https://dspace.univ-ouargla.dz/jspui/handle/123456789/40882 Sun, 06 Sep 2026 21:29:41 GMT 2026-09-06T21:29:41Z https://dspace.univ-ouargla.dz/jspui/handle/123456789/40986 Titre: Organizational Change and its Relationship to the Performance of the Algerian Economic Institution Auteur(s): زهية عزيون; لطفي دنبري Résumé: This study examines the relationship between organizational change and the performance of Algerian economic institutions through a case study of the production branches of the National Company for Public Works Equipment (ENMTP). The study adopts a descriptiveanalytical approach and relies on a questionnaire administered to a random sample of 164 managers out of a population of 210. Data were analyzed using SPSS version 26, applying Pearson correlation, simple and multiple linear regression, and ANOVA. The results reveal statistically significant relationships between organizational change dimensions and performance, highlighting the importance of adopting an integrated and balanced approach to managing organizational change to enhance performance and sustainability Description: Journal of Quantitative Economics Studies Mon, 01 Jun 2026 00:00:00 GMT https://dspace.univ-ouargla.dz/jspui/handle/123456789/40986 2026-06-01T00:00:00Z https://dspace.univ-ouargla.dz/jspui/handle/123456789/40985 Titre: The Impact of Digital Transformation on Enhancing Operational Efficiency at the Skikda Port Institution Auteur(s): فاطيمة بوادو; شيماء بكوش Résumé: This study aims to analyze the impact of digital transformation across its five dimensions (infrastructure, systems, training, strategic leadership, and service quality) on operational efficiency at the Port of Skikda. Using a descriptive-analytical approach, data was collected via a questionnaire from 66 employees and analyzed using SPSSv27. The results concluded a statistically significant positive impact of digital transformation on enhancing operational efficiency, with "strategic leadership" emerging as the most influential dimension. Digitalization contributed to reducing time and resource waste while improving logistical coordination, despite challenges from remaining manual procedures. The study recommended accelerating full automation of administrative processes to enhance the port's internationalcompetitiveness Description: Journal of Quantitative Economics Studies Mon, 01 Jun 2026 00:00:00 GMT https://dspace.univ-ouargla.dz/jspui/handle/123456789/40985 2026-06-01T00:00:00Z https://dspace.univ-ouargla.dz/jspui/handle/123456789/40983 Titre: Analyzing the Impact of Information System on Decision-Making Processes Auteur(s): فاطمة زهراء بن زعمية Résumé: The study aims to identify information systems and their impact on decision-making at Algeria telecom in Ain Temouchent, the study was divided in two variables: an independent variable and a dependent variable, the dimensions of information systems is(technical infrastructure, information quality, speed of information flow), and the dependent variable decision-making, we used the descriptive-analytical method, employing a questionnaire as a tool to collect data and information, from a simple random sample of executives and decision-makers within the organization, and we conducted a statistical analysis using a statistical software program SPSS. The study concluded that there is a positive relationship between information systems and decision-making at Algeria telecom in Ain Temouchent, we found a statistically significant impact of information systems in all their dimensions, on decision-making within the organization, this confirms that the information systems within the organization are efficient and of high quality, which positively reflects on the accuracy the organization interests and contributing to the improvement of its decision-making and administrative processes Description: Journal of Quantitative Economics Studies Mon, 01 Jun 2026 00:00:00 GMT https://dspace.univ-ouargla.dz/jspui/handle/123456789/40983 2026-06-01T00:00:00Z https://dspace.univ-ouargla.dz/jspui/handle/123456789/40981 Titre: Testing the Ability of Deep Learning Models LSTM and Transformers to Predict the Price Behavior of the S&P 500 Index Auteur(s): محمد يزيد صالحي; أسماء كسري Résumé: This study aims to test the ability of deep learning models (LSTM and Transformers) to predict the price behavior of the S&P 500 index, with a focus on comparing the performance of both models under different market scenarios. The study adopted a quantitative experimental approach, using daily data of the S&P 500 index from January 2015 to December 2023, with a total of 2,264 trading days. Two main models were constructed: a three-layer LSTM model and a Transformer model customized for financial data. The performance of both models was evaluated using four main metrics: Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Directional Accuracy. Paired samples t-test and Wilcoxon test were used to verify the statistical significance of differences. The results showed a clear superiority of the LSTM model over the Transformer in all performance metrics. The LSTM achieved an RMSE of 79.86 compared to 145.19 for the Transformer, and recorded a directional accuracy of 51.22% compared to 48.17% for the Transformer. Statistical tests showed significant differences between the performance of the two models at the 0.05 significance level Description: Journal of Quantitative Economics Studies Mon, 01 Jun 2026 00:00:00 GMT https://dspace.univ-ouargla.dz/jspui/handle/123456789/40981 2026-06-01T00:00:00Z