风险博弈与行政指导下的消费品召回管理协同机制研究

摘要：

【目的】针对消费品供应链复杂化背景下，监管机构与企业因信息不对称在缺陷认定中产生的博弈冲突，研究如何通过行政指导构建协同治理机制。【方法】构建非完全信息动态博弈模型，量化监管方“社会福利最大化”与企业“损失最小化”的目标函数；分析行政约谈在信号传递与置信威胁中的重构作用；结合案例，剖析“召回不足”与“过度召回”的成因。【结果】行政约谈能打破信息垄断，促使企业后验信念向真实风险收敛，引导博弈从“混同均衡”向“分离均衡”跃迁。案例证明，监管能力缺失会导致召回不足，而舆论压力扭曲声誉函数则会引发过度召回；行政指导可有效调整支付结构，引导企业策略向公共利益靠拢。【结论】应建立基于风险矩阵的预协商与专家仲裁机制，构建单品级数字化追溯体系，实施动态分级响应与差异化补救，推动召回治理从对抗走向协同，实现安全与效率的平衡。

Abstract:

[Objective] Aiming at the game conflicts between regulatory agencies and enterprises in defect identification caused by information asymmetry in the context of complex consumer product supply chains, this paper studies how to construct a collaborative governance mechanism through administrative guidance. [Methods] An incomplete information dynamic game model is constructed to quantify the objective functions of “social welfare maximization” for regulators and “loss minimization” for enterprises. The study analyzes the reconstructive role of administrative interviews in signal transmission and credible threats. Combined with cases, the causes of “under-recall” and “over-recall” are analyzed. [Results] Administrative interviews can break information monopolies, prompting enterprises’ posterior beliefs to converge toward true risks and guiding the game from a “pooling equilibrium” to a “separating equilibrium”. Cases demonstrate that a lack of regulatory capacity leads to under-recall, while public opinion pressure distorting the reputation function triggers over-recall. Administrative guidance can effectively adjust the payoff structure and steer enterprise strategies toward the public interest. [Conclusion] It is recommended to establish pre-consultation and expert arbitration mechanisms based on risk matrices, construct single-item digital traceability systems, and implement dynamic hierarchical responses and differentiated remedies. These measures aim to shift recall governance from confrontation to collaboration, achieving a balance between safety and efficiency.

引用格式：李雪，朱一，张天龙. 风险博弈与行政指导下的消费品召回管理协同机制研究[J]. 标准化学报，2026(8)：26-31.

基金项目：本文受国家市场监督管理总局科技计划项目“基于电商平台评论数据的人工智能分析技术在消费品危害识别与风险评估预警中的应用研究”（项目编号：2024MK037）；江苏省市场监督管理局科技计划项目“激励耦合视角下产品召回信用监管机制构建与技术工具开发研究”（项目编号：KJ2026057）资助。

作者简介：李雪，硕士，工程师，研究方向为缺陷产品召回管理。朱一，大专，工程师，研究方向为缺陷产品召回管理。张天龙，通信作者，博士，正高级工程师，研究方向为缺陷产品召回管理及标准化。