VALDÉS ALARCÓN, MARCOS EDUARDO
Preferred name
VALDÉS ALARCÓN, MARCOS EDUARDO
Main Affiliation
GIST - Grupo de Investigación Sistema turístico
Web Site
ORCID
0000-003-0906-1814
Scopus Author ID
58806336500
9 results
Now showing 1 - 9 of 9
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Item type:Publication, Convolutional Neural Networks for Automated and Non Intrusive Measurement of Customer Satisfaction in Restaurants(MDPI AG, 2025-12-03); ; ; ; Customer satisfaction (CS) is a cornerstone of competitiveness in the hospitality sector, particularly in restaurants, where service interactions are highly sensory and time-sensitive. Traditional measurement instruments, such as SERVQUAL, SERVPERF, and the American Customer Satisfaction Index, provide valuable diagnostic insights but remain limited by recall bias, social desirability, and delayed feedback. Advances in deep learning now enable non-intrusive, real-time monitoring of customer experience. This study evaluates the feasibility of using a convolutional neural network (CNN) to automatically classify customer satisfaction based on facial expressions captured at the point of payment in a restaurant. From an initial dataset of over 5000 images, 2969 were validated and labeled through a binary self-report mechanism. The CNN, implemented with transfer learning (MobileNetV2), achieved robust performance, with 93.5% accuracy, 92.8% recall, 91.0% F1-score, and an area under the ROC curve of 0.93. Comparative benchmarks with Support Vector Machine and Random Forest classifiers confirmed the superiority of the CNN across all metrics. The findings highlight CNNs as reliable and scalable tools for continuous CS monitoring, complementing rather than replacing classical survey-based approaches. By integrating implicit, real-time signals with traditional instruments, restaurants can strengthen decision-making, enhance service quality, and co-create personalized experiences while addressing challenges of explainability, external validity, and data ethics. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Demographic Capital and the Conditional Validity of SERVPERF: Rethinking Tourist Satisfaction Models in an Emerging Market DestinationTourist satisfaction models typically assume that service performance dimensions carry the same weight for all travelers. Drawing on Bourdieu, we reconceptualize age, gender, and region of origin as demographic capital, durable resources that mediate how visitors decode service cues. Using a SERVPERF-based survey of 407 international travelers departing Quito (Ecuador), we test measurement invariance across six sociodemographic strata with multi-group confirmatory factor analysis. The four-factor SERVPERF core (Access, Lodging, Extra-hotel Services, Attractions) holds, yet partial metric invariance emerges: specific loadings flex with demographic capital. Gen-Z travelers penalize transport reliability and safety; female visitors reward cleanliness and empathy; and Latin American guests are the most critical of basic organization. These patterns expose a boundary condition for universalistic satisfaction models and elevate demographic capital from a descriptive tag to a structuring construct. Managerially, we translate the findings into segment-sensitive levers, visible security for youth and regional markets, gender-responsive facility upgrades, and dual eco-luxury versus digital-detox bundles for long-haul segments. By demonstrating when and how SERVPERF fractures across sociodemographic lines, this study intervenes in three theoretical conversations: (1) capital-based readings of consumption, (2) the search for boundary conditions in service-quality measurement, and (3) the shift from segmentation to capital-sensitive interpretation in emerging markets. The results position Ecuador as a critical case and provide a template for destinations facing similar performance–perception mismatches in the Global South. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A Simple Overview in Magnetic Resonance Imaging Application in Evaluation of Food Quantity and Quality Aspects(United Scientific Group, 2024-10-03) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Review of Some Thermal Methods in Drying and Roasting Processes(United Scientific Group, 2024-09-18) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, The Effect of Optimizing the Stripping and Drying Parameters During Industrial Extraction on the Physicochemical Properties of Soybean Oil(MDPI AG, 2025-02-14); Soybean oil is the second most consumed vegetable oil worldwide and is recognized as a source of heart-healthy polyunsaturated fatty acids. Optimizing the extraction process in the oil industry is essential for both economic and environmental sustainability. This research aimed to determine the optimal conditions for various extraction parameters—stripper temperature (110–140 °C), stripper pressure (150–210 mbar), and dryer pressure (60–120 mbar)—and their effects on the physicochemical properties of soybean oil. These properties include oil-insoluble fine substances, acidity, the color index, peroxide value, oxidative stability, and moisture content. The results indicated that the stripper temperature significantly influenced oil-insoluble fine substances, acidity, the color index, and peroxide value (p < 0.05). The optimal conditions for oil extraction were found to be a stripper temperature of 110 °C, a stripper pressure of 150 mbar, and a dryer pressure of 120 mbar. Under these conditions, the oil-insoluble fine substances, acidity, the color index, peroxide value, oxidative stability, and moisture content of soybean oil were in the ranges of 0.2–0.58%, 0.63–1.15%, 4.3–5.5, 0.67–1.23 meqO2/kg, 3–5.5, and 0.05–0.11%, respectively. These findings provide valuable insight for optimizing soybean oil extraction processes to enhance quality and efficiency. Future advancements in industrial oil extraction are expected to focus on integrating efficient, eco-friendly technologies and enhancing precision through automation and data analytics to optimize yield and minimize waste. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Mycotoxins’ Contamination in Food and Feeds: A Review(United Scientific Group, 2023-11-06) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Effect of Optimizing the Black Plum Peel Extract as Natural Antioxidant and Storage Time on Oxidative Stability of Sunflower Oil(United Scientific Group, 2024-07-02) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Physical Properties, Antioxidant Activity, and Antimicrobial Properties of Edible Film Prepared from Black Plum Peel Extract as a Valuable By-product of Plum Processing(United Scientific Group, 2023-11-17) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Infrared Roasting Salted Pistachio Nut Moisture Loss Kinetic and Mathematical Modeling(United Scientific Group, 2023-11-17); Toktam Mohammadi Moghaddam