Search Results (405)

Having in view the current global disruptive social and economic landscape, sustainability becomes more important than ever. As producers become more concerned about adopting more sustainable practices, customer awareness towards sustainable behavior must be the focus of all stakeholders. Within this context, the SHIFT framework (proposed in 2019) highlights the manner in which consumers’ traits and attitudes influence their propensity towards sustainable consumption. It consists of five factors considered to be relevant to consumer behavior: Social influence, Habit formation, Individual self, Feelings and cognition, and Tangibility. Different from previous studies, this research focuses on applying the SHIFT framework to the automotive industry, taking into consideration the contribution of digital technologies to fostering sustainable consumer behavior throughout the entire product lifecycle. Using a qualitative research approach, the most relevant digital technologies in the automotive industry were identified and mapped in relation to the three phases of consumption (choice, usage, and disposal). The research aimed to develop and test an original conceptual framework, starting from the SHIFT. The results of the study highlight the fact that the digital technologies, in their diversity, are integrated in different ways into each of the three phases, facilitating the adoption of sustainable consumption. To achieve sustainability, the two key stakeholders, consumers and producers, should share a common ground on capitalizing the opportunities offered by digital technologies. Full article

Proton therapy has emerged as a highly precise and tissue-sparing radiotherapy technique, capitalizing on the unique energy deposition pattern of protons characterized by the Bragg peak. Ensuring treatment accuracy relies on calibration phantoms, often composed of tissue-equivalent polymeric materials. This study investigates the dosimetric behavior of four commonly used polymers—Parylene, Epoxy, Lexan, and Mylar—by analyzing their linear energy transfer (LET) values and Bragg curve characteristics across various proton energies. Experimental LET data were collected and used to train and evaluate the predictive power for Bragg peak of multiple artificial intelligence models, including kNN, SVR, MLP, RF, LWRF, XGBoost, 1D-CNN, LSTM, and BiLSTM. These algorithms were optimized using 10-fold cross-validation and assessed through statistical error and performance metrics including MAE, RAE, RMSE, RRSE, CC, and R². Results demonstrate that certain AI models, particularly RF and LWRF, accurately (in terms of all evaluation metrics) predict Bragg peaks in Epoxy polymers, reducing the reliance on costly and time-consuming simulations. In terms of CC and R² metrics, the LWRF model demonstrated superior performance, achieving scores of 0.9969 and 0.9938, respectively. However, when evaluated against MAE, RMSE, RAE, and RRSE metrics, the RF model emerged as the top performer, yielding values of 12.3161, 15.8223, 10.3536, and 11.4389, in the same order. Additionally, the SVR model achieved the highest number of statistically significant differences when compared pairwise with the other eight models, showing significance against six of them. The findings support the use of AI as a robust tool for designing reliable calibration phantoms and optimizing proton therapy planning. This integrative approach enhances the synergy between materials science, medical physics, and data-driven modeling in advanced radiotherapy systems. Full article

This study investigates the critical determinants of customer retention in casual dining restaurants within the context of the post-pandemic “new normal.” Anchored in service quality and consumer behavior theories, the research examines the influences of food quality, health measures, perceived price, brand image, ambiance, and location on customer decision making. Using Partial Least Squares Structural Equation Modeling (PLS-SEM), data from 336 respondents in the National Capital Region, Philippines were analyzed to assess the relationships among these variables and their effects on restaurant selection and customer retention. The results reveal that food quality (β = 0.698, p < 0.05) exerts the strongest influence on restaurant selection, followed by health measures (β = 0.477, p = 0.001), perceived price (β = 0.378, p < 0.02), and brand image (β = 0.341, p < 0.035). Furthermore, health measures (β = 0.436, p = 0.002) and restaurant selection (β = 0.475, p < 0.05) significantly enhance customer retention, while ambiance and location were not found to be significant predictors. These findings offer theoretical contributions to the service quality and consumer trust literature and provide practical and policy-relevant insights for food establishments adapting to health-driven consumer expectations. The study highlights the need for the strategic integration of safety protocols, pricing value, and brand positioning to foster long-term loyalty and resilience in the evolving food service market. Full article

