Sustainability

26 pages, 5970 KB

Open AccessArticle

Evolution and Drivers of the Anabranching Lower North River, Pearl River Basin, China: Insights from Remote Sensing and Hydrological Observations during 1990–2022

by Xiao Zhao, He Qing Huang, Jing Qiu, Zhilin Zhang, Qingya Li and Jingjing Zhu

Sustainability 2026, 18(3), 1706; https://doi.org/10.3390/su18031706 - 6 Feb 2026

Abstract

The Lower North River (LNR) exhibits a distinctive anabranching pattern in the Pearl River Basin, China. However, research has predominantly focused on vertical channel adjustments relying on in situ measurements, while the large-scale spatiotemporal dynamics of the anabranching planform have received limited attention. [...] Read more.

The Lower North River (LNR) exhibits a distinctive anabranching pattern in the Pearl River Basin, China. However, research has predominantly focused on vertical channel adjustments relying on in situ measurements, while the large-scale spatiotemporal dynamics of the anabranching planform have received limited attention. To address this gap, this study quantified the evolution of the anabranching planform from 1990 to 2022 using remote sensing images, focusing on anabranching intensity and island morphology, and analyzed driving factors using hydrological observations. Results revealed three evolutionary phases driven by shifting dominance of human interventions. During the first phase (1990–2004), the LNR experienced a moderate decline in anabranching intensity and widespread shrinkage of river islands, primarily attributed to sediment starvation induced by upstream dams. In the second phase (2004–2013), the decline in anabranching intensity accelerated and the proportion of expanding islands increased, driven by unregulated sand mining and channel regulation. In the third phase (2013–2022), the rapid decline in anabranching intensity decelerated and the islands shifted from a shrinkage-dominated to a stable-dominated state following the implementation of strict mining management and the physical confinement imposed by engineering structures. These findings reveal distinct morphological responses of the LNR to flow–sediment regimes and anthropogenic physical interventions, offering insights into the sustainable management of large anabranching rivers worldwide in the Anthropocene. Full article

(This article belongs to the Special Issue Sediment Movement, Sustainable Water Conservancy and Water Transport)

30 pages, 9131 KB

Open AccessArticle

Multi-Objective Optimization Design of High-Power Permanent Magnet Synchronous Motor Based on Surrogate Model

by Zhihao Zhu, Xiang Li, Yingzhi Lin, Hao Wu, Junhui Chen, Niannian Zhang, Thomas Wu, Bo Lin and Suyan Wang

Sustainability 2026, 18(3), 1705; https://doi.org/10.3390/su18031705 (registering DOI) - 6 Feb 2026

Abstract

Energy scarcity has evolved into one of the most pressing challenges confronting the global community today. Fuel-driven loaders suffer from drawbacks such as high fuel consumption, low energy conversion efficiency, and heavy pollution, which not only aggravate atmospheric environmental pollution but also exacerbate [...] Read more.

Energy scarcity has evolved into one of the most pressing challenges confronting the global community today. Fuel-driven loaders suffer from drawbacks such as high fuel consumption, low energy conversion efficiency, and heavy pollution, which not only aggravate atmospheric environmental pollution but also exacerbate the global energy crisis, directly undermining sustainable development goals. In contrast, permanent magnet synchronous motors (PMSMs) have become the preferred choice for the electrification of loaders owing to their exceptional torque density, strong overload capacity, and high reliability. However, during the optimal design of high-power interior permanent magnet synchronous motors (IPMSMs), traditional methods encounter issues with inadequate optimization efficiency and excessive computational expenses, thus hindering the large-scale deployment of power systems for eco-friendly loaders. Therefore, this paper takes a 125 kW, 3000 rpm IPMSM as the research object and proposes a multi-objective optimization strategy integrating a high-precision surrogate model with modern intelligent algorithms. This approach not only enhances motor performance but also cuts down computational overhead, which holds considerable significance for reducing industrial carbon emissions and driving the sustainable development of the manufacturing industry. Taking the key performance of IPMSM as the optimization objective and the related structural parameters as the optimization variables, the multi-performance characteristic index, interaction effect and comprehensive sensitivity of the variables are calculated and analyzed by fuzzy Taguchi experiment, and the hierarchical dimension reduction in the variables is completed. The Multicriteria Optimal-Latin Hypercube Sampling (MO-LHS) method is adopted to construct the sample data space, and a back-propagation neural network (BPNN) surrogate model is used to predict and fit the motor performance. The second-generation non-dominated sorting genetic algorithm (NSGA-II) is employed for iterative optimization, and the optimized motor dimension parameters are obtained through the Pareto optimal solution. Finally, through finite element analysis (FEA) and experiments, the rated torques obtained are 417.6 N·m and 425.1 N·m, respectively, with an error not exceeding 1.8%. This verifies the correctness and effectiveness of the proposed multi-objective optimization method based on the surrogate model. Full article

(This article belongs to the Section Energy Sustainability)

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24 pages, 580 KB

Open AccessArticle

Social Trust and Corporate Greenwashing in China: The Role of Informal Institutions for Sustainability

by Weixin Dong, Youcai Yang and Yan Chen

Sustainability 2026, 18(3), 1704; https://doi.org/10.3390/su18031704 - 6 Feb 2026

Abstract

Corporate greenwashing poses a significant challenge to global sustainability efforts. Drawing on firm-level data from China, this study explores the effect of social trust as a key informal institution on inhibiting greenwashing behavior. We find that social trust significantly reduces the level of [...] Read more.

