Abstract
The communication of sustainability values shared between product developers and customers is an important catalyst for effective collaboration that inspires sustainable consumption. Despite the many tools developed for assessing and communicating the product’s sustainability performance, customers are facing difficulties in understanding product sustainability information. The knowledge gaps remain underexplored about how product sustainability information is perceived and how this impacts customer purchasing behaviour. This paper outlines a new approach, driven by both backcasting and forecasting thinking, for understanding and modelling customer preferences for product sustainability information. We report findings from a case study of a large workplace furniture manufacturer. The study explored the potential of (i) identifying prioritised sustainability attributes using sustainability design space (SDS) and (ii) applying machine learning to model customer preferences.
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Financial support from the Knowledge Foundation in Sweden is gratefully acknowledged. Sincere thanks to the industrial research partners.
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Kwok, S.Y., Hallstedt, S.I., Boeva, V. (2021). Understanding Customer Preference: Outline of a New Approach to Prioritise Sustainability Product Information. In: Scholz, S.G., Howlett, R.J., Setchi, R. (eds) Sustainable Design and Manufacturing 2020. Smart Innovation, Systems and Technologies, vol 200. Springer, Singapore. https://doi.org/10.1007/978-981-15-8131-1_3
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DOI: https://doi.org/10.1007/978-981-15-8131-1_3
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