Racah Institute of Physics, The Hebrew University, 91904, Jerusalem, Israel.
QuTech and Kavli Institute of Nanoscience, Delft University of Technology, 2600 GA, Delft, The Netherlands.
Sci Rep. 2020 Sep 15;10(1):15080. doi: 10.1038/s41598-020-71558-x.
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 that the overall mismatch is considerable 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.
当人们在做出重要决策，如选择健康保险或学校时，往往不确定哪些属性水平符合他们的真实偏好。在做出选择后，他们可能会意识到自己的不确定性导致了不匹配：选择了次优的选择，而另一个可用的选择更符合他们的需求。我们从中央规划者的角度研究了这种不确定性下决策的总体影响。我们使用 Voronoi 镶嵌图的表示来将所有个体和替代方案定位在属性空间中。我们提供了正确匹配的概率表达式，并通过分析和数值计算来计算匹配的平均百分比。我们测试了对不确定性水平和位置的依赖性。我们发现，即使不确定性水平较低，总体不匹配也相当大，这可能是政策制定者关注的问题。我们进一步探讨了一种常用的实践，即将服务代表分配给个人来协助他们做出决策。我们表明，在给定的预算和不确定性水平下，有效的分配是针对那些接近几个 Voronoi 单元边界的个体，但不在边界上的个体。
