Search Results (5,502)

This study explores entertainment consumption patterns in Romania, a transitional digital culture characterized by high digital connectivity but underdeveloped physical infrastructure. Employing a dual qualitative coding methodology, this research combines inductive analysis of consumer focus groups with deductive analysis of expert interviews, enabling a multi-layered interpretation of both overt behaviors and latent emotional drivers. Seven key thematic dimensions, motivational depth, perceived barriers, emotional needs, clarity of preferences, future behavioral intentions, social connection, and identity construction, were analyzed and compared using a Likert-based scoring framework, supported by a radar chart and comparison matrix. Findings reveal both convergence and divergence between consumer and expert perspectives. While consumers emphasize immediate experiences and logistical constraints, experts uncover deeper emotional motivators such as validation, mentorship, and identity formation. This behavioral–emotional gap suggests that, although digital entertainment dominates due to accessibility, it often lacks the emotional richness associated with physical formats, which are preferred but less accessible. This study underscores the importance of triangulated qualitative inquiry in revealing not only stated preferences but also unconscious psychological needs. It offers actionable insights for designing emotionally intelligent and culturally responsive entertainment strategies in digitally saturated yet infrastructure-limited environments. Full article

The introduction of mobile banking is essential in today’s financial sector, where technological innovation plays a critical role. To remain competitive in the current market, businesses must analyze client attitudes and perspectives, as these influence long-term demand and overall profitability. While previous studies have explored general adoption behaviors, limited research has examined how individual factors such as social influence, lifestyle compatibility, financial technology self-efficacy, and perceived usage cost affect mobile banking adoption among specific generational cohorts. This study addresses that gap by offering insights into these variables, contributing to the growing literature on mobile banking adoption, and presenting actionable recommendations for financial institutions targeting younger market segments. Using a structured questionnaire survey, data were collected from both users and non-users of mobile banking among the Gen Z population in the United States. The regression model significantly predicts mobile banking adoption, with an intercept of $-0.548$ ($p < 0.001$). Among the independent variables, perceived cost of usage has the strongest positive effect on adoption ($B=0.857$, $\beta =0.722$, $p < 0.001$), suggesting that adoption increases when mobile banking is perceived as more affordable. Social influence also has a significant positive impact ($B=0.642$, $\beta =0.643$, $p < 0.001$), indicating that peer influence is a central driver of adoption decisions. However, self-efficacy shows a significant negative relationship ($B=-0.343$, $\beta =-0.339$, $p < 0.001$), and lifestyle compatibility was found to be statistically insignificant ($p=0.615$). These findings suggest that reducing perceived costs, through lower fees, data bundling, or clearer communication about affordability, can directly enhance adoption among Gen Z consumers. Furthermore, leveraging peer influence via referral rewards, Partnerships with influencers, and in-app social features can increase user adoption. Since digital self-efficacy presents a barrier for some, banks should prioritize simplifying user interfaces and offering guided assistance, such as tutorials or chat-based support. Future research may employ longitudinal designs or analyze real-life transaction data for a more objective understanding of behavior. Additional variables like trust, perceived risk, and regulatory policies, not included in this study, should be integrated into future models to offer a more comprehensive analysis. Full article

E-commerce growth has reshaped consumer behavior and retail services, driving parcel demand and challenging last-mile logistics. Existing research predominantly relies on survey data and global regression models that overlook intra-urban spatial heterogeneity in shopping behaviors. This study bridges this gap by analyzing e-commerce demand’s spatial distribution from a retail service perspective, identifying key drivers, and evaluating implications for omnichannel strategies and logistics. Utilizing waybill big data, spatial analysis, and multiscale geographically weighted regression, we reveal: (1) High-density e-commerce demand areas are predominantly located in central districts, whereas peripheral regions exhibit statistically lower volumes. The spatial distribution pattern of e-commerce demand aligns with the urban development spatial structure. (2) Factors such as population density and education levels significantly influence e-commerce demand. (3) Convenience stores play a dual role as retail service providers and parcel collection points, reinforcing their importance in shaping consumer accessibility and service efficiency, particularly in underserved urban areas. (4) Supermarkets exert a substitution effect on online shopping by offering immediate product availability, highlighting their role in shaping consumer purchasing preferences and retail service strategies. These findings contribute to retail and consumer services research by demonstrating how spatial e-commerce demand patterns reflect consumer shopping preferences, the role of omnichannel retail strategies, and the competitive dynamics between e-commerce and physical retail formats. Full article

