Search Results (4,599)

Supplier selection in healthcare is a complex multi-criteria decision-making (MCDM) challenge requiring a balance of sustainability, resilience, and operational efficiency. Traditional methods struggle with scalability and subjectivity when applied to large administrative datasets. This study introduces a transparent hybrid Machine Learning–MCDM (ML–MCDM) framework, validated using a U.S. Medicare dataset of 661 suppliers. The framework integrates eXtreme Gradient Boosting (XGBoost) and SHapley Additive exPlanations (SHAP) for criterion prioritization, the Full Consistency Method (FUCOM) for mathematically consistent weighting, and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) for final ranking. As the dataset lacks direct sustainability metrics, seven indicators were synthetically generated; thus, the results serve as proof-of-concept demonstration of the framework’s architecture. Specifically, XGBoost–SHAP is trained to predict a synthetically constructed Overall Performance Score (OPS), meaning that the resulting feature importance output constitutes an algorithmic consistency check—confirming that the pipeline correctly recovers importance signals deliberately embedded in the training target. For interpretability, suppliers were segmented into five performance profiles via K-Means: Strategic Partners (17.7%), Green Leaders (18.6%), Reliable Emergency Suppliers (18.2%), Balanced Performers (20.4%), and Developing Suppliers (25.1%). Carbon Footprint Score (0.408) and Emergency Response Capability (0.316) achieved the highest feature importance. FUCOM-derived weights prioritized On-Time Delivery Rate (0.272), Carbon Footprint Score (0.222), and Emergency Response Capability (0.220). The top supplier attained a TOPSIS closeness coefficient of 0.800, showing strong discrimination. Sensitivity analysis across four scenarios confirmed ranking robustness, maintaining Spearman correlations ρ ≥ 0.977. This ML–FUCOM–TOPSIS approach provides an auditable, scalable, and policy-relevant decision-support tool, enabling procurement managers to navigate high-dimensional data while ensuring operational continuity and environmental responsibility in healthcare supply chains. Full article

This paper examines the role of Multimodal Journey Planners (MJPs) as a link between user-oriented personalization and the broader societal goals of sustainable urban mobility. In smart cities, MJPs may serve as digital decision-support tools that connect individual mobility choices with broader sustainability objectives. Although contemporary journey planners increasingly display multiple criteria, such as travel time, cost, CO₂ emissions, and number of transfers, they still generally rely on predefined and non-personalized criterion weights and rarely infer travellers’ actual preferences from observed choices. The paper therefore proposes a transparent methodological proof-of-concept that combines multicriteria decision-making and inverse optimization to discover individual preference weights and enable personalized, preference-aware planning of multimodal routes. The Weighted Sum Method (WSM) is adopted as the basic ranking framework, and the proposed approach is evaluated within a controlled methodological testbed based on multimodal journey scenarios in Vienna. The results indicate that, within the available methodological testbed, the preference-discovery-based model achieved closer in-sample agreement with user-provided route evaluations than the model based on explicitly rated criteria. This was observed in the ranking-agreement analysis, where a more favourable penalty-point ratio was obtained in 19/21 cases (90.5%) and in the numerical error comparison, where lower in-sample reconstruction errors were obtained for 18/21 users (85.71%) across all scenarios. The paper further considers the tension between individual and system-level goals, as well as a conceptual extension toward system-aware re-ranking of alternatives. Within the broader framework of smart mobility, the importance of interoperability and open data is also recognized, with National Access Points (NAPs) for multimodal travel information potentially representing an important precondition for the development of advanced and transparent MJP solutions. Full article

The structure, functionality, nutritional value, and sensory properties of food are significantly influenced by interactions between proteins and carbohydrates. These interactions occur through hydrogen bonding, electrostatic forces, hydrophobic interactions, and, in many cases, the covalent attachment of sugars to proteins via the Maillard reaction. High starch content in food matrices promotes interactions between proteins and starch components such as amylose and amylopectin, affecting gelation, retrogradation, and thickening. These interactions improve shelf stability and product quality. Additionally, protein–carbohydrate interactions regulate nutrient digestibility and glycemic response, playing a crucial role in the development of functional foods for diabetes and weight management. In silico studies have demonstrated that dietary fibers like pectin and cellulose can improve water retention and textural properties in processed meat products. Furthermore, processing techniques such as enzymatic hydrolysis, fermentation, pulsed electric fields (PEF), and low-temperature drying have been found to improve the functional properties and shelf life of food products. This review synthesizes recent findings on protein–carbohydrate interactions and highlights their potential in creating healthier, more appealing, and sustainable foods that align with modern consumer preferences. Full article