Corporate greenwashing poses a significant challenge to global sustainability efforts. Drawing on firm-level data from China, this study explores the effect of social trust as a key informal institution on inhibiting greenwashing behavior. We find that social trust significantly reduces the level of greenwashing. Our mechanism analysis suggests that social trust restrains greenwashing primarily by enhancing corporate information transparency, alleviating managerial short-termism, and easing financial constraints. Further heterogeneity tests show that the effect is stronger in firms not audited by Big Four auditors and those without voluntary environmental disclosure, as well as in regions with weaker formal institutional environments. We also examine multidimensional trust and find that generalized trust plays a dominant role in curbing greenwashing, whereas personalized and institutional trust show limited effects. These findings highlight the importance of social capital and informal institutional forces in promoting corporate environmental accountability and advancing sustainable development goals. Full article

(This article belongs to the Special Issue Do Businesses Increase Their Value by Adopting Innovative Sustainability Practices?)

21 pages, 1499 KB

Open AccessArticle

A Conceptual Framework for Sustainable Pollution Control in Informal Economies with Generative AI

by Akira Nagamatsu, Yuji Tou and Chihiro Watanabe

Sustainability 2026, 18(3), 1703; https://doi.org/10.3390/su18031703 - 6 Feb 2026

Abstract

Intangible environmental externalities in informal economies are hard to detect, attribute, and regulate because transaction records and evidentiary trails are fragmented. This conceptual paper reframes pollution control from improving model performance to designing institutions for verifiability and examines how generative AI (GAI) can [...] Read more.

Intangible environmental externalities in informal economies are hard to detect, attribute, and regulate because transaction records and evidentiary trails are fragmented. This conceptual paper reframes pollution control from improving model performance to designing institutions for verifiability and examines how generative AI (GAI) can both strengthen and undermine that verifiability. Integrating transaction-structure theory, institutional economics, and digital-governance research, we derive four propositions: (P1) standardized, interoperable evidence and hybrid auditing allow GAI to lower verification costs; (P2) opaque, multi-tier transactions and concentrated data control enable plausible falsification; (P3) detection reduces pollution only when linked to remediation through enforcement capacity; and (P4) incentives must reward verified, not merely claimed, circularity to deter greenwashing. We illustrate feasibility and boundary conditions through three precedents: Amazon’s unit-level identifiers and sustainability labeling, India’s CPCB extended producer responsibility portal for plastic packaging, and Brazil’s nationwide e-invoicing infrastructure (NF-e/SPED). The framework offers actionable design principles, testable hypotheses, and measurable indicators (evidence linkage, audit-log completeness, time-to-remediation) for future empirical work. The framework is intended to support analytic generalization for policy and practice across contexts. Full article

(This article belongs to the Special Issue Harnessing the Digital Economy for Environmental Pollution Control: Policies, Practices, and Perspectives)

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18 pages, 408 KB

Open AccessArticle

Social Sustainability of the Teaching Profession: Pedagogical Beliefs and Pre-Service Teachers’ Digital Competence in STEAM

by Merve Şahin

Sustainability 2026, 18(3), 1702; https://doi.org/10.3390/su18031702 - 6 Feb 2026

Abstract

The integration of digital technologies into early childhood education extends beyond mere technical necessity; it constitutes a fundamental pillar of social sustainability within the teaching profession. Yet, a persistent paradox remains in teacher education: the “Attitude–Competence Gap,” where pre-service teachers’ enthusiasm for technology [...] Read more.

The integration of digital technologies into early childhood education extends beyond mere technical necessity; it constitutes a fundamental pillar of social sustainability within the teaching profession. Yet, a persistent paradox remains in teacher education: the “Attitude–Competence Gap,” where pre-service teachers’ enthusiasm for technology fails to translate into practical proficiency. This study interrogates this disconnect within a STEAM framework, specifically examining whether digital competence is driven by general technological attitudes or domain-specific pedagogical beliefs. Utilizing an explanatory sequential mixed-methods design, we analyzed data from 200 Child Development students, followed by in-depth semi-structured interviews with 15 participants who exhibited high attitudes but low initial competence. Hierarchical regression analysis yielded a critical insight: while general attitudes toward digital storytelling did not predict competence (p > 0.05), pedagogical beliefs regarding the use of children’s literature in mathematics were a strong predictor of technical proficiency (β = 0.35, p < 0.001). Qualitative evidence corroborated that students overcame technical limitations not through technological affinity but through a motivation to concretize abstract mathematical concepts via storytelling. These findings suggest that to foster sustainable STEAM education, teacher training curricula must prioritize the “why” (pedagogical conviction) over the “how” (technical mechanics), thereby closing the gap between digital intention and action. This study uniquely demonstrates that domain-specific pedagogical convictions, rather than general technological enthusiasm, are the fundamental drivers of digital competence in STEAM, providing an empirical basis for more resilient teacher education models. Full article

