In this study, we investigate the effects of recovery yield rate on pricing decisions in reverse supply chains. Motivated by the automotive parts remanufacturing industry, we consider an end‐of‐life product from which a particular part can be recovered and remanufactured for reuse, and the remainder of the product can be recycled for material recovery. Both the supply of end‐of‐life products and demand for remanufactured parts are price‐sensitive. Yield of the recovery process is random and depends on the acquisition price offered for the end‐of‐life products. In this setting, we develop models to determine the optimal acquisition price for the end‐of‐life products and the selling price for remanufactured parts. We also analyze the effects of yield variation to the profitability of remanufacturing, benefits of delaying pricing decisions until after yield realization, and value of perfect yield rate information.

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In traditional supply chain models it is generally assumed that full information is available to all parties involved. Although this seems reasonable, there are cases where chain members are independent agents and possess different levels of information. In this study, we analyze a two-echelon, single supplier-multiple retailers supply chain in a single-period setting where the capacity of the supplier is limited. Embedding the lack of information about the capacity of the supplier in the model, we aim to analyze the reaction of the retailers, compare it with the full-information case, and assess the value of information and the effects of information asymmetry using game theoretic analysis. In our numerical studies, we conclude that the value of information is highly dependent on the capacity conditions and estimates of the retailers, and having information is not necessarily beneficial to the retailers.

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pagesSupply disruptions have important effects on supply chains causing serious financial and intangible damages. In this study, we consider an infinite horizon, continuous review inventory model with deterministic stationary demand where supply is subject to disruption. The supply process alternates between two states randomly: one in which it functions normally ("ON" period) and one in which it is disrupted ("OFF" period). Unsatisfied demand is backordered in off periods. In this setting we seek the value of disruption orders which can be placed at the beginning of OFF-periods with the same fixed cost. Utilizing renewal theory, we derive the total expected cost function and determine the cost minimizing regular order-up-to level and characterize the order-up-to level for disruption orders. We also conduct an extensive numerical analysis and compare the results with the model with no opportunity of disruption orders. We conclude that if the shortage cost is relatively high, placing disruption order always reduces or does not change the expected total cost and if disruption orders are placed then the regular order-up-to levels is generally so close to EQO with backorders.