Although performance information is widely promoted to improve the accountability of public service provision, behavioral research has revealed that motivated reasoning leads recipients to update their beliefs inaccurately. However, the reasoning processes of service users has been largely neglected. We develop a theory of public service users’ motivated reasoning about performance information stemming from their identification with the organization providing their services. We address a significant challenge to studying motivated reasoning—that widely used existing research designs cannot rule out alternative cognitive explanations, especially Bayesian learning, such that existing findings could be driven by strong prior beliefs rather than biased processing of new information. We use a research design incorporating Bayesian learning as a benchmark to identify departures from accuracy motivated reasoning process. We assess the empirical implications of the theory using a preregistered information provision experiment among parents with children using public schools. To assess their identity based motivated reasoning we provide them with noisy, but true, performance information about their school. Overall, we find no evidence of directionally motivated reasoning. Instead, parents change their beliefs in response to performance feedback in a way that largely reflects conservative Bayesian learning. Performance reporting to service users is less vulnerable to motivational biases in this context than suggested by the general literature on motivated reasoning. Furthermore, exploratory findings show that performance information can correct erroneous beliefs among misinformed service users, suggesting that investment in reporting performance to service users is worthwhile to inform their beliefs and improve accountability.

中文翻译：

---

公共服务用户对绩效信息的反应：贝叶斯学习还是动机推理？


尽管绩效信息被广泛推广以提高公共服务提供的问责制，但行为研究表明，动机推理会导致接收者不准确地更新他们的信念。然而，服务使用者的推理过程却在很大程度上被忽视了。我们开发了一种公共服务用户对绩效信息的动机推理理论，这种推理源于他们对提供服务的组织的认同。我们解决了研究动机推理的重大挑战——广泛使用的现有研究设计不能排除替代的认知解释，尤其是贝叶斯学习，这样现有的发现可能是由强烈的先验信念驱动的，而不是由新信息的偏见处理驱动的。我们使用包含贝叶斯学习的研究设计作为基准来识别与准确性驱动的推理过程的偏差。我们通过在公立学校就读孩子的家长中进行预先注册的信息提供实验来评估该理论的实证意义。为了评估他们基于身份的动机推理，我们向他们提供有关学校的嘈杂但真实的表现信息。总的来说，我们没有发现有方向性动机推理的证据。相反，父母会根据表现反馈改变他们的信念，这在很大程度上反映了保守的贝叶斯学习。与有关动机推理的一般文献所建议的相比，在这种情况下向服务用户提供的绩效报告更不容易受到动机偏见的影响。 此外，探索性发现表明，绩效信息可以纠正被误导的服务用户的错误信念，这表明向服务用户报告绩效的投资对于告知他们的信念并提高问责制是值得的。