About the Journal

Aims and Scope

Ecosystem Intelligence is an international, interdisciplinary, peer-reviewed, open-access journal dedicated to research on intelligence in, of, and for complex ecosystems. It advances theories, methods, evidence, technologies, designs, and governance approaches for understanding and responsibly shaping ecosystems composed of interdependent human, technological, organisational, institutional, economic, social, biological, and environmental components.

Research may examine intelligence exercised by actors and agents within ecosystems, intelligence emerging from interactions at ecosystem level, or intelligence developed for observing, modelling, designing, governing, and transforming ecosystems.

The journal views ecosystems as dynamic configurations of actors, agents, organisations, technologies, infrastructures, institutions, resources, relationships, and environments whose behaviour and outcomes cannot be adequately understood by examining any single component in isolation. Ecosystem Intelligence concerns the capacities and processes through which ecosystem conditions are sensed and interpreted; data, information, and knowledge are generated and shared; decisions and actions are coordinated; resources and capabilities are mobilised; value is created and distributed; and ecosystems learn, adapt, innovate, remain viable, or transform.

Intelligence may be expressed through human, biological, collective, organisational, institutional, computational, artificial, or hybrid capacities. It may be intentionally designed or emerge from interactions among ecosystem components, and it may be widely distributed or concentrated in particular organisations, platforms, institutions, or infrastructures. The journal examines both the beneficial and adverse consequences of different forms and distributions of intelligence.

The journal welcomes research addressing, but not limited to:

  • the conceptual, theoretical, epistemological, and methodological foundations of Ecosystem Intelligence, including ecosystem boundaries, levels and units of analysis, and relationships with established fields and theories;
  • ecosystem structures and dynamics, including actors and roles, networks, interdependencies, complementarity, modularity, emergence, self-organisation, co-evolution, path dependence, formation, growth, decline, renewal, and collapse;
  • data, information, knowledge, sensing, sensemaking, learning, prediction, foresight, transparency, explainability, uncertainty, and decision support across ecosystems;
  • human, collective, organisational, institutional, computational, artificial, and hybrid intelligence, including human–AI collaboration, intelligent agents, multi-agent systems, autonomous systems, and digitally mediated or cyber-physical ecosystems;
  • distributed agency, behaviour, decision-making, cooperation, competition, conflict, coordination, orchestration, markets, standards, institutions, regulation, and governance;
  • innovation, entrepreneurship, business models, ecosystem services, value creation, value capture and distribution, performance, productivity, and economic and societal outcomes;
  • sustainability, resilience, robustness, adaptability, security, trust, legitimacy, systemic risk, cascading effects, fragility, viability, and trade-offs across actors, scales, and time horizons;
  • ecosystem design, intervention, experimentation, transition pathways, institutional change, infrastructure development, adaptive governance, and transformation under uncertainty; and
  • power, responsibility, ethics, fairness, justice, inclusion, representation, privacy, data governance, accountability, and the distribution of benefits, costs, risks, and decision authority.

These themes are illustrative and non-exhaustive. They do not constitute fixed journal sections, a prescribed definition of the field, or a mandatory analytical framework.

The journal welcomes theoretical, conceptual, methodological, computational, qualitative, quantitative, empirical, experimental, comparative, participatory, design-oriented, governance-oriented, review, perspective, and critical contributions. Relevant methods may include case and longitudinal research, network analysis, agent-based and multi-agent modelling, system dynamics, optimisation, artificial intelligence, behavioural analytics, digital twins, virtual laboratories, integrated assessment, scenario methods, field and laboratory experiments, participatory modelling, and mixed-method research.

Contributions may examine business, entrepreneurial, innovation, industrial, supply-chain, digital, platform, data, media, energy, climate, environmental, social–ecological, food, agriculture, water, health, urban, mobility, infrastructure, public-sector, education, research, community, or other complex ecosystems. No application domain, discipline, technology, or method is inherently preferred.

To fall within the journal’s scope, a manuscript should make Ecosystem Intelligence a substantive part of its research problem, analysis, method, design, or contribution. It should identify a meaningful ecosystem-level unit of analysis or intervention, examine relevant interdependencies among multiple components, and contribute to understanding, enabling, evaluating, governing, or transforming intelligence and its consequences at ecosystem level.

