Dynamic game strategies for construction and demolition waste recycling with learning and reference effects

Construction and demolition waste (C&DW) recycling can effectively reduce the environmental impacts caused by the massive amounts of untreated C&DW, and can promote the sustainable development of the construction industry. This study aims to provide relevant insights for the implementation of C&DW recycling, and can be practically used to guide participants' dynamic strategies in the presence of both the reference price effect and cost learning effect. Based on game theory, a static model is developed as a benchmark, including a construction materials manufacturer and a C&DW recycler under a government subsidy. Then, a dual-period dynamic model combining the learning and reference effects is established to broaden the understanding of C&DW recycling management. On this basis, the decisions and revenues of players are compared and analysed, and managerial insights are obtained through numerical analysis. It is found that both the learning and reference effects affect the manufacturer's decisions and revenues, and that the reference effect has a much greater impact on profit than the learning effect. In addition, only the learning effect has a positive influence on the recycler's recycling efforts and profits, thereby promoting C&DW recycling and reducing environmental impacts. Moreover, government subsidies always benefit the environment and recycler, and as the learning ability becomes stronger, the subsidy becomes more efficient in reducing the environmental impacts and improving the recycler's profit. Comparatively, the impact of subsidy on the manufacturer's profits depends on the learning ability. When the learning ability is relatively high, a higher subsidy is detrimental to the manufacturer in the short term but benefits it in the long term.