Conference Agenda

The purpose of this pre-experimental study was to analyze and improve the baggage management system by incorporating technological tools into the improvement proposal, with the aim of speeding up the process of selecting and loading luggage at Cajamarca's Armando Revoredo Iglesias Airport. A diagnosis of the initial situation was carried out to obtain the data necessary for the design of the proposal, using methods such as Monte Carlo simulation and queueing theory. The simulation was developed using Promodel software, incorporating a conveyor belt system and an automated sorter. As a result, there was a 43.53% reduction in average waiting time and a 36.36% reduction in the number of passengers in line compared to the initial scenario.

This study aimed to determine the relationship between the digital marketing mix and the purchase decision of consumers of imported cosmetic products in Lima Norte, 2025. The research followed a quantitative approach, with a non-experimental design, basic type, correlational scope, and cross-sectional cut. To this end, a survey was administered to a simple random sample of 384 consumers who purchased imported cosmetic products through digital platforms. As a result, the data indicated a high positive correlation between the digital marketing mix and the purchase decision (Spearman = 0.830), reflecting a statistically significant relationship between both variables. Regarding the dimensions, place (0.746) and promotion (0.700) showed a high positive correlation with the purchase decision, while product (0.687) and price (0.513) presented a moderate positive correlation, suggesting that accessibility and digital communication are more closely related to consumer decision-making. Therefore, it is concluded that digital marketing mix strategies are significantly related to the purchase decision, as consumers actively consider them throughout their purchasing process. Furthermore, 90.6% of respondents perceived these strategies at a high level, confirming their decisive role in the digital purchasing experience.

Peru’s recent growth is closely tied to mining, where copper and associated mineral exports shape output and public revenues. In this context, explosives providers such as Orica play an enabling yet largely invisible role in productivity, safety and environmental outcomes. This paper examines how Orica’s operations in Peru contribute to industrial development through three dimensions: technological innovation in blasting, safety and risk management, and sustainable growth. Using a qualitative case study design based on corporate reports, industry analyses and national statistics, the study connects company initiatives with macro indicators of mining dependence on gross domestic product and exports. The first-dimension analyses digital blasting ecosystems, advanced bulk explosives and wireless initiation systems that seek to optimize fragmentation, reduce unplanned stoppages and improve energy efficiency along the mining value chain. The second examines how frameworks such as ISO 31000 and safety culture research are translated into training, procedures and digital monitoring to prevent fatalities, high potential incidents and occupational exposures. The third explores Orica’s decarbonization trajectory, including recent double digit reductions in net scope one and two greenhouse gas emissions and a forty five per cent reduction target for twenty thirty, together with efforts to reduce nitrate leaching and water use. By situating these practices within a copper dependent and socially demanding development model, the paper argues that blasting can evolve from a cost line item into a strategic lever for competitiveness, resilience and more responsible resource development.

The main objective of this research is to determine the relationship between capital structure and profitability in Peruvian agribusiness companies registered with the Superintendency of Securities Market during the period 2016-2023, with the aim of identifying how the debt-to-equity ratio influences their financial performance.

The study used a quantitative, correlational, and non-experimental design approach, relying on a documentary analysis of the financial statements of the selected companies. The methodology allowed for the calculation of ratios such as ROA, ROE, debt, and capital debt.

The population consisted of nine agroindustrial companies, of which four were selected through non-probabilistic convenience sampling, considering the availability of complete financial information for the period studied.

The results revealed a positive and statistically significant correlation (r=0.436; p<0.05) between capital structure and profitability. Companies that managed to maintain a balanced ratio between debt and equity achieved better levels of profitability for shareholders (average ROE = 0.88). However, low return on assets (average ROA = 0.013) was identified, highlighting the need to optimize operational efficiency.

Keyword: Estructura de capital, Rentabilidad, Agroindustrial, Endeudamiento, Finanzas empresariales

Agriculture is one of the most relevant economic activities globally, where pests such as the whitefly (Bemisia tabaci) generate significant crop losses. Traditional detection methods, in addition to being labor-intensive, present low effectiveness, which has driven the exploration of alternatives based on artificial intelligence (AI). The development of these technologies has enabled notable advancements in the early identification of B. tabaci, improving efficiency and reducing agricultural damage. However, their implementation faces operational challenges—such as foliage occlusion, lighting variability, and high equipment costs—as well as limitations in technical knowledge within the agricultural sector, particularly in Spanish-speaking regions.

This systematic review (without meta-analysis) analyzes computer vision methods and drones for the detection and quantification of B. tabaci through a non-experimental descriptive design. Thirty open-access articles (2020–2025, in English, Spanish, or Chinese) were selected from seven databases (Scopus, SpringerLink, EBSCOhost, Web of Science, Scielo, ResearchGate, MDPI). These studies employed convolutional neural networks (CNNs), object detection models (Faster R-CNN, YOLOv4/v8), near-infrared spectroscopy (NIR), and hyperspectral imaging. The studies utilized CNNs, Faster R-CNN/YOLOv4/v8 detection models, NIR sensors, and various types of cameras, achieving >90% precision in the detection of adults, eggs, and pre-visual viral symptoms. The most effective techniques were CNNs (95.08%), YOLOv8 (87% on Raspberry Pi), and hyperspectral imaging (98%), consistently exceeding 85% precision. The optimal model selection depends on the type of analysis (leaf surface vs. internal symptoms), the pest's developmental stage, and crop characteristics, especially spectral variation. Hyperspectral systems excelled in early detection, while YOLO offered more accessible solutions for practical implementation.

La mecanización agrícola en zonas de extrema altitud, como el Altiplano peruano (3830 m.s.n.m.), enfrenta una barrera termodinámica crítica: la baja densidad del aire (hipoxia) impide la combustión completa de la gasolina, dificultando el arranque en frío y generando emisiones altamente tóxicas que afectan la salud del operador. En respuesta a esta problemática, esta investigación evalúa la incorporación del hidrógeno como vector energético en un motor utilitario (Toyaki TK-GX35).

A diferencia de las conversiones convencionales, el estudio adoptó un enfoque dual: primero, se validó experimentalmente un sistema híbrido de inyección de HHO generado in situ mediante electrólisis solar (basado en Vilca Callata, 2024), y segundo, se desarrolló el análisis teórico para una futura conversión total. Los resultados de campo demostraron que el enriquecimiento con hidrógeno actúa como un catalizador de ignición, logrando un arranque inmediato (1.02 segundos) sin necesidad de estrangulamiento (choke) y mejorando significativamente el desempeño ambiental al reducir la opacidad de los gases en un 93% y las emisiones de CO en un 66%. Si bien el modelo teórico advierte que un ciclo 100% hidrógeno en motores aspirados implica una pérdida de potencia volumétrica del 60%, se concluye que el sistema híbrido es la solución técnica viable actual para mitigar el impacto ambiental y operativo en la agricultura altoandina.