Sustainability

27 pages, 538 KB

Open AccessArticle

How Does Entrepreneurial Defection Influence Ambidextrous Innovation? The Chain Mediation of Entrepreneurial Learning and Organizational Change

by Hengsheng Gu, Yuchen Zhang, Yi Lu, Yubin Zhou and Qun Fu

Sustainability 2025, 17(24), 10943; https://doi.org/10.3390/su172410943 (registering DOI) - 7 Dec 2025

Abstract

Entrepreneurial defection, which leads to the loss of core talents and key resources, poses a severe threat to the innovation capacity and sustainable development of entrepreneurial enterprises. However, the mechanism through which it influences ambidextrous innovation—a key driver of sustainability comprising exploitative (short-term [...] Read more.

Entrepreneurial defection, which leads to the loss of core talents and key resources, poses a severe threat to the innovation capacity and sustainable development of entrepreneurial enterprises. However, the mechanism through which it influences ambidextrous innovation—a key driver of sustainability comprising exploitative (short-term optimization) and exploratory (long-term breakthrough) activities—remains empirically unclear. Grounded in the Conservation of Resources Theory, this study analyzes 553 questionnaires from entrepreneurial enterprises (≤8 years old) to investigate the impact of entrepreneurial defection on ambidextrous innovation, focusing on the chain mediating roles of entrepreneurial learning and organizational change. The findings reveal that (1) Entrepreneurial defection does not directly promote ambidextrous innovation; its positive effect is fully mediated by entrepreneurial learning, organizational change, and their sequential path. (2) Significant heterogeneity exists in this mediating effect: the path via entrepreneurial learning is stronger for exploitative innovation, whereas the path via organizational change exerts a weak negative interference on exploratory innovation, though the positive effect of learning remains dominant. (3) Entrepreneurial learning is the core mediator, accounting for over 70% of the total indirect effect, and facilitates a “learning-change-innovation-sustainability” cycle. This study fills a critical empirical gap and extends the application of Conservation of Resources Theory. It offers practical insights for entrepreneurs: by strengthening learning and guiding organizational change, the pressure of resource loss can be transformed into a driver for dual innovation, enabling a transition from crisis recovery to sustainable development capability upgrading. Full article

(This article belongs to the Special Issue Ecodesign of Products and Sustainable Manufacturing)

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17 pages, 1235 KB

Open AccessReview

Microbial Synergistic Interactions in Mixed Cultures for Improved and Sustainable Power Generation in Microbial Fuel Cells: A Review

by Asmamaw Abat Getu, Wubliker Dessie, Juvens Sugira Murekezi, Md Sourav Sarker, Geng Chen, Oluwadamilola Oluwatoyin Hazzan and Yong Xiao

Sustainability 2025, 17(24), 10942; https://doi.org/10.3390/su172410942 (registering DOI) - 7 Dec 2025

Abstract

Nonrenewable energy sources dominate global energy production, but their depletion and environmental impact pose serious challenges. The need for alternative and eco-friendly energy sources is increasingly evident. In this regard, utilizing knowledge gained from natural microorganisms to generate bioelectricity is a promising solution [...] Read more.

Nonrenewable energy sources dominate global energy production, but their depletion and environmental impact pose serious challenges. The need for alternative and eco-friendly energy sources is increasingly evident. In this regard, utilizing knowledge gained from natural microorganisms to generate bioelectricity is a promising solution via microbial fuel cells (MFCs). Microbial fuel cells are an environmentally friendly technology that generates power from diverse organic substrates through the ‘catalytic’ activity of microorganisms. Although, MFCs still generate relatively low power, various scale-up studies have shown noticeable improvements in power output. Among the available strategies, mixed-culture systems are the simplest, sustainable, and direct way to improve bioelectricity production. However, the mixed culture microbial synergistic interactions and competition that drive power generation remain poorly understood. To address this, the objective of this review is to assess how synergistic interactions and metabolic networks within mixed microbial cultures enhance bioelectricity generation in microbial fuel cells. This review also explores the mixed-culture microbial fuel cell system as a promising renewable technology with potential applications in sustainable energy production. Full article

(This article belongs to the Section Energy Sustainability)

29 pages, 13940 KB

Open AccessArticle

Evaluation of Mechanical Properties of Concrete with Plastic Waste Using Random Forest and XGBoost Algorithms

by Mohammed K. Alkharisi and Hany A. Dahish

Sustainability 2025, 17(24), 10941; https://doi.org/10.3390/su172410941 (registering DOI) - 7 Dec 2025

Abstract

The increasing global production of plastic (P) waste presents a critical environmental challenge, while the construction industry’s demand for sustainable materials continues to grow. The building industry’s reliance on natural aggregates, a contributor to environmental degradation, requires sustainable alternatives. Utilizing plastic waste as [...] Read more.

