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The purpose of this paper is to investigate the most recurrent variables characterizing the collaborative relationships of industrial symbiosis (IS) (hereinafter also referred to as “anatomic” variables) established in the attempt to adopt circular economy (CE) by collecting evidence from a rich empirical set of implementation cases in Italy.

The current literature on IS was reviewed, and a content analysis was performed to identify and define the “anatomic” variables affecting its adoption in the circular economy. We followed a multiple-case study methodology investigating 50 cases of IS in Italy and performed a content analysis of the “anatomic” variables characterizing each case.

This research proposes the “anatomic” variables (i.e. industrial sectors involved, public actors involvement, governmental support, facilitator involvement and geographical proximity) explaining the cases of IS in the circular economy. Each “anatomic” variable is discussed at length based on the empirical evidence collected, with a particular reference to the impact on the different development strategies (i.e. “bottom-up” and “top-down”) in the cases observed.

Current literature on IS focuses on a sub-set of variables characterizing collaboration in IS. This research builds on extant literature to define a new framework of five purposeful “anatomic” variables defining IS in the circular economy. Moreover, we also collect and discuss a broad variety of empirical evidence in what is a still under-investigated context (i.e. Italy).

The United Nations Industrial Development Organisation (UNIDO) proposed the development of eco-industrial parks (EIP) related to the 9th, 12th, and 13th of the sustainable development goals (SDGs) for ensuring green industrial practice to deal with climate change. The first approach to EIP is choosing a suitable site, however, it is not a simple task, because it involves spatial factors and is always impaired by uncertainties that require more than one decision module. There is a fewer study in objectively assessing the criteria for the selection of suitable sites for EIP development to contribute to the SDG initiative. This study provides an integrated process for assessing a consistent weight of criteria for EIP site selection. Nine steps were used in the fuzzy-analytical hierarchy process namely criterion identification, hierarchical structure construction, triangular fuzzy number matrix, geometric ratio, fuzzy relative weight, defuzzification, normalisation, sensitivity analysis (SA) and weight ranking. When tested using spatial and non-spatial criteria for EIP site selection, results show transportation infrastructure (13%), raw materials (12%), water bodies (12%), climate (10%), labour (9%), land use (9%), markets (9%), governmental policies (8%), existing industries (7%), urban settlement (6%), and restricted areas (5%). The SA verified that any evaluation error of 2% or 5% on the criteria weight is insignificant, but for 10% error, results can be distorted. The study has developed a consistent, simple approach integrating hierarchical and uncertainty modules for choosing EIP locations, and it is proposed as a guide for selecting suitable greenfield or brownfield EIP sites for sustainable industrial practices.

The paper aims to contribute to the Circular Economy debate from the Entrepreneurship Education perspective. Despite scholars' growing interest in both these research streams, scarce consideration is given to the comprehension of their mutual implications and meaning.

The paper is based on a cross-case analysis. It compares 16 higher education programmes launched by Universities in Europe aimed to create competences and skills for Circular Economy in students with different profiles. The analysis provides a critical view of the emerging trends for the entrepreneurship education skills and competencies needed for the emerging circular entrepreneurship paradigm.

The paper discusses the main trends of Entrepreneurship Education focused on Circular Economy debate at the European level: rationale and learning objectives (why); contents (what), target students and stakeholders (who) and the learning processes (how). Four thematic areas are identified as common patterns: circular economy business model, green supply chain management, technology entrepreneurship and innovation and public policies and institutional frameworks.

The paper sheds new light on a still under-researched area, suggesting several implications and avenues for future research in Circular Economy and Entrepreneurship Education. Limitations regard the need to analyse education programmes from a larger geographical area, to take into consideration interesting experiences in the rest of the world and to also collect quantitative data.

Practical implications arise for the development of learning initiatives for the Circular Economy: learning objectives and new thematic areas focused on circular, sustainable and innovative rethinking of the process for creating value in the incumbent companies; exploring meaning and benefits of collaborative approaches and participation in the circular economy innovation ecosystem and developing advanced models for soft-skills development in terms of leadership, motivational and creative skills.

