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E-Commerce Letters 2025
寡头垄断市场下非对称信息对企业决策的影响研究——基于Stackelberg博弈模型
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Abstract:
本文首先假定寡头垄断市场中的企业之间进行决策时,会通过影响市场价格进而影响对手企业的决策行为。在此基础上,利用推测变差方法构建了一个动态Stackelberg博弈模型。并假设市场中处于垄断主体的企业掌握了进入者企业的部分产量决策信息。在此基础上,对模型均衡点的稳定性与存在性进行了理论分析,并通过数值模拟,分析了推测变差和非对称信息对系统稳定性的影响。得到以下结论:第一,随着推测变差增大(或减小)到某个值,系统会失去稳定性,这说明市场竞争激烈程度过大或过小都会使得系统失稳。但引入非对称信息后,随着外推精度增大,推测变差减小,系统稳定性反而得到增强,此时激烈的市场竞争有利于系统稳定。第二,对比不存在非对称信息的经典情形,引入非对称信息后的系统稳定区域更大,抗初始值扰动能力更强。并且在完全不对称信息的情形下,系统的稳定区域达到最大。
This paper first assumes that when enterprises in an oligopolistic market make decisions, they will influence the decision-making behavior of rival enterprises by affecting the market price. On this basis, a dynamic Stackelberg game model is constructed by using the conjectural variation method. It is assumed that the enterprises in the dominant position of the monopoly in the market have mastered part of the output decision-making information of the entrant enterprises. On this basis, a theoretical analysis is carried out on the stability and existence of the equilibrium point of the model, and through numerical simulation, the impacts of conjectural variation and asymmetric information on the stability of the system are analyzed. The following conclusions are obtained: First, as the conjectural variation increases (or decreases) to a certain value, the system will lose its stability, which indicates that either excessive or insufficient intensity of market competition will lead to the instability of the system. However, after introducing asymmetric information, as the extrapolation accuracy increases and the conjectural variation decreases, the stability of the system is instead enhanced. At this time, intense market competition is conducive to the stability of the system. Second, compared with the classical situation without asymmetric information, the system with asymmetric information has a larger stable region and stronger ability to resist the disturbance of the initial value. And in the case of completely asymmetric information, the stable region of the system reaches the maximum.
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