1 Introduction
The current state of the textile industry has major ecological, economic and social impacts. Especially the current “fast fashion”-trend causes increasing negative effects on the environment and the people employed in the textile industry who produce raw materials and clothes. The textile sector produces large quantities of solid waste and wastewater and consumes a lot of resources (Kozlowski et al. 2012). To produce raw materials, especially cotton fibers, genetically modified seeds (Kaur et al. 2013) and pesticides (EJF 2007) are widely used. Due to low prices and high competition, workers are exploited (Fletcher 2013).
Currently several ways to target these issues are suggested by different authors. Besides reduction of inputs and waste (Kozlowski et al. 2012) and sustainable design (e.g. Fletcher 2013) literature considers Product-service systems (PSS) as one way to reduce negative effects (Roy 2000; Baines et al. 2007). They are considered to be less harmful than conventional production and use patterns (Mont 2002), in case of the textile industry mass production of clothes and the current trend of “fast-fashion” (quick change of trends and offered styles to sell a lot of cheap and non-durable garments) (Fletcher 2013).
Product-Service Systems (PSS) are, according to the definition of Goedkoop et al., “a marketable set of products and services capable of jointly fulfilling a user’s need” (Goedkoop et al. 1999). Tukker presented eight archetypical models of PSS in 2004 (Tukker 2004) and published a review on PSS eleven years later (Tukker 2015). He states that renting, a use-oriented PSS, can have significant benefits due to the more intensive use of goods. He also discusses limitations of PSS in a business-to-consumer context. The value of owning things instead of sharing them seems to be an important obstacle.
2 Business Model: Renting of Casual Wear
Business model: Renting of casual wear
The arrow on the left and the grey “End-of-life”-process on the right represent the (conventional) value chain of the textile industry. End-of-life will be neglected in this work since it remains unclear whether the disposal after renting differs in any way from the disposal in conventional consumption. The white processes are the circular business model provided by the start-ups.
3 Proposed Method
Though many Life Cycle Assessment (LCA, ISO 2006) articles dealing with textiles exist, there are only a few which are dealing with PSS in the textile industry (Piontek and Müller 2018). While many articles analyzing the life cycle of t-shirts (Zhang et al. 2015), different fibres (Shen et al. 2010) or a new technology (Agnhage et al. 2017) use e.g. a number of garments or a certain amount of material as the functional unit, this approach does not seem feasible for a PSS providing the possibility for an alternative use pattern like renting. To model the divergent impacts of an alternative consumption pattern, a broader approach is needed. Castellani et al. conducted a study of avoided impacts of the activity of a second-hand shop which includes T-shirts and sweaters (Castellani et al. 2015).
Zamani et al. recently published a paper assessing the environmental impacts of a fashion library (Zamani et al. 2017). They focused on the prolonged service life of three types of garments in Sweden. We, in contrast, want to focus on the changed impacts of alternative clothing consumption of one consumer renting some of her clothes instead of buying them.
Therefore, we developed the functional unit “one year of varied use of clothing” by combining data from different sources. It represents the clothing consumption of one female consumer in Germany during one average year. We used data on purchase frequencies provided by a study by Spiegel Media (Spiegel QC 2015). Using data by Greenpeace (Greenpeace e.V. 2015) and of our research project (Geiger et al. 2017), we estimated the average period of use. Information on which types of clothes are rented have been provided by the start-ups (Apel 2017; Fendel 2017).
Schematic representation of the functional unit of conventional consumption
It is the schematic result of the combination of the previously mentioned data. We model an average year of consumption n of one person by combining new purchases, disposed clothes and the number of clothes owned.
Jacket 1 and Jacket 2 are bought sometime before year n, are owned during year n and will be disposed sometime after year n. Jacket 3 gets purchased in autumn of year n and will be disposed several years later. Jacket 4 was bought several years before year n and gets disposed after summer of year n.
Schematic representation of the functional unit of a renting-scenario
The described procedure will allow us to compare the environmental impacts of conventional consumption and conventional consumption combined with renting of one person in one year. We are planning to allocate the environmental impact of production of each garment proportional to the seasons of usage or ownership during the same year. For our example shown in Figs. 2 and 3 we assume an average period of use of 4 years (16 seasons) for a jacket. Therefore, for conventional consumption we will take 12/64 of the total production impacts of the four jackets into account. 12/64 because of 4 seasons for Jacket 1, 4 seasons for Jacket 2, 2 seasons (autumn and winter) for Jacket 3 and 2 seasons (spring and summer) for Jacket 4. For our renting scenario, we only have to consider 8/64 of the production impacts following the same procedure. It must be considered, that renting can cause additional impacts for shipping and cleaning (Zamani et al. 2017).
4 Summary and Outlook
We presented a brief overview of the development of the functional unit “one year of varied use of clothing” which we will use to assess the changed environmental impacts of renting clothes instead of buying them. Assessing all the impacts for different kinds of clothes (including end-of-life) of both scenarios will allow us to make a statement on whether renting has benefits for the environmental impacts of one average person. It will be possible to use different baseline—as well as renting-scenarios to consider the divergent consumption patterns of different consumer groups. With this attributional method, we only assess the environmental impacts of one person, which is adequate, as the interviewed start-ups are currently niche companies and provide an offer for people interested in alternative consumption as well as people who want to try a new style modeled (Apel 2016; Wilkening and Fendel 2016; Krichel 2016). To understand the overall influence of renting, a different approach will be needed. We plan to simulate the business model shown in Fig. 1 for a fictional company providing renting of clothes on a bigger scale.
We also think that it will be possible to use this approach to conduct LCA-studies in different regions (using different input-data for the functional unit) or even apply it to other branches (e.g. car sharing or tool rental).
Acknowledgements
We want to thank Samira Iran (TU Berlin), Markus Dimmer and Viktor R. Moritz Meissner (both Ulm University) for their input and support.