The debate on CE can also be rooted in the paradigm of entrepreneurship as a core process to advance knowledge on valuable and sustainable innovation.

Circular economy is presented as an approach to economic growth that is in line with sustainable development. However, the recent literature has highlighted the limits of the concept in terms of environmental sustainability. The study examines the relationship between circular economy and conservation of ecosystems, using a case study on the implications of a circular economy for Slovak forests and forest sector.

This study adopts a qualitative methodology through a focused review of the relevant literature on circular economy and sustainable development and primary data gathered through semi-structured interviews with 15 experts and practitioners in the forest sector, forest conservation and circular economy context, both from within as well as outside of Slovakia.

The study finds that the forestry sector has an important role to play in a shift to a circular economy in Slovakia, with significant opportunities for improved efficiency as well as substitution of wood for non-renewable resources. There is also growing potential for ecosystem stewardship and restoration. However, the increased application of biomass could crowd out other needs, including for biodiversity. Safeguarding these services depends ultimately on good governance.

The study highlights that circular economy taken in a narrow focus on resource efficiency is insufficient to ensure environmental sustainability but rather needs to be set within the broader environmental and social context.

This research identifies the enablers for implementing circular supply chains (CSCEs) and analyzes interrelationships between them to quantify their driving and dependence power to understand the critical CSCEs.

Initially, 10 CSCEs are identified for the Indian apparel industries through an extant literature review and validated using the Delphi method by seeking experts' opinions. The identified CSCEs are subjected to a novel neutrosophic interpretive structural modeling (N-ISM) method to capture the interrelationships between CSCEs and compute the driving and dependence power of CSCEs.

The findings of the present research work revealed that “supportive legislative framework, awareness of circular economy's potential for revenue gain and availability of trained research and development (R&D) team” are the critical CSCEs that need to be considered while implementing a circular supply chain in apparel industries.

This study offers insightful implications to guide practitioners in implementing the circular economy in apparel supply chains.

This research work is one of the earlier studies to analyze the enablers for implementing circular supply chains. This study has explored CSCEs in the context of apparel industries. From a methodological perspective, the novel N-ISM method is worth highlighting as the originality of the work.

The enormous amount of waste generated and the scarcity of natural resources worldwide have encouraged societies and industries to adopt the Circular Supply Chain (CSC) concept. With a focus on zero-waste generation, Circular Economy (CE) mimics the ecosystem cycle as an alternative to the traditional linear economic model. This paper aims to investigate the evolution of research themes in this research area, hence, trace the trajectory of development in the field of CSC.

The authors conduct scientometric analysis using Pajek and VOSviewer software to identify key themes in the Circular Supply Chain Management (CSCM) field. The Citation Path Analysis (CPA), including Main Path and Local Path analysis, has been followed by a critical review of the papers. This paper includes highlighting the interrelationships between the information flows in the topic of study as well as an analysis of keywords co-occurrence.

The analysis of keywords co-occurrence revealed that the earlier years of research in CSC were more inclined toward value chain, stakeholders and green supply chains, whereas, in recent years, topics like logistics, Industry 4.0 and food supply chain have been more focused upon. Further, the Main Path Analysis (MPA) revealed an evolving trajectory that examines challenges and opportunities in CSC, the economic aspects of implementing CSC, the impact on the firm's revenue growth and collaboration between multiple echelons of a supply chain and Industry 4.0.

The adoption of scientometrics analysis unveils the hidden flow of information, various themes of research and their interconnections. The development of research trajectories and progressive attention paid to certain topics is also discovered. The research findings could be used by researchers for further theoretical and research development.

This paper traces the path of development in the field of CSC and its emerging trends and provides a thorough understanding of the same. It enables research scholars to conduct an in-depth study in the CSC domain, adding to the body of literature.

Though the circular economy (CE) is a current buzzword, this still lacks a precise definition. In the absence of a clear notion of what that term includes, actions taken by the government and companies may not be well informed. In particular, those actions need to consider what people mean when people talk about the CE, either to refocus people's decisions or to undertake a more effective communications strategy.

