Beyond greenwashing: how circular economy metrics could revolutionize ESG investing

Environmental, Social, and Governance (ESG) investing has gained global traction as a framework for sustainable finance, yet it remains vulnerable to greenwashing where firms exaggerate environmental claims to attract capital. This article argues that integrating circular economy (CE) metrics into ESG frameworks offers a more transparent and measurable approach to sustainability assessment. CE metrics such as Circular Material Use Rate (CMUR), lifecycle carbon intensity, and the Product Circularity Index (PCI) enable objective evaluations of material recovery, resource efficiency, and long-term ecological impact. Drawing on corporate examples like IKEA and Renault, and policy instruments such as the EU Circular Economy Action Plan and Digital Product Passports, the paper demonstrates how CE integration can reduce systemic risk and align financial performance with regenerative outcomes. Institutional entrepreneurship and regulatory innovations including Extended Producer Responsibility (EPR) and green public procurement are identified as key catalysts for mainstreaming circularity within ESG investing. Additionally, technologies like blockchain and AI-driven lifecycle analytics are highlighted as vital enablers of real-time verification and investor-grade circular data. Ultimately, this article envisions a transformative shift toward CE-aligned ESG investing, where financial decisions are grounded in auditable sustainability metrics and structured to promote long-term environmental integrity and accountability.

1 Introduction

Environmental, Social, and Governance (ESG) investing has emerged as a dominant paradigm in modern finance, reflecting a growing recognition of the need for businesses to operate within planetary boundaries while contributing to social equity and ethical governance (Adams and Larrinaga-González, 2007; Galaz et al., 2018; Landau et al., 2020). This approach seeks to align financial markets with broader societal goals, leveraging capital flows to drive sustainable economic transformations. However, despite its rapid ascent, ESG investing is increasingly beset by structural challenges, including pervasive greenwashing, inconsistent performance metrics, and the over-reliance on self-reported, unverifiable data (Bodellini, 2023; Dumrose et al., 2022). Consequently, Greenwashing refers to the strategic misrepresentation of environmental performance to attract sustainability-focused investors threatens the very integrity of ESG frameworks, undermining their capacity to drive genuine systemic change (Bernini and La Rosa, 2024; Ghitti et al., 2024).

Moreover, the persistence of greenwashing can be traced to foundational weaknesses in current ESG assessment methodologies (Adams and Larrinaga-González, 2007; Aqueveque et al., 2018). Unlike financial reporting, which adheres to standardized quantitative benchmarks, ESG metrics often lack consistency and transparency, allowing firms to selectively disclose favorable data while obscuring critical negative impacts (Albitar et al., 2020; Rinaldi et al., 2022; Baah et al., 2022). This selective reporting creates a distorted view of corporate sustainability, leading to mispriced risk and misallocated capital (Lin et al., 2023; Wang and Sarkis, 2017). For example, Lin et al. (2023) demonstrated that firms engaged in greenwashing often exhibit significant equity mispricing, reflecting deeper structural issues within ESG evaluation frameworks (Lin et al., 2023; Liu et al., 2024; Alonso-Almeida et al., 2021). This mispricing not only compromises investor confidence but also undermines the potential for financial markets to drive authentic sustainability transitions (Rodríguez-Espíndola et al., 2022; Sneideriene and Legenzova, 2025).

Circular economy (CE) metrics offer a compelling alternative, addressing these deficiencies by providing robust, data-driven measures of sustainability performance (Aerts and Cormier, 2009; Ahmad et al., 2023). Unlike conventional ESG metrics, which frequently rely on subjective interpretations or qualitative assessments, CE metrics emphasize measurable, tangible outcomes such as resource efficiency, waste reduction, and lifecycle analysis (Jakubelskas and Skvarciany, 2023; Atstāja et al., 2022). For instance, Amin et al. (2024) reported that firms adopting CE principles achieved up to 30% reductions in material costs and 25% decreases in waste generation, underscoring the financial viability of circular models (Amin et al., 2024). These findings synchronize with Kristoffersen et al. (2021), who highlighted that firms with advanced circular capabilities outperform their peers by up to 20% in resource efficiency and 15% in long-term profitability, reinforcing the economic case for CE integration (Kristoffersen et al., 2021; Fernando et al., 2022).

Furthermore, CE metrics capture long-term sustainability dynamics that traditional ESG frameworks often overlook. Studies by Le et al. (2022) and Fatimah et al. (2023) demonstrate that CE practices enhance resource regeneration, reduce lifecycle carbon emissions, and improve supply chain resilience, providing a more comprehensive assessment of environmental impact (Le et al., 2022; Fatimah et al., 2023). Unlike ESG metrics, which often emphasize short-term outputs, CE metrics capture the full spectrum of value creation, including resource recovery, waste minimization, and lifecycle efficiency (Baah et al., 2022; Cavicchi et al., 2022). For example, the Ellen MacArthur Foundation (2021) estimates that a full-scale shift to CE could generate global economic benefits worth $4.5 trillion by 2030, reflecting the immense economic potential of this paradigm shift.

However, significant challenges remain. Despite their promise, CE metrics are not without limitations. Albitar et al. (2020) and Rinaldi et al. (2022) emphasize the need for standardized methodologies and consistent data reporting to fully integrate CE metrics into mainstream ESG frameworks. The absence of such frameworks limits the ability of investors to make fully informed decisions, potentially reinforcing the same market inefficiencies that ESG was intended to correct (Amin et al., 2024; Baldi and Pandimiglio, 2022). Moreover, the reliance on self-reported data remains a critical obstacle, as it introduces significant bias and reduces the reliability of sustainability claims (Barney, 1991; Chaudhuri et al., 2022). For instance, Chaudhuri et al. (2022) argue that without robust verification mechanisms, CE metrics risk being co-opted into the same credibility crisis that plagues conventional ESG assessments (Chaudhuri et al., 2022; Le et al., 2022).

Econometric analyses further revalidate these gaps. Khan (2022) conducted a meta-analysis demonstrating that firms adopting CE principles report significantly lower volatility in ESG performance, reflecting the stability and resilience associated with resource-efficient business models (Khan, 2022; Balluchi et al., 2020). Similarly, Kristoffersen et al. (2021) identified a direct correlation between circular practices and improved financial performance, highlighting the potential for CE metrics to reshape investment strategies (Kristoffersen et al., 2021; Ahmad et al., 2023). These findings are supported by empirical evidence from Amin et al. (2024), who demonstrated that CE practices not only reduce operational costs but also enhance long-term financial stability by mitigating resource dependency and promoting systemic resilience (Braun, 2019; Le et al., 2022).

The Material Circularity Indicator (MCI) is one such key metric that measures the extent to which a company’s products or processes retain the value of materials through reuse, recycling, and remanufacturing, rather than relying on virgin resources (Ellen MacArthur Foundation, 2021). Companies that integrate MCI into their operations show greater resource efficiency and reduced waste generation, making this metric a valuable tool for identifying greenwashing. For example, Aerts and Cormier (2009) found that firms incorporating MCI into their production processes reduced raw material costs by up to 30%, illustrating the economic and environmental benefits of circular strategies (Aerts and Cormier, 2009; Ahmad et al., 2023). Similarly, the Circular Material Use Rate (CMUR) measures the proportion of recycled or reused materials in a company’s total material input, offering a clear indication of resource circularity (Le et al., 2022; Fatimah et al., 2023). Companies with higher CMUR scores often show lower carbon footprints and reduced dependency on raw materials, which also enhances supply chain resilience by reducing exposure to volatile material markets (Baah et al., 2022; Carroll, 1979).

The Product Circularity Index (PCI) evaluates the circular potential of individual products by considering factors such as design for disassembly, material recovery, and end-of-life recycling (Fernando et al., 2022; Ahmad et al., 2023). This metric enables more precise differentiation between genuinely circular businesses and those engaging in superficial greenwashing, offering a granular view of a company’s sustainability performance (Cottafava et al., 2019; Daugaard and Ding, 2022). Additionally, the Lifecycle Carbon Intensity (LCI) metric measures the carbon emissions associated with a product’s entire lifecycle, from raw material extraction to disposal (Fatimah et al., 2023; De Freitas Netto et al., 2020). This metric is critical in identifying companies that have reduced their carbon footprint through closed-loop production and resource recovery (Kristoffersen et al., 2021; Cavicchi et al., 2022). For instance, Kristoffersen et al. (2021) found that firms employing CE practices reported up to 30% reductions in lifecycle carbon intensity, highlighting the substantial environmental benefits of these strategies (Table 1).

Table 1

Table 1. Strategic pathways for advancing circular economy metrics in ESG investing.

Econometric studies provide further evidence of the financial viability and risk-mitigation potential of CE metrics. Khan (2022) demonstrated that firms adopting CE principles experienced significantly lower volatility in ESG performance, suggesting that resource-efficient business models contribute to stability and resilience. Similarly, Kristoffersen et al. (2021) identified a direct link between circular practices and improved financial performance, suggesting that CE metrics could revolutionize investment strategies (Kristoffersen et al., 2021; Du et al., 2021). Moreover, Amin et al. (2024) found that CE practices reduce operational costs and enhance long-term financial stability by mitigating resource dependency and promoting resilience in business models (Amin et al., 2024; Dumrose et al., 2022; Munonye and Munonye, 2025).

Existing scholarly engagement has further reinforced the potential of CE metrics to mitigate the risk of greenwashing by promoting greater transparency and accountability in corporate reporting. Baah et al. (2022) found that companies using CE metrics were more likely to achieve long-term profitability and investor trust, as these metrics provide verifiable data that reduces opportunities for manipulation. This data-driven approach not only helps identify companies committed to sustainable practices but also offers investors an objective basis for assessing environmental risks, improving their ability to avoid exposure to greenwashed claims (Dvorský et al., 2023a; Fiandrino et al., 2022).

Consequently, this paper addresses a critical and timely research agenda: How can circular economy (CE) metrics redefine ESG impact assessment in ways that render greenwashing both technically infeasible and ethically indefensible? What conceptual and operational gaps persist in current ESG methodologies that inhibit their ability to measure circularity with empirical clarity? And how can financial instruments evolve to embed these new metrics in mainstream portfolio construction and regulatory policy not as symbolic add-ons but as mechanisms of material ecological accountability? These questions challenge the epistemological underpinnings of ESG reporting and the economic assumptions that privilege disclosure over transformation. They also confront the pervasive issue of greenwashing, which thrives on the opacity and inconsistency of ESG indicators. Far from being a peripheral concern, greenwashing constitutes a systemic dysfunction: a performative illusion in which sustainability is curated as brand equity rather than embedded as material practice.

