发表机构
ZEW – Leibniz Centre for European Economic Research; Karlsruhe Institute of Technology (KIT); Düsseldorf Institute for Competition Economics (DICE); Heinrich Heine University Düsseldorf; Department of Economics, Maynooth University（ZEW 欧洲经济研究中心; 卡尔斯鲁厄理工学院; 杜塞尔多夫竞争经济学研究所; 杜塞尔多夫海因里希·海涅大学; 梅努斯大学经济学系）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究通过受控实验考察基于规则的定价算法设计特征（如价格战警告、预配置策略和语言模型建议）对市场结果的影响，发现多数设计变体通过提高起始价格和促进合作性算法设计而推高市场价格，对竞争政策与平台监管具有启示意义。
AI 中文摘要
基于规则的定价工具在数字商务中广泛使用，然而我们对其设计如何影响市场结果知之甚少。在一项受控市场实验中，参与者使用仪表盘构建定价算法，在多个时期内进行序贯伯特兰博弈竞争。我们改变了商业重定价工具中常见的设计特征：关于价格战的警告、预配置策略以及来自大型语言模型的建议。大多数处理变体提高了市场价格，其效应由起始价格的上升和更具合作性的算法设计所驱动。这些结果对竞争政策、平台监管以及当前关于监管算法设计工具的讨论具有重要意义。
英文摘要
Rule-based pricing tools are widespread in digital commerce, yet we know little about how their design shapes market outcomes. In a controlled market experiment, participants use dashboards to build pricing algorithms competing in a sequential Bertrand game over multiple periods. We vary design features commonly found in commercial repricing tools: warnings about price wars, pre-configured strategies, and advice from a large language model. Most treatment variations raise market prices with effects driven by an increase in starting prices and more cooperative algorithm designs. The results matter for competition policy, platform regulation and current discussions on regulating algorithm design tools.
