Soft skills are increasingly recognised as decisive factors for employability and career advancement in the global labour market. This study examines their role in the professional trajectories of university graduates in Ecuador, analysing both the competencies supplied by higher education and the structural demand of the labour market. Based on institutional surveys applied to 3358 graduates from the Salesian Polytechnic University (Cuenca campus), the results show that more than $90\%$ of graduates remain in operational positions, while only $5\%$ reach tactical or managerial levels. To address this phenomenon, five key soft skills—leadership, effective communication, teamwork, problem-solving, and adaptability—were evaluated through a structured questionnaire using Likert-type items. The findings reveal a persistent concentration of professionals in lower organisational levels and heterogeneous perceptions of the applicability of academic training. These outcomes highlight both individual skill gaps and structural limitations of the Ecuadorian labour market, such as the scarcity of managerial positions and the prevalence of family-based business structures. In response, the study proposes a sector-based curricular improvement strategy that systematically incorporates soft skills into university programmes, differentiated by economic sectors such as education, health, commerce, public administration, industry, and primary activities. Grounded in empirical evidence, this approach provides a practical framework to enhance graduates’ career progression, foster more equitable professional mobility, and strengthen the relevance of higher education. The model can be replicated across other Latin American universities facing similar challenges, while also aligning with international standards for competency-based education.

This study develops an integrated methodological approach for interpreting used oil analysis results in diesel engines, focusing on optimizing maintenance strategies. The methodology combines a literature review with a quantitative assessment of 156 lubricant analysis reports from a fleet of diesel waste collection trucks operating in Cuenca, Ecuador, a high-altitude city. The framework includes critical limits for key lubricant parameters, correlation analysis, and Principal Component Analysis (PCA) to identify dominant degradation mechanisms. The Binary Segmentation (BS) algorithm is also used for Change-Point Detection. The findings indicate four primary degradation pathways: thermal–chemical degradation influenced by sulfur, oxidation, and soot; metallic wear and base depletion, involving iron, chromium, and copper; external contamination linked to silica and copper; and viscosity alteration due to lubricant aging. Significant degradation shifts were identified at approximately 346 and 444 service hours, suggesting critical points for condition-based maintenance interventions. This study highlights the effectiveness of multivariate statistical tools in enhancing the interpretation of used oil analysis and optimizing predictive maintenance strategies. The integration of Change-Point Detection and multivariate analysis provides a robust framework for defining oil change intervals based on lubricant condition rather than fixed time- or mileage-based criteria. This approach offers practical benefits for fleet operations, enabling the reduction in operational costs, enhancing engine reliability, and minimizing the environmental impact of unnecessary lubricant changes.

In a global context where soft skills have become decisive for employability and professional advancement, this study analyses its role in the career paths of university graduates in Ecuador. Based on an analysis of 1,884 graduates from the Salesian Polytechnic University (Cuenca campus), it was found that more than 90% of them work at operational levels within organisations. In comparison, only 5% hold tactical or managerial positions. This finding highlights a disconnect between university education and the skills required by the contemporary labour market. The study proposes a curriculum improvement strategy based on the sectoral identification of key soft skills, differentiated by economic sectors such as education, health, commerce, public administration, industry, and primary activities. This proposal is based on the cross-referencing of empirical data with international theoretical frameworks. It seeks to guide the progressive inclusion of crosscutting skills such as leadership, adaptability, critical thinking, and effective communication within university curricula. The results suggest a differentiated training strategy tailored to the productive environment, which can significantly enhance the career paths of graduates, facilitating their transition to positions of greater responsibility. The proposal can be replicated in other Latin American universities facing similar challenges of professional mobility and educational mismatch.

El presente estudio se centra en generar una propuesta metodológica para la asignación de recursos humanos en la ejecución de tareas de mantenimiento. Ésta considera: La implementación de un algoritmo que supone un conjunto de actividades de mantenimiento (recursos o tareas), un conjunto formado por el personal de mantenimiento (agentes), una relación de plausibilidad sobre los recursos, una relación jerárquica sobre los agentes y la preferencia que los agentes tienen sobre los recursos. Estos supuestos llevan a una jerarquización del personal e identificación de las tareas críticas. Esta jerarquización toma como parte fundamental a la gestión del conocimiento ya que, la función de mantenimiento requiere de conocimientos técnicos muy específicos, normalmente almacenados de manera tácita entre el personal que opera en estas áreas. La metodología se complementa con una jerarquización de las tareas usando la metodología de análisis de modos de falla, efectos y criticidad (AMFE). Los resultados aplicados a una flota de vehículos muestran que se necesitan otros supuestos para obtener criterios equitativos y justos en la asignación de las tareas de mantenimiento, los cuales se consideran como ponderaciones en una función de la gestión de conocimiento que incluyen: Criterios de experiencia profesional, experiencia en la empresa, talante y autoformación.

El mundo actual se encuentra impulsado por el conocimiento, donde el ritmo del cambio es vertiginoso debido en gran medida a la tecnología que interviene directamente dando ventaja a las diferentes organizaciones (Khamdun et al., 2021). En esta línea, el desarrollo de la tecnología es posible por la intervención del ser humano y sus habilidades para transformarla, pero es indudable que existen habilidades interpersonales que apoyan estos procesos, y son conocidas como “competencias holísticas (Chan y Luk, 2022), “habilidades blandas”, “habilidades del siglo XXI”, “habilidades para la empleabilidad” (Barrie, 2006). Estas son cada vez más importantes y críticas para el éxito de cualquier profesión (Caeiro et al., 2021; Mulcahy et al., 2018; Olo et al., 2021; Sharvari y Kulkarni, 2019). Dado que el objetivo del presente estudio no es distinguir diferentes conceptualizaciones, se acuñará el término “competencias holísticas”.

Aquaculture production systems rely on the reliable operation of mechanical and electromechanical equipment to maintain stable environmental conditions. In shrimp farming, failures in critical assets may directly affect dissolved oxygen availability and compromise production stability. Despite the operational importance of these systems, structured methodologies for asset criticality assessment and maintenance prioritization in aquaculture remain limited. This study proposes a multi-criteria decision-making framework based on the Analytic Hierarchy Process (AHP) to evaluate and prioritize critical assets in shrimp aquaculture production systems. The model integrates nine technical and operational criteria related to reliability, maintainability, operational exposure, and production impact. The proposed methodology was applied to three key assets in the Primary Production stage: mechanical aerators, turbines, and stationary engines. The results indicate that mechanical aerators exhibit the highest criticality score (0.350), followed by stationary engines (0.328) and turbines (0.322). These findings highlight the dominant operational role of aeration systems in maintaining dissolved oxygen levels and ensuring production stability in shrimp farming systems. The proposed framework demonstrates that multi-criteria decision models can effectively support maintenance prioritization by transforming expert knowledge and operational information into a structured and consistent evaluation process. The methodology provides a replicable decision-support tool that can assist managers and maintenance planners in improving asset management and resource allocation in aquaculture production systems.