Sistema Regional de Información
en línea para Revistas Científicas de América Latina,
el Caribe, España y Portugal

Elflein, A. M. ([1918] 2020). Por los pueblos serranos. Introducción, selección y notas Ana Negri. (Serie: Colección relato licenciado Vidriera, núm. 84). México: Universidad Nacional Autónoma de México. 90 pp., ISBN 978-607-30-3455-5

Gómez Rojas, J. C. (Coord.: 2019). Arte, Mito y Territorio. México: Ediciones del Lirio 134. p. ISBN: 978-607-8569-96-0

The calculation of costs is a necessary tool for the identification of unprofitable services and activities that do not add value. The objective of the research is to propose a procedure for calculating the costs of the services of the Center for Molecular Immunology (CIM) through ABC costing. The methods were used: analysis, bibliographic study, synthesis, economic statistics and comparison of indicators. Together with: the logical history, system approach, documentation consultation and expert criteria. They were combined with the techniques: group dynamics, experiences, interviews, productivity assets and flowchart. It is recommended to include the cost information obtained in the CIM Board of Directors and to update the cost sheets annually. Its application allows a complete distribution of the expenses consumed by the activities towards the services. The application of the procedure allows expanding the scope of economic analysis for better decision making.

At present, companies face new economic models and to be dedicated a lot of time and resources to get, process, apply, and project information. If they do not collect the appropriate data, the information generated will not be accurate, the results will likely be wrong, and any decision made will not be the most appropriate. Business Intelligence (BI) and Business Analytics (BA), used properly, can present competitive advantages, allowing organizations to know their current status and forecast future market behaviour, carrying out proactive actions based on predictive and prescriptive analysis. In this work, it is proposed to assist small and medium businesses (PyMEs) by integrating BI and BA into their information systems. The case of a local transport PyME is presented where the benefits of applying free software tools, such as PowerBI Desktop, Orange, KNime, and Knowage, were analysed and evidenced.

We build a global bankruptcy prediction model using a support vector machine trained only on firms' endogenous information in the form of financial ratios. The model is tested not only on entirely random unseen data but on samples taken from specific global regions and industries to test for prediction bias, achieving satisfactory prediction performance in all cases. While support vector machines are not easily interpretable, we explore variable importance and find it consistent with economic intuition.  

The goal of this paper is to analyze the effects of the increase in international prices on the reallocation of resources and the economic growth of a small and open economy. To do this, two adjustment mechanisms are introduced in a two-sector economic growth model, one for labor and the other for the debt-capital ratio. We show that the direction of migration between wages is completely determined by the proportion of total labor employed in the sector of natural resources; and that the external loan decisions, at any instant of time, is a percentage of the net debt stock, the speed of which is the proportional discrepancy of the adjustment of external capital and the expected marginal product and the world interest rate, thereby we find a growth path (within the stable manifold) that allows the optimal growth path.

We introduce a binary recursive procedure to extend the standard solution to solve 2-player cooperative games. This procedure uses adjusted games and the binary total partitions of the set of players. We show that the resulting extension is a solution concept for n-player cooperative games which satisfies a recursive formula and we prove that this formula is satisfied by a solution concept if and only if the solution concept is the Shapley value.

Businesses across Latin America are working towards economic recovery. Among the different strategies in place, organizations are transforming to data-driven enterprises to use analytics to achieve their goals in a variety of business processes. This Consumer-Packaged Goods (CPG) industry study case shows how business intelligence can help to reach their goals, applying business analytics and machine learning to forecast the demand. The study focuses in one product in one presentation, which has more than thirty flavors available sold by 275 stores across country. The study case discusses how enterprise current use of traditional forecasting methods such as autoregression and moving average are being used, the results they are getting and more important, what limitations and challenges they are facing.  The current situation is compared against the proposed machine learning based approach leveraging sales data from two whole years, data visualization was transformed from static and manual procedures into an automated continuous delivery approach with insights available near real time. Also, it is discussed why data granularity played an important factor to create the proposed forecasting models and how machine learning capabilities provide a better and more accurate results. Lastly, it is discussed the implementation of data-driven philosophy explaining what components were required, how they interact among each other, data gathering alternatives, what types of transformation were required, and what technologies were selected. This comprehensive study case can help other enterprises looking to start their quest to become data-driven organization relaying on business analytics to make better decisions during their efforts for economic recovery.