Proposition of a scoring method for the S-LCA assessment phase

The current method used to score the performances at the assessment phase in social life cycle assessment (S-LCA) presents some implicit assumptions that can generate or improve the errors at the final aggregated results.... [ view full abstract ]

The current method used to score the performances at the assessment phase in social life cycle assessment (S-LCA) presents some implicit assumptions that can generate or improve the errors at the final aggregated results. There is no problem related to the qualitative analysis point of view. However, this is not true for the quantitative assessment. The Performance Reference Point (PRP) technique is used to establish the Classification Levels (CLs) of the subcategories indicators and the linear value function is normally used to score the CLs. Nevertheless, we cannot guarantee that they follow a linear behavior considering the complexity of the subcategories indicators. This means that the basic requirement of one indicator is not necessarily valued in the same way than another because each subcategory presents some singularities that must be considered at the scoring phase. Actually, this aspect is not contemplated in S-LCA studies. This gap makes the use of social assessment to support decision-making a challenge.
This paper aims to propose a method to establish a customized function value to quantify the CLs’ of the subcategories indicators based on the value judgment of a focal group formed by experts in S-LCA.
Two phases compose our research. Three steps characterize the first phase: (i) the definition of the focal group; (ii) the data collection and analysis and (iii) the definition of the value function shape for each subcategory indicator. At the second phase, we apply our method to present how it can be used in S-LCA studies.
It was possible to observe that when we modify the shape of the value function, the final performance changes. This result proves that the shape of the value function can influence the decision-making process. This research fulfilled the current gap at the assessment phase of S-LCA by proposing a method to score the classification levels of the subcategories indicators. It allows a more precise performance considering the complexity of the indicators used to measure the social impacts. The customization of the value function can provide a precision improvement of the performances results. This model can be used for all types of product systems. By the framework application on a hypothetical case, we can conclude that it is possible to obtain a more precise quantified performance.