Search Results (5,676)

This study examines the impact of family multidimensional poverty on cognitive function among older adults in China using the 2018 Chinese Longitudinal Healthy Longevity Survey (CLHLS). Filling a critical gap in the existing literature, we construct a multidimensional poverty index (MPI) based on the Alkire-Foster methodology to evaluate cognitive decline within the context of China’s post-poverty-eradication landscape. Utilizing quantile regression analysis, our findings demonstrate that multidimensional poverty exerts a significant, negative effect on cognitive function, which is more pronounced among individuals at lower cognitive quantiles, consistent with the cumulative disadvantage theory. Furthermore, we identify substantial urban–rural and regional disparities, revealing unique socio-economic inequalities. By linking multidimensional poverty to elderly cognitive health through psychosocial pathways, this study provides empirical evidence that reducing multidimensional deprivation among older adults is integral to achieving both SDG1 and SDG3 in China’s post-eradication context, demonstrating that income-based metrics alone are insufficient to capture the full burden of poverty on elderly cognitive health. Full article

Ensuring uninterrupted access to essential medicines in public healthcare systems is a persistent challenge with clinical, economic, and environmental implications. Oncology services are particularly vulnerable to stockouts, which compromise therapeutic continuity and increase reliance on urgent procurement with high carbon and waste footprints. This study proposes a risk-informed, data-driven framework for pharmaceutical inventory governance in a high-complexity public oncology hospital in Chile, aligning with sustainability goals and green supply chain principles. Using operational data from 2023–2024, we integrate descriptive analytics, ABC–XYZ segmentation, and a continuous-review (s, Q) policy extended through a Logistic Risk Index (LRI) that consolidates demand variability, supply performance, and clinical-economic criticality. Empirical analysis reveals strong expenditure concentration in AX/AY segments and significant misalignment between institutional and analytically derived parameters. A Monte Carlo simulation N = 1000 runs per scenario) compares baseline, adjusted, and fully risk-informed policies under stochastic demand and lead-time conditions. Results show that the risk-informed configuration reduces stockout exposure by up to 46%, improves fill rates (93.1% → 96.4%), and shortens replenishment delays, while maintaining total logistic cost stability. Critically, urgent orders decrease from 27.4 to 14.8 per year, avoiding an estimated 630 kg CO₂ emissions and 25 kg of packaging waste annually. These findings demonstrate that resilience, efficiency, and sustainability are not competing objectives but can be jointly achieved through integrated analytics and governance. The proposed approach offers a scalable blueprint for public health systems seeking to transition from reactive inventory management toward anticipatory, transparent, and sustainability-oriented decision-making, contributing to SDG 3 (health and well-being) and SDG 12 (responsible consumption and production). Full article

The Ghanaian economy faces significant challenges in providing robust policy support and cohesive ecosystem structures that enable small- and medium-sized enterprises (SMEs) operating in the country to effectively convert entrepreneurial marketing activities into sustainable social outcomes. The research examines the effect of entrepreneurial marketing on sustainable social performance of SMEs using entrepreneurial ecosystem policy as the mediating variable. The Resource Dependency Theory, Resource-Based View and the Stakeholder Theory were utilized, and the study was designed a cross-sectional survey. The data collected were based on 386 SME owners and managers of different sectors in Ghana. Structural equation modeling with SmartPLS 3 was used to test the proposed relationships. The results indicate that entrepreneurial marketing has a significant positive impact on sustainable social performance. In addition to that, ecosystem policy has a strong and positive impact on sustainable social performance. The mediating effect of ecosystem policy in the relationship between entrepreneurial marketing and sustainable social was found to be positive. The research has limitations in that it was cross-sectional and specific to Ghana, which might limit its generalizability. Longitudinal and cross-country designs may be used in future studies to include the dynamic effects of policy interventions. Hypothetically, the research moves towards the mediating role of the ecosystem policy in the relationship between marketing and sustainability. In practice, the study findings highlight the necessity to use combined policy frameworks that empower SMEs to enhance their marketing strengths and social investments to meet Sustainable Development Goals (SDGs) 8, 9, and 12. The research finds that enabling policies of entrepreneurial ecosystems are needed to convert the marketing efforts by SMEs into a sustainable social value. Full article

