Repositorio Institucional del ITESO (ReI)
El Repositorio Institucional del ITESO (ReI), es un depósito digital que integra la producción académica de la universidad, quien administra, conserva y pone a disposición en modo de acceso abierto los trabajos de investigadores, profesores y estudiantes de esta casa de estudios.
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Modelo conceptual para diseño de mapa de viaje para la transformación digital sistémica en MiPyMEs
(ITESO, 2025-11) Puentes-Hernández, Edgar A.; Montiel-Vega, Miguel
Las Micro Pequeñas y Medianas Empresas (MiPyMEs) en México han tenido un bajo desempeño en términos de competitividad en los últimos 20 años. Esto es preocupante debido a su gran impacto en la sociedad, política y economía del país. La baja adopción de tecnologías, como herramienta de apoyo, es una de las principales causas, de acuerdo con el INEGI. La transformación digital ha demostrado fortalecer las capacidades competitivas, la innovación y la productividad de las MiPyMEs. Sin embargo, la dificultad con la que se encuentran las empresas al iniciarse en este proceso de adopción de tecnologías digitales no es menor. Además de existir impactos positivos a nivel organizacional, de desempeño y de industria/sociedad, también existen riesgos como problemas de seguridad y privacidad que deben ser abordados, aunado a esto se encuentra la complejidad técnica que implica la integración de dichas tecnologías. Esta investigación, desde un enfoque mixto, busca reducir la “brecha digital” a la que se enfrentan las MiPyMEs en el contexto actual para fortalecer sus capacidades competitivas y de innovación, por lo que surgen cuestionamientos para identificar las estrategias que permitan facilitar su adopción. Mismos cuestionamientos a los que se buscará dar respuesta a través de una revisión sistemática de la literatura y las bases teóricas sobre ciclos de vida de una organización, madurez y presencia digital de las mismas. Los instrumentos para la recopilación de información serán la aplicación de encuestas, entrevistas semi-estructuradas y etnografía digital a los actores y plataformas que son parte del ecosistema MiPyME desde una perspectiva constructivista, con un método de investigación-acción buscando un impacto positivo en el desarrollo económico, social y ecológico del país.
Estrategias empresariales en el turismo de naturaleza en la ZMG: un estudio de caso sobre su contribución a los ODS 8.5, 11.4 y 11.a
(ITESO, 2025-05) Sánchez-Gutiérrez, Osmar; Silvia-Flores, Martha L.
Este estudio analiza la relación entre las estrategias empresariales de organizaciones vinculadas al turismo de naturaleza en la Zona Metropolitana de Guadalajara (ZMG) y su alineación con los Objetivos de Desarrollo Sostenible (ODS), específicamente el ODS 8 (trabajo decente y crecimiento económico) y el ODS 11 (ciudades y comunidades sostenibles), a través de las metas 8.5, 11.4 y 11.a. El objetivo es visibilizar los esfuerzos concretos que estas organizaciones realizan en favor del desarrollo empresarial sostenible. Se empleó una metodología cualitativa de carácter exploratorio, mediante entrevistas semiestructuradas a representantes de 10 organizaciones, lo que representa el 32% de la población identificada (31 organizaciones). Los hallazgos muestran una implementación limitada de estrategias alineadas con los ODS. En relación con la meta 8.5, se identificaron iniciativas de proveeduría local poco formalizadas; respecto a la meta 11.4, la escasa conexión responde a la baja demanda del público hacia la conservación del patrimonio natural y cultural; y en cuanto a la meta 11.a, se observa una débil vinculación con comunidades rurales debido a su limitada integración en la experiencia turística. Este trabajo aporta evidencia empírica sobre los desafíos para fortalecer la sostenibilidad en el turismo de naturaleza y sugiere nuevas líneas de investigación y acción para el sector. Las principales limitaciones del estudio radican en su alcance geográfico y en el número reducido de casos analizados.
Data Mart Design to Increase Transactional Flow of Debit and Credit Card in Peruvian Bodegas
(Science and Information Organization, 2025) Morales-Arevalo, Juan C.; Aquise-Gonzales, Erick M.; Carpio-Ore, William Y.; Mendoza-Sáenz, Emmanuel V.; Mazzarri-Rodriguez, Carlos J.; Remotti-Becerra, Erick E.; Medina-LaPlata, Edison H.; Luis F. Luque-Vega
The objective of this research is to design a Data Mart to identify tactical actions and increase the use of POS (points of sale) in the bodega business sector of Lima, Peru. A quantitative approach, using transaction history data, is applied using the Kimball methodology. This involves the ETL (Extract, Transform, Load) process to create a dimensional model and to develop a dashboard to visualize key indicators using Power BI. This solution is expected to improve the detection and analysis of transactional errors, categorized by geographic location and business sector while enhancing decision-making processes. This research improves the transactional flow and digital payment adoption in small businesses, fostering greater financial inclusion in the Peruvian market. Therefore, the methodology and tools to be applied in this research offer a framework as a model for similar contexts, especially in emerging markets, which will allow closing gaps in digital payment adoption and financial inclusion.