(This article belongs to the Special Issue Digital Learning and Sustainable STEAM Education)

23 pages, 2127 KB

Open AccessArticle

Climate Resilience Assessment in Regions, Cities, Strategic Services, and Critical Infrastructure: Implementation and Outcomes

by Rita Salgado Brito, Maria Adriana Cardoso, Ana Mendes, Anabela Oliveira, Alex de la Cruz-Coronas, Marianne Bügelmayer-Blaschek and Elena Veza

Sustainability 2026, 18(3), 1701; https://doi.org/10.3390/su18031701 - 6 Feb 2026

Abstract

Resilience to climate change is a complex concept, especially in metropolitan areas where diverse services and stakeholders interact. Promoting sustainable climate adaptation, a resilience assessment method focused on regional areas and nature-based solutions is presented, along with its open-access, web-based platform, supporting resilience [...] Read more.

Resilience to climate change is a complex concept, especially in metropolitan areas where diverse services and stakeholders interact. Promoting sustainable climate adaptation, a resilience assessment method focused on regional areas and nature-based solutions is presented, along with its open-access, web-based platform, supporting resilience assessment, planning, and monitoring. Floods, droughts, heat or cold waves, windstorms, and forest fires can be assessed. A framework for holistic assessment and other framework, addressing critical infrastructure, are integrated. Four resilience dimensions are assessed: organizational (governance, social aspects, finance); spatial (exposure, impacts, and mapping); functional (service management, interdependencies); and physical (infrastructure robustness, redundancy). Strategic services comprise, e.g., water, waste, and natural areas. Resilience capacities, e.g., to prevent, respond, and recover from disruptions, are also assessed. The paper emphasizes new developments and assessment. Practical step-by-step guidance aligned with assessment purposes is included, aiming to address observed limitations (e.g., fragmented service provision, communication silos, data constraints). Overall results of a Spanish metropolitan area (AMB) and an exploratory application to an Austrian rural case (SLR) are also presented. Following the guidelines, AMB progressed from an essential to a comprehensive assessment. Overall, almost 1/3 of the metrics are advanced or progressing. SLR assessed its resilience capabilities regarding electrical infrastructure. Full article

(This article belongs to the Special Issue Asset-Level Modelling to Achieve a Better Understanding of Climate-Related Impacts)

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18 pages, 398 KB

Open AccessArticle

Evaluation of ESG Implementation Performance in the Textile Industry from a Transparency and Accountability Perspective Based on MCDM and Cluster Analysis

by Burçin Tutcu, Güler Ferhan Ünal Uyar, Neylan Kaya, Aslıhan Ersoy Bozcuk, Mustafa Terzioğlu and Münevver Sena Özden

Sustainability 2026, 18(3), 1700; https://doi.org/10.3390/su18031700 - 6 Feb 2026

Abstract

Effective management of Environmental, Social, and Governance (ESG) practices within the framework of transparency and accountability in businesses is crucial for enhancing their compliance capacity in the face of regulatory pressures and contributing to the early detection of environmental and social risks. This [...] Read more.

Effective management of Environmental, Social, and Governance (ESG) practices within the framework of transparency and accountability in businesses is crucial for enhancing their compliance capacity in the face of regulatory pressures and contributing to the early detection of environmental and social risks. This study aims to evaluate the ESG disclosure-based performance of businesses operating in the textile, clothing, and leather sectors in Turkey by examining their ESG indicators from a transparency and accountability perspective. The CRITIC (Criteria Importance Through Intercriteria Correlation) method was used to determine the relative importance levels of the indicators, while the MABAC (Multi-Attributive Border Approximation Area Comparison) and COPRAS (Complex Proportional Assessment) methods were used to rank the performance of businesses within the framework of these indicators. Finally, clustering analysis was used to classify businesses with similar characteristics. The findings show that corporate governance principles are the most important indicator, and that Kordsa Teknik Tekstil A.Ş. and Söktaş Tekstil Sanayi ve Ticaret A.Ş. exhibit a significant and positive difference in terms of transparency and accountability in their ESG practices compared to other businesses. The combined use of CRITIC, MABAC, COPRAS, and cluster analysis offers an innovative, robust decision-making approach and holistic methodological integration for assessing ESG disclosure-based performance in the context of transparency and accountability for businesses. Full article

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29 pages, 529 KB

Open AccessArticle

Perceived Data and Privacy Security Threats for Stakeholders in the Context of Industry 5.0: Evidence from Poland

by Dominika Kansy and Dagmara Modrzejewska

Sustainability 2026, 18(3), 1699; https://doi.org/10.3390/su18031699 - 6 Feb 2026

Abstract

This article scientifically addresses the challenges related to data security and stakeholder privacy faced by companies operating in the European Union. These challenges stem largely from the global digital transformation, within which the European Union imposes regulations governing data protection and stakeholder privacy. [...] Read more.

