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摘要翻译：
本文介绍了寡头垄断市场中的两个观点动力学模型，并将其应用于一个新进入者挑战两个规模相同的在位者的情形。这两个模型在影响消费者选择的两种力量--（本地的）社会互动和（全球的）广告--相互作用的方式上有所不同。我们用平均场方法和蒙特卡罗模拟研究了模型的一般行为，并用波兰电信市场的数据对模型进行了校正。对于其中一个模型，临界性被观察到--低于某个临界广告水平，市场接近锁定的情况，一个市场领导者主导市场，所有其他品牌消失。有趣的是，对于这两个模型，在一致性水平$P\in(0.3,0.4)$时都获得了与实际数据的最佳拟合。这与所罗门·阿施在他著名的社会实验中发现的从众水平非常一致。
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英文标题：
《Outflow Dynamics in Modeling Oligopoly Markets: The Case of the Mobile
Telecommunications Market in Poland》
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作者：
Katarzyna Sznajd-Weron, Rafa{\l} Weron and Maja W{\l}oszczowska
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最新提交年份：
2008
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分类信息：
一级分类：Quantitative Finance 数量金融学
二级分类：General Finance 一般财务
分类描述：Development of general quantitative methodologies with applications in finance
通用定量方法的发展及其在金融中的应用
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一级分类：Physics 物理学
二级分类：Physics and Society 物理学与社会
分类描述：Structure, dynamics and collective behavior of societies and groups (human or otherwise). Quantitative analysis of social networks and other complex networks. Physics and engineering of infrastructure and systems of broad societal impact (e.g., energy grids, transportation networks).
社会和团体（人类或其他）的结构、动态和集体行为。社会网络和其他复杂网络的定量分析。具有广泛社会影响的基础设施和系统（如能源网、运输网络）的物理和工程。
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一级分类：Quantitative Finance 数量金融学
二级分类：Trading and Market Microstructure 交易与市场微观结构
分类描述：Market microstructure, liquidity, exchange and auction design, automated trading, agent-based modeling and market-making
市场微观结构，流动性，交易和拍卖设计，自动化交易，基于代理的建模和做市
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英文摘要：
In this paper we introduce two models of opinion dynamics in oligopoly markets and apply them to a situation, where a new entrant challenges two incumbents of the same size. The models differ in the way the two forces influencing consumer choice -- (local) social interactions and (global) advertising -- interact. We study the general behavior of the models using the Mean Field Approach and Monte Carlo simulations and calibrate the models to data from the Polish telecommunications market. For one of the models criticality is observed -- below a certain critical level of advertising the market approaches a lock-in situation, where one market leader dominates the market and all other brands disappear. Interestingly, for both models the best fits to real data are obtained for conformity level $p \in (0.3,0.4)$. This agrees very well with the conformity level found by Solomon Asch in his famous social experiment.
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PDF链接：
https://arxiv.org/pdf/0809.1534
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