Since people voice people's opinions mainly through social media nowadays, special attention has to be paid to discussions on those media. In this paper, the authors focus on Twitter as a popular social platform to deliver one's thoughts quickly and fast. The authors' research aim is to get the perceptions of people about the CE. After collecting more than 100,000 tweets over 16 weeks, the authors analyse those tweets to understand the public discussion about the CE. The authors conduct a frequency analysis of the most recurring words, including the words' association with other words in the same context and categorise them into a set of topics.

The authors show that the discussion focuses on the usage of resources and materials that heavily endanger sustainability, i.e. carbon and plastic and the harmful habit of wasting. On the other hand, the two most common good practices associated with the CE and sustainability emerge as recycling and reuse (the latter being mentioned far less). Also, the business side of the CE appears to be relevant.

The outcome of this analysis can drive suitable communication strategies by which companies and governments interested in the development of the CE can understand what is actually discussed on social media and call for the attention.

This paper addresses the lack of a standard definition the authors highlighted in the Introduction. The results confirm that people understand CE by looking both at CE's constituent activities and CE's expected consequences, namely the reduction of waste, the transition to a green economy free of plastic and other pollutants and the improvement of the world climate.

Various publications have extensively documented the advantages of a circular economy in ensuring sustainability and limiting climate change. Despite academic records emphasising the need to adopt this business strategy, entrepreneurs in developing countries prefer linear economies. This reluctance is attributable to several factors, including insufficient infrastructure and technology, limited financial access, inadequate education systems and the prevalence of informal enterprises. Therefore, a thorough analysis of the underlying economic, political and social conditions is required to identify the drivers of circular economies (CEs) and their contribution to entrepreneurship in developing countries.

In this study, the authors first conducted a comprehensive quantitative literature review based on LangChain to identify the critical CE drivers from the social, technological and organisational perspectives. Based on the input from the expert panel of Iranian academic and industry professionals, the authors applied an integrated fuzzy interpretive structural modelling and cross-impact matrix multiplication approach to classification (Fuzzy-ISM-MICMAC) to investigate the chronology of entrepreneurial drivers.

Level-based model results reveal entrepreneurial drivers in developing nations and their interrelationships, specifically underlining the importance of supply chain factors and stakeholder preferences. Thus, the differences between the perception of the main drivers in developed and developing economies can be identified, with the former paying particular attention to legislative and financial factors. The study's findings contribute to conserving resources, reducing waste and adopting more sustainable corporate practices, thereby assisting developing countries in achieving development goals.

This study employs an innovative quantitative systematic literature review approach that relies on a large language model to identify the drivers of the CE. Furthermore, it adopts a systematic approach to examine the enablers of the CE rather than a narrow and individual perspective of the entrepreneurial drivers. The study employs the fuzzy ISM MICMAC technique to showcase the prioritisation of entrepreneurial prospects in emerging economies.

The sustainable transition towards the circular economy requires the effective use of artificial intelligence (AI) and information technology (IT) techniques. As the sustainability targets for 2030–2050 increasingly become a tougher challenge, society, company managers and policymakers require more support from AI and IT in general. How can the AI-based and IT-based smart decision-support tools help implementation of circular economy principles from micro to macro scales?

This chapter provides a conceptual framework about the current status and future development of smart decision-support tools for facilitating the circular transition of smart industry, focussing on the implementation of the industrial symbiosis (IS) practice. IS, which is aimed at replacing production inputs of one company with wastes generated by a different company, is considered as a promising strategy towards closing the material, energy and waste loops. Based on the principles of a circular economy, the utility of such practices to close resource loops is analyzed from a functional and operational perspective. For each life cycle phase of IS businesses – e.g., opportunity identification for symbiotic business, assessment of the symbiotic business and sustainable operations of the business – the role played by decision-support tools is described and embedding smartness in these tools is discussed.

Based on the review of available tools and theoretical contributions in the field of IS, the characteristics, functionalities and utilities of smart decision-support tools are discussed within a circular economy transition framework. Tools based on recommender algorithms, machine learning techniques, multi-agent systems and life cycle analysis are critically assessed. Potential improvements are suggested for the resilience and sustainability of a smart circular transition.