The increasing global production of plastic (P) waste presents a critical environmental challenge, while the construction industry’s demand for sustainable materials continues to grow. The building industry’s reliance on natural aggregates, a contributor to environmental degradation, requires sustainable alternatives. Utilizing plastic waste as a partial aggregate substitute in concrete offers dual advantages: preserving limited resources and redirecting waste from landfills. This research uses advanced machine learning (ML) to forecast the mechanical properties of P waste concrete. Random Forest (RF) and eXtreme Gradient Boosting (XGBoost) models with particle swarm optimization (PSO) were developed to predict compressive and tensile strengths of P waste concrete. A comprehensive dataset comprising 196 datapoints for compressive strength (CS) and 100 datapoints for tensile strength (TS) of P waste concrete was collected from the literature. The input parameters encompassed the plastic (P), cement (C), water-to-cement ratio (W/C), coarse aggregate (CA), fine aggregate (FA), and curing age (Age), while the outputs were CS and TS of P waste concrete. The constructed models were assessed utilizing various statistical metrics. The findings indicate that coefficient of determination of both XGBoost (CS, R² = 0.9911, and TS, R² = 0.9947) and RF (CS, R² = 0.9757, and TS, R² = 0.9737) models performed well, with XGBoost indicating better performance with fewer prediction errors. SHAP analysis emphasizes the substantial effect of P waste on concrete strength properties followed by C and Age. Furthermore, GUIs for predicting TS and CS of concrete containing P waste utilizing both RF and XGBoost models were developed. Overall, this study not only achieves superior accuracy through hybrid PSO-ML models but also contributes to sustainable construction materials and computational material science, offering a data-driven framework for optimizing mix designs that incorporate plastic waste, which can accelerate its adoption in eco-friendly engineering applications. Full article

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22 pages, 3131 KB

Open AccessArticle

Evaluating Crumb Rubber Modified (CRM) Asphalt as a Sustainable Binder Alternative for High-Friction Surface Treatments

by Abdallah Aboelela, Alireza Roshan and Magdy Abdelrahman

Sustainability 2025, 17(24), 10940; https://doi.org/10.3390/su172410940 (registering DOI) - 7 Dec 2025

Abstract

High-friction surface treatments (HFSTs) are widely applied to improve pavement safety by enhancing long-term skid resistance. Although epoxy resins are commonly used due to their strength and durability, their high cost, susceptibility to delamination, incompatibility with substrates of flexible pavements, and adverse environmental [...] Read more.

High-friction surface treatments (HFSTs) are widely applied to improve pavement safety by enhancing long-term skid resistance. Although epoxy resins are commonly used due to their strength and durability, their high cost, susceptibility to delamination, incompatibility with substrates of flexible pavements, and adverse environmental concerns limit their long-term performance. This study presents crumb rubber modified (CRM) asphalt as a sustainable alternative binder for HFST applications. CRM binders offer high performance and compatibility with existing pavement surfaces, cost effectiveness and reduced environmental impacts as compared to epoxy binders. In addition, the binder development utilizes enhanced recycling technologies for interacting with used tire rubber with asphalt. The evaluated CRM binders were prepared under varying interaction temperatures, crumb rubber contents, and types. The developed binders were evaluated for friction performance with two aggregate sources, calcined bauxite (CB) and rhyolite (Rhy). Binder characterization included rheological testing conducted through both frequency sweep and temperature sweep procedures. HFST mixes were evaluated using the British Pendulum Test (BPT), the Dynamic Friction Tester (DFT), and the Circular Track Meter (CTM) in collaboration with the Three-Wheel Polishing Device (TWPD) to simulate the traffic-induced polishing effect. The results showed that CRM content influenced binder performance under polishing. CRM asphalt-based HFST with a relatively high CRM content (15%) maintained a greater coefficient of friction (COF) and exhibited polishing resistance, showing low reduction in the COF after the total number of polishing cycles. In contrast, mean profile depth (MPD) analysis revealed that the most macrotexture efficiency was found in binders with a lower CRM content (10%) after completing the total number of polishing cycles. Analysis of Variance (ANOVA) showed a significant effect of the interaction conditions and rheological properties of CRM binders on the British pendulum number (BPN) loss due to the polishing process. As expected, aggregate source further influenced the resistance to polishing; CB outperformed Rhy with significantly lower aggregate loss under polishing. Overall, the results confirmed that CRM asphalt binders can effectively serve as a sustainable, flexible, and cost-effective alternative binder in HFST. Full article

(This article belongs to the Special Issue Strategies for Improving the Sustainability of Asphalt Pavements)

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19 pages, 1233 KB

Open AccessArticle

The Impact of Open Public Data on Corporate Low-Carbon Technological Innovation: Evidence from China

by Jing Wang, Jie Wang and Zhijian Cai

Sustainability 2025, 17(24), 10939; https://doi.org/10.3390/su172410939 (registering DOI) - 7 Dec 2025

Abstract

Open public data is a vital institutional arrangement for overcoming data constraints in corporate low-carbon technological innovation. Using a panel dataset of China’s Shanghai and Shenzhen A-share listed firms over the 2007–2023 period, this study employs a difference-in-differences (DID) approach to examine the [...] Read more.

