Geotagged social media data offer a valuable tool for identifying nature tourism hotspots and monitoring human-wildlife interactions. Previous studies have demonstrated the utility of hashtags in detecting popular tourist areas linked to wildlife, such as seal haul-out sites, both within and beyond designated Special Areas of Conservation (Mancini et al., 2018). Similarly, data mining techniques have been used to monitor recreational activities like fishing, providing insights into fisher behaviours and fish populations (Monkman et al., 2018). Integrating social media analytics with ecological monitoring presents a novel approach for assessing ecotourism’s impact on charismatic megafauna, such as seals and seal tourism.

This study analyses georeferenced Instagram© posts from 2014 to 2023 within the Ythan Estuary catchment, Aberdeenshire. The area lies within the Forvie National Nature Reserve, a protected and ecologically significant coastal site in Scotland, adjacent to Newburgh Seal Beach, a popular recreational area. Using hashtag analysis and data mining techniques, we examine whether visitor motivations, personal significance, and proximity to the site can be quantified from social media activity. Given the estuary’s history of human recreation, its growing seal population, and its designation as a critical seal habitat, this location provides a compelling case study for evaluating the sustainability of seal tourism.

We specifically extracted posts referencing seals to assess their relationship with visitor motivations and proximity patterns. Temporal trends in posting behaviour were analysed to determine the impact of the 2017 seal haul-out protection measures and the 2020 COVID-19 pandemic on visitor activity and social media engagement.

Much of the environmental movement in the US is shaped by grassroots organizations working alongside communities, research institutions, and governmental agencies. This creates localized networks for environmental stewardship across the country, which may be shaped by both shared national and international forces and also unique region-specific circumstances. This raises the question of how local environmental stewardship networks are different and alike. Are there phenomena that are unique to environmental stewardship networks and how do they resemble other more widely studied organizational networks? Here, we analyze eight different collaborative environmental stewardship networks, representing eight US cities and regions, within eight different US states across the country. We employ exponential random graph models (ERGMs) to model each network and compare and contrast the forces at play within each one. The networks range in size from 44 organizations to 1,313 organizations, with an average of 324. We use data collected through various rounds of the USDA Forest Service’s Stewardship Mapping and Assessment Project (STEW-MAP), which has been conducted since 2007 and has been replicated in over a dozen cities globally. Preliminary results have shown a shared propensity for anti-preferential attachment and high mutuality, while cities differ on effects for both organizational focus and type. This work helps us understand local environmentalism broadly within the US context and can provide evidence for how environmental stewardship efforts scale with size, population, urbanization, and more.

Power has increasingly been integrated into institutional analysis to explain behavior, interactions, and outcomes in environmental governance. Yet, actor-focused theories of power do not fully capture the influences, hierarchies, and power relations that span multiple decision-making situations, and the power that actors exert via powerful linked situations. Social Network Analysis (SNA) offers graph theoretic measures to quantify different relationships and examine power relations among nodes based on their structural connections. This paper leverages a multimode network approach and a nascent power typology from institutional analysis to theorize and assess interdependences between situations and actors as two forms of power: ‘power-over’ and ‘power-to’. We describe ´power over’ as situation-centered pragmatic, framing, and design power, manifested via AS linkages of biophysical transactions, information, and institutions, respectively. ‘Power-to’ is theorized as the capacity of actors to exert influences, determined by their involvement in situations (membership). We operationalize these NAS concepts via multimode motifs that assess the extent of ‘power-over’ situations and ‘power-to’ actors. The framework is applied to examine deforestation outcomes of the Indonesian palm oil value chain. Data sources include semi-structured interviews with 16 policy actors, supplemented by secondary datasets from peer-reviewed and media articles. Among 11 delineated situations, policymaking and certification situations exert substantial design power, whereas global market, discourse, and monitoring situations manifest significant framing power. We note the interplay between design power by the Indonesian policymaking and framing power by the global market, reinforcing the growth-centered expansion of oil palm plantations. Among 22 aggregated actor typologies, producing companies, NGOs, and the Indonesian government demonstrate high ‘power-to’, stemming from their participation not only in the greatest number of decision-making situations, but also the ones exerting substantial ‘power-over’.

