Sustainable design and repair: Leveraging circular economy and machine learning for product development

Q1 Economics, Econometrics and Finance
Noushin Mohammadian , Omid Fatahi Valilai , Alexander Schlüter
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引用次数: 0

Abstract

Optimising resource efficiency is essential for sustainable product lifecycle management (PLM). This motivates the use of novel methodologies such as sustainable design, circular economy concepts, and causal machine learning algorithms. This study focuses on repair as one of the circular economy principles and investigates how tutorials promote the "Design for Repair" idea in three industry sectors: textiles, electronics, and vehicle accessories. To evaluate consumer engagement and sentiment, the paper has analysed user feedback from YouTube© repair instructions using sentiment analysis, emotion analysis, and other data visualisation approaches. The findings are encouraging, demonstrating a generally positive response to repair-oriented programming, with high levels of trust and anticipation among viewers. Fluctuations in sentiment and engagement underscore the importance of constant content enhancement and smart dissemination via omnichannel touch points. A well-planned digital marketing strategy is critical for promoting circularity and fostering a culture of repair and sustainability, ensuring these principles reach and resonate with a broader audience. This study emphasises the importance of educational repair videos in promoting a culture of sustainability and repair. Integrating these insights into PLM strategy can increase consumer acceptance, encourage eco-friendly practices, and dramatically minimise environmental impact, hence facilitating the move to more green manufacturing systems.
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来源期刊
Journal of Open Innovation: Technology, Market, and Complexity
Journal of Open Innovation: Technology, Market, and Complexity Economics, Econometrics and Finance-Economics, Econometrics and Finance (all)
CiteScore
11.00
自引率
0.00%
发文量
196
审稿时长
1 day
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