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In the face of climate change, the circular economy is attracting the attention of public authorities, international institutions, industry and academia. There is currently no consensus on its definition and it varies according to the sectors and actors. The objectives of this work are threefold: (i) to identify all the discourses and initiatives attributed to the circular economy in order to situate them according to whether they belong to weak or strong sustainability; (ii) to enhance the value of this information by centralizing it, and creating tools to facilitate its exploration and access; (iii) to analyze how these initiatives allow circular economy to address global sustainability. Questions regarding data sources and processing of this information were raised to facilitate the collection of relevant data. This work focuses on information published on social networks, in particular Twitter called X now. Several data processing techniques such as text mining, geocoding and knowledge graph generation are applied. Data visualization tools are used to show the distribution of the data on a spatial, thematic and temporal level. The results obtained confirm the over-representation of circular economy practices based on weak sustainability in developed countries, while circular economy initiatives based on strong sustainability are most common in the Global South. This paper provides evidence on the social contribution of circular economy, which is less addressed in the technocentric approach. [Display omitted] • Global circular economy initiatives are collected, analyzed and mapped. • Circular economy initiatives are classified as strong or weak sustainability. • Weak sustainability initiatives exist in Global North, strong ones in Global South. • The circular economy is reconciled with the social pillar of sustainability. • Circular Economy can be linked to theories of social and environmental justice. [ABSTRACT FROM AUTHOR]

International headlines over the last few years have been dominated by extreme weather events, and floods have been amongst the most frequent and devastating. These disasters represent high costs and functional disruptions to societies and economies. The consequent breakdown of the economic equilibrium exacerbates the losses of the initial physical damages and generates indirect costs that largely amplify the burden of the total damage. Neglecting indirect damages results in misleading results regarding the real dimensions of the costs and prevents accurate decision-making in flood risk management. To obtain an accurate assessment of total flooding costs, this paper introduces the flood footprint concept, as a novel accounting framework that measures the total economic impact that is directly and indirectly caused to the productive system, triggered by the flooding damages to the productive factors, infrastructure and residential capital. The assessment framework account for the damages in the flooded region as well as in wider economic systems and social networks. The flood footprint builds on previous research on disaster impact analysis based on Input-Output methodology, which considers inter-industry flows of goods and services for economic output. The framework was applied to the 2007 summer floods in the UK to determine the total economic impact in the region of Yorkshire and The Humber. The results suggest that the total economic burden of the floods was approximately 4% of the region's GVA (£2.7 billion), from which over half comes from knock-on effects during the 14 months that the economy of Yorkshire and The Humber last to recover. This paper is the first to apply the conceptual framework of flood footprint to a real past event, by which it highlights the economic interdependence among industrial sectors. Through such interrelationships, the economic impacts of a flooding event spill over into the entire economic system, and some of the most affected sectors can be those that are not directly damaged. Neglecting the impact of indirect damages would underestimate the total social costs of flooding events, and mislead the correspondent actions for risk management and adaptation. [ABSTRACT FROM AUTHOR]

This paper proposes a novel agent-based model (ABM) to assess actual informal water market (IWM) trade—a highly common form of reallocating water globally, but where analysis is challenging due to data paucity. Because, typically, there is not an integrated or centralized institution coordinating transactions in IWMs, social networks and communications between farmers play a key role. This makes applications of ABMs in the informal space appealing and useful. Survey and interview data are used for the model development via a sample of farmers in Mojen Area, Iran. Also, in the final model, some critical human behaviors (e.g. adaptability and self-interest) are described in the form of parameters and formulas, with optimum values calibrated based on the Mojen sample as well as making possible a detailed assessment of the effects on water transaction and farmers' profit margins. The result of the simulation reveals that IWM trade frees up water for use by other farmers in the Mojen area, especially when stronger social networks are in place where the average number of water transactions will be increased—about 50%. The presence of IWMs also contributes to a more stable cultivation area in dry years, where water trading helps protect perennial crops that have become an increased production system choice in recent years. Further, informal water markets help farmers to optimally use water supply in order to deal with lower rainfall years and fulfil water needs during higher rainfall years due to increasing cultivation areas. [Display omitted] • An agent-based social network model for informal water market (IWM) simulation is developed. • A method of trades and an updating rule for simulating profit margins are proposed. • Experience, prior knowledge, and land area are three factors affecting water exchanges. • IWM can greatly improve the situation of water scarcity. • IWM stimulates farmers to use water in the best way in both trading and irrigation. [ABSTRACT FROM AUTHOR]

