Las herramientas de Inteligencia de Negocios potencian la capacidad de toma de decisiones en las PYMES.
Resumen
Implementar las herramientas de inteligencia de negocios (BI) en las pequeñas y medianas empresas (PYMEs) lleva implícito una serie de ventajas y limitaciones. El enfoque de esta investigación fue cualitativo y la metodología exploratoria. Las técnicas de recolección de datos se basaron en la entrevista semiestructurada y la revisión de la literatura, y para el análisis de los datos se utilizó la técnica de análisis temático. Se realizaron entrevistas a una muestra (n=7) propietarios de este tipo de empresas. Uno de los hallazgos clave fue que la BI ofrece ventajas en diversas áreas operativas: desde finanzas hasta marketing, permitiendo a las empresas maximizar recursos y minimizar riesgos.
Citas
Adnane, Y. I., & Zerari, M. (2024). Optimizing business intelligence classification rule mining using quantum-inspired genetic algorithm. IEEE Access. https://ieeexplore.ieee.org/abstract/document/10683701/
Alkhwaldi, A. F. (2024). Understanding the acceptance of business intelligence from healthcare professionals’ perspective: An empirical study of healthcare organizations. International Journal of Organizational Analysis. https://www.emerald.com/insight/content/doi/10.1108/IJOA-10-2023-4063/full/html
Alzghoul, A., Khaddam, A. A., Abousweilem, F., Irtaimeh, H. J., & Alshaar, Q. (2024). How business intelligence capability impacts decision-making speed, comprehensiveness, and firm performance. Information Development, 40(2), 220-233. https://doi.org/10.1177/02666669221108438
Bai, A., Satarpour, M., Mohebbi, F., & Forati, A. M. (2024). Digital Crowdsourcing and VGI: Impact on information quality and business intelligence. Spatial Information Research, 32(4), 463-471. https://doi.org/10.1007/s41324-024-00572-2
Bharathi, G. P., Chandra, I., Sanagana, D. P. R., Tummalachervu, C. K., Rao, V. S., & Neelima, S. (2024). AI-driven adaptive learning for enhancing business intelligence simulation games. Entertainment Computing, 50, 100699.
Cristo, S., Ferreira, J. J., Teixeira, A., & McDowell, W. C. (2024). Knowledge spillovers in business intelligence organisations: A strategic entrepreneurship perspective. International Entrepreneurship and Management Journal, 20(2), 733-759. https://doi.org/10.1007/s11365-023-00896-9
Fabian, A. A., Uchechukwu, E. S., & Blessing, E. O. (2024). Business Intelligence and Decision-Making in Micro Small and Medium Enterprises in Africa. Sch J Econ Bus Manag, 4, 124-133.
Hosen, M. S., Islam, R., Naeem, Z., Folorunso, E. O., Chu, T. S., Al Mamun, M. A., & Orunbon, N. O. (2024). Data-Driven Decision Making: Advanced Database Systems for Business Intelligence. Nanotechnology Perceptions, 687-704.
Hossain, Q., Yasmin, F., Biswas, T. R., & Asha, N. B. (2024). Integration of Big Data Analytics in Management Information Systems for Business Intelligence. Saudi J Bus Manag Stud, 9(9), 192-203.
Ibeh, C. V., Asuzu, O. F., Olorunsogo, T., Elufioye, O. A., Nduubuisi, N. L., & Daraojimba, A. I. (2024). Business analytics and decision science: A review of techniques in strategic business decision making. World Journal of Advanced Research and Reviews, 21(2), 1761-1769.
Jaradat, Z., Al-Dmour, A., Alshurafat, H., Al-Hazaima, H., & Al Shbail, M. O. (2024). Factors influencing business intelligence adoption: Evidence from Jordan. Journal of Decision Systems, 33(2), 242-262. https://doi.org/10.1080/12460125.2022.2094531
Jewel, R. M., Chowdhury, M. S., Al-Imran, M., Shahid, R., Puja, A. R., Ray, R. K., & Ghosh, S. K. (2024). Revolutionizing Organizational Decision-Making for Stock Market: A Machine Learning Approach with CNNs in Business Intelligence and Management. Journal of Business and Management Studies, 6(1), 230-237.
