Conference Agenda

In medical centers authorized by the Ministry of Transport and Communications (MTC) for driver's licenses (Trujillo, La Libertad–2023), an evaluation was conducted to determine if Business Intelligence (BI), conceived as a socio-technical capability, is associated with Decision Making. A quantitative, cross-sectional, and correlational study was developed, working with a census (n=37) of establishments. Likert questionnaires were applied (BI: 9 items; Decision Making: 20 items), and non-parametric associations were estimated using bootstrap support. The overall relationship was very strong (ρ=0.858; p=1.16e−11; 95% CI [0.711, 0.941]); by dimension, D1–V2=0.726, D2–V2=0.652, and D3–V2=0.740, with robustness verified via τ-b=0.729 and leave-one-out sensitivity. The central contribution is to make the BI→TD link measurable, replicable and traceable, connecting specific capabilities with facets of the decision-making process in a regulated service of high social responsibility.

This study analyzes the impact of investment in information and communication technologies (ICTs) on Ecuador's economic growth, considering the role of complementary factors such as investment in education and research and development (R&D). A quantitative, non-experimental, and explanatory approach is adopted, using annual macroeconomic data and a multiple linear regression model estimated using ordinary least squares. The results show that ICT investment has a positive and statistically significant effect on Gross Domestic Product (GDP) growth, confirming its role as a relevant determinant of the country's economic performance. In contrast, investment in education and R&D does not show significant effects in the short term, suggesting the presence of time lags and structural limitations typical of developing economies. Econometric analyses indicate an adequate model fit and the absence of severe multicollinearity problems, although moderate heteroscedasticity is detected, corrected using robust standard errors.

University accreditation has become a strategic process for quality assurance in Higher Education Institutions, characterized by increasing regulatory, organizational, and decision-making complexity. In the Ecuadorian context, external evaluation models require cross-institutional management based on evidence and interdepartmental coordination, exposing the limitations of fragmented management approaches. In response to this scenario, the objective of this study is to propose a digital collaborative management model supported by artificial intelligence to enhance operational efficiency, information traceability, and institutional coordination in university accreditation projects.

The study adopts a qualitative, applied, and propositional approach, grounded in documentary analysis of specialized scientific literature, a review of the quality assurance regulatory framework, and a conceptual modeling process.

As a result, a cyclical architecture structured around five interrelated components is proposed: institutional input and project governance, intelligent core, collaborative platform, institutional output, and impact evaluation. The discussion shows that the main contribution of the model lies in its systemic and integrative approach, which goes beyond instrumental digitalization. It is concluded that the model provides a relevant conceptual framework to guide the management of university accreditation projects and opens future research avenues focused on its implementation and empirical validation.

This study analyzes the export ecosystem of micro, small, and medium-sized enterprises (MSMEs) producing coffee and cocoa in Honduras and proposes the conceptual design of a digital market intelligence tool aimed at strengthening their competitiveness. Although they represent 99% of the country's productive units and generate nearly 70% of employment, these enterprises face significant limitations in accessing strategic information on international markets. Using a mixed approach combining surveys, semi-structured interviews, and document review, the research identifies structural barriers related to institutional fragmentation, low digitization, and a lack of up-to-date data. The expected outcome is a conceptual model for a centralized and accessible digital platform that provides information on prices, technical requirements, and consumer trends to improve decision making and export planning. The study contributes to the digital transformation and internationalization of Honduran MSMEs in the coffee and cocoa sectors.

This article analyzes the application of information technology outsourcing in China, South Korea, and India during the period 2019–2025. In a context marked by accelerated digital transformation, outsourcing has become a key strategy to optimize costs, strengthen business management, and improve operational efficiency in the logistics, manufacturing, and retail sectors. Through a systematic literature review and the PRISMA methodology, this study examines how technological solutions—such as automation, artificial intelligence, cybersecurity, cloud platforms, and software development—enhance productivity and competitiveness in Asian organizations. The findings indicate that technological outsourcing not only supports innovation and cost reduction but also contributes to strengthening digital capabilities and business resilience across the region.

The security of government data centers is critical to protect sensitive information and ensure the continuity of public services in the face of growing cyber threats. This study identifies, through systematic review using PICO and PRISMA methodologies, the factors that influence the security of these infrastructures, analyzing 30 scientific studies (2020-2025) from indexed databases. The results reveal that malware, ransomware, phishing, and DDoS attacks exploit vulnerabilities such as poor access controls and inadequate configurations. Budget constraints and shortage of trained personnel hinder the implementation of security measures. Emerging technologies such as cloud security, artificial intelligence, machine learning, edge computing, blockchain, and Zero Trust offer promising solutions, although their adoption faces organizational and financial barriers. The geographical concentration of studies in Asia and Europe limits generalization to Latin America. It is concluded that strengthening security requires prioritizing basic controls, investing in continuous training, and adopting hybrid architectures under robust public policies.

Requirement’s engineering is a critical phase in the software life cycle, yet many projects still fail due to ambiguous, incomplete or weakly managed requirements. This systematic literature review analyses how the specification and management of software requirements influence the quality of information systems. The study compares formal and informal practices across different project contexts and identifies the metrics, attributes and standards used to assess their impact on reliability, maintainability, usability, efficiency and security/explainability. The research question was structured using the PICO framework and the search strategy followed PRISMA-S guidelines. Searches were executed in Scopus, Web of Science and EBSCO for the period 2020–2025, applying predefined inclusion and exclusion criteria. Out of 1,083 records, 38 primary studies were selected for detailed analysis. The results show that projects adopting explicit requirements engineering practices—such as structured templates, traceability, formal reviews and systematic change management—report fewer post-release defects, lower rework effort and higher project success than those relying on minimal or informal documentation. Non-functional requirements, particularly reliability, performance, security, usability and explainability, emerge as key drivers of architecture and long-term quality. Most studies employ at least five complementary indicators combining product, process and user-oriented measures, and recent works incorporate AI-based techniques (NLP, ensemble learning, LLMs) to support classification and quality assurance of requirements. The review concludes with practical guidelines for strengthening requirements engineering in both traditional and agile development settings.