Background/Objectives: Intergenerational care plays a significant role in shaping household dietary quality and human capital development in China. Influenced by the legacy of the one-child policy, the care provided in these families often prioritizes child-focused practices. This study examines how intergenerational care influences schoolchildren’s sugar-sweetened beverage (SSB) consumption. Methods: This study utilizes data from the 2014–2015 China Education Panel Survey (CEPS) to investigate the impact of intergenerational care on schoolchildren’s dietary behaviors, with a focus on sugar-sweetened beverage (SSB) consumption. We apply both ordinary least squares (OLS) regression and the ordered logit model to estimate the impacts, and we use the instrumental variables approach to address potential endogeneity. Results: Schoolchildren from only-child families report greater SSB consumption, while those from multi-child families consume less. Intergenerational care is linked to more digital media exposure, more pocket money, and less parental supervision. These findings withstand rigorous validation through multiple robustness checks, including sample restriction strategies and propensity score matching (PSM) analysis. The effect is especially pronounced among boys, schoolchildren from families with higher parental education levels, and schoolchildren attending schools without formal nutrition education programs. Conclusions: The result indicates that intergenerational care significantly increases SSB consumption among schoolchildren from only-child families. Community nutrition and school health education programs can reduce schoolchildren’s SSB consumption, thereby lowering risks of obesity and other public health concerns. Full article

The mud crab (Scylla paramamosain), also known as the mangrove crab, thrives in shallow mangrove forests, subtidal zones, and muddy intertidal habitats. It is a highly valuable species in the mangroves and estuaries of tropical regions and is in high demand in Vietnam’s coastal markets. This study provides a comprehensive analysis of the key factors influencing consumer behavior and purchasing decisions regarding mud crabs in Vietnam’s three largest cities: Can Tho City, Ho Chi Minh City, and Hanoi Capital. To achieve this, the research employs rigorous analytical methods, including Cronbach’s alpha reliability test, principal component analysis, and multivariate regression analysis, to identify the primary determinants of consumer behavior and purchasing preferences for fresh mud crabs. The multiple regression analysis reveals two key factors that significantly influence consumer choices: nutritional knowledge and convenience awareness. Most of consumers perceive fresh mud crabs as superior in quality, expecting them to offer greater freshness; higher levels of protein, amino acids, and minerals; as well as excellent flesh texture and enhanced palatability. Based on these findings, two strategic directions are proposed for the sustainable development of Vietnam’s crab industry: (1) improving the nutritional quality of crab products to align with consumer expectations for health benefits and (2) enhancing the distribution network and diversifying product offerings to improve accessibility and convenience for consumers. Full article

This paper investigates the spillover effects and transmission networks of systemic risk within China’s national economic sectors under extreme conditions from both time and frequency domain perspectives, building upon the spillover index methodology and calculating the ∆CoVaR index for Chinese industries. The findings indicate the following: (1) Extreme-risk spillovers synchronize across industries but exhibit pronounced time-varying peaks during the 2008 Global Financial Crisis, the 2015 crash, and the COVID-19 pandemic. (2) Long-term spillovers dominate overall connectedness, highlighting the lasting impact of fundamentals and structural linkages. (3) In terms of risk volatility, Energy, Materials, Consumer Discretionary, and Financials are most sensitive to systemic market shocks. (4) On the risk spillover effect, Consumer Discretionary, Industrials, Healthcare, and Information Technology consistently act as net transmitters of extreme risk, while Energy, Materials, Consumer Staples, Financials, Telecom Services, Utilities, and Real Estate primarily serve as net receivers. Based on these findings, the paper suggests deepening the regulatory mechanisms for systemic risk, strengthening the synergistic effect of systemic risk measurement and early warning indicators, and coordinating risk monitoring, early warning, and risk prevention and mitigation. It further emphasizes the importance of avoiding fragmented regulation by establishing a joint risk prevention mechanism across sectors and departments, strengthening the supervision of inter-industry capital flows. Finally, it highlights the need to closely monitor the formation mechanisms and transmission paths of new financial risks under the influence of the pandemic to prevent the accumulation and eruption of risks in the post-pandemic era. Authorities must conduct annual “Industry Transmission Reviews” to map emerging risk nodes and supply-chain vulnerabilities, refine policy tools, and stabilize market expectations so as to forestall the build-up and sudden release of new systemic shocks. Full article

