We propose a novel framework using individual choice data and Bayesian updating to predict which consumers are most responsive to information—namely those consumers whose pre-information choices reveal a high level of uncertainty surrounding their preferences. We apply our method to the study of consumer acceptance of genetically modified animal products, which prior research has revealed is a particularly polarising subject. Utilising conditional willingness-to-pay estimates from mixed logit models, we find that individuals with higher preference uncertainty prior to receiving information are most responsive. Implications of our results are discussed in the context of recent breakthroughs in biotechnology.

中文翻译：

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预测对信息的响应：动物产品中消费者对生物技术的接受程度

我们提出了一个新颖的框架，该框架使用个人选择数据和贝叶斯更新来预测哪些消费者对信息的响应速度最快，即那些信息前选择对他们的偏好存在高度不确定性的消费者。我们将我们的方法应用于转基因动物产品的消费者接受度研究，先前的研究表明这是一个两极分化的话题。利用混合logit模型中的有条件支付意愿估计，我们发现在接收信息之前具有较高偏好不确定性的个人反应最快。在生物技术的最新突破中讨论了我们的研究结果的含义。