Open public data is a vital institutional arrangement for overcoming data constraints in corporate low-carbon technological innovation. Using a panel dataset of China’s Shanghai and Shenzhen A-share listed firms over the 2007–2023 period, this study employs a difference-in-differences (DID) approach to examine the impact of open public data on corporate low-carbon technological innovation. The results show that open public data has a significant positive effect on corporate low-carbon technological innovation, and the results remain robust across multiple validation tests. Mechanism tests point out that government transparency negatively moderates the promotional effect of public data openness on corporate low-carbon technological innovation, while barriers to factor mobility positively moderate this effect. The heterogeneity analysis indicates that the positive impact of open public data is more pronounced among firms characterized by higher R&D investment, lower financial constraints, and greater digitalization. Further analysis indicates that open public data also exhibits significant geographic and industry spillover effects, with the geographic spillover following an inverted U-shaped pattern of decay and the industry spillover driven by peer imitation. This study provides evidence on leveraging open public data to stimulate low-carbon innovation and facilitate green economic transformation, offering valuable insights for advancing data-driven sustainable development globally. Full article

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17 pages, 2488 KB

Open AccessArticle

Constructing a Cradle-to-Gate Carbon Emission Assessment and Analysis Framework Based on Life Cycle Thinking: A Case Study of Bicycle Brake Cable Products

by Jui-Che Tu, Pei-Chi Huang, Shi-Chen Luo and Kharisma Creativani

Sustainability 2025, 17(24), 10938; https://doi.org/10.3390/su172410938 (registering DOI) - 7 Dec 2025

Abstract

In 2023, the bicycle industry in Taiwan reached a historic high. However, concerns about carbon emissions persist, particularly during the material acquisition and manufacturing stages of bicycle production. This study utilizes the Life Cycle Assessment (LCA) method, using SimaPro 9.5 for cradle-to-gate carbon [...] Read more.

In 2023, the bicycle industry in Taiwan reached a historic high. However, concerns about carbon emissions persist, particularly during the material acquisition and manufacturing stages of bicycle production. This study utilizes the Life Cycle Assessment (LCA) method, using SimaPro 9.5 for cradle-to-gate carbon emission data analysis. This study thoroughly examines the complete life cycle of a bicycle brake cable product through a carbon reduction evaluation tool, identifying carbon hotspots in the product’s life cycle. The data reveals that packaging accounts for the highest proportion of factory carbon emissions in the brake cable product analysis (34.42%), followed by the product’s casing (30.60%), with the leading materials being metal, plastic, and paper. Throughout the cradle-to-gate process, we collaborated with product developers to utilize the LCA carbon reduction evaluation tool to analyze the life cycle of the brake cable product. By aligning market and development needs, we supported manufacturers in identifying additional carbon reduction strategies at the material selection, mechanical design, and manufacturing process stages. These strategies include using natural raw materials, reducing packaging volume, developing lightweight products, and investing in integrated equipment. By implementing these measures, companies can reduce the product’s carbon footprint and enhance resource efficiency during production. This assessment tool serves as a communication bridge between designers and engineers, translating LCA quantitative data into references for design and management decision-making. It also functions as a simplified analytical tool for SMEs to conduct preliminary diagnosis of carbon emission hotspots and plan improvement directions, particularly suitable for manufacturers lacking consulting resources and carbon inventory capabilities. The research findings not only help companies integrate carbon reduction thinking early in product development, forming a closed-loop system of quantitative analysis and design actions, but also provide concrete references for Taiwan’s bicycle industry to promote supply chain collaboration, achieve green transformation, and meet global carbon reduction goals. Full article

(This article belongs to the Special Issue Toward Net-Zero Futures: Innovations in Carbon Management and Sustainable Transitions)

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20 pages, 5116 KB

Open AccessArticle

Spatiotemporal Distribution of Cross-Platform Public Opinion in the 2023 Dezhou Earthquake: Implications for Disaster-Resilient Emergency Management

by Chen Li, Xurui Wang and Yanjun Ye

Sustainability 2025, 17(24), 10937; https://doi.org/10.3390/su172410937 (registering DOI) - 7 Dec 2025

Abstract

Social media platforms have emerged as a critical infrastructure for disaster communication and emergency management. However, how public opinion varies across platforms during earthquake events and how such differences can inform resilient disaster strategies remain underexplored. This study analyzes public opinion responses to [...] Read more.