The rapid growth of Digital Financial Services (DFSs), including what is occurring in Indonesia, necessitates evaluation methods that are capable of objectively and systematically handling multiple assessment criteria. Therefore, this study aimed to propose a hybrid FSS–CRITIC–TOPSIS framework for selecting optimal DFSs. Fuzzy soft sets (FSSs) were used to model uncertainty and subjectivity in criterion assessments. The Criteria Importance Through Inter-criteria Correlation (CRITIC) method determined the weights objectively based on the degree of contrast and inter-criteria correlation. Subsequently, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method was used to rank the alternatives based on the closeness to the ideal solution. The incorporation led to a formally defined decision operator, τ, which mapped FSS to complete preference orderings while ensuring provable stability and strong discriminative properties. The framework was applied to five major Indonesian digital wallets, namely ShopeePay, GoPay, OVO, LinkAja, and DANA, as well as being evaluated across five criteria. This framework identified DANA as the optimal alternative, with a score of 0.9282, followed by ShopeePay (0.8354) and GoPay (0.6958). Comparative analysis with other methods showed a near-perfect ranking correlation (ρ = 0.9−1) with a more proportional score distribution and ranking results that reflected actual conditions. Sensitivity analysis also confirmed robustness, with ranking changes remaining logically consistent underweight variations. In conclusion, the FSS-CRITIC-TOPSIS framework provided an effective, mathematically rigorous method for multi-criteria decision-making (MCDM) under uncertainty, which applied to digital wallet selection as well as potential extension to broader evaluation contexts supporting SDGs 8, 9, and 10. Full article

The Black Sea is highly vulnerable to environmental degradation, making the evaluation of contaminant transfer within its food webs essential for ecosystem protection, sustainable resource management, and human health risk assessment. Marine organisms accumulate contaminants through three main processes: bioconcentration (direct uptake from the abiotic environment), biomagnification (trophic transfer through consumption of contaminated prey), and bioaccumulation, which integrates contaminants from all exposure pathways. Despite numerous studies reporting contaminant concentrations in Black Sea waters, sediments, and biota, integrated analyses of trophic transfer within both pelagic and benthic food webs in the Romanian coastal sector remain limited. This study assessed the bioamplification of heavy metals—HMs, persistent organic pollutants—POPs (OCPs, PCBs) and polycyclic aromatic hydrocarbons—PAHs along the main pelagic and benthic food webs in the Romanian coastal sector, based on concentrations measured in representative invertebrate and fish species. The results revealed a compartment-driven contamination pattern, with the benthic food web functioning as an important reservoir and transfer pathway. Heavy metals showed variable and context-dependent trophic transfer, with selective amplification for Cu and Ni in some benthic links, trophic dilution or neutral transfer for Cd and Pb, and more consistent retention for Cr. In contrast, several PCB congeners showed clear biomagnification, particularly in benthic predator–prey relationships. PAHs displayed compound-dependent trophic transfer, with more pronounced amplification in benthic pathways. Overall, biomagnification was stronger for organic pollutants, particularly PCBs, than for heavy metals. The study contributes to two United Nations Sustainable Development Goals (SDGs): SDG 14 (Life Below Water) and SDG 12 (Responsible Consumption and Production). Full article

Mountain Social–Ecological Systems (MtSES) are global assets, providing essential ecosystem services to nearly half of humanity, yet they are disproportionately vulnerable to global change, experiencing “polytraps” of depopulation, poverty, and environmental degradation. Despite the inherent human dimension in sustainability, the social pillar remains conceptually chaotic, forming a highly fragmented “publication labyrinth”, and is often neglected in favor of more easily quantifiable environmental and economic metrics. These oversights leave mountain communities in a precarious state, underscoring an urgent need for robust, context-specific assessment tools. This paper addresses this critical gap by employing a two-step methodology: first, a literature review identifies prevailing social sustainability issues in mountain contexts; second, a comparative analysis evaluates prominent frameworks and indicator-based tools against these themes, using Ostrom’s multi-tier Social–Ecological Systems (SES) framework as the theoretical lens. Our findings reveal a persistent environmental bias in MtSES research and highlight the necessity for frameworks that integrate local knowledge, address power imbalances, and support bottom-up governance. A tool is proposed with indicators specifically for mountainous contexts. This study contributes to theory by offering a structured approach to unpack the elusive “social” in SES and to practice by providing a model and tool for developing actionable, context-sensitive social sustainability assessments, thereby fostering resilience and equitable development in vulnerable mountain regions. Ultimately, by operationalizing these social dimensions, this research provides a direct roadmap for achieving key United Nations Sustainable Development Goals in marginalized high-altitude contexts, particularly focusing on No Poverty (SDG 1), Good Health and Well-being (SDG 3), Reduced Inequalities (SDG 10), Sustainable Communities (SDG 11), and Peace, Justice, and Strong Institutions (SDG 16). Full article