Design, Implementation, and Control of a Linear Electric Actuator for Educational Mechatronics
(MDPI, 2023-09) Nava-Pintor, Jesús A.; Carlos-Mancilla, Miriam A.; Guerrero-Osuna, Héctor A.; Luque-Vega, Luis F.; Carrasco-Navarro, Rocío; Castro-Tapia, Salvador; Mata-Romero, Marcela E.; González-Jiménez, Luis E.; Solís-Sánchez, Luis O.
Kinematics is a fundamental topic in engineering, robotics, mechatronics, and control systems and significantly resolves some of these fields’ most pressing issues. It is essential to assess the balance between a topic’s theoretical framework and its empirical validation to succeed in engineering. Educational tools have gained significant attention for their ability to enhance the learning experience by providing the hands-on experiences necessary to assess theoretical frameworks
and empirical validations. This paper presents a system incorporating state-of-the-art features, including a fuzzy controller enabling precise control of a linear actuator and a USB camera, to provide an interactive experience. The USB camera captures the position of the actuator, providing realtime visual feedback and allowing the students to validate their theoretical understanding through practical experiments. Precision, accuracy, resolution, and the implementation of the fuzzy controller are measured to evaluate the whole system’s performance. The design, implementation, and control of our educational electrical linear actuator for teaching kinematics concepts contribute to a practical educational tool and advance interactive learning approaches in the field.
Development and Evaluation of Solar Radiation Sensor Using Cost-Effective Light Sensors and Machine Learning Techniques
(MDPI, 2025-05) Nava-Pintor, Jesús A.; Alcalá-Rodríguez, Uriel E.; Guerrero-Osuna, Héctor A.; Mata-Romero, Marcela E.; Lopez-Neri, Emmanuel; García-Vázquez, Fabián; Solís-Sánchez, Luis O.; Carrasco-Navarro, Rocío; Luque-Vega, Luis F.
The accurate measurement of solar radiation is essential for applications in agriculture, renewable energy, and environmental monitoring. Traditional pyranometers provide high-precision readings but are often costly and inaccessible for large-scale deployment. This study explores the feasibility of using low-cost ambient light sensors combined with statistical and machine learning models based on linear, random forest, and support vector regressions to estimate solar irradiance. To achieve this, an Internet of Things-based system was developed, integrating the light sensors with cloud storage and processing capabilities. A dedicated solar radiation sensor (Davis 6450) served as a reference, and results were validated against meteorological API data. Experimental validation demonstrated a strong correlation between sensor-measured illuminance and solar irradiance using the random forest model, achieving a coefficient of determination (R2) of 0.9922, a root mean squared error (RMSE) of 44.46 W/m2, and a mean absolute error (MAE) of 27.12 W/m2. These results suggest that low-cost light sensors, when combined with data-driven models, offer a viable and scalable solution for solar radiation monitoring,
particularly in resource-limited regions.
Design and Implementation of a Robotic Arm for a MoCap System within Extended Educational Mechatronics Framework
(MDPI, 2023-09) Lopez-Neri, Emmanuel; Luque-Vega, Luis F.; González-Jiménez, Luis E.; Guerrero-Osuna, Héctor A.
Educational mechatronics aims to be the evolution of educational robotics so it can be identified as a part of the educational paradigm of the university, its academic spaces, infrastructure, and practical activities. The fundamental goal of this framework is to develop the knowledge and skills that the new industrial world, inspired by the latest technologies, necessitates. This work proposes the modular design of a robotic arm aligned with the extended educational mechatronics
conceptual framework by designing and implementing educational tools to develop the knowledge and skills required for Industry 4.0. The 3D-printed, low-cost robotic arm is designed to be used in a motion capture system for robotics applications to build kinematics concepts for a learning process. In particular, the instructional design to build the mechatronic concept of a robot workspace is carried out considering the three learning levels: concrete, representational, and abstract. The above demonstrates how the proposed pedagogical methodology can impact Industry 4.0 in the small- and medium-sized enterprises’ context.
A Low-Cost Wearable Device to Estimate Body Temperature Based on Wrist Temperature
(MDPI, 2024-03) Mata-Romero, Marcela E.; Simental-Martínez, Omar A.; Guerrero-Osuna, Héctor A.; Luque-Vega, Luis F.; Lopez-Neri, Emmanuel; Ornelas-Vargas, Gerardo; Castañeda-Miranda, Rodrigo; Martínez-Blanco, María R.; Nava-Pintor, Jesús A.; García-Vázquez, Fabián
The remote monitoring of vital signs and healthcare provision has become an urgent necessity due to the impact of the COVID-19 pandemic on the world. Blood oxygen level, heart rate, and body temperature data are crucial for managing the disease and ensuring timely medical care. This study proposes a low-cost wearable device employing non-contact sensors to monitor, process, and visualize critical variables, focusing on body temperature measurement as a key health
indicator. The wearable device developed offers a non-invasive and continuous method to gather wrist and forehead temperature data. However, since there is a discrepancy between wrist and actual forehead temperature, this study incorporates statistical methods and machine learning to estimate the core forehead temperature from the wrist. This research collects 2130 samples from 30 volunteers, and both the statistical least squares method and machine learning via linear regression are applied to analyze these data. It is observed that all models achieve a significant fit, but the third-degree polynomial model stands out in both approaches. It achieves an R2 value of 0.9769 in the statistical analysis and 0.9791 in machine learning.