Pick-an-Object Mechanisms
提出一种新的单边匹配市场机制“选物机制”，通过个性化菜单让参与者依次选择物品，并证明其能实现常用分配规则且比直接机制更易引发真实行为，实验验证了其优势。
We introduce a new family of mechanisms for one-sided matching markets, denoted pick-an-object (PAO) mechanisms. When implementing an allocation rule via PAO, agents are asked to pick an object from individualized menus. These choices may be rejected later on, and these agents are presented with new menus. When the procedure ends, agents are assigned the last object they picked. We characterize the allocation rules that can be sequentialized by PAO mechanisms and the ones that can be implemented in a robust truthful equilibrium. We justify the use of PAO as opposed to direct mechanisms by showing that its equilibrium behavior is closely related to the one in obviously strategy-proof (OSP) mechanisms, but implements commonly used rules, such as Gale-Shapley DA and top trading cycles, which are not OSP implementable. We run laboratory experiments comparing truthful behavior when using PAO, OSP, and direct mechanisms to implement different rules. These indicate that agents are more likely to behave in line with the theoretical prediction under PAO and OSP implementations than their direct counterparts. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Funding: This research is funded by the National Natural Science Foundation of China [Grant 72033006]. R. Hakimov was supported by the Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung [Project 100018_189152]. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.4908 .