Climate change and rapid urbanization are intensifying flood risks in China, particularly in regions with complex terrain and dense populations. Traditional risk assessment methods often lack the flexibility to handle uncertainties in multi-dimensional risk systems. This study proposes a probabilistic flood risk assessment framework integrating Monte Carlo simulation with a composite indicator system from the perspective of disaster system theory. Taking Hunan Province as a case study, we constructed a hierarchical indicator system encompassing environmental susceptibility, hazard intensity, exposure vulnerability, and mitigation capacity. The analytic hierarchy process (AHP) and coefficient of variation (CV) methods were combined for indicator weighting, and Monte Carlo simulation was employed to quantify uncertainties and classify risk levels. Results reveal significant spatial heterogeneity in flood risk across the province, with high-risk areas concentrated in regions exhibiting intense rainfall, dense river networks, and insufficient mitigation infrastructure. The study provides a transferable, data-driven approach for spatially explicit flood risk zoning, offering evidence-based insights for land-use planning, resilient infrastructure development, and sustainable flood governance. This research contributes to the integration of probabilistic modeling into land system science, supporting disaster risk reduction and climate adaptation strategies aligned with SDG 11. This study also provides policy-relevant insights for regional flood governance by supporting risk-informed land-use planning, targeted infrastructure investment, and adaptive flood management strategies, thereby contributing to more resilient and sustainable land system development under increasing climate uncertainty. Full article

Global climate change and increasingly complex geological conditions have led to more frequent landslides in the red-bed sedimentary layers of western Sichuan, China, posing severe threats to human safety and hindering progress toward regional Sustainable Development Goals (SDGs), particularly those related to disaster risk reduction and ecological protection. To address this challenge and advance sustainable disaster management, this study proposes a lightweight hybrid model, termed Transformer–Attention–LSTM, which integrates the global attention mechanism of Transformers with the local time-series modeling capabilities of Long Short-Term Memory networks. Focusing on the Kuyaogou landslide, the model achieves an optimal balance between parameter scale, sequence length, and prediction accuracy. The mean Coefficient of Determination (R²) values for the test samples in the X, Y, and Z directions reached 0.948, representing enhancements of 9.9%, 4.2%, and 2.3%, respectively, compared to the suboptimal Attention–LSTM model. Concurrently, the Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) were reduced to 9.23 mm and 7.17 mm, respectively. Based on these displacement predictions, the landslide evolution stage was determined by calculating the tangent angle, indicating that the Kuyaogou landslide will remain in a stable creep phase over the ensuing ten-day period with low overall risk of rapid movement, though localized instability requires continued monitoring. This research provides a ‘small, fast, and accurate’ paradigm for red-bed landslide displacement prediction, offering scientific support for disaster prevention and emergency decision-making. The framework demonstrates potential for broader application in monitoring other geological hazards, thereby contributing to the implementation of sustainable development strategies in geohazard-prone regions. Full article

The Sustainable Development Goals (SDGs) are global objectives adopted by countries worldwide to achieve sustainable development by 2030 and consist of 17 goals and 169 specific targets. Among them, SDG 15 (Life on Land) aims to conserve terrestrial ecosystems and promote their sustainable use. Successful implementation of SDG 15 requires continuous management of terrestrial ecosystems and positive forest transitions. However, systematic analyses examining the role of green official development assistance (ODA), which supports environmental improvement in developing countries, remain limited. Accordingly, this study investigates the role that green ODA can play in forest transitions. Focusing on green ODA provided to developing countries between 2010 and 2023, this study employed shapley additive explanations (SHAP), an explainable artificial intelligence (XAI) technique, to predict its influence on SDG 15 implementation scores and to analyze the contributions of economic, environmental, and social indicators. In addition, a SHAP value-based decomposition and a gap index were calculated to examine the contribution of green ODA relative to its input. The results indicate that the overall contribution of green ODA to SDG 15 implementation in developing countries is relatively limited. However, statistically significant effects were observed in country groups with higher levels of SDG 15 implementation performance. In contrast, the effects were weakened or constrained in some country groups with lower levels of SDG 15 implementation. These findings suggest that green ODA may function as a transition accelerator that facilitates positive forest transitions in countries with stronger capacities for implementing SDG 15. Strengthening and improving the existing limitations of green ODA could enhance its role and enable it to contribute more effectively to sustainable development and the conservation of terrestrial ecosystems in developing countries. Full article

