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Search Results (1,955)

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Keywords = international competitiveness

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18 pages, 313 KiB  
Article
Sustainability and Profitability of Large Manufacturing Companies
by Iveta Mietule, Rasa Subaciene, Jelena Liksnina and Evalds Viskers
J. Risk Financial Manag. 2025, 18(8), 439; https://doi.org/10.3390/jrfm18080439 - 6 Aug 2025
Abstract
This study explores whether sustainability achievements—proxied through ESG (environmental, social, and governance) reporting—are associated with superior financial performance in Latvia’s manufacturing sector, where ESG maturity remains low and institutional readiness is still emerging. Building on stakeholder, legitimacy, signal, slack resources, and agency theories, [...] Read more.
This study explores whether sustainability achievements—proxied through ESG (environmental, social, and governance) reporting—are associated with superior financial performance in Latvia’s manufacturing sector, where ESG maturity remains low and institutional readiness is still emerging. Building on stakeholder, legitimacy, signal, slack resources, and agency theories, this study applies a mixed-method approach (that consists of two analytical stages) suited to the limited availability and reliability of ESG-related data in the Latvian manufacturing sector. Financial indicators from three large firms—AS MADARA COSMETICS, AS Latvijas Finieris, and AS Valmiera Glass Grupa—are compared with industry averages over the 2019–2023 period using independent sample T-tests. ESG integration is evaluated through a six-stage conceptual schema ranging from symbolic compliance to performance-driven sustainability. The results show that AS MADARA COSMETICS, which demonstrates advanced ESG integration aligned with international standards, significantly outperforms its industry in all profitability metrics. In contrast, the other two companies remain at earlier ESG maturity stages and show weaker financial performance, with sustainability disclosures limited to general statements and outdated indicators. These findings support the synergy hypothesis in contexts where sustainability is internalized and operationalized, while also highlighting structural constraints—such as resource scarcity and fragmented data—that may limit ESG-financial alignment in post-transition economies. This study offers practical guidance for firms seeking competitive advantage through strategic ESG integration and recommends policy actions to enhance ESG transparency and performance in Latvia, including performance-based reporting mandates, ESG data infrastructure, and regulatory alignment with EU directives. These insights contribute to the growing empirical literature on ESG effectiveness under constrained institutional and economic conditions. Full article
(This article belongs to the Section Business and Entrepreneurship)
29 pages, 1125 KiB  
Article
Orchestrating Power: The Cultural–Institutional Nexus and the Rise of Digital Innovation Ecosystems in Great Power Rivalry
by Deganit Paikowsky, Dmitry Payson and Yaacov Falkov
Systems 2025, 13(8), 643; https://doi.org/10.3390/systems13080643 - 1 Aug 2025
Viewed by 356
Abstract
This article examines how digital innovation ecosystems have emerged as strategic institutions of power in contemporary world politics. It argues that, unlike Cold War technological rivalries driven by centralized, state-led control, today’s digital competition depends on states’ capacity to orchestrate scalable, multistakeholder ecosystems. [...] Read more.
This article examines how digital innovation ecosystems have emerged as strategic institutions of power in contemporary world politics. It argues that, unlike Cold War technological rivalries driven by centralized, state-led control, today’s digital competition depends on states’ capacity to orchestrate scalable, multistakeholder ecosystems. Using a cultural–institutional framework, we explain how differences in strategic culture and institutional governance impact the ecosystem’s vitality and performance. A qualitative comparative analysis of the United States, China, and Russia reveals that constructive orchestration, aligning state institutions with generative, commercial-to-national innovation flows, enhances digital leadership, whereas rigid, obstructive governance limits it. This highlights ecosystem governance as a critical dimension of statecraft in the digital age. The findings underscore that the positions of great powers in the global technological hierarchy depend not only on resources or capabilities but also on the effectiveness of ecosystem governance as an evolving instrument of geopolitical power. Full article
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34 pages, 1543 KiB  
Article
Smart Money, Greener Future: AI-Enhanced English Financial Text Processing for ESG Investment Decisions
by Junying Fan, Daojuan Wang and Yuhua Zheng
Sustainability 2025, 17(15), 6971; https://doi.org/10.3390/su17156971 - 31 Jul 2025
Viewed by 213
Abstract
Emerging markets face growing pressures to integrate sustainable English business practices while maintaining economic growth, particularly in addressing environmental challenges and achieving carbon neutrality goals. English Financial information extraction becomes crucial for supporting green finance initiatives, Environmental, Social, and Governance (ESG) compliance, and [...] Read more.
