Search Results (149)

Metabolic dysfunction-associated steatotic liver disease (MASLD) affects 25–30% of adults globally. Dietary sugar reduction is one of the key therapeutic targets, but elimination of sugar-sweetened foods may compromise adherence to calorie-restricted diets. Brazzein, a natural sweet protein that is 500–2000 times sweeter than sucrose, offers a promising substitute, yet clinical data in patients with MASLD are lacking. In a double-blind, randomized, two-period crossover trial, 103 adults with MASLD tasted iso-sweet vanilla ice cream sweetened with either brazzein or sucrose on two consecutive days. Overall impression and sensory attributes (appearance, color, aroma, taste, and texture) were rated on 5-point hedonic scales, and the percentage of the 100 g portion consumed was recorded. Brazzein-sweetened ice cream met the prespecified criteria for both non-inferiority and equivalence versus sucrose for overall impression. Top-2 box acceptance (ratings ≥ 4) was extremely high and nearly identical (96.1% for brazzein and 98.1% for sucrose). Mean consumption exceeded 98% of the portion for both products, with no significant difference between sweeteners. Secondary sensory ratings were closely similar, and multivariate analyses indicated highly overlapping sensory profiles. Exploratory subgroup analyses suggested consistent findings across most demographic and clinical characteristics, although participants with advanced liver fibrosis (LSM ≥ 9.6 kPa) showed numerically higher ratings for sucrose. In exploratory analyses, liver stiffness was associated with slightly lower intake at higher stiffness values. This study provides the first evidence that brazzein-sweetened ice cream maintains short-term sensory acceptability comparable to a conventional sucrose-sweetened product in adults with MASLD. These findings support further development and evaluation of brazzein-containing sugar-reduced foods, including repeated-exposure sensory studies and separate metabolic investigations. 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

Background: Obesity is a heterogeneous chronic disease in which eating behavior phenotypes may influence treatment response. Yet, anti-obesity medication (AOM) selection is still largely guided by anthropometric and metabolic parameters, with limited use of behavioral phenotyping in routine practice. We evaluated whether multidimensional eating behavior changes, measured by the Brazilian Eating Behavior Phenotype Scale (Escala de Fenótipos do Comportamento Alimentar, EFCA), differ across commonly used AOMs in a real-world cohort. Methods: We conducted a retrospective, observational, real-world study in obesity outpatient care settings in São Paulo, Brazil. Adults with obesity (18–65 years) treated with a single principal AOM for 6 months and paired baseline/6-month follow-up EFCA and anthropometric data were included. Analyses focused on early responders (≥5% total body weight loss at 3 months). Five AOM groups available in Brazil were analyzed: semaglutide (oral or subcutaneous), naltrexone/bupropion, sibutramine, topiramate, and tirzepatide. Outcomes included percent weight loss, EFCA total score, and five EFCA subscales (hedonic, emotional, compulsive, hyperphagic, disorganized). Within-medication behavioral changes were assessed using paired tests and standardized effect sizes (Cohen’s dz, 95% CI), summarized in heatmap form. Results: The analytical cohort comprised 66 early responders with paired EFCA assessments at baseline and 6 months. EFCA profiling revealed distinct behavioral response fingerprints across AOMs. Effect size mapping showed predominantly large behavioral effects (many dz ≥ 0.8) in hedonic, emotional, hyperphagic, and compulsive domains. Strongest signals included emotional eating reductions with naltrexone/bupropion (dz 2.04), tirzepatide (dz 1.77), semaglutide (dz 1.52), and topiramate (dz 1.54); hedonic reductions with tirzepatide (dz 2.06), semaglutide (dz 1.55), and naltrexone/bupropion (dz 1.52); hyperphagic reductions with tirzepatide (dz 1.50) and semaglutide (dz 1.34); and compulsive reductions with topiramate (dz 1.41) and consistent effects across tirzepatide, semaglutide, and sibutramine (≈dz 0.95–0.96). Disorganized eating showed heterogeneous/attenuated responsiveness, from near-null with tirzepatide (dz 0.03) to large but imprecise effects in smaller groups (e.g., topiramate dz 1.24, wide CI). Conclusions: In this responder-enriched real-world cohort, AOMs showed distinct and reproducible EFCA behavioral signatures, supporting a clinically actionable phenotype-informed framework to prioritize, sequence, and monitor obesity pharmacotherapy beyond nonspecific weight reduction, while highlighting disorganization as a potential target for adjunctive behavioral strategies. Full article

