Business intelligence for dynamic commercial management in SMEs: A systematic review.

Authors

  • Juan Santos Fernandez Universidad Nacional de Trujillo https://orcid.org/0000-0002-8882-9256
  • Carmen Idalia Niño Ladron de Guevara Arroyo Universidad Nacional de Trujillo
  • Xiomara Sadith Amambal Bances Universidad Nacional de Trujillo
  • Luis Enrique Boy Chavil Universidad Nacional de Trujillo

DOI:

https://doi.org/10.31243/id.v20.2024.2586

Keywords:

business management, business intelligence, SMEs, technology

Abstract

Achieving success and being competitive in their field is crucial for SMEs, which is why they must carry out an efficient management of their administrative processes. Technological development has allowed greater control of these processes thanks to its significant progress, the objective of this article is to review publications that have been made in the last five years, where 52 articles on the use of business intelligence (BI) in the management of business processes in SMEs were analyzed. Among the articles analyzed, 47 were found to address BI applications, with Performance Management and KPIs being the most mentioned. Likewise, a study was made with respect to the technologies and methodologies employed, these aspects were addressed in 41 articles, where Artificial Intelligence, and agile methodology Scrum are mentioned in particular, which indicates their prevalence. Within the scope of AI tools used, Machine Learning stood out as the most popular option, representing 18% of the studies examined. With these results, SMEs can easily identify which are the most popular technology tools and software development methodologies, this will be useful for them when selecting technologies that will improve the management of their business processes. The analysis emphasizes the crucial importance of technology in improving and optimizing business management in SMEs.

Author Biographies

  • Juan Santos Fernandez , Universidad Nacional de Trujillo

    Industrial Engineer, Systems Engineer, Master in Production, Doctor in Science and Engineering. Full-time professor assigned to the Systems Engineering Department of the Universidad Nacional de Trujillo. Undergraduate and graduate professor at the National University of Trujillo, with research in Scientific Research Methodology, Systems Simulation, Predictive Models and Software Engineering.

  • Carmen Idalia Niño Ladron de Guevara Arroyo, Universidad Nacional de Trujillo

    Student of the National University of Trujillo of the Systems Engineering career.

  • Xiomara Sadith Amambal Bances , Universidad Nacional de Trujillo

    Student of the National University of Trujillo of the Systems Engineering career.

  • Luis Enrique Boy Chavil, Universidad Nacional de Trujillo

    B.Sc. in Computer Science-UNMSM, B.Sc. in Systems Engineering-USS. Systems Engineering USS, Master in University Teaching UCV, concluded studies of Master in Systems Engineering with mention in Administration and IT Management at UNT, Doctor in Higher Education UCV. Author of the books with ISBN Data Engineering, Introduction to Databases, co-author of the book Introduction to Programming with Visual C++, author of the book Data Modeling. Full-time professor and current Director of the Department of Systems Engineering UNT.

    Translated with DeepL.com (free version)

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Published

2025-01-28

How to Cite

Business intelligence for dynamic commercial management in SMEs: A systematic review. (2025). Investigación Y Desarrollo, 20(1). https://doi.org/10.31243/id.v20.2024.2586

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