AB
aristeidis bitzenis
University of Macedonia
Thessaloniki, Greece
About this Research Topic
Manuscript Submission Deadline 1 March 2027
This Research Topic is currently accepting articles
Background
The accelerating convergence of digital transformation and sustainability imperatives is profoundly reshaping contemporary economic and production systems. Artificial intelligence, big data, and digital platforms are becoming increasingly embedded within industrial processes, supply chains, and global value networks, thereby offering expanded opportunities for efficiency gains, technological innovation, and enhanced decision support. At the same time, growing concerns regarding resource depletion, climate change, and environmental degradation have intensified the imperative for circular economy approaches that promote resource efficiency, waste minimization, and more sustainable patterns of production and consumption. However, the expansion of digital infrastructure, particularly energy-intensive data centers, introduces a new set of sustainability challenges that complicate these transitions. This evolving landscape underscores the critical importance of integrating AI-driven solutions with circular economy principles in order to enable systemic, resource-efficient, and environmentally sustainable transitions across industry and global markets.
The transition toward sustainable and circular economic systems is increasingly being shaped by the rapid diffusion of artificial intelligence and a broad spectrum of digital technologies. This evolving landscape, however, presents a fundamental dual challenge. On the one hand, artificial intelligence offers considerable potential to enhance resource efficiency, optimize production processes, and improve overall sustainability performance. On the other hand, its expansion is associated with escalating energy demands and intensifying environmental pressures, particularly those linked to digital infrastructures such as large-scale data centers.
Against this backdrop, the present Research Topic seeks to investigate and critically engage with this inherent tension by examining the conditions under which artificial intelligence can be effectively leveraged to advance circular economy transitions while simultaneously minimizing its environmental footprint. More specifically, the objective is to identify scalable and data-driven solutions capable of supporting resource-efficient systems across industrial sectors, infrastructural configurations, and global value chains. In parallel, the Research Topic aims to explore the governance arrangements, institutional mechanisms, and business models that are necessary to enable and sustain a genuinely sustainable form of digital transformation. By convening interdisciplinary perspectives, this Special Issue aspires to generate actionable and policy-relevant knowledge that meaningfully bridges technological innovation with tangible sustainability outcomes, thereby addressing a critical gap in contemporary research.
This Research Topic welcomes interdisciplinary contributions that advance sustainability science through the development and application of innovative, AI-enabled solutions designed to support circular economy transitions and resource-efficient systems across industry, infrastructure, and global value chains. In alignment with the journal’s emphasis on addressing interconnected environmental, economic, and societal challenges, the scope encompasses areas such as modeling and optimization for decision support, sustainable production and consumption systems, climate-friendly and resource-efficient digital infrastructure (including data centers), sustainable supply chain management, and circular resource use alongside waste reduction strategies. Particular emphasis is placed on studies that meaningfully integrate technological innovation with policy frameworks, governance structures, and institutional dynamics, as well as contributions that demonstrably support the United Nations Sustainable Development Goals (notably SDGs 8, 9, and 12). Submissions may include, but are not limited to, original research articles, systematic reviews, policy analyses, and practice-oriented studies; however, all contributions must clearly establish their sustainability relevance, employ robust and validated methodological approaches, and demonstrate measurable environmental, economic, and social impacts, in accordance with the journal’s standards for rigorous and impactful sustainability research.
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
Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.
Keywords: sustainable digital transformation, artificial intelligence, circular economy, AI-driven decision support systems, sustainable supply chain management, ESG and sustainable business models, institutional governance and digital transparency, AI for sustainability
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.