Emerging markets face growing pressures to integrate sustainable English business practices while maintaining economic growth, particularly in addressing environmental challenges and achieving carbon neutrality goals. English Financial information extraction becomes crucial for supporting green finance initiatives, Environmental, Social, and Governance (ESG) compliance, and sustainable investment decisions in these markets. This paper presents FinATG, an AI-driven autoregressive framework for extracting sustainability-related English financial information from English texts, specifically designed to support emerging markets in their transition toward sustainable development. The framework addresses the complex challenges of processing ESG reports, green bond disclosures, carbon footprint assessments, and sustainable investment documentation prevalent in emerging economies. FinATG introduces a domain-adaptive span representation method fine-tuned on sustainability-focused English financial corpora, implements constrained decoding mechanisms based on green finance regulations, and integrates FinBERT with autoregressive generation for end-to-end extraction of environmental and governance information. While achieving competitive performance on standard benchmarks, FinATG’s primary contribution lies in its architecture, which prioritizes correctness and compliance for the high-stakes financial domain. Experimental validation demonstrates FinATG’s effectiveness with entity F1 scores of 88.5 and REL F1 scores of 80.2 on standard English datasets, while achieving superior performance (85.7–86.0 entity F1, 73.1–74.0 REL+ F1) on sustainability-focused financial datasets. The framework particularly excels in extracting carbon emission data, green investment relationships, and ESG compliance indicators, achieving average AUC and RGR scores of 0.93 and 0.89 respectively. By automating the extraction of sustainability metrics from complex English financial documents, FinATG supports emerging markets in meeting international ESG standards, facilitating green finance flows, and enhancing transparency in sustainable business practices, ultimately contributing to their sustainable development goals and climate action commitments. Full article
25 pages, 516 KiB  
Article
Exploring a Sustainable Pathway Towards Enhancing National Innovation Capacity from an Empirical Analysis
by Sylvia Novillo-Villegas, Ana Belén Tulcanaza-Prieto, Alexander X. Chantera and Christian Chimbo
Sustainability 2025, 17(15), 6922; https://doi.org/10.3390/su17156922 - 30 Jul 2025
Viewed by 239
Abstract
Innovation is a strategic driver of sustainable competitive advantage and long-term economic growth. This study proposes an empirical framework to support the sustained development of national innovation capacity by examining key enabling factors. Drawing on an extensive review of the literature, the research [...] Read more.
Innovation is a strategic driver of sustainable competitive advantage and long-term economic growth. This study proposes an empirical framework to support the sustained development of national innovation capacity by examining key enabling factors. Drawing on an extensive review of the literature, the research investigates the interrelationships among governmental support (GS), innovation agents (IA), university–industry R&D collaborations (UIRD), and innovation cluster development (ICD), and their influence on two critical innovation outcomes, knowledge creation (KC) and knowledge diffusion (KD). Using panel data from G7 countries spanning 2008 to 2018, sourced from international organizations such as the World Bank, the World Intellectual Property Organization, and the World Economic Forum, the study applies regression analysis to test the proposed conceptual model. Results highlight the foundational role of GS in providing a balanced framework to foster collaborative networks among IA and enhancing the effectiveness of UIRD. Furthermore, IA emerges as a pivotal actor in advancing innovation efforts, while the development of innovation clusters is shown to selectively enhance specific innovation outcomes. These findings offer theoretical and practical contributions for policymakers, researchers, and stakeholders aiming to design supportive ecosystems that strengthen sustainable national innovation capacity. Full article
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26 pages, 836 KiB  
Article
The Impact of Organizational Agility on the Sustainable Development of the Organization in the Context of Economy 5.0
by Artur Kwasek, Maria Kocot, Stanisław Rodowicki, Krzysztof Kandefer, Marika Szymańska, Dariusz Soboń and Adrianna Trzaskowska-Dmoch
Sustainability 2025, 17(15), 6907; https://doi.org/10.3390/su17156907 - 30 Jul 2025
Viewed by 300
Abstract
The aim of this article is to identify key factors shaping organizational agility as a determinant of the sustainable development of an organization in the conditions of Economy 5.0. The research used the survey method conducted in 2024 on a sample of 312 [...] Read more.