Based on Social Network Theory and the Planned Behaviour Theory, this paper adopts a multi-group analysis of structural equation model and uses the low-carbon behavioural intention as a mediator to analyse the role of social network embeddedness in influencing residents' low-carbon household behaviours. Based on the reliability test of the scale and the first-order confirmatory factor analysis, the direct and mediating effect dual models are used to verify the proposed research hypothesis; furthermore, based on demographic and family characteristics, a multi-group structural equation model analysis is conducted. The empirical results show that social network embeddedness will significantly improve residents' low-carbon household behaviours and reduce household carbon emissions. Social networks will embed residents' low-carbon household behaviours through direct effects and incomplete mediation of low-carbon behavioural intentions as mediators. Multi-group analysis result shows that female and highly-educated groups exhibited better low-carbon household behaviours, and different family scales, monthly incomes and consumption, housing size, and living area show significant influences on low-carbon household behaviours. • The direct and mediating dual effects were verified from SNE to residents' LHB. • The SNE significantly affects and directly reduces residents' LHB. • The SNE indirectly promotes residents' LHB through behavioral intention. • Different personal and family characteristics significantly affect residents' LHB. [ABSTRACT FROM AUTHOR]

Solidarity economy organizations (SEOs), community-based firms that usually operate in the third sector (nonprofit ventures) and are created by the members of the communities they serve, are believed to have the potential to contribute to a more sustainable world. However, little evidence has been produced so far about the factors that make these organizations more sustainable. In this paper, we analyze the impact of five key factors (source of capital, organization size, gender of leaders, incubation and networking) on the sustainability of more than 6000 Brazilian informal SEOs. We validated the constructs through a set of techniques belonging to the calculations of structural equations. Our study provides four key findings: social incubation and networking have a strong impact on the sustainability of SEOs, organizational size is (surprisingly) not important for the sustainability of these organizations, external sources of capital positively affect the sustainability of SEOs and finally, SEOs with more women leaders are more sustainability-oriented. Taken together, our findings indicate a path towards sustainability within the solidarity economy sector. Image 1 • Networking and incubation tend to be highly important for SEOs which want to increase their sustainability. • SEOs have the capacity to be socially, environmentally and economically sustainable, irrespective of their size. • The use of external sources of capital positively affect the sustainability of SEOs. • Female membership proved to be positive for the sustainability of SEOs. • The participation of SEOs in networks is an important condition to foster their sustainability. [ABSTRACT FROM AUTHOR]

This paper incorporates the multiregional input-output (MRIO) and social network analysis (SNA) methods to investigate China's embodied carbon transfer across provinces. We estimate the amount of interprovincial embodied carbon transfer from 2002 to 2012, analyse the spatial correlation network structure of carbon transfer and its determinants. Our work can clarify the spatial distribution and different roles of provinces in the carbon transfer network. The empirical results show the spatio-temporal evolution of embodied carbon transfer; in 2002, embodied carbon transfer occurred from the energy-rich northern provinces to the developed eastern and central provinces, but in 2012, it transferred to developing southwestern and southern provinces. Moreover, the northwestern provinces act as "bridges" between the central and eastern provinces; eastern provinces play a "bidirectional spillover" role that transfers carbon internally and externally. The embodied carbon transfer network proposed here can help policy makers further clarify individual provinces' carbon emissions reduction responsibilities and curb national carbon emissions. • The spatial correlation network structure of embodied carbon transfer in China is analysed. • The carbon emissions is with obvious regional disequilibrium and the transfer is "geographic adhesiveness". • Northwestern provinces act as "bridges" meanwhile Eastern provinces play a "bidirectional spillover" role in carbon transfer. • The environmental path dependence is most important in affecting embodied carbon transfer in 2012. [ABSTRACT FROM AUTHOR]

Among scholars, politicians and practitioners, the term “circular economy” (CE) has become increasingly familiar, but the concept comes from different epistemological fields and there is still a lack of consensus and convergence in the literature. This paper investigates the trends and gaps on the pathways convergence of the circular economy literature. The research method is a combination of semantic analysis, bibliometrics, networks and content analysis in a systematic literature review. The sample is composed of 327 articles extracted from the Web of Science and Scopus database. The results point out the lack of consensus on terminologies and definitions, thus, based on semantic analysis, a definition is proposed. In addition, the literature shows two main clusters, with different backgrounds, of different leading research groups in distinctive geographic regions. One cluster focuses on ecoparks and industrial symbiosis, mostly in the context of China. The second cluster is concerned with supply chains, material closed loops and business models. [ABSTRACT FROM AUTHOR]