This article scientifically addresses the challenges related to data security and stakeholder privacy faced by companies operating in the European Union. These challenges stem largely from the global digital transformation, within which the European Union imposes regulations governing data protection and stakeholder privacy. The digital transformation in the European Union focuses on the integration of people and technology, sustainable development, and the resilience of management systems, which are the pillars of Industry 5.0. From a practical perspective, the paper examines the current level of awareness among employees of the enterprise in Poland regarding data and privacy risk management in today’s economic environment. The paper presents both a theoretical review and, in the empirical section, the results of primary research. The study was conducted in Poland on a sample of 556 enterprises from various economic sectors. The paper begins with Introduction. Background presents a literature review conducted on the conditions for enterprise functioning in the evolving paradigm of Industry 5.0, as well as the fundamental legal requirements regarding data security and stakeholder privacy across business activities. Materials and Methods presents the research methods employed to assess how respondents perceive threats to data security and stakeholder privacy. Results summarizes the research findings. In Discussion, both practical business implications are addressed, and the role of technology and organizational procedures in responsible data and privacy management is highlighted. Furthermore, the importance of creating ethical cyber–physical environments as an element of sustainable enterprise transformation is emphasized. Finally, Conclusions presents the results and key findings regarding the level of awareness among employees of Polish enterprises about data security and stakeholder privacy in the context of digital transformation. Full article

20 pages, 2643 KB

Open AccessArticle

An Operation Mode Analysis Method for Power Systems with High-Proportion Renewable Energy Integration Based on Autoencoder Clustering

by Ying Zhao, Lianle Qin, Liangsong Zhou, Huaiyuan Zong and Xinxin Guo

Sustainability 2026, 18(3), 1698; https://doi.org/10.3390/su18031698 - 6 Feb 2026

Abstract

With the integration of high-proportion renewable energy, the operation modes of the power system are becoming increasingly complex and diverse. The typical operation modes selected with manual experience cannot comprehensively represent system operating characteristics. To more accurately analyze system operating characteristics, an analysis [...] Read more.

With the integration of high-proportion renewable energy, the operation modes of the power system are becoming increasingly complex and diverse. The typical operation modes selected with manual experience cannot comprehensively represent system operating characteristics. To more accurately analyze system operating characteristics, an analysis method for power system operation modes based on autoencoder clustering is proposed. Compared to other clustering methods, the autoencoder clustering method can adapt to data of different types and structures, extract features and perform clustering in a reduced-dimensional space, and suppress noise in the data to a certain extent. First, multi-dimensional analysis metrics for power system operation modes are proposed. The metrics are used to evaluate system characteristics such as cleanliness, security, flexibility, and adequacy. The evaluation metrics for clustering are designed based on the metrics. Second, an operation mode analysis framework is constructed. The framework uses an autoencoder to extract implicit coupling relationships between system operation variables. The encoded feature vectors are used for clustering, which helps to find the internal similarities of the operation modes. Regulation resources such as pumped hydro storage are also considered in the framework. Finally, the proposed method is tested on the IEEE 39-node system. In the test, the comparison of clustering evaluation metrics and operation mode analysis errors shows that the proposed method has the best clustering performance and operation mode analysis effect compared to other clustering methods. The results prove that the proposed method can effectively extract the inner correlations and coupling relations of high-dimensional operating vectors, form consistent operation mode clusters, select typical operation modes, and accurately assess the characteristics and risks of the power system with high-proportion renewable energy integration. This paper helps to build a stronger power system that can integrate a higher proportion of renewable energy, replace fossil fuel generation, and contribute to a higher level of sustainable development. Full article

(This article belongs to the Special Issue Advanced Planning, Operation and Control Methods for Sustainable Power Systems)

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29 pages, 7083 KB

Open AccessArticle

Assessing the Vulnerability of Water and Wastewater Infrastructure to Climate Change for Sustainable Urban Development

by Aldona Skotnicka-Siepsiak, Joanna Gil-Mastalerczyk, Piotr Knyziak, Monika Mackiewicz, Romuald Szeląg and Michał Bednarczyk

Sustainability 2026, 18(3), 1697; https://doi.org/10.3390/su18031697 - 6 Feb 2026

Abstract

Climate change increasingly affects the sustainability and reliability of urban water and wastewater infrastructure. This study analyzes the relationship between climatic variables and the frequency of failures in water and sewage networks in northeastern Poland, using operational data from the Mrągowo system (2020–2023) [...] Read more.

