Centro de Investigación en Empresa, Sociedad y Tecnología

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El Centro de Investigación en Empresa, Sociedad y Tecnología -ESTec tiene como misión la investigación del comportamiento de organizaciones, empresas e individuos en relación con la selección y uso de tecnologías y el desarrollo de innovaciones. Adicionalmente, el ESTec se interesa por investigar el comportamiento humano y organizacional en el marco de los esfuerzos de sostenibilidad que llevan adelante nuestras sociedades.

El ESTec mediante sus esfuerzos de investigación busca generar conocimiento útil para la sociedad y para sus integrantes a fin de que puedan aprovechar los avances de la tecnología y contribuir a un desarrollo sostenible.

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Comparative analysis of previous YOLO detectors and YOLOv26s for real-time weapon detection in video surveillance
(Frontiers Media SA, 2026-04-28)
Fierro Silva, Carlos Julio
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Del-Valle-Soto, Carolina
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Bran, Carlos
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Varela Aldas, José
Real-time weapon detection in video surveillance is a critical capability for artificial intelligence assisted security systems, particularly in scenarios constrained by low latency, limited computational resources, and strict power efficiency requirements typical of edge artificial intelligence deployments. This work presents a comparative analysis of lightweight YOLO based object detectors, namely YOLOv8s, YOLOv9s, YOLOv10s, and YOLOv11s, vs. the recently introduced YOLOv26s model. In contrast to conventional benchmarking studies, this work extends the evaluation to real-world edge deployment conditions using an NVIDIA Jetson Nano device, explicitly measuring end-to-end latency, including preprocessing, inference, and post-processing stages. While earlier YOLO variants primarily relied on convolutional neural network architectures and intermediate explorations such as attention centered designs aimed to improve detection accuracy, YOLOv26 represents a paradigm shift by being designed from the ground up for low power edge devices, emphasizing architectural simplicity and deployment efficiency. To ensure a fair and reproducible evaluation, all models are trained on the same weapon detection dataset under a unified experimental protocol using small scale variants.The experimental results reveal that, despite exhibiting comparable inference times, different models show significantly different real-time performance due to variations in post-processing complexity. Specifically, models such as YOLOv8s, YOLOv9s, and YOLOv11s incur a substantial post-processing overhead, whereas YOLOv10s and YOLOv26s produce compact output representations that drastically reduce post-processing cost.This leads to a clear separation in deployment behavior, where end-to-end latency is reduced from approximately 300 ms to 125–130 ms, effectively doubling the achievable frame rate on embedded hardware. Rather than proposing a universal ranking, the study analyzes the trade offs introduced by architectural evolution and optimization strategies, providing technical criteria to support model selection under resource constrained deployment scenarios and demonstrating that post-processing efficiency, rather than inference speed alone, is the dominant factor in real-time edge performance. Copyright © 2026 Fierro Silva, Del-Valle-Soto, Bran and Varela-Aldás.
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Predictive Motivations in Satisfaction and Loyalty in Sustainable Coastal and Marine Destinations: Galapagos National Park, Ecuador
(MDPI AG, 2026-08-06)
Carvache-Franco, Mauricio
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Núñez-Naranjo, Aracelly Fernanda
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Carvache-Franco, Orly
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Torres-Naranjo, Mónica
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Carvache-Franco, Wilmer
Studying sustainability in marine and coastal tourism within national parks is essential to balance visitor use with the conservation of fragile ecosystems and biodiversity. In this context, the Galápagos Archipelago is a major coastal and marine destination in Ecuador, recognized as a UNESCO World Heritage Site. The aim of this empirical study was (i) to identify the principal motivational dimensions in sustainable coastal and marine destinations; (ii) to determine which motivations significantly predict tourist satisfaction in these contexts; and (iii) to establish which motivations influence loyalty in sustainable coastal and marine destinations. The research was conducted in situ, obtaining 407 valid questionnaires. Multiple regression analysis and exploratory factor analysis were applied. The results reveal six motivational factors: learning; heritage and nature; sun and beach; sports; authentic coastal experience; novelty; and social interaction. The motivation that most strongly predicts satisfaction is heritage and nature, followed by novelty. Likewise, the motivation that most strongly predicts loyalty is heritage and nature, with additional influence from sun and beach and sports motivations. These findings provide practical guidance for the development of sustainable destination management plans and contribute to the academic literature on sustainability, satisfaction, and loyalty in coastal and marine tourism contexts. © 2026 by the authors.
