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Online product reviews are a valuable resource for product developers toimprove the design of their products. Yet, the potential value of customerfeedback to improve the sustainability performance of products is still to beexploited. The present paper investigates and analyzes Amazon product reviewsto bring new light on the following question: ``What sustainable designinsights can be identified or interpreted from online product reviews?''. To doso, the top 100 reviews, evenly distributed by star ratings, for three productcategories (laptop, printer, cable) are collected, manually annotated, analyzedand interpreted. For each product category, the reviews of two similar products(one with environmental certification and one standard version) are comparedand combined to come up with sustainable design solutions. In all, for the sixproducts considered, between 12% and 20% of the reviews mentioned directly orindirectly aspects or attributes that could be exploited to improve the designof these products from a sustainability perspective. Concrete examples ofsustainable design leads that could be elicited from product reviews are givenand discussed. As such, this contribution provides a baseline for future workwilling to automate this process to gain further insights from online productreviews. Notably, the deployment of machine learning tools and the use ofnatural language processing techniques to do so are discussed as promisinglines for future research.

Can Online Customer Reviews Help Design More Sustainable Products? A Preliminary Study on Amazon Climate Pledge Friendly Products