Eva in the Time of Covid in Ecuadorian Communication and Information Companies

This article uses economic value added (EVA) to determine the performance of Ecuadorian communication and information companies in the year 2020. Being a COVID-19 pandemic year, the sector's performance has not been as expected. It has been studied which variables are influential in the EVA. The results determined that earnings before interest and taxes (BAIT) and net operating profit after tax (NOPAI) had a positive impact on EVA, while weighted average cost of capital (WACC) and return on invested capital (ROIC) were not significant for EVA performance. Company management should design actions that contribute to wealth generation taking into account the level of post-pandemic risk.

EVa in the time of covid in Ecuadorian communication and information companies

This article uses economic value added (EVA) to determine the performance of Ecuadorian communication and information companies in the year 2020. Being a COVID-19 pandemic year, the sector's performance has not been as expected. It has been studied which variables are influential in the EVA. The results determined that earnings before interest and taxes (BAIT) and net operating profit after tax (NOPAT) had a positive impact on EVA, while weighted average cost of capital (WACC) and return on invested capital (ROIC) were not significant for EVA performance. Company management should design actions that contribute to wealth generation taking into account the level of post-pandemic risk. © 2022 IEEE Computer Society. All rights reserved.

Augmented Data Deep Learning Model to Prediction of S&P500 Index: A Case Study Including Data of COVID-19 Period

The forecasting of the financial markets, as the SP500 Index, is an arduous task because their data is highly noisy, non-linear, complex, dynamic, non-parametric, and chaotic. In this context, this study proposes a two-phase method to predict the values of the Index: In the first phase, the Index data are preprocessed and used as input to train a Deep Learning Neural Network (DNN) using augmented data and scaling techniques;in the second phase, the trained model and a sliding window technique are used to predict the values in time, step by step. The data set to train and validate the model include the atypical period of COVID-19. According to the results obtained, the model has good performance. Thus, the research offers a new experience in data analysis and can help economic policymakers and institutional investors with accurate forecasts of the stock market. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

SYSTEMATIC REVIEW ON UNIVERSITY REMOTE EDUCATION IN LATIN-AMERICA IN PANDEMIC

Due to the Covid-19 pandemic, the world has undergone changes, and the education sector has had to adapt to a new situation (the non-presence of its community) in which strategies have been developed and strengthened in order to achieve the goals set by each of the institutions. It is in this context that remote education has been presented as a solution. The objective was to systematize the experiences and evidence on the practices of remote university education in Latin America during the Covid-19 pandemic. Thirteen scientific articles in Spanish, Portuguese and English were analyzed from: Scopus, Ebsco, Proquest, Scielo and Dialnet. These were filtered using inclusion and exclusion criteria, with articles published between 2020 and 2021. Among the conclusions, it was found that the experiences in Latin America have been conditioned to the logistic and training characteristics of the educational community.

Evaluation of the survival of ecuatorian communication companies through efficiency

The impact of COVID-19 is a factor that has an extraordinary influence on all companies. Ecuadorian social communication companies do not escape from this reality. This work seeks to determine the technical efficiency and survival of companies in the Ecuadorian media sector, for the years 2015 to 2109, and if the state of survivals affects technical efficiency. Envelope data analysis (DEA) is used in this work to measure efficiency and Tobit regression. A balanced panel of 110 companies from the media sector has been used. The results show that companies in the TV Production and Promotion and Advertising sectors have been more efficient in the years of studies. On the other hand, the level of survival of companies is significant to explain the technical efficiency of companies in the communication sector. © 2021, Associacao Iberica de Sistemas e Tecnologias de Informacao. All rights reserved.