The aim of this article is to identify key factors shaping organizational agility as a determinant of the sustainable development of an organization in the conditions of Economy 5.0. The research used the survey method conducted in 2024 on a sample of 312 respondents. It analyzed the impact of decision-making processes, identification with the goals of the organization, tolerance of rapid changes, internal communication, internal motivation and implementation of the idea of work–life balance. Based on the results, an original mathematical model was constructed presenting the relationships between the analyzed variables. The research results confirmed a significant relationship between the level of organizational agility and the ability of the organization to implement the sustainable development strategy. It was identified that factors such as quick and accurate decision-making, strong identification of employees with the goals of the organization and efficient communication have the greatest impact on strengthening this ability. The limitation of the research was the homogeneity of the sample and the inability to fully take into account variables related to the industry and cultural context. The research highlights that enhancing organizational agility is crucial for achieving sustainable development and building lasting competitive advantage in the dynamic context of the Economy 5.0. Full article
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19 pages, 5927 KiB  
Article
Modeling the Anti-Adhesive Role of Punicalagin Against Listeria Monocytogenes from the Analysis of the Interaction Between Internalin A and E-Cadherin
by Lorenzo Pedroni, Sergio Ghidini, Javier Vázquez, Francisco Javier Luque and Luca Dellafiora
Int. J. Mol. Sci. 2025, 26(15), 7327; https://doi.org/10.3390/ijms26157327 - 29 Jul 2025
Viewed by 301
Abstract
Listeria monocytogenes poses health threats due to its resilience and potential to cause severe infections, especially in vulnerable populations. Plant extracts and/or phytocomplexes have demonstrated the capability of natural compounds in mitigating L. monocytogenes virulence. Here we explored the suitability of a computational [...] Read more.
Listeria monocytogenes poses health threats due to its resilience and potential to cause severe infections, especially in vulnerable populations. Plant extracts and/or phytocomplexes have demonstrated the capability of natural compounds in mitigating L. monocytogenes virulence. Here we explored the suitability of a computational pipeline envisioned to identify the molecular determinants for the recognition between the bacterial protein internalin A (InlA) and the human E-cadherin (Ecad), which is the first step leading to internalization. This pipeline consists of molecular docking and extended atomistic molecular dynamics simulations to identify key interaction clusters between InlA and Ecad. It exploits this information in the screening of chemical libraries of natural compounds that might competitively interact with InIA and hence impede the formation of the InIA–Ecad complex. This strategy was effective in providing a molecular model for the anti-adhesive activity of punicalagin and disclosed two natural phenolic compounds with a similar interaction pattern. Besides elucidating key aspects of the mutual recognition between InIA and Ecad, this study provides a molecular basis about the mechanistic underpinnings of the anti-adhesive action of punicalagin that enable application against L. monocytogenes. Full article
(This article belongs to the Special Issue Computational Approaches for Protein Design)
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36 pages, 7410 KiB  
Review
The Influence of Hydrogen Bonding in Wood and Its Modification Methods: A Review
by Ting Zhang, Yudong Hu, Yanyan Dong, Shaohua Jiang and Xiaoshuai Han
Polymers 2025, 17(15), 2064; https://doi.org/10.3390/polym17152064 - 29 Jul 2025
Viewed by 337
Abstract
Construction wood has a high economic value, and its construction waste also has multiple consumption values. Natural wood has many advantages, such as thermal, environmental, and esthetic properties; however, wood sourced from artificial fast-growing forests is found to be deficient in mechanical strength. [...] Read more.