Rising volumes of textile waste necessitate the development of more efficient recycling systems, with a primary focus on the optimization of sorting technologies. Near-infrared (NIR) spectroscopy is a state-of-the-art method for fiber identification; however, its accuracy in quantifying textile blends, particularly common polyester/cotton blend textiles, still requires refinement. This study explores the potential and limitations of NIR spectroscopy for quantifying cotton content in post-consumer textiles. A lab-scale NIR sorter and a handheld NIR spectrometer in complementary wavelength ranges were applied to a diverse range of post-consumer textile samples to test model accuracies. Results show that the commonly assumed 10% accuracy threshold in industrial sorting can be exceeded, especially when excluding textiles with <35% cotton content. Identifying and excluding the range of non-linearity significantly improved the model’s performance. The final models achieved an RMSEP of 6.6% and bias of −0.9% for the NIR sorter and an RMSEP of 3.1% and bias of −0.6% for the handheld NIR spectrometer. This study also assessed how textile characteristics—such as color, structure, product type, and alkaline treatment—affect spectral behavior and model accuracy, highlighting their importance for refining quantification when high-purity inputs are needed. By identifying current limitations and potential sources of errors, this study provides a foundation for improving NIR-based models. Full article

Background/Objectives: Acrylamide is a probably carcinogenic to humans that naturally forms during the thermal processing of foods. An individual’s lifestyle—especially dietary habits and physical activity—may influence the severity of acrylamide’s adverse health effects. This study aimed to examine the relationship between adolescents’ dietary and exercise behaviors and their dietary acrylamide exposure and associated health risks. Methods: This descriptive and cross-sectional study was conducted with 370 high school students in Türkiye. Data were collected using the Nutrition Exercise Behavior Scale (NEBS) and a retrospective 24-h dietary recall questionnaire. Acrylamide exposure was calculated based on food intake to estimate carcinogenic (CR) and non-corcinogenic (target hazard quotient: THQ) health risks and analyzed in relation to NEBS scores. Results: Findings indicated that while adolescents are beginning to adopt healthy eating and exercise habits, these behaviors are not yet consistent. Emotional eating and unhealthy food choices still occur. Higher acrylamide exposure and risk values were observed in boys and underweight individuals. This can be explained mainly by the fact that boys consume more of certain foods—especially bread, which contains relatively higher levels of acrylamide—than girls do, and that underweight individuals have lower body weights despite consuming similar amounts of food as other groups. Bread products emerged as the primary source of daily acrylamide intake. Positive correlations were found between NEBS total and subscale scores and acrylamide exposure and health risk values. Conclusions: The study demonstrates a significant association between adolescents’ health behaviors and acrylamide exposure. These results underscore potential public health concerns regarding acrylamide intake during adolescence and emphasize the need for targeted nutritional interventions to reduce risk and promote sustainable healthy behaviors. Full article

The present study focuses on the attractiveness and perceived value of differentiated quality labels, such as the Protected Designation of Origin (PDO) and Protected Geographical Indication (PGI), for agri-food products from Extremadura (Spain). In doing so, it addresses a gap in the scientific literature concerning consumer behavior toward products bearing these certifications. The results show that awareness of these quality schemes is significantly higher among middle-aged and older individuals, underscoring the need for more modern and targeted communication strategies. The findings highlight the strategic role of agri-food marketing in promoting certified products and emphasize the importance of bridging the generational gap in consumer education. Overall, differentiated quality schemes are perceived as strategic tools to enhance the competitiveness of local products, strengthen cultural identity, and foster sustainable rural economies. Furthermore, this study identifies a negative relationship between the consumption of certified products and the awareness of certification and a positive relationship with the willingness to pay a premium. Consumers with greater awareness tend consume these products less, although they are more willing to pay higher prices for items bearing quality labels. Full article

