TY - GEN
T1 - Can online customer reviews help design more sustainable products? A preliminary study on Amazon climate pledge friendly products
AU - Saidani, Michael
AU - Kim, Harrison
AU - Ayadhi, Nawres
AU - Yannou, Bernard
N1 - Publisher Copyright:
Copyright © 2021 by ASME.
PY - 2021
Y1 - 2021
N2 - Online product reviews are a valuable resource for product developers to improve the design of their products. Yet, the potential value of customer feedback to improve the sustainability performance of products is still to be exploited. The present paper investigates and analyzes Amazon product reviews to bring new light on the following question: “What sustainable design insights can be identified or interpreted from online product reviews?”. To do so, the top 100 reviews, evenly distributed by star ratings, for three product categories (laptop, printer, cable) are collected, manually annotated, analyzed and interpreted. For each product category, the reviews of two similar products (one with environmental certification and one standard version) are compared and combined to come up with sustainable design solutions. In all, for the six products considered, between 12% and 20% of the reviews mentioned directly or indirectly aspects or attributes that could be exploited to improve the design of these products from a sustainability perspective. Concrete examples of sustainable design leads that could be elicited from product reviews are given and discussed. As such, this contribution provides a baseline for future work willing to automate this process to gain further insights from online product reviews. Notably, the deployment of machine learning tools and the use of natural language processing techniques to do so are discussed as promising lines for future research.
AB - Online product reviews are a valuable resource for product developers to improve the design of their products. Yet, the potential value of customer feedback to improve the sustainability performance of products is still to be exploited. The present paper investigates and analyzes Amazon product reviews to bring new light on the following question: “What sustainable design insights can be identified or interpreted from online product reviews?”. To do so, the top 100 reviews, evenly distributed by star ratings, for three product categories (laptop, printer, cable) are collected, manually annotated, analyzed and interpreted. For each product category, the reviews of two similar products (one with environmental certification and one standard version) are compared and combined to come up with sustainable design solutions. In all, for the six products considered, between 12% and 20% of the reviews mentioned directly or indirectly aspects or attributes that could be exploited to improve the design of these products from a sustainability perspective. Concrete examples of sustainable design leads that could be elicited from product reviews are given and discussed. As such, this contribution provides a baseline for future work willing to automate this process to gain further insights from online product reviews. Notably, the deployment of machine learning tools and the use of natural language processing techniques to do so are discussed as promising lines for future research.
KW - Customer feedback
KW - Data-driven design
KW - Ecolabels
KW - Online reviews
KW - Sustainability-related comments
KW - Sustainable design
UR - http://www.scopus.com/inward/record.url?scp=85119952501&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85119952501&partnerID=8YFLogxK
U2 - 10.1115/DETC2021-69705
DO - 10.1115/DETC2021-69705
M3 - Conference contribution
AN - SCOPUS:85119952501
T3 - Proceedings of the ASME Design Engineering Technical Conference
BT - 33rd International Conference on Design Theory and Methodology (DTM)
PB - American Society of Mechanical Engineers (ASME)
T2 - 33rd International Conference on Design Theory and Methodology, DTM 2021, Held as Part of the ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE 2021
Y2 - 17 August 2021 through 19 August 2021
ER -