different channel configurations. Raghunathan and Yue (2006) analyzed return policies as a way to implement information sharing in a supply chain. However, the problems considered by these papers and ours are different.
Our work differs from the bulk of supply chain information exchange literature in one key respect. Prior research assumes that information is always shared truthfully, and thus does not focus on information distortion. We analyze the incentives for information distortion and propose a mechanism in which the disincentives for information sharing and incentives for information distortion are eliminated.
Our work is also related to the supply chain coordination and contracts literature. Cachon and Lariviere (2005) demonstrated that revenue sharing coordinates a supply chain with a single retailer. Wang et al. (2004) studied consignment contracts with revenue sharing. They showed, under such a contract, that both the overall channel performance and the performance of individual firms depend critically on demand-price elasticity and on the retailer's share of the channel cost. Gerchak and Wang (2004) derived the equilibrium revenue-sharing allocation and production quantities in an assembly system. Lariviere and Porteus (2000) studied the case in which an upstream vendor sets the wholesale price for a retailer facing a newsvendor problem. Tsay et al. (1999) reviewed this literature in the supply management area. They pointed out that "virtually all multi-player models (in this review) rely at some level on common knowledge of all parameters." Recently, researchers have started to model the information asymmetry between players. Corbett (1999), Ha (1999) and Porteus and Whang (1999) considered contracting problems in which the party offering the contract is less informed than its potential partner. Their emphasis was on inducing information revelation. Cachon and Lariviere (2001) addressed the contracting problem in which a manufacturer, who offers the contract to a supplier, has superior information and derived contracts that allow the manufacturer to share its demand forecast credibly with its supplier. Li et al. (2005) studied the role of forward commitments and option contracts in a supply chain with asymmetric information. In their model, the supplier is assumed to be less informed about the demand distribution than the retailer. They examined how profits are affected by the contracting arrangements and by the degree of asymmetric information. Chakravarty and Zhang (2005) addressed the optimal contracting problem between two firms collaborating on capacity investment.
Unlike the contract literature in which one party is usually assumed to have superior information, both parties have private information in our model. Consequently, neither party can design a take-it-or-leave-it contract and still enjoy the benefits of information sharing.
Marketing and economics literature has also studied the impact of forecast sharing on pricing. This literature typically considers the competition in a duopoly that uses different forecasts of the market demand. Vives (1984) identified conditions under which the sharing of private information between competitors is profitable. Raju and Roy (2000) analyzed the impact of firm size, product substitutability, and intensity and mode of competition on the value of forecast information. Unlike the studies in the marketing and economics literature mentioned above, our study investigates the sharing of forecast information within a vertical supply chain. A supply chain differs from a duopoly in that the manufacturer and the retailer in a supply chain are competitors in a vertical sense, rather than the usual horizontal competition among retailers considered by the marketing literature. In the supply chain we consider, the end-consumer demand is dependent only on the retailer price, which, in turn, depends on the wholesale price. In a duopoly, demand is affected by the prices of both firms and both firms compete for the same customers.
3. Model framework
We analyze a two-level supply chain that has one retailer and one manufacturer and sells a single product. The production cost to the manufacturer is c per unit. The cost to the retailer is the wholesale price...
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