We study a sender-receiver model where the receiver can commit to a decision rule before the sender determines the information policy. The decision rule can depend on the signal structure and the signal realization that the sender adopts. This framework captures applications where a decision-maker (the receiver) solicit advice from an interested party (sender). In these applications, the receiver faces uncertainty regarding the sender's preferences and the set of feasible signal structures. Consequently, we adopt a unified robust analysis framework that includes max-min utility, min-max regret, and min-max approximation ratio as special cases. We show that it is optimal for the receiver to sacrifice ex-post optimality to perfectly align the sender's incentive. The optimal decision rule is a quota rule, i.e., the decision rule maximizes the receiver's ex-ante payoff subject to the constraint that the marginal distribution over actions adheres to a consistent quota, regardless of the sender's chosen signal structure.

翻译：我们研究一个发送者-接收者模型，其中接收者可以在发送者确定信息政策之前承诺一个决策规则。该决策规则可以依赖于发送者采用的信号结构和信号实现。这一框架捕捉了决策者（接收者）向利益相关方（发送者）征求建议的应用场景。在这些应用中，接收者面临关于发送者偏好及可行信号结构集合的不确定性。因此，我们采用一个统一的鲁棒分析框架，将最大最小效用、最小最大遗憾和最小最大逼近比作为特例包含在内。我们证明，对接收者而言，牺牲事后最优性以完美对齐发送者激励是最优的。最优决策规则是一种配额规则，即该规则在约束条件下最大化接收者的事前收益，该约束要求无论发送者选择的信号结构如何，行动上的边际分布必须遵循一致的配额。