Search Results (838)

Traditional food systems are increasingly threatened by industrialised agri-food production based on standardised processes, economies of scale, and lower production costs. This transformation risks undermining not only the economic viability of artisanal producers but also the cultural heritage, pastoral knowledge, and territorial identities embedded in traditional foods. This study contributes to rural studies and food heritage research by examining whether consumers’ willingness to pay a premium for traditionally produced foods can sustain endangered rural production systems within competitive PDO markets. Focusing on Fiore Sardo PDO cheese, the study combines a Bertrand duopoly framework with the Theory of Planned Behaviour (TPB) to connect market competition, consumer beliefs, and support for traditional agri-food systems. Data from 1640 Italian consumers were analysed using structural equation modelling. The findings show that attitudes towards cultural preservation, social recognition of traditional production, and perceived support for shepherd communities significantly influence consumers’ willingness to purchase and pay premium prices for traditionally produced cheese. Consumers associate artisanal production not only with superior sensory quality and authenticity but also with the protection of cultural identity, traditional pastoral practices, and rural landscapes. By integrating behavioural and economic perspectives, the study demonstrates that willingness to pay operates as a market mechanism through which consumers actively contribute to the resilience of traditional food systems facing industrial competition. The study advances existing literature by showing how cultural values, behavioural intentions, and market dynamics jointly shape the economic sustainability of traditional foods. Full article

Behavioral interventions are widely used to promote sustainable consumption, but their effectiveness under high-friction real-world conditions remains uncertain, especially when multiple tools are combined. We report a quasi-experimental natural field study conducted in a busy urban café in Tel Aviv, Israel, examining the isolated and combined effects of a localized identity-based social-norm cue and a small financial incentive on reusable cup adoption. Across four consecutive weeks and 9414 hot-beverage transactions, a baseline week was followed by a norm condition, a 1 NIS discount condition, and a combined condition. Reusable cup use increased from 3.33% at baseline to 3.59% in the norm week, 4.19% in the incentive week, and 3.72% in the combined week, but none of these changes reached statistical significance. The financial incentive produced the largest descriptive increase, whereas the combined intervention did not outperform the incentive alone. Across the intervention period, reusable cup use exceeded the number expected under the baseline rate by approximately 35 purchases. These bounded null findings suggest that low-cost behavioral tools may yield only modest gains in convenience-driven consumption settings and that combining policy tools does not necessarily generate additive effects. The study contributes ecologically grounded evidence on the boundary conditions of sustainable behavior change and highlights the importance of testing behavioral policies under realistic implementation constraints. Full article

The Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) provides monthly cash-value benefits (CVBs) for fruits and vegetables. In addition to fresh produce, WIC agencies may allow households to purchase frozen and canned produce using CVBs. The use of these options may support benefit redemption for households who face inequitable barriers to accessing fresh produce, such as households living on tribal lands. This study examined (1) associations between frozen/canned food CVB purchases and overall CVB redemption and (2) predictors of frozen/canned food purchasing within a Tribal Organization using administrative data collected between November 2024 and April 2025 and a participant survey. Administrative data analyses included 4787 Inter Tribal Council of Arizona WIC-participating households; survey analyses included 1165 respondents. Mixed-effects models showed that households purchasing frozen and canned foods using CVBs, instead of only fresh, redeemed more of their CVBs. Further, higher frozen/canned purchasing predicted higher redemption rates. Households with multiple WIC participants were more likely to purchase frozen and canned foods using CVBs than single-participant households. The most commonly reported reason for purchasing frozen/canned foods in surveys was longer shelf life. Findings indicate that allowing and promoting frozen and canned food options may improve CVB utilization for American Indian families. Full article

CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart) systems remain a widely deployed defense against automated abuse, but advances in machine learning have reduced the effectiveness of traditional challenge-based designs and exposed limitations in proprietary risk-scoring systems. This paper presents an adaptive, reinforcement learning-based CAPTCHA defense framework for high-security web applications. The proposed system formulates bot detection as a partially observable Markov decision process and uses a Proximal Policy Optimization (PPO) agent with Long Short-Term Memory to analyze streamed behavioral telemetry, including mouse movements, clicks, keystrokes, and scrolling, over sequential interaction windows. During the observation phase, the agent can continue observing or deploy a honeypot as an early-intervention and evidence-gathering action; after sufficient session evidence is accumulated, it can issue graded CAPTCHA challenges, allow a session, or block it. To complement the sequential agent, the framework also includes an XGBoost classifier that produces a session-level human-likelihood score as a supervised benchmark. The accompanying reinforcement learning environment and code base are publicly available, allowing future researchers to train, evaluate, and extend adaptive CAPTCHA policies as bot capabilities evolve. Experiments conducted on a sandbox ticket-purchasing web application demonstrate that the proposed methodology achieves strong preliminary performance on human-generated sessions and real bot sessions produced by scripted, replay-based, and Large Language Model (LLM)-powered agents. Among the evaluated reinforcement learning algorithm variants, Soft PPO achieved the best performance with 97.7% accuracy, 100% precision, and a 97.6% F1 score. Correspondingly, the XGBoost classifier achieved 99.48% accuracy, a 1.000 ROC-AUC (receiver operating characteristic area under the curve), and a 0.9919 F1 score. Our results indicate that sequential reinforcement learning can support accurate and low-friction bot detection, while the accompanying classifier provides a complementary binary benchmark. Compared to proprietary systems, the proposed framework emphasizes transparency, auditability, and explicit sequential decision-making rather than black-box risk scoring. Overall, this work introduces a publicly available, open, and adaptive CAPTCHA defense framework that supports transparent experimentation with behavior-based bot mitigation while also identifying the remaining limits that must be addressed before commercial deployment. Full article

The modern world faces numerous challenges related to environmental degradation, climate change, and the growing demand for food in the context of rapid population growth. One of the key areas in which solutions supporting the idea of sustainable development can be sought is in society’s dietary habits and the implementation of innovative approaches to food production. Among these, 3D food printing has attracted growing attention as a promising approach for designing plant-based products with tailored structure, composition, and sensory properties. However, the broader adoption of 3D-printed foods may depend largely on consumer acceptance. The aim of this study was to compare the sensory evaluation and perceived market value of two plant-based salmon analogues: a conventional vegan product commercially available on the domestic market (Product A) and a vegan salmon analogue produced using a 3D food printing approach (Product B). An exploratory consumer study was conducted with 20 adult participants representing two dietary groups: meat consumers and non-meat consumers. Two tasting panels were organised, and both products were evaluated using a structured hedonic questionnaire covering appearance, aroma, colour, taste, texture, packaging, perceived ingredient composition, acceptable price, and purchase intention. Data were analysed descriptively and by means of McNemar’s test and the Wilcoxon signed-rank test, including subgroup analyses by dietary profile. Product B received significantly more favourable ratings for aroma, taste, texture, and acceptable price, and it generated a higher declared purchase intention than Product A. The difference in purchase intention between the two products was statistically significant. More positive evaluations of Product B were particularly evident among non-meat consumers. These findings suggest that, in the context of this exploratory tasting study, the 3D-printed plant-based salmon analogue showed promising consumer acceptance, especially among respondents already oriented toward plant-based diets. Full article

The aim of this study was to characterize ruminal degradation and postruminal digestibility of dry matter (DM) and crude protein (CP) in full-fat raw soybeans (ffSB), extruded full-fat raw soybeans (effSB) and soybean cake (SBc) derived from three non-GMO locally grown soybean varieties (PETRINA, ERICA and VIOLA). To hasten data interpretation, ruminal degradation and postruminal digestibility of the conventional solvent-extracted soybean meal (SBM) was also investigated. Effective rumen degradation (ERD) of DM was lower for SBc (0.726) than for SBM (0.777; p < 0.001). Independent of soy variety, it was less for SBc than ffSB (0.801) and the least for effSB (0.783; p < 0.001). Intestinal DM digestibility was higher for SBM (0.946) compared to ffSB (0.708) and effSB (0.604), and regardless of soybean variety, it was lower for effSB than for SBc (0.866; p < 0.01). The ERD of CP was higher for ffSB (0.817) compared to SBM (0.6858; p = 0.007), and, independent of soy variety, it was less for SBC (0.773) than ffSB and the lowest for effSB (0.750; p < 0.001). Intestinal digestibility of CP was higher for SBM (0.998) compared to ffSB (0.944), effSB (0.926), and SBc (0.943). Regardless of soybean variety, it was lower for effSB than for ffSB and SBc (p < 0.002). However, interactions between product type and soybean variety were also detected for almost all investigated parameters, except for c for DM and c and ERD for CP (p < 0.001), with variety ERICA showing the lowest ERD and variety PETRINA showing the highest intestinal digestibility. The study demonstrated that the type of soybean processing and soybean variety significantly affected ERD and intestinal digestibility of DM and CP. Soy products (effSB and SBc) produced by the farmer on his own farm from non-GMO soybeans harvested on his own farm can serve as valuable feed material for cattle, making him independent from the need to purchase imported SBM. Full article

