Purpose

The Higg Materials Sustainability Index (MSI) consists of five life cycle indicators to help the apparel industry inform material selection at the design stage. Until 2020, the Higg MSI applied a single score and after much debate, in 2021, indicators will no longer be aggregated. The problem of tradeoffs remains, and so this study evaluates potential aggregation approaches to help decision makers deal with tradeoffs that solve previous issues and allow for an integrated view.

Methods

Aggregation can be compensatory such as in the case of the weighted sum in the previous Higg MSI, or partially compensatory, and this relates as to how tradeoffs are managed. This study compares aggregation in the Higg MSI to four other aggregation methods via a comparative application using six textile materials (cotton, wool, PET, nylon 6, lyocell, and viscose) that, while not functionally equivalent on a mass basis, serve as an illustration of the effects of aggregation. This paper compares three compensatory aggregation methods to results from the Higg MSI—internal normalization of division by maximum, global normalization, monetization—and one partially compensatory method—stochastic multi-attribute analysis (SMAA). Methods were chosen to ensure a broad coverage according to their applicability to the Higg MSI.

Results and discussion

The comparison of raw materials using the impact categories used in the MSI Higg show tradeoffs, particularly for two materials which are the best performing materials in two impact categories and worse performing materials in the other two impact categories (out of four categories). For materials presenting tradeoffs, results show a distinct pattern between compensatory methods and SMAA. Compensatory single score methods place these materials in the lowest ranks, even lower than a material which is not the best performing material in any category. In SMAA, these same two materials rank above the mediocre material. There is a difference in how compensatory methods and partially compensatory methods handle the tradeoffs, between impacts and the resulting ranking of the materials.

Conclusions

Analysis shows that the current approach to aggregation in the Higg MSI is based on a weighted sum and, as with the other fully compensatory approaches, has three fundamental problems: linear compensation between poor and good performances, lack of accounting of mutual differences, and inverse proportionality. These problems can lead to material decisions that may enable burden shifting and unintended environmental consequences as a result of using the Higg MSI.

Recommendations

The Higg MSI needs to support companies in understanding the environmental sustainability of their products to be able to identify improvement options in a way that can adapt to the industry’s environmental concerns and business strategy. Therefore, it is recommended that the Higg MSI apply aggregation that is methodologically defensible regardless of the material in question to incentivize a healthy competition for environmental stewardship among industry members.

中文翻译：

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评估未来 Higg MSI 情景的替代环境决策支持矩阵

目的

Higg 材料可持续性指数 (MSI) 由五个生命周期指标组成，可帮助服装行业在设计阶段为材料选择提供信息。直到 2020 年，Higg MSI 应用单一分数，经过多次辩论，到 2021 年，指标将不再汇总。权衡问题仍然存在，因此本研究评估了潜在的聚合方法，以帮助决策者权衡解决以前的问题并允许综合视图。

方法

聚合可以是补偿性的，例如在先前 Higg MSI 中的加权总和的情况下，或部分补偿性的，这与如何管理权衡有关。这项研究通过使用六种纺织材料（棉，羊毛，PET，尼龙6，莱赛尔纤维和粘胶纤维）的对比应用，将希格MSI中的聚合与其他四种聚合方法进行了比较，这些纺织材料虽然在功能上不等同于质量，但可以用作纺织材料。聚集效应的图示。本文将三种补偿聚合方法与 Higg MSI 的结果进行比较——最大除法的内部归一化、全局归一化、货币化——以及一种部分补偿聚合方法方法——随机多属性分析 (SMAA)。根据它们对 Higg MSI 的适用性，选择方法以确保广泛的覆盖范围。

结果和讨论

使用 MSI Higg 中使用的影响类别的原材料比较显示了权衡，特别是对于在两个影响类别中表现最佳的两种材料和在其他两个影响类别（四个类别中）表现较差的材料。对于呈现权衡的材料，结果显示补偿方法和 SMAA 之间存在明显的模式。补偿性单分法将这些材料置于最低等级，甚至低于在任何类别中都不是表现最佳材料的材料。在 SMAA 中，这两种相同的材料排名在平庸的材料之上。补偿方法和部分补偿方法如何处理影响和材料的最终排名之间的权衡是不同的。

结论

分析表明，目前 Higg MSI 中的聚合方法基于加权和，并且与其他完全补偿方法一样，存在三个基本问题：表现不佳和良好表现之间的线性补偿、缺乏对相互差异的考虑以及逆相称性。这些问题可能导致重大决策，这些决策可能会因使用 Higg MSI 而导致负担转移和意外环境后果。

推荐建议

Higg MSI 需要支持公司了解其产品的环境可持续性，以便能够以适应行业环境问题和业务战略的方式确定改进选项。因此，建议 Higg MSI 应用在方法上合理的聚合，而不管所涉及的材料如何，以激励行业成员之间对环境管理的健康竞争。