A Systematization and Comparison Framework to Facilitate Structured Selection of Sustainability Assessment Approaches

Abstract

Sustainability assessments (SA) of products, processes, organizations, strategies, etc. aim at providing a basis for decision-making towards (more) sustainable practices and principles. An extensive variety of SA approaches as well as a wide diversity of assessment situations exist, making situation-specific approach selection a complex issue. However, well-founded selection is crucial, as selecting unsuitable approaches for respective assessment situations can lead to incorrect, inconclusive, insignificant, implausible or vulnerable results. Structured, situation-specific selection processes for SA approaches can reduce these effects. However, there is a lack of respective concepts, criteria, guidelines or frameworks for decision-, i.e. selection-support. Based on this, the goal of this work is to develop a systematization and comparison framework, which facilitates structured selection of situation-specific SA approaches. In previous works, Bitter et al. (2018a, 2018b, 2019) proposed a requirements-set for SA approaches, a criteria-set for a systematization and comparison framework as well as respective spectra and specifications for the criteria. In this work, these elements are combined and implemented in form of a meta framework. By means of the criteria-set, SA approaches are characterized and subsequently quantified using the criteria-spectra. Thus, via an extensive rule base, the “fit” of SA approaches to situation-specific requirements, i.e. desired characteristics can be calculated. Based on these calculations within the meta framework, structured decision-support towards the situation-specific selection of suitable SA approaches is provided. For future works, the developed systematization and comparison framework can be used to systematically investigate the influence – nature and extend – of approach selection on assessment results.



Author Information
Jan Bitter, RWTH Aachen University, Germany
Daniela Janssen, Institute for Management Cybernetics, Germany
Frank Hees, RWTH Aachen University, Germany

Paper Information
Conference: IICSEEHawaii2020
Stream: Education

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