Scientific research on climate change emphasizes carbon performance (CP) as essential to sustainable management. The framework examines business greenhouse gas emissions from environmental restrictions and public expectations. CP has been explored for pollution monitoring and financial incentives like carbon credits, but sociological knowledge of corporate networks as sustainability advocates is lacking. This study examines CP through the lens of corporate centrality, defined as a company’s position based on its connectivity and influence within a network. It analyzes different types of centralities in Mexican corporations, employing social network analysis (SNA) and metrics such as degree, closeness, eigenvector, and betweenness centrality. The research focuses on networks of shared board members (board interlocks) and the carbon emissions reported by these companies. Using a symmetric undirected matrix to account for board interlock connections, our findings reveal whether companies with higher centrality implement more effective sustainability practices, positioning them as key nodes for disseminating emission reduction strategies. Furthermore, the study aims to identify the challenges faced by peripheral companies, which, despite having less influence, exhibit greater flexibility to adopt innovative approaches. This research offers theoretical and practical frameworks to improve business sustainability plans and highlights the significance of network dynamics in advancing low-carbon economies. The findings enhance the domain of business management and sustainability, emphasizing the significance of collaboration and leadership in addressing climate change. The report provides pragmatic ideas for formulating public policies and business initiatives that enhance the role of core enterprises and promote sustainable development.

We investigate the relationship between the interlocks created by CEO outside directorships and corporate ESG performance. We want to verify if ESG practices (or declarations of such performance) spread between interlocked companies.

We test the following hypotheses:

H1: The number of interlocking ties created by a CEO serving as a member of other companies’ boards or committees is positively related to the focal company’s ESG performance.

H2: (Influence) CEO interlocks between two companies leads to a higher similarity in ESG performance.

H3: (Selection) Similarity in ESG performance increases the probability of creation of interlocks by common directors.

H4: Companies, whose current CEOs share additional employment in at least one company other than the ones they serve as CEOs (are potential peers), become more similar in their ESG performance.

We study the development of the two-mode director interlock network of a set of large European companies and their ESG performance. For similarity in performance, we consider both overall ESG ordinal ratings in a given category (Environmental, Social and Governance) and compliance to the same particular ESG items (represented by a two-mode network: companies by a set of binary ESG indicators).

The sample covers the 150 biggest nonfinancial companies (selected based on Stoxx Europe 600). Data related to CEOs, their outside directorships, and companies’ characteristics are taken from ORBIS and Boardex databases; ESG performance data are from EIKON DataStream. We utilize Stochastic Actor-oriented Models, estimated in RSiena, for coevolution of a two-mode board interlock network and ESG performance between 2018 and 2022.

This research advances our understanding of the structural barriers that hinder the application of good governance principles in Marine Protected Areas (MPAs) as socio-ecological systems. Drawing on our experience in European projects since 2012 and focused on the Spanish case since 2018, we have identified, through both primary and secondary data, various barriers that impede progress towards an efficient marine governance. These insights led us to develop a methodology for evaluating MPA governance efficiency based on stakeholder perceptions, implemented in our OGMAR platform (Observatory of Marine Governance), which covers 858 Spanish MPAs (marine and coastal-marine areas). In this proposal, we apply our methodology to define a typology of management models derived from good governance principles, formulating hypotheses on which groups of actors are most likely to perceive each model. We then test the framework against data collected via OGMAR, incorporating network analysis to construct bipartite actor–governance model networks, identify clusters of actors with shared perceptions, and perform a multilevel spatial examination of governance patterns. By contrasting the theoretical framework with empirical data from Spanish stakeholders, we identify structural barriers that undermine good governance. Further exploration of these challenges through OGMAR data highlights opportunities to strengthen management efficiency and stakeholder participation in decision-making. Ultimately, this study contributes to improving environmental and marine governance by demonstrating how the proposed methodology, combined with network analysis of stakeholder perceptions, can help design interventions that advance the sustainability of socio-ecological systems and foster sustainable human development.

This paper examines the characteristics of inter-organisational networks in post-disaster recovery, focusing on their ability to adapt and remain effective over time. While extensive research has explored such networks during the preparedness and response phases, their role in long-term recovery has received less attention. Unlike the response phase, recovery is a multi-year process involving the sustainable restoration of the physical, economic, social and psychological well-being of affected communities.

The existing research landscape is fragmented, with scholars from different disciplines applying different empirical and theoretical approaches to different disaster types and networks. To provide a more systematic basis for studying the sustainability of inter-organisational networks, this study conducts an integrative review, synthesising knowledge across research traditions to identify common themes.

