Forced Labor in Labor Supply Chains: Contracting and Information Asymmetry

Problem definition : We examine how market and economic factors influence the occurrence of forced labor in supply chains and how buying companies can develop optimal contracts to prevent forced labor in the presence of information asymmetry between the buyer and the agent. Methodology/results : We develop a game-theoretic model of a labor supply chain comprising a socially aware buyer and a profit-maximizing labor agent. Our equilibrium analysis shows that the audit cost affects the extent to which the buyer can extract surplus from the agent. In the asymmetric information case, we design a menu of contracts and show that the difference in the agent’s earnings dictates how an unconstrained optimal contract can be adjusted to be incentive compatible. Our result suggests that it is optimal for the buyer to leave a surplus to agents with high recruitment capability (measured in terms of the labor pool size) regardless of the audit cost. As we extend our analysis to the multiagent case, we develop a “sequential” menu of contracts that ensures no coercion and maximum buyer profit. We apply our model to a data set of labor agents for recruiting foreign agricultural workers in the United States. Managerial implications : To implement incentive-compatible contracts that deter coercive labor outcomes, the buyer may need to allocate informational rents to the agent by foregoing a portion of its surplus. We find that information asymmetry regarding the agent’s true recruitment capability necessitates that the buyer offers a “menu of contracts” to prevent the risk of forced labor. This menu benefits exactly one type of agent, depending on the earnings differential between the available contracts, but always leaves a financial surplus for agents with strong recruitment capabilities. When multiple potential agents are available, the buyer can employ a reverse auction mechanism to select one agent. Though the core insights from contracting with a single agent continue to apply, their impact diminishes as the number of potential agents grows.