In response this study proposes a recalibration of ESG investing through the lens of circularity not as a supplementary dimension, but as a foundational grammar through which sustainability must be redefined. Circular economy metrics, grounded in material flows, product lifecycles, regenerative capacity, and resource recirculation, offer an empirically verifiable basis to distinguish authentic ecological value creation from symbolic compliance. Where ESG frameworks tend to favor intention-based disclosures, CE metrics compel outcome-based accountability. They resist abstraction by aligning financial signals with thermodynamic and systemic constraints, offering investors tools to trace sustainability in the real economy. As such, CE metrics help reconcile financial rationality with environmental integrity, transforming ESG from a reputational mechanism into a material driver of capital reallocation (Munonye, 2025a; Walker et al., 2021; Ahmad et al., 2023; Amin et al., 2024).

Ultimately, the emergence of circular economy metrics signals more than methodological advances. It reflects a philosophical evolution in the architecture of economic thought. Through embedding principles of regeneration, restoration, and planetary limits into the DNA of investment decision-making, CE metrics not only expose the epistemic frailties of existing ESG regimes but also offer a blueprint for reconfiguring finance itself as a system in service to life, not extraction. This paper therefore does not simply analyze the integration of CE into ESG. It performs it by reframing sustainability not as a secondary consideration but as the core grammar through which economic meaning is written, capital is valued, and futures are built.

2 Methodology

This study adopts a narrative literature review methodology, chosen for its capacity to generate conceptual depth and integrative synthesis in complex, interdisciplinary research contexts (Ahmad, 2025). In contrast to systematic reviews that prioritize replicability, exhaustiveness, and quantitative aggregation, the narrative approach enables critical engagement with thematic patterns, conceptual tensions, and emergent paradigms particularly salient in the dynamic intersection of (CE) metrics and (ESG) investing. As these fields evolve under growing scrutiny over sustainability claims, a narrative method provides the flexibility to trace intellectual developments, reveal normative contestations, and articulate theoretical linkages that might otherwise remain obscured (Greenhalgh et al., 2018; Ferrari, 2015).

The methodology is grounded in an interpretivist epistemology, which emphasizes meaning making as a reflexive and iterative process shaped by the literature, empirical cases, and the analytical lens of the researcher. This orientation enables transdisciplinary synthesis by drawing from environmental economics, industrial ecology, corporate sustainability, critical finance, and accounting. It allows for the interrogation of how CE metrics, as forms of quantification and governance, may both challenge and reproduce dominant ESG logics. Through this lens, the paper examines whether CE-based indicators genuinely promote transparency and material circularity or simply offer a new register for performative compliance.

The corpus of literature reviewed spans from 2007 to 2025, reflecting a critical period in which ESG investing has expanded in institutional and regulatory prominence, while circular economy thinking has moved from industrial symbiosis discourse into mainstream financial reporting. Peer-reviewed academic sources were prioritized, especially those published in high-impact journals across sustainability studies, environmental policy, business ethics, and financial regulation. The review also included publications from major sustainability research institutes and international governance bodies, provided they were grounded in peer-reviewed analysis or technical validation. Keyword searches were conducted across academic databases such as Scopus, Web of Science, and Google Scholar using terms including “circular economy metrics,” “ESG investing,” “greenwashing,” “non-financial disclosures,” “impact investing,” “circular finance,” and “sustainability reporting.” An initial set of over 170 documents was assembled, from which approximately 130 were retained based on analytical richness, citation relevance, and direct engagement with the theoretical and empirical challenges at the CE–ESG nexus.

The analysis was structured around four key thematic axes that emerged inductively from the literature: (1) metric standardization and transparency, (2) digital technologies for ESG traceability, (3) institutional entrepreneurship and regulatory dynamics, and (4) critical case-based insights into the application and misapplication of CE frameworks in ESG contexts. A case-oriented narrative integration strategy was employed to embed empirical complexity into the review, reflecting the methodological rigor of narrative synthesis, which prioritizes contextual interpretation and theoretical connectivity across diverse studies. As Allen (2017) notes, such approaches enable the integration of heterogeneous evidence into coherent analytical narratives, while Ahmad (2025) emphasizes their value in capturing depth and nuance often lost in purely systematic aggregations. Leading firms such as IKEA, Apple, and Unilever were analyzed for their documented efforts to synchronize CE metrics with ESG performance reporting. These were contrasted with industries particularly in fashion, mining, and digital manufacturing where claims of circularity have often been scrutinized as forms of greenwashing or symbolic compliance. This contrastive framing revealed key tensions between declared sustainability intentions and material practices, as well as the structural opacity within current non-financial reporting regimes.

To further enhance analytical depth, conceptual triangulation was applied, following methodological guidance from Baumeister and Leary (1997) and Snyder (2019). Circular economy indicators such as material flow analysis, resource retention ratios, lifecycle value accounting, and circular value retention metrics were assessed with existing ESG evaluation frameworks. This process illuminated significant gaps in prevailing ESG methodologies particularly their limited capacity to track material circularity and end-of-life accountability and demonstrated how CE metrics could offer a more rigorous, system-wide approach to sustainability evaluation.

This methodology ultimately supports a reflexive and critical engagement with the literature, offering a robust analytical basis for rethinking the epistemic foundations of ESG investing (see Figure 1). Rather than treating CE metrics as technical supplements to existing disclosure practices, the narrative approach surfaces their potential to recalibrate how sustainability is defined, measured, and enacted within financial systems. In doing so, it contributes to a broader conversation about transforming ESG from a performative, compliance-driven exercise into a domain of authentic, circular value creation.

Figure 1

Figure 1. Conceptual framework of the methodology applied for the study (Source: Developed by the Authors).

2.1 Section snippet

Section 3 examines how circular economy metrics can expose and mitigate greenwashing, arguing that measurable indicators of material recovery and value retention strengthen ESG credibility. Section 4 builds on this by exploring how institutional entrepreneurship and policy innovation catalyze financial ecosystems that embed circularity principles within governance and regulation. Section 5 links institutions and digital systems, showing how AI and investor attention translate regulatory intent into efficient, measurable green innovation and financially material ESG performance. Section 6 advances discussion through the lens of digital transformation, showing how AI, IoT, and blockchain enhance data integrity and traceability in ESG reporting. Section 7 grounds these frameworks in practice through case studies of leading firms, revealing both the successes and limitations of metric-based circularity adoption. Section 8 synthesizes these insights into a vision for circular investment portfolios, proposing financial models that reward regenerative value creation. Finally, Section 9 concludes with strategic recommendations, outlining pathways for policymakers, investors, and corporations to align financial performance with circular sustainability outcomes.

3 Addressing greenwashing through circular economy metrics

Greenwashing, as a systemic pathology within the ESG investing paradigm, persists not merely as a consequence of isolated corporate misrepresentation, but as a structural outcome of epistemological ambiguity, metric inconsistency, and interpretive looseness embedded in prevailing sustainability reporting frameworks (Ghitti et al., 2024; Bodellini, 2023; Bernini and La Rosa, 2024). Within this interpretive vacuum, firms are able to exploit the semiotic elasticity of ESG categories, leveraging investor goodwill and disclosure-oriented evaluation mechanisms to amplify environmental claims that are weakly substantiated or materially misleading (Fatimah et al., 2023; Baah et al., 2022; Ahmad et al., 2023). The resulting inability to systematically distinguish between performative sustainability signaling and substantive environmental performance undermines the epistemic credibility of ESG markets, distorts capital allocation, and generates persistent mispricing, asymmetric risk exposure, and declining institutional trust (Bodellini, 2023; Ghitti et al., 2024; Baah et al., 2022).

Circular economy (CE) metrics intervene in this structural failure by operationalizing sustainability through measurable, verifiable, and temporally consistent indicators that substantially reduce narrative discretion and expose the material dimensions of corporate environmental performance (Kristoffersen et al., 2021; Fatimah et al., 2023; Munonye, 2025a). Unlike conventional ESG disclosures, CE metrics are grounded in physical resource flows and lifecycle impacts, enabling the empirical assessment of regenerative performance rather than symbolic alignment. Core indicators include material recovery rates, reaching 60–85% among advanced circular firms resource productivity per unit of GDP, which has improved by approximately 30% in high-performing circular economies, and lifecycle carbon intensity reductions of up to 25% in CE-aligned operations (Ellen MacArthur Foundation, 2021; Baah et al., 2022; Ahmad et al., 2023). Complementary measures such as waste diversion ratios exceeding 70% in circular manufacturing systems and the Circular Material Use Rate (CMUR), now formally embedded across all 27 EU member states, further enhance comparability, auditability, and resistance to greenwashing by anchoring ESG claims in quantifiable material outcomes rather than discretionary narrative constructs (Ellen MacArthur Foundation, 2021; Ahmad et al., 2023).

For instance, Renault’s CE roadmap includes a quantifiable goal of 60% remanufactured automotive components by 2025 benchmarked against ISO 8887 standards. Similarly, Philips’ CE scorecard tracks product-as-a-service transitions, revealing a 20% increase in circular revenues between 2020 and 2023 (Fatimah et al., 2023; Iliev et al., 2023; Chaudhuri et al., 2022). These initiatives substantiate sustainability claims with clear numerical targets, third-party verification, and year-over-year tracking addressing greenwashing not through rhetoric but through auditable performance.

The integration of CE metrics into ESG frameworks transforms sustainability from a rhetorical category into an operational domain by enabling real-time tracking, standardized lifecycle accounting, and cross-sector comparability (as shown in Figure 1). This shift is evident in the Material Circularity Indicator (MCI) and Product Circularity Index (PCI), both of which are used by global firms to benchmark product-level sustainability. IKEA, for example, has achieved a 57% circular product index rating across its home furnishing lines and committed to 100% circular design by 2030 (Ellen MacArthur Foundation, 2021; Chaudhuri et al., 2022; Bernini and La Rosa, 2024).