A keyword search was conducted in major academic databases, including Scopus, EBSCOhost and Web of Science. The selection process involved screening of titles and abstracts, followed by a full-text review based on pre-defined inclusion criteria, resulting in 17 papers using a network approach. Inductive coding was combined with deductive coding based on the collaborative resilience framework, covering diversity of actors and resources, trust and reciprocity, leadership, community buy-in and structure.

Preliminary findings reveal five core factors impeding the sustainability of inter-organizational networks: bureaucratic constraints, power imbalances, fragmented responsibilities, unclear goals and organisational turnover. Additionally, the study finds that most networks are initially centralised, facilitating coordination in the early stages. However, over time, these networks tend to decentralise as recovery efforts progress and responsibilities become more distributed.

The increasing complexity of environmental challenges highlights the need for a deeper understanding of social-ecological systems. However, conservation efforts often fail due to misalignment between ecological processes and the social, political, or institutional structures governing these ecosystems. Sustainable governance approaches should therefore account for the specific ecological conditions.

Given these complexities, forest management provides a particularly relevant context for examining social-ecological alignment. Forests are dynamic systems where ecological and social processes interact across multiple scales, requiring coordinated management strategies. Multifunctional forests face increasing demands as they must balance ecological, social, and economic objectives sustainably. In Germany, state forest management is expected to serve as a role model in addressing these objectives. However, this requires cooperation and collaboration among forest district managers, particularly for conservation efforts spanning multiple jurisdictions.

To examine these connections, we investigate the horizontal interactions between forest district managers and their alignment with ecological conditions. Specifically, we ask:

(i) To what extent do forest district managers within a state forest enterprise engage in horizontal cooperation and collaboration?

(ii) How do patterns of cooperation and collaboration among forest district managers align with ecological patterns?

(iii) How does the alignment between cooperation and collaboration patterns and ecological structures influence self-assessed performance?

We address these questions through a social-ecological network analysis, combining social network data from an online survey with ecological data on species distribution. The survey, completed by 20 out of 21 district managers, captured self-reported cooperation and collaboration patterns. Ecological patterns are understood as the abundance of species of higher management and societal concern (capercaillie, golden jackal, lynx, wolf, wildcat, partridge, and bark beetle) in the districts.

By integrating social network analysis with ecological patterns, this study provides a frame for assessing how well governance structures align with ecological conditions to support sustainable forest management. Understanding these network interactions is essential for identifying opportunities to strengthen cooperation and collaboration, potentially contributing to more resilient and and sustainable management practices.

This article examines the mechanisms through which social and environmental safeguard (SES) experts establish legitimacy in global governance, emphasizing the role of professional social networks in shaping and consolidating this emerging field of expertise. Over the past 10–15 years, SES expertise has developed at the intersection of international organizations (IOs), policy frameworks, and consultancy markets, yet its boundaries and professional norms remain fluid. Drawing on Bourdieu’s field theory and social network analysis (SNA), this study explores how SES professionals—both internal officers and external consultants—mobilize social, cultural, economic, and symbolic capital to gain recognition and authority. Through a mixed-methods approach—interviews with 25 SES experts and computational analysis of 200 LinkedIn profiles—the research uncovers patterns in professional trajectories, network formation, and reputational signaling. By analyzing how SES professionals leverage their affiliations, credentials, and digital visibility to navigate institutional hierarchies, this study sheds light on the evolving nature of expertise in development governance and the role of social networks in structuring professional legitimacy.

Global temperatures are rising and recent summers have seen more droughts, falling groundwater levels, and forest loss. This has increased awareness about preparing for climate change's effects on water management. A variety of actors is involved in the management or governance of water resources, including representatives from the private sector (e.g., farmers or industry associations), non-governmental organizations (NGOs) (e.g., environmental groups), water providers, governmental agencies or political actors in legislative or executive institutions. To achieve water security, civil society, communities, political decisionmakers, water managers and all other actors involved have to be included. Research on water issues is carried out both in the environmental sciences, more specifically hydrology, but also increasingly in the social and political sciences. However, cross-disciplinary research is still rare and underdeveloped. To address the uncertainty of future developments, scenario analysis has become state of the art in research and policy advice. We contribute with a cross-disciplinary study using cross-impact-balance (CIB) analysis. We analyse governance networks and complex policy decision-making processes combined with storylines for future climate scenarios to find efficient strategies for water resilience, adaptive capacity building and carbon reduction to support informed decision-making.