Construction wood has a high economic value, and its construction waste also has multiple consumption values. Natural wood has many advantages, such as thermal, environmental, and esthetic properties; however, wood sourced from artificial fast-growing forests is found to be deficient in mechanical strength. This shortcoming makes it less competitive in certain applications, leading many markets to remain dominated by non-renewable materials. To address this issue, various modification methods have been explored, with a focus on enhancing the plasticity and strength of wood. Studies have shown that hydrogen bonds in the internal structure of wood have a significant impact on its operational performance. Whether it is organic modification, inorganic modification, or a combination thereof, these methods will lead to a change in the shape of the hydrogen bond network between the components of the wood or will affect the process of its breaking and recombination, while increasing the formation of hydrogen bonds and related molecular synergistic effects and improving the overall operational performance of the wood. These modification methods not only increase productivity and meet the needs of efficient use and sustainable environmental protection but also elevate the wood industry to a higher level of technological advancement. This paper reviews the role of hydrogen bonding in wood modification, summarizes the mechanisms by which organic, inorganic, and composite modification methods regulate hydrogen bond networks, discusses their impacts on wood mechanical properties, dimensional stability, and environmental sustainability, and provides an important resource for future research and development. Full article
(This article belongs to the Special Issue Recent Progress on Lignocellulosic-Based Polymeric Materials)
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28 pages, 5373 KiB  
Article
Transfer Learning Based on Multi-Branch Architecture Feature Extractor for Airborne LiDAR Point Cloud Semantic Segmentation with Few Samples
by Jialin Yuan, Hongchao Ma, Liang Zhang, Jiwei Deng, Wenjun Luo, Ke Liu and Zhan Cai
Remote Sens. 2025, 17(15), 2618; https://doi.org/10.3390/rs17152618 - 28 Jul 2025
Viewed by 315
Abstract
The existing deep learning-based Airborne Laser Scanning (ALS) point cloud semantic segmentation methods require a large amount of labeled data for training, which is not always feasible in practice. Insufficient training data may lead to over-fitting. To address this issue, we propose a [...] Read more.
The existing deep learning-based Airborne Laser Scanning (ALS) point cloud semantic segmentation methods require a large amount of labeled data for training, which is not always feasible in practice. Insufficient training data may lead to over-fitting. To address this issue, we propose a novel Multi-branch Feature Extractor (MFE) and a three-stage transfer learning strategy that conducts pre-training on multi-source ALS data and transfers the model to another dataset with few samples, thereby improving the model’s generalization ability and reducing the need for manual annotation. The proposed MFE is based on a novel multi-branch architecture integrating Neighborhood Embedding Block (NEB) and Point Transformer Block (PTB); it aims to extract heterogeneous features (e.g., geometric features, reflectance features, and internal structural features) by leveraging the parameters contained in ALS point clouds. To address model transfer, a three-stage strategy was developed: (1) A pre-training subtask was employed to pre-train the proposed MFE if the source domain consisted of multi-source ALS data, overcoming parameter differences. (2) A domain adaptation subtask was employed to align cross-domain feature distributions between source and target domains. (3) An incremental learning subtask was proposed for continuous learning of novel categories in the target domain, avoiding catastrophic forgetting. Experiments conducted on the source domain consisted of DALES and Dublin datasets and the target domain consists of ISPRS benchmark dataset. The experimental results show that the proposed method achieved the highest OA of 85.5% and an average F1 score of 74.0% using only 10% training samples, which means the proposed framework can reduce manual annotation by 90% while keeping competitive classification accuracy. Full article
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18 pages, 417 KiB  
Article
The Role of Service Quality in Enhancing Technological Innovation, Satisfaction, and Loyalty Among University Students in Northern Cyprus
by Birgül Gürbüzer and Ahmet Münir Acuner
Sustainability 2025, 17(15), 6832; https://doi.org/10.3390/su17156832 - 28 Jul 2025
Viewed by 336
Abstract
In the increasingly competitive landscape of higher education, student satisfaction and loyalty are recognized as essential components for institutional sustainability and long-term success. This study aims to examine the interrelationships between service quality, technological innovation, student satisfaction, and student loyalty within higher education [...] Read more.
In the increasingly competitive landscape of higher education, student satisfaction and loyalty are recognized as essential components for institutional sustainability and long-term success. This study aims to examine the interrelationships between service quality, technological innovation, student satisfaction, and student loyalty within higher education institutions in the Turkish Republic of Northern Cyprus (TRNC). Grounded in relationship marketing theory and the expectancy–disconfirmation paradigm, the research develops and tests a structural model that investigates the impact of perceived service quality on technological innovation, student satisfaction, and loyalty. The data were collected from 448 undergraduate students studying in the faculties of education at five leading private universities in TRNC, selected based on their international academic rankings. The analysis, conducted using structural equation modelling (SEM), reveals that service quality significantly and directly influences technological innovation, student satisfaction, and student loyalty. Additionally, technological innovation has a positive but comparatively weaker effect on student loyalty. Among the variables, student satisfaction emerges as the strongest determinant of loyalty, serving as a key mediator in the relationship between service quality and loyalty. This research contributes to the higher education literature by extending the traditional service quality–loyalty framework with the inclusion of technological innovation. The findings offer practical insights for university administrators, emphasizing the importance of delivering high-quality educational services combined with continuous digital innovation to enhance the student experience and foster long-term student commitment. Full article
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41 pages, 1344 KiB  
Article
Strengthening Smart Specialisation Strategies (S3) Through Network Analysis: Policy Insights from a Decade of Innovation Projects in Aragón
by David Rodríguez Ochoa, Nieves Arranz and Marta Fernandez de Arroyabe
Economies 2025, 13(8), 218; https://doi.org/10.3390/economies13080218 - 26 Jul 2025
Viewed by 294
Abstract
This paper applies a multi-level social network analysis to examine Aragón’s innovation ecosystem, focusing on a decade of competitive public projects (2014–2023) aligned with the region’s Smart Specialisation Strategy (S3) 2021–2027. By mapping and weighting the participation of regional entities across regional, national, [...] Read more.