Narrow-vein deposits have historically been valuable in producing gold, tin, copper, silver, lead, and zinc. Developing these mineral resources is sometimes challenging due to economic and safety concerns. Given the small to medium scale of production, narrow-vein mining could be labor-intensive with increased exposure of the miners to hazardous conditions. A safe, mechanized, efficient, and sustainable method can be invaluable to operators looking to develop narrow-vein mineral resources. The comminution circuit (consisting of crushing and grinding) is downstream of most mineral resources’ extraction processes. Comminution is significantly energy-intensive, consuming almost half of the energy supplied to a mineral-processing activity. Thus, several engineers have investigated the continued development of sustainable narrow-vein mining and comminution technologies. This journal article focuses on a developed innovative, safe, mechanized, and continuous narrow-vein mining technology that has further made accessing narrow-vein deposits more economically feasible and efficient while reducing dilution of ores. The article also extensively presents the impact of this new mining approach on the daily production of the operation and the observed particle size distributions of the day-to-day operational output. Subsequently, the article evaluates and presents the impact of the new procedure of mineral extraction on the resultant size of the cuttings generated as well as the expected energy input of the comminution process downstream of the mining operation. The novelty of the mining method upon which this work is based is improved capital expenditure and reduced dilution. With the new mining method, otherwise-uneconomic narrow-vein deposits can be accessed. Full article

Bloom’s taxonomy provides a well-established framework for categorizing the cognitive complexity of assessment questions, ensuring alignment with course learning outcomes (CLOs). Achieving this alignment is essential for constructing meaningful and valid assessments that accurately measure student learning. However, in higher education, the large volume of questions that instructors must develop each semester makes manual classification of cognitive levels a time-consuming and error-prone process. Despite various attempts to automate this classification, the highest accuracy reported in existing research has not exceeded 93.5%, highlighting the need for further advancements in this area. Furthermore, the best-performing deep learning models only reached an accuracy of 86%. These results emphasize the need for improvement, particularly in the application of deep learning models, which have not been fully exploited for this task. In response to these challenges, our study explores a novel approach to enhance the accuracy of cognitive level classification. We leverage a combination of augmentation through synonym substitution, advanced feature extraction techniques utilizing DistilBERT and TF-IDF, and a robust ensemble model incorporating soft voting. These methods were selected to capture both semantic meaning and term frequency, allowing the model to benefit from contextual depth and statistical relevance. Additionally, Bayesian optimization is employed for hyperparameter tuning to refine the model’s performance further. The novelty of our approach lies in the fusion of sparse TF-IDF features with dense DistilBERT embeddings, optimized through Bayesian search across multiple classifiers. This hybrid design captures both term-level salience and deep contextual semantics, something not fully exploited in prior models focused solely on transformer architectures. Our soft-voting ensemble capitalizes on classifier diversity, yielding more stable and accurate results. Through this integrated approach outperformed previous configurations with an accuracy of 96%, surpassing the current state-of-the-art results and setting a new benchmark for automated cognitive level classification. These findings have significant implications for the development of high-quality, scalable assessments in educational settings. Full article

Although impulsive and hedonic purchasing behaviors may seem to contradict sustainability principles, there are unexplored opportunities through which social media platforms and influencers can redirect these impulses toward sustainable actions. Young consumers, increasingly concerned about the ecological impact of their choices, can be encouraged to adopt responsible and sustainable buying behaviors when these are promoted attractively, enjoyably, and emotionally satisfyingly through social media. This research investigates how social media communication influences hedonic and impulsive purchasing behavior in the Romanian clothing market. In the context where social media is one of the main sources of information and influence for consumers, the research analyzes several determining factors of the purchase decision. Price reductions and the use of credit cards are highlighted as elements that facilitate spontaneous and hedonic targeted purchases, while the attractiveness of clothing items and the need felt play an important role in terms of the desire to buy. In addition, sources of information (such as reviews) have a major impact on consumers’ perceptions and their purchase intentions. Additionally, the study investigates factors such as overall shopping experience and its influence on consumer loyalty. It is approached from two perspectives: attitudinal loyalty, reflected in the preference for brands promoted on social media, and behavioral loyalty, expressed through repeat purchases. The results show that social media acts as an accelerator for hedonic and impulsive buying behaviors, prompting consumers to react quickly to stimuli such as discount campaigns or personalized recommendations. The conclusions highlight the importance of adopting digital marketing strategies that capitalize on the consumers emotional need while also strengthening brand loyalty. These perspectives can guide companies in the clothing industry to adapt their promotion methods to the specifics of the Romanian market and the consumer behavior. Full article