This presentation uses network approaches to analyse how oil and gas companies and host governments construct community engagement processes, with implications for political corporate social responsibility (CSR) and meaningful community engagement in environmental governance. Drawing on comparative analysis of oil exploration and extraction in Atlantic Canada and Norway, the research investigates how global frameworks—including sustainability goals (e.g., the Paris Agreement, UN SDGs,), Human Rights-Based Approaches (HRBA), Indigenous rights frameworks (e.g., UNDRIP) — are translated into regionally specific engagement networks around offshore oil development. Data sources include corporate reports, government documents, and web content. Using Discourse Network Analysis (DNA), a method integrating social network analysis and textual analysis, we examine the networks that connect engagement frameworks with corporate actors, governmental institutions, and a range of rightsholders and stakeholders including social movement organizations, labour associations, Indigenous communities, and municipalities. The findings reveal regional contrasts: the Norwegian cases emphasize environmental frameworks — with greater attention to the Paris Agreement — and corporatist networks of inclusion in engagement processes, while the Canadian case foregrounds Indigenous rights-based approaches. Across both regions, gender-based approaches remain peripheral, reflecting gaps in inclusive engagement. These distinctions illustrate how despite the aura of universalism of global engagement frameworks, these are translated into regionally-distinct networks of engagement that structure environmental governance by framing which stakeholders/rightsholders are included, as well as shaping the boundaries of climate and environmental debates. By highlighting the intersection of public engagement frameworks and rightsholder/stakeholder networks, we offer insights into equitable engagement strategies for extractive development and social-environmental sustainability.

As urban areas continue to expand, the conversion of agricultural land into urban planning zones has become an irreversible trend. However, in light of sustainability considerations, farmers’ rights, and principles of justice, this study conducted an empirical investigation in Huwei, Yunlin, Taiwan, to examine the social conflicts and contradictions arising during the transformation process and to propose rational urban design recommendations. Rice farming in Huwei began in the early 20th century, and large-scale rice paddies emerged as a definitive landscape feature after World War II. However, the recent establishment of a high-speed rail station in Huwei has influenced local land development patterns, significantly affecting urban planning and agricultural land use.

Incorporating a sustainable environmental governance framework while aligning with the United Nations Sustainable Development Goals on justice and equality, this study examined the effects of government policies and rice farming on various social groups and environmental sustainability through a social network analysis. Additionally, geographic information system overlay analysis was performed to investigate the historical context of agricultural development, the contemporary distribution of farmland, and the relationship between urban planning and land use in Huwei. Furthermore, qualitative interviews were conducted to capture the perspectives and power dynamics among different social groups. By integrating these approaches, this study aimed to propose strategies for preserving rice farming culture within urban planning zones, contributing to the planning for and development of a resilient and sustainable environment.

This study examines the impact of a major earthquake on sustainable cocoa production in rural Indonesian communities, specifically focusing on how social networks influenced farmers' adoption of agricultural practices – recommended seedling sources and fertilizers and female empowerment – and their ability to secure favorable cacao bean prices. Targeting 3,727 registered cacao farmers in Central Sulawesi, we collected socioeconomic network, agricultural, psychological, and disaster-related data. These data were combined with pre-disaster agricultural survey data from the same farmers. Results from social network analysis revealed that the earthquake significantly altered information dissemination and social influence patterns regarding agricultural practices. For instance, post-earthquake fertilizer choices in some neighboring subnetworks reversed, deviating from network clusters detected by modularity clustering algorithm. In contrast, farmers achieving higher cacao bean prices were concentrated within established social networks, indicating that access to beneficial price information relied on long-standing connections rather than newly formed ones. Differences in the damage level by the earthquake and village affiliation did not strongly predict the above changes. Further analysis using edge and node attributes explores the specific conditions that drove these changes, aiming to elucidate the factors influencing resilience and vulnerability in post-disaster agricultural communities. This study highlights the fragility of sustainable agriculture programs in the face of natural disasters and suggests the need to understand how actors on social networks adapt under extreme stress.