This paper applies a multi-level social network analysis to examine Aragón’s innovation ecosystem, focusing on a decade of competitive public projects (2014–2023) aligned with the region’s Smart Specialisation Strategy (S3) 2021–2027. By mapping and weighting the participation of regional entities across regional, national, and European calls, the study uncovers how all types of local actors organise themselves around key specialisation areas. Moreover, a comparative benchmark is introduced by analysing more than 33,000 Horizon 2020 and Horizon Europe initiatives without Aragonese partners, revealing how to fill structural gaps and enrich the regional ecosystem through international collaboration. Results show strong funding concentration in four fields—Energy, Health, Agri-Food, and Advanced Technologies—while other historically strategic areas like Hydrogen and Water remain underrepresented. Although leading institutions (UNIZAR, CIRCE, ITA, AITIIP) play central roles in connecting academia and industry, direct collaboration among them is limited, pointing to missed synergies. Expanding previous SNA-based assessments, this study introduces a diagnostic tool to guide policy, proposing targeted actions such as challenge-driven calls, dedicated support programs, and cross-border consortia with top EU partners. Applied to two contrasting specialisation areas, the method offers sector-specific recommendations, helping policymakers align Aragón’s innovation capabilities with EU priorities and strengthen its position in both established and emerging domains. Full article
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26 pages, 16392 KiB  
Article
TOSD: A Hierarchical Object-Centric Descriptor Integrating Shape, Color, and Topology
by Jun-Hyeon Choi, Jeong-Won Pyo, Ye-Chan An and Tae-Yong Kuc
Sensors 2025, 25(15), 4614; https://doi.org/10.3390/s25154614 - 25 Jul 2025
Viewed by 326
Abstract
This paper introduces a hierarchical object-centric descriptor framework called TOSD (Triplet Object-Centric Semantic Descriptor). The goal of this method is to overcome the limitations of existing pixel-based and global feature embedding approaches. To this end, the framework adopts a hierarchical representation that is [...] Read more.
This paper introduces a hierarchical object-centric descriptor framework called TOSD (Triplet Object-Centric Semantic Descriptor). The goal of this method is to overcome the limitations of existing pixel-based and global feature embedding approaches. To this end, the framework adopts a hierarchical representation that is explicitly designed for multi-level reasoning. TOSD combines shape, color, and topological information without depending on predefined class labels. The shape descriptor captures the geometric configuration of each object. The color descriptor focuses on internal appearance by extracting normalized color features. The topology descriptor models the spatial and semantic relationships between objects in a scene. These components are integrated at both object and scene levels to produce compact and consistent embeddings. The resulting representation covers three levels of abstraction: low-level pixel details, mid-level object features, and high-level semantic structure. This hierarchical organization makes it possible to represent both local cues and global context in a unified form. We evaluate the proposed method on multiple vision tasks. The results show that TOSD performs competitively compared to baseline methods, while maintaining robustness in challenging cases such as occlusion and viewpoint changes. The framework is applicable to visual odometry, SLAM, object tracking, global localization, scene clustering, and image retrieval. In addition, this work extends our previous research on the Semantic Modeling Framework, which represents environments using layered structures of places, objects, and their ontological relations. Full article
(This article belongs to the Special Issue Event-Driven Vision Sensor Architectures and Application Scenarios)
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26 pages, 3489 KiB  
Article
Techno-Economic Analysis of Hydrogen Hybrid Vehicles
by Dapai Shi, Jiaheng Wang, Kangjie Liu, Chengwei Sun, Zhenghong Wang and Xiaoqing Liu
World Electr. Veh. J. 2025, 16(8), 418; https://doi.org/10.3390/wevj16080418 - 24 Jul 2025
Viewed by 248
Abstract
Driven by carbon neutrality and peak carbon policies, hydrogen energy, due to its zero-emission and renewable properties, is increasingly being used in hydrogen fuel cell vehicles (H-FCVs). However, the high cost and limited durability of H-FCVs hinder large-scale deployment. Hydrogen internal combustion engine [...] Read more.
