Materials and Actor Network Theory, a way to flesh out Life Cycle Assessment?☆

LCA (Life Cycle Assessment) is an established method to measure the economic, social and environmental impact of a good or a service, with particular attention to its value chain or its life cycle. However, it is heavily biased in favor of environmental issues, actually environmental burdens or stressors: the economic dimension is only tackled in LCC (Life Cycle Costing) and the social in a restricted approach called SLCA (Social Life Cycle Assessment). The idea of developing a more ambitious and wider encompassing method has been elusive, except when MFA (Material Flow Analysis) was proposed as an alternative and a competing discipline, but, eventually, the two methods proposed separate but complementary views of the world. In order to reach beyond LCA and its present weaknesses, it would be necessary to base the new approach on concepts embedded in SSH (Social Sciences and Humanities) rather than in STEM (Science Technology Engineering Mathematics) disciplines. This article describes the process under way to move in that direction. In a first step, a panorama will be drawn of the strengths and weaknesses of LCA and of LCT (Life Cycle Thinking). The analysis will focus on LCA weaknesses. On the way to extending LCA into SSH territory, an approach developed by Knowledge and Innovation, Italy, and called SCM (Social Cycle of Materials) looks at materials from a historical perspective. It shows how various resolutions (closures) are proposed to answer issues raised at different times, as a result of society's demand. The method proposes a distinctly new way of looking at materials cycles. The connection between this new approach and the traditional LCA cycle remains, however, to be done. In this paper, we propose to use ANT (Actor Network Theory), a concept developed by Bruno Latour, Michel Callon and Madeleine Akrich, to propose reconstructing the concept of LCA. The approach ambitions to list the various "stakeholders" related to materials in their value chain, like what is done in LCA, but also across long time, like what is done in SCM, and to include all actors in the sense of ANT, which means inanimate objects as well as elements of the geosphere and of the biosphere. It is expected to gain some insight into moving away from the indicator-based style of LCA. Clearly, we are still exploring and, most probably, we may end up complementing traditional LCA, most certainly not replacing it.