The inner beauty functional food sector has grown rapidly in South Korea. These products are orally consumed bioactive formulations designed to improve skin health, hair vitality, and overall wellness. However, empirical evidence on consumption patterns and product format preferences across different demographic groups remains limited. This cross-sectional study examined consumption patterns, purchase channels, and product format preferences among 502 Korean adults who had experience with inner beauty functional foods. Chi-square analysis was used to examine differences in consumption reasons, duration of use, purchase channels, and product format preferences according to socio-demographic characteristics. Results showed that skin health was the dominant consumption motivation (47.6%), particularly among younger and female consumers, while weight management and hair and nail health were more prevalent among older adults. Online purchasing dominated (57.8%), with significant age- and education-based variation; consumers in their 20s purchased online at 67.5%, declining to 44.4% among those aged 40 and above. Capsule and tablet formats were most prevalent overall (41.6%), with males, married consumers, and graduate-degree holders showing significantly stronger preference for this format, whereas gummy and chewable formats were more frequently preferred by female consumers. These findings provide practical implications for inner beauty producers, food distributors, and nutrition educators seeking to align product development and communication strategies with the heterogeneous preferences of Korean inner beauty consumers. Full article

This review develops a configurational account of the relationship between religion and transnationalism by addressing a specific analytical limitation in the existing literature: its tendency to oscillate between substantializing religious traditions as already constituted entities that move across borders and segmenting transnational religion into disconnected domains such as networks, migrant communities, diasporic identities, institutions, political mobilization, digital mediation, social support, or pilgrimage. While these approaches have generated substantial empirical insight, they leave undertheorized the relational formation through which religious authority, practice, identity, material circulation, symbolic boundary-making, institutional organization, and mediated presence are assembled and made socially effective across multiple scales. To clarify this problem, the review reconstructs scholarship on religion and transnationalism through five major thematic domains: transnational religious networks, religious identity in transnational contexts, religion as a catalyst of transnationalism, the embedding of religion in transnational social practices, and distinctive forms of transnational religion. This reconstruction shows that transnational religious phenomena are inadequately understood as the spatial extension of pre-given traditions, as residual expressions of ethnicity or migration, or as discrete networks, movements, institutions, or diasporic communities. They are better grasped as historically contingent and relationally ordered formations whose temporary coherence is produced through the interaction of actors, authorities, practices, discourses, infrastructures, legal-regulatory environments, memories, obligations, and material flows. Building on the concept of social configuration, the review therefore proposes transnational religious configurations as a more precise unit of analysis for studying how the religious and the transnational are mutually constituted rather than externally connected. It defines such configurations as historically specific formations in which religious categories, institutions, practices, authorities, material resources, symbolic boundaries, and cross-border conditions of possibility are articulated across local, national, transnational, and global scales. The review operationalizes this approach through three analytical levels—conditions of possibility, construction and characteristics, and social realities and consequences—and illustrates its explanatory purchase by examining a new phenomenon within the contemporary transnational revival of Shi‘i Islam. Full article