Econometric analysis reveals strong correlations between CE adoption and ESG performance. Khan (2022) found that firms integrating CE practices experience 18–30% lower volatility in ESG ratings. Kristoffersen et al. (2021) report that CE-aligned companies outperform linear peers by up to 15% in profitability and 20% in resource efficiency. These metrics shift ESG from a qualitative disclosure model to a quantitatively grounded forecasting system, enhancing investor confidence and reducing exposure to greenwashed assets (Amin et al., 2024; Cavicchi et al., 2022).

In the apparel sector, Patagonia’s Worn Wear initiative offers a compelling example of how circular economy (CE) metrics can produce actionable insights and outcomes when embedded into corporate sustainability strategies. By systematically tracking reuse and repair metrics, Patagonia has reported a 35% reduction in product end-of-life waste and a 20% increase in customer lifecycle engagement since integrating CE metrics into its reporting architecture (Chaudhuri et al., 2022; Kristoffersen et al., 2021; Ahmad et al., 2023). These achievements are not incidental but stem from Patagonia’s deliberate design of business processes around circularity, including resale platforms, garment repair hubs, and consumer education on material longevity. Crucially, the transparency in metric disclosure allows investors and stakeholders to benchmark performance against environmental outcomes rather than marketing claims.

In sharp contrast, H&M’s much-publicized Conscious Collection underscores the dangers of weak metricization and performative sustainability. Investigations into the collection revealed that nearly 60% of advertised sustainable garments had higher synthetic content than baseline offerings, despite being marketed under green narratives (Earth.Org, 2023; Fatimah et al., 2023). This case demonstrates how, in the absence of standardized CE metrics, firms can exploit narrative ambiguity to inflate sustainability credentials a practice increasingly critiqued as greenwashing. The juxtaposition between Patagonia and H&M highlights the centrality of robust, auditable, and comparable metrics in validating sustainability claims and in preventing reputational ESG from substituting for actual ecological performance.

Additionally, the deployment of Digital Product Passports (DPP) offers a transformative pathway for embedding lifecycle transparency into production and consumption systems. Integral to the EU’s Ecodesign for Sustainable Products Regulation, DPPs standardize traceable data on lifecycle carbon footprints, recycled content, and reuse frequency (EP, 2021; EC, 2019; Bodellini, 2023). Companies like Miele and Bosch, early adopters of this system, report a 28% improvement in product traceability compliance and a 22% reduction in supply chain opacity, demonstrating how digital infrastructure can operationalize circular metrics across complex value chains (Bernini and La Rosa, 2024). By allowing end-users and regulators to access real-time product histories, DPPs shift sustainability from intention to verification, from policy ambition to measurable practice.

These developments reflect a broader alignment between CE metrics and regulatory frameworks. Instruments such as the EU Taxonomy for Sustainable Activities and the Sustainable Finance Disclosure Regulation (SFDR) are gradually embedding CE-specific indicators into legal compliance regimes. For instance, firms are now required to demonstrate a minimum 20% improvement in resource use per revenue unit and provide mandatory reporting on waste-to-product conversion rates (Jakubelskas and Skvarciany, 2023; Amin et al., 2024). This legislative shift transforms compliance from being narrative-bound to metric-bound, thereby constraining firms’ ability to rely solely on reputational ESG and demanding verifiable impact through quantifiable data.

Emerging technologies further enable the infrastructure necessary for metric operationalization at scale. Circularise’s blockchain-based traceability platform currently verifies over 50 million product flows, offering immutable data on material composition, origin, and end-of-life options (Cheng et al., 2023). Similarly, Everledger’s AI-powered ESG auditing tools have shown a 35% reduction in sustainability reporting discrepancies during pilot programs (Xue et al., 2021; Ahmad et al., 2023). These technological interventions not only increase transparency but also allow for dynamic, third-party validation of circularity metrics, providing investors with credible insights into portfolio-level CE alignment. In effect, they construct a new layer of epistemic accountability in sustainable finance.

Standardization is critical for achieving metric comparability and legitimacy across geographies and sectors. The ISO 59020 standard, set for adoption by over 43 countries by 2025, offers a harmonized methodology for measuring circular performance across product systems (Baah et al., 2022; Fatimah et al., 2023). By codifying indicators such as material circularity, durability, reparability, and design-for-disassembly, ISO 59020 eliminates discretionary metric definitions that have historically undermined the integrity of sustainability reporting. The emergence of such standards marks a crucial pivot from firm-defined metrics to internationally agreed benchmarks, thereby leveling the playing field for investors and firms alike.

Simultaneously, these developments are catalyzing innovations in sustainable investing. Positive selection strategies, now gaining traction in circular finance, deploy CE metrics as a basis for asset inclusion. For instance, BlackRock’s Circular Economy Fund and BNP Paribas’ Circular ETF integrate criteria such as Circular Material Use Rate (CMUR) and waste-reduction ratios into their investment theses. Notably, these funds have achieved a 17% higher average ESG score than their conventional counterparts over a three-year horizon (Kristoffersen et al., 2021; Cavicchi et al., 2022; Amin et al., 2024). This evidences that financial performance and circularity are not mutually exclusive but increasingly interdependent.

Moreover, CE metrics are reconfiguring ESG investing from a realm of reputational theatre into a science of regenerative value creation. Through embedding principles such as durability, dematerialization, and closed-loop systems into financial disclosures, CE metrics create architectures of accountability that are both auditable and economically rational (Gray and Bebbington, 2000; Adams and Larrinaga-González, 2007; Galli et al., 2023). They move sustainability from the periphery of investor concern to the core of valuation practices, enabling more rigorous, data-driven investment decisions. In doing so, they expose the epistemological vacuity of ESG frameworks that rely on self-reported, unstandardized metrics and elevate the discourse toward systemic transformation.

Therefore, the incorporation of operationalized CE metrics constitutes both a paradigmatic and infrastructural evolution in sustainable finance thereby reducing greenwashing practices (as shown in Figure 2). These metrics offer a bridge between policy aspirations and market accountability, transforming transparency from a voluntary principle to a fiduciary obligation (Munonye, 2025a). As firms, regulators, and investors co-produce the metrics of circularity, the financial system is gradually reoriented toward regenerative value, systemic resilience, and long-term planetary stewardship (Fatimah et al., 2023; Bernini and La Rosa, 2024; Kristoffersen et al., 2021). This reconfiguration does not merely improve upon ESG investing it transcends it, providing the epistemic, operational, and ethical scaffolding for a post-extractive economic paradigm.

Figure 2

Figure 2. Combating greenwashing through circular economy metrics. This figure demonstrates how circular economy (CE) metrics and indicators counter greenwashing by replacing ambiguous ESG claims with measurable, verified performance indicators. It highlights the integration of these metrics into regulatory frameworks, fostering transparent, accountable, and regenerative investment practices that shift sustainability toward a data-driven financial paradigm (Source: Developed by the Authors).

4 Institutional entrepreneurship and policy catalysts for circular finance

In an era defined by planetary boundaries, biospheric stress, and cascading ecological tipping points, the future of sustainable finance increasingly hinges on a shift from extractive logic to regenerative systems a transformation driven by institutional entrepreneurship and policy catalysts capable of embedding circular economy (CE) metrics into the very grammar of ESG investing (Landau et al., 2020; Krummaker, 2019; Ahmad et al., 2023; Amin et al., 2024). Institutional entrepreneurs, whether visionary firms, regulatory vanguards, civil society networks, or transnational coalitions do not merely adjust existing systems but confront structural inertia and epistemological closure by challenging the assumptions underpinning value, materiality, and fiduciary responsibility (Liu et al., 2024; Marrucci et al., 2022a; Alonso-Almeida et al., 2021; Patil et al., 2021). In doing so, they drive a paradigmatic transition wherein capital flows are no longer rewarded for surface-level ESG compliance, but for quantifiable circular outcomes such as resource productivity, lifecycle decoupling, and value retention across extended product and infrastructure lifespans (Fatimah et al., 2023; Bernini and La Rosa, 2024; Khajuria et al., 2022; EC, 2019).

This redirection is neither spontaneous nor market-driven alone it is scaffolded by the deliberate alignment of CE indicators like the Circularity Gap Metric (Ellen MacArthur Foundation, 2021), GDP-per-material input ratios, and carbon-adjusted return on investment metrics, which together measure not just profitability but the regenerative potential of economic activity (Mehrotra and Jaladi, 2022; Nguyen et al., 2020; Rinaldi et al., 2022). Leading firms such as IKEA, Philips, and Renault exemplify this realignment, integrating product modularity, disassembly scores, and remanufacturing benchmarks into ESG reporting mechanisms redefining competitiveness through the lens of closed-loop value (Chaudhuri et al., 2022; Ramakrishna and Ramasubramanian, 2024; Ahmad et al., 2023; Atstāja et al., 2022). Renault’s ReFactory initiative, for example, operationalizes ISO 8887 standards to achieve a 60% increase in circular components by 2025, providing a blueprint for CE disclosures that go beyond storytelling into verifiable performance (Fatimah et al., 2023; Cottafava et al., 2019; Iliev et al., 2023; Walker et al., 2021).

Yet these firm-level initiatives are inseparable from the policy architectures that institutionalize circularity within finance. The European Circular Economy Action Plan and the European Green Deal serve not just as high-level policy roadmaps but as meta-regulatory frameworks that embed CE logic into taxonomies, bond eligibility, and sustainability-linked disclosures (EP, 2021; EC, 2019; Babkin et al., 2023; Jakubelskas and Skvarciany, 2023). These frameworks hardwire CE into capital allocation via instruments such as Extended Producer Responsibility (EPR) and Digital Product Passports (DPP), which render material flows traceable, audit-ready, and accountable to both regulators and investors (Dumrose et al., 2022; Rinaldi et al., 2022; Ahmad et al., 2023; Munonye, 2025a). For example, the EU’s DPP initiative set for phased deployment starting in 2026 enables asset managers to evaluate a firm’s resource recirculation rate, embedded carbon intensity, and end-of-life recoverability as part of sustainable finance assessments (Bernini and La Rosa, 2024; Bodellini, 2023; Baldi and Pandimiglio, 2022).