Climate change increasingly affects the sustainability and reliability of urban water and wastewater infrastructure. This study analyzes the relationship between climatic variables and the frequency of failures in water and sewage networks in northeastern Poland, using operational data from the Mrągowo system (2020–2023) and meteorological records from 1966 to 2023. Statistical analyses and trend assessments were employed to identify climate-related failure patterns and infrastructure vulnerabilities. Climatic parameters—including temperature extremes, precipitation, snow cover, and sunshine duration—were analyzed in relation to infrastructure reliability. The results indicate rising temperatures, reduced snowfall, and altered precipitation regimes. Although extreme cold corresponded with increased sewage network failures, no significant association was found for high temperatures. Precipitation and snow cover showed weak correlations, except during heavy rainfall events. The study highlights the need to integrate climate resilience into water infrastructure management through preventive maintenance, smart monitoring, and nature-based solutions. Findings contribute to sustainable urban development strategies by demonstrating how climate variability directly affects service reliability. By identifying climate-sensitive failure thresholds, the study supports sustainable infrastructure management by enabling risk-informed adaptation strategies that reduce service disruptions, resource losses, and environmental impacts. This case study offers methodological insights and empirical evidence that may support the assessment of climate-related vulnerability of water and wastewater infrastructure in similar urban contexts. Full article

32 pages, 1931 KB

Open AccessArticle

Novel Safety Index Calculation Models for Ship Collision Risk Assessment to Enable Sustainable Maritime Transportation

by Muhamad Imam Firdaus, Muhammad Badrus Zaman and Raja Oloan Saut Gurning

Sustainability 2026, 18(3), 1696; https://doi.org/10.3390/su18031696 - 6 Feb 2026

Abstract

Maritime safety is a key element of sustainable maritime transportation, particularly in strait regions with dense vessel traffic and dynamic environmental conditions that increase collision risk. Based on historical records, ship collisions can result in severe human casualties, environmental pollution, cargo and infrastructure [...] Read more.

Maritime safety is a key element of sustainable maritime transportation, particularly in strait regions with dense vessel traffic and dynamic environmental conditions that increase collision risk. Based on historical records, ship collisions can result in severe human casualties, environmental pollution, cargo and infrastructure damage, operational disruptions, and substantial economic losses; therefore, a reliable and integrated safety assessment is essential to support safe, efficient, and sustainable maritime transportation. This study proposes a novel safety index framework to assess the ship’s collision risk by integrating vessel characteristics, ship encounter conditions, operational time parameters, and oceanographic factors such as currents and waves. The analysis is based on questionnaire data, AIS records, and oceanographic information collected over a one-month period with a three-minute temporal resolution. Case studies are conducted in the Bali Strait and the Lombok Strait using grid-based spatial segmentation to represent spatial risk patterns. Two safety index models are developed. Model I emphasizes vessel, encounter, and temporal factors, while Model II extends the assessment by fully integrating oceanographic conditions. To improve interpretability and practical applicability, the calculated safety index is further transformed into a normalized safety index with values bounded between 0 and 1, allowing for explicit risk classification. A multivariate contribution analysis is applied to identify dominant risk factors. The results show that the maritime risk in both straits is mainly influenced by vessel traffic intensity, sailing hours, days of the week, and environmental conditions. High-risk zones in the Bali Strait are concentrated near Ketapang and Gilimanuk Ports, while elevated risks in the Lombok Strait are observed near Padangbai and Lembar Ports and along the ALKI II shipping route. Full article

(This article belongs to the Section Sustainable Transportation)

21 pages, 152252 KB

Open AccessArticle

Urban Heat Island: Assessing the Influence of Urban Morphology on Air and Surface Temperatures

by Reyhaneh Zeynali, Emanuele Mandanici and Gabriele Bitelli

Sustainability 2026, 18(3), 1695; https://doi.org/10.3390/su18031695 - 6 Feb 2026

Abstract

This study investigates the interplay between urban morphology, vegetation, and thermal environments by integrating mobile air temperature (AT) measurements with satellite-derived land surface temperature (LST). The case study is the city of Bologna (Italy). Correlation analysis revealed strong multicollinearity among morphological indicators, with [...] Read more.