Understanding the dynamic interplay between human societies and ecosystems is central to achieving sustainability. Social-ecological network approaches provide a powerful framework for disentangling the complex and evolving relationships between people and ecosystems. While existing research has shown that specific social-ecological network structures can support environmental sustainability, their temporal dynamics and connections to social sustainability outcomes remain poorly understood. Using longitudinal panel data from 629 resource-dependent fishers in Kenyan coastal communities, we examined how social-ecological networks evolve and relate to material and subjective wellbeing – measuring access to resources and livelihood satisfaction, respectively. Both wellbeing measures exhibited dynamic changes but increased overall, coinciding with a growing tendency for fishers to form social relationships with others who rely on the same species, creating ‘closed social-ecological triangles’. Existing research, including in these same communities, has linked this network configuration to ecological benefits such as higher fish biomass and functional richness. However, our results from multilevel, temporal autologistic actor attribute models revealed that fishers embedded in these configurations were more likely to experience declines in subjective wellbeing over time. These findings uncover a hidden trade-off between environmental benefits and individual social outcomes, underscoring the need for governance strategies that account for the evolving and multifaceted nature of human-environment interactions to effectively navigate multiple sustainability objectives.

Keywords: sustainable food choices, food waste, responsible consumption, social influence

Food choices and sustainability awareness among university students can be analyzed by social interactions.

This study applies network analysis to explore how students’ social connections influence their knowledge and adoption of sustainable food practices within a university collective catering system.

Data have been obtained from an online survey conducted at the University of Trieste (Italy) to examine students’ eating habits, food waste behaviors, and sustainability awareness, while also mapping peer behavior on food choice and food waste.

The study aims to investigate whether social influence plays a significant role in shaping food choices and if such influence occurs mainly through horizontal (peer-to-peer) or vertical (opinion leaders/university environment/professors) networks. By applying network analysis, the aim is to explore how social connections influence the adoption of sustainable food behaviors.

This research aligns with Sustainable Development Goals (SDGs), especially with Goal 12 (Responsible Consumption and Production) offering insights into how social networks can be leveraged to promote sustainability and good practices in higher education. Moreover, findings could also support the development of targeted actions, such as educational campaigns, and to encourage responsible food consumption and reduce food waste among students and in the university canteen.

The accelerating urgency of climate change necessitates innovative strategies to integrate sustainability into supply chain management (SCM). This article bridges network theory and sustainable supply chain management (SSCM) to examine how network structures and firm-level sustainability performance interact to shape sustainable practices across complex supply chain networks. Employing a multi-scalar approach, the research spans macro-level analysis of an entire network and meso-level insights from industry-specific sectors.

The study utilizes Social Network Analysis (SNA) and Exponential Random Graph Models (ERGMs) to explore how sustainability metrics influence network connectivity, firm centrality, and tie formation. Key findings highlight the role of central firms as sustainability hubs and the significance of relational dynamics, such as homophily, in shaping collaborative behaviors.

This research contributes theoretically by integrating network theory into SSCM, offering new insights into the structural and relational dynamics critical to advancing sustainable supply chains. Practically, it provides actionable guidance for managers and policymakers, advocating for interventions such as digital traceability systems, targeted support for central firms, and collaborative platforms to foster resilience and sustainability. The findings underscore the importance of leveraging network configurations and central actors to drive systemic change, paving the way for resilient, adaptive, and sustainable supply chains aligned with global climate goals.

Transformations are prevalently difficult to grasp in their process and dynamics. In the literature they are therefore predominantly described ex-post. To better understand this social phenomenon, it is important to examine transformations, such as the energy transition, as they unfold. Particularly in complex infrastructures like electricity supply, it becomes evident how microstructural decisions generate macrostructural effects and vice versa. In this, Network analysis presents itself as a suitable methodological approach, as it allows for scale-free analysis and the dynamic representation of interdependent levels.

The goal is to make transformation processes as such more tangible. Therefore, the study addresses the research question: What needs to be mobilized in a transformation process to change the distribution of capital within the field in the desired way? By combining Bourdieu’s concept of capital with network-theoretical approaches, the study investigates how small-scale changes can lead to large-scale transformations. A case study of an energy transition living lab serves as an empirical approach to examine theoretical assumptions and explore possibilities for analysing transformations in their processualism.

The theoretical framework is defined by a targeted reduction of field structure and an expanded interpretation of Bourdieu’s concept of capital. Particular attention is given to the forms of relationships between entities within the transformation process. The study adopts a temporal perspective, analysing capital mobilization and the expansion of influence within the network over time. The results aim to provide deeper insights into the dynamics of transformation processes and enhance the understanding of their internal logics.