These policy tools function not just as compliance mechanisms but as structural re-incentivizers internalizing previously unpriced externalities and rendering linear production financially obsolete. EPR laws in Germany, through the Verpackungsgesetz, legally mandate corporate accountability for post-consumer waste streams, prompting investments in take-back infrastructure, eco-design, and modularity (Amin et al., 2024; Ghitti et al., 2024; Ahmad et al., 2023; Zheng L. et al., 2023). Simultaneously, performance-linked sovereign debt such as France’s Green OAT bonds or the European Investment Bank’s Circular Bioeconomy Investment Platform align capital issuance with KPIs like CO₂ offset per euro and waste diversion per annum redefining sovereign creditworthiness through circular metrics (Reboredo and Ugolini, 2020; Nguyen et al., 2020; Jakubelskas and Skvarciany, 2023; Le et al., 2020).

Institutional entrepreneurship is also pivotal in confronting a central paradox within ESG investing: the divergence between rating proliferation and analytical precision. The ESG field is plagued by fragmented metrics, inconsistent methodologies, and opacity in scoring conditions that institutional entrepreneurs address by rooting ESG criteria in CE principles that are inherently measurable, verifiable, and lifecycle-based (Lyon and Montgomery, 2015; Sneideriene and Legenzova, 2025; Balluchi et al., 2020; Fiaschi et al., 2020). By advancing indicators such as product lifespan, repair frequency, virgin material input share, and secondary raw material usage, firms and rating agencies can move from symbolic metrics to evidence-based differentiation (Babkin et al., 2023; Ahmad et al., 2023; Ramakrishna and Ramasubramanian, 2024; Zioło et al., 2024).

Philips, for instance, developed a CE Scorecard used internally to benchmark business units based on product circularity metrics, linking circularity to profitability and impact-weighted financial performance thereby rendering CE an asset management variable rather than corporate social responsibility afterthought (Kristoffersen et al., 2021; Chaudhuri et al., 2022; Alonso-Almeida et al., 2021; Fatimah et al., 2023). The growing use of such metrics in executive compensation, investor reporting, and capital expenditure models signifies the institutionalization of CE logics into core financial analytics.

This catalytic role of institutional entrepreneurs extends beyond firm boundaries, encompassing multi-level governance systems in which supranational institutions, national governments, and decentralized coalitions co-create the structural scaffolding for circular finance ecosystems (Munonye, 2025a; Babkin et al., 2023; Fatimah et al., 2023; Amin et al., 2024). In this context, national CE strategies such as Finland’s Roadmap to Circularity, the Netherlands’ CE Action Plan, and China’s Circular Economy Promotion Law do not merely represent state planning documents, but reconstitute the relationship between public procurement, industrial innovation, and capital flow (Khajuria et al., 2022; Iliev et al., 2023; Jakubelskas and Skvarciany, 2023; Ramakrishna and Ramasubramanian, 2024). For instance, Finland’s directive requiring all publicly funded construction projects to meet CE criteria by 2035 not only mobilizes over €7 billion in sustainable infrastructure investment but also signals to investors that material reuse, disassembly design, and lifecycle carbon metrics are no longer optional thereby reconfiguring market expectations and capital pricing models (Wagner et al., 2020; Uyar et al., 2020; Zara, 2020).

However, circular finance are financial mechanisms that channel capital toward regenerative, resource-efficient, and closed-loop systems can only scale beyond national exemplars if institutional entrepreneurship evolves from fragmented leadership to orchestrated governance. This entails the institutionalization of cross-sectoral infrastructures platforms, standardization bodies, and innovation clusters that coordinate capital, knowledge, and compliance across entire value chains (Signori et al., 2021; Walker et al., 2021; Velte, 2023; Patil et al., 2021). Initiatives such as the Ellen MacArthur Foundation’s CE100 network, the World Economic Forum’s Scale360° platform, and UNEP’s Sustainable Finance Hub demonstrate how institutional entrepreneurs aggregate regulatory legitimacy, narrative coherence, and investor trust through collaborative problem-solving and systemic experimentation (Ellen MacArthur Foundation, 2021; Fatimah et al., 2023; Bernini and La Rosa, 2024; Renneboog et al., 2008).

In this sense, institutional entrepreneurs engage in both norm construction and norm disruption. They do not merely align with prevailing ESG expectations they redefine the contours of materiality, reframe fiduciary duty through the lens of intergenerational equity, and challenge orthodoxies that privilege short-term shareholder returns over long-term planetary stability (Carroll, 1979; Burritt and Schaltegger, 2010; Gray and Bebbington, 2000; Galli et al., 2023; Adams and Larrinaga-González, 2007). This process is dialectical: while one hand works within existing disclosure regimes, the other drafts post-linear standards embedding principles such as decoupling, regeneration, and distributive resilience directly into capital modeling frameworks and investment committee mandates (Khan, 2022; Huang, 2021; Munonye, 2025b; Walker et al., 2021).

Enabling technologies particularly blockchain, lifecycle-based AI, and digital product passports play an indispensable role in this transformation (Khajuria et al., 2022; Munonye and Ajonye, 2024a). They provide the material conditions under which CE performance can be verified, scaled, and priced, translating sustainability from a narrative claim into an econometric parameter (Cheng et al., 2023; Xue et al., 2021; Hassani and Bahini, 2024; García-Muiña et al., 2021; Zheng L. et al., 2023). Startups like Circularise and Everledger are deploying cryptographically secure systems that trace material provenance, reuse frequency, and carbon intensity across multiple production cycles establishing a radical transparency infrastructure that investors can use to evaluate CE performance at the product level (Heras-Saizarbitoria et al., 2022; Goldreyer and Diltz, 1999). Moreover, these traceability systems do not operate in a regulatory vacuum. The EU’s Ecodesign for Sustainable Products Regulation and the Sustainable Finance Disclosure Regulation (SFDR) are rapidly institutionalizing data formats and assurance protocols that integrate CE metrics into disclosure mandates, investor fact sheets, and fund prospectuses (Gray and Bebbington, 2000; Fonseca, 2010). These policy infrastructures create mandatory gateways for CE metrics to enter the financial mainstream, ensuring not only compliance but alignment between ecological impact and capital flow.

Consequently, Institutional entrepreneurship plays a critical role in de-risking circular innovation, particularly through the orchestration of demand-side strategies that alter market structures and expectations (see Figure 3). Governments, development banks, and multilateral institutions are increasingly leveraging instruments such as green public procurement (GPP), fiscal incentives, and tax harmonization to generate market-pull dynamics for circular economy (CE) integration. These mechanisms reduce perceived investment risks while enhancing the financial attractiveness of circular business models, thereby mitigating the first-mover disadvantage often faced by sustainability pioneers (Khajuria et al., 2022; Cavicchi et al., 2022; Atstāja et al., 2022).

Figure 3

Figure 3. Summarizes policy instruments and institutional support for circular finance. This figure illustrates the systemic interaction between institutional entrepreneurship and policy catalysts within circular finance. It emphasizes the roles of firms, regulatory frameworks, and financial instruments in integrating circular economy metrics into ESG investing, thereby promoting sustainable capital flows (Source: Developed by the Authors).

A compelling illustration of this institutional catalytic role is the Netherlands’ Circular Procurement Green Deal, which mobilizes over €100 billion annually in public contracts toward goods and services that comply with stringent CE criteria. These include minimum recycled content thresholds, lifetime extension guarantees, reparability indices, and modular design principles (Alonso-Almeida et al., 2021; Fatimah and Biswas, 2017; Cheng et al., 2023). Such targeted interventions not only stimulate industrial adaptation but also institutionalize circularity as a standard of public value creation.

These policy levers are further underpinned by macroprudential imperatives that are reconfiguring the financial risk landscape (Galaz et al., 2018; Baldi and Pandimiglio, 2022). As climate transition risk becomes internalized within global capital markets, assets entrenched in linear production models such as fossil-fuel infrastructure, fast fashion, or disposable packaging supply chains are increasingly subject to rapid devaluation and obsolescence, a phenomenon widely recognized as stranded asset risk (Nguyen et al., 2020; Munonye and Munonye, 2025).

In contrast, according to Kristoffersen et al. (2021) firms embedded in circular economic logic demonstrate superior adaptability and systemic resilience, particularly when assessed using multidimensional performance metrics. Key indicators such as resource circularity, emissions per use cycle, and product durability position CE-aligned firms as robust candidates for long-duration ESG portfolios (Iliev et al., 2023; Kristoffersen et al., 2021; Delmas and Burbano, 2011). These companies not only meet emerging regulatory thresholds but also embody the principles of ecological embeddedness and long-term value retention, which are foundational to sustainable finance paradigms.

Finally, the epistemological shift demanded by circular finance goes beyond tools and metrics it reimagines the ontological premises of economic value. Institutional entrepreneurs must articulate new imaginaries of prosperity where capital is not maximized through throughput but conserved through renewal; where growth is not indexed by scale but by the system’s capacity to regenerate its inputs (Adams and Larrinaga-González, 2007; Galli et al., 2023; Yamoah et al., 2022). Circular finance, in this light, ceases to be a niche extension of ESG and becomes its future: a radical, coherent, and actionable reordering of how finance intersects with ecology, ethics, and intergenerational responsibility (Bernini and La Rosa, 2024; Ahmad et al., 2023; Patil et al., 2021).

5 Artificial intelligence, investor attention, and corporate green development: an innovation efficiency perspective

Within the broader ambition of moving beyond greenwashing in ESG investing, the interaction between artificial intelligence (AI), investor attention, and corporate green development represents a decisive analytical frontier. Rather than treating sustainability as a symbolic disclosure exercise, recent scholarship increasingly conceptualizes green development as an efficiency-driven innovation process, where digital intelligence and capital market scrutiny jointly discipline firms toward substantive environmental value creation.

AI fundamentally reshapes the green innovation process by enhancing firms’ ability to identify, optimize, and scale environmentally efficient technologies. At the micro level, AI reduces information asymmetries within firms by improving process monitoring, resource allocation, and risk anticipation, thereby lowering the uncertainty traditionally associated with green R&D investments (Li et al., 2024; De Vries et al., 2015). This internal efficiency channel is complemented by an external performance effect: AI-enabled green innovation mitigates operating risks and stabilizes cash flows, translating environmental investment into superior financial outcomes rather than cost burdens (Ai et al., 2024; Hair et al., 2014). From an ESG-investing perspective, this establishes AI as a structural enabler of credible sustainability signals, not merely a productivity tool.

