In this paper, we introduce discrete choice experiments (DCEs) and provide foundational knowledge on the topic. DCEs are one of the most popular methods within econometrics to study the distribution of choices within a population. DCEs are particularly useful when studying the effects of categorical variables on choice. Procedurally, a DCE involves recruiting a large sample of individuals exposed to a set of choice arrays. The factors that are suspected to affect choice are varied systematically across the choice arrays. Most commonly, DCE data are analyzed with a multinomial logit statistical model with a goal of determining the relative utility of each relevant factor. We also discuss DCEs in comparison with behavioral choice models, such as those based on the matching law, and we show an example of a DCE to illustrate how a DCE can be used to understand choice with behavioral, social, and organizational factors.

在本文中，我们介绍了离散选择实验(DCE) 并提供有关该主题的基础知识。DCE 是计量经济学中研究人群中选择分布的最流行方法之一。在研究分类变量对选择的影响时，DCE 特别有用。在程序上，DCE 涉及招募大量暴露于一组选择数组的个人样本。被怀疑影响选择的因素在选择数组中系统地变化。最常见的是，DCE 数据使用多项式 Logit 统计模型进行分析，目的是确定每个相关因素的相对效用。我们还讨论了 DCE 与行为选择模型（例如基于匹配律的模型）的比较，并且我们展示了一个 DCE 示例来说明如何使用 DCE 来理解具有行为、社会、