To enhance the performance of online food delivery (OFD) services, it is essential to strengthen consumers’ intentions to use OFD apps, which are the core interface of this business. Accordingly, this study aims to identify the cognitive mechanisms that shape consumers’ intentions to use OFD apps and explore strategies to encourage their adoption. To achieve this, the study develops a research model that incorporates segmented dimensions of service convenience as key motivational factors, along with variables from the Technology Acceptance Model (TAM). A survey was conducted among OFD consumers in China, and the proposed research model was empirically tested using data from 478 valid responses. The analysis revealed that all six dimensions of service convenience serve as significant motivational drivers of OFD app usage. Furthermore, the study demonstrates that consumers’ coupon proneness and user-generated online reviews have significant moderating effects that reinforce the mechanism by which consumers adopt and use OFD apps. The findings and implications discussed in this study are expected to provide valuable insights and practical guidance for formulating effective strategies to promote more active consumer engagement with OFD apps in the future. Full article

This study dives into what drives people to use AR filters in the catering industry, focusing on the Hong Kong market. The main idea is to determine how “perceived value” shapes users’ intentions to engage with these filters. To do this, the research combines concepts from two popular models—the extended Technology Acceptance Model (TAM) and the Satisfaction–Loyalty Model (SLM)—to understand what influences perceived value. The survey data were then analyzed with Structural Equation Modeling (SEM) to see how perceived usefulness, enjoyment, satisfaction, and value connect to users’ intentions. The results showed that “perceived value” is a big deal—the main factor driving whether people want to use AR filters. Things like how useful or enjoyable the filters are and how satisfied users feel all play a role in shaping this perceived value. These findings are gold for marketing teams and AR developers, especially in the catering world. Combining TAM and the Satisfaction–Loyalty Model offers a fresh perspective on how AR technology influences consumer behavior. On top of that, it gives practical advice for businesses looking to make the most of AR filters in their marketing and customer experience strategies. Full article

The formation mechanism of Virtual Reality (VR) Immersive Experience (VRIE) is notably complex; this study aimed to dynamically decode its underlying drivers by innovatively integrating Flow Theory and Privacy Calculus Theory, focusing on Perceptual-Interactive Fidelity (PIF), Consumer Willingness to Immerse in Technology (CWTI), and the applicability of Loss Aversion Theory. To achieve this, we analyzed approximately 30,000 user reviews from Amazon using Latent Semantic Analysis (LSA) and regression analysis. The findings reveal that user attention’s impact on VRIE is non-linear, suggesting an optimal threshold, and confirm PIF as a central influencing mechanism; furthermore, CWTI significantly moderates users’ privacy calculus, thereby affecting VRIE, while Loss Aversion Theory showed limited explanatory power in the VR context. These results provide a deeper understanding of VR user behavior, offering significant theoretical guidance and practical implications for future VR system design, particularly in strategically balancing user cognition, PIF, privacy concerns, and individual willingness. Full article