However, AI’s transformative potential is magnified when intersecting with investor attention mechanisms. Investor attention operates as an informational filter that reallocates capital toward firms capable of demonstrating measurable green innovation efficiency. Bao et al. (2025) empirically demonstrates that heightened investor attention strengthens the relationship between ESG strength and green innovation efficiency, particularly when innovation outcomes are evaluated through network-based efficiency metrics rather than aggregate scores. This finding is critical: it implies that attentive capital markets reward how efficiently firms convert ESG inputs into environmental outputs, rather than the volume of disclosures themselves directly countering greenwashing incentives.

Institutional investors further reinforce this discipline mechanism through preference alignment and coordinated monitoring. Wu et al. (2023) show that clustered institutional ownership with shared ESG preferences significantly accelerates low-carbon innovation, especially in governance-constrained contexts such as family firms. In this sense, investor attention becomes an active governance force that complements AI-driven internal capabilities, jointly shaping corporate green development trajectories.

At the macro-financial level, AI-enhanced green innovation also alters the risk–return profile of ESG assets. By stabilizing earnings under energy and market uncertainty, firms with strong AI-enabled green capabilities contribute to the resilience and predictability of ESG portfolios (Yang et al., 2024). Liu et al. (2025) synthesize this dynamic by framing AI as a catalyst that converts environmental ambition into scalable green development outcomes.

Collectively, these insights suggest that ESG investing can transcend greenwashing only by prioritizing innovation efficiency metrics at the intersection of AI capability and investor attention where sustainability is verified through performance, not promise.

6 Digital transformation and the future of ESG metrics

The digital revolution has reached a philosophical inflection point in sustainability, demanding more than tokenistic disclosures or fragmented metrics (Milne, 1996; Torelli, 2023). Instead, it calls for a radical reimagination of what we measure, why we measure it, and how we link (ESG) data to real-world impacts (Chaudhuri et al., 2022; Du et al., 2010). Central to this transformation is the seamless integration of artificial intelligence (AI), the Internet of Things (IoT), and blockchain technologies into the ESG architecture reshaping sustainability metrics from backward-looking compliance tools to forward-looking instruments of systemic transition (Kristoffersen et al., 2021; Munonye and Ajonye, 2024b; Liu et al., 2024; Babkin et al., 2023).

In the age of ecological limits and investor skepticism, ESG investing demands not only visibility but verifiability. Greenwashing has proliferated precisely because traditional metrics narrative-heavy, data-light fail to link operational decisions with circular outcomes in real time (Bernini and La Rosa, 2024; Ghitti et al., 2024; Bodellini, 2023; Sneideriene and Legenzova, 2025; Liu et al., 2024). The triad of AI, IoT, and blockchain disrupts this opacity by enabling continuous tracking of material flows, quantifying carbon handprints (the net positive impact of an activity), and generating lifecycle assessments that are algorithmically auditable, not merely asserted (Xue et al., 2021; Aerts and Cormier, 2009; Jakubelskas and Skvarciany, 2023; Zara, 2020).

The application of IoT in ESG metrics has proven transformative, particularly in capturing granular data on energy use, material inputs, and waste recovery in manufacturing and logistics. For example, in the e-waste recycling sector, embedded IoT sensors within electronics allow firms to monitor wear, usage cycles, and component health, feeding into digital twins that enable predictive maintenance and end-of-life material recovery (Kristoffersen et al., 2021; García-Muiña et al., 2021; Rinaldi et al., 2022; Amin et al., 2024; Xue et al., 2021). This has made it possible to track resource recovery rates in real-time, a metric that once relied on retrospective audits or supplier declarations. In South Korea, LG Electronics has implemented a blockchain-IoT hybrid platform to trace appliance components from manufacture to recycling, achieving verified resource recovery rates exceeding 85% a benchmark far surpassing EU Directive thresholds (EP, 2015).

Blockchain, in turn, provides immutable records of these flows, enabling investors to verify not only that recycling occurred but where, how, and to what end. Smart contracts can automate compliance with circular procurement clauses, for instance by releasing payment only when recycled content meets thresholds or when materials are verified as closed loop (Babkin et al., 2023; Burritt and Schaltegger, 2010; Ahmad et al., 2023; Bernini and La Rosa, 2024). This technological coupling offers more than transparency it constitutes a reengineering of ESG accountability, where firms are incentivized to internalize circularity as a performance variable, not a reputational afterthought (Jamali and Karam, 2018; Li, 2023).

While carbon footprints emphasize harm minimization, carbon handprints reflect a paradigm shift: quantifying the net benefit a process or product delivers to society and the biosphere (Peter et al., 2015; Zafar et al., 2022). AI enables this recalibration by analyzing vast, multidimensional datasets to assess how a company’s actions such as product redesigns or supply chain shiftsgenerate comparative reductions in emissions, water use, or toxicity relative to baseline scenarios (Kristoffersen et al., 2021; Cavicchi et al., 2022; Xue et al., 2021; Amin et al., 2024; DeMiguel et al., 2009). For example, machine learning models have been used in the textile sector to predict lifecycle emissions reductions from fiber reuse, estimating handprints in kilograms of CO₂ equivalent avoided per ton of reclaimed material (Fatimah et al., 2023; García-Muiña et al., 2021; Galli et al., 2023; Atstāja et al., 2022; Rinaldi et al., 2022).

Through shifting the analytical gaze from punishment to potential, carbon handprint metrics enabled by AI empower ESG investors to reward positive externalities, rather than merely screen out negative ones. This opens the door to incentive models such as performance-linked green bonds, where interest rates decrease in proportion to verified handprint growth (Reboredo and Ugolini, 2020; Gutierrez et al., 2022).

Traditional ESG scores have often been dismissed as opaque, inconsistent, or even misleading (Sneideriene and Legenzova, 2025; DeMiguel et al., 2009; Albitar et al., 2020; Lin et al., 2023; Bodellini, 2023). The application of AI to construct real-time circularity indices offers a pathway beyond these limitations. However, through mining structured and unstructured data ranging from LCA databases to satellite imagery AI can assess not only whether a firm discloses sustainability efforts but whether its operations actually align with CE principles in practice (Kristoffersen et al., 2021; Cavicchi et al., 2022; Fatimah et al., 2023; Ahmad et al., 2023; Liu et al., 2024). AI-generated indices such as the Circularity Performance Score (CPS) combine metrics like input recirculation rate, virgin material displacement, and post-consumer recovery ratios into a composite score dynamically updated with real-world data (Li, 2023; Liu and Li, 2024).

This continuous performance model, unlike static ESG ratings, is responsive to changing behaviors, product recalls, supply chain disruptions, or regulatory violations. For example, a firm may initially receive a high ESG score due to its sustainability commitments, but a decline in its circularity metrics detected through IoT sensors and flagged by AI automatically lower its CPS, alerting investors to deteriorating material efficiency (Galaz et al., 2018; García-Sánchez et al., 2022).

Perhaps the most revolutionary dimension of AI is not descriptive but prescriptive. Through reinforcement learning algorithms, companies and investors can model future scenarios, estimating the financial and ecological consequences of various circular strategies (Ahmad et al., 2023; Xue et al., 2021; Le et al., 2020; Liu et al., 2024; Babkin et al., 2023). For instance, AI tools developed by Finnish circular economy platforms allow companies to simulate the cost savings and emissions reductions from material substitution, reuse schemes, or reverse logistics innovations. These simulations are increasingly used by institutional investors to assess the robustness of ESG portfolios under climate transition scenarios, integrating CE metrics such as durability-adjusted asset value or lifecycle-adjusted ROI (Ha et al., 2022; Ghitti et al., 2024).

Prescriptive analytics also support capital allocation by identifying underfunded innovation areas with outsized sustainability impacts such as food upcycling, regenerative packaging, or e-mobility battery reuse networks (Lu et al., 2022; Morea et al., 2022). In this way, AI not only tracks circularity but strategically channels financial flows toward its expansion.

Specifically, Digital product passports (DPPs), as mandated under the European Commission’s Ecodesign for Sustainable Products Regulation, are a linchpin in connecting ESG investing with verifiable circularity, serving not merely as compliance tools but as algorithm-readable repositories of a product’s entire lifecycle data, including material origin, recyclability scores, embedded carbon, and reuse cycles (Rinaldi et al., 2022; Babkin et al., 2023; EP, 2021; Ahmad et al., 2023; Amin et al., 2024). When these passports are embedded with blockchain technology and IoT tracking, they transcend their static role and become active data infrastructures, enabling investors to retrieve real-time data on material degradation, embedded toxins, and end-of-life recovery pathways, thereby converting sustainability claims into audited and auditable material flows (Zheng L. et al., 2023; Kristoffersen et al., 2021; Ghitti et al., 2024; Bodellini, 2023; Fatimah et al., 2023). For example, in the European textile and electronics sectors, pilot programs using DPPs integrated with AI-based material scoring algorithms have revealed discrepancies as high as 27% between disclosed and actual recycled content discrepancies that would have gone undetected in traditional ESG audits, thereby highlighting the indispensable role of real-time data integrity systems in mitigating greenwashing risk (Bernini and La Rosa, 2024; Huang, 2021; EP, 2021).

As ESG investing expands into emerging markets where data infrastructure is weaker and regulatory harmonization is inconsistent, the portability and modularity of digital circularity tools become paramount, especially for integrating small- and medium-sized enterprises (SMEs) into global sustainable finance ecosystems (Chowdhury et al., 2022; Kuzma et al., 2021; Amin et al., 2024; Ahmad et al., 2023; Fatimah et al., 2023). Blockchain-based certification systems offer a lightweight but rigorous mechanism for SMEs to demonstrate compliance with CE criteria, such as zero-landfill processes, closed-loop water systems, and bio-based input sourcing, without the high audit costs typically required by large ESG rating agencies (Edgley et al., 2015; Atstāja et al., 2022; Mehrotra and Jaladi, 2022; García-Muiña et al., 2021). In Vietnam and India, for example, decentralized data platforms have enabled agro-industrial clusters to track biomass conversion rates and soil regeneration metrics through satellite IoT and mobile reporting feeding directly into sustainability-linked finance instruments structured by development finance institutions and ESG-oriented funds (Cheng et al., 2023; Ahmad et al., 2023; Le et al., 2022; Patil et al., 2021; Fatimah et al., 2023). These digital interventions are not peripheral but central to equity-driven sustainability transitions, reducing informational asymmetry and lowering the barrier for capital access in the global South.

