Facultad de Ciencias Económicas y Empresariales - CampCM
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Item type:Publication, Informe de producción científica 2019(Universidad Panamericana, 2019); ; ; - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Research ecosystem 2025(Universidad Panamericana, 2025); ; Dear campus members, It is with great satisfaction that we present our Research Ecosystem 2025, a publication that reflects the sustained growth and strategic maturation of research at Universidad Panamericana. This edition builds on an increasingly comprehensive vision of university research, one in which technology transfer and innovation, institutional funding for research, and international rankings positioning affirm themselves as complementary pillars of our scientific activity. Our scientific production maintains its commitment to quality, with more than 50% of our indexed publications appearing in high-impact Q1 and Q2 journals. This year’s report also introduces, for the first time, a dedicated section on copyright and industrial models alongside patents, reflecting the growing diversity and maturity of our intellectual property portfolio, now spanning areas as varied as aeronautics, semiconductor technology, healthcare devices, and sustainable materials. © Universidad Panamericana. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, The Sustainable Industrial Site of the Future Based on Energy Efficiency, Renewable Energy, Artificial Intelligence, and Energy PolicyThe world’s high emissions of carbon dioxide are the primary cause of climate change and its harmful consequences, such as floods, storms, and droughts. According to the Intergovernmental Panel on Climate Change, human-induced warming reached approximately 1 °C above preindustrial levels in 2017, increasing at 0.2 °C per decade. The industrial sector contributes greatly to this global warming, as it is among the largest energy consumers. Indeed, industrial processes require a lot of energy, for example, for cooling, venting, pumping, producing steam, and hot water. This chapter focuses on industrial sites and aims to find a global solution to accelerate their transition toward sustainability. The study defines a clear and robust framework to obtain a sustainable industrial site and to keep it sustainable. Technologies (both well-proven technologies and new technologies) and policies are examples of tools used during the research. The method used is also supported by the current state-of-the-art on carbon emissions reduction and energy savings. The framework is based on four levers: energy efficiency, artificial intelligence, renewable energy, and energy policy and management. This framework can be used by any organization, stakeholders, and policymakers. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Informe de producción científica 2018(Universidad Panamericana, 2018); ; ; - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Community style leadership's effects on organisational performance: analysis across industries and firm sizes in MexicoScholars and practitioners, across fields of study, have spent decades analysing and documenting the complexities of different styles of leadership encountered throughout industries around the world. With that, a series of constructs and respective definitions have been developed to better understand the implications of taking on certain leadership styles. Mintzberg’s (2009) communityship concept is no exception; in fact, it has motivated the development of this empirical study aimed to uncover the characteristics of a community style leadership in organisations operating in Mexico. This study contributes to the understanding of the intricacies of a community style leadership and its potential impacts on collaborator satisfaction and commitment towards the firm, as well as on organisational performance The authors © Inderscience Publishers © International Journal of Management Concepts and Philosophy. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Estimating Conditional Labor Productivity Penalties from Non-Communicable Diseases Using Double Machine Learning: Evidence from Mexican Household Data(MDPI AG, 2026); Non-communicable diseases (NCDs) represent a growing challenge for developing countries, as they are among the leading causes of morbidity and mortality within the working-age population. Beyond their effects on health outcomes, NCDs are associated with reductions in labor productivity, which may influence long-term development dynamics through human capital. This study estimates the conditional labor productivity penalty associated with Non-Communicable Diseases (NCDs) among employed workers in Mexico using an observational high-dimensional framework. By addressing high-dimensional confounding under the Conditional Independence Assumption (CIA), the analysis isolates the relationship between NCD status and hourly labor earnings. Using microdata from the Mexican National Survey of Household Income and Expenditure, labor productivity is defined as the ratio of labor income to hours worked. To obtain robust causal estimates, a Double Machine Learning (DML) framework is implemented, integrating regularized regression and machine learning algorithms to control for high-dimensional confounding factors. These covariates include socioeconomic, demographic, and health-related variables, allowing for flexible adjustment of observable heterogeneity across individuals. The empirical findings demonstrate a statistically significant conditional negative penalty of −11.44% (p = 1.03 × 10−11, 95% CI: [−14.59, −8.40]) on hourly labor earnings under the cross-fitted DML specification using XGBoost and Random Forest. To resolve an observational measurement artifact where chronic individuals report artificially inflated hourly wages due to severe hours contraction, a presenteeism adjustment factor ((Formula presented.)) was calibrated. Incorporating this presenteeism correction, the aggregate national economic burden among the employed population is estimated at approximately 496.82 billion pesos annually. The findings suggest that NCDs constitute a relevant constraint on labor productivity at the microeconomic level. The study highlights the importance of prevention-oriented health strategies, workplace health promotion, and early disease management. From a methodological perspective, the results illustrate the usefulness of Double Machine Learning for purging high-dimensional confounding in cross-sectional survey data, providing robust conditional empirical benchmarks for public health policy. © 2026 by the authors. © MPDI © Applied Sciences. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Informe de producción científica 2020(Universidad Panamericana, 2020); ; - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Financial education and internal governance on short food supply chains: evidence from vulnerable rural communities in Latin America(Springer Science and Business Media LLC, 2026); ; - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Informe de producción científica 2022(Universidad Panamericana, 2022); ; - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Informe de producción científica 2021(Universidad Panamericana, 2021); ;