Attributional or consequential Life Cycle Assessment: A matter of social responsibility

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Abstract

Results of Life Cycle Assessment (LCA) are critically dependent on the system boundaries, notably the choice of attributional or consequential modelling. Published LCA studies rarely specify and justify their modelling choices. Since LCA studies are typically performed within the context of social responsibility and product life cycle management, this article investigates the relationship between social responsibility paradigms and the system modelling choices in LCA. We identify three different social responsibility paradigms: Value chain responsibility, Supply chain responsibility and Consequential responsibility. We point out that while there is no generally right or wrong choice of system model, each responsibility paradigm implies a specific matching system model. We then argue that all responsibility paradigms ultimately imply a consequential perspective, namely that of responding to the concerns of the system stakeholders. Although value or supply chains are systems defined without concern for consequences, and thus may include activities that the decision maker cannot influence, the chosen system is still analysed and assessed by accounting for its social consequences, and it is for these consequences that social responsibility is then taken. We argue that it is inconsistent to exclude consequences of own actions (i.e. the consequential system) while including consequences from actions of others in value chain or supply chain. We thus conclude that a consistent socially responsible decision-maker must always take responsibility for the activities in the consequential product life cycle and may additionally take responsibility for the consequences of other activities in the value chain or supply chain. We end the article with recommendations on reporting on LCA system models that are more specific than those of the current LCA standards.

Original languageEnglish
JournalJournal of Cleaner Production
Volume174
Pages (from-to)305-314
Number of pages10
ISSN0959-6526
DOIs
Publication statusPublished - 10 Feb 2018

Keywords

  • Product life cycle
  • Sphere of influence
  • Supply chain
  • System modelling
  • Value chain

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