Search Results (79)

High penetrations of renewable generation are increasing the need for long-duration energy storage capable of intertemporal balancing and reserve provision. However, the market value of heterogeneous storage portfolios under shared grid-connection constraints remains insufficiently quantified. This study develops a risk-averse day-ahead co-bidding model for a hybrid pumped-hydro and compressed-air energy storage (CAES) portfolio participating jointly in energy and spinning-reserve markets. Monte Carlo sampling and scenario reduction are used to represent price uncertainty, while conditional value-at-risk (CVaR) captures downside-profit risk. Shared point-of-common-coupling (PCC) constraints explicitly couple electricity sales, purchases, and reserve offers. Compared with homogeneous pumped-hydro expansion, replacing the equivalent incremental pumped-hydro capacity with CAES increases the cumulative reserve bid by 65.71%, while expected profit decreases by 1.17% and raw-scenario back-test CVaR remains nearly unchanged, decreasing by only 0.05%. Relative to the unconstrained hybrid-storage case, the shared PCC constraints reduce expected profit, raw-scenario back-test CVaR, and reserve bids by 1.01%, 1.34%, and 18.62%, respectively. Scenario-reduction sensitivity and synthetic price–spread analyses indicate that the main operating mechanisms remain stable within the assumed scenario-generation framework, while sensitivity analyses reveal diminishing returns from CAES expansion and saturation of PCC-related profit gains near 5000 MW. Because all price scenarios are synthetic and neither historical nor independent out-of-sample market data are used, these analyses constitute model-based robustness tests rather than seasonal or real-market validation. The findings support the coordinated configuration of heterogeneous storage, grid-interface capacity, and risk preferences, but should be interpreted as market-bidding-level comparative evidence under the adopted equivalent CAES representation rather than as market-specific profitability forecasts. Full article

India’s rapid expansion of utility-scale solar photovoltaic (PV) capacity is increasingly constrained by aging assets and the temporal mismatch between generation and peak demand. This study develops a techno-economic framework integrating battery energy storage systems (BESSs) with repowered solar PV projects, using repowered electricity as a low-cost charging source. A capacity-based assessment estimates national repowering potential of 7.2 GWp under power purchase agreement constraints and 10.9 GWp under technical limits. The levelized cost of repowered electricity is ₹1.40/kWh, significantly lower than prevailing utility-scale solar tariffs under stated assumptions. Levelized storage costs range from ₹5.08 to ₹4.12/kWh for 2–6 h durations, declining with improved inverter and balance-of-system utilization. Financial analysis under a ₹10 per kWh peak tariff arbitrage scenario yields internal rates of return between 17.5% and 24.2%, with positive project viability across configurations. Sensitivity analysis identifies capital cost as the dominant economic driver. Environmental benefits include annual greenhouse gas reductions of 13.8–17.2 MtCO₂, accumulating to 411–514 MtCO₂ over the project lifetime. These findings demonstrate that repowering-integrated battery storage offers a cost-effective, scalable pathway to enhance renewable integration, displace fossil fuel peak generation, and support India’s low-carbon transition, highlighting a viable framework for improving system flexibility and overall system performance. Full article

This paper develops and evaluates a predictive analytics framework for influencer marketing return on investment (ROI), integrating hybrid deep learning architectures with trust-aware modelling to address the dual purpose of (a) developing a rigorous evaluation framework for influencer campaign performance and (b) examining the effectiveness of influencer marketing predictors. The concept of influencer marketing has quickly grown to be one of the most effective mediums within the contemporary digital advertising landscape. Due to the growing number of brands dedicating huge amounts of budgets to social media partnerships, the importance of data-driven approaches that can predict the outcomes of campaigns and, consequently, ensure the best possible return on investment (ROI) has become urgent. This paper introduces a machine learning system that can be used to forecast the sales of products promoted by influencer marketing campaigns based on campaign-level features, including type of platform, influencer type, type of campaign, time of the year, number of engagements, estimated reach, and campaign duration. A publicly available influencer marketing ROI dataset was trained and tested on an XGBoost regression model with a coefficient of determination ($R^2$) of 0.95 indicating high predictive power and generalization. The results show that engagement metrics and estimated reach are some of the most impactful factors in sales performance, and additional contextual factors like platform selection, type of campaign, and timing of the year also moderate results. In addition to predictive modelling, this paper explains how artificial intelligence (AI) can be strategically integrated throughout the influencer marketing lifecycle. With the inclusion of AI-based analytics, marketers will be able to leverage their intuitive decision-making processes with quantifiable and replicable measures and approaches that can lead to true consumer trust and lasting brand resonance. The framework proposed can provide practitioners and researchers with a scalable basis for implementing intelligent systems in the context of influencer marketing. Recent computer science research further demonstrates that AI-driven frameworks spanning generative content modelling, AI-powered CRM architectures for understanding consumer preferences on social media, and parasocial-trust models of influencer engagement provide strong methodological complements to the predictive approach developed here, while governance and project management considerations for deploying such systems are increasingly addressed in the literature. Concurrently, a growing body of influencer marketing research examines how platform affordances shape information-seeking and trust, how influencer attributes and social satisfaction mediate purchase intention, how influencer marketing drives sustainable consumption, and how social media measurably shapes health-related behaviours all of which motivate the predictive and trust-modelling objectives of this work. Full article

This study aims to provide insight into consumer purchasing decisions by integrating eye-tracking data with forecasting techniques. First, the study investigates how consumption motives (hedonic vs. utilitarian) and purchasing purposes (for oneself vs. for others) influence visual attention and decision-making processes. An experimental design was conducted with 128 participants in a simulated online shopping environment, where eye-tracking data were collected based on fixation counts and durations across defined Areas of Interest (AOIs). Second, a total of 20 input features were collected, comprising fixation counts and fixation durations for 10 review-related Areas of Interest (AOIs), and these features were evaluated across the experimental scenarios, while the binary output variable represented the participant’s purchase decision. These biometric features, together with scenario information, were used to forecast purchasing decisions using six machine-learning methods, including Artificial Neural Networks, Random Forest, Support Vector Machine, K-Nearest Neighbors, Naive Bayes, and Logistic Regression. The results indicate that consumers’ visual attention aligns with their consumption motives and purchasing purposes, revealing distinct gaze patterns across different scenarios. In the forecasting phase, the accuracy of different methods for predicting purchasing decisions using review-related eye-tracking data is evaluated. Support Vector Machines achieved the highest overall accuracy, approximately 59–60% across the evaluated datasets, compared with a validation-specific majority-class baseline of 53.85%. This corresponds to a modest improvement of approximately 5.15–6.15 percentage points over the naive benchmark. Overall, the findings suggest that objectively recorded review-related eye-tracking data can be operationalized as behavioral input features in a machine-learning-based purchase-decision classification framework, highlighting the methodological value of integrating eye-tracking insights with consumer behavior forecasting. 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

Background: Informal Street food vending plays a vital role in urban food systems by supporting livelihoods and improving access to affordable meals. Despite this contribution, persistent food hygiene and safety challenges continue to threaten public health and business sustainability. Existing research largely frames hygiene as a regulatory compliance issue, with limited empirical attention to how hygiene practices are associated with enterprise performance. Guided by the Health Belief Model (HBM) and the Balanced Scorecard (BSC), this study examined the relationship between food hygiene and safety practices, behavioural compliance, and business sustainability among informal food vendors. Methods: A cross-sectional mixed-methods design was used, combining vendor interviews (n = 30) and structured stall observations (n = 30). Quantitative data were analysed using descriptive and inferential statistics. Qualitative data were thematically analysed. Results: Only 50% of vendors held a valid Certificate of Acceptability (COA), despite 83% reporting prior inspections. Vendors operating for over seven years were significantly more likely to be certified (χ² = 8.23, p = 0.005), and certification was strongly associated with regulatory awareness (χ² = 16.12, p < 0.001). Although 70% reported awareness and 77% prior hygiene training, gaps persisted in sanitation, pest control, and consistent hygiene practices. Compliance was significantly associated with gender and education level (p < 0.05), as well as business duration and inspection history. Female vendors and those with at least secondary education were more likely to practice good hygiene, including the use of protective gear (χ² = 13.89, p = 0.008) and regular handwashing. Hygiene practices were also significantly linked to sustainability indicators aligned with Balanced Scorecard domains, including staffing levels, income categories, and operational duration (p < 0.05). Vendors employing more staff reported higher income, and visibly hygienic practices were associated with customer loyalty and repeat purchases, highlighting hygiene as both a public health requirement and a driver of business sustainability. Conclusions: The findings indicate that hygiene functions not only as a public health requirement but also as a strategic business asset. Integrating behavioural drivers with performance metrics offers a practical framework for designing interventions that strengthen both public health protection and the sustainability of informal enterprises. Full article

Sorghum (Sorghum bicolor L.) is an environmentally friendly crop known for its nutritional and bioactive properties. This study investigated the effects of sorghum on the antioxidant properties and consumer acceptance of nurungji, a traditional Korean snack. To understand the antioxidant contribution of ferulic acid in sorghum during non-enzymatic browning, the antioxidant activity of ferulic acid was evaluated using a sugar (glucose or fructose)–lysine Maillard reaction model system. Nurungji samples were prepared with varying sorghum blending ratios (SN0, SN25, SN50, SN75, and SN100) and heating durations (0, 1, 3, and 5 min). The total polyphenol and total flavonoid contents of nurungji increased significantly in a sorghum concentration- and heating duration-dependent manner. Antioxidant activities, including DPPH and ABTS radical scavenging activities, ferric reducing antioxidant power (FRAP), and reducing power, exhibited trends similar to those of the antioxidant components. In the isolated model system, the addition of ferulic acid significantly enhanced the antioxidant capacity of the Maillard reaction products (MRPs), with the fructose–lysine–ferulic acid solution exhibiting the highest activity. These results support the proposed mechanism that during the thermal processing of nurungji, complex polymeric phenolic compounds within the sorghum are degraded, releasing free ferulic acid that actively boosts the overall antioxidant properties of the resulting MRPs. Although the antioxidant properties of nurungji increased with higher sorghum concentration, the consumer acceptance evaluations indicated that SN0 and SN25 received significantly higher scores for overall acceptance, taste acceptance, and purchase intention (p < 0.05). Full article

Urban mobility is increasingly affected by air pollution and traffic congestion caused by conventional private vehicles, as well as by insufficient flexibility of public transport. Micromobility devices (MMDs) can mitigate these and other negative impacts on quality of life due to their distinctive characteristics, the significance of which is investigated in this research. To address these challenges facing the modern city, a system of 15 hierarchically unstructured criteria influencing the deployment of MMDs in urban areas was established. The relative weights of these criteria were calculated based on the assessments of 16 experts and the criterion weights were determined using four multi-criteria decision-making (MCDM) methods: ARTIW-L (Average Rank Transformation into Weight—Linear), ARTIW-N (Average Rank Transformation into Weight—Non-Linear), DPW (Direct Percentage Weight), and AHP (Analytic Hierarchy Process). The results indicate that the expert judgments are consistent, as Kendall’s coefficient of concordance 0.406 is 3.8 times greater than the minimum value of 0.106 (at a significance level 0.05 and 14 degrees of freedom). In addition, the consistency ratios (C.R.) calculated from the AHP pairwise comparison matrices were below 0.1. The demonstrated consistency of the expert judgements and the compatibility of all matrices justify adopting the average of the relative weights obtained using the four MCDM methods as the final solution. According to the experts, the most important criteria for MMD deployment are travel safety (0.1336), travel duration (0.1302), the influence of infrastructure quality on comfort (0.0841), impact on health (0.0805), and the cost of purchasing an MMD (0.0713), while the remaining criteria are of lower significance. Based on the research results it is expected that the identified micromobility implementation measures will be useful for decision-makers and urban development planners. Full article

The correct valuation of collateral supporting real estate loans has always been a key issue for the stability of the credit system. Substandard lending practices and the absence of uniform valuation approaches have historically contributed to the accumulation of non-performing loans. In recent years, several regulatory measures operating at both the European and national level have introduced principles, rules and procedures aimed at standardizing the valuation of properties pledged as collateral for credit exposures. These interventions seek to promote greater transparency, consistency, and prudence in property appraisals, thereby enhancing the soundness and resilience of the financial system. In January 2025, the updated Regulation (EU) 575/2013 came into force, incorporating the Basel III reform (also referred to as Basel 3+ or Basel IV). Among the innovations introduced, the concept of property value (PV) is particularly relevant, a prudential value that excludes expectations of price growth and considers the sustainability of the value over time in relation to the duration of the loan. PV is defined as a derived value with respect to market value (MV), determined by considering the main current and forward-looking risk factors that may arise during the life of the loan, including environmental, social and governance (ESG) risks, the intrinsic characteristics of the property and expectations regarding the economic cycle. This paper proposes a quantitative model for the determination of PV, applied to a practical case involving a residential property located in a medium-sized city in Italy’s Veneto region. The model adopts a deterministic and a probabilistic approach, the latter implemented through Monte Carlo simulation, which is indeed a generalization of the deterministic one. The model links the assessment of PV to the possible evolution of the property’s key parameters and the real estate cycle over the duration of the loan. It was tested under the assumption of a twenty-year mortgage originated in 2025 for the purchase of a residential property in Italy, considering two alternative locations: a suburban area and a city-centre area. The analysis conducted showed a substantially higher MV haircut for the suburban property compared with the central location. This difference reflects the fact that PV is less sensitive to real estate cycle fluctuations in more premium, central locations. Furthermore, the use of Monte Carlo simulation in the probabilistic approach enabled the calibration of the haircut according to a predefined confidence level, confirming the pattern observed in the deterministic framework. The combined evidence strengthens the empirical robustness of the model and highlights the importance of locational and cyclical dynamics in collateral valuation. Full article

Product visual strategies (PVS) on food packaging influence how consumers visually inspect products at the point of purchase. However, evidence comparing transparent windows and product images remains mixed, particularly regarding how these strategies interact with food unit size (FUS) and shape visual attention patterns. Moreover, few studies have examined these effects using objective eye-tracking measures within controlled experimental designs. This study employed a 2 × 2 between-subjects quasi-experiment to investigate the effects of PVS (transparent window and product image) and FUS (large unit and small unit) on visual attention and subsequent product-related evaluations. A total of 160 participants viewed realistic chocolate package stimuli that varied only in visual strategy and unit size. Eye movements were recorded using Tobii Pro Glasses 2. Visual attention was assessed through Time to First Fixation (TFF) and Fixation Duration (FD), while expected tastiness, expected quality, and purchase intention were measured using standardized self-report scales. The results showed that transparent-window packaging attracted visual attention more rapidly and sustained longer fixations than product-image packaging. These attention differences were accompanied by higher expected tastiness, expected quality, and purchase intention. While food unit size alone showed limited effects on eye-movement measures, a significant interaction was observed: small-unit designs elicited greater visual attention and more favorable evaluations only when the product was directly visible through a transparent window. Overall, the findings demonstrate how product visual strategies and food unit size jointly shape visual attention allocation during packaging inspection. By integrating eye-tracking measures with evaluation and behavioral intention outcomes, this study contributes to applied eye-movement research in food packaging contexts. Full article

This research evaluates Battery Energy Storage Systems (BESS) and Compressed Air Vessels (CAV) as complementary solutions for enhancing micro-grid resilience, flexibility, and sustainability. BESS units ranging from 5 to 400 kWh were modeled using a Nonlinear Autoregressive Neural Network with Exogenous Inputs (NARX) neural network, achieving high SOC prediction accuracy with R² > 0.98 and MSE as low as 0.13 kWh². Larger batteries (400–800 kWh) effectively reduced grid purchases and redistributed surplus energy, improving system efficiency. CAVs were tested in pumped-storage mode, achieving 33.9–57.1% efficiency under 0.5–2 bar and high head conditions, offering long-duration, low-degradation storage. Waterhammer-induced CAV storage demonstrated reliable pressure capture when Reynolds number ≤ 75,000 and Volume Fraction Ratio, VFR > 11%, with a prototype reaching 6142 kW and 170 kWh at 50% air volume. CAVs proved modular, scalable, and environmentally robust, suitable for both energy and water management. Hybrid systems combining BESS and CAVs offer strategic advantages in balancing renewable intermittency. Machine learning and hydraulic modeling support intelligent control and adaptive dispatch. Together, these technologies enable future-ready micro-grids aligned with sustainability and grid stability goals. Full article

Three-wheelers (3Ws—autos or auto-rickshaws) occupy a unique yet salient and substantive position within the context of India’s urban mobility. They provide critical first-and-last-mile connectivity, fill public transit coverage gaps, boost local and urban agglomeration economies, and are a major income source for millions. Their value and utility are especially pronounced in rapidly emerging Tier-II cities such as Amritsar. The city’s 7500-strong diesel 3W (d3W) fleet is the backbone of its transportation network but also contributes to air pollution. Though Amritsar’s favorable policies to transition the d3W fleet to electric (e3W) have reduced purchase costs by 40–60%, barriers remain. This study investigates the influence of the e3W user experience through a first-of-a-kind three-day pilot trial for ~300 d3W drivers. By leveraging a pre- and post-intervention framework combining surveys and trip diaries, this study evaluated how direct exposure influences adoption intentions, perceptions, and the social dynamics underpinning decision-making. In total, ~6% of participants switched to e3Ws following the trial, and there was a 20% drop in “don’t know” answers regarding charging duration and range. The results show non-random and meaningful shifts in attitudes, a greater awareness of range and charging times, improved views on charging convenience and vehicle safety, and air quality benefits. Full article

In today’s fierce market competition, enterprises must quickly attract consumers’ attention to products and prompt them to make purchases. Based on regulatory focus theory, this study examines the impact of the congruence between different types of goal framing in advertising (promotion vs. prevention) and product types (hedonic vs. utilitarian) on individual consumer decision-making, as well as the underlying psychological mechanisms. The findings are as follows: (1) A goal-framing effect was observed, such that individuals allocated more attention and exhibited higher purchase intentions toward products presented with promotion-framed advertising. (2) A matching effect between goal-framing type and product type was identified: promotion framing increased purchase intentions for hedonic products, whereas prevention framing increased purchase intentions for utilitarian products. (3) Processing fluency mediated the effect of goal–product matching on consumer decision-making. (4) The presence of time pressure amplified the goal-framing effect, leading to stronger preferences under promotion-framed advertisements, as reflected in both longer fixation durations and higher purchase intentions. By integrating regulatory focus theory with product type matching, this study leverages eye-tracking data to reveal the cognitive processes underlying consumer decision-making and the moderating role of time pressure on goal-framing effects. The findings enrich the motivational perspective in consumer behavior research and provide empirical guidance for designing differentiated advertising strategies and optimizing advertising copy. Full article

Despite extensive research on green consumption, consumer purchase intentions for bamboo products under China’s “replacing plastic with bamboo” policy remain underexplored, given growing plastic pollution concerns. Research remains focused on established green products (e.g., green agriculture, energy-efficient appliances, new energy vehicles), overlooking consumer behavior and cognition toward emerging bamboo alternatives. This study employs eye-tracking technology to examine purchase intentions and visual attention allocation mechanisms for bamboo versus plastic products, analyzing the role of green consumption values (GCVs). Using a 2 (material: bamboo/plastic) × 2 (GCVs: high/low) mixed design, we recorded fixation duration, fixation count, and heatmaps from 70 participants. Behavioral results revealed significantly higher purchase intention for bamboo products, particularly among high-GCV consumers. Eye-tracking data showed greater visual attention (fixation duration/count) to bamboo products, with high-GCV participants exhibiting significantly stronger attentional bias toward bamboo. Findings demonstrate that bamboo’s eco-friendly attributes enhance both purchase intention and visual attention allocation, validating material salience in green decision-making. High GCVs strengthen automatic attentional bias toward sustainable materials, reinforcing purchase inclinations. This research provides empirical support for VBN theory at the cognitive level and offers policy-relevant insights for promoting “Bamboo Instead of Plastic” initiatives. Full article

Background/Objectives: Antimicrobial resistance (AMR) is a major threat to human, animal, and environmental health. To tackle AMR in the livestock sector, there is a need to understand the antimicrobial use (AMU) practices of different stakeholders in order to target the common knowledge gaps and inappropriate practices with tailored interventions. In the Western Balkans, published evidence shows the presence of AMR in both humans and animals. Since studies on AMU have mainly been conducted in humans, there is a significant knowledge gap about AMU in the livestock sector. The aim of this study was to assess the knowledge, attitudes, and practices of farmers, veterinarians, veterinary pharmacy personnel, and feed mill personnel related to AMU (focusing on antibiotics) and AMR in Albania, Bosnia and Herzegovina, Kosovo (References to Kosovo shall be understood to be in the context of Security Council resolution 1244 (1999)), Montenegro, North Macedonia, and Serbia. Methods: Field interviews were conducted in 2022 with 2815 participants in selected regions of the countries. Results: The findings showed that farmers engaged in imprudent practices, including purchasing antimicrobials without a prescription, administering antimicrobials for growth promotion, and disposing of expired antimicrobials in the garbage. Farmers’ main knowledge gaps were related to the duration of antimicrobial treatment and the differentiation between AMR and antimicrobial residues. This study also revealed poor record-keeping on animal treatments and a lack of some biosecurity measures. In terms of the attitudes and practices of veterinarians and veterinary pharmacy personnel, the belief that antimicrobial drugs are important for growth promotion, and the common use and sales of highest priority critically important antimicrobials should be targets for future interventions. Conclusions: Despite significant ongoing efforts to tackle AMR, there is still a need for training, awareness-raising, and policy interventions to address the knowledge gaps identified by this study and optimize AMU in the livestock sector in the Western Balkans. Full article