Supply chain coordination issues have been of great interest to researchers for many years especially since 1990s there has been a surge in research in these topics (Burgess et al. 2006). Different perspectives has been proposed on SCC such as “the order, forecasting, procurement, and information sharing procedures among the members of the supply chain” (Therese M. Flaherty, 1996) and “SCC is concerned with managing dependencies between various supply chain members and the joint efforts of all supply chain members to achieve mutually defined goals” (Arshinder, Arunda Kapur, 2007).
According to (Omkar D. Palsule-Desai 2012) a SC is perfectly coordinated when the decisions on optimal quantity to be ordered by retailer under decentralized setting equals that of centralized one and yields non-zero profit to both players. There exist two common structures for SC management: Centralized or integrated supply chain with the single decision maker and decentralized with a network consists of multiple decision makers having different information and incentives.
Evidence exists that centralized structure is the ideal status of the SC when there are more than two decision makers since otherwise the profit would be less than optimal. ( Tirole1990, Corbet and tang 1999,corbet et al 2004) Decentralized decision making gives rise to problems causing sub-optimality: double marginalization (Spengler 1950), high inventory holding costs (Boctor et al. 2004),low response time and flexibility (Iyer and Bergen 1997), opportunism created by bilateral dependent relations (Williamson, 1996), risk and vulnerability (Pfohl et al.2010) , excess inventory, lead times, lost sales, manufacturing costs, customer retention, and revenue enhancements (Fisher et al. 1994; Lee et al. 1997) and etc.
SC coordination decisions revolve around different topics. For instance, logistics (Stock et al. 2000), inventory (Piplani and Fu 2005, Zou et al. 2004, Wu and Ouyang 2003), forecasting (Avis 2001), Integrated production-distribution, integrated procurement-production (Kim et al. 2006) and etc. The degree to which mechanisms manage to succeed in coordination reflects in SC profitability, flexibility, handling uncertainty (Kaur Arshinder et al.2011).
Various methods exist in the literature to coordinate SC (page 14): information technology, information sharing, joint decision making (cost consideration, forecasting, ordering and Order coordination , revenue sharing contracts), resource sharing, knowledge sharing, joint working, joint design and development of product, joint promotions, implementing information systems, designing risk sharing contracts, saving sharing (Chen and Chen, 2005) SC contracts are quite popular and widely adopted in coordinating supply chain. Raut et al. asses the profit impact of various SC contracts.
According to T. Coltman, issues that continue to exist are the feasibility of cooperation in contract design process, the way firms cooperate to achieve efficiency and equitability in contracts and renegotiating contracts to mitigate the risks in contract design (T. Coltman et al. 2009). They believe that contracts evolve as time passes due to trust building and information transparency. “Routine can also be used to foster a climate of positive reinforcement independent of trust that can allow firms to avoid detailed monitoring and coordination costs” (Zollo et al., 2002).
Supply chain contracts are designed to motivate the downstream members to order more than their optimal order quantities. Cost of overstock motivates downstream members to order less than optimal quantity that can maximize supply chain profit. Contracts like buyback and revenue sharing contracts can enhance expected sales and reduces risk of retailer like stock outs and risk of supplier like inability to match capacity when order comes. Different Types of Contracts Revenue sharing contracts is one type of contracts used in coordinating supply chain.
Cachon, in particular, compare and contrast revenue sharing with other contracts – such as buyback, price-discount, quantity-discount, quantity flexibility, etc. – mentioned in the literature (Cachon, 2003) and (Cachon and Lariviere 2005). They claim that revenue sharing motivates the retailer to order the supply chain optimal quantity thus the supply chain will be coordinated. The coordinating contract is independent of the revenue function and revenue sharing is based on fixed predetermined sharing factors. One contract can coordinate a supply chain with multiple independent retailers.
Buy-back contracts are used in coordinating the fixed-price newsvendor (Pasternack 1985). The manufacturer (seller) agrees to buy back the unsold units from the retailer (buyer) for agreed prices at the end of the selling season (Hau and Li, 2008). Cachon et Al. show that coordinating buy-back contract results in the same share of expected channel profits as the coordinating revenue-sharing contract for any demand. This can be explained by the fact that a buy back is equivalent to reducing the retailer’s cost of purchasing a unit while also reducing the fraction of revenue he keeps.
They have shown that buy back contract is a special case of their proportional revenue-sharing contract and that contract can coordinate problems that buy backs cannot. In particular, since a coordinating revenue-sharing contract is independent of the retail price, it can coordinate a newsvendor problem with price-dependent demand. According to them, there exist some limitations for revenue sharing contracts including additional administrative cost, retailer effort and moral hazard that should be taken into account in evaluating non-contract coordination vs.a contract one.
Taylor (2002) and Krishnan et al. (2004) combine a buy-back contract with a sales-rebate contract to coordinate the newsvendor with effort-dependent demand. In Sales-rebate contract the supplier charges the buyer a per unit wholesale price but then gives the buyer a rebate per unit sold above a fixed threshold. Like buy-backs or quantity flexibility contracts, sales-rebate contracts coordinate the fixed-price newsvendor when properly designed, but are not appropriate for the price-setting newsvendor.
(Krishnan et al. 2004, Taylor 2002) For the fixed-price newsvendor, the quantity discount achieves coordination. Quantity discount contracts are similar to revenue-sharing contracts, because with both contracts, the buyer’s expected profit is proportional to the supply chain’s expected profit. Still, these contract types are not equivalent (Cachon and Lariviere 2005). A quantity flexibility contract achieves coordination of the fixed-price newsvendor problem by compensating the buyer for a certain amount of unsold goods.
Although the benefit for the buyer is a gain in quantity flexibility, she should be prepared to pay a higher cost per unit compared to a pure wholesale price contract to compensate the supplier for the increased exposure to demand uncertainty. QF contracts can bring about further benefits for a supplier: FQ spoils time window of reordering thus correcting the order is difficult. Consequently, the buyer is motivated to order more to recoup the costs of under stock. If supplier and buyer agree that the final order must be in a range predefined by a QF contract, this can improve forecasts. (Tsay et al.1999)
Tsay and Lovejoy (1999) study a more complex problem with multiple locations, periods, lead times, and forecast updates. In these multi-period models, they show that QF contracts decrease order variability, setting back the bullwhip effect. Cachon and Lariviere (2005) compare QF contracts to revenue-sharing and demonstrate several differences. Unlike the revenue-sharing contract, the QF contract cannot coordinate the price-setting newsvendor. Moreover, a coordinating QF contract depends on the demand distribution, which implies that one cannot simply write down a contract that works for all markets.