Beetroot (Beta vulgaris L.) is a plant grown for its roots, which are used to obtain sugar, feed animals, and for human use. Beetroot skin, a by-product of food processing, is a significant source of bioactive compounds, including dietary fiber and antioxidants. The primary objective of this work was to utilize beetroot skin powder to produce value-added nougat. Analytical methods, like antioxidant activity tests, proximate analysis, and sensory assessments, are used to determine the impact of beetroot skin powder on the final product. The beetroot skin powder extract had a remarkable content of phytochemicals and antioxidant activity. The inhibitory effect of the extract was tested on enzymes linked to metabolic syndrome, oxidative stress, and inflammation. The beetroot skin powder extract inhibited α-glucosidase, α-amylase, lipase, and lipoxygenase enzymes. The characterization of value-added nougat illustrates the multifunctionality of beetroot peel powder within its composition, serving as a significant source of natural compounds with antioxidant, coloring, and flavoring properties. This enhances sensory attributes, including color, aroma, and texture, augmenting product diversity and consumer appeal. This is evidenced by the increase in the total content of betalains (3.77 ± 0.09 mg/g DW.) and polyphenols (69.48 ± 2.88 mg GAE/100 g DW.), which lead to high antioxidant activity (73.89 ± 3.65 mM Trolox/100 g DW.) for the nougat sample with 6% added beetroot powder. Thus, beetroot skin powder replaced chemically synthesized additives with antioxidants and natural pigments, improving life quality and implicitly capitalizing on beetroot processing by-products, supporting circular economy principles at the global level. Full article

As global climate change intensifies and carbon emission policies become increasingly stringent, carbon risk has emerged as a crucial factor influencing corporate operations and financial markets. Based on data from A-share listed companies in China from 2009 to 2022, this paper empirically examines the pricing mechanism of carbon risk in the Chinese capital market and explores how different corporate signaling behaviors affect the carbon risk premium. The findings reveal the following: (1) Carbon risk exhibits a significant positive premium (annualized at about 1.33% per standard deviation), which remains robust over longer time windows and after replacing the measurement variables. (2) Heterogeneity analysis shows that the carbon risk premium is not significant in high-energy-consuming industries or before the signing of the Paris Agreement, possibly due to changes in investor expectations and increased green awareness. Additionally, a significant difference in the carbon risk premium exists between brown and green stocks, reflecting a “labeling effect” of green attributes. (3) Issuing green bonds, as an active corporate signaling behavior, effectively mitigates the carbon risk premium, indicating that market investors highly recognize and favor firms that actively convey green signals. (4) A “greenwashing” indicator constructed from textual analysis of environmental information disclosure suggests that greenwashing leads to a mispricing of the carbon risk premium. Companies that issue false green signals—publicly committing to environmental protection but failing to implement corresponding emission reduction measures—may mislead investors and create adverse selection problems. Finally, this paper provides recommendations for corporate carbon risk management and policy formulation, offering insights for both research and practice in the field. Full article

This paper investigates the long-term impact of integrating emerging Small Modular Reactors (SMR) in modern power systems. A chronological simulation of the Greek day-ahead market and real-time balancing market with fine time granularity is conducted for a future 20-year period (2032–2051) under four SMR penetration scenarios using a specialized integrated market simulation software. Simulation results indicate that SMR units can be regarded as a promising electricity generation solution in the forthcoming energy transition landscape. The introduction of up to 3 GW of SMR capacity is projected to significantly decrease reliance on gas imports by up to 62%, reduce carbon emissions by up to 52%, and lower overall electricity costs for end-consumers by up to 21% as compared to a baseline scenario without SMRs. It is anticipated that SMR units are expected to leverage their operating advantages and generally achieve positive financial results when participating directly in the wholesale market. However, their economic viability is highly dependent on their initial capital expenditure and other operating cost components, which at present are highly uncertain. Full article