This study investigates the interplay between urban morphology, vegetation, and thermal environments by integrating mobile air temperature (AT) measurements with satellite-derived land surface temperature (LST). The case study is the city of Bologna (Italy). Correlation analysis revealed strong multicollinearity among morphological indicators, with building density and floor area ratio nearly collinear, while vegetation cover (PV) remained the most independent predictor. A composite urban density indicator (CUDI), derived through principal component analysis, was introduced to address redundancy among morphological metrics. Ordinary least squares regressions demonstrated significant associations, with PV exerting a pronounced cooling effect and CUDI amplifying both AT and LST. Model diagnostics confirmed statistical robustness, though residual spatial autocorrelation necessitated spatial regression approaches. Spatial lag models (SLMs) substantially improved explanatory power, highlighting spatial spillovers and neighborhood effects as central to understanding urban heat dynamics. Comparative analysis with spatial error models reinforced the dominance of SLM in capturing localized dependencies. Despite limitations in spatial coverage, temporal scope, and indicator transferability, findings emphasize the critical roles of vegetation and urban compactness in shaping thermal environments. This work underscores the necessity of integrating greening strategies with urban form management for effective heat mitigation and provides a methodological framework for analyzing urban heat islands through multi-source thermal and morphological data. Full article

(This article belongs to the Special Issue Measurement Systems, Models, Tools, and Innovative Techniques for Sustainable Urban Planning and Regeneration)

21 pages, 952 KB

Open AccessArticle

Institutional Pressure and Seafarers’ Rights Protection: The Mediating Role of ESG Strategy in the Chinese Shipping Industry

by Shouchao Zhu, Xingguo Cao, Bin Dong and Junghwan Choi

Sustainability 2026, 18(3), 1694; https://doi.org/10.3390/su18031694 - 6 Feb 2026

Abstract

Moving beyond passive legal compliance is a critical challenge for the global shipping industry in protecting seafarers’ rights. Drawing on interviews with 32 Chinese shipping executives, this study conceptualizes Environmental, Social, and Governance (ESG) strategy not merely as a disclosure tool, but as [...] Read more.

Moving beyond passive legal compliance is a critical challenge for the global shipping industry in protecting seafarers’ rights. Drawing on interviews with 32 Chinese shipping executives, this study conceptualizes Environmental, Social, and Governance (ESG) strategy not merely as a disclosure tool, but as a critical “governance translation” mechanism. We propose a theoretical model where external accountability pressures drive the institutionalization of seafarers’ rights protection (SRP), mediated effectively by corporate ESG engagement. We find that this process is positively moderated by three boundary conditions: the localization of international conventions, the intensity of Port State Control (PSC) enforcement, and the maturity of organizational governance. Practically, the findings suggest that policymakers should prioritize the clear localization of international standards to reduce ambiguity. For managers, the study demonstrates that embedding SRP into board oversight and digital monitoring systems is essential for transforming labor rights from a cost center into a sustainable strategic advantage. Full article

(This article belongs to the Special Issue Sustainable Management of Shipping, Ports and Logistics)

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21 pages, 2370 KB

Open AccessArticle

Dynamic State Estimation for Sustainable Distribution Systems Considering Data Correlation and Noise Adaptiveness

by Qihui Chen, Yifan Su, Bo Hu, Changzheng Shao, Longxun Xu and Chenkai Huang

Sustainability 2026, 18(3), 1693; https://doi.org/10.3390/su18031693 - 6 Feb 2026

Abstract

The integration of distributed renewable energy sources into distribution networks is a key approach to achieving sustainable and low-carbon power systems. However, high renewable penetration significantly increases the volatility and uncertainty of distribution systems, posing challenges to renewable energy accommodation and reliable operation. [...] Read more.

The integration of distributed renewable energy sources into distribution networks is a key approach to achieving sustainable and low-carbon power systems. However, high renewable penetration significantly increases the volatility and uncertainty of distribution systems, posing challenges to renewable energy accommodation and reliable operation. To address these challenges, active control of distribution networks is required, which in turn relies on accurate system states. In practice, the limited number and accuracy of measurement devices in distribution networks make dynamic state estimation a critical technology for sustainable distribution systems. In this paper, a novel dynamic state estimation method for sustainable distribution systems is proposed, incorporating spatiotemporal data correlation and adaptiveness to process and measurement noise. A CNN-BiGRU-Attention model is developed to reconstruct high-accuracy real-time pseudo-measurements, compensating for insufficient sensing infrastructure. Furthermore, a noise adaptive dynamic state estimation method is proposed based on an improved unscented Kalman filter. An amplitude modulation factor (AMF) is applied to track time-varying process noise, while an evaluation method based on robust Mahalanobis distance (RMD) is embedded to deal with non-Gaussian measurement noise. Finally, simulation studies on the IEEE 33-bus three-phase unbalanced distribution network demonstrate the effectiveness and robustness of the proposed method. Full article

(This article belongs to the Special Issue Operation and Control of Sustainable Power and Renewable Energy Systems)

25 pages, 475 KB

Open AccessArticle

Employee Benefits Supporting Well-Being at the Intersection of Meaning and Cost: A Sustainability Perspective from Generation Z

by Ümit Deniz İlhan and Damla Nurcan Özkılınç

Sustainability 2026, 18(3), 1692; https://doi.org/10.3390/su18031692 - 6 Feb 2026

Abstract

This study examines how employee benefit practices link employee well-being with financial sustainability in sustainable organization management. Focusing on Generation Z, it investigates the intersection between meaning attributed to employee benefits and managerial decision-making guided by financial rationality. Drawing on human resources management [...] Read more.