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Electronic Word of Mouth and Sustainability: A Bibliometric Approach
(Springer Nature Switzerland, 2026)
Cruz Cárdenas, Jorge
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Ramos-Galarza, Carlos
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Palacio-Fierro, Andrés
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Guadalupe-Lanas, Jorge
Electronic word of mouth (eWOM) is a type of human-computer interaction that comprises simple, two-way communication, disseminating information about companies, brands, and products through digital spaces. Given the significant interest in eWOM, various extant studies have sought to structure this field of study through a bibliometric approach. As the literature on eWOM has continued to grow, bibliometric studies on eWOM have begun to be specialized. Following this line of work, the present bibliometric study seeks to unravel eWOM’s structure as it applies to sustainability, a topic of great current importance. Using the Scopus database, 1,968 documents were identified. Descriptive and productivity analyses characterize the field of eWOM and sustainability as a rapidly growing and multidisciplinary field, in which China and the United States stand out in the literature. Science mapping analyses have identified four clusters of terms associated with research lines: 1) human behavior in eWOM, 2) social aspects of eWOM and sustainability, 3) eWOM’s impact on sustainability and tourism, and 4) eWOM’s technological aspects and measurement. The overlay visualization of term analysis reveals an evolution in research interest, progressing from technological aspects, through economic and behavioral aspects, to the current emphasis on sustainability and tourism. Finally, this study discusses these results’ implications for theory and practice. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.
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Analysis of YOLOv26 Variants (Nano to Extra-Large) for Real-Time Weapon Detection in Video Surveillance
(IEEE, 2026-07)
Fierro Silva, Carlos Julio
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Del-Valle-Soto, Carolina
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Varela Aldas, José
Real-time weapon detection in video surveillance systems is a critical requirement for proactive security applications, particularly under the computational and latency constraints imposed by edge artificial intelligence deployments. While the YOLO family of object detectors has undergone continuous architectural evolution, the recently introduced YOLOv26 represents a significant redesign aimed at improving efficiency, stability, and deployment suitability across a wide range of hardware platforms. This work presents a comprehensive and homogeneous experimental evaluation of the full YOLOv26 model family, ranging from nano (YOLOv26n) to extra-large (YOLOv26x) variants, for real-time weapon detection in surveillance imagery. All models are trained and evaluated under identical conditions using a dataset that explicitly includes visually similar non-weapon objects as hard negatives, enabling a realistic assessment of false positives and false negatives in safety critical scenarios. The analysis encompasses training and validation dynamics, precision, recall evolution, mean Average Precision (mAP) at multiple IoU thresholds, class-wise confusion matrices, and inference latency. Results show that performance improves consistently from smaller to medium sized models, with YOLOv26m achieving the most balanced trade off between detection accuracy, robustness, and computational cost. Larger variants provide marginal accuracy gains at significantly higher complexity, revealing diminishing returns for edge oriented deployments. Overall, the findings demonstrate that the YOLOv26 architecture offers a scalable and mature detection framework, where model selection can be guided by explicit operational criteria rather than raw accuracy alone. This study establishes a strong baseline for future work on real world edge deployment, multi camera surveillance systems, and hardware aware optimization of next generation YOLO detectors. © 2026 IEEE.
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Взаимосвязь демонстративного потребления в социальных сетях и одиночества (на примере постинга о путешествиях)
(National Research University, Higher School of Economics (HSE), 2026-03-30)
Maksimenko, Aleksandr
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Zabelina, Ekaterina
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Cruz Cárdenas, Jorge
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Zagladina, Alexandra
Social networks have intensified conspicuous consumption, turning visual travelrelated content into a key tool for status self-presentation and the affirmation of social position. The present study is aimed at examining the socio-demographic markers of conspicuous consumption on social networks and its relationship with loneliness. The study involved 100 respondents (M = 39.34; SD = 10.31), including 43% men and 57% women, who actively travel and post photographs from their trips on social networks. The following instruments were used: the Conspicuous Consumption of Posting Travel Photos Scale (CCPS) and the Social and Emotional Loneliness Scale for Adults (SELSA). Data were analyzed using confirmatory factor analysis, as well as correlational and comparative analyses. Four factors of tourism snobbery were identified: “pure conspicuous consumption” — the publication of status-related photographs emphasizing wealth and belonging to the upper class; “group inclusion” — the desire to conform to trends through images from popular destinations; “uniqueness of the place” — the demonstration of rare locations to stand out and emphasize the exclusivity of the experience; and “uniqueness of the self” — the desire to showcase originality and aesthetic taste through visual content. Gender differences manifest in the fact that women more often use travel-related content to express their uniqueness. With age, the need for conspicuous consumption decreases; income level also affects the nature of self-presentation, as respondents with higher income are less likely to emphasize status. In addition, the results showed that posting photographs with the aim of joining a group is positively correlated with romantic and social loneliness, but negatively correlated with family loneliness. A relationship was found between social loneliness and the motivation to demonstrate the uniqueness of the visited place and one’s own personality, which indicates an attempt to compensate for a lack of social ties through self-presentation in the digital environment. Overall, conspicuous consumption on social networks can be viewed as a dynamic phenomenon situated at the intersection of social comparison, self-presentation, and loneliness. © 2026, National Research University Higher School of Economics (HSE University). All rights reserved.
