Relational database models offer a pathway for the storage, standardization, and analysis of factors influencing national sports development. While existing research delves into the factors linked with sporting success, there remains an unexplored avenue for the design of databases that seamlessly integrate quantitative analyses of these factors. This study aims to design a relational database to store and analyse quantitative sport development data by employing information technology tools. The database design was carried out in three phases: (i) exploratory study for context analysis, identification, and delimitation of the data scope; (ii) data extraction from primary sources and cataloguing; (iii) database design to allow an integrated analysis of different dimensions and production of quantitative indicators. An entity-relationship diagram and an entity-relationship model were built to organize and store information relating to sports, organizations, people, investments, venues, facilities, materials, events, and sports results, enabling the sharing of data across tables and avoiding redundancies. This strategy demonstrated potential for future knowledge advancement by including the establishment of perpetual data updates through coding and web scraping. This, in turn, empowers the continuous evaluation and vigilance of organizational performance metrics and sports development policies, aligning seamlessly with the journal’s focus on cutting-edge methodologies in the realm of digital technology.

This study investigates the relationships among entrepreneurship, technical competency, and business performance, focusing on CEOs in the beauty service industry in the Busan area. A total of 215 survey responses were collected, with 213 valid responses selected for final analysis after excluding 2 unsuitable responses. The key findings of the study are as follows: First, entrepreneurship was found to partially influence technical competency. Second, technical competency was found to influence business performance. Third, entrepreneurship was found to partially influence business performance. Fourth, technical competency was found to partially mediate the relationship between entrepreneurship and business performance. Based on these results, the study systematically analyzes and explains the causal relationships among the entrepreneurship of CEOs in the beauty service industry, their technical competency, and business performance. It also seeks to provide useful reference materials for strengthening the innovation and competitiveness of CEOs in the beauty service industry and establishing a theoretical foundation for future research in related fields.

Innovation management and economic sustainability have become one of the business challenges to consolidate. given the above, the objective of the study is to determine the relationship between innovation and economic sustainability in small and medium-sized enterprises (SMEs) in Latin America. through an empirical study, 2660 SMEs were examined, 1729 small and 931 medium-sized, located in 13 Latin American countries. the data obtained by applying a survey were processed using a non-linear canonical correlation analysis (NLCCA). The findings identify functional and operational risks in SMEs that weaken innovative potential, in addition to technical-operational barriers—lack of knowledge and low investment that limit economic sustainability, whose importance transcends towards transformations of business models and effectiveness of resources that promote business sustainability. contributions are suggested for the management of public policies aimed at strengthening innovation and economic sustainability to project the emerging economies of Latin America.

This project analyzes the evolution of the manufacturing sector in Portugal from 2009 to 2021, focusing on the variations in the number of active companies across various subcategories, such as food, textiles, and metal product industries. The goal of this analysis is to understand the dynamics of growth and contraction within each sector, providing insights for companies to adjust their market and operational strategies. Key objectives include analyzing the overall evolution in the number of companies, identifying subcategories with notable changes, and providing a comprehensive analysis of observed trends and patterns. The study is based on data from PORDATA 2024, and the research employs temporal trend analysis, linear and quadratic regression, and the Pareto representation to identify patterns of growth and decline. By comparing annual data, the project uncovers periods of growth and decline, allowing for a deeper understanding of the sector’s dynamics. The findings also highlight variations in periods of economic crises and during the Covid-19 pandemic, and recommendations for action are presented to support businesses resilience and continuity. These results are valuable for companies within the manufacturing sectors analyzed and policy makers, guiding strategic decisions to navigate the complexities of the market dynamics and to ensuring long-term organizational sustainable success.