The agro-tourism integration model combines agricultural production, rural life, and tourism experiences, bringing new opportunities for the sustainable development of counties. The objective of this study is to explore the impact of the agro-tourism integration on the sustainable development of counties, reveal the underlying mechanisms and regional heterogeneity effects, and provide a scientific basis for the formulation of rural revitalization policies. Based on panel data from 1749 counties in China from 2008 to 2021, an empirical test using a propensity score matching-difference-in-differences (PSM-DID) model found that the National Policy on Leisure Agriculture and Rural Tourism Demonstration Counties significantly enhances the level of sustainable development in counties through three mechanisms: stimulating consumer demand, attracting capital inflows, and optimizing industrial structure. Moreover, the effect is more pronounced in the western regions of China. In terms of theory, this study shifts the focus to the county level, constructing a comprehensive measurement index system for county-level sustainable development. It analyzes the mechanisms through which the integration of agriculture and tourism operates and verifies the policy effects. In terms of practice, policy implementations are proposed to adopt a multi-pronged approach to increase agricultural-tourism consumption; to promote government-enterprise cooperation and introduce long-term funding; and to develop the service industry in a location-specific manner to continuously optimize the industrial structure. This study indicates that agro-tourism integration is an effective path for the sustainable development of counties. The policy design needs to take into account the differences in regional resource endowments. This has important implications for promoting county-level development in a location-specific manner under the rural revitalization strategy. Full article

This study explores integrating Bitcoin mining with lignocellulosic biorefineries to create an additional revenue stream. Profits from mining can help offset internal costs, reduce business expenses, or lower consumer prices. Using sensitivity analysis and Monte Carlo simulations, this study identifies key profitability drivers, such as electricity costs, hardware expenses, starting year, and operational time. Time emerged as an extremely sensitive factor and showed that delaying mining operations significantly raised production costs and the probability of profitable outcomes. In contrast, longer mining durations had a smaller yet sizable impact. Hardware costs, computational efficiency, and electricity prices also strongly influenced the outcomes. The majority of simulated events showed a loss. Moreover, the model showed that the marginal profitability of mining decreases over time. Nonetheless, the model demonstrated that under favourable conditions, it is possible to integrate Bitcoin mining into biorefineries and other productive ventures, thereby allowing for cost recovery using Bitcoin profits. For a biorefinery to mine Bitcoin and maximise cost recovery, it must start early, access low electricity prices, and preserve hardware capital characterised by low expenditure and high revenues. Finally, a discussion about the opportunities, risks, and regulations is highlighted. Full article

Background: Oral diseases represent a constant burden for health care and socio-economic systems as they are correlated to other non-communicable diseases. The aim of the proposed intervention is to test the effect of daily tooth brushing and oral health education on the oral health status of kindergarten children. Methods: The protocol will be conducted based on a previous epidemiological survey and conducted over 24 months; it has been developed on different levels. Dental hygienists will receive specific training to deliver oral health promotion to children and nursery educators. Training will focus on tailoring key messages to the specific age at visit; this will be outlined in the care pathway and offer practical preparation for delivering interventions and a toothpaste/toothbrush scheme. It will also, involving involve offering free daily tooth brushing to every 4–6-year-old child attending nursery. Data will be collected in four kindergartens in the capital or metropolitan areas, two kindergartens each in two large cities, and one kindergarten each in four villages from different geographic areas. Procedures used to assess the outcomes of each activity will be tailored to specific outcomes. Daily tooth-brushing activities will be monitored using qualitative research. A cost analysis including the distribution of necessary materials and correct delivery of products that shows price trends and percentage differences over the time span as well as consumer price index evaluation for the given time span will be conducted. Clinical outcomes will be evaluated using the caries incidence rate; this will be calculated for each tooth as the unit of analysis and evaluated using a multi-step approach. Discussion: Downstream oral health prevention interventions, like clinical prevention and oral health promotion, aim to enhance children’s quality of life. The program’s goal is to progress towards upstream interventions for a more significant impact. Full article