Background/Objectives: Excessive sugar intake through sugar-sweetened beverages (SSBs) has raised global concerns due to its association with various health risks. This study evaluates the effectiveness of nudges—in the form of order placement, variety expansion, and a combination of both—in promoting non-SSB purchases at self-service kiosks, a key environment for SSB consumption. Methods: This study was conducted using a real-world kiosk at food and beverage outlets in South Korea from 28 May to 12 July, 2024. A total of 183 consumers aged 19 to 29 participated in this study. A single kiosk device was used with four screen layouts, each reflecting a different nudge strategy. Participants were unaware of these manipulations when making their purchases. After their purchases, participants completed a survey. All data were analyzed using IBM SPSS Statistics for Windows, Version 29.0. Results: Females reported significantly higher positive attitudes, preferences, and perceived necessity regarding nudges compared to males. In particular, both the single (variety) and combination (order and variety) nudges received positive responses from females (p < 0.001). The combination nudge significantly increased non-SSB purchases compared to the control (p < 0.05) and single (order) nudge groups (p < 0.01), which suggests that combination nudge is effective in promoting healthier beverage choices. Females were also more likely to purchase non-SSBs than males (p < 0.05). Conclusions: The findings suggest that the combination nudge strategy effectively promotes healthier beverage choices in real kiosk settings. Notably, females demonstrate significantly higher positive attitudes, preferences, and perceived necessity regarding nudges compared to males, and are also more likely to purchase non-SSBs. These findings offer valuable insights for real-world applications aimed at encouraging healthier consumption behaviors. Full article

Background: Taste changes are common during pregnancy and can have a significant impact on dietary habits. Objective: This study aimed to investigate the influence of the perception of sweet and fat taste on diet in pregnant diabetic women. Methods: This cross-sectional observational study included 66 pregnant women, 33 with gestational diabetes and 33 with pre-gestational type 2 diabetes. Taste perception tests were conducted to evaluate thresholds for detecting sweet and fatty tastes. Dietary surveys were used to assess daily nutrient intake, and various biochemical parameters, such as glycemia, HbA1c, and cholesterol, were analyzed. Results: The low-fat taster group (threshold > 0.75 mmol/L) included more patients with diabetes compared to those with gestational diabetes. All diabetic patients had low sucrose perception. Although pregnant women with gestational diabetes detected sweetness at high concentrations, pregnant women with diabetes detected it at lower concentrations (0.012 ± 0.023 mmol/L vs. 0.006 ± 0.005 mmol/L; p = 0.3). High-fat tasters exhibited elevated glycemia compared to low-fat tasters (6.04 ± 1.88 mmol/L vs. 7.47 ± 3.4 mmol/L; p = 0.03). They also had higher cholesterol (p = 0.04) and lower HDL-C levels (4.96 ± 1.04 mmol/L vs. 1.36 ± 0.29 mmol/L; p = 0.03). High-fat tasters showed more frequent daily consumption of oil, butter, cheese, and chocolate. The highly sweet tasters had higher cholesterol levels and lower LDL levels. Individuals who reported being highly sensitive to sweet taste consumed more daily oil, sweetened yogurt, or cream desserts, as well as white sugar. Conclusions: These findings indicate that altered sensitivity to fat and sweet tastes is associated with different dietary habits and metabolic profiles in pregnant women with diabetes. Specifically, reduced sensitivity to the taste of fat is associated with higher consumption of high-fat foods and poorer lipid profiles. In contrast, sensitivity to sweet taste correlates with an increased intake of sugary and fatty foods. Understanding these taste-related behaviors can help develop personalized nutritional strategies to improve metabolic control and maternal–fetal outcomes in this high-risk group. Full article

Research concerning green marketing has predominantly focused on consumer behavior. However, aspects such as the extent to which Small and Medium Enterprises (SMEs) embrace green marketing values, their ability to implement the green marketing mix, and the integration of green marketing into their business culture are critically important. This research aims to provide the 4P (product, price, place, and promotion)-focused green marketing literature with a measurement tool to assess how SMEs implement green marketing practices. The study employed a descriptive design and possesses an exploratory nature. Scale development involved two stages: First, analyses were conducted on a pre-test sample of 159 individuals, revealing the initial scale structure. Second, these analyses were repeated on a larger group of 387 participants. The scale was finalized by confirming the consistency of results across both analyses. Statistical Package for the Social Sciences (SPSS) version 24 and Analysis of Moment Structures (AMOS) version 24 were utilized for descriptive statistics and the scale development process. The final validated 12-item scale demonstrates a robust three-factor structure (“Environmental Promotion”, ”Green Packaging”, and ”Green Distribution”), explaining 62.6% of the total variance. The scale exhibits excellent psychometric properties, including high internal consistency (Cronbach’s α = 0.912), strong model fit from Confirmatory Factor Analysis (CFA), and both convergent and discriminant validity, as indicated by an Average Variance Extracted (AVE) value of 0.605. The scale is deemed applicable to larger populations. Full article

