RI: Small: Theory and Application of Mechanism Design for Team Formation

Vanderbilt University, Nashville TN

Investigators

Abstract

In a world where complexity of tasks abounds, teamwork is the norm rather than the exception. Formation of effective teams is therefore vital in nearly any organization, and across a broad array of domains, such as large-scale software projects, course projects, military operations, construction projects, and search-and-rescue tasks. Successful team formation, however, hinges on having knowledge about how individuals working on a team complement each other in service of a task, their ability to work together, as well as potentially misaligned preferences about goals that the different tasks may achieve. The goal of this project is to develop a general-purpose team formation exchange service, leveraging new theoretical foundations for designing team formation mechanisms when the abilities and preferences of prospective teammates are uncertain. Such an exchange would significantly improve the ability of organizations to dynamically form agile and efficient project teams, reducing conflict and better aligning individual and organizational incentives. This project considers an exceptionally challenging conceptual and technical problem of mechanism design in the context of team formation in service of a set of goals. The core conceptual challenge lies in modeling the problem in sufficient detail to capture considerations such as achievement of sub-goals by tasks, agent capabilities, task requirements, and agent preferences about goals and teammates, but avoiding unnecessary detail to maintain tractability. The proposed research offers a novel modeling framework aimed at balancing these two considerations. The technical contributions involve both novel theoretical treatment of the problem, such as characterizations of novel extensions of mechanisms from related domains, including combinatorial assignment, entirely new mechanisms tailored to the problem at hand, and algorithmic contributions to optimal scalable automated mechanism design leveraging specific problem structure. Additionally, the proposed research will blend experimental economics research with contributions in theoretical and computational economics by using human subject experiments as one of the means to evaluate the developed mechanisms.