Quantitative research increasingly supports the claim that digitally verified CE performance correlates positively with both risk-adjusted returns and long-term operational resilience, thereby challenging the outdated assumption that sustainability and profitability are in tension (Reboredo and Ugolini, 2020; Dvorský et al., 2023b; Ahmad et al., 2023; Amin et al., 2024; Ghitti et al., 2024). Empirical studies show that firms using AI-optimized waste diversion models outperform sectoral peers on return on equity by an average of 4.2%, while blockchain-traceable reverse logistics systems reduce supply chain disruptions by up to 31%, particularly during black swan events such as the COVID-19 pandemic or the Suez Canal blockage (Kristoffersen et al., 2021; Liu et al., 2024; Landau et al., 2020; Amin et al., 2024; Fatimah et al., 2023). Such findings provide critical input for ESG investors seeking to differentiate between performative ESG behavior and structural alignment with circular economy outcomes, establishing new econometric baselines for sustainability risk modeling that go beyond legacy carbon accounting or governance scores (Ghitti et al., 2024; Bernini and La Rosa, 2024; Ahmad et al., 2023; Kristoffersen et al., 2021; Sneideriene and Legenzova, 2025).

Therefore, as digital transformation rewires ESG reporting from narrative disclosure to empirical validation, a deeper ontological question emerges how do we define value in the post-linear economy, and who decides what metrics matter (Gray and Bebbington, 2000; Adams and Larrinaga-González, 2007; Burritt and Schaltegger, 2010; Galli et al., 2023; Patil et al., 2021)? The transition to a data-rich ESG ecosystem forces financial actors to abandon proxy measures that approximate sustainability (e.g., board diversity or CSR budgets) in favor of circular metrics that demand ontological accountability to the biosphere, such as per-product exergy loss, material regeneration coefficients, and social handprint indices (Fatimah et al., 2023; Engelhardt et al., 2021; Cavicchi et al., 2022). It is in this space between empirical rigour and ethical reckoning that digital ESG technologies must operate, not only measuring the circular economy but enacting it as a new economic philosophy.

The future of ESG metrics will thus not be written solely in regulatory decrees or boardroom pledges but coded into algorithmic logic, IoT protocols, and machine learning models that mediate the boundary between capital and life systems (Ramakrishna and Ramasubramanian, 2024; Fernando et al., 2022). This shift requires vigilance as much as celebration. The rise of digital sustainability platforms risks re-centralizing ESG authority in opaque algorithms and private data monopolies unless governed by open data standards, participatory design processes, and a commitment to just transition principles that center marginalized voices (Galli et al., 2023; Sneideriene and Legenzova, 2025). To avoid replicating the same asymmetries the ESG movement was meant to dismantle, institutional entrepreneurs must advocate not only for digital efficiency but for digital democracy, ensuring that the tools we build to measure circularity also embody ethics.

In contrast, the convergence of AI, IoT, and blockchain technologies represents not a peripheral update to ESG investing but a foundational shift in how sustainability is conceptualized, verified, and valued (as shown in Figure 4). Through enabling real-time tracking of material flows, lifecycle accountability, and predictive scenario analysis, these technologies allow ESG investing to move beyond aspiration toward transformation. Crucially, they empower investors to align capital not merely with stated ESG commitments but with empirically verified circular outcomes outcomes that can be measured in carbon handprints, recovery rates, and regenerative system impacts (Balluchi et al., 2020; Adams and Larrinaga-González, 2007). Currently digital architecture of ESG continues to evolve, it must be grounded in philosophical clarity, empirical rigor, and ethical foresight recognizing that in the Anthropocene, sustainability is not a feature to be tracked, but the very grammar by which economies must operate (Aqueveque et al., 2018; Guerard, 1998).

Figure 4

Figure 4. Digital transformation of ESG metrics. Illustrates the integration of AI, IoT, and blockchain in ESG metrics, emphasizing real-time data validation, lifecycle accountability, and circularity-driven investment. It highlights transparency, reduced greenwashing, and predictive analytics for sustainable financial decisions (Source: Developed by the Authors).

7 Lessons from the frontlines: case studies in circular economy metrics

The rapid diffusion of ESG investing has created the illusion of methodological maturity; however, closer scrutiny of firm-level practices reveals that the integration of circular economy (CE) metrics remains uneven, politically contested, and analytically under-specified (Baldi and Pandimiglio, 2022; Ghitti et al., 2024; Sneideriene and Legenzova, 2025). While corporations such as IKEA, Apple, Unilever, Philips, and Patagonia are frequently cited as exemplars of circular transition, their cases demand deeper critical interrogation not as success narratives, but as diagnostic sites exposing the institutional, financial, and epistemic limits of contemporary ESG architectures (Kristoffersen et al., 2021; Ahmad et al., 2023; Amin et al., 2024). When rigorously examined, these cases demonstrate that CE metrics do not merely complement ESG investing; they fundamentally challenge its dominant logics by re-embedding materiality, temporality, and physical throughput into financial valuation systems (Burritt and Schaltegger, 2010; Galli et al., 2023).

IKEA’s commitment to full product circularity by 2030 is often framed as a paradigmatic success, yet its analytical significance lies in its internal metricization architecture rather than its aspirational targets (Ellen MacArthur Foundation, 2021; Chaudhuri et al., 2022). The firm’s Circular Product Design Scorecards evaluating modularity, repairability, recyclability, and ease of disassembly represent a structural shift from narrative sustainability toward operationalized measurability (García-Muiña et al., 2021; Jakubelskas and Skvarciany, 2023). Crucially, these indicators function as decision constraints within product development and supplier selection, distinguishing IKEA from firms that merely append circular rhetoric to ESG disclosures (Ahmad et al., 2023; Babkin et al., 2023). Nonetheless, reliance on internally generated lifecycle assessments raises concerns regarding verification bias, epistemic closure, and supplier-level data asymmetries particularly in low-income manufacturing regions, thereby exposing the fragility of firm-driven CE metricization in the absence of harmonized external audit regimes (Iliev et al., 2023; Ghitti et al., 2024).

Apple’s closed-loop supply chain further complicates the CE–ESG nexus by highlighting technology as both enabler and limiter of circularity (Fatimah et al., 2023; Amin et al., 2024). The Daisy disassembly robot, capable of reclaiming rare earth elements and critical minerals at scale, has delivered measurable improvements in material recovery rates, which Apple translates into a Materials Circularity Metric modeled after the Ellen MacArthur Foundation’s framework (Cheng et al., 2023; Patil et al., 2021). While this metric is embedded into investor disclosures and executive compensation structures signaling genuine governance integration (Krummaker, 2019; Marrucci et al., 2022b) critical asymmetries persist. Circular gains remain concentrated in high-value components, while software-induced obsolescence, restricted repair ecosystems, and shortened product lifecycles remain underweighted in ESG assessments, illustrating how CE metrics can be selectively optimized around what is measurable rather than what is systemically transformative (Ghitti et al., 2024; Le et al., 2022).

Unilever presents a contrasting case, operationalizing circularity primarily through packaging and consumer-level waste metrics in the fast-moving consumer goods sector (Munonye and Ajonye, 2024c; García-Muiña et al., 2021). Indicators such as post-consumer resin ratios, refill participation rates, and waste footprint per consumer use are directly linked to capital allocation and green bond pricing, generating measurable financial benefits (Renneboog et al., 2008; Signori et al., 2021). Yet, from a critical analytical perspective, these intensity-based gains coexist with rising absolute material throughput driven by volume growth, revealing rebound effects that ESG investors frequently overlook (Braun, 2019; Bernini and La Rosa, 2024). This highlights the limitations of relative efficiency metrics in the absence of absolute reduction thresholds (Dvorský et al., 2023a).

Failure cases expose these weaknesses most starkly. H&M’s Conscious Collection exemplifies performative circularity, where sustainability labels function as semiotic devices rather than material indicators (Earth.Org, 2023; Bodellini, 2023). The absence of verifiable lifecycle data and misleading fiber composition claims revealed not only firm-level misrepresentation but systemic ESG rating failures that continued to reward disclosure volume over material circularity performance (Kristoffersen et al., 2021; Ghitti et al., 2024). This case illustrates how disclosure-centric ESG methodologies generate greenwashing equilibria by enabling reputational signaling to substitute for substantive transformation (Lyon and Montgomery, 2015; Baldi and Pandimiglio, 2022).

At the asset-manager level, controversies surrounding ESG-branded funds most notably BlackRock further demonstrate this structural decoupling (Dvorský et al., 2023b; Todaro and Torelli, 2024). Empirical analyses indicate that a majority of firms within such portfolios disclose no substantive CE data, despite high environmental scores, revealing what can be termed “circularity arbitrage” (Sneideriene and Legenzova, 2025; Toxopeus et al., 2021). This phenomenon underscores the inadequacy of voluntary disclosure regimes and the need for taxonomy-embedded, mandatory CE indicators (Iliev et al., 2023; Ghitti et al., 2024).

The European Investment Bank (EIB) provides a partial counterpoint by embedding CE criteria directly into financing eligibility, linking capital access to metrics such as CO₂ avoided per euro invested and recycled content per funded ton (EC, 2019; EP, 2021; Hambali and Adhariani, 2024). By conditioning finance on verified circular impact, the EIB shifts ESG investing from asset selection toward structural economic steering (Torelli et al., 2020; Venturelli et al., 2024). However, scalability challenges and cross-border verification constraints remain unresolved (Iliev et al., 2023).

Across these cases, a unifying insight emerges: the effectiveness of CE metrics depends less on technological sophistication than on governance integration, incentive alignment, and temporal horizons (DeMiguel et al., 2009; Lin et al., 2023). Firms embedding circular indicators into long-term investment logic consistently outperform those treating circularity as a reporting category, exposing the short-termism embedded within dominant ESG paradigms (Gray and Bebbington, 2000; Adams and Larrinaga-González, 2007).

Moreover, these frontline cases demonstrate that CE metrics possess transformative potential only when standardized, audited, and embedded within financial decision-making architectures (Ahmad et al., 2023; Amin et al., 2024). Without enforceable thresholds and investor accountability, circularity risks remaining rhetorical rather than operational reproducing the very greenwashing ESG claims to overcome (Sneideriene and Legenzova, 2025; Ghitti et al., 2024).

