Dynamic Complexity Analysis of R&D Levels in the Automotive Industry under the Dual-Credit Policy

Abstract

The dual-credit policy, as an important emerging policy in the Chinese automotive industry intended to achieve energy savings, emissions reductions, and promote the development of new energy vehicles (NEVs), has attracted considerable attention from scholars. This study investigates how this policy affects the research and development (R&D) levels of both component suppliers and vehicle manufacturers in the automotive supply chain. Assuming the bounded rationality of the participants, we construct a complex dynamic evolutionary model under Stackelberg games to explore the impact of the policy on the dynamic game behavior and equilibrium stability of R&D levels. Furthermore, we examine the influences of various parameters on the R&D level complex system. The findings reveal that the disparity in the proportion of NEVs in the policy should not be too large; otherwise, bifurcation and chaos may occur in the R&D level game system. Moreover, higher supplier research efficiency contributes to the stability of R&D levels, while the higher credit trading price is not suitable for stable R&D levels. This paper theoretically reveals the dynamic impact of the dual-credit policy on the R&D levels in the automotive supply chain, bridging the gap between previous studies assuming decision-makers as fully rational and the reality of bounded rationality. It also provides managerial recommendations for the implementation details of this policy.