Dynamic game strategies of a two-stage remanufacturing closed-loop supply chain considering Big Data marketing, technological innovation and overconfidence

Abstract

In the “Internet+” era, involving third-party Internet recycling platforms (IRPs) has revolutionized the operation models of closed-loop supply chains (CLSCs) in China. This study explores the impact of technological innovation, Big Data marketing and overconfidence on supply chain member decision-making. We propose a two-stage remanufacturing CLSC dynamic model consisting of a manufacturer, an IRP, and a supplier based on differential game theory. By comparing the optimal decisions of each member in three scenarios, we find that the IRP’s overconfident behavior is beneficial to both the manufacturer and the IRP but will damage the supplier's profit. Although a suitable cost-sharing ratio can enable the manufacturer and IRP to achieve a “win–win” situation, an excessive level of confidence will inhibit the incentives of the cost-sharing strategy, negatively affecting the manufacturer's interests. Interestingly, a cost-sharing contract will become inefficient under certain conditions, i.e., highly efficient level of technological innovation, highly efficient Big Data marketing, and a high level of overconfidence, negatively affecting the manufacturer’s interests. Additionally, technological innovation efficiency and marketing efficiency will have different effects on the IRP's recycling price. A cost-sharing contract and the IRP’s overconfidence will prompt the IRP to exert more efforts on technological innovation and Big Data marketing and to significantly reduce the manufacturing costs and recycling costs for all members. Notably, although the IRP’s overconfidence and cost-sharing strategies may damage the supplier’s profit, the total profit of the CLSC increases.