The application of computer science in management and economics is a rapidly growing field that combines the analytical and technological capabilities of computer science with the strategic and operational needs of management and economics. The main aim of this research paper is to analyze the main academic contributors, sources, and international collaborations from 2014 to 2022 in computer science in the areas of management and economics, as well as to analyze the main subtopics developed over time. Bibliometric techniques were used to carry out the literature review, which allows an objective analysis of the academic literature through quantitative indicators. The results reveal a significant shift towards data-driven decision making in management, with artificial intelligence and machine learning improving predictive analytics, operational efficiency, and economic forecasting and modeling, highlighting the essential role of digital transformation in these disciplines, with significant implications for researchers, practitioners and decision-makers. It concludes that all stakeholders should work to develop a more informed and innovative approach to maximize the exploitation of the potential offered by computational sciences in different contexts. This includes the integration of advanced computational tools to improve decision making and operational efficiency, or the exploitation of computational models for more effective forecasting and policy decision making, as well as the continuous analysis of emerging areas in this field, being aware of the ethical, privacy and security challenges presented by these technologies, in order to ensure a responsible and equitable application

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