Composite Indicators (CIs, a.k.a. indices) are increasingly used as they can simplify interpretation of results by condensing the information of a plurality of underlying indicators in a single measure. This paper demonstrates that the strength of the correlations between the indicators is directly linked with their capacity to transfer information to the CI. A measure of information transfer from each indicator is proposed along with two weight-optimization methods, which allow the weights to be adjusted to achieve either a targeted or maximized information transfer. The tools presented in this paper are applied to a case study for resilience assessment of energy systems, demonstrating how they can support the tailored development of CIs. These findings enable analysts bridging the statistical properties of the index with the weighting preferences from the stakeholders. They can thus choose a weighting scheme and possibly modify the index while achieving a more consistent (by correlation) index.

复合指标（CI，又名指数）越来越多地被使用，因为它们可以通过将多个基础指标的信息浓缩在一个单一的度量中来简化对结果的解释。本文表明，指标之间相关性的强度与其将信息传输到 CI 的能力直接相关。提出了每个指标的信息传输度量以及两种权重优化方法，这些方法允许调整权重以实现有针对性或最大化的信息传输。本文中介绍的工具应用于能源系统弹性评估的案例研究，展示了它们如何支持 CI 的定制开发。这些发现使分析师能够将指数的统计特性与利益相关者的加权偏好联系起来。因此，他们可以选择加权方案并可能修改指数，同时获得更一致的（通过相关性）指数。