This review paper takes as its starting point a number of intriguing conundrums. Firstly, there is much interest in the research community in the assessment of happiness as a part of sustainability, including the development of indicators and indices, although it is often acknowledged that quantifying something as subjective as happiness is a challenge. Secondly, despite this compelling and oft-repeated case, the Sustainable Development Goal (SDG) indicator framework has just one mention of ‘happiness’ in all the 267 indicator metadata documents. While ‘sustainable happiness’ is often stated as a desired outcome of the SDGs, it seems that happiness has not been regarded as part of the ongoing assessment process. The review answers the question as to why that should be so. The methodology is founded on a review of the existing literature on SDG indicators and happiness, especially the insights gained from established examples of happiness indices, such as the Gross National Happiness Index (GNHI) of Bhutan and the Happy Planet Index (HPI), as well as other initiatives to create such indices in parallel to the SDGs, such as the ‘SDGs for Happiness’ and the ‘Sustainable Wellbeing Index’. Given that indicators and indices are typically intended to attract attention from the media, the paper explores the reporting of various happiness indices in one form of media—newspapers. One would expect that happiness indicators and indices would have an attraction for journalists, but do they? The review concludes that the complexity of measuring happiness on top of a ‘quagmire’ (as some authors put it) of quantification challenges with the SDG indicators seems the most likely explanation for its absence to date. But with experience gained by 2030, maybe there will be an opportunity to consider the inclusion of happiness, drawing insights in particular from the GNHI and HPI, for a successor SDG indicator framework. Full article

Against the backdrop of the United Nations Sustainable Development Goals (SDGs), innovation-driven development serves as the core engine of long-term sustainable economic development, while resource misallocation has emerged as a critical bottleneck constraining sustainable innovation and coordinated regional development. Grounded in the neoclassical theory of factor allocation, this paper incorporates capital misallocation, labor misallocation and the digital economy into a unified analytical framework. Using China’s provincial panel data spanning 2001 to 2024, we systematically investigate the impact effects, underlying transmission mechanisms and regional heterogeneity of resource misallocation and the digital economy on scientific and technological innovation through benchmark regression, robustness tests and heterogeneity analysis. The results show that resource misallocation exerts a significant and robust inhibitory effect on technological innovation, with the inhibitory effect of capital misallocation being more pronounced than that of labor misallocation. The digital economy has a significant positive driving effect on technological innovation, and it can also indirectly boost technological innovation by alleviating resource misallocation, with its mitigating effect on resource misallocation presenting obvious structural differences and a stronger correction effect on capital misallocation than on labor misallocation. Economic growth and technological innovation form a mutually reinforcing “growth-innovation” virtuous cycle. In addition, the innovation effects of both resource misallocation and the digital economy exhibit significant regional heterogeneity, where the digital economy’s innovation-driven effect and misallocation-mitigating effect are notably stronger in eastern China than in the central and western regions. The theoretical contribution of this paper lies in constructing a transmission mechanism framework of “digital economy to resource misallocation to technological innovation”, which enriches the connotations of factor allocation and innovation theories. Its practical value is to provide policymakers with differentiated development paths for the digital economy and optimization strategies for factor allocation, thus facilitating the effective implementation of the innovation-driven development strategy. Full article