Jones, V. A. (2024). Business intelligence solutions for enhanced accounting decision-making in digital transformation. Engineering Science Letter, 3(01), 11-15.
Kazemi, A., Kazemi, Z., Heshmat, H., Nazarian-Jashnabadi, J., & Tomášková, H. (2024). Ranking factors affecting sustainable competitive advantage from the business intelligence perspective: Using content analysis and F-TOPSIS. Journal of Soft Computing and Decision Analytics, 2(1), 39-53.
López, J., & Pérez, I. (2022). Docencia universitaria y transposición didáctica. Estudio de percepción. Chakiñán, Revista de ciencias sociales y humanidades, 16, 24-34. https://doi.org/10.37135/chk.002.16.01
Mavutha, W. (2024). Determining business intelligence adoption stages for apparel SMMES in Durban, South Africa: Received: 09th October 2023; Revised: 26th October 2023, 18th December 2023; Accepted: 20th December 2023. Socialis Series in Social Science, 6, 31-47.
Mohammed, A. B., Al-Okaily, M., Qasim, D., & Al-Majali, M. K. (2024). Towards an understanding of business intelligence and analytics usage: Evidence from the banking industry. International Journal of Information Management Data Insights, 4(1), 100215. https://doi.org/10.1016/j.jjimei.2024.100215
Moreno, M., & Hernández, W. G. (2024). The Business Intelligence Blueprint: Integrating Analytics, Big Data, and Project Management for Organizational Triumph. Journal Environmental Sciences And Technology, 3(1), 161-175.
Mudau, T. N., Cohen, J., & Papageorgiou, E. (2024). Determinants and consequences of routine and advanced use of business intelligence (BI) systems by management accountants. Information & Management, 61(1), 103888.
Nazir, J., & Das, P. K. (2024). The Systematic Literature Review on Business Intelligence Towards Entrepreneurial Orientation of Ventures. Applying Business Intelligence and Innovation to Entrepreneurship, 1-20. https://doi.org/10.4018/979-8-3693-1846-1.ch001
News Center Microsoft Latinoamérica. (2023, marzo 21). PyMEs ecuatorianas consideran que transformación digital impacta su negocio. News Center Latinoamérica. https://news.microsoft.com/es-xl/93-de-las-pymes-ecuatorianas-considera-que-transformacion-digital-impacta-positivamente-su-negocio/
Solanki, A., Jain, K., & Jadiga, S. (2024). Building a Data-Driven Culture: Empowering Organizations with Business Intelligence. International Journal of Computer Trends and Technology, 72(2), 46-55.
Tsiu, S., Ngobeni, M., Mathabela, L., & Thango, B. (2024a). Applications and Competitive Advantages of Data Mining and Business Intelligence in SMEs Performance: A Systematic Review. https://doi.org/10.20944/preprints202409.0940.v1
Tsiu, S., Ngobeni, M., Mathabela, L., & Thango, B. (2024b). Applications and Competitive Advantages of Data Mining and Business Intelligence in SMEs Performance: A Systematic Review. https://www.preprints.org/manuscript/202409.0940
Udeh, C. A., Orieno, O. H., Daraojimba, O. D., Ndubuisi, N. L., & Oriekhoe, O. I. (2024). Big data analytics: A review of its transformative role in modern business intelligence. Computer Science & IT Research Journal, 5(1), 219-236.
Urefe, O., Odonkor, T. N., Obeng, S., & Biney, E. (2024). Innovative strategic marketing practices to propel small business development and competitiveness. Magna Scientia Advanced Research and Reviews, 11(2), 278-296. https://doi.org/10.30574/msarr.2024.11.2.0122
Usman, M., Moinuddin, M., & Khan, R. (2024). Unlocking insights: Harnessing the power of business intelligence for strategic growth. International Journal of Advanced Engineering Technologies and Innovations, 1(4), 97-117.
Wohlfarth, B., Linder, N., Schmitz, F. M., Hari, R., Elfering, A., & Guttormsen, S. (2024). Self-directed learning among general practitioners in the German-speaking part of Switzerland: A qualitative study using semi-structured interviews. Swiss Medical Weekly, 154. https://boris.unibe.ch/199675/
