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Hotspot identification in the clothing industry using social life cycle assessment—opportunities and challenges of input-output modelling
Chalmers University of Technology, Sweden.
RISE, SP – Sveriges Tekniska Forskningsinstitut.ORCID iD: 0000-0002-3536-7895
Chalmers University of Technology, Sweden.
Chalmers University of Technology, Sweden.
2018 (English)In: The International Journal of Life Cycle Assessment, ISSN 0948-3349, E-ISSN 1614-7502, Vol. 23, no 3, p. 536-546Article in journal (Refereed) Published
Abstract [en]

Purpose: A cradle-to-gate, input/output-based social life cycle assessment (SLCA) was conducted using the Swedish clothing consumption as a case study. The aim was to investigate the influence of the cut-off rule and the definition of “hotspots” in social hotspot assessment. A second aim was to identify social hotspots of Swedish clothing on a national level. Methods: The case study was based on the SLCA methodology provided in the Guidelines for Social Life Cycle Assessment of Products (Benoît and Mazijn 2009). An input/output model was used to define the product system from cradle to gate. The negative social hotspots were evaluated for a set of social indicators that were selected by consumers. The impact assessment was conducted on a sector and country level by using the Social Hotspots Database. The identified sectors of the economy with high and very high levels of risk were listed for each social indicator. Results and discussion: The results pinpointed some hotspots throughout the supply chain for Swedish clothing consumption. Some unexpected sectors such as commerce and business services in Bangladesh were identified as important hotspots as well as main sectors in the production phase such as plant fibres, textiles and garments that would be expected also on the bases of a traditional process analysis. A sensitivity analysis on different cut-off values showed the extent to which the choice of cut-off rule can directly affect the results via influence over the number of country-specific sectors (CSSs) in the product system. The influence of the hotspot definition was investigated by evaluating the working hour intensity for low- and medium-risk levels for three different indicators. The results show that for child labour, 92 % of the share of working hours was associated with low- and medium-risk levels. Therefore, the evaluation of risk levels other than high and very high can provide a more complete picture of the hotspots. Conclusions: The application of input/output-based SLCA on the clothing production supply chain provided a more complete picture of the social hotspots than with traditional process-based SLCA. Some unexpected sectors related to commerce and business appeared as social hotspots in the clothing industry. The study explored some important parameters in applying an input/output-based SLCA. The results show that the cut-off values and definition of hotspots in relation to risk levels can directly influence the results. 

Place, publisher, year, edition, pages
2018. Vol. 23, no 3, p. 536-546
Keywords [en]
Fashion, SHDB, SLCA, Social Hotspot identification, Social Hotspots Database, Social impact
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:ri:diva-317DOI: 10.1007/s11367-016-1113-xScopus ID: 2-s2.0-84964370956OAI: oai:DiVA.org:ri-317DiVA, id: diva2:938623
Available from: 2016-06-17 Created: 2016-06-17 Last updated: 2019-08-02Bibliographically approved

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Sandin, Gustav

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