Social media platforms have emerged as a critical infrastructure for disaster communication and emergency management. However, how public opinion varies across platforms during earthquake events and how such differences can inform resilient disaster strategies remain underexplored. This study analyzes public opinion responses to the 2023 M5.5 Dezhou earthquake across three major Chinese social media platforms—Sina Weibo, Bilibili, and Douyin—based on 28,557 posts. By combining Latent Dirichlet Allocation (LDA), Word2Vec, and Convolutional Neural Networks (CNNs), we examine the temporal, spatial, thematic, and emotional patterns of public discourse. The results show (1) a bimodal public attention pattern within 24 h of the earthquake, with platform-specific response timings; (2) spatial clustering of public concern in the epicenter (Shandong) and historically high-risk regions (Sichuan–Chongqing); (3) differentiated topic preferences reflecting platform functions—emotional expression (Weibo), science popularization (Bilibili), and real-time impact sharing (Douyin); and (4) a predominance of positive/neutral sentiment, influenced by user demographics and algorithmic content curation. This study proposes a resilience-oriented public opinion analysis framework aligned with the disaster lifecycle and offers recommendations for platform-specific risk communication, psychological support, and policy planning. Findings contribute to digital disaster governance and the integration of social media analytics into sustainable emergency management. Full article

38 pages, 1920 KB

Open AccessArticle

Lean Implementation in Sustainable Energy Entrepreneurship: Key Drivers for Operational Efficiency

by T. A. Alka, M. Suresh, Ateekh Ur Rehman and Shanthi Muthuswamy

Sustainability 2025, 17(24), 10936; https://doi.org/10.3390/su172410936 (registering DOI) - 7 Dec 2025

Abstract

This research examines the drivers of lean implementation in sustainable energy enterprises (SEEs) to balance efficiency, sustainability, and competitiveness. This research investigates the interdependence among lean drivers and classifies them by driving power and dependence. This study followed a novel mixed-method approach combining [...] Read more.

This research examines the drivers of lean implementation in sustainable energy enterprises (SEEs) to balance efficiency, sustainability, and competitiveness. This research investigates the interdependence among lean drivers and classifies them by driving power and dependence. This study followed a novel mixed-method approach combining a systematic literature review for driver identification, interviews with entrepreneurs for expert consensus, and analysis using total interpretive structural modelling (TISM), cross-impact matrix multiplication applied to classification (MICMAC), and a graph-theoretic approach (GTA). The result indicated that leadership commitment, teamwork and collaboration, and time management are high drivers; cost reduction, resource optimization, and continuous improvement are linkage drivers; and customer focus and flexibility are found as dependent drivers, revealing the sustainable outcome. This provides a structured pathway for the SEEs for the lean implementation drivers, where prioritization is required. The exploration adds to the Resource-Based View, dynamic capability theory, system theory, etc. The study calls for policymakers’ interventions in designing capacity-building programmes, leadership training, and collaborations. This research incorporated the antecedents–decisions–outcomes (ADO) framework for highlighting the antecedents, leading to decisions, and the outcomes of the choices, with future research questions connecting with multiple sustainable development goals (SDGs), such as SDG7, SDG9, SDG12, and SDG13. Full article

(This article belongs to the Special Issue Entrepreneurship and Innovation Management under Sustainable Development)

18 pages, 8460 KB

Open AccessArticle

Simulation of Fracture Propagation and Permeability Enhancement in Heterogeneous Coal Seams During Hydraulic Fracturing Using a Thermo-Hydro-Mechanical-Damage Coupling Model

by Sukai Wang, Lipeng Zhang, Yonglong Li, Wei Liu, Xionghui Liu, Yan Liang, Songling Pu, Lei Sun, Shiqi Liu and Wenkai Wang

Sustainability 2025, 17(24), 10935; https://doi.org/10.3390/su172410935 (registering DOI) - 7 Dec 2025

Abstract

The development of deep coalbed methane is hindered by the strong heterogeneity of coal mechanical properties and complex hydraulic fracturing behavior. To identify the key factors controlling fracture geometry and permeability enhancement, this study developed a thermo-hydro-mechanical-damage coupled model within a COMSOL Multiphysics [...] Read more.

