A sweeping analysis of nearly a thousand recent scientific papers has revealed that circular-economy research is undergoing a dramatic transformation—from a field once dominated by recycling and waste disposal into a data-driven effort to redesign entire production systems. The study, published in Environmental and Sustainability Indicators, maps how researchers are connecting circular business models, artificial intelligence, supply chains, construction, pollution control and the United Nations Sustainable Development Goals. Its central message is striking: the circular economy is no longer being treated as a technical fix for rubbish, but as a systemic transition that could reshape how societies produce, consume and manage resources.
The researchers examined 859 peer-reviewed journal articles published in 2024, using records retrieved from Scopus in July 2025. The dataset was deliberately restricted to original research articles, excluding conference papers, book chapters and review articles. This gave the authors a high-resolution snapshot of the field’s most recent direction, rather than a complete reconstruction of every paper published over decades. The broader literature suggests that circular-economy scholarship passed through three stages: a foundation-building period from 2015 to 2017, when definitions and recycling dominated; an expansion phase from 2018 to 2019, marked by policy and industrial symbiosis; and a maturation period from 2020 through 2025, characterized by digital technologies, sustainability metrics and recovery strategies after the COVID-19 pandemic.
To see how the field is organized, Melanie M. Orbeso, Angelo I. Reyes and Robethel DR. Andres combined three forms of bibliometric analysis. Citation analysis identifies influential papers by counting how often they are cited. Co-citation analysis examines which publications are cited together, revealing the intellectual foundations and schools of thought that researchers draw upon. Co-word analysis tracks keywords that repeatedly appear in the same papers, exposing the concepts and topics that are moving into the scientific mainstream. Rather than relying on a single software platform, the team triangulated results from VOSviewer, CiteSpace and the bibliometrix package in R, then tested whether the observed clusters remained stable when analytical thresholds were changed.
This approach uncovered a research landscape with several distinct but increasingly connected streams. One cluster centers on methodological foundations, including the tools used to map scientific knowledge itself. Another links sustainable business models with supply-chain management, asking how companies can create value while keeping products, components and materials in circulation. A third focuses on the conceptual and institutional challenges of implementing circular systems across different countries and economic contexts. A fourth brings together digital technologies and circularity, while a fifth connects established theoretical frameworks with emerging applications. In keyword networks, construction and lifecycle management formed a particularly clear sectoral cluster, alongside themes involving electronic waste, demolition materials, recycling and environmental impact.
The most visible shift is the rise of digital language within circular-economy research. Artificial intelligence, big data, Industry 4.0, digital transformation and decision-making increasingly appear alongside terms such as sustainable development, waste management and supply-chain management. These technologies could support circular systems by making materials traceable, predicting when equipment will fail, matching waste streams with potential users and optimizing manufacturing processes. Internet-of-things sensors can monitor the condition and location of products, while digital twins—computer models that mirror physical assets—can simulate how buildings, factories or infrastructure will perform over time. Blockchain systems may provide tamper-resistant records of material origins and product histories, although the study emphasizes that the presence of a technology in academic literature does not prove that it has delivered large-scale environmental benefits in practice.
The analysis placed Sustainable Development Goal 12, responsible consumption and production, at the heart of circular-economy research. Its triangulated score was 6.07, far ahead of the other goals, reflecting the frequency and interconnectedness of terms such as “circular economy,” “waste management,” “recycling” and “sustainable production.” Climate Action, SDG 13, ranked second with a score of 4.25, driven by research on environmental sustainability, climate change, life-cycle assessment, emissions reduction and carbon footprints. SDG 9, which covers industry, innovation and infrastructure, ranked third at 2.27 and was strongly associated with artificial intelligence, Industry 4.0, innovation and digital transformation. Together, these results show that researchers increasingly view circularity as a mechanism for linking industrial innovation with climate and resource objectives.
The study also identified a wider environmental reach than is often apparent in discussions focused on factories and landfills. SDG 15, Life on Land, was connected to natural resources, ecosystem conservation, biodiversity and land degradation. SDG 14, Life Below Water, emerged through research on plastic pollution, freshwater contamination and marine ecosystems. A highly cited 2018 study on freshwater plastic pollution had accumulated 486 citations in the analyzed record, helping strengthen the connection between circular-economy strategies and aquatic protection. SDG 6, Clean Water and Sanitation, appeared through wastewater treatment, water pollution, clean water and water reuse. SDG 7, Affordable and Clean Energy, was linked to renewable energy, energy efficiency and clean-energy systems, though the connection was comparatively weaker and more fragmented.
Several influential papers illustrate how these connections operate. A study on the utilization and environmental risks of coal gangue, a waste material generated by coal mining, was the most cited work in the dataset, with 715 citations. Its focus on converting industrial byproducts into useful resources while controlling environmental hazards captures the circular economy’s promise—and its complexity. Research on anaerobic digestion treats food waste as a feedstock for producing biogas and recovering nutrients. Studies of construction and demolition waste examine how buildings can be designed, documented and dismantled so that materials retain value. Other work connects Industry 4.0 with sustainable industrial engineering, suggesting that digital data could help coordinate material flows across firms rather than optimizing each factory in isolation.
Yet the map also exposes serious weaknesses. Circular economy remains an unstable concept, with researchers and practitioners using the term to describe everything from recycling programs to broad economic transformations. The authors attempted to address this problem by consolidating synonyms such as “circularity,” “closed-loop economy,” “circular business strategy,” “resource recovery” and “sustainable manufacturing” before analyzing keyword networks. Even so, bibliometric methods can only interpret the metadata and language attached to papers; they cannot determine whether a proposed circular system actually reduces resource extraction, emissions or inequality. The analysis is also limited to Scopus and to 2024 journal articles, potentially excluding regional research, conference work and rapidly developing studies from countries with weaker representation in international databases.
Geography is one of the clearest unresolved issues. Circular-economy scholarship is concentrated in China, the United Kingdom, Italy, the Netherlands and Germany, while Africa, Southeast Asia and Latin America remain comparatively underrepresented. That imbalance matters because circular systems depend heavily on local infrastructure, informal labor, consumption patterns, institutions and access to finance. A model developed for a highly industrialized European supply chain may not work in a city where waste collection is informal or where materials are repaired and reused outside formal markets. The authors therefore call for research that treats social equity, consumer behavior and cultural adoption as central scientific questions rather than secondary considerations. They also urge researchers to connect urban and rural material flows, break down sectoral silos and study how circular policies function over time.
The next frontier, according to the analysis, is not simply adding more technology or publishing more definitions. It is developing reliable ways to measure whether circular strategies produce durable environmental and social gains. Researchers need standardized indicators that can be compared across industries and countries, dynamic models that track impacts over years rather than at a single moment, and life-cycle assessments capable of handling uncertainty and shifting system boundaries. Artificial intelligence may help create real-time monitoring and predictive environmental models, but those systems will require high-quality, interoperable data and transparent assumptions. The researchers argue that circularity must ultimately be evaluated across micro, meso and macro levels: the decisions of individual firms, the relationships within industrial networks and supply chains, and the policies and institutions that shape entire economies. Their bibliometric map suggests that this integration is beginning—but the success of the circular economy will depend on turning an increasingly connected research agenda into measurable change in the real world.