Informal waste picking and scrap collection constitute critical yet highly precarious livelihood strategies among economically marginalised women in rural South Africa. This article presents a cross-sectional mixed-methods study, guided by Sen’s Capability Approach as its analytical framework, examining the lived experiences, motivations, and livelihood outcomes of 126 Black African women engaged in scrap collection along the N2 Highway in the Eastern Cape, specifically in Mthatha, Xhora, and Qumbu. The study integrates quantitative descriptive statistics with qualitative thematic analysis derived from structured interviewer-administered questionnaires. The findings indicate that participation in scrap collection is overwhelmingly driven by structural economic constraints, including chronic unemployment, household poverty, and extensive caregiving responsibilities, rather than autonomous occupational choice. The sample is characterised by limited educational attainment, frequently disrupted by poverty, bereavement, early marriage, and early caregiving roles, which collectively constrain access to formal employment opportunities. Participants consistently described scrap collection as physically hazardous, economically insecure, and detrimental to both physical health and psychosocial wellbeing, while remaining indispensable for household survival. Through the lens of the Capability Approach, these conditions reflect severe restrictions in substantive freedoms, particularly in relation to economic security, bodily health and human dignity. Expressions of acceptance are interpreted as manifestations of adaptive preferences formed under conditions of prolonged structural deprivation rather than indicators of genuine agency. The study contributes to informal economy scholarship by demonstrating how intersecting structural inequalities constrain capability sets and limit livelihood trajectories and calls for targeted policy interventions to enhance occupational safety, income security and access to sustainable livelihood alternatives. Full article

In the current context, where sustainability has become a global imperative, emerging markets have increasingly incorporated green finance as a strategic pillar to foster long-term growth and stability. This study examines the evolution, trends, and key challenges of sustainable investment in emerging economies, with a particular focus on the integration of environmental, social, and governance (ESG) criteria. A systematic literature review was conducted using Scopus and Web of Science, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol, based on a sample of 399 articles published over the past decade. The findings reveal a significant expansion in academic output on ESG investments in emerging markets, with an average annual growth rate of 14.06% and an international co-authorship rate of 37.34%. China, the United Kingdom, South Africa, and the United States emerge as leading contributors, particularly since 2020. However, critical gaps persist, including inconsistencies in ESG ratings and the limited adaptation of ESG frameworks to local socioeconomic and institutional conditions. Future research should focus on strengthening public policy frameworks, designing effective fiscal incentives, assessing the distributive implications of green finance, and leveraging technologies such as fintech, blockchain, and artificial intelligence to enhance ESG rating consistency, transparency, risk measurement, and the overall efficiency of sustainable investments. Full article

Optimizing nitrogen management is essential for maintaining high spring maize yield while mitigating nitrous oxide (N₂O) emissions in irrigated areas. However, the interactive effects of total nitrogen application rate and starter nitrogen proportion on yield and N₂O emissions remain insufficiently quantified. Reliable assessment of these interactions requires well-calibrated DeNitrification–DeComposition (DNDC) simulations, yet existing calibration studies often emphasize crop parameters while neglecting soil parameters critical for soil hydrothermal dynamics and N₂O production. In this study, field data from shallow-buried drip-irrigated spring maize in Tongliao during 2024–2025 were used to conduct Extended Fourier Amplitude Sensitivity Test (EFAST) sensitivity analysis on 12 crop and 13 soil parameters of the DNDC model. Sensitive parameters were calibrated using the differential evolution algorithm, and 64 nitrogen management scenarios were simulated by combining eight total nitrogen application rates (100, 150, 200, 250, 300, 350, 400, and 450 kg N ha⁻¹) with eight starter nitrogen proportions (0%, 15%, 25%, 30%, 35%, 40%, 45%, and 50% of the total nitrogen rate). The results showed that DNDC outputs were jointly controlled by crop and soil parameters, among which maximum yield, leaf carbon-to-nitrogen ratio, stem fraction, grain carbon-to-nitrogen ratio, thermal degree days for maturity, grain fraction, soil organic carbon (SOC) decrease rate below topsoil, soil clay content, soil porosity, wilting point and depth of top soil with uniform SOC content were dominant. Compared with the conventional crop-parameter calibration, the sensitivity-screened parameter set improved the simulation of both cumulative N₂O emissions and yield. Across the 64 scenarios, cumulative N₂O emissions ranged from 0.42 to 4.87 kg [N]/ha, while simulated maize yield ranged from 1597 to 6347 kg [C]/ha. N₂O emissions increased with total nitrogen rate, whereas yield increased initially and then reached a plateau. Increasing the starter nitrogen proportion did not substantially enhance yield but increased N₂O emission risk under high nitrogen rates. Overall, the scenario with 300 kg/ha and no nitrogen applied at sowing achieved a relatively high yield of 5519 kg [C]/ha while maintaining a low cumulative N₂O emission of 0.98 kg [N]/ha and was therefore identified as the preferred trade-off strategy under shallow-buried drip irrigation. This study provides an EFAST–DNDC framework for optimizing nitrogen management to sustain spring maize yield while reducing N₂O emissions in the West Liaohe Plain. Full article

