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Introducing weights to life cycle sustainability assessment—how do decision-makers weight sustainability dimensions?

  • LIFE CYCLE SUSTAINABILITY ASSESSMENT
  • Published:
The International Journal of Life Cycle Assessment Aims and scope Submit manuscript

Abstract

Purpose

Decisions based on life cycle sustainability assessment (LCSA) pose a multi-criteria decision issue, as impacts on the three different sustainability dimensions have to be considered which themselves are often measured through several indicators. To support decision-making at companies, a method to interpret multi-criteria assessment and emerging trade-offs would be beneficial. This research aims at enabling decision-making within LCSA by introducing weights to the sustainability dimensions.

Methods

To derive weights, 54 decision-makers of different functions at a German automotive company were asked via limit conjoint analysis how they ranked the economic, environmental, and social performance of a vehicle component. Results were evaluated for the entire sample and by functional clusters. Additionally, sustainability respondents, i.e., respondents that dealt with sustainability in their daily business, were contrasted with non-sustainability respondents. As a last step, the impact of outliers was determined. From this analysis, practical implications for ensuring company-optimal decision-making in regard to product sustainability were derived.

Results and discussion

The results showed a large spread in weighting without clear clustering. On average, all sustainability dimensions were considered almost equally important: the economic dimension tallied at 33.5%, the environmental at 35.2%, and the social at 31.2%. Results were robust as adjusting for outliers changed weights on average by less than 10%. Results by function showed low consistency within clusters hinting that weighting was more of a personal than a functional issue. Sustainability respondents weighted the social before the environmental and economic dimension while non-sustainability respondents put the economic before the other two dimensions. Provided that the results of this research could be generalized, the retrieved weighting set was seen as a good way to introduce weights into an operationalized LCSA framework as it represented the quantification of the already existing decision process. Therefore, the acceptance of this weighting set within the respective company was expected to be increased.

Conclusions

It could be shown that conjoint analysis enabled decision-making within LCSA by introducing weights to solve a multi-criteria decision issue. Furthermore, implications for practitioners could be derived to ensure company-optimal decision-making related to product sustainability. Future research should look at expanding the sample size and geographical scope as well as investigating the weighting of indicators within sustainability dimensions and the drivers that influence personal decision-making in regard to weighting sustainability dimensions.

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Notes

  1. The term “n-tier” or “tier-n” is often used to express that a section in the supply chain beyond tier-1 (direct supplier) or tier-2 (sub-supplier) is concerned. The “n” symbolizes that it can be a position at variable depth in the supply chain, which also can differ in length—one supply chain might have five tiers while another might have eight. There is no consistent use of this term in the literature—it is used to denote the entire supply chain (Zimmer et al. 2017), parts of the supply chain after tier-1 or tier-2 (Wolf 2011), or to refer to the last supplier in a given supply chain (Wolf 2011; Kerkow et al. 2012). In this paper, “n-tier supplier” denotes the last supplier in a given supply chain.

  2. Even though the word “error” is contained in this metric, its application to measure consistency does not imply a judgment of any sort, but rather reflects the deviation from the average. It is not the intention to declare that respondents that deviate from the average are making an error.

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Acknowledgements

This paper is part of a PhD thesis sponsored by the BMW Group. The authors thank the valuable input of three anonymous reviewers that greatly contributed to the improvement of the manuscript.

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Authors and Affiliations

  1. Chair of Sustainable Engineering, Institute of Environmental Technology, Technische Universität Berlin, Office Z1, Strasse des 17. Juni 135, 10623, Berlin, Germany

    Peter Tarne, Annekatrin Lehmann & Matthias Finkbeiner

  2. Product Sustainability, BMW Group, Knorrstraße 147, 80788, Munich, Germany

    Peter Tarne

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  1. Peter Tarne
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  2. Annekatrin Lehmann
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  3. Matthias Finkbeiner
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Correspondence to Peter Tarne.

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Responsible editor: Jeroen Guinée

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Tarne, P., Lehmann, A. & Finkbeiner, M. Introducing weights to life cycle sustainability assessment—how do decision-makers weight sustainability dimensions?. Int J Life Cycle Assess 24, 530–542 (2019). https://doi.org/10.1007/s11367-018-1468-2

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