CAREER: Design of Two-sided Markets In Dynamic and Uncertain Environments: Theoretical and Operational Issues

这项教师早期职业发展(Career)项目奖的研究目标是研究动态和不确定环境下双边市场的设计。由于随机到达市场两侧，系统中的代理数量会随着时间的推移而演变。工程师在进入系统时报告他们的首选项，并根据首选项的兼容性和未来选项的值接受或拒绝匹配提议。该奖项的主要目标是通过考虑代理人的动态交互、不确定性和前瞻性行为，以高效的方式设计这样的市场。研究方法是在给定的策略下，计算每个代理人从保持不匹配中获得的预期收益，作为市场设计者的效用承诺，这将使(动态)个人理性匹配报价的算法成为可能。该算法将被推广到代理可能在比赛前不知道他们对匹配的真实偏好，并且双方都生成多个匹配的环境。进一步的分析将赋予代理人诚实行为的直接激励，并考虑这样一种可能性，即市场设计师通过观察他们对匹配报价的反应来了解代理人的偏好，而代理人通过观察他们获得的报价来了解可用合作伙伴的分布。如果成功，这项研究的结果将导致市场布局的改善，在这些市场中，需要匹配双边代理人群体的市场，如劳动力市场、器官移植、儿童收养和寄养。该奖项可以提供建模和分析工具，以最大限度地提高匹配系统的效率和参与者的福利。这项研究是通过结合经济学中匹配/市场设计中开发的工具和操作中常用的工具来实现的。开发的数学还将帮助培训研究生和本科生，并为卡内基梅隆大学和宾夕法尼亚州领养交易所(PAE)之间正在进行的私人-公共合作伙伴关系做出贡献。

The research objective of this Faculty Early Career Development (CAREER) Program award is to study the design of two-sided markets in dynamic and uncertain settings. The population of agents in the system evolves over time due to stochastic arrivals to both sides of the market. Agents report their preferences upon entering the system, and either accept or reject match offers based on the compatibility of preferences as well as value of future options. The primary goal of this award is to design such marketplaces in an efficient way by taking into account dynamic interaction, uncertainty and forward looking behavior of agents. The research approach is to compute each agent's expected benefit from remaining unmatched as a utility promise from the market designer under a given policy, which will enable an algorithm for (dynamically) individually-rational match offers. The algorithm will be generalized to the environment where agents may not know their true preferences over matches before the match and there are multiple matches generated on both sides. Further analysis will endow agents with straightforward incentives for truthful behavior and consider the possibility that a market designer learns about agent preferences by observing their responses to match offers while the agents learn about the distribution of available partners by observing the offers they get.If successful, the results of this research will lead to improvements in the layout of markets where there is a need to match two-sided populations of agents such as labor markets, organ transplant, child adoption, and foster care. The award can provide modeling and analysis tools to maximize the efficiency of the matching system and the welfare of its participants. The research is made possible by combining tools developed both in matching/market design in economics and those commonly used in operations. The mathematics developed will also help train graduate and undergraduate students as well as contribute to an ongoing private public partnership between Carnegie Mellon and Pennsylvania Adoption Exchange (PAE).