The German industrial and energy sectors accounted for over 52% of national greenhouse gas emissions in 2024. This is influenced both by an ongoing demand for fossil fuels and the usage of emission-intensive raw and processed materials. With the current European directive on corporate sustainability reporting, a push is being made for companies to publish annual emission reports. However, as per a study conducted by the authors, small and medium-sized companies have difficulties accurately calculating emissions across their supply chain without relying on external service providers. As a scientific institute with a real production facility for metal machining, the ETA (Energy Technologies and Applications) Factory bridges the gap between academia and manufacturing enterprises. The authors have used this disposition to calculate scope 1–3 emissions for the factory as per the Greenhouse Gas Protocol across three years, while progressively attempting to automate data collection for all scopes. CO₂e emissions for the years 2022–2024 were 86.3 tCO₂e, 146.9 tCO₂e, and 86.1 tCO₂e, respectively. Emission categories were assessed in terms of relevance to the institute and subsequently used to analyze the emission activities of the factory. The highest contributor to emissions was electricity purchasing for 2022 and 2024, along with business travel for 2023. Within scope 3, the emissions produced by business travel showed the highest impact across all years, followed by either energy-related activities or purchased goods. The sensitivity of CO₂e factors was also investigated, showing discrepancies between 25% and 130% for the utilized CO₂e factor for steel. Automation of data collection benefits largely from implemented manufacturing systems, such as manufacturing execution systems or enterprise resource planning systems. Full article

Food waste fashion—garments produced from agricultural and food industry by-products, such as fruit peels, coffee grounds, and grape marc—represents a radical yet understudied innovation within the circular economy. This study proposes the Fashion Innovation Adoption Model, a novel framework that organizes consumer adoption of fashion innovations across three hierarchical levels: a distal level comprising sociodemographic characteristics, an intermediate cognitive–evaluative level comprising consumer decision-making styles and functional product attribute evaluations, and a proximal psychosocial level comprising attitudes, static and dynamic social norms, and past fashion purchasing behavior. The model is applied for the first time to food waste fashion as a paradigmatic case of radical circular innovation in the textile sector. Hypotheses were tested via structural equation modeling on a sample of 396 Italian consumers. Purchase intention was directly predicted by attitudes, static and dynamic norms, and general fashion purchasing, whereas sustainable fashion purchasing showed no effect. Among product attributes, only sustainability information influenced both attitudes and intentions. Perfectionism and hedonism were positively associated with intention through sustainability information, while impulsivity and habit were negatively associated with intention. Sociodemographics influenced intention only indirectly, via cognitive and normative mechanisms. These findings reveal complex pathways linking psychological profiles and perceived product attributes to circular fashion adoption, with implications for communication strategies emphasizing sustainability information and targeting heterogeneous consumer motivations. Full article

Predicting garlic prices is difficult because the crop behaves as both an agricultural commodity and a speculative asset. Unlike staple grains, which follow more predictable seasonal supply cycles, garlic can be stored for over a year, its production is geographically concentrated, and its demand remains inelastic. This industry structure makes it susceptible to speculative hoarding, where even minor harvest deficits may trigger sharp price spikes. A typical example is the “Suan Ni Hen” (crazy garlic) phenomenon in the Chinese market: during the 2009–2010 and 2016 periods, speculative capital repeatedly exploited expectations of harvest reduction to engage in large-scale hoarding. According to data released by China’s National Development and Reform Commission (NDRC) at the end of October 2016, national wholesale garlic prices surged by 90% year-on-year, with purchase prices in some major producing areas doubling or multiplying within a short period. Such short-term price bubbles, together with severe volatility and abrupt regime shifts, can make standard forecasting models unreliable in this uncertain environment. Existing methods, ranging from traditional seasonal algorithms to deep learning networks, often overlook the need to decouple the local trend-weekly-seasonal baseline from the dynamic effects of multi-source external signals. This paper proposes GPF-EVMoLE, a compositional multi-step forecasting framework built on an explicit division of labor. The framework first extracts an interpretable local trend and weekly-seasonal baseline through an ETS decomposition module. Two specialized components then process the residual signal: a temporal fusion Transformer-style variable selection network (VSN) uses multi-source external features to identify informative macroeconomic and environmental signals at each forecasting step, while a Mixture of Linear Experts (MoLE) models phase-wise regime shifts within the residual series. Together, these modules adaptively integrate heterogeneous information. This study evaluates the framework on a custom daily evaluation dataset containing 17,685 records across six major producing regions in three provinces. At 7-day and 14-day forecasting horizons, GPF-EVMoLE consistently outperforms eight representative statistical, machine learning, and deep learning baselines across MAE, RMSE, and MAPE metrics. Ablation studies verify the necessity of each component, showing that structural separation of the forecasting tasks helps overcome the limitations of monolithic models and provides an accurate and interpretable solution for complex agricultural markets. Full article