The development of deep coalbed methane is hindered by the strong heterogeneity of coal mechanical properties and complex hydraulic fracturing behavior. To identify the key factors controlling fracture geometry and permeability enhancement, this study developed a thermo-hydro-mechanical-damage coupled model within a COMSOL Multiphysics 6.3-MATLAB R2022b co-simulation framework, incorporating a Weibull random field to characterize mechanical heterogeneity. Sensitivity analysis demonstrates that tensile strength is the predominant factor governing both the fracturing damage zone and permeability-enhanced area, with its damage area extreme difference (10.094) and coefficient of variation (0.85) significantly surpassing those of other parameters. Poisson’s ratio and elastic modulus emerge as key secondary parameters, while compressive strength shows the lowest sensitivity. The parametric influences exhibit distinct patterns: tensile strength shows a strong negative correlation with damage and permeability-enhanced areas (up to 85% reduction), whereas the maximum permeability enhancement rate follows a non-monotonic trend, peaking at 215 when tensile strength reaches 3.33 MPa. Compressive strength minimally affects the damage area (~15%) but steadily improves the maximum permeability enhancement rate (7.5% increase). Elastic modulus exhibits an optimal value (8.93 GPa) for maximizing damage area, while negatively correlating with maximum permeability enhancement rate (9.1% decrease). Fracture morphology is differentially controlled by multiple parameters: low compressive strength promotes fracture deflection and branching, elastic modulus regulates fracture network complexity, and low Poisson’s ratio enhances coal brittleness to effectively activate natural fractures, thereby facilitating complex fracture network formation. Full article

(This article belongs to the Special Issue Greenhouse Gas Emission Reduction for Sustainable Resource Utilization)

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18 pages, 320 KB

Open AccessArticle

The Contribution of Regional Products to Short Agri-Food Supply Chains

by Luiza Ossowska, Dorota Janiszewska, Patrycja Beba, Monika Małgorzata Wojcieszak-Zbierska and Grzegorz Kwiatkowski

Sustainability 2025, 17(24), 10934; https://doi.org/10.3390/su172410934 (registering DOI) - 7 Dec 2025

Abstract

Short food supply chains are a typical solution for traditional food distribution systems. Geographic proximity is a key determinant of both short supply chains and regional products. Regional foods are linked to a place, both through the origin of raw materials and through [...] Read more.

Short food supply chains are a typical solution for traditional food distribution systems. Geographic proximity is a key determinant of both short supply chains and regional products. Regional foods are linked to a place, both through the origin of raw materials and through their ties to traditions. The aim of the study is to identify the key features of farmers–regional food producers building short food supply chains. The research material comes from surveys conducted in July 2024. The research covered farmers–small producers of regional food in Poland. 252 questionnaires were selected for the presented research. The respondents were divided into two groups: farmers who sold only directly and farmers who used sales intermediaries. Research shows that direct sales dominate among farmers and producers of regional food in Poland. Factors of particular importance in building short regional food supply chains include connections to recipes and family traditions, in terms of knowledge and practical skills. Given the numerous advantages of short regional food supply chains, this activity is worth supporting. Institutional support should encompass not only financial assistance but also organizational support to help connect producers with consumers. Promotional activities highlighting regional food and its producers could be another pillar of support. Full article

(This article belongs to the Special Issue Food, Supply Chains, and Sustainable Development—Second Edition)

32 pages, 8288 KB

Open AccessArticle

Multisource Remote Sensing and Machine Learning for Spatio-Temporal Drought Assessment in Northeast Syria

by Abdullah Sukkar, Ozan Ozturk, Ammar Abulibdeh and Dursun Zafer Seker

Sustainability 2025, 17(24), 10933; https://doi.org/10.3390/su172410933 (registering DOI) - 7 Dec 2025

Abstract

Increasing aridity across the Middle East Region has intensified concerns about the impacts of drought in conflict-affected Northeast Syria (NES). In this study, drought dynamics and their drivers from 2000 to 2023 were analyzed by integrating ERA5-Land meteorological data, MODIS land-surface indicators, FLDAS [...] Read more.

Increasing aridity across the Middle East Region has intensified concerns about the impacts of drought in conflict-affected Northeast Syria (NES). In this study, drought dynamics and their drivers from 2000 to 2023 were analyzed by integrating ERA5-Land meteorological data, MODIS land-surface indicators, FLDAS soil moisture, and ISRIC soil properties at 250 m resolution. The integration of these multisource datasets contributes to a more comprehensive understanding of drought dynamics by combining information on weather conditions, vegetation status, and soil characteristics. The proposed drought analysis framework clarifies independent controls on meteorological, agricultural, and hydrological drought, underscoring the role of land-atmosphere feedback through soil temperature. This workflow provides a transferable approach for drought monitoring and hypothesis generation in arid regions. For this purpose, different XGBoost models were trained for the vegetation health index (VHI), the standardized precipitation-evapotranspiration index (SPEI), and surface soil-moisture anomalies, excluding target-related variables to prevent data leakage. Model interpretability was achieved using SHAP, complemented by time-series, trend, clustering, and spatial autocorrelation analyses. The models performed well (R² = 0.86–0.90), identifying soil temperature, SPEI, relative humidity, precipitation, and soil-moisture anomalies as key predictors. Regionally, soil temperature rose (+0.069 °C yr⁻¹), while rainfall (−1.203 mm yr⁻¹) and relative humidity (−0.075% yr⁻¹) declined. Spatial analyses demonstrated expanding heat hotspots and persistent soil moisture deficits. Although 2018–2019 were anomalously wet, recent years (2021–2023) exhibited severe drought. Full article

