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All Journal Bulletin of Electrical Engineering and Informatics
Igor Aguilar-Alonso
Universidad Nacional Mayor de San Marcos
Electrical & Electronics Engineering

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Deep learning techniques business performance optimization in micro, small, and medium-sized enterprises: systematic review Carlos Roberto Sampedro Guaman; Miguel Angel Cano Lengua; Ciro Rodriguez Rodriguez; Igor Aguilar-Alonso
Bulletin of Electrical Engineering and Informatics Vol 15, No 1: February 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i1.9819

Abstract

The application of deep learning is transforming how micro, small, and medium-sized enterprises (MSMEs) operate. By using data-driven insights, these firms overcome traditional analytical limitations and improve decision-making. This study explores factors influencing deep learning adoption in MSMEs, identifies effective strategies, and compares performance between companies that implement these methods and those that do not. The objective is to analyze the impact of deep learning on optimizing the performance of MSMEs. The methodology consisted of a scientific review following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) system and a bibliometric analysis to map international contributions. The results show that techniques such as recurrent neural networks (RNNs), long short-term memory (LSTM) networks, transformers, and deep reinforcement learning (DRL) are crucial for marketing strategy prediction, customer experience personalization, and inventory management, leading to better return on investment (ROI), loyalty, and efficiency. Despite the potential benefits, there's still no enough research on how small businesses with limited resources use these methods and deal with issues like poor infrastructure and data access. Deep learning is essential for MSMEs' sustainability and competitiveness, even if there are challenges.
Co-Authors Carlos Roberto Sampedro Guaman Ciro Rodriguez Rodriguez Miguel Angel Cano Lengua