Short answer
When designing products for usage-focused business models, embed digital technologies to enable real-time monitoring, predictive maintenance, and efficient end-of-life processing, thereby maximizing resource efficiency and product longevity.
- Field
- Sustainability
- Source
- Sustainability (2018)
- Method
- Conceptual framework development and case study analysis.
- Evidence
- Strong effect
Digital technologies like IoT and Big Data enable specific functionalities that improve resource efficiency, extend product lifespan, and close material loops within usage-focused business models, thereby accelerating the transition to a circular economy. This sustainability research insight is drawn from a 2018 study published in Sustainability. Using Conceptual framework development and case study analysis., researchers explored how this design variable affects real-world outcomes. The key design takeaway: When designing products for usage-focused business models, embed digital technologies to enable real-time monitoring, predictive maintenance, and efficient end-of-life processing, thereby maximizing resource efficiency and product longevity.
Digital technologies significantly enhance circular economy adoption in usage-focused business models.
Digital technologies like IoT and Big Data enable specific functionalities that improve resource efficiency, extend product lifespan, and close material loops within usage-focused business models, thereby accelerating the transition to a circular economy.
Sustainability · 2018
Key Findings
- 01IoT, Big Data, and analytics enable eight specific functionalities: improving product design, attracting target customers, monitoring and tracking product activity, providing technical support, providing preventive and predictive maintenance, optimizing product usage, upgrading the product, and enhancing renovation and end-of-life activities.
- 02These functionalities positively affect three CE value drivers: increasing resource efficiency, extending product lifespan, and closing the loop.
- 03Digital technologies help overcome previous drawbacks of usage-focused business models for CE adoption.
Application
Design takeaway
When designing products for usage-focused business models, embed digital technologies to enable real-time monitoring, predictive maintenance, and efficient end-of-life processing, thereby maximizing resource efficiency and product longevity.
How to apply
For a washing machine designed for a 'laundry-as-a-service' model, integrate IoT sensors to monitor usage patterns, predict maintenance needs, and track component wear. This data can inform design improvements, optimize service schedules, and facilitate component recovery at end-of-life.
Project actions
- 01When designing a product for a circular economy, think about how digital technology can help track its use, fix it when it breaks, or even upgrade it.
- 02Consider how a 'product-as-a-service' model could work for your design and what digital features would be essential.
Method & Evidence
Variables
Strengths & Limitations
Strengths
- +Provides a clear conceptual framework linking digital tech to CE.
- +Uses a real-world case study to illustrate concepts.
Limitations
The study is conceptual, so its findings might not apply perfectly to all types of products or industries. It's also based on one company, so more examples would be helpful.
Reliability & validity
The conceptual framework is logically sound, but its validity relies on the accuracy of the literature review and the representativeness of the single case study. Reliability would be enhanced by testing the framework across multiple diverse cases.
Think critically
How might the cost and complexity of integrating advanced digital technologies impact the accessibility and adoption of circular economy models, especially for smaller businesses or in developing economies?
Design Principles
"Digital Enablement for Circularity: Design products and services with integrated digital technologies to facilitate resource efficiency, extend product lifespan, and enable closed-loop systems within usage-focused business models."
Understanding how digital technologies facilitate circular economy principles is crucial for designers developing sustainable products and services. This insight helps in integrating technology-driven solutions for resource management and waste reduction, aligning with the design focus on sustainable design and innovation.
What This Means for Your Design
Using smart technology like internet-connected sensors (IoT) and big data analysis can make products last longer and be reused more easily, especially when companies rent out products instead of selling them.
How to use in your project
- 1.When discussing your product's sustainability, you can cite this paper to explain how integrating digital technologies (e.g., IoT for monitoring) can extend product lifespan and enable circularity in a usage-focused model.
- 2.If your design incorporates a service model, use this research to justify the inclusion of digital features for better resource management.
Add to My Project
Quick Cite
Paragraph starter
Bressanelli et al. (2018) highlight that digital technologies, such as the Internet of Things (IoT) and Big Data analytics, are crucial enablers for the circular economy, particularly within usage-focused business models. Their conceptual framework and case study demonstrate that these technologies facilitate functionalities like improved product design, predictive maintenance, and optimized usage, which in turn increase resource efficiency, extend product lifespan, and close material loops. This suggests that integrating digital solutions from the outset is vital for designing sustainable products and services within a circular economy framework.
Source
Sustainability
Exploring How Usage-Focused Business Models Enable Circular Economy through Digital Technologies
journal · 2018
View sourceQuestions About This Research
- What does the research say about digital technologies significantly enhance circular economy adoption in usage-focused business models?
- When designing products for usage-focused business models, embed digital technologies to enable real-time monitoring, predictive maintenance, and efficient end-of-life processing, thereby maximizing resource efficiency and product longevity. Evidence: Sustainability (2018).
- Why does "Digital technologies significantly enhance circular economy adoption in usage-focused business models." matter for design?
- Understanding how digital technologies facilitate circular economy principles is crucial for designers developing sustainable products and services. This insight helps in integrating technology-driven solutions for resource management and waste reduction, aligning with the IB DT focus on sustainable design and innovation.
- How can designers apply this research?
- When designing products for usage-focused business models, embed digital technologies to enable real-time monitoring, predictive maintenance, and efficient end-of-life processing, thereby maximizing resource efficiency and product longevity.
- What were the main findings?
- IoT, Big Data, and analytics enable eight specific functionalities: improving product design, attracting target customers, monitoring and tracking product activity, providing technical support, providing preventive and predictive maintenance, optimizing product usage, upgrading the product, and enhancing renovation and end-of-life activities.. These functionalities positively affect three CE value drivers: increasing resource efficiency, extending product lifespan, and closing the loop.. Digital technologies help overcome previous drawbacks of usage-focused business models for CE adoption.
- What research method was used?
- Conceptual framework development and case study analysis..
- How strong is the evidence?
- Evidence strength is rated Strong effect, based on a 2018 journal from Sustainability.
- What should I do differently in my next project?
- For a washing machine designed for a 'laundry-as-a-service' model, integrate IoT sensors to monitor usage patterns, predict maintenance needs, and track component wear. This data can inform design improvements, optimize service schedules, and facilitate component recovery at end-of-life.
- What are the limitations?
- The study is conceptual and based on a single case study, limiting generalizability. Further empirical validation across diverse industries is needed.