In the 21^st century, the world is facing increasingly scarce natural resources and environmental pollution. The green supply chain has attracted attention, as it emphasizes the implementation of green environmental protection concepts in every link, especially the recycling and remanufacturing activities, which are very important for reducing negative environmental impacts and improving the economic efficiency of enterprises. Due to the existence of proprietary information in many parts of the green supply chain remanufacturing process, manufacturers may lie about the quality and quantity of recycling. By providing inaccurate or misleading information, manufacturers can mask actual environmental performance or gain an unfair economic or competitive advantage. Meanwhile, consumers and the market are increasingly concerned about corporate social responsibility in green supply chains. It is widely believed that enterprises should bear the corresponding social responsibility and environmental responsibility.
Based on these points, the article delves into the problem of misreporting during the recycling process within green supply chains, particularly the potential for manufacturers to misreport during the recycling of old mobile phones, as well as the impact of corporate social responsibility (CSR) on green supply chains. Remanufactured mobile phones consume less energy during the production process, effectively reducing the carbon footprint and protecting natural resources. This study employs the Stackelberg game approach, with the retailer as the leader and the manufacturer as the follower. It establishes a two-level green supply chain model that considers the manufacturer's information misreporting and corporate social responsibility. The optimal decisions of the supply chain members are analyzed within this framework. Following this, theoretical derivations are used to reveal the strategic choices and equilibrium outcomes of manufacturers and retailers under varying degrees of misreporting and social responsibility. Finally, through numerical simulations, the conclusions derived from these methods are validated, and the potential negative impact of false positives on supply chain efficiency is demonstrated. Based on these findings, corresponding management recommendations are proposed.