晴读（35）：精读期刊论文

摘要：回收渠道竞争关系激励模型（模型SN）。该部分构建了竞争关系下制造商的契约设计规划问题（P1），通过目标函数（5）最大化制造商期望效用，并以参与约束式（6）保证回收商接受契约、激励相容约束式（7）确保回收商选择自身期望效用最大化的努力水平，求解后得到命题1，明确

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“晴读（35）：精读期刊论文《基于委托代理理论的逆向供应链激励机制设计与回收模式选择》的能力信息对称下的激励机制设计模型”

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"Qing Du (35): Intensive Reading of the Journal Paper "Incentive Mechanism Design and Recycling Mode Selection in Reverse Supply Chains

Based on Principal-Agent Theory:" Incentive Mechanism Design Under Symmetric Ability Information

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今天小编将从思维导图、精读内容、知识补充三个板块为大家带来《基于委托代理理论的逆向供应链激励机制设计与回收模式选择》的能力信息对称下的激励机制设计模型。

一、思维导图（Mind Map）

二、内容精读（Conduct in-depth reading of the material）

1.回收渠道竞争关系激励模型（模型SN）。该部分构建了竞争关系下制造商的契约设计规划问题（P1），通过目标函数（5）最大化制造商期望效用，并以参与约束式（6）保证回收商接受契约、激励相容约束式（7）确保回收商选择自身期望效用最大化的努力水平，求解后得到命题1，明确了能力信息对称且竞争关系下制造商为回收商提供的最优契约（包含α和β的具体表达式）、回收商的最优努力水平，以及回收商和制造商各自的最优期望效用，为竞争关系下的激励机制设计提供了量化依据。

1. Incentive Model for Competitive Relationship in Recycling Channels (Model SN). This section constructs the manufacturer's contract design programming problem (P1) under competitive relationships. It maximizes the manufacturer's expected utility through the objective function (5), uses the participation constraint equation (6) to ensure recyclers accept the contract, and the incentive compatibility constraint equation (7) to ensure recyclers choose the effort level that maximizes their own expected utility. After solving, Proposition 1 is obtained, which clarifies the optimal contract (including specific expressions of α and β) provided by the manufacturer to recyclers, the recyclers' optimal effort level, and the respective optimal expected utilities of recyclers and the manufacturer under the conditions of symmetric ability information and competitive relationships, thereby providing a quantitative basis for the design of incentive mechanisms under competitive relationships.

2.回收渠道合作关系激励模型（模型SC）。此部分针对合作关系设计了制造商契约设计规划问题（P2），其目标函数旨在最大化制造商期望效用，约束条件同样包含保证回收商接受契约的参与约束和引导回收商选择最优努力水平的激励相容约束，通过求解该规划问题得出命题2，确定了能力信息对称且合作关系下制造商给回收商的最优契约参数、回收商的最优努力水平，以及双方的最优期望效用，与竞争关系模型形成对比，为合作关系下的激励机制提供了理论支撑。

2. Incentive Model for Cooperative Relationship in Recycling Channels (Model SC). This section designs the manufacturer's contract design programming problem (P2) for cooperative relationships. Its objective function aims to maximize the manufacturer's expected utility, and the constraint conditions also include the participation constraint to ensure recyclers accept the contract and the incentive compatibility constraint to guide recyclers to select the optimal effort level. By solving this programming problem, Proposition 2 is derived, which determines the optimal contract parameters provided by the manufacturer to recyclers, the recyclers' optimal effort level, and the respective optimal expected utilities of both parties under the conditions of symmetric ability information and cooperative relationships. It forms a contrast with the competitive relationship model and provides theoretical support for the design of incentive mechanisms under cooperative relationships.

3.静态比较分析。基于命题1和命题2的结果，该部分展开能力信息对称下模型参数对回收绩效的影响分析，得出推论1、推论2和推论3。推论1阐述了最优回收绩效分享比例βiS∗在不同关系（竞争或合作）下，随努力成本系数a、绝对风险规避系数ρ、不确定因素σ²、努力产出系数b、竞争强度系数k、合作强度系数t等参数变化的规律及背后原因；推论2表明无论竞争还是合作关系，最优努力水平eSi∗随k（或t）、b增大而增大，随a、ρ、σ²增大而减小的共性特征及逻辑；推论3则指出制造商最优期望效用UMS∗随k（或t）增大而增大，且两种关系下回收商均仅获得固定期望效用-ω的结论，为理解参数影响提供了全面视角。

3. Static Comparative Analysis. Based on the results of Proposition 1 and Proposition 2, this section conducts an analysis on the impact of model parameters on recycling performance under symmetric ability information, and derives Corollary 1, Corollary 2, and Corollary 3. Corollary 1 expounds the variation rules and underlying reasons of the optimal recycling performance sharing ratio βiS∗ under different relationships (competitive or cooperative) with parameters such as the effort cost coefficient a, absolute risk aversion coefficient ρ, uncertainty factor σ², effort output coefficient b, competition intensity coefficient k, and cooperation intensity coefficient t; Corollary 2 indicates the common characteristics and logic that the optimal effort level eSi∗ increases with the increase of k (or t) and b, and decreases with the increase of a, ρ, and σ², regardless of competitive or cooperative relationships; Corollary 3 points out the conclusion that the manufacturer's optimal expected utility UMS∗ increases with the increase of k (or t), and recyclers only obtain a fixed expected utility -ω under both relationships, providing a comprehensive perspective for understanding the impact of parameters.