However, at a theoretical level, the struggle to meaningfully integrate circular economy metrics into ESG investing reflects a broader epistemic tension between financial abstraction and material reality. Conventional ESG frameworks operate primarily through proxy indicators policies, commitments, disclosure scores, and management systems that are legible to financial markets but only indirectly connected to physical resource flows (Gray and Bebbington, 2000; Adams and Larrinaga-González, 2007). Circular economy metrics, by contrast, are ontologically grounded in biophysical throughput, lifecycle duration, and material retention, forcing ESG systems to confront dimensions of value that resist short-term monetization and narrative simplification (Burritt and Schaltegger, 2010; Galli et al., 2023). This ontological mismatch explains why CE metrics are persistently marginalized within ESG ratings despite their superior explanatory power regarding long-term environmental risk.

From a political economy perspective, CE metrics also threaten entrenched accumulation logics by rendering visible the structural dependence of corporate profitability on linear extraction and planned obsolescence (Braun, 2019). Unlike carbon intensity metrics which can often be improved through efficiency gains without altering business models circularity indicators such as product longevity, reuse rates, and material recirculation ratios directly challenge volume-based growth strategies (Fatimah and Biswas, 2017; Bernini and La Rosa, 2024). As a result, firms and asset managers face strong incentives to selectively adopt CE metrics that align with existing profitability structures while excluding those that would necessitate deeper economic restructuring, reinforcing what scholars describe as “selective sustainability institutionalization” (Lyon and Montgomery, 2015; Ghitti et al., 2024).

Critically, this selectivity is amplified by ESG rating methodologies that prioritize cross-firm comparability over causal relevance, favoring standardized disclosures even when they obscure material differences in circular performance (Baldi and Pandimiglio, 2022; Dvorský et al., 2023b). The consequence is a performative equilibrium in which firms optimize for score improvement rather than systemic impact, and investors misinterpret ESG ratings as signals of resilience rather than reflections of disclosure compliance (Sneideriene and Legenzova, 2025). CE metrics disrupt this equilibrium by demanding sector-specific thresholds, absolute reduction targets, and lifecycle-based verification features that undermine the universalizing logic of current ESG indices (Iliev et al., 2023; Amin et al., 2024).

Ultimately, the transformative potential of circular economy metrics lies not merely in improved measurement, but in their capacity to re-politicize ESG investing, reintroducing questions of material limits, temporal justice, and intergenerational equity into financial decision-making (see Figure 5). Without this theoretical reorientation, ESG risks remaining a technocratic exercise in risk management, rather than a genuine mechanism for steering capital toward regenerative economic systems.

Figure 5

Figure 5. Navigating ESG integration in circular economy transitions. The diagram highlights key drivers environmental benefits, cost savings, innovation and barriers high costs, regulatory uncertainties, and consumer awareness affecting ESG integration in circular economy practices. These elements converge into a dynamic zone of challenges and opportunities for sustainable business transformation (Source: Developed by the Authors).

8 Toward circular investment portfolios

While the limitations of conventional ESG investing become increasingly apparent marked by vague disclosures, inconsistent metrics, and the rise of greenwashing the need for a next-generation framework has emerged, one that can align capital allocation with verifiable sustainability outcomes through circular economy principles that reconfigure how value is measured, preserved, and regenerated over time (Fatimah et al., 2023; Bodellini, 2023; Bernini and La Rosa, 2024; Ahmad et al., 2023; Ghitti et al., 2024). This evolution necessitates a paradigmatic shift from portfolio strategies that screen for ESG compliance to investment models that actively reward circularity performance, embedding metrics such as Circular Value Retention (CVR), Resource Recovery Ratios (RRR), lifecycle extension indices, and post-consumer material re-entry scores directly into asset selection, risk modeling, and valuation mechanisms (Kristoffersen et al., 2021; Amin et al., 2024; Jakubelskas and Skvarciany, 2023; Le et al., 2022; Liu et al., 2024).

The concept of circularity-weighted portfolios emerges as a corrective to ESG investing’s structural blind spots, introducing allocation logics that prioritize companies based on circular performance across product design, resource input, recovery efficiency, and system regeneration (Cheng et al., 2023; Alonso-Almeida et al., 2021; Baah et al., 2022; Babkin et al., 2023; Khajuria et al., 2022). In such a framework, CVR becomes a central metric, quantifying the retained value of a product or material throughout its lifecycle as a percentage of its initial economic and functional value thus penalizing planned obsolescence and rewarding durability, reparability, and modularity (Fatimah and Biswas, 2017; García-Muiña et al., 2021; Amin et al., 2024; EP, 2021). Companies that extend product life cycles through reuse systems, product-as-a-service models, or remanufacturing would exhibit higher CVR scores, which can then be weighted into asset selection algorithms, rebalancing portfolios toward regenerative business models and away from extractive ones (Chaudhuri et al., 2022; Patil et al., 2021; Bodellini, 2023; Ghitti et al., 2024; Le et al., 2022).

Resource Recovery Ratio (RRR) serves as a complementary metric, capturing the efficiency and integrity of material reclamation post-consumption, expressed as the ratio of recovered usable material to total product mass at end-of-life (Iliev et al., 2023; EC, 2019; Ahmad et al., 2023; Kristoffersen et al., 2021; Amin et al., 2024). A company with a high RRR not only demonstrates environmental stewardship but signals long-term supply chain resilience and cost savings, making it a more robust candidate for ESG-oriented capital. For instance, Apple’s disassembly robots recover over 95% of rare earth elements from returned iPhones generating a quantifiable RRR that can be integrated into circular fund performance benchmarks and serve as a hedge against resource volatility and geopolitical supply disruptions (Fatimah et al., 2023; Cheng et al., 2023; Ahmad et al., 2023; EP, 2021; Kristoffersen et al., 2021). Investors equipped with this metric can model material scarcity exposure and forecast portfolio vulnerability to linear input dependencies, enabling a more predictive form of sustainability valuation (Amin et al., 2024; Ghitti et al., 2024; Zheng M. et al., 2023).

The implementation of such metrics also requires digital traceability infrastructure, wherein AI, blockchain, and IoT technologies form the backbone of auditable, real-time circularity data (Zheng M. et al., 2023; Liu et al., 2024; Cavicchi et al., 2022). Investment funds such as BlackRock’s Circular Economy Fund and BNP Paribas’s Circular Economy strategy have begun integrating granular lifecycle and input–output data to reweight portfolios around firms with measurable closed-loop operations, signaling a move from ESG “branding” to ESG engineering (Cheng et al., 2023; Fatimah et al., 2023; Iliev et al., 2023; Kristoffersen et al., 2021; Le et al., 2022). These funds use circular indicators as criteria for stock inclusion or exclusion penalizing companies with low recyclate inputs or short product lifespans and rewarding those that publish lifecycle emissions reductions verified through third-party audit mechanisms (Babkin et al., 2023; Velte, 2023).

Crucially, the integration of CVR and RRR into asset pricing models can reveal the shadow costs of linear operations, such as stranded assets, regulatory risks, and carbon taxation exposure, providing the analytical basis for discounted cash flow projections that internalize ecological depreciation (Reboredo and Ugolini, 2020; Baldi and Pandimiglio, 2022; Fatimah et al., 2023; Galaz et al., 2018; Marrucci et al., 2022a). This revaluation mechanism ensures that firms with high circularity performance are no longer merely ethical outliers but financial frontrunners, with more stable return profiles, reduced input volatility, and lower transition risk under climate-aligned policy scenarios (Khajuria et al., 2022; Dvorský et al., 2023a; Amin et al., 2024; Jakubelskas and Skvarciany, 2023; Kristoffersen et al., 2021). At the portfolio level, scenario modeling suggests that high-circularity firms exhibit 15–28% lower downside risk under carbon pricing models and outperform sector peers during supply chain shocks due to localized recovery loops and diversified input sourcing (Le et al., 2022; Ahmad et al., 2023; Iliev et al., 2023; Ghitti et al., 2024; Fatimah et al., 2023).

Moreover, portfolio rebalancing based on circular metrics encourages capital reallocation toward sectors that are undervalued by traditional ESG filters, such as waste-to-resource innovation, bio-based materials, and industrial symbiosis platforms that create positive externalities through circular interfirm exchanges (Chowdhury et al., 2022; Alonso-Almeida et al., 2021; Dutta et al., 2020; Amin et al., 2024; Patil et al., 2021). For instance, funds that include regenerative agriculture firms using closed-loop nutrient cycles not only capture higher RRR and soil carbon sequestration scores but also reduce portfolio exposure to synthetic fertilizer markets, which are both carbon-intensive and geopolitically sensitive (Khajuria et al., 2022; Babkin et al., 2023; Hambali and Adhariani, 2024). These dimensions provide a multidimensional investment rationale that integrates environmental, social, and systemic risk considerations enhancing both ethical integrity and financial prudence.

The resilience of circularity-weighted portfolios becomes even more critical under the rising influence of policy mechanisms such as the EU Taxonomy for Sustainable Activities, the Sustainable Finance Disclosure Regulation (SFDR), and the upcoming mandatory Corporate Sustainability Reporting Directive (CSRD), which increasingly position material efficiency, lifecycle emissions, and product longevity as essential indicators of compliance and capital eligibility (EP, 2021; EC, 2019; Iliev et al., 2023; Bodellini, 2023; Ghitti et al., 2024). Investment strategies that incorporate metrics like Circular Value Retention and Resource Recovery Ratios can thus serve not only as tools for environmental risk management but as anticipatory governance mechanisms, aligning portfolio exposure with future regulatory pathways and fiscal instruments such as carbon border adjustment mechanisms or circularity-linked tax incentives (; Le et al., 2022; Fiaschi et al., 2020; Edgley et al., 2015).

