Conference Agenda

The research aimed to determine the relationship between foreign direct investment (FDI) and employment in Peru (2014-2023). A quantitative methodology with non-experimental design and correlational scope was used. The sample included annual data on FDI and formal employment, obtained from the Central Reserve Bank (BCR) and the Ministry of Labor (MTPE). The analysis used Pearson's coefficient, previously validating normality with Shapiro-Wilk. The results showed a high and significant positive evaluation (r=0.815; p=0.004), highlighting the impact of FDI in strategic sectors and the need for equitable public policies.

The research examines the impact of artificial intelligence (AI) on sustainable entrepreneurial ecosystems in Lima, Peru, highlighting its influence on business sustainability and competitiveness. Utilizing a quantitative approach based on structural equation modeling (PLS-SEM) and a non-experimental design, the study analyzed data from 385 entrepreneurs with experience in and use of advanced technologies. The findings reveal that AI significantly enhances business sustainability (β=0.63, p<0.001) by optimizing resources and reducing costs, while also improving business performance (β=0.49, p<0.01) through better decision-making and service personalization. However, barriers such as insufficient technical knowledge (42%), high implementation costs (36%), and limited access to technological infrastructure (28%) were identified. These limitations underscore the need for public policies that promote digital training, subsidies for advanced technologies, and infrastructure development. Despite these challenges, AI adoption enables businesses to address sustainability and innovation demands, establishing itself as a key catalyst for transforming traditional business models. In conclusion, AI has the potential to strengthen Lima's entrepreneurial ecosystems by improving business sustainability and competitiveness, provided that the identified barriers are addressed through institutional support and technical training strategies.

This study analyzes the impact of Design Thinking on the development of entrepreneurial competencies among university students in Lima, Peru. Using a quantitative approach based on structural equation modeling (CB-SEM) and a non-experimental design, the study evaluated 385 students with active entrepreneurial experience. The findings reveal that Design Thinking significantly influences creativity (β = 0.62, p < 0.001) and problem-solving (β = 0.55, p < 0.01), highlighting its ability to foster an iterative and sustainable entrepreneurial approach. Barriers such as lack of practical knowledge (41%), time constraints (33%), and limited access to technological resources (26%) were also identified, limiting its effective implementation. The study emphasizes the need for specific educational strategies, such as innovation laboratories and interdisciplinary programs, to address these challenges. Policy implications include promoting alliances between universities, governments, and companies to ensure resources and training in advanced methodologies. Despite the challenges, Design Thinking has proven to be a transformative tool that enhances sustainability and innovation in university-based entrepreneurship. This work contributes not only to the theoretical development of the field but also offers practical recommendations to strengthen entrepreneurial ecosystems in emerging contexts. In conclusion, Design Thinking can catalyze significant progress towards more sustainable and inclusive entrepreneurship, provided that identified barriers are addressed through collaborative and strategic approaches.

This research aims to apply Lean Manufacturing tools to reduce delay times in a transportation company. The materials and methods that were applied were to first perform an initial diagnosis of the processes in the delivery area, where problems such as the disorganization and delays of shipments and deliveries of packages, a time study was used where 20 shifts were taken to identify the Lean 5S, Kanban and Kaizen. Likewise, shelves for orders, software, boards and Kanban cards were implemented. As results and discussion we have that the application od Lean tools allowed a reduction of 26 minutes compared to the initial cycle, in addition to the 76% reduction in waiting time, the 5S reduced 84% of the order search time, Kanban improved task compliance by 66% and Kaizen improved labeling and listing activities by 76,6%. In conclusion, the application of 5S, Kanban and Kaizen tools proved to be key to reducing delay times in the parcel area of a Peruvian transportation company.

The general objective of this research is to analyze the "relationship between consumer behavior and the purchasing decision process in 3-star hotels in the city of Arequipa, 2024". The methodology used was quantitative, non-experimental, cross-sectional and correlational. A Likert scale questionnaire from 1 to 5 was used for each variable, which were developed by Orbegoso et al. (2022). The questionnaire consists of 31 questions, of which 7 correspond to the filter questions, the following 13 questions evaluate the first variable, and the remaining 11 questions correspond to the evaluation of the second variable. The instrument used was validated by 3 experts to corroborate its reliability, for which SPSS was used, where the level of reliability level was 0.867. Regarding Spearman's Rho, the result was 0.566. This instrument was applied to a sample of 385 consumers of both sexes of 3-star hotels, where it was determined that there is a moderate positive correlation between the variables. The consumer’s personal, social, cultural and psychological factors have a low positive relationship between the PDC, but the factor of that most influences the PDC is the personal factor, due to the fact thar the consumers’ purchasing power is greater in comparison with the other factors.

The objective of this study was to analyze the implementation of Reliability Centered Maintenance (RCM) in a Peruvian metal-mechanical company to reduce failures in the critical machine, specifically the A10 mill.The research employed a quantitative and experimental design, using documentary analysis and personal interviews as techniques, together with instruments such as a documentary guide and a questionnaire. Tools such as the criticality matrix, Failure Mode and Effects Analysis (FMEA), Pareto diagram, decision tree and hour counter were used. The Shapiro-Wilk test confirmed the normality of the data with a significance level of 0.365: The implementation of the RCM increased the Mean Time Between Failure (MTBF) to 161.2 hours, reflecting an improvement in operational reliability. However, Student's t-test yielded a p-value of 0.690, indicating that there was no statistically significant difference between the pre- and post-implementation periods. These results suggest a positive but inconclusive impact on failure reduction and reliability.The study highlights the potential of RCM to optimize maintenance resources and improve the availability of critical equipment. However, further analysis and a longer implementation period are needed to obtain statistically significant results and fully validate its effectiveness.

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