مشخصات پژوهش

Effective supply chain coordination is a key strategy for enhancing profitability across the entire channel. This coordination is typically facilitated through contracts, such as the buyback contract, which allows a retailer to return unsold items to the supplier at a reduced price. However, efficient decision-making within these contracts depends on reliable demand forecasts. Market demand is inherently uncertain, and this challenge is acute for innovative products that lack historical data. The absence of data prevents the application of probability theory for demand prediction, while fuzzy theory also has drawbacks that can lead to misleading results. To address this, we employ uncertainty theory to analyze how a buyback contract can counteract the undesirable effects of double marginalization. We model a supply chain with one supplier and two retailers. In one scenario, each player operates independently, using its own estimate of demand which is modeled as an uncertain variable, to determine order and supply levels. In a second, coordinated scenario, the retailers share their demand estimates with the supplier, who then decides on the supply level for each. We demonstrate our findings with a prototype example where demand follows a linear uncertainty distribution and also describe how such distributions can be practically estimated.