This study proposes a multi-criteria decision-making framework for determining optimal locations for shared micromobility stations in Kars, Türkiye. The approach integrates spatial data with structured expert evaluation and applies the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to rank candidate locations. Eight representative locations were evaluated based on five criteria: points of interest (POId), public transport distance, activity level, accessibility, and installation suitability. Spatial indicators were obtained through map-based measurements, while qualitative criteria were assessed using expert-based scoring by 11 experts. The results indicate that locations with high activity density, strong accessibility, and a high concentration of POIs achieve the highest suitability scores. The city center (L2) and Kafkas University (L1) were identified as the most suitable locations, with closeness coefficients of 0.862 and 0.783, respectively. In contrast, the train station (L5) showed the lowest suitability, with a closeness coefficient of 0.326. A sensitivity analysis confirmed that the ranking structure remained unchanged under moderate variations in criteria weights, indicating the robustness of the proposed model. The findings suggest that micromobility systems are primarily driven by intra-urban mobility demand rather than by long-distance transportation nodes. From a sustainability perspective, the proposed framework supports evidence-based planning of shared micromobility infrastructure, which can contribute to reducing dependence on private automobiles, improving urban accessibility, and promoting low-carbon transportation. The findings provide practical guidance for municipalities seeking to develop environmentally sustainable, socially accessible, and resource-efficient urban mobility systems in medium-sized cities. The framework can also support broader sustainable urban development strategies and contribute to the achievement of sustainable mobility objectives. Full article

This study investigates asymmetric consumer responses to recycled thermoplastics, with a focus on the roles of eco-consciousness, sustainability knowledge, perceived concerns, trust, and value congruence. Using survey data from Hungarian consumers, the study applies linear and binary logistic regression analyses to examine how these factors influence brand perception, willingness to pay, and communication preferences. The results show that economic concerns act as a dominant barrier, significantly reducing both brand evaluations and willingness to pay, while functional concerns play a more limited role. Trust in sustainability communication and positive brand perception emerge as strong predictors of willingness to pay, with brand perception showing a stronger effect. Eco-consciousness consistently influences consumer responses, whereas sustainability knowledge demonstrates more selective and context-dependent effects. In addition, consumers show a clear preference for credible, evidence-based communication, while informal and promotional signals are less effective. Overall, the findings highlight the importance of reducing perceived risk, strengthening brand perception, and aligning sustainability communication with consumer expectations to support the adoption of recycled thermoplastics in the automotive industry. Full article

Students’ reading preferences and voices are increasingly relevant for informing teaching practices and strengthening students’ motivation and engagement with reading, thus making their reading experiences meaningful. However, in Chile, there is still little evidence regarding the reading preferences and perspectives of primary school students. Therefore, this study analyzes students’ preferences and perceptions of the texts assigned by their teachers, as well as the pedagogical practices for reading mediation applied across various subjects in the La Araucanía Region of southern Chile. To this end, using a qualitative, multiple-case study design, we conducted 9 discussion groups on reading mediation and discourse genres with 96 students in grades 3–6, each connected to one of 6 outstanding teachers. Thus, we applied an inductive content analysis, constructing categories through initial coding, focused coding, and interpretive analysis, all of which underwent triple review and calibration by team members. The findings show that, in general, students value the support and scaffolding their teachers provide to facilitate reading, comprehension, and participation. However, they express a desire for greater agency in selecting texts and for more opportunities to engage in dialogue around these texts, especially in subjects other than Language Arts. These results highlight the importance of reading mediation across subjects, including student text selection and dialogic interaction, to promote motivation and sustained reading practices in primary education. Full article

