Conference Agenda

ABSTRACT: This study analyzes business perceptions of competitiveness in Argentina using a quantitative approach. Based on a national survey conducted in 2024 of 400 firms from different sectors and of varying sizes, 84 variables were collected and grouped into six key factors: institutional, labor, educational, financial, governance, and innovation-related. The overall objective is to examine the influence of these factors on the competitiveness of the industrial sector compared with other economic activities in the country, identifying their interactions and impact. Multiple correspondence analysis and hierarchical clustering were applied. The estimated results reveal strong sectoral inertia in opinions—favorable, neutral, or unfavorable—regarding Argentina’s current competitiveness conditions. The variables most strongly associated with favorable perceptions were the quality of university education, digital skills, internship programs, and the adoption of disruptive business models. By providing uncommon micro-level evidence for a middle-income economy, the study refines the emerging literature on competitiveness ecosystems and offers a baseline against which forthcoming reforms can be monitored. Policy recommendations emphasize a dual strategy: sustained investment in human capital—especially secondary education and digital capabilities—and macro-financial stabilization.

This study analyzes the incorporation of digital tools in administrative management and their influence on the optimization of administrative processes in a company dedicated to the manufacturing of structural metal products, located in the district of Villa El Salvador (Lima, Peru), 2025. The research adopted a quantitative approach with a non-experimental explanatory design. The study population consisted of 50 employees, and data were collected through a survey using two structured questionnaires. Instrument validity was confirmed by expert judgment, and reliability was verified using Cronbach’s alpha (digital tools α = 0.73; administrative process α = 0.89). Ordinal logistic regression was applied for hypothesis testing due to the non-normal distribution of the data. The results revealed a significant influence of digital tools on the administrative process, with a Nagelkerke coefficient of 0.34. At the dimensional level, the influence was observed in planning (0.37), organization (0.56), management (0.55), and control (0.27). The findings indicate that digital tools exert a moderate yet significant impact on administrative optimization, highlighting the need to strengthen digital planning and control mechanisms to improve organizational efficiency and decision-making processes.

The purpose of this article was to evaluate equipment availability before and after the implementation of Total Productive Maintenance (TPM) at Cantol. The identified problem was low equipment availability, caused by mechanical and electronic failures and prolonged setup times, resulting in significant operational downtime losses. Historical availability records from the pre- and post-TPM implementation phases were used for the analysis, considering the company's implemented pillars, such as preventive maintenance, autonomous maintenance, and staff training. During the pre-implementation phase, average equipment availability was 55% for the transfer machine, 55% for the pear set assembly machine, and 53% for the vibratory machine. In the post-implementation phase, these values increased to 70%, 75%, and 68%, respectively. This increase demonstrates the effectiveness of TPM by significantly contributing to the reduction of unplanned downtime and the optimization of operating time, reaffirming its viability and applicability in a peruvian metalworking company.

The process for obtaining construction permits in the Central District of Honduras is characterized by institutional fragmentation, long response times, and high administrative costs, placing the municipality below regional performance benchmarks. This study analyzes the structural causes of inefficiency and proposes a framework for process optimization based on administrative modernization. A mixed-methods design was applied, combining document review, comparative analysis using World Bank indicators (Doing Business, 2020), semi-structured interviews with public officials, and surveys of system users. The findings reveal duplication of requirements, lack of technological interoperability, absence of process traceability, and low document standardization, which result in inefficiency, increased transaction costs, and operational discretion. Based on this evidence, a digital one-stop system is proposed, supported by principles of process reengineering, results-based public management, and inter-agency governance. This article presents the theoretical basis, diagnostic results, and methodology that support this proposal.

This study examines the structural determinants of tax revenue in Guatemala, El Salvador, and Honduras over the period 1991–2023. Using a balanced panel dataset and a fixed-effects model with Driscoll–Kraay robust standard errors, the analysis evaluates the role of demographic conditions, labor market performance, and trade openness in explaining variations in tax revenue as a percentage of GDP. The empirical strategy incorporates macroeconomic controls and applies alternative model specifications, including a global model and a parsimonious specification, to assess the robustness of results. The findings indicate that population size and trade openness exert a positive and statistically significant effect on tax revenue, while unemployment is associated with a negative impact. In contrast, short-run economic growth, inflation, and gross capital formation do not display consistent significance across specifications. These results suggest that tax performance in small and open economies is driven primarily by structural factors rather than short-term cyclical fluctuations. The study contributes to the empirical literature on fiscal performance in developing economies by providing region-specific evidence for the Northern Triangle of Central America and offers relevant insights for the design of tax policies aimed at strengthening revenue capacity through structural and labor market-oriented reforms.

Abstract- This systematic literature review aims to analyze ethical practices related to manipulation and social responsibility in design in order to identify pedagogical approaches that foster more conscious, empathetic, and socially responsible practice. The methodology used the PIO model, focused on undergraduate and graduate graphic design students, and was based on a corpus of 20 academic sources indexed in Scopus and Web of Science since 2021. The results indicate that although students develop a critical attitude and a high level of ethical awareness, they face a significant gap between awareness and practical action, since in commercial dilemmas they prioritize client needs over ethically sound decisions. Therefore, the review emphasizes the need to renew the curriculum through active methodologies such as reflective pedagogy, values-based education, and challenge-based learning, which are essential for training designers capable of questioning profit-driven logic and avoiding deceptive practices.

The present study aimed to evaluate the association between attitudes toward learning and academic goals through a structural equation modeling (SEM) approach in students from a public university in Peru (2025). The research adopted an observational, prospective, cross-sectional, and analytical design, with a sample of 442 participants. Two instruments were employed: a six-item Attitudes Toward Learning Scale validated using the Partial Least Squares (PLS) method, and a 20-item Academic Goals Scale validated through Confirmatory Factor Analysis (CFA). Data analysis was conducted using structural equation modeling. In the first stage, the measurement model was validated; subsequently, the structural model was estimated using Jamovi. The results indicated that attitudes toward learning were significantly associated with academic goals (β = 0.75), specifically with learning goals (β = 0.68) and performance goals (β = 0.51), while showing an inverse relationship with social validation goals (β = −0.36). Goodness-of-fit indices supported an adequate model specification (CFI and TLI > 0.90; RMSEA < 0.06). In conclusion, a positive attitude toward learning is positively related to both academic and performance goals and negatively related to social validation goals. These findings suggest that students with strong learning-oriented attitudes rely less on external approval.