Equity Pay In Networked Teams

TL;DR

This paper analyzes how to optimally allocate equity shares among agents in networked teams to motivate effort, considering the network structure and complementarities, with implications for team selection and equity levels.

Contribution

It characterizes the optimal equity allocation using a neighborhood balance condition and identifies the structure of teams that should receive positive equity in networked settings.

Findings

Optimal equity allocation balances neighbors' total equity shares.

Teams with positive equity form tight-knit, highly interconnected subsets.

Equity levels increase with the strength of team complementarities.

Abstract

A group of agents each exert effort to produce a joint output, with the complementarities between their efforts represented by a (weighted) network. Under equity compensation, a principal motivates the agents to work by giving them shares of the output. We describe the optimal equity allocation. It is characterized by a neighborhood balance condition: any two agents receiving equity have the same (weighted) total equity assigned to their neighbors. We also study the problem of selecting the team of agents who receive positive equity, and show this team must form a tight-knit subset of the complementarity network, with any pair being complementary to one another or jointly to another team member. Finally, we give conditions under which the amount of equity used for compensation is increasing in the strength of a team's complementarities and discuss several other applications.