This study examines the spatial distribution of socioeconomic conditions in Colombia, using Moran's Index as a tool for spatial autocorrelation analysis. Key indicators related to education, health, infrastructure, access to basic services, employment, and housing conditions are addressed, allowing the identification of inequalities and structural barriers. The research reveals patterns of positive autocorrelation in several socioeconomic dimensions, suggesting a concentration of poverty and underdevelopment in certain geographic areas of the country. The results show that municipalities with more unfavorable conditions tend to cluster spatially, particularly in the northern, northwestern, western, eastern, and southern regions of the country, while the central areas exhibit better conditions. Permutation analyses are employed to validate the statistical significance of the findings, and LISA cluster maps highlight the regions with the highest concentration of poverty and social vulnerability. This work contributes to the literature on inequality and regional development in emerging economies, demonstrating that public policies should prioritize intervention in territories that exhibit significant spatial clustering of poverty. The methodology and findings provide a foundation for future studies on spatial correlation and economic planning in both local and international contexts.

This study delves into the dynamic landscape of pension funds in Colombia, examining both its current research status and practical implications. Understanding the state of pension systems is crucial for individuals' financial security and a country's overall economic stability, especially given factors such as an aging population and evolving socio-economic dynamics. By comprehensively analyzing scholarly publications on Colombian pension funds using the Scopus database, this research sheds light on key trends and contributors shaping policy formulation and financial planning. The analysis covers a period from 1987 to 2023, identifying 71 relevant articles through keyword searches and filters. Various metrics, including publication trends, citations, international collaboration, and authorship dynamics, were quantitatively assessed. The results reveal an annual growth rate of 5.37%, with research articles comprising 81.69%, review articles 7.04%, and other formats like books, book chapters, and conference papers making up 11.27% of the total documents. Notably, countries such as the UK, the USA, Spain, and Colombia emerge as key contributors to the literature. Among authors, Mesa-Lago, L., stands out as a significant figure, with one of the earliest publications on the topic. The findings underscore the growing importance of pension funds in Colombia, particularly in the context of fund performance research amid financial crises. The prevalence of international collaboration suggests a global interest in understanding and contributing to the development of Colombian pension systems. Furthermore, the study identifies research gaps, particularly in areas concerning the socio-economic impact of pension policies, providing a roadmap for future investigations. Policymakers, financial practitioners, and researchers can leverage these insights to inform strategic decision-making and address critical challenges in optimizing pension fund management in Colombia.

Telecommunications markets have a giant impact on countries’ economies. An example of this is the great potential offered by the internet service, which allows growth in various aspects such as productivity, education, health, and connectivity. A few companies dominate telecommunications markets, so there is a high market concentrations risk. In that sense, the state has to generate strong regulation in the sector. Models for measuring competition in telecommunications markets allow the state to monitor the concentration performance in these markets. The prediction of competition in the telecommunications market based on artificial intelligence techniques would allow the state to anticipate the necessary controls to regulate the market and avoid monopolies and oligopolies. This work’s added value and the main objective is to measure the current concentration level in the Colombian telecommunications market, this allows for competitive analysis in order to propose effective strategies and methodologies to improve competition in the future of Colombian telecommunications services operators. The main result obtained in the research is the existence of concentration in the Colombian telecommunications market.

The propagation of plant material in the arracacha crop is commonly done vegetatively through asexual seed, this activity has allowed its multiplication and conservation over time. The plant material available is of low quality, affecting the development and potential yield of the crop and therefore the producer’s income. The objective of the research was to comparatively analyze two technologies for the production of arracacha seed: local technology and Agrosavia technology. The information for the local technology was obtained from surveys applied to farmers and the selection was made using the deterministic sampling technique, and for the Agrosavia technology through the recording of data and production costs in research lots at commercial scale. Descriptive statistics and calculation of economic return indicators were applied for the two situations. The results show that the use of quality seed allows obtaining higher seed production (251,559 unit ha^-1) and tuberous roots (25,875 kg ha^-1), being superior to local technology by 14% and 28% respectively; thus, the arracacha producer acquires greater economic efficiency by obtaining lower unit cost per kilo produced and better net income with a marginal rate of return of 316.45. The results achieved are useful for farmers, companies and entities that wish to produce quality seed and support the arracacha production system in Colombia.

The xanthorrhiza species of the genus Arracacia belongs to the Apiaceae family and is known for its ability to generate tuberous reservoir roots that are harvested annually and marketed fresh in South American countries such as Colombia, Brazil, Venezuela, Peru, Bolivia and Ecuador. In Colombia, arracacha is planted mainly in 15 departments and the regional cultivars are differentiated by the color of the leaves, petiole and tuberous root, the best known being amarilla común or paliverde, yema de huevo, and cartagenera. There are studies that have characterized regional materials by applying a limited number of descriptors, but they do not allow knowing the morphology and phenotypic differentiation of each one; therefore, their definition and characterization constitute a support in breeding programs that allow the efficient use of the genetic potential and increase the knowledge about the diversity of cultivars. Phenotypic characterization and description of three cultivars was performed during two production cycles (2016 and 2018) in two phases (vegetative and productive) applying 74 morphological variables (42 qualitative and 32 quantitative) organized in seven groups of variables: plant, leaf, leaflet, petiole, propagule, stock and tuberous root. A factorial analysis for mixed data (FAMD) was performed, which incorporated a multivariate analysis with all variables and identified 11 discriminant variables, 8 qualitative and 3 quantitative, which can be used in processes of characterization of arracacha materials. A morphological description of each cultivar was made, which means that this is the first complete characterization study of regional arracacha materials in Colombia.

The growth of mobile Internet has facilitated access to information by minimizing geographical barriers. For this reason, this paper forecasts the number of users, incomes, and traffic for operators with the most significant penetration in the mobile internet market in Colombia to analyze their market growth. For the forecast, the convolutional neural network (CNN) technique is used, combined with the recurrent neural network (RNN), long short-term memory network (LSTM), and gated recurrent unit (GRU) techniques. The CNN training data corresponds to the last twelve years. The results currently show a high concentration in the market since a company has a large part of the market; however, the forecasts show a decrease in its users and revenues and the growth of part of the competition. It is also concluded that the technique with the most precision in the forecasts is CNN-GRU.