This study introduces a comprehensive framework for understanding sustainable online shopping preferences, validated using survey data collected in Serbia and Slovenia in 2025 (n = 572), thereby enhancing its generalizability. The primary aim of this research is to examine the extent to which specific environmental, social, and economic indicators influence decision-making processes for online purchasing and delivery. A detailed quantitative analysis was conducted using a structured questionnaire that included a wide range of variables related to online shopping behaviors and delivery preferences. The findings indicate that preferences for sustainability are inherently complex and multifaceted, shaped by critical factors such as environmental concerns, social responsibility, trust, skepticism towards sustainability claims, willingness to pay (WTP), and price sensitivity. Demographic variables, particularly gender and age, show consistent links to preferences for environmental considerations and corporate social responsibility (CSR), while income impacts trust-related behaviors and WTP. Furthermore, the analysis distinguishes between two distinct decision-making approaches: a value-driven sustainability cluster represented by EcoIndex, SocialIndex, and WTPIndex, and a cost-minimization strategy focused on price sensitivity (PriceIndex), with trust acting as a related yet separate factor (CredibilityIndex). Overall, this study emphasizes that a range of interconnected dimensions significantly shape sustainable online shopping preferences. The study was conducted in two developing European countries. Additionally, the findings highlight the need to address universal market barriers, such as price sensitivity, information asymmetry, and consumer skepticism. In a business context, they underscore the importance of adopting advanced analytical methods to enhance decision-making and optimize sustainable business strategies. Full article

Increasing ocean temperatures are expected to increase the energy needs of marine organisms, therefore increasing food demand to sustain their metabolism. However, food is limited in the aquatic environment and reduced availability may be intensified by the advance of climate change. Despite the importance of these interacting factors, few studies have explored their combined effects, particularly in early stages of the fish. To address this gap, we investigated how increased temperatures and reduced food availability influence agonistic behaviors, risk-taking, exploratory activity, social preference, and shoal structure in the early stages of Sparus aurata (55 dph). Fish were exposed for two weeks to a cross-experimental design involving two temperature conditions (24 °C and 28 °C) and two levels of food availability (9% and 4.5% of body weight). Our findings revealed that temperature and food restriction significantly reduced aggressiveness. Fish subjected to low food availability, regardless of temperature, exhibited bolder behavior, took greater risks, and engaged in more exploration. Higher temperatures independently increased exploratory activity but did not affect risk-taking. Fish from the four treatment conditions demonstrated a preference to associate with shoals. However, under food restriction, fish were more likely to abandon their shoals, and the low food availability in the high temperature treatment led to looser shoal formations. Overall, our results suggest that food availability has a higher impact than temperature. Fish on low food availability reduced energy expenditure on aggressive behaviors, but engaged in riskier behaviors and increased exploration, probably in an effort to locate food resources. Full article

Walking tourism is an important form of thematic and sustainable tourism, especially in rural and naturally attractive destinations. It contributes to diversifying the tourist environments and improving destination management. This paper analyses the role of walking tourism in destination management and uses an integrated machine-learning model to predict tourist preferences. A key focus of this study is identifying the key factors influencing walking tourism preferences, including demographic, socioeconomic, behavioural, and activity-related variables. The methodology of this study is based on an integrated Machine Learning (ML) approach. CatBoostClassifier was used as the primary predictive model, and hyperparameter optimization was performed using Particle Swarm Optimization (PSO). Model interpretability was ensured through SHapley Additive exPlanations (SHAP) analysis, supported by CatBoost feature importance evaluation. This combination enables both high prediction accuracy and transparent explanation of variable influence. The research is based on 467 responses collected through an anonymous online survey. Results confirm that walking tourism is predominantly linked to natural and mountain experiences, which have strong implications for destination planning and tourism product development. The proposed model provides reliable predictions of tourist preferences under class imbalance conditions, achieving a macro-F1 score of 0.5114. Additionally, key factors influencing the choice of walking tours were identified, supporting destination managers in tourist segmentation, tourism product development, and sustainable allocation of destination resources. Full article