This study examines how employee benefit practices link employee well-being with financial sustainability in sustainable organization management. Focusing on Generation Z, it investigates the intersection between meaning attributed to employee benefits and managerial decision-making guided by financial rationality. Drawing on human resources management (HRM) and finance perspectives, employee benefits are conceptualized as mechanisms for balancing human-centered value creation and economic resilience. A qualitative design was used, based on semi-structured interviews with 15 Generation Z employees and 20 human resources (HR) and finance managers in Türkiye. Data were analyzed through thematic analysis and the Gioia methodology to develop an inductive, multi-level framework. The findings indicate that Generation Z employees view employee benefits as psychosocial resources reflecting justice, autonomy, psychological safety, and value alignment—core components of subjective and eudaimonic well-being—while managers assess them primarily through financial sustainability logics such as cost control and return on investment. Overall, meaning- and cost-oriented perspectives emerge as mutually reinforcing within sustainable organizational systems. The study proposes the Meaning–Cost Balance (MCB) Framework, conceptualizing employee benefits as a strategic management mechanism aligning employee well-being with financial resilience. Positioned at the intersection of HRM and financial sustainability, the framework contributes to sustainable organization management and offers a transferable basis for future comparative research. Full article

(This article belongs to the Special Issue Sustainable Organization Management and Entrepreneurial Leadership)

35 pages, 2261 KB

Open AccessArticle

Green Finance and Urban Ecological Resilience: Institutional, Technological, and Behavioral Mechanisms

by Xiaoyong Zhou, Yingying Dong, Zaozhuang Liao and Zhengbo Peng

Sustainability 2026, 18(3), 1691; https://doi.org/10.3390/su18031691 - 6 Feb 2026

Abstract

Building resilient cities that can survive, adapt, and thrive amid climate and ecological challenges has become a global priority, yet achieving this goal requires adequate financial support. This study investigates the impact of green finance on urban ecological resilience (UER) by exploiting the [...] Read more.

Building resilient cities that can survive, adapt, and thrive amid climate and ecological challenges has become a global priority, yet achieving this goal requires adequate financial support. This study investigates the impact of green finance on urban ecological resilience (UER) by exploiting the establishment of China’s Green Finance Reform and Innovation Pilot Zones (GFPZs) as a policy shock. Using a DPSIR-based (driving force–pressure–state–impact–response) evaluation framework and a staggered difference-in-differences approach with panel data from 277 cities (2011–2022), the empirical results show that (1) the GFPZ policy significantly enhances UER; (2) green finance improves UER through three transmission channels—government environmental governance, green technological innovation, and public environmental participation; (3) the policy effects display clear spatial and structural heterogeneity, with stronger impacts in southern, less-developed, and non-traditional industrial cities, as well as positive local effects, negative spatial spillovers, and significant synergies with national big data pilot zones. This study clarifies how financial instruments contribute to building resilient cities and offers insights for embedding green finance into urban ecological strategies. Full article

(This article belongs to the Topic Advances in Urban Resilience for Sustainable Futures)

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30 pages, 2958 KB

Open AccessArticle

Bridging the Theory–Practice Gap: A Design Methodology for Green Infrastructure Implementation in Mid-Adriatic Coastal Cities

by Timothy D. Brownlee, Simone Malavolta and Graziano Enzo Marchesani

Sustainability 2026, 18(3), 1690; https://doi.org/10.3390/su18031690 - 6 Feb 2026

Abstract

Green Infrastructure (GI) is crucial for urban climate adaptation, providing ecosystem services like mitigating the urban heat island effect and enhancing stormwater management, alongside benefits for public health and biodiversity. Effective GI implementation remains challenging, particularly in dense, rapidly urbanized mid-Adriatic coastal cities, [...] Read more.

Green Infrastructure (GI) is crucial for urban climate adaptation, providing ecosystem services like mitigating the urban heat island effect and enhancing stormwater management, alongside benefits for public health and biodiversity. Effective GI implementation remains challenging, particularly in dense, rapidly urbanized mid-Adriatic coastal cities, classified as climate hotspots like other Mediterranean contexts. This paper presents a replicable applied trans-scalar methodology for detailed GI design scenarios, developed through the EU-funded LIFE+ A_GreeNet project to bridge the theory–practice gap and enable pilot implementations in multiple Italian mid-Adriatic coastal municipalities. The research details a comprehensive, multi-disciplinary, five-phase process applied to the Sant’Antonio district of San Benedetto del Tronto—a dense, trafficked urban area projected to face “extremely strong heat stress” by 2050. Design interventions included spatial optimization, strategic species replacement, the creation of vegetated bioretention basins, and systematic pavement de-sealing. The application of the model demonstrated significant improvements: a substantial increase in permeable surface area (+194%), a measurable reduction in the UTCI index (average ENVI-MET simulated reduction of 1.17 °C by 2030), and a series of benefits resulting from increased green space and enhanced meteorological water management. This research offers local authorities a tangible model to accelerate climate-adaptive solutions, showing how precise GI design creates resilient, comfortable, and human-centered urban spaces. Full article

