Conference Agenda

Food waste in supermarkets is a challenge in terms of sustainability and operational efficiency. This study analyzes reverse logistics as a strategy to reduce food waste in supermarkets in Tegucigalpa. Using a mixed approach, surveys and interviews were conducted with managers and logistics experts, identifying the main causes of waste, such as product expiration, poor inventory management and overpurchasing. The findings show that, although some supermarkets apply redistribution and discounting strategies, the lack of regulations, technological costs and organizational resistance limit their adoption. The use of technologies such as RFID and blockchain to optimize traceability and reduce losses is highlighted. As a proposal, a Manual of Processes and Indicators for Inventory Control is developed, which establishes procedures to improve the management of perishable products and optimize redistribution. It is concluded that reverse logistics is key to minimize waste, but its success requires government incentives, clear regulations, strategic alliances and training

This study analyzes the impact of artificial intelligence (AI) in optimizing warehouse management in the Peruvian pharmaceutical sector. A quantitative, non-experimental, cross-sectional design was used, with a sample of 80 companies in the sector. Statistical analyzes were applied to evaluate the relationship between AI and logistics efficiency. The results indicate that AI significantly improves cost reduction and time optimization in the supply chain. Three key areas were identified: process automation, systems integration and data analysis. The strongest influence was found in data analysis, with a 44.6% impact on cost reduction and 46.6% on time optimization. Automation contributed 31% to cost reduction, while systems integration improved time by 26%. Additionally, it was observed that companies that implemented AI achieved a 20% reduction in frozen stock and an 18% decrease in delivery delays. The correlation between time optimization and cost reduction was high (85.8%), showing that the use of AI generates comprehensive improvements in logistics. It is concluded that AI is a key tool to improve the efficiency and competitiveness of the pharmaceutical sector, facilitating data-based decision making and optimizing warehouse management.

The coffee industry, recognized as one of the most widely consumed products both nationally and internationally, has positioned Honduras as the sixth largest coffee producer and exporter worldwide, holding a 4% share of the global production, which is dominated by countries like Brazil, Vietnam, Colombia, Indonesia, and Ethiopia. Within the North, Central America, and Caribbean Coffee Production group, Honduras leads with a 31% share. According to the statistical report from the Honduran Coffee Institute (IHCAFE), global coffee exports for the 2020-2021 harvest reached 168.17 million 46 kg bags, marking a 2.05% increase compared to the 2019-2020 harvest, which recorded 166.12 million 46 kg bags. This research focused on identifying and defining a method for projecting inventories within coffee exporting companies. The methodology involved collecting information on inventory management methods used in other countries, with the goal of selecting the most frequently employed method for implementation. This chosen method provides crucial data on optimal inventory quantities, total inventory costs, frequency, period, and reorder points for coffee. The results yielded accurate projections of inventory, considering economic factors, time periods, and weight units. This project not only describes the identified method but also assists in establishing specific values and factors that are critical to the operations of coffee exporting companies.

This study investigates the impact of Logistics 5.0 on small-scale retail supply chains, focusing on enhancing operational efficiency, customer experience, and adaptability within nanostores. The research explores the integration of AI-driven inventory management and IoT-enabled supply chains in the context of the smart economy. A systematic review of literature was conducted to analyze the implementation of Logistics 5.0 technologies, with data collected from multiple databases, including Scopus, Web of Science, and JSTOR. The findings reveal a 77% reduction in stockouts, a 60% decrease in overstocking, and a 21.7% increase in sales following the integration of Logistics 5.0. These results confirm the proposition that Logistics 5.0 enhances supply chain efficiency (Proposition 1), improves customer experience through real-time data and AI (Proposition 2), and fosters adaptability through human-machine collaboration (Proposition 3). The research offers actionable insights for nanostore retailers and policymakers, demonstrating how Logistics 5.0 can enhance access to goods in underserved communities, improving economic resilience and sustainability within small-scale retail sectors. Future studies could expand these findings by investigating the broader social and environmental implications of Logistics 5.0 in small retail contexts, paving the way for sustainable practices in smart retail ecosystems.

The objective of this research was to analyze the exports of Peruvian textile and clothing sector to the United States market for the year 2030. This analysis identified a target scenario, outlining strategic projections that forecast an annual growth of at least 5% in the market share of Peruvian cotton garments. The study employed a non-experimental design with a descriptive and propositional scope, incorporating structural analysis through the MICMAC tool. This method, which relies on expert consensus within the sector, identified four key factors: informality, investment in R&D, utilization of installed production capacity, and product attractiveness. These factors, when interacting with key social actors—such as business owners, government entities, and the National Society of Industries—generate strategic synergies. Additionally, SMIC-Prob software was used to construct future scenarios. The main findings suggest that implementing the proposed strategies could result in a 25.42% increase in the total export value of cotton garments to the U.S., while fostering sustainable growth in the sector through cleaner production practices and optimized logistics routes. This study provides the sector with a prospective framework as a strategic decision-making tool, offering deeper insights into the effects of economic and social factors on industrial competitiveness. Future research directions include applying the model to similar sectors and conducting international comparative studies.

The objective of this study focuses on determining the relationship between logistics management and cost reduction in transportation companies; in addition, it seeks the relationship of transportation management, warehouse management and information management with cost reduction. The research follows a quantitative approach, with a correlational and descriptive scope, to examine the connection between logistics management and operational cost reduction. The sample is composed of 100 workers, including drivers and administrative personnel, to whom a structured survey was applied as the main data collection instrument. The results show that there is a strong positive correlation between logistics management and the dimensions analyzed in relation to cost reduction. In particular, significant correlations were found with logistics management (r = 0.775; p < 0.001), information management (r = 0.683; p < 0.001) and transportation and warehouse management (r = 0.693; p < 0.001). It is concluded that proper logistics management, especially in the areas of information, transportation and warehousing, is associated with significant cost reductions in heavy-duty trucking companies. These practices not only improve efficiency and customer satisfaction, but also ensure a competitive advantage in the market.