Research focused on an individual technology, algorithm, device, organisation, platform, infrastructure, policy instrument, or operational process may be suitable when its relationships with other ecosystem components and its ecosystem-level significance are central to the study. Work is generally outside the journal’s scope when it optimises or evaluates an isolated component, uses ecosystem only as a descriptive label or application setting, reports a technical implementation without an ecosystem-level contribution, or presents stakeholder lists or ecosystem maps without substantive theoretical, methodological, empirical, design, governance, or critical advancement.

The journal does not require adherence to a single definition, framework, method, disciplinary perspective, or normative position. Clearly formulated and scientifically rigorous extensions, critiques, competing explanations, and alternative conceptualisations are welcome.

Audience and Readership

Ecosystem Intelligence serves an international and interdisciplinary readership concerned with how intelligence is generated, distributed, coordinated, governed, and applied in complex ecosystems, and how it shapes ecosystem performance, value creation, sustainability, resilience, equity, viability, and transformation.

Its primary audience includes researchers and scholars in complex systems and network science; computer science, artificial intelligence, data science, informatics, engineering, and human–computer interaction; management, economics, innovation, entrepreneurship, and organisation studies; behavioural and social sciences; governance, public policy, law, and ethics; and environmental, sustainability, transition, infrastructure, urban, and design studies. The journal also welcomes readers and contributors from domain-oriented fields examining business, industry, digital platforms, energy, climate, food, water, health, mobility, cities, and other complex ecosystems.

The journal is also relevant to research-informed practitioners, policymakers, public authorities, industry and civil-society organisations, infrastructure and platform operators, designers, and other decision-makers seeking rigorous theories, evidence, methods, technologies, and governance approaches for understanding or shaping complex ecosystems.

The journal’s readership is defined by engagement with meaningful ecosystem-level questions rather than by a particular discipline, sector, technology, method, or professional role.

Publisher and Hosting

Ecosystem Intelligence is published by the University of Southern Denmark and hosted on tidsskrift.dk by the Royal Danish Library.

Editorial decisions are made independently by the journal’s editors. The publisher and hosting institution do not determine the acceptance or rejection of individual manuscripts.

Publication Model

The journal follows a continuous-publication model. Articles are published online as soon as they have completed peer review, production, and final editorial approval. Published articles are collected in one annual volume.

Editorial Process and Peer Review

All submissions undergo an initial editorial screening for scope, originality, quality, and fit with the journal’s mission.

Scholarly manuscripts that pass screening undergo single-anonymous peer review: reviewer identities are not disclosed to authors, while author identities are visible to reviewers. Each manuscript is normally evaluated by at least two independent external reviewers with relevant expertise. Please see the Reviewer Guidelines for further information.

Editorial decisions are made by the Editor-in-Chief or an assigned editor on the basis of reviewer reports and the journal’s quality standards. Invited scholarly manuscripts undergo the same peer-review process as unsolicited scholarly submissions. Editorials and other non-research editorial content are clearly identified and are subject to editorial review rather than external peer review.

Access Policy

The journal provides immediate open access to all published content. No subscription, embargo period, payment, or reader registration is required to read or download published articles.

Fees

The journal charges no submission fee, article processing charge (APC), publication fee, page charge, or colour charge.

Copyright and Terms of Use

Articles published in Ecosystem Intelligence are published under the Creative Commons Attribution 4.0 International Licence (CC BY 4.0).

Authors retain copyright in their articles. By publishing in Ecosystem Intelligence, authors grant the journal a non-exclusive, permanent, and irrevocable right to publish, distribute, and preserve the article in all published forms.

CC BY 4.0 permits others to read, download, copy, distribute, print, search, link to, share, and adapt the article for any purpose, including commercial use, provided that appropriate credit is given to the authors, article, journal, and publisher and that a link to the licence is provided.

Authors are responsible for obtaining permission to include any third-party material not covered by the article’s Creative Commons licence. Reuse of such material may require permission from the original copyright holder.

Publication Ethics and Editorial Policies

The journal’s policies on research integrity, authorship, competing interests, editorial independence and recusal, data and code, participant and animal ethics, corrections and retractions, complaints and appeals, citation integrity, and special issues are set out in Publication Ethics and Editorial Policies.

AI Policy

Please see the journal’s AI Policy.