(This article belongs to the Special Issue Critical Thinking and Practices in Climate Change and Environmental Policy)

28 pages, 1010 KB

Open AccessArticle

Prioritization of Disruptive Risks in Sustainable Closed-Loop Manufacturing Supply Chains

by Wogiye Wube, Eshetie Berhan, Gezahegn Tesfaye, Tsega Y. Melesse and Pier Francesco Orrù

Sustainability 2026, 18(3), 1689; https://doi.org/10.3390/su18031689 - 6 Feb 2026

Abstract

Manufacturing industries are increasingly applying sustainable closed-loop supply chains (CLSCs) to meet economic, environmental, and societal goals. The increasing complexity and interdependence associated with the sustainability CLSCs make them highly vulnerable to disruption risks that threaten continuity and sustainability. However, prior studies fall [...] Read more.

Manufacturing industries are increasingly applying sustainable closed-loop supply chains (CLSCs) to meet economic, environmental, and societal goals. The increasing complexity and interdependence associated with the sustainability CLSCs make them highly vulnerable to disruption risks that threaten continuity and sustainability. However, prior studies fall short of guiding how disruption risks in sustainable CLSCs can be systematically prioritized under uncertainty in a stable and decision-relevant manner. To fill this literature void, this study develops a hybrid of the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy-TOPSIS) method and the genetic algorithm (GA) technique to prioritize disruption risks under uncertainty. Triangular fuzzy numbers are used to capture the imprecision of 13 experts from industry and academia, whereas the GA technique used aimed to improve stability and reduce the variability commonly observed in conventional fuzzy multi-criteria decision-making methods. The method is validated through a real-world case study, identifying supplier disruption risk, route disruption risk, and industrial accidents as the most critical risks. Moreover, sensitivity analysis is conducted to validate the robustness of GA-based Fuzzy-TOPSIS, demonstrating its superior stability and reliability compared to the classical Fuzzy-TOPSIS method in uncertain environments. The novelty of this study lies in embedding a GA-driven approach within the fuzzy-TOPSIS structure to explicitly address ranking instability under uncertainty in sustainable CLSCs. The study provides significant theoretical contributions by enhancing multi-attribute decision-making regarding disruption risk in sustainable CLSC literature, as well as practical insights for decision-makers to efficiently allocate resources by focusing mitigation investments on consistently high-priority risks instead of low-priority ones. Full article

(This article belongs to the Special Issue Innovative Technologies for Sustainable Industrial Systems)

22 pages, 5908 KB

Open AccessArticle

Mapping Metropolitan Structures with Digital Models as a Supporting Tool in Spatial and Strategical Planning—The Case Study of the GZM Metropolis

by Tomasz Bradecki, Krzysztof Kafka, Agnieszka Majorek-Gdula, Błażej Mól and Paulina Miszczak

Sustainability 2026, 18(3), 1688; https://doi.org/10.3390/su18031688 - 6 Feb 2026

Abstract

This study presents the results of comprehensive functional-spatial analyses conducted using cellular models in relation to the cities of the GZM Metropolis and its surroundings. The Abbreviation “GZM” stands for Górnośląsko-Zagłębiowska Metropolia, due to its location, which in English has been recognized as [...] Read more.

This study presents the results of comprehensive functional-spatial analyses conducted using cellular models in relation to the cities of the GZM Metropolis and its surroundings. The Abbreviation “GZM” stands for Górnośląsko-Zagłębiowska Metropolia, due to its location, which in English has been recognized as the GZM Metropolis. The GZM Metropolis, the largest metropolitan area in Poland, has a complex administrative and spatial structure that includes 41 very diverse municipalities, which poses a significant challenge in interpreting data and understanding its complexity. The research was conducted by a multi-person and interdisciplinary team using various tools, including geographic information systems (GIS) and statistical data. The spatial models built on the basis of the collected data were visualized using augmented reality tools to facilitate data interpretation. Special attention was paid to environmental aspects, especially blue-green infrastructure, which plays a key role in maintaining this heavily urbanized area. Furthermore, the authors developed urbanization scenario models for the GZM Metropolis based on their own approaches to cellular modeling and examined the integration of artificial intelligence techniques to further refine these forecasts. Full article

(This article belongs to the Special Issue Measurement Systems, Models, Tools, and Innovative Techniques for Sustainable Urban Planning and Regeneration)

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