Healthy food service guidelines (HFSG) comprise food, nutrition, behavioral design, and other standards to guide the purchasing, preparation, and offering of foods and beverages in worksites and institutional food service. To date, there have been few attempts to synthesize evidence for HFSG effectiveness in non-K-12 or early childhood education sectors, particularly at worksites and institutional food services. We conducted a scoping review to achieve the following: (1) characterize the existing literature on the effectiveness of HFSG for improving the institution’s food environment, financial outcomes, and consumers’ diet quality and health, and (2) identify gaps in the literature. The initial search in PubMed and Web of Science retrieved 10,358 articles; after screening and snowball searching, 68 articles were included for analysis. Studies varied in terms of HFSG implementation settings, venues, and outcomes in both U.S. (n = 34) and non-U.S. (n = 34) contexts. The majority of HFSG interventions occurred in venues where food is sold (e.g., worksite cafeterias, vending machines). A diversity of HFSG terminology and measurement tools demonstrates the literature’s breadth. Literature gaps include quasi-experimental study designs, as well as interventions in settings that serve dependent populations (e.g., universities, elderly feeding programs, and prisons). Full article

Foraging behavior in hens is an important indicator of animal welfare. It involves both the search for food and exploration of the environment, which provides necessary enrichment. In addition, it has been inversely linked to damaging behaviors such as severe feather pecking. Conventional studies rely on manual observation to investigate foraging location, duration, timing, and frequency. However, this approach is labor-intensive, time-consuming, and subject to human bias. Our study developed computer vision-based methods to automatically detect foraging hens in a cage-free research environment and compared their performance. A cage-free room was divided into four pens, two larger pens measuring 2.9 m × 2.3 m with 30 hens each and two smaller pens measuring 2.3 m × 1.8 m with 18 hens each. Cameras were positioned vertically, 2.75 m above the floor, recording the videos at 15 frames per second. Out of 4886 images, 70% were used for model training, 20% for validation, and 10% for testing. We trained multiple You Only Look Once (YOLO) object detection models from YOLOv9, YOLOv10, and YOLO11 series for 100 epochs each. All the models achieved precision, recall, and mean average precision at 0.5 intersection over union (mAP@0.5) above 75%. YOLOv9c achieved the highest precision (83.9%), YOLO11x achieved the highest recall (86.7%), and YOLO11m achieved the highest mAP@0.5 (89.5%). These results demonstrate the use of computer vision to automatically detect complex poultry behavior, such as foraging, making it more efficient. Full article

Despite growing interest in AI technologies, there is a lack of integrated models explaining AI adoption in SMEs from a consumer perspective. This study addresses this gap. Although artificial intelligence (AI) has gained traction in digital innovation strategies, especially among SMEs, existing research lacks integrative models that address cognitive, contextual, and emotional factors driving AI adoption. This study addresses this gap by developing a theoretical model based on TAM and UTAUT2, enhanced with passion, workplace integration, and trust. Drawing on the Technology Acceptance Model and consumer trust theories, the study provides empirical insights into how these factors shape behavioral intentions to adopt AI technologies. The findings aim to inform both theory and practice by highlighting how emerging digital tools affect consumer decision making and engagement across personal and professional contexts. The study contributes to both theory and practice by offering empirical evidence on the drivers of AI adoption and by providing managerial recommendations for SMEs to implement AI-driven personalization responsibly. Full article