Upcycled foods, produced from edible side-streams that would otherwise be discarded, offer a promising pathway toward circular and sustainable food systems. However, consumer acceptance in China remains limited. Drawing on the Theory of Planned Behaviour (TPB) and integrating eco-wellness awareness and cultural values, this study examines the drivers of Chinese consumers’ acceptance of upcycled foods. Survey data from 612 consumers across multiple provinces were analysed using structural equation modelling. The results show that attitude is the strongest predictor of purchase intention, followed by subjective norms and perceived behavioural control. Health awareness and consumer innovativeness significantly enhance both attitude and perceived behavioural control, while environmental awareness primarily strengthens perceived behavioural control. Collectivism positively influences all TPB components, whereas frugality strengthens attitude and subjective norms only. Perceived risk plays a limited role. The findings highlight the importance of health-oriented and culturally grounded communication strategies for promoting circular food consumption in China. Full article

Artificial intelligence (AI) has gradually been applied to food production. Many companies now face a choice between adopting AI technology and adhering to the traditional methods of food production. Existing studies have reported inconsistent findings regarding consumer perceptions of AI-produced food, yet little research has examined how consumers form motive inferences on businesses that transition from traditional practices to adopting AI in new food development. Based on motivation inference theory, this paper investigates the impact of food production methods on consumer inferences and purchase intention. Through three experiments, we find that AI-produced food evokes more negative motive inference in trust building and lowers purchase intention than traditionally produced food. Furthermore, such effect is driven by a serial mediating effect through cost-cutting attribution and perceived ulterior motive. Additionally, it is attenuated when the food company has a high corporate reputation. This research advances research on AI application in food from a consumer motive inference perspective, providing suggestions on firms’ adoption of AI-based practices in food production. Full article

To explore the evolutionary dynamics of green product markets under bounded rationality, this study develops a tripartite evolutionary game model involving the government, passenger vehicle enterprises, and consumers, using China’s new energy vehicle (NEV) market as a case study. By integrating system dynamics with real-world data and policies, the paper simulates strategy evolution paths and identifies equilibrium conditions. The results show a unique evolutionarily stable strategy: the government refrains from regulation, enterprises actively produce NEVs, and consumers actively purchase green products. The government’s strategy is primarily influenced by enterprises, while enterprises’ strategy is mainly driven by consumers. Numerical analysis reveals that when the premium payment ratio of green products (price difference relative to conventional vehicles) is controlled between 27.27% and 31.82%, the market evolves most rapidly toward the ideal equilibrium. Furthermore, when the additional positive benefit ratio of green consumption falls below 36.36%, market formation and development are severely hindered; raising this ratio to 40.91% yields significant promotion effects, beyond which marginal benefits diminish. These findings provide quantitative benchmarks for policy design and strategic decision-making to foster self-sustaining green product markets. Full article

The article provides a comprehensive review of empirical studies on consumer attitudes, motivations, and behaviors in the functional food market. The main objective of this study is to identify groups of determinants and to update and systematize current knowledge on the influence of various factors on consumer purchasing decisions in this market. Based on an analysis of international research published between 2004 and 2025, four key groups of determinants were identified: (1) health- and trust-related factors, (2) cognitive and psychological factors, (3) perceptual and product-related factors, and (4) socio-demographic and segmentation factors. The analysis confirms that purchasing decisions in this product category are complex and multidimensional. They result from the interaction between rational factors (health-related and cognitive) and emotional-symbolic factors (psychological and sensory). The strongest predictors of functional food acceptance include perceived health benefits, trust in producers and information sources, sensory attractiveness, and product naturalness. Socio-demographic characteristics, such as age, education level, and income, further differentiate purchasing intentions and behaviors. Overall, the findings highlight the need for further comparative and cross-cultural research, as cultural and economic conditions may significantly shape consumer decisions across markets. The results obtained have both theoretical and practical implications. They contribute to a better understanding of consumer decision-making processes and emphasize the importance of promoting health awareness. Full article