The paper advances a conceptualization of sustainability in urban regeneration as communicative practice taking place within networks of social actors. To demonstrate the potential of this perspective, we propose an interdisciplinary methodology integrating social network analysis from sociology and multi-criteria decision analysis (fuzzy logic) from operations research to calculate a sustainability communicator score for each actor involved in a regeneration network. The score is based on three dimensions: a sustainability vision (relying on the three pillar model of sustainability), a formal network influence dimension (based on organizational practice and decision-making position) and an informal network influence dimension (drawing on degree, betweenness, eigenvector and closeness centrality measures from social network analysis). The framework allows the identification and ranking of sustainability communicators, based on the preferences of specific users, while also allowing for variable degrees of vagueness. We illustrate the methodology by means of a case study of a social network of actors (N = 28) involved in the sustainable regeneration of a brownfield site in Porto Marghera, Venice, Italy. The methodology is expandable beyond the actor level to allow for the ranking of more complex network configurations for promoting sustainability. [ABSTRACT FROM AUTHOR]

Natural resource accounting plays a critical role in sustainable utilization and conservation of natural resources. This paper aims to review research progress on natural resource accounting for the period of 1995–2014. The main research methods for this study include bibliometric analysis and social network analysis, covering publications’ performances, characteristics of related journals, countries, institutions, authors and keywords. The results show that the total amount of publications on natural resource accounting has increased rapidly since 2001. The most productive journal, country, institution, and author are Journal of Environmental Management, USA, University of California, and Dr. Chen, respectively. All of them have higher academic influence. Meanwhile, natural resources that attract most attentions are water and energy. The six main research methods in this field include mathematic modeling, emergy, exergy, ecological footprint (EF), life cycle assessment (LCA) and material flow analysis (MFA).Reasons for the prominent performance of key countries and institutions are then discussed and uncovered, as well as for six methods. Finally, suggestions on how to further promote the development of this research field are raised. [ABSTRACT FROM AUTHOR]

Solar energy is becoming one of the most attractive renewable sources. In many cases, due to a wide range of financial or installation limitations, off-grid small scale micro power panels are favoured as modular systems to power lighting in gardens or to be integrated together to power small devices such as mobile phone chargers and distributed smart city facilities and services. Manufacturers and systems' integrators have a wide range of options of micro-scale photo voltaic panels to choose from. This makes the selection of the right panel a challenging task and risky investment. To address this and to help manufacturers, this paper suggests and evaluates a novel approach based on integrating empirical lab-testing with short-term real data and neural networks to assess the performance of micro-scale photovoltaic panels and their suitability for a specific application in specific environment. The paper outlines the combination of lab testing power output under seasonal and hourly conditions during the year combined with environmental and operating conditions such as temperature, dust accumulation and tilt angle performance. Based on the lab results, a short in-situ experimental work is implemented and the performance over the year in the selected location in Kuwait is evaluated using deep learning neural networks. The findings of this approach are compared with simulation and long-term real data. The results show a maximum error of 23% of the neural network output when compared with the actual data, and a correlation values with previous work within 87.3% and 91.9% which indicate that the proposed approach could provide an experimental rapid and accurate assessment of the expected power output. Hence, supporting the rapid decision-making process for manufacturers and reducing investment risks. • Lab testing is implemented to evaluate relative performance of solar panels. • Performance of photovoltaic panels is predicted using neural networks. • Real in-situ data confirms the effectiveness of the suggested novel approach. • The results help solar systems manufacturers for rapid prediction of performance. [ABSTRACT FROM AUTHOR]

Business incubators (BI) are increasingly expected to nurture sustainability-driven start-ups and contribute to the economy's sustainable transformation. However, while previous (qualitative) research suggested a positive relationship between BI support services and sustainable impacts by entrepreneurs, no study has explored this link statistically, leaving sustainability-driven business incubation (SBI) haphazard and strategically ill-informed. Given the absence of a comprehensible assessment approach, this paper develops a coherent theoretical framework for structuring SBI. Moreover, it quantitatively investigates the relationship between entrepreneurs' usage of various BI support services and their self-proclaimed contributions to the UN Sustainable Development Goals (SDGs). Building on a sample of 299 German university spin-off start-ups, we provide empirical evidence that BI support services are generally related to the sustainable impacts of entrepreneurs. However, at a more nuanced level, we show that economic and ecological SDGs are associated with only a few BI services. In contrast, social SDGs are attained by a broad support service portfolio. In conclusion, we advise policymakers and BI managers to recognize the diverse support needs of sustainable entrepreneurs and tailor BI programs towards specific sustainability challenges rather than generalized approaches. [Display omitted] • A theoretical framework for sustainability-driven business incubation • Economic SDGs are related to infrastructure and team composition • Social SDGs are related to a broad range of incubator services • Environmental SDGs are related to funding and network support • Specialized incubator strategies may prove more impactful than generalized approaches [ABSTRACT FROM AUTHOR]