(This article belongs to the Topic Disaster and Environment Monitoring Based on Multisource Remote Sensing Images)

18 pages, 2306 KB

Open AccessArticle

Computer Simulation as a Tool for Cost and CO₂ Emission Analysis in Production Process Simulations

by Szymon Pawlak and Mariola Saternus

Sustainability 2025, 17(24), 10932; https://doi.org/10.3390/su172410932 (registering DOI) - 7 Dec 2025

Abstract

Sustainable development is currently a key priority in improving production systems, requiring an integrated approach that combines economic efficiency, environmental responsibility, and rational energy management. In response to these challenges, this article presents a novel application of computer simulation as a tool for [...] Read more.

Sustainable development is currently a key priority in improving production systems, requiring an integrated approach that combines economic efficiency, environmental responsibility, and rational energy management. In response to these challenges, this article presents a novel application of computer simulation as a tool for comprehensively assessing the impact of technological improvements in the machining process. The study introduces and compares two models: a baseline model representing the actual state of the machinery fleet with conventional machine tools, and an innovative alternative model incorporating modern numerically controlled (CNC) machines. The results demonstrate, for the first time in this context, that the implementation of CNC technology not only significantly reduces process time and energy demand but also improves resource efficiency, thereby lowering CO₂ emissions and operating costs. This research highlights the innovative use of computer simulation to support decision-making in sustainable manufacturing, offering a practical framework for evaluating technological modernization options and promoting the sustainable development of production enterprises. Full article

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22 pages, 9023 KB

Open AccessArticle

From Experiment to Example: Evaluating the Sustainability of Shore Nourishment in the Southeastern Baltic (Palanga, Lithuania)

by Donatas Pupienis, Darius Jarmalavičius, Gintautas Žilinskas and Dovilė Karlonienė

Sustainability 2025, 17(24), 10931; https://doi.org/10.3390/su172410931 (registering DOI) - 7 Dec 2025

Abstract

Coastal erosion and increasingly severe storms present a growing challenge to the sustainable management of sandy shorelines. This study examines the geomorphological, sedimentological and geochemical responses of the Palanga coastal area in the Lithuanian Baltic Sea to beach nourishment projects implemented between 2006 [...] Read more.

Coastal erosion and increasingly severe storms present a growing challenge to the sustainable management of sandy shorelines. This study examines the geomorphological, sedimentological and geochemical responses of the Palanga coastal area in the Lithuanian Baltic Sea to beach nourishment projects implemented between 2006 and 2012. A multi-parameter approach was used, combining cross-shore profile monitoring with grain-size, magnetic susceptibility, mineralogical and geochemical analyses, in order to assess sediment redistribution and post-nourishment adjustments. The results demonstrate that nourishment projects substantially increased beach width, height and sand volume; however, the shoreline response was uneven in space and time. Subsequent years were characterised by gradual sediment redistribution along and across the coast, resulting in partial morphological stabilisation. Elevated concentrations of heavy minerals and trace elements immediately after nourishment indicated short-term enrichment from mineralogically distinct material, which was later diluted by natural reworking. The findings demonstrate that properly designed and monitored nourishment enhances coastal resilience, representing a human-induced adjustment within the prevailing coastal morphodynamic regime. While the socio-ecological effects were not directly evaluated, the identified geoindicators offer insights into the physical sustainability of coastal systems, emphasising the importance of evidence-based, adaptive management in line with the United Nations Sustainable Development Goals (SDGs 11, 13 and 14). Full article

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18 pages, 417 KB

Open AccessArticle

Selective Attributes and Purchase Behavior for Black Sesame (Sesamum indicum L.) Seolgi: An Empirical Study of South Korean Consumers

by Chan Ho Choi, Ji Ahn Han and Ki Han Kwon

Sustainability 2025, 17(24), 10930; https://doi.org/10.3390/su172410930 (registering DOI) - 7 Dec 2025

Abstract

The purpose of this study is to examine how the selective attributes of Heugimja Seolgi, a traditional Korean food, influence consumers’ purchasing behavior. Data were collected through an online survey of adults in their 20s to 60s residing in the Republic of [...] Read more.

