Palabras clave
Vocational Education
Administrative in Practice
Data-Based Decision Making
Institutional Competitiveness
Cómo citar
Resumen
Purpose: This study conceptualizes Competitive Intelligence (CI) as a strategic capability to support intelligence-based decision-making in higher vocational education administration. It examines the extent to which CI practices enhance decision quality, operational efficiency, and institutional competitiveness, addressing the gap between data use and strategic intelligence in educational management.
Methodology/approach: A mixed-methods design was employed, combining quantitative survey