4.回收模式决策分析。该部分围绕能力信息对称下制造商的回收模式选择展开，先通过推论4分析竞争与合作强度对回收商努力水平的影响，明确不同强度组合下（t与t0、k与T0的关系）回收商在两种关系下最优努力水平的高低情况及对应策略；再通过命题3给出制造商选择回收模式的最优策略条件，依据t与t1、k与T1的关系确定不同强度组合下制造商在两种关系中最优期望效用的高低，同时进一步分析了T1随t、a、ρ、σ²变化的规律及制造商选择合作模式意愿变化的原因，为制造商实际回收模式决策提供了明确指引。

4. Recycling Mode Decision Analysis. This section focuses on the manufacturer's recycling mode selection under symmetric information about ability. First, through Corollary 4, it analyzes the impact of competition and cooperation intensity on recyclers' effort levels. It clarifies the comparison of recyclers' optimal effort levels under the two relationships (competitive and cooperative) and the corresponding strategies under different intensity combinations (the relationships between t and t0, k and T0). Then, through Proposition 3, it puts forward the optimal strategy conditions for manufacturers to select recycling modes, determines the comparison of manufacturers' optimal expected utilities under the two relationships under different intensity combinations based on the relationships between t and t1, k and T1, and further analyzes the variation rules of T1 with t, a, ρ, σ² as well as the reasons for the changes in manufacturers' willingness to choose the cooperative mode, providing clear guidance for manufacturers' practical recycling mode decisions.

三、知识补充（Supplementary Knowledge）

1.风险厌恶：风险厌恶是经济学和决策理论中描述个体或主体面对不确定性时决策偏好的核心概念，指当面对期望收益相同但风险程度不同的选项时主体更倾向于选择风险更低、结果更确定的选项而非风险更高、结果波动更大的选项。

1. Risk Aversion: Risk aversion is a core concept in economics and decision theory that describes the decision-making preferences of individuals or entities when facing uncertainty. It refers to the tendency of an entity to prefer options with lower risk and more certain outcomes over those with higher risk and greater outcome volatility, when the expected returns of these options are the same.

2.Holmstrom委托代理模型：由经济学家Bengt Holmstrom提出的、用于分析委托人和代理人之间信息不对称问题的经典理论模型，其核心是研究在代理人行动难以被委托人直接观察（或观察成本极高）且存在不确定性因素影响最终产出的情况下，委托人如何设计最优激励契约，以引导代理人选择符合委托人利益的行动，从而平衡代理人的个人利益与委托人的目标，解决因信息不对称可能引发的“道德风险”问题，该模型为后续企业治理、供应链管理、劳动契约设计等领域的激励机制研究提供了重要理论基础。

2. Holmstrom Principal-Agent Model: A classic theoretical model proposed by economist Bengt Holmstrom, which is used to analyze the information asymmetry problem between principals and agents. Its core is to study how the principal designs an optimal incentive contract to guide the agent to choose actions that are in line with the principal's interests, under the circumstances where the agent's actions are difficult for the principal to directly observe (or the observation cost is extremely high) and there are uncertain factors affecting the final output. This helps balance the agent's personal interests with the principal's goals and solve the "moral hazard" problem that may arise due to information asymmetry. The model provides an important theoretical foundation for subsequent research on incentive mechanisms in fields such as corporate governance, supply chain management, and labor contract design.

3.Milgrom委托代理模型：是经济学家Paul Milgrom在委托代理理论框架下提出的重要拓展模型，其核心是在传统委托代理问题的基础上，进一步纳入多任务场景、团队协作或动态决策等更贴近现实的因素，研究当代理人需同时处理多个具有不同产出特性或优先级的任务（或存在多代理人协作）时，委托人如何设计兼顾任务间平衡的激励契约，以避免代理人因单一任务的强激励而忽视其他重要任务（即“任务间替代效应”），从而实现对代理人行为的更精准引导，该模型为解决多任务委托代理场景下的激励协调问题提供了关键理论支撑，广泛应用于组织管理、薪酬设计等领域。

3. Milgrom Principal-Agent Model: An important extended model proposed by economist Paul Milgrom under the framework of principal-agent theory. Its core is to further incorporate more realistic factors such as multi-task scenarios, team collaboration, or dynamic decision-making based on traditional principal-agent problems. It studies how the principal designs an incentive contract that balances multiple tasks when the agent needs to handle multiple tasks with different output characteristics or priorities (or when there is multi-agent collaboration), to prevent the agent from neglecting other important tasks due to strong incentives for a single task (i.e., the "inter-task substitution effect"), thereby achieving more precise guidance on the agent's behavior. This model provides key theoretical support for solving incentive coordination problems in multi-task principal-agent scenarios and is widely applied in fields such as organizational management and compensation design.

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