Introducing weights to life cycle sustainability assessment—how do decision-makers weight sustainability dimensions?
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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.
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.
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.
KeywordsAutomotive company Conjoint analysis LCSA Limit conjoint analysis MCDA Multi-criteria decision analysis Sustainability dimensions Weighting
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.
- Adepoju JA, Ipinyomi RA (2016) Construction of asymmetric fractional factorial designs. Int J Eng Appl Sci 3:88–91Google Scholar
- Backhaus K, Erichson B, Plinke W, Weiber R (2011a) Multivariate Analysemethoden. Eine anwendungsorientierte Einführung, 13th edn. Springer-Verlag, BerlinGoogle Scholar
- Baier D, Brusch M (eds) (2009) Conjointanalyse. Springer Berlin Heidelberg, BerlinGoogle Scholar
- Finkbeiner M, Reimann K, Ackermann R (2008) Life cycle sustainability assessment (LCSA) for products and processes. In: SETAC Europe 18th annual meeting, 25–29 May. Warsaw, PolandGoogle Scholar
- Johnson R, Orme B (1996) How many questions should you ask in choice-based conjoint studies? Sawtooth Softw Research P:23Google Scholar
- JRC (2012) Towards a life-cycle based European sustainability footprint framework. Publications Office of the European Union, LuxembourgGoogle Scholar
- Kerkow U, Martens J, Müller A (2012) Vom Erz zum Auto - Abbaubedingungen und Lieferketten im Rohstoffsektor und die Verantwortung der deutschen AutomobilindustrieGoogle Scholar
- Klöpffer W, Grahl B (2014) From LCA to sustainability assessment. In: Life Cycle Assessment (LCA). Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim, pp 357–374Google Scholar
- Kohne F, Totz C, Wehmeyer K (2005) Consumer preferences for location-based service attributes: a conjoint analysis. Int J Manag Decis Mak 6:16Google Scholar
- Orme B (2010) Sample size issues for conjoint analysis. In: Getting started with conjoint analysis: strategies for product design and pricing research, second Edi. Research Publishers LLC, Madison, pp 57–66Google Scholar
- Rao VR (2014) Theory and design of conjoint studies (ratings based methods). In: Applied conjoint analysis. Springer Berlin Heidelberg, Berlin, Heidelberg, pp 37–78Google Scholar
- Traverso M, Tarne P, Wagner V (2015) Towards a comprehensive approach for the sustainability assessment of a product: product social impact assessment. In: Pfeffer P (ed) 6th International Munich Chassis Symposium 2015. Springer-Verlag, pp 161–174Google Scholar
- UNEP/SETAC Life Cycle Initiative (2011) Towards a life cycle sustainability assessment - making informed choices on products. UNEP/SETAC Life Cycle Initiative, FranceGoogle Scholar
- Voeth M, Hahn C (1998) Limit conjoint-analyse. Mark Zeitschrift für Forsch und Prax 20:119–132Google Scholar