Generative Artificial Intelligence (GenAI) has rapidly spread worldwide, driving structural changes and redefining approaches to knowledge. This trend has introduced significant challenges, particularly within higher education, where its adoption and acceptance are crucial for pedagogical transformation. However, the increasing integration of GenAI also raises pressing questions related to sustainability, encompassing both its environmental impact (e.g., energy consumption and carbon footprint of AI models) and social and ethical implications (e.g., responsible use, equity, and digital inclusion). This study investigates the factors influencing the adoption and acceptance of GenAI among higher education students, considering these sustainability dimensions. Using an adapted version of the UTAUT2 (Unified Theory of Acceptance and Use of Technology) model, the research analysed data from 229 students, collected in 2025, employing the Partial Least Squares method. By integrating the sustainability perspective, this work seeks to offer an understanding of the challenges and opportunities that GenAI presents for a more equitable and ecologically conscious educational future. The study demonstrates that habit and performance expectancy are the primary drivers of GenAI adoption among students, suggesting that its integration into higher education should prioritize functional value and ethical habit-building over social or hedonic factors. Full article

The highly competitive nature of the online food delivery (OFD) market faces a serious retention problem, with acquiring new users typically being much more expensive than retaining existing users. Traditional prediction methods that rely primarily upon static transactional metrics such as recency and frequency are often unable to capture the psychological ‘disconfirmation’ which occurs prior to churn. To fill this gap, this study proposes a framework based on Expectation-Confirmation Theory (ECT). Unsupervised K-Means clustering was employed to classify a simulated and filtered dataset with 1500 customer records containing behaviour, geography, etc. This framework also couples sentiment analysis from BERT, allowing it to identify psychological “silent” attrition. Heterogeneous cohorts, which exhibit different psychological antecedents (utilitarian versus hedonic), were identified. The empirical results of our analyses demonstrated that Random Forest Classifiers with segment-specific features outperform baseline transactional models (F1 = 0.76) with an F1 Score of 0.89. The visual analytic interface developed provides a holistic view of the consumption process than traditional prediction models, including prescriptive, automated segment-based mitigation strategies. Our findings contradict the assumption that the “frequency–loyalty” model applies to all users. High-frequency discretionary users are found to be elastic in terms of retention and will experience significant churn. By utilising the automated action log, managers can plan targeted, highly efficient retention strategies rather than blanket discounting approaches. Full article

The proliferation of generative artificial intelligence (AI) as an autonomous recommendation agent fundamentally challenges traditional paradigms of marketing communication. As AI systems increasingly mediate consumer–brand relationships, understanding how artificial agents construct persuasive discourse—distinct from human communicators—becomes critical for developing effective dual-channel marketing strategies. Grounded in Source Credibility Theory and the Computers Are Social Actors (CASA) paradigm, this study investigates the semantic and structural divergence between AI-generated product recommendations and human influencer marketing messages in social commerce contexts. Employing a mixed-methods computational approach integrating term frequency analysis, TF-IDF weighting, Latent Dirichlet Allocation (LDA) topic modeling, and BERT-based contextualized semantic embedding analysis (KR-SBERT), we examined 330 Instagram influencer posts and 541 AI-generated responses concerning inner beauty enzyme products—a hybrid category combining functional health claims with hedonic beauty appeals—in the Korean social commerce market. AI-generated responses were collected through a systematically designed query protocol with empirically grounded prompts derived from actual consumer search behaviors, and analytical robustness was verified through sensitivity analyses across multiple parameter thresholds. Our findings reveal a fundamental divergence in persuasive architecture: human influencers construct experiential narratives exhibiting message characteristics typically associated with peripheral-route cues (sensory descriptions, emotional testimonials, social context), while AI recommendations employ systematic, evidence-based discourse exhibiting message characteristics typically associated with central-route argumentation (functional mechanisms, ingredient specifications, objective criteria). Topic modeling identified four distinct thematic clusters for each source type: human discourse centers on embodied experience and relational consumption, whereas AI discourse organizes around informational utility and rational decision support. Jensen–Shannon Divergence analysis (JSD = 0.213 bits) confirmed moderate distributional divergence, while chi-square testing (χ² = 847.23, p < 0.001) and Cramér’s V (0.312, indicating a medium-to-large effect) demonstrated statistically significant and substantively meaningful differences. These findings extend CASA theory by demonstrating that AI recommendation agents develop a characteristic “AI communication signature” distinguishable from human persuasion patterns. We propose an integrated Dual-Agent Persuasion Proposition—synthesizing CASA, ELM, and Source Credibility perspectives—suggesting that AI and human recommenders serve complementary functions across different stages of the consumer decision journey—a proposition whose predictions regarding sequential persuasive effectiveness and consumer processing routes await experimental validation. These findings carry implications for AI content strategy optimization, platform design, and emerging regulatory frameworks for AI-generated content labeling. Full article

