Better Demand Signal, Better Decisions? Evaluation of Big Data in a Licensed Remanufacturing Supply Chain with Environmental Risk Considerations

Big data ability helps obtain more accurate demand signal. However, is better demand signal always beneficial for the supply chain parties? To answer this question, we investigate a remanufacturing supply chain (RSC), where demand uncertainty is significant, and the value to reduce environmental risk is large. Specifically, we focus on a licensed RSC comprising an original equipment manufacturer (OEM) and a third-party remanufacturer (3PR). The latter pays a unit license fee to the former, and can be risk averse to the demand of remanufactured products. We show that the OEM and the risk-neutral 3PR always have incentives to improve their big data abilities to increase their profits. However, when the 3PR is risk averse, big data might hurt its profit: the value of big data is positive if its demand signal accuracy is sufficiently low. Interestingly, we find that while information sharing hurts the 3PR, it benefits the OEM as well as the supply chain. Thus, if costly information sharing is allowed, a win-win situation can be achieved. We also find that information sharing generates more valuation when the 3PR is risk averse than that when the 3PR is risk neutral. More importantly, we find that the 3PR's risk attitude and demand signal accuracy can significantly mitigate the negative environmental impact (measured by the amount of the waste): (1) the more risk neutral the 3PR is, the better the environment is; (2) the more accurate demand signal is, the better the environment is.