R. Koide
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7 records found
1
Achieving a circular economy requires not only quantifying material stocks and flows but also understanding the dynamic processes that shape them over time. While Material Flow Analysis (MFA) is widely used to track physical stocks and flows, MFA has limited capacity to represent behavioral feedback, endogenous system responses, and temporal delays. System Dynamics (SD), by contrast, is well suited to capturing feedback structures and non-linear system behavior, but it does not inherently enforce mass conservation. Despite these fundamental differences, the two approaches are often applied without a clear conceptual distinction. Here, we compare and integrate MFA and SD to develop a modelling framework that is both mass balanced and feedback driven. Using three simplified models (MFA, SD, and integrated SD-MFA), we demonstrate that the integrated approach can simultaneously preserve mass balance and represent causal relationships, feedback loops, and time delays. The combined framework offers a more robust basis for analyzing circular economy transitions, enabling the assessment of not only how materials flow through systems, but also how socio-technical dynamics influence those flows over time.
Lifestyle change modelling for climate change mitigation
Complementary strengths, policy support, and research avenues
Consumer preferences regarding product acquisition, repair, and discharge towards a circular economy
A segment-specific market simulation based on conjoint analysis
Consumer preferences for a circular economy are known to be heterogeneous; however, most existing studies focus exclusively on the product acquisition phase and assume homogeneous utilities. This study aims to understand consumer segments for circular business models in terms of consumer preferences and market shares, and to investigate the commonalities across the three phases of consumer engagement in the circular economy: acquisition, repair, and discharge. We combined choice-based conjoint analysis, ensemble clustering, and market simulation, and applied them to three typical products (refrigerators, laptops, and children's goods) in the Japanese market. The analysis revealed the consistent existence of key consumer segments across the three phases. First, circular-oriented segments (12–33 % of the population, depending on the phase and product category) show a high willingness to adopt circular business models (e.g., 67–100 % within-segment share), making them a promising entry point for target-based marketing. Second, price-sensitive segments (13–30 %) could play a pivotal role in mainstreaming circular business models, highlighting the need for substantial price reductions of circular offers relative to linear offers. Third, balanced decision-makers (19–38 %), who tend to resist traditional circular options (e.g., reuse), are open to new circular business models (e.g., refurbish, subscription, functional upgrading, sharing), indicating the importance of designing attractive product service offers. Finally, linear-insistent segments (24–51 %) almost never choose circular products and repair options (e.g., 0–2 % segment-wise share). This results in a persistently high total market share of linear options, even under ambitious scenarios; e.g., 44–57 % of acquisitions are brand-new, and 51 % of broken products remain unrepaired. Although linear-insistent behaviour in any of these phases may act as a bottleneck, overlapping membership among consumer segments suggests the potential for positive spillover across phases. This study's approach enables more nuanced consumer segmentation, facilitating the identification of diffusion stages, the design of appealing product services, and the development of target-wise marketing strategies towards the circular economy.
Given the urgent need to promote climate-friendly behaviours, the implementation of carbon footprint calculators with actionable recommendations is increasing. This study analysed data from >7000 users of a Japanese carbon footprint calculator to investigate the characteristics and factors affecting voluntary commitment to decarbonisation actions and the gaps in achieving the 1.5-degree mitigation target. The results showed voluntarily committed actions were insufficient to meet the 2030 personal carbon footprint target, with only 31 %, 18 %, and 7.3 % of users potentially achieving targets in the domains of housing, mobility, and goods/services, respectively. The seven user segments that were identified exhibited very different levels of engagement. For example, ‘lifestyle change enthusiasts’ committed to as many as 25 actions, corresponding to an equivalent of 2.8 tCO2e of footprint reduction, while ‘curious bystanders’ rarely committed to any actions. Demographically, younger and male users tended to prioritise high-impact actions, whereas female users and users aged 50–60 years old were more likely to commit to a range of actions. Notably, actions requiring substantial financial investment had an 8 % lower commitment probability, and ‘shift’ actions were 6 % less preferred than ‘avoid’ actions”. These findings contribute to a deeper understanding of the considerable gap between self-committed actions and mitigation targets, and suggest that more effective use of footprint information could facilitate greater engagement. Tailored strategies could better motivate the ‘curious bystanders’ segment and encourage female and older users to focus on high-impact actions.
Despite the need for methodologies that support early-phase decision-making in the transition to a circular economy, current sustainability assessments often lack a prospective method that dynamically accounts for consumer decision-making based on empirical evidence. This study addresses this need by evaluating the circularity and environmental impacts of circular business models over a 30-year period, using an empirically grounded agent-based model coupled with life cycle assessment and material flow analysis. We developed a methodology to parameterize agents’ decision-making using data from demographically representative surveys and to prospectively assess the sustainability impacts of circular strategies. The case study examines the reuse, refurbishment, and subscription models of refrigerators and laptops in Japan. Results from Morris Elementary effects method and scenario analyses revealed that manufacturer-led refurbishment could reduce emissions of the whole society by 10%–12% and extend product lifetimes by 30%–33%. In contrast, the subscription model shows minimal benefits, with improvements of only 0%–3%, primarily due to consumer preferences for new products. Our consequential approach extends beyond technical strategies to evaluate the effectiveness of strategies targeting consumer behavior, including pricing, advertisements, and improvements in repair and collection services. The findings highlight the need for combining synergistic circular and diffusion strategies and suggest the need for a reorientation of policy efforts from end-of-life material recovery to refurbishment, reuse, and repair, supported by intensive campaigns and substantial price reductions in circular offerings. The methodology presented here facilitates prospective, dynamic, and consequential assessments of circular economy strategies to enhance consumer acceptance and ensure sustainability gains.
Regional sensitivity analysis to assess critical parameters in circular economy interventions
An application to the dynamic MFA model
In evaluating a circular economy (CE), one needs to address the complexity arising from indicators with multiple objectives, multiple means of implementation with combinations of CE strategies, and the uncertainty inherent in resource cycle systems. Regional sensitivity analysis (RSA) is a version of global sensitivity analysis that can be used to determine whether the output variables of a mathematical model lie within a certain range. Although RSA has found application in a wide range of fields, no prior studies sought to apply the method to industrial ecology. In this study, RSA is applied to a dynamic material flow analysis (MFA) model to identify the essential factors and analyze the conditions under which two indicators, greenhouse gas emissions and total material requirement, are influenced, in the case studies for digital cameras and smartphones. To this end, RSA with 10,000 Monte Carlo simulations were performed. Two factors were found to be especially important: (1) controlling the collection channels of end-of-life products, and (2) encouraging consumers to use products over a longer period. It was also suggested that, for ambitious reductions in environmental impacts, the achievement of targets should be given priority over the speed of implementation of strategies. To avoid catastrophic environmental impacts, the first step should be to ensure higher recycling rates using well-developed collection routes. This study represents a major step forward from simply forecasting future cycles with the dynamic MFA model to the application of RSA to systematically consider parameter uncertainties with various possibilities of combined circular economy strategies.