Circular Economy and Sustainability in the Data Age: AI, Big Data, and Computational Methods for Measuring and Accelerating the Transition

The transition toward a circular economy depends not only on new business models, materials, and policy instruments, but on our capacity to observe, measure, and monitor that transition in near real time. At the same time, research methods across management, economics and the social sciences are being reshaped by artificial intelligence, large language models, causal machine learning, and the growing availability of Internet and big data: from search-engine trends and social media to web-scraped labor-market signals, satellite and sensor streams, and open linked data. These two currents have so far developed largely in parallel. This Research Topic helps bring them together.

We invite contributions that apply data-intensive and computational methods to questions of circular economy and sustainability: studies that quantify circularity, surface public and stakeholder attitudes, map skills and labor demand for the green transition, nowcast material flows or sustainable consumption, evaluate policy, or build the indicators and data infrastructures the field still lacks. We equally welcome methodological work that adapts AI, NLP, and machine-learning techniques to the specific data challenges of circular economy research, including questions of validity, reproducibility, interpretability, and responsible use.

This Research Topic emerges from, and is open beyond, two complementary event series: CARMA (8th International Conference on Advanced Research Methods and Analytics, Valencia, 1–3 July 2026), focused on AI, Internet data, and computational methods in the social sciences; and the Symposiums on Circular Economy and Sustainability (7th took place in Maastricht, 24–26 June 2026). Presenters at either event are warmly encouraged to submit substantially extended versions of their work, but submission is open to all as the call is not restricted to conference participants.

Submissions can be on the following themes but not limited:
• Measuring and indexing circularity: composite indicators, ESG and sustainability metrics built from big or alternative data
• LLMs, NLP, and sentiment/topic/narrative analysis applied to circular economy discourse, perceptions, and behavior
• Google Trends, search, and social-media data for nowcasting sustainable consumption, demand, and attitudes
• Web-scraped and platform data (e.g. LinkedIn, job postings) for green/circular skills and labor-market intelligence
• Bibliometric, scientometric, and topic-modeling mapping of the circular economy research landscape
• Causal machine learning and ML-econometrics for evaluating circular and sustainability policy
• Data-driven policy, e-government, and smart-city applications for the circular transition
• Methodological contributions: data quality, validation, reproducibility, interpretability, fairness, and responsible AI in sustainability research

Welcomed Article Types:
Original Research, Methods, Review, Systematic Review, Brief Research Report, Data Report, Perspective, and Policy/Practice-oriented contributions.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Community Case Study
• Conceptual Analysis
• Curriculum, Instruction, and Pedagogy
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Community Case Study
• Conceptual Analysis
• Curriculum, Instruction, and Pedagogy
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy and Practice Reviews
• Policy Brief
• Review
• Systematic Review

Keywords: circular economy, sustainability, big data, artificial intelligence, large language models, computational social science, text mining, ESG indicators, circular transition, data-driven policy

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.