Contracting with a Mechanism Designer

2025-07-16

AI Summary

This paper studies incentive design under information asymmetry among requesters, platforms, and workers in crowdsourcing markets. Addressing the setting where requesters cannot directly interact with workers, we formulate a scalable three-stage Stackelberg game and propose a novel auction-theoretic framework—“virtual-value pricing”—proving that linear revenue-sharing contracts constitute the optimal mechanism. We innovatively introduce two metrics—Price of Dual Marginalization (PoDM) and Price of Anarchy (PoA)—to quantify efficiency losses due to information asymmetry, deriving tight or nearly tight bounds under anonymous pricing and robust market assumptions. Our results demonstrate that, despite constraints imposed by platform intermediation and distributional uncertainty, linear contracts efficiently transmit incentives and sustain near-optimal system efficiency.

Technology Category

• Game Theory and Economic Paradigms: Mechanism Design
• Multiagent Systems: Mechanism Design
• Humans and AI: Crowd Sourcing and Human Computation

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Security and Privacy: Large-scale security measurements

Abstract

This paper explores the economic interactions within modern crowdsourcing markets. In these markets, employers issue requests for tasks, platforms facilitate the recruitment of crowd workers, and workers complete tasks for monetary rewards. Recognizing that these roles serve distinct functions within the ecosystem, we introduce a three-party model that distinguishes among the principal (the requester), the intermediary (the platform), and the pool of agents (the workers). The principal, unable to directly engage with agents, relies on the intermediary to recruit and incentivize them. This interaction unfolds in two stages: first, the principal designs a profit-sharing contract with the intermediary; second, the intermediary implements a mechanism to select an agent to complete the delegated task. We analyze the proposed model as an extensive-form Stackelberg game. Our contributions are fourfold: (1) We fully characterize the subgame perfect equilibrium. In particular, we reduce the principal's contract design problem to a novel auction-theoretic formulation we term virtual value pricing, and reveals that linear contracts are optimal even when the task have multiple outcomes and agents' cost distributions are asymmetric. (2) To quantify the principal's utility loss from delegation and information asymmetry, we introduce the price of double marginalization (PoDM) and the classical price of anarchy (PoA), and derive tight or nearly tight bounds on both ratios under regular and monotone hazard rate (MHR) distributions. (3) We further examine these two ratios in a natural setting where the intermediary is restricted to anonymous pricing mechanisms, and show that similar qualitative insights continue to hold. (4) Finally, we extend our results on both ratios to a robust framework that accommodates scenarios in which the principal lacks precise information about the market size.

Problem

• Modeling three-party interactions in crowdsourcing markets
• Analyzing optimal contracts and delegation losses
• Quantifying utility loss from information asymmetry

Innovation

• Three-party model: principal, intermediary, agents
• Virtual value pricing for contract design
• Price of double marginalization and anarchy