Driven by carbon neutrality and peak carbon policies, hydrogen energy, due to its zero-emission and renewable properties, is increasingly being used in hydrogen fuel cell vehicles (H-FCVs). However, the high cost and limited durability of H-FCVs hinder large-scale deployment. Hydrogen internal combustion engine hybrid electric vehicles (H-HEVs) are emerging as a viable alternative. Research on the techno-economics of H-HEVs remains limited, particularly in systematic comparisons with H-FCVs. This paper provides a comprehensive comparison of H-FCVs and H-HEVs in terms of total cost of ownership (TCO) and hydrogen consumption while proposing a multi-objective powertrain parameter optimization model. First, a quantitative model evaluates TCO from vehicle purchase to disposal. Second, a global dynamic programming method optimizes hydrogen consumption by incorporating cumulative energy costs into the TCO model. Finally, a genetic algorithm co-optimizes key design parameters to minimize TCO. Results show that with a battery capacity of 20.5 Ah and an H-FC peak power of 55 kW, H-FCV can achieve optimal fuel economy and hydrogen consumption. However, even with advanced technology, their TCO remains higher than that of H-HEVs. H-FCVs can only become cost-competitive if the unit power price of the fuel cell system is less than 4.6 times that of the hydrogen engine system, assuming negligible fuel cell degradation. In the short term, H-HEVs should be prioritized. Their adoption can also support the long-term development of H-FCVs through a complementary relationship. Full article
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53 pages, 1950 KiB  
Article
Redefining Energy Management for Carbon-Neutral Supply Chains in Energy-Intensive Industries: An EU Perspective
by Tadeusz Skoczkowski, Sławomir Bielecki, Marcin Wołowicz and Arkadiusz Węglarz
Energies 2025, 18(15), 3932; https://doi.org/10.3390/en18153932 - 23 Jul 2025
Viewed by 324
Abstract
Energy-intensive industries (EIIs) face mounting pressure to reduce greenhouse gas emissions while maintaining international competitiveness—a balance that is central to achieving the EU’s 2030 and 2050 climate objectives. In this context, energy management (EM) emerges as a strategic instrument to decouple industrial growth [...] Read more.
Energy-intensive industries (EIIs) face mounting pressure to reduce greenhouse gas emissions while maintaining international competitiveness—a balance that is central to achieving the EU’s 2030 and 2050 climate objectives. In this context, energy management (EM) emerges as a strategic instrument to decouple industrial growth from fossil energy consumption. This study proposes a redefinition of EM to support carbon-neutral supply chains within the European Union’s EIIs, addressing critical limitations of conventional EM frameworks under increasingly stringent carbon regulations. Using a modified systematic literature review based on PRISMA methodology, complemented by expert insights from EU Member States, this research identifies structural gaps in current EM practices and highlights opportunities for integrating sustainable innovations across the whole industrial value chain. The proposed EM concept is validated through an analysis of 24 EM definitions, over 170 scientific publications, and over 80 EU legal and strategic documents. The framework incorporates advanced digital technologies—including artificial intelligence (AI), the Internet of Things (IoT), and big data analytics—to enable real-time optimisation, predictive control, and greater system adaptability. Going beyond traditional energy efficiency, the redefined EM encompasses the entire energy lifecycle, including use, transformation, storage, and generation. It also incorporates social dimensions, such as corporate social responsibility (CSR) and stakeholder engagement, to cultivate a culture of environmental stewardship within EIIs. This holistic approach provides a strategic management tool for optimising energy use, reducing emissions, and strengthening resilience to regulatory, environmental, and market pressures, thereby promoting more sustainable, inclusive, and transparent supply chain operations. Full article
(This article belongs to the Section B: Energy and Environment)
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24 pages, 2758 KiB  
Article
A Techno-Economic Analysis of Integrating an Urban Biorefinery Process Within a Wastewater Treatment Plant to Produce Sustainable Wood Adhesives
by Blake Foret, William M. Chirdon, Rafael Hernandez, Dhan Lord B. Fortela, Emmanuel Revellame, Daniel Gang, Jalel Ben Hmida, William E. Holmes and Mark E. Zappi
Sustainability 2025, 17(15), 6679; https://doi.org/10.3390/su17156679 - 22 Jul 2025
Viewed by 404
Abstract
Societies are aiming to have a higher ecological consciousness in wastewater treatment operations and achieve a more sustainable future. With this said, global demands for larger quantities of resources and the consequent waste generated will inevitably lead to the exhaustion of current municipal [...] Read more.
