论文标题
在不确定性下对正确分配的预期概率进行建模
Modelling the expected probability of correct assignment under uncertainty
论文作者
论文摘要
在做出重要的决定（例如选择健康保险或学校）时，人们通常不确定哪些属性适合其真正的偏好。毕竟，他们可能会意识到自己的不确定性导致了不匹配：选择一个优化的替代方案，而另一种可用的替代方案可以更好地满足他们的需求。 从中央计划者的角度来看，我们在这里研究了这种不确定性下的决策。我们使用Voronoi Tessellations的表示来在属性空间中找到所有个人和替代方案。我们提供了正确匹配概率的表达式，并在分析和数值上计算匹配的平均百分比。我们测试依赖不确定性和位置的水平。 我们发现，即使对于低不确定性，总体上不匹配 - 对决策者的可能问题。我们进一步探索了一种常用的实践 - 分配服务代表以协助个人的决定。我们表明，在给定的预算和不确定性级别内，有效分配是针对接近几个Voronoi细胞之间边界但在边界上不正确边界的个体。
When making important decisions such as choosing health insurance or a school, people are often uncertain what levels of attributes will suit their true preference. After choice, they might realize that their uncertainty resulted in a mismatch: choosing a sub-optimal alternative, while another available alternative better matches their needs. We study here the overall impact, from a central planner's perspective, of decisions under such uncertainty. We use the representation of Voronoi tessellations to locate all individuals and alternatives in an attribute space. We provide an expression for the probability of correct match, and calculate, analytically and numerically, the average percentage of matches. We test dependence on the level of uncertainty and location. We find overall considerable mismatch even for low uncertainty - a possible concern for policy makers. We further explore a commonly used practice - allocating service representatives to assist individuals' decisions. We show that within a given budget and uncertainty level, the effective allocation is for individuals who are close to the boundary between several Voronoi cells, but are not right on the boundary.