The purpose of this study is to examine how the selective attributes of Heugimja Seolgi, a traditional Korean food, influence consumers’ purchasing behavior. Data were collected through an online survey of adults in their 20s to 60s residing in the Republic of Korea who had previously consumed Heugimja Seolgi. Most respondents were in their 30s (34.5%) and 60s (25.7%). A total of 342 valid responses were analyzed using SPSS 25.0. Diversity and image, as sub-factors of the selective attributes for Heugimja Seolgi, were found to have a significantly positive impact on repurchase behavior, whereas quality did not show a statistically significant effect. This finding suggests that to increase repurchase rates, these factors must be considered, as Heugimja Seolgi is commonly chosen as a meal replacement, snack, or gift. Consumers also place great importance on the hygiene, cleanliness, and image of the stores selling the product. Ongoing research in this area is essential for the sustainable development of the Korean rice cake industry and is expected to contribute significantly to promoting the cultural and nutritional significance of traditional Korean rice cakes. Full article

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18 pages, 1683 KB

Open AccessArticle

The Cascade of Exclusion: A Mixed-Methods Study of Welfare Inequity and Its Foundational Determinants Among Thailand’s Homeless Population

by Warisara Kitkiwan and Chitralada Chaiya

Sustainability 2025, 17(24), 10929; https://doi.org/10.3390/su172410929 (registering DOI) - 7 Dec 2025

Abstract

Achieving sustainable development (SD) and enhancing urban quality of life are undermined by the systemic exclusion of marginalized groups. Despite the global expansion of welfare systems, a welfare paradox persists, wherein universal policies often reinforce exclusion. This study investigates this paradox through a [...] Read more.

Achieving sustainable development (SD) and enhancing urban quality of life are undermined by the systemic exclusion of marginalized groups. Despite the global expansion of welfare systems, a welfare paradox persists, wherein universal policies often reinforce exclusion. This study investigates this paradox through a mixed-methods analysis of welfare inequity among homeless individuals in Khon Kaen, Thailand. Combining a quantitative survey (n = 202) with in-depth interviews of homeless persons and state officials, we model the structural nature of this exclusion. Results reveal systemic disparities by gender, age, and displacement causes. Critically, a predictive model identifies housing and education access as foundational determinants, collectively explaining 89.9% of the variance in economic inclusion (R² = 0.899, p < 0.001). Qualitative data elucidate the mechanisms behind these statistics, highlighting how the lack of official documentation and institutional stigma sever access to the broader welfare system. We conceptualize these interdependencies as a foundational capability cascade, where deficits in core domains trigger compounding exclusion. By integrating statistical modeling with narrative evidence, this research provides a robust framework for social exclusion and offers an evidence-based roadmap for designing equity-focused policy reforms that are essential for inclusive urban sustainability. Full article

(This article belongs to the Special Issue Quality of Life in the Context of Sustainable Development)

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23 pages, 744 KB

Open AccessArticle

Driving Sustainable Entrepreneurship Through AI and Knowledge Management: Evidence from SMEs in Emerging Economies

by Qasem Mohammed Alshammakhi and Riyaz Abdullah Sheikh

Sustainability 2025, 17(24), 10928; https://doi.org/10.3390/su172410928 (registering DOI) - 6 Dec 2025

Abstract

This study investigates how artificial intelligence (AI) capabilities shape sustainable entrepreneurship (SE) among small and medium-sized enterprises (SMEs) in emerging economies. Focusing on knowledge management (KM) as a mediator, entrepreneurial orientation (EO) as a moderator, and government policy support (GPS) as an enabler, [...] Read more.

This study investigates how artificial intelligence (AI) capabilities shape sustainable entrepreneurship (SE) among small and medium-sized enterprises (SMEs) in emerging economies. Focusing on knowledge management (KM) as a mediator, entrepreneurial orientation (EO) as a moderator, and government policy support (GPS) as an enabler, the research draws upon the Knowledge-Based View, Dynamic Capabilities Theory, and Institutional Theory. Using data from Saudi Arabian SMEs operating within the Vision 2030 agenda, the structural model demonstrates that AI primarily influences sustainability when firms possess robust KM systems capable of translating digital insights into actionable practices. Both EO and GPS strengthen the conversion of knowledge into sustainable outcomes, where EO fosters innovation and proactivity, and GPS provides essential resources and legitimacy. Nevertheless, excessive reliance on policy incentives may divert firms toward compliance rather than substantive transformation. Conceptually, this paper situates KM at the core of sustainability transformation, with policy support shaping the institutional context. The findings offer actionable guidance for SME managers and policymakers seeking to advance the United Nations Sustainable Development Goals (SDGs) through strategic engagement with AI and KM. Full article

(This article belongs to the Special Issue AI-Driven Entrepreneurship and Sustainable Business Innovation)

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23 pages, 13024 KB

Open AccessArticle

Assessing Urban Flood Risk and Identifying Critical Zones in Xiamen Island Based on Supply–Demand Matching

by Lin Cheng, Guotao Li, Gong Liu and Zhi Zheng

Sustainability 2025, 17(24), 10927; https://doi.org/10.3390/su172410927 (registering DOI) - 6 Dec 2025

Abstract

The supply–demand relationship of flood regulation services (FRS) plays a vital role in mitigating urban flooding. Yet, existing studies still fall short in the comprehensiveness of FRS indicators, the accuracy of assessment scope, and the fine-scale analysis needed to delineate spatial supply–demand features [...] Read more.