In practical terms, this means that circular portfolios can be calibrated through multi-metric optimization models, using circular KPIs as constraints and weighting factors within portfolio theory frameworks thus incorporating environmental logic into the heart of financial optimization (Cheng et al., 2023; Reboredo and Ugolini, 2020; Dutta et al., 2020; Nguyen et al., 2020; Galaz et al., 2018). For example, a mean–variance portfolio could be reconstructed to minimize lifecycle emissions per unit of financial return, while maximizing aggregate Circular Value Retention across portfolio constituents, resulting in a dynamic efficiency frontier that simultaneously hedges systemic resource risk and supports regenerative value creation (Kristoffersen et al., 2021; Jakubelskas and Skvarciany, 2023; Amin et al., 2024; Ahmad et al., 2023; Fatimah et al., 2023). By applying these principles, asset managers can construct portfolios that perform competitively under conventional financial metrics while demonstrating superior ecological productivity, creating dual-track return profiles that address both fiduciary and planetary obligations (Ghitti et al., 2024; Iliev et al., 2023; Babkin et al., 2023; Sneideriene and Legenzova, 2025; Cheng et al., 2023).

This reconfiguration also opens the door to the development of new financial instruments and asset classes designed specifically around circular performance, such as circular equity indices, circularity-linked performance bonds, and lifecycle-dividend ETFs that return capital proportionally to verified environmental gains rather than pure profit extraction (Jakubelskas and Skvarciany, 2023; Dutta et al., 2020; Munonye and Munonye, 2025; Amin et al., 2024). These instruments can be tied to real-world metrics, such as material recirculation rates, packaging return ratios, or product repair rates ensuring that financial performance is directly linked to ecological outcomes and societal benefit (Le et al., 2022; EP, 2021; Iliev et al., 2023; Fatimah et al., 2023; García-Muiña et al., 2021). Such tools can be used by institutional investors, sovereign wealth funds, and pension systems seeking to de-risk long-term liabilities through investments in circular infrastructure, product-as-a-service models, and bioeconomy platforms that reduce volatility and enhance asset longevity (Chaudhuri et al., 2022; Amin et al., 2024; Ahmad et al., 2023; Bernini and La Rosa, 2024; Ghitti et al., 2024).

At the systemic level, circular investment portfolios help correct a core dysfunction of the current ESG regime: the overvaluation of incremental compliance and the undervaluation of structural transformation (Bodellini, 2023; Dvorský et al., 2023a; Marrucci et al., 2022a; Khajuria et al., 2022; Bernini and La Rosa, 2024). ESG scores have often rewarded firms for disclosure volume rather than performance integrity, enabling reputational arbitrage while ignoring material flows, repairability, or lifecycle design all of which are central to circular economy logic (Kristoffersen et al., 2021; Babkin et al., 2023; Fatimah et al., 2023; Sneideriene and Legenzova, 2025; Ahmad et al., 2023). Circular portfolios, by contrast, demand quantifiable proof of sustainability no longer treating it as a narrative attribute but as a material structure of value creation, efficiency, and regeneration (Cheng et al., 2023; Ghitti et al., 2024; Amin et al., 2024; García-Muiña et al., 2021; Alonso-Almeida et al., 2021).

Philosophically, the shift toward circular investment portfolios is not merely a methodological improvement but a metaphysical redirection away from extractivist logics that define value as depletion, and toward regenerative paradigms that see value as renewal and reciprocity (Gray and Bebbington, 2000; Burritt and Schaltegger, 2010; Galli et al., 2023; Adams and Larrinaga-González, 2007; Ramakrishna and Ramasubramanian, 2024). In this worldview, financial returns are not isolated outputs but ecological expressions, contingent on the durability, reparability, and reusability of the systems from which they arise. Circular metrics such as CVR and RRR become instruments of moral as well as monetary valuation, connecting investor decisions to planetary carrying capacity and intergenerational justice (Ghitti et al., 2024; Amin et al., 2024; Le et al., 2022).

Therefore, the next frontier of ESG investing must transcend the current matrix of passive exclusions and vague generalizations, adopting circularity-weighted portfolios as a framework for designing financial architectures that are empirically grounded, ethically sound, and economically resilient (as shown in Figure 6). This transition demands innovation not only in financial instruments but in investment culture, data governance, and systemic accountability requiring regulators, institutional investors, and corporate boards to jointly commit to embedding circularity into the DNA of capital allocation. In doing so, the ESG movement can fulfill its latent promise: not just to measure the world more carefully, but to remake it more justly, ensuring that every dollar invested is not only profitable but restorative (United Nations, 2015).

Figure 6

Figure 6. Next frontiers of circular investment portfolio. Visualizes the transition from conventional ESG investing to circular investment portfolios, integrating metrics like Circular Value Retention (CVR) and Resource Recovery Ratios (RRR) to prioritize long-term value preservation, reduced waste, and resource efficiency (Source: Developed by the Authors).

9 Conclusion and strategic recommendations

The integration of circular economy (CE) metrics into environmental, social, and governance (ESG) investing represents more than a technical evolution (see Figure 7); it constitutes a fundamental redefinition of sustainability, financial materiality, and the fiduciary logic of capital markets, especially as global regulators, investors, and corporations increasingly acknowledge the insufficiency of traditional ESG indicators to capture systemic ecological risk and long-term value creation (Ahmad et al., 2023; Bodellini, 2023; Amin et al., 2024; Kristoffersen et al., 2021). While ESG investing was initially conceived as a bridge between ethical imperatives and market returns, its credibility has been increasingly compromised by greenwashing, compliance-based metrics, and a lack of operational traceability, particularly in sectors with complex supply chains or short-term investment horizons (Bernini and La Rosa, 2024; Fatimah et al., 2023; Ghitti et al., 2024; Baldi and Pandimiglio, 2022). Against this backdrop, the adoption of CE metrics offers a corrective pathway embedding lifecycle logic, material flow transparency, and regeneration thresholds directly into the evaluative architecture of financial markets, thereby pushing ESG investing toward actual environmental impact rather than symbolic alignment (Jakubelskas and Skvarciany, 2023; Cheng et al., 2023; Atstāja et al., 2022).

Figure 7

Figure 7. Intersection of CE metrics into ESG investing. This framework visualizes how embedding (CE) metrics into ESG investing transcends conventional sustainability measures by quantifying resource efficiency and lifecycle impacts. This integration challenges superficial ESG claims, promoting accountability, systemic change, and regenerative finance, thereby reshaping investment paradigms toward genuinely sustainable and circular economic models (Source: Developed by the Authors).

More prominently, the research significance of this study rests in its argument that CE metrics do not merely enhance ESG evaluation but reconfigure the ontological foundations of sustainable finance by introducing a quantifiable, interoperable, and lifecycle-sensitive methodology capable of operationalizing planetary boundaries within investment decision-making. In doing so, this paper positions CE metrics as the missing analytical infrastructure that can transition ESG investing from disclosure-driven legitimation toward empirically grounded regenerative value creation a shift increasingly supported by emerging literature on investor attention and corporate greenwashing, which shows that markets misinterpret sustainability signals when disclosures lack verifiable substance, and by studies on artificial intelligence and corporate green development, which demonstrate that AI-enabled innovation efficiency can reduce environmental risk only when underlying data architectures incorporate circularity-aligned indicators. These insights further strengthen the case that CE-informed data systems are not optional enhancements but necessary prerequisites for credible ESG transformation.

However, explicit limitations must also be acknowledged. First, this study remains primarily conceptual and literature-driven, meaning that empirical validation of specific CE metrics across industries such as Circular Value Retention or Resource Recovery Ratios requires future econometric testing and sectoral calibration. Second, the analysis focuses predominantly on large multinational firms and financial institutions, leaving open the question of how SMEs, informal sector actors, and emerging-market enterprises can implement CE-aligned reporting within their resource constraints. Third, the paper does not engage extensively with potential geopolitical frictions, such as regulatory fragmentation between the EU, US, and Asia, which could slow or distort the global adoption of circular taxonomies. These limitations signal fertile terrain for future research.

Future studies can build on this paper by conducting longitudinal analyses of how investor attention measured through search trends, social media signals, and trading volumes influences the diffusion of CE disclosures and moderates greenwashing incentives. Scholars can also explore how machine learning–based innovation efficiency models interact with circularity KPIs to predict corporate environmental performance, and how AI-driven lifecycle auditing tools reshape rating agency methodologies. Additionally, interdisciplinary research combining behavioral finance, industrial ecology, and digital governance can examine how CE metrics influence investor psychology, risk perception, and portfolio evolution across different market regimes.

However, the implications of a CE-ESG convergence are profound. For investors, it signals a paradigmatic recalibration of valuation strategies no longer anchored solely in linear cash flow models or sectoral beta coefficients but informed by material circularity, ecosystem dependencies, and resilience to systemic shocks such as raw material scarcity or carbon regulation (Ahmad et al., 2023; Amin et al., 2024; Bernini and La Rosa, 2024). For policymakers, it underscores the urgency of creating regulatory feedback loops that align fiscal incentives, procurement standards, and financial market rules with CE objectives, ensuring that the pricing of capital reflects not only risk and return but renewal and responsibility (EP, 2021; EC, 2019). For corporate leaders, it demands the reimagination of value propositions not as extractive growth trajectories but as circular stewardship models where durability, disassembly, traceability, and social inclusivity constitute enduring competitive advantage (Chaudhuri et al., 2022; García-Muiña et al., 2021).

Furthermore, this study reaffirms that the future of ESG investing will depend not on incremental refinements to legacy frameworks but on a systemic reorientation toward circularity-based metrics capable of embedding regenerative logic at the heart of financial decision-making thereby positioning CE metrics not merely as tools of measurement but as catalysts of a fundamental transition toward an economically resilient, ecologically restorative, and socially equitable global financial system.

Ultimately, the adoption of circular economy metrics within ESG investing is not simply a policy adjustment or data refinement but a rearticulation of the economic grammar through which sustainability is enacted, capital is valued, and futures are imagined. If accompanied by rigorous standardization, robust regulation, and inclusive collaboration, CE metrics can finally bridge the credibility gap in ESG investing providing investors and regulators with the actionable intelligence necessary to channel capital toward genuinely sustainable outcomes. The road ahead demands bold institutional entrepreneurship, technological precision, and a moral commitment to regeneration, but the reward is a financial system capable of healing, not just hedging against the crises it helped create.

Author contributions

WC: Conceptualization, Data curation, Formal analysis, Supervision, Validation, Writing – original draft, Writing – review & editing, Visualization. DM: Data curation, Formal analysis, Writing – original draft, Writing – review & editing.

Funding

The author(s) declared that financial support was not received for this work and/or its publication.

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declared that Generative AI was not used in the creation of this manuscript.

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