论文标题
表演能力
Performative Power
论文作者
论文摘要
我们介绍了表演能力的概念，该概念衡量了运营算法系统（例如数字内容推荐平台）的公司的能力，以导致参与者人群的变化。我们将表演能力与数字经济竞争的经济研究联系起来。传统的经济概念与确定数字平台中的反竞争模式的困难尤其是由于市场定义的复杂性。相比之下，表演能力是一种因果观念，可以识别出对市场，其内部，参与者，产品或价格的最低知识。 低表现力意味着公司做得比在当前数据上优化其目标更好。相比之下，高性能权力的公司将受益于将人口转向更有利可图的行为。我们在一个简单的理论模型中确认，该模型垄断最大化表现力。企业个性化的能力会增加表现力量，而竞争和外部选择会降低表现力量。在经验方面，我们提出了一种观察性因果设计，以在数字平台如何显示内容中从不连续性中识别出表现力。这允许从有关数字平台的各种研究中重新利用因果关系，以此作为表现力的下限。最后，我们推测表演能力在数字市场中可能在竞争政策和反托拉斯执法中发挥的作用。
We introduce the notion of performative power, which measures the ability of a firm operating an algorithmic system, such as a digital content recommendation platform, to cause change in a population of participants. We relate performative power to the economic study of competition in digital economies. Traditional economic concepts struggle with identifying anti-competitive patterns in digital platforms not least due to the complexity of market definition. In contrast, performative power is a causal notion that is identifiable with minimal knowledge of the market, its internals, participants, products, or prices. Low performative power implies that a firm can do no better than to optimize their objective on current data. In contrast, firms of high performative power stand to benefit from steering the population towards more profitable behavior. We confirm in a simple theoretical model that monopolies maximize performative power. A firm's ability to personalize increases performative power, while competition and outside options decrease performative power. On the empirical side, we propose an observational causal design to identify performative power from discontinuities in how digital platforms display content. This allows to repurpose causal effects from various studies about digital platforms as lower bounds on performative power. Finally, we speculate about the role that performative power might play in competition policy and antitrust enforcement in digital marketplaces.
