英文标题：
《A network approach to cartel detection in public auction markets》
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作者：
Johannes Wachs, J\\\'anos Kert\\\'esz
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最新提交年份：
2019
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英文摘要：
  Competing firms can increase profits by setting prices collectively, imposing significant costs on consumers. Such groups of firms are known as cartels and because this behavior is illegal, their operations are secretive and difficult to detect. Cartels feel a significant internal obstacle: members feel short-run incentives to cheat. Here we present a network-based framework to detect potential cartels in bidding markets based on the idea that the chance a group of firms can overcome this obstacle and sustain cooperation depends on the patterns of its interactions. We create a network of firms based on their co-bidding behavior, detect interacting groups, and measure their cohesion and exclusivity, two group-level features of their collective behavior. Applied to a market for school milk, our method detects a known cartel and calculates that it has high cohesion and exclusivity. In a comprehensive set of nearly 150,000 public contracts awarded by the Republic of Georgia from 2011 to 2016, detected groups with high cohesion and exclusivity are significantly more likely to display traditional markers of cartel behavior. We replicate this relationship between group topology and the emergence of cooperation in a simulation model. Our method presents a scalable, unsupervised method to find groups of firms in bidding markets ideally positioned to form lasting cartels.
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中文摘要：
相互竞争的公司可以通过集体定价来增加利润，从而给消费者带来巨大的成本。这类公司集团被称为卡特尔，因为这种行为是非法的，所以它们的运作是秘密的，很难被发现。卡特尔感到了一个重大的内部障碍：成员国感到短期内存在欺骗动机。在这里，我们提出了一个基于网络的框架，以检测投标市场中的潜在卡特尔，其理念是，一组公司能够克服这一障碍并保持合作的机会取决于其互动模式。我们根据企业的共同竞价行为创建了一个企业网络，检测相互作用的群体，并衡量他们的凝聚力和排他性，这是他们集体行为的两个群体层面特征。将该方法应用于一个学校牛奶市场，我们检测到一个已知的卡特尔，并计算出它具有很高的内聚性和排他性。在格鲁吉亚共和国2011年至2016年授予的近150000份公共合同中，发现的具有高度凝聚力和排他性的群体更有可能表现出卡特尔行为的传统标志。我们在一个仿真模型中复制了组拓扑和合作出现之间的这种关系。我们的方法提出了一种可扩展的、无监督的方法，用于在投标市场中找到处于理想位置的公司群体，以形成持久的卡特尔。
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分类信息：

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：Computer Science        计算机科学
二级分类：Social and Information Networks        社会和信息网络
分类描述：Covers the design, analysis, and modeling of social and information networks, including their applications for on-line information access, communication, and interaction, and their roles as datasets in the exploration of questions in these and other domains, including connections to the social and biological sciences. Analysis and modeling of such networks includes topics in ACM Subject classes F.2, G.2, G.3, H.2, and I.2; applications in computing include topics in H.3, H.4, and H.5; and applications at the interface of computing and other disciplines include topics in J.1--J.7. Papers on computer communication systems and network protocols (e.g. TCP/IP) are generally a closer fit to the Networking and Internet Architecture (cs.NI) category.
涵盖社会和信息网络的设计、分析和建模，包括它们在联机信息访问、通信和交互方面的应用，以及它们作为数据集在这些领域和其他领域的问题探索中的作用，包括与社会和生物科学的联系。这类网络的分析和建模包括ACM学科类F.2、G.2、G.3、H.2和I.2的主题；计算应用包括H.3、H.4和H.5中的主题；计算和其他学科接口的应用程序包括J.1-J.7中的主题。关于计算机通信系统和网络协议（例如TCP/IP）的论文通常更适合网络和因特网体系结构（CS.NI）类别。
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一级分类：Economics        经济学
二级分类：General Economics        一般经济学
分类描述：General methodological, applied, and empirical contributions to economics.
对经济学的一般方法、应用和经验贡献。
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一级分类：Quantitative Finance        数量金融学
二级分类：Economics        经济学
分类描述：q-fin.EC is an alias for econ.GN. Economics, including micro and macro economics, international economics, theory of the firm, labor economics, and other economic topics outside finance
q-fin.ec是econ.gn的别名。经济学，包括微观和宏观经济学、国际经济学、企业理论、劳动经济学和其他金融以外的经济专题
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