Societies are aiming to have a higher ecological consciousness in wastewater treatment operations and achieve a more sustainable future. With this said, global demands for larger quantities of resources and the consequent waste generated will inevitably lead to the exhaustion of current municipal wastewater treatment works. The utilization of biosolids (particularly microbial proteins) from wastewater treatment operations could generate a sustainable bio-adhesive for the wood industry, reduce carbon footprint, mitigate health concerns related to the use of carcinogenic components, and support a more circular economic option for wastewater treatment. A techno-economic analysis for three 10 MGD wastewater treatment operations producing roughly 11,300 dry pounds of biosolids per day, in conjunction with co-feedstock defatted soy flour protein at varying ratios (i.e., 0%, 15%, and 50% wet weight), was conducted. Aspen Capital Cost Estimator V12 was used to design and estimate installed equipment additions for wastewater treatment plant integration into an urban biorefinery process. Due to the mechanical attributes and market competition, the chosen selling prices of each adhesive per pound were set for analysis as USD 0.75 for Plant Option P1, USD 0.85 for Plant Option P2, and USD 1.00 for Plant Option P3. Over a 20-year life, each plant option demonstrated economic viability with high NPVs of USD 107.9M, USD 178.7M, and USD 502.2M and internal rates of return (IRRs) of 24.0%, 29.0%, and 44.2% respectively. The options examined have low production costs of USD 0.14 and USD 0.19 per pound, minimum selling prices of USD 0.42–USD 0.51 per pound, resulting in between 2- and 4-year payback periods. Sensitivity analysis shows the effects biosolid production fluctuations, raw material market price, and adhesive selling price have on economics. The results proved profitable even with large variations in the feedstock and raw material prices, requiring low market selling prices to reach the hurdle rate of examination. This technology is economically enticing, and the positive environmental impact of waste utilization encourages further development and analysis of the bio-adhesive process. Full article
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20 pages, 1487 KiB  
Article
Structural Evolution and Factors of the Electric Vehicle Lithium-Ion Battery Trade Network Among European Union Member States
by Liqiao Yang, Ni Shen, Izabella Szakálné Kanó, Andreász Kosztopulosz and Jianhao Hu
Sustainability 2025, 17(15), 6675; https://doi.org/10.3390/su17156675 - 22 Jul 2025
Viewed by 387
Abstract
As global climate change intensifies and the transition to clean energy accelerates, lithium-ion batteries—critical components of electric vehicles—are becoming increasingly vital in international trade networks. This study investigates the structural evolution and determinants of the electric vehicle lithium-ion battery trade network among European [...] Read more.
As global climate change intensifies and the transition to clean energy accelerates, lithium-ion batteries—critical components of electric vehicles—are becoming increasingly vital in international trade networks. This study investigates the structural evolution and determinants of the electric vehicle lithium-ion battery trade network among European Union (EU) member states from 2012 to 2023, employing social network analysis and the multiple regression quadratic assignment procedure method. The findings demonstrate the transformation of the network from a centralized and loosely connected structure, with Germany as the dominant hub, to a more interconnected and decentralized system in which Poland and Hungary emerge as the leading players. Key network metrics, such as the density, clustering coefficients, and average path lengths, reveal increased regional trade connectivity and enhanced supply chain efficiency. The analysis identifies geographic and economic proximity, logistics performance, labor cost differentials, energy resource availability, and venture capital investment as significant drivers of trade flows, highlighting the interaction among spatial, economic, and infrastructural factors in shaping the network. Based on these findings, this study underscores the need for targeted policy measures to support Central and Eastern European countries, including investment in logistics infrastructure, technological innovation, and regional cooperation initiatives, to strengthen their integration into the supply chain and bolster their export capacity. Furthermore, fostering balanced inter-regional collaborations is essential in building a resilient trade network. Continued investment in transportation infrastructure and innovation is recommended to sustain the EU’s competitive advantage in the global electric vehicle lithium-ion battery supply chain. Full article
(This article belongs to the Section Economic and Business Aspects of Sustainability)
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