Optimal planning of incentive-based quality in closed-loop supply chains

Electronic firms are being required to collect used products for environmental purposes. In order to meet requirements, these firms carry out collection activities and provide incentive offers to attract product returns. These product returns may then undergo recovery options such as refurbishing, remanufacturing, cannibalizing, and controlled disposal. A mixed integer nonlinear programming model for a closed-loop supply chain that includes decisions for collection activities, incentive offers, and recovery options is formulated and validated. Quantity is modeled as a function of incentive offers between the collection centers and consumers, while quality of product returns follows an arbitrary probability distribution based on the incentive level. Quality of product returns dictates the possible recovery options, which these products can undergo. The model is then subjected to scenario analysis, which identified conditions wherein rebate or discount incentives are preferred, and when low or high incentive levels are favored. High stockout costs to secondary consumers encouraged the model to perform more cash rebate activities to stimulate more product returns. Meanwhile, when both the costs of activities and stockouts are high, the model is induced to carry out discount activities as this would generate sales rather than the cash rebate which simply incentivizes the participation in the take-back program.