Background: The decline in physical activity during the transition to early adolescence poses a significant threat to lifelong health and well-being, directly impacting the targets of Sustainable Development Goal 3 (SDG 3). To design effective preventive interventions, researchers need developmentally appropriate tools to measure the psychological drivers of physical activity. Objectives: This study aimed to adapt the Attitude Towards Sport Scale (ATSS) for middle school students (ages 10–15) and evaluate its psychometric properties. Methods: We used a mixed-methods approach comprising a qualitative cognitive think-aloud phase (n = 27) and a quantitative cross-sectional validation phase (N = 531). Data were analyzed using robust Confirmatory Factor Analysis (CFA). Results: The results supported the structural model, demonstrating that the original three-factor structure fits the early adolescent sample acceptably. The scale demonstrated high composite reliability across all dimensions. Furthermore, the adapted ATSS-EA showed strong criterion-related validity through high correlations with perceived physical literacy and actual physical activity durations. It also successfully differentiated between licensed athletes and non-licensed students. Conclusions: The adapted ATSS-EA provides a developmentally appropriate tool for educators and researchers to monitor sport attitudes and identify students at risk of physical disengagement. Full article

Massive Open Online Courses (MOOCs) serve as catalysts for sustainable education by democratizing access to lifelong learning. While this potentially positions them as a key driver of the United Nations Sustainable Development Goal 4 (SDG 4), their long-term impact depends heavily on the implementation of inclusive design and ethical governance. This study evaluates the social sustainability of the AKADEMA platform—defined through equity of access, institutional trust, and long-term learner retention—using Badrul Khan’s e-learning framework. Employing a multi-layered mixed-methods design, the study triangulates subjective user perceptions—gathered via quantitative surveys (N = 209; a convenience sample of 6140 contacted users) and qualitative insights (n = 122)—with objective structural evidence from a technical accessibility audit. Although the results indicate high satisfaction with pedagogical quality, the findings reveal specific structural nuances regarding platform inclusivity and user diversity. Specifically, data triangulation highlights a notable ‘privacy awareness gap’—where working professionals demonstrate higher sensitivity regarding data governance than learners—alongside structural barriers hindering ‘Universal Design’ for learners with disabilities. Consequently, to strengthen the sustainability of open education models, future strategies should emphasize digital equity and institutional trust, ensuring that technical environments align with the promise of inclusive quality education. Full article

Noise pollution has become an increasingly discussed environmental problem in recent years. Developing a traffic infrastructure and recent sustainability goals require new solutions to mitigate noise pollution. This paper investigates the efficiency of the noise barrier made entirely of recycled materials. This solution would help achieve the United Nations sustainable development goals (SDGs). The proposed barrier target SDGs are: Good Health and Well-being (SDG 3); Industry, Innovation, and Infrastructure (SDG 9); Sustainable Cities and Communities (SDG 11); Climate Action (SDG 13). The changed barrier parameters were the parameters of the perforated panel and the air gap behind the porous material. To solve the optimisation problem, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method was used. The results showed that the proposed barrier configuration was the following: perforation shape—round, perforation diameter—5 mm, increment angle perforation—30°, thickness of the perforated panel—10 mm, porous absorbing material (composite rubber granule and hemp shive panel (RGHS))—50 mm thick, 20% of hemp shive content, air gap between absorbing material and the rigid backing—100 mm. The total thickness of the noise barrier was 180 mm. The acoustic parameters of the noise barrier structure were: α_avg. = 0.24, peaking at 0.51 (1250 Hz) and R_W = 39.7 ± 1.0 dB. These results indicate that the proposed barrier made of recycled materials could be a sustainable alternative for noise pollution mitigation and improving people’s quality of life. Full article

The Air-front Smart City (ASC) concept is proposed to address the stagnation of industries in developed countries and stimulate economic growth in developing countries while maintaining a higher quality of life for people and contributing to decarbonization and overall United Nations SDGs in an existing study. However, no studies have been conducted to assess ASC policies. Therefore, this study integrates the integrated accessibility index into the quality of life (QOL) and quality of business (QOB) evaluation models to assess the startup ecosystem in Aichi, Singapore, and Munich within the ASC concept. The study uses survey data conducted in Aichi to estimate monetary values of QOL and QOB component indicators, calculates the integrated accessibility indices, and estimates QOL and QOB. Furthermore, the study sets scenarios to assess the impacts of living and business urban policies in Aichi. Additionally, the study using Aichi parameters compares the startup ecosystem in Singapore and Munich. The result shows that the key drivers of startup attraction are corporate tax rate, economic growth, and safety; enhancing these indicators directly increases startups’ QOB, business partners, and residents’ QOL. It was found that QOB in Singapore is comparatively higher, whereas QOL is higher in Aichi. Full article