This paper presents an agent-based model of the technological adoption of solar panels, including potential adopters' characteristics and their interactions. This study analyzes the theoretical impact of seven social influence strategies on the adoption of solar panels by householders within a solar neighborhood in the Providencia district, Chile. In this case study, established adopters account for 0.9% of the population, opinion leaders for 1.3%, and individuals in the network for 97.8%. Considering the population's high-level ambition and tolerance of uncertainty, we found that householders are mainly characterized as optimizers (89.7%), followed by inquirers (7.6%), repeaters (2.3%), and imitators (0.3%) agents. Our agent-based simulation model evaluated the social influence strategies based on economic, environmental, and social benefits. The results show that social influence strategies lead to a 19.27% increase, on average, in the total number of adopters concerning the base case. Then, we performed a multi-objective analysis to select the best adoption strategy. These results show that selecting the most connected agents in the network is a robust strategy the decision-makers have environmental or financial concerns. However, if the decision-makers' primary interest is maximizing the diffusion scope of solar panel neighborhoods, random agent selection is the most advisable strategy, given its ease of implementation. [Display omitted] • Consumat approach and Campbell's paradigm were integrated into a simulation model. • The results from seven social influence strategies are compared. • Selective seeding and random seeding are found to be the most effective strategies. [ABSTRACT FROM AUTHOR]

Waste management has become a serious problem in China, with households generating an increasing amount of waste. To tackle this problem, many city administrations have implemented regulations on household waste separation and are stepping up efforts to improve awareness. Moreover, the existence of individual interactions in social networks makes the cost of raising awareness highly uncertain. Therefore, this paper aims to describe the individual interactions based on dynamics of opinion spread method and build the incentive strategy model that is extended to three robust incentive strategy models based on various uncertain sets by robust optimization: Box-SO Model, Ellipsoid-SO Model and Box-Ellipsoid-SO Model. The simulation results indicated that a higher uncertain level parameter or a lower interaction threshold leads to lower public awareness, in which the Ellipsoid-SO Model has the best robustness with sacrificing 7.96% of the total awareness value, but the Box-Ellipsoid-SO Model loses 24.24%. Meanwhile, cost constraint has a direct effect on public awareness, and people with a high frequency of social interactions are key to improving public awareness of household waste separation. Additionally, the results have several management implications that are conducive to improving public awareness and behavior of household waste separation in social networks: (1) The fundamental premise of improving public waste separation behavior is to stimulate awareness; (2) Small-scale activities are more efficient than large-scale activities in improving pro-environment opinion; (3) Given the existence of opinion leaders, propaganda for residents should be pertinently targeted. • Social interactions of awareness on household waste separation are studied. • Incentive models with cost uncertainties are proposed to improve awareness. • Awareness values of robust models are lower than basic model due to uncertainty. • Ellipsoid-SO Model has best robustness with losing 7.96% of the total awareness. • Small-scale activities are more efficient to improve public awareness. [ABSTRACT FROM AUTHOR]

This paper examined the carbon market literature from 1992 to 2011 using bibliometric techniques based on the database of Science Citation Index (SCI) and Social Science Citation Index (SSCI). Of 5809 publications, 82% were journal articles. Our analysis documents that carbon market publications are expanding rapidly. Based on the contribution of countries and their h-index, the US has published most and been most influential in this area, followed by the UK, Canada, Germany and China. The Chinese Academy of Sciences (120), US Forestry Service (70) and University of Maryland (68) were the most productive research institutes. The most common subject category, Environment Sciences (1551), experienced an exponential increase with an average growth rate of about 50%, and the most productive journal was Energy Policy (469). According to the analysis of keywords, the hotspots related to carbon markets were “global warming” and “carbon tax” in the 1990's, but “climate change” and the “clean development mechanism” superceded them in the most recent decade. The most cited article published in Science in carbon market research is presented. This analysis is not only helpful for policymakers and others to understand trends in the field, but may also influence researchers' selection of future studies. [ABSTRACT FROM AUTHOR]