The growing demand for clean-label bakery products requires a deeper understanding of how functional ingredients and physicochemical properties shape consumer perception. This study characterized nine commercial clean-label breads formulated with alternative flours, oilseeds, and functional ingredients by integrating instrumental analyses (color, porosity, free amino acids, total phenolic content, antioxidant activity) with consumer evaluation using hedonic testing and Check-All-That-Apply (CATA). Sixty-five consumers evaluated the breads under blind conditions. Results showed that flour type and seed inclusion significantly affected color, structure, and bioactive compound levels. Breads with higher phenolic content and antioxidant activity (GB-B, GB-C, GB-D, PB-I) exhibited more complex aroma profiles, whereas breads with higher porosity (GB-A, PB-G) were perceived as softer. Taste and texture showed the strongest correlation with overall liking (r > 0.84). CATA and penalty analysis identified soft, easy to chew, sweet, and umami as key drivers of liking, while dry, adhesive, bran odor, and bitter negatively impacted acceptance. Data revealed that consumer preference depends on the balance between structural attributes, flavor development, and nutritional composition. These findings provide actionable insights for the formulation of clean-label breads that balance health benefits and sensory acceptance. Full article

This study investigates the Wider Economic Impacts (WEIs) of railway infrastructure in Italy by analysing how station characteristics and surrounding urban contexts are capitalized into residential property values. A nationwide cross-sectional dataset covering 985 railway stations is used to estimate a Hedonic Price Model (HPM) combining observed variables and latent constructs derived from Confirmatory Factor Analysis (CFA). Results show that railway centrality, long-distance service provision, and multimodal integration are positively associated with housing prices. In particular, shared mobility services generate significant value uplift effects, especially around Local and Local Plus stations. Conversely, car-oriented accessibility is negatively associated with residential values, reflecting the capitalization of traffic-related externalities. Socioeconomic and tourism-related characteristics further contribute to heterogeneous capitalization patterns across the national territory. The findings provide systemic empirical evidence to support investment prioritization, multimodal integration, and value uplift of station areas within the Italian railway network. Full article

Wine represents one of the most complex food matrices from a sensory perspective, as its appreciation emerges from the interaction between chemical composition, perceptual mechanisms, and contextual influences. Contemporary research in oenology and sensory science increasingly recognizes wine evaluation as an integrated perceptual event shaped by cognition, memory, and affect, rather than a simple response to aroma or flavor cues. Live music is widely used in hospitality settings to enhance consumer experience; however, its specific influence on wine appreciation and emotional responses remains insufficiently explored, particularly in real-world contexts. This study investigates how two contrasting musical atmospheres—melancholic/relaxing and upbeat/motivational—modulate hedonic evaluations and emotional profiles during public wine tastings, compared with a no-music condition. Data were collected across five live tasting events (5 Wednesdays of Emotions) using structured questionnaires that included hedonic ratings and multidimensional emotional measures. Statistical analyses were conducted using non-parametric tests, meta-analytic p-value combination, and cumulative link mixed models for ordinal data. The presence of music significantly enhanced overall wine appreciation compared to the silent condition, although the magnitude and direction of the effect varied across individuals and musical styles. Upbeat/motivational music generally produced stronger and more consistent increases in liking than melancholic/relaxing music. Emotional responses—particularly positive surprise—emerged as key mediators of hedonic improvement and showed strong associations with overall liking. Preference profiling revealed distinct response patterns, indicating that auditory modulation of wine perception is not uniform across consumers. These findings support a crossmodal interpretation in which music shapes wine appreciation primarily through emotion-based and expectancy-related mechanisms rather than through direct sensory enhancement. By demonstrating these effects in ecologically valid tasting environments, the study highlights the role of auditory context as a meaningful component of multisensory wine experiences. Full article