The supply–demand relationship of flood regulation services (FRS) plays a vital role in mitigating urban flooding. Yet, existing studies still fall short in the comprehensiveness of FRS indicators, the accuracy of assessment scope, and the fine-scale analysis needed to delineate spatial supply–demand features and precisely identify critical areas. Using Xiamen Island as a case study, we first quantify ecosystem-based FRS supply with the InVEST model and assess socioeconomic FRS demand under the H-E-V framework; second, we perform parcel-level supply–demand matching to identify spatial patterns and typologies; then, we diagnose FRS status via the coupling–coordination degree model (CCDM); and finally, we delineate flood-risk hotspots through priority-intervention grading. The results indicate that (1) higher FRS supply clusters in the south, southwest, and northeast, whereas demand is markedly higher in the central–northern sector, yielding an overall pattern of “pronounced mismatch in the central and north, with relatively sufficient supply along the periphery.” (2) Low supply–high demand zones exhibit the highest flood risk and contain higher proportions of industrial, transportation, and residential land. (3) These low supply–high demand zones are further subdivided into five priority-intervention levels, for which we propose tiered, differentiated risk-management strategies. Collectively, the findings clarify supply–demand mechanisms and mismatch characteristics, providing decision support for urban flood safety and sustainable development. Full article

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31 pages, 8537 KB

Open AccessReview

Research Progress in Sustainable Mechanized Processing Technologies for Waste Agricultural Plastic Film in China

by Jiayong Pei, Mingzhu Cao, Hongguang Yang, Fengwei Gu, Feng Wu, Man Gu, Peng Chen, Chenxu Zhao and Peng Zhang

Sustainability 2025, 17(24), 10926; https://doi.org/10.3390/su172410926 (registering DOI) - 6 Dec 2025

Abstract

The mechanized processing of waste agricultural film is a crucial technical pathway for addressing agricultural-film pollution. Achieving resource recovery through mechanized waste-film processing—and thereby promoting the sustainable management of agricultural-film pollution—remains a major challenge for green agricultural development. This study systematically reviews the [...] Read more.

The mechanized processing of waste agricultural film is a crucial technical pathway for addressing agricultural-film pollution. Achieving resource recovery through mechanized waste-film processing—and thereby promoting the sustainable management of agricultural-film pollution—remains a major challenge for green agricultural development. This study systematically reviews the progress and limitations of shredding and film–impurity separation technologies deployed in China’s mechanized waste-film treatment. Based on multi-database searches and citation tracking of the literature published between 2000 and 2025, it comparatively evaluates key unit operations, including cutterhead/blade kinematics, specific energy-consumption (SEC) control, and airflow (air-classification) separation, complemented by engineering analyses of representative machinery. The findings indicate that integrated mechanized recovery lines have become the mainstream approach, although the recovered fraction still contains a high impurity load. Drum-type and shear-type shredding exhibit trade-offs between energy efficiency and mitigation of film wrapping/entanglement. Airflow separation and drum-screen or vibrating-screen modules show reduced separation efficiency and process stability at high moisture contents or when impurities have particle sizes comparable to the film; system complexity and maintenance burdens also warrant consideration. To address these issues, a process framework is proposed that integrates drum pre-crushing, shear fine shredding, air classification, and multi-stage screening, together with variable-frequency drive (VFD) speed control, torque monitoring, and modular design, providing a sustainable pathway for the clean separation and resource recovery of agricultural plastic film waste. Full article

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16 pages, 226 KB

Open AccessArticle

Promoting Moral Values and Improving Academic Achievement Through Sustainable Learning for University Students

by Zohra Lassoued, Amina Badidja and Kheira Lazar

Sustainability 2025, 17(24), 10925; https://doi.org/10.3390/su172410925 (registering DOI) - 6 Dec 2025

Abstract

This study aims to identify the effect of using a problem-solving-based sustainable learning model in the Educational Guidance and Counseling course, aiming to promote moral values and enhance the academic achievement of Education Sciences students at the University of El Oued in Algeria. [...] Read more.

This study aims to identify the effect of using a problem-solving-based sustainable learning model in the Educational Guidance and Counseling course, aiming to promote moral values and enhance the academic achievement of Education Sciences students at the University of El Oued in Algeria. A quasi-experimental design was used to measure the effect on (38 students) divided into two groups: an experimental group (19 students) and a control group (19 students). Data were collected through a pre-test and a post-test of the moral values scale, in addition to an achievement test administered to both groups. The results reveal that the use of the problem-based sustainable learning method has a positive impact on students of Education Sciences in terms of promoting their moral values and improving their academic achievement. Finally, this study recommends the necessity of applying sustainable learning models in university teaching as a way to contribute to the process of improving the outcomes of the higher education system. Full article

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