The development of new technologies and techniques for industrial carbon reduction has risen to prominence in contemporary engineering and economics studies, a trend triggered by rising levels of concern regarding climate change. Within this context, the scientific literature puts emphasis on energy topics and energy policy. Studies from the social science, economics and management science perspectives would benefit from a coherent and recognized taxonomy of the subthemes, a taxonomy that spans disciplines and guides studies of the carbon reduction and technology (CRT) debate in the various industrial sectors. This paper identifies and analyses the existing body of literature; it systematically reviews a set of 3310 scholarly contributions. The study also conducts a semantic social network analysis from that dataset's keywords, identifying promising core themes. Findings include the need for more management research in this field, the need for an interdisciplinary research agenda. We also observe a growing contribution of the Chinese academy to this complex and diversified debate. [ABSTRACT FROM AUTHOR]

Agent-based models (ABMs) have been adopted to simulate different kinds of complex systems, from biological systems to complex coupled human-natural systems (CHANS). In particular, when used to simulate man-managed systems, they allow considering human behavioural aspects within the modelling framework. On the other hand, environmental Life Cycle Assessment (LCA) has become an acknowledged tool in research, industry and policy to assess systems' environmental sustainability. More recently, LCA is being applied to assess the potential environmental impacts of large scale policy actions (e.g., actions to combat climate change). This paper describes the application of a coupled ABM-LCA model to simulate cropping activities in the Grand Duchy of Luxembourg. The ABM considers farmers' proneness to risk, which was assessed via a naïve Bayesian model trained with the results of a survey distributed to the farmers of the study region. The goal of the study is to assess the effects of the agents' interactions, that can take place in a farmers' social network, on the agricultural activities. Geographic Information System (GIS) information, national statistics and naïve Bayesian model are used to parameterize agents' behaviour and interaction rules. We believe such assessment is necessary for the successful design of public adaptation strategies and subsidy schemes since governmental adaptation actions are needed to reduce emissions due to agricultural activities. Two scenarios (with different levels of farmers' environmental awareness) were simulated. The results show that the mean and variance of the distribution of farmers' environmental awareness change due to the effect of the interactions and, as a consequence, farmers' long-term decisions concerning agricultural activities are affected. This is reflected in the environmental impacts generated by such activities. [Display omitted] • A tight coupling between an ABM and a LCA module has been implemented. • Naive Bayesian model is a viable instrument to estimate farmers' proneness to risk. • Farmers' social network and interactions have been simulated using different criteria. • Farmers' green consciousness distribution slightly influences the simulated LCIA results. • Cumulative environmental impacts can be reduced via selected set of rules for agents. [ABSTRACT FROM AUTHOR]

In recent years, the use of social media has considerably increased interaction between the public sector and citizens. At the same time, environmental issues such as climate change are increasingly gaining importance in society. In such a scenario, local governments are called to engage and communicate with citizens on environmental issues and policies. This article explores whether and how local governments use the social platform Facebook with organizational legitimacy purposes and to interact with citizens on environmental sustainability. The paper contributes to understanding of how a social media platform could be regarded as a tool for disclosure of environmental information by local governments and the related organizational challenges. Starting from the list of all Italian municipalities with more than 100,000 inhabitants, we analyse text data scraped from each local government's Facebook page over a six-year period (2012–2017). The study is twofold: firstly, it measures the municipalities' disclosure of environmental issues via Facebook, considering also some independent variables such as political orientation and geographical area; secondly, it evaluates citizens' reactions with local governments' environmental posts looking also at the organizational processes connected to the evolution of sustainability disclosure. Findings indicate an increasing general use of Facebook by local governments as a tool for sustainability disclosure despite a decrease in other sustainability reporting practices. During the same period, citizens' reaction with environmental posts grew faster than interest in general posts. Municipalities communicated more on environmental issues they perceived as relevant, although they did not align themselves with citizens' views. In fact, there seems to be a decoupling of interests. This study contributes to the literature on social platforms' use by municipalities in the environmental disclosure system. • Facebook is widely used by Italian municipalities to disclose environmental topics. • Stakeholder interactions in environmental topics is high, with an increasing trend over time. • There is a misalignment between municipal environmental disclosure and citizens' expectations. • Facebook usage for local environmental issues is still an exchange legitimacy practice – not a decision-making support tool. • Social media communication by LGOs is not influenced by political party or geographical location. [ABSTRACT FROM AUTHOR]