The South American silver croaker, Plagioscion squamosissimus, holds significant importance for the artisanal fisheries operating in the sub-middle and lower courses of the São Francisco River, located in northeastern Brazil. Its complex horizontal movement patterns and habitat-use preferences are not fully understood in the waters of hydroelectric dam reservoirs, raising important questions for the rational and sustainable management of this species. This study aimed to identify the habitat use of P. squamosissimus individuals captured in three fishers’ associations (Olho D’água do Casado, Petrolândia and Rodelas). Individuals were collected between September 2023 and March 2024. A selection of 25 individuals per location from the same age group (+2 years) was used, following annual age estimation based on existing growth curves. Element-to-calcium (element/Ca) ratios in the otolith cores and edges were determined using laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). The data were analyzed using univariate and multivariate statistics to assess the degree of separation between individuals in relation to natal origin (otolith cores) and time of capture (otolith edges) from the three sampling sites. Significant differences in element/Ca ratios between core and edges of the otolith were observed for Ba/Ca, Mg/Ca, Mn/Ca and Sr/Ca ratios. These results indicate an ontogenetic change in the habitat use, in which similarity in core signatures suggests a common natal origin, likely influenced by shared environmental conditions of the individuals investigated in this study. Full article

The horse represents one of the most physiologically specialized athletic mammals, capable of sustaining both high-intensity and prolonged exercise. Central to this remarkable performance capacity is the metabolic adaptability of skeletal muscle and its mitochondrial network. This narrative review synthesizes current evidence from equine, human, and rodent studies on exercise-induced mitochondrial remodeling in equine skeletal muscle. A comprehensive literature search was conducted across PubMed, Web of Science, and Scopus using terms related to equine exercise physiology, mitochondrial biology, and skeletal muscle metabolism. Preference was given to peer-reviewed original research and review articles. Mitochondria regulate oxidative phosphorylation, substrate oxidation, redox signaling, and cellular responses to metabolic stress induced by exercise. Training induces extensive mitochondrial adaptations, including mitochondrial biogenesis, remodeling of the respiratory chain, enhanced oxidative phosphorylation efficiency, and increased metabolic flexibility. These adaptations are believed to contribute to improvements in aerobic capacity, delayed fatigue onset, and enhanced recovery following exercise, although direct mechanistic evidence in horses remains limited. In equine skeletal muscle, mitochondrial plasticity is closely linked to muscle fiber composition and the distribution of oxidative and glycolytic fibers. Exercise-induced signaling pathways involving AMP-activated protein kinase (AMPK), Ca²⁺-dependent kinases, and the transcriptional coactivator PGC-1α regulate mitochondrial biogenesis and metabolic remodeling. In addition, mitochondrial dynamics, including fusion, fission, and mitophagy, maintain mitochondrial quality and functional efficiency during repeated training stimuli. Experimental studies in Thoroughbred and Standardbred horses demonstrate that training has been associated with increases in mitochondrial density and respiratory capacity in equine skeletal muscle, contributing directly to improved aerobic performance and metabolic efficiency. However, mitochondrial adaptations must be interpreted within the broader context of musculoskeletal adaptation, as metabolic improvements may occur faster than structural adaptation of tendons and ligaments. This review synthesizes current knowledge on exercise-induced mitochondrial remodeling in equine skeletal muscle, while highlighting the limited mechanistic evidence available in horses and the need for more standardized longitudinal studies. Full article

This study aims to explore and evaluate the factors influencing Gen Z’s intention to choose green tourism destinations in Hanoi, Vietnam. The paper proposes a comprehensive analytical framework by integrating the Stimulus-Organism-Response (S-O-R) model and the Theory of Planned Behavior (TPB). A mixed-method approach was employed, in which quantitative data were collected from 269 Gen Z respondents in Hanoi and analyzed using the Partial Least Squares Structural Equation Modeling (PLS-SEM) technique through SmartPLS. The findings reveal that external environmental stimuli, including green destination image (GDI) and social media influence (SMI), positively affect individuals’ internal psychological states, namely environmental awareness (EA), attitude toward green tourism (ATT), and subjective norms (SM). These psychological states, in turn, exert positive effects and strongly promote Gen Z’s intention to choose green tourism destinations in Hanoi. This study not only contributes to filling the theoretical gap in sustainable tourism consumption behavior in the digital era but also provides practical managerial implications for policymakers and tourism businesses in developing communication strategies and tourism products that align with the preferences and expectations of younger generations. Full article