Institute for Biocomputation and Physics of Complex Systems, Universidad de Zaragoza, Zaragoza, Spain.
Unidad Mixta Interdisciplinar de Comportamiento y Complejidad Social (UMICCS), UC3M-UV-UZ, Madrid, Spain.
Sci Rep. 2020 Jul 6;10(1):11113. doi: 10.1038/s41598-020-68094-z.
Global supply networks in agriculture, manufacturing, and services are a defining feature of the modern world. The efficiency and the distribution of surpluses across different parts of these networks depend on the choices of intermediaries. This paper conducts price formation experiments with human subjects located in large complex networks to develop a better understanding of the principles governing behavior. Our first experimental finding is that prices are larger and that trade is significantly less efficient in small-world networks as compared to random networks. Our second experimental finding is that location within a network is not an important determinant of pricing. An examination of the price dynamics suggests that traders on cheapest-and hence active-paths raise prices while those off these paths lower them. We construct an agent-based model (ABM) that embodies this rule of thumb. Simulations of this ABM yield macroscopic patterns consistent with the experimental findings. Finally, we extrapolate the ABM on to significantly larger random and small-world networks and find that network topology remains a key determinant of pricing and efficiency.
全球农业、制造业和服务业的供应链网络是现代世界的一个重要特征。这些网络中不同部分的剩余分配效率取决于中介机构的选择。本文通过位于大型复杂网络中的人类主体进行价格形成实验，以更好地理解支配行为的原则。我们的第一个实验发现是，与随机网络相比，在小世界网络中，价格更高，交易效率显著降低。我们的第二个实验发现是，网络中的位置不是定价的重要决定因素。对价格动态的考察表明，处于最便宜路径（即活跃路径）上的交易者会提高价格，而不在这些路径上的交易者则会降低价格。我们构建了一个包含这一经验法则的基于代理的模型（ABM）。该 ABM 的模拟产生了与实验结果一致的宏观模式。最后，我们将 ABM 外推到更大的随机和小世界网络上，并发现网络拓扑仍然是定价和效率的关键决定因素。
