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This study proposes an adaptive and differentiated inventory management model to improve operational efficiency and profitability of neighborhood stores in Panama, considering their specific constraints and complexities. Through a mixed methodological approach, combining qualitative strategies (literature review, interviews, focus groups, and observations) and quantitative strategies (historical sales and inventory data, statistical techniques, and the EOQ model), a model based on the Economic Order Quantity (EOQ) was developed.
The results highlight a 71.4% reduction in demand forecasting error, implying a substantial decrease in sales lost due to stockouts. The study emphasizes the importance of considering the variability in inventory maintenance costs among products, linked to diverse storage and preservation requirements, as a critical factor in adapting the EOQ model to neighborhood stores.
The study contributes to the literature by addressing a critical gap, demonstrating the potential of using adapted inventory management systems based on EOQ to improve the profitability and competitiveness of neighborhood stores. Although it has limitations, such as being based on data from a single store, its practical implications are significant.
The adoption of the proposed model is recommended, providing training and accessible technological tools for its effective implementation. Future research is suggested to address the study's limitations and explore integration with emerging technologies.