The increasing demand for plant-based alternatives, driven by veganism, lactose intolerance, and greater health consciousness, has intensified research into dairy-free frozen desserts. This study investigates the development of a plant-based ice cream alternative utilizing oleosomes extracted from sunflower seed kernels as natural emulsifiers, eliminating the need for synthetic additives. Oleosomes were obtained through aqueous extraction from raw kernels, incorporated into emulsions in three levels (0, 12, and 24%), and combined with sunflower seed oil, tahini, date paste, and water to create the ice cream (IC) formulations. The physicochemical properties of three formulations of a sugar-free frozen dessert were studied. Physicochemical analyses assessed nutritional value, color (CIELab), melting time, stability, overrun, viscosity, and texture profile (TPA). Sensory evaluation was conducted using a hedonic test to assess the impact of tahini type (sunflower seed tahini or pumpkin seed kernel tahini) on the product acceptance. Results showed that higher oleosome content improved emulsion stability and melting resistance, while also producing a softer (30.74 ± 0.28 N), less adhesive (1.87 ± 0.20 mJ) texture, suitable for plant-based ice cream. Sensory analysis revealed a clear preference for the pumpkin tahini formulation, which scored 8.21 ± 0.62 for overall appreciation. The findings demonstrate that the addition of oleosome might improve textural attributes of the products, while the consumer preference could also be influenced by the type of tahini involved in the formulation. However, further studies are necessary to corroborate the proposed interaction mechanisms of ingredients. Full article

Artificial intelligence (AI) is transforming customer experience management (CXM) by enabling real-time, data-driven, and personalized interactions across digital touchpoints, including chatbots, voice assistants, generative AI, and immersive platforms. This study presents a PRISMA-based systematic literature review of 59 peer-reviewed studies published between 2021 and 2026, examining how AI-enabled personalization, privacy concerns, and customer value interact within AI-mediated customer experiences. Drawing on the Personalization–Privacy–Value (PPV) framework, the review synthesizes evidence on how AI-driven personalization enhances utilitarian, hedonic, experiential, relational, and emotional value, thereby strengthening satisfaction, engagement, loyalty, and behavioral intentions. At the same time, the findings reveal persistent tensions, as privacy concerns, perceived surveillance, algorithmic bias, and contextual moderators—including generational differences, cultural expectations, and technological literacy—frequently constrain value creation and erode trust. The review highlights that personalization benefits are highly contingent on transparency, perceived control, and ethical alignment, rather than personalization intensity alone. The study contributes by integrating ethical AI considerations into CXM research and clarifying conditions under which AI-enabled personalization leads to value creation versus value destruction. Managerially, the findings underscore the importance of ethical governance, transparent data practices, and customer-centered AI design to sustain trust and long-term customer relationships. Future research should prioritize longitudinal analyses of trust development, demographic heterogeneity, and cross-sector comparisons of AI governance as AI technologies become increasingly embedded in service ecosystems. Full article

Oats (Avena sativa L.) are a rich source of β-d-glucans, dietary fibre, proteins, and lipids. However, the behaviour of these components in wheat–oat composite systems during baking, particularly with regard to matrix-dependent analytical responses, remains unclear. This study evaluated the compositional changes, technological performance, and sensory quality of wheat bread enriched with various forms of oat. Composite flours containing 5–15% wholegrain oat flour, commercial oat bran, milled commercial oat flakes, or milled sprouted oat grain (sprouted under laboratory conditions for three days at 25 °C) were prepared using the Slovakian oat cultivar ‘Peter’. The raw materials, flour blends, and baked breads were analysed for β-d-glucans (BG), total dietary fibre (TDF), starch, proteins, and lipids using standardised enzymatic, gravimetric, and polarimetric methods. Bread quality was assessed through loaf volume measurements and a sensory evaluation using a 5-point hedonic scale by seven trained panellists. Multivariate statistical analysis was applied to integrate compositional, technological, and sensory data. Compared to wheat flour (0.24% BG and 3.45% TDF), the incorporation of oats significantly increased the contents of BG, TDF, proteins, and lipids, with oat bran showing the strongest enrichment effect (owing to 15.69% TDF in the raw material). Baking induced oat-form-dependent changes in the measured BG and TDF content. The level of BG diminished in wholegrain oat blends but increased or remained stable in bran-rich systems. This reflects differences in matrix structure and analytical extractability, rather than true compositional gains. Meanwhile, starch content consistently declined across all composite breads. Fibre-rich formulations exhibited reduced loaf volume and altered both bread geometry and morphology, particularly at 15% substitution. Breads containing 5% oat flour or moderate levels of oat bran (5 or 10%) were considered the most acceptable in terms of nutritional enhancement and quality attributes. Germinated oat breads showed the greatest technological impairment and the lowest sensory scores. Overall, moderate oat enrichment strikes a balance between nutritional improvement and technological performance without significantly compromising sensory quality. These findings emphasise the significance of matrix effects when interpreting standard total dietary fibre and β-d-glucans analyses and offer an integrated analytical and technological framework for the rational design of fibre-enriched cereal products. Full article

Participation in running events has expanded worldwide, consolidating itself as a form of active leisure and a driver of social and tourism engagement. Although runners’ motivations have been extensively studied, perceived inclusivity, understood as motivation derived from the event’s promotion of equitable participation across gender, age and functional ability, has rarely been examined as a distinct motivational dimension within structural models. This study analyses the motivational structure of participants in the Elche Half Marathon (Spain) and assesses the incremental contribution of inclusivity to traditional motivational frameworks. Based on a sample of 1053 valid responses, a two-stage psychometric and segmentation approach was applied. Exploratory and confirmatory factor analyses (EFA and CFA) were conducted to compare a four-factor model (sport-related hedonism, competition, socialization and digital socialization) with an extended five-factor model incorporating inclusivity. Subsequently, cluster analyses were performed using factor scores derived from each model. The results show that the inclusion of inclusivity improves model fit and increases explained variance, while also generating a more differentiated segmentation structure. The extended model revealed six motivational profiles, some of which displayed continuity with the classical solution, while others were reconfigured when inclusivity was introduced. Overall, the findings indicate that inclusivity functions as a complementary and context-dependent motivational dimension that refines the understanding of participation heterogeneity in running events. Rather than replacing traditional motives, inclusivity contributes incremental explanatory value and enhances the identification of motivational profiles, offering relevant insights for the design and management of mass-participation sporting events. Full article

Road running tourism events continue to grow worldwide and are increasingly leveraged by destinations seeking diversification and seasonality reduction. This study examines the motivational structure of participants in the 2025 Half Marathon Magaluf (Mallorca, Spain)—a mature Mediterranean resort undergoing tourism repositioning—and analyses how motivation-based segments relate to socio-demographic, sporting and tourism behaviours. Data were collected through a self-administered online survey (N = 306). An Exploratory Factor Analysis (EFA), followed by a Confirmatory Factor Analysis (CFA), validated a five-factor motivational structure: sport-related hedonism, socialisation, personal challenge, inclusiveness and digital interaction. A k-means cluster analysis identified five distinct segments—Digital Enthusiasts, Inclusive Enjoyers, Socializers, Hedonic Achievers and Inclusivists—each exhibiting differentiated patterns in Experience-Use History (EUH), origin, gender, and running-club membership. Notably, Socializers recorded the longest stays, Inclusive Enjoyers were overrepresented among first-time visitors, and Digital Enthusiasts and Hedonic Achievers included a higher share of international runners. These findings expand traditional motivational models by incorporating inclusiveness and digital interaction as emerging drivers and offer actionable recommendations for event organisers and destination managers seeking to enhance overnight stays and support destination repositioning strategies. Full article

Vegetable consumption in childhood remains below recommendations worldwide, particularly in disadvantaged socioeconomic groups. Building on prior work showing no socioeconomic status (SES) differences in children’s liking of familiar vegetables, this study examined whether their sensory and emotional descriptions vary by SES and how these relate to liking beyond hedonic ratings. A total of 363 Chilean fourth graders (9–10 years) from five SES groups evaluated eight vegetables at school. For each sample, children rated overall liking (7-point facial hedonic scale) and completed two CATA (Check-All-That-Apply) tasks: a child-derived sensory list (13 terms) and a validated emoji-based emotion list (33 items). Data were analyzed using Cochran’s Q tests, correspondence analyses, and mean-impact analyses. The use and diversity of sensory and emotional descriptors differed significantly between socioeconomic groups (p < 0.05): children from higher SES levels employed a broader and more differentiated vocabulary, while those from lower SES backgrounds used fewer significant terms. Across the sample, juicy, fresh, and mild flavors increased liking, whereas strong aroma decreased it (p < 0.05); positive emojis increased liking, whereas negative and neutral ones had no effect. These findings reveal that perceptual and affective representations are socially patterned, underscoring the need to foster sensory–affective literacy in lower-SES contexts. Full article