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Institutional trauma, absence of accountability, and psychopathology in a juvenile serial homicide case
(Frontiers Media SA, 2026-05-25)
Ramos Galarza, Carlos
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Obregón, Jennifer
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Guerrero, Brenda
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Cruz Cárdenas, Jorge
Juan Fernando Hermosa, infamously known as “The Child of Terror, ” committed 23 murders in Ecuador between 1991 and 1992. This perspective article offers a conceptual and theoretical analysis of the interplay between institutional trauma, accountability, and psychopathology in juvenile justice settings, using Hermosa’s trajectory as an illustrative example. Drawing on publicly available judicial records, academic literature, and journalistic sources, we advance the argument that institutional trauma, harm inflicted or exacerbated by juvenile justice and residential systems themselves, and the complete absence of organizational accountability may interact to worsen, rather than reduce, severe antisocial outcomes. Hermosa’s incarceration at the Virgilio Guerrero Institute is examined not as empirical evidence but as a theoretically informative case that highlights the potential consequences of punitive, non-rehabilitative environments. We propose that without procedural, therapeutic, restorative, and systemic accountability mechanisms, juvenile justice settings risk becoming trauma-generating institutions that compound pre-existing psychopathology. Particular attention is given to the hypothesized intersection of early childhood maltreatment and later institutional trauma as a pathway toward severe antisocial development. This perspective concludes by outlining key accountability mechanisms, external oversight, youth grievance procedures, trauma-informed staff training, and transparent error remediation, as essential components for preventing the escalation of violence among at-risk youth. The article aims to stimulate theoretical discussion and inform policy reform rather than to generalize from a single case. Copyright © 2026 Ramos-Galarza, Obregón, Guerrero and Cruz-Cárdenas.
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Artificial Intelligence Anxiety in the Educational Context: Psychometric Adaptation of the Scale on a Sample of Russian Students
(Moscow Polytechnic University, 2026-06-24)
Maksimenko, A. A.
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Cruz Cárdenas, Jorge
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Zabelina, E. V.
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Kurapov, S. V.
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Pevneva, A. N.
Today, there is a growing anxiety about artificial intelligence in the educational space, which greatly affects the willingness to make technological decisions and plan for one's professional future. In empirical studies, AI anxiety is defined as a complex phenomenon including a range of negative emotional responses that shapes in people due to development and potential impact of artificial intelligence on various spheres of life. Given the impact of AI anxiety on learning, career choices, participation in the digital economy, and mental well-being, there is a need for its holistic conceptual description and reliable diagnosis. The aim of the study is to present a reliable and valid Russian-language tool for diagnosing AI anxiety in students. The adopted basis and modified for a student sample (N = 521) "Artificial Intelligence Anxiety Scale" (M.H. Alkhaibani et al.) showed an acceptable level of the external and internal validity as well as reliability on internal consistency. The factor analysis confirmed the five-factor structure of the questionnaire: concerns related to AI accuracy and reliability; concerns related to academic integrity (plagiarism); and concerns stemming from regulatory uncertainty (guidelines), fears of loss of learning and cognitive skills, as well as a decrease in motivation. External validity is confirmed by the correlations with neuroticism and conscientiousness as personality traits, image of the future, attitude towards artificial intelligence, and some socio-demographic characteristics. Adapted and modified psychodiagnostic tool for studying AI anxiety opens up opportunities for research on a Russian-speaking student sample. © Максименко А.А., Круз-Карденес Х., Забелина Е.В., Курапов С.В., Певнева А.Н., 2020. Creative Commons Attribution 4.0 License.
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Structure-Based Innovation Index (SBII) and Firm Performance in Ecuadorian Manufacturing SMEs: Evidence from Capital Efficiency and Sales per Employee
(MDPI AG, 2026-04-23)
Godoy Hurtado, Edgar Paul
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Vayas Ortega, Germania
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Suárez Pérez, Juan Carlos
Manufacturing SMEs in Ecuador operate under macroeconomic volatility and limited financing; improvements in processes and management are key mechanisms for sustaining productivity and competitiveness. In contexts where conventional innovation indicators are unavailable, financial ratios constitute replicable signals that close a measurement gap in emerging economies. This study constructs the Structure-Based Innovation Index (SBII) as the mean of within-sample percentile ranks of capital efficiency (EBIT/Assets) and sales per employee, using financial statements from the SCVS, sectoral indicators from ENESEM, and size classification from REEM. The sample includes 58 formal manufacturing SMEs in Ecuador in 2023, stratified by province and size. Performance is measured through labor productivity and operating profitability (EBIT/Sales). Tercile comparisons reveal clear performance differentiation: the high-SBII group exhibits substantially higher median sales per employee (USD 129,552 vs. USD 40,176 in the low group) and higher operating profitability. Signals are more strongly reflected in productivity than in margins, indicating that operational gains materialize earlier. A robustness check using SBIIalt confirms that gradients are not index artifacts. High-performing SMEs are distinguished by institutionalized operational discipline: asset utilization, throughput stability, and cost control. The SBII is a replicable proxy for structure-based innovation in data-constrained environments. The findings align with SDGs 8, 9, and 12. © 2026 by the authors.
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Cognitive and emotional predictors of self-regulated learning: a structural model based on executive functions, learning strategies, and sense of coherence
(2025)
Ramos Galarza, Carlos
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Jennifer Obregón
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Nancy Lepe-Martínez
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Milenko Del Valle
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Brenda Guerrero-Tates
Self-Regulated Learning (SRL) is a complex process that enables university students to consciously manage their learning and achieve strong academic performance throughout their academic career. This process is influenced by various factors, particularly within the cognitive and emotional domains. Specifically, SRL is shaped by variables such as Executive Functions, Sense of Coherence, and Learning Management Strategies. In this study, we hypothesized that Conscious Monitoring of Responsibilities, Supervisory Attentional System, Deliberate Emotion Regulation, Manageability, Meaningfulness, and Conscious Motivational Strategies contribute significantly to the variance observed in SRL. Two explanatory models were proposed to represent the dynamic relationships among these variables. The study involved a sample of 1316 university students from two Latin American countries: Chile (n = 631, Mage=20.18, SD=2.06) and Ecuador (n = 685, Mage=20.71, SD=1.99). Three scales were used to assess the variables included in the models, each demonstrating acceptable to strong internal consistency (α=0.70 to 0.85). The results revealed moderate to strong correlations among the variables (r = 0.27 to 0.64). The explained variance of SRL was 24% for the emotional and 30% for the cognitive dimensions. Both proposed models demonstrated adequate fit indices (CFI=0.96, RMSEA=0.05, SRMR=0.04), supporting the structural validity of the models. These findings suggest that SRL is the result of a complex interaction between cognitive and emotional factors. The models proposed in this study offer a valuable foundation for the development of targeted interventions aimed at enhancing SRL in university students and, consequently, improving their academic performance
22
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Retraction Note: A New Extended VIKOR Approach Using q-Rung Orthopair Fuzzy Sets for Sustainable Enterprise Risk Management Assessment in Manufacturing Small and Medium-Sized Enterprises
(2025)
Sun Cheng
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Sun Jianfu
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Melfi Alrasheedi
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Saeidi, Parvaneh
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Arunodaya Raj Mishra
The Editor-in-Chief and the publisher have retracted this article. The article was submitted to be part of a guest-edited issue. An investigation by the publisher found a number of articles, including this one, with a number of concerns, including but not limited to compromised editorial handling and peer review process, inappropriate or irrelevant references or not being in scope of the journal or guest-edited issue. Based on the investigation’s findings the Editor-in-Chief therefore no longer has confidence in the results and conclusions of this article. The authors disagree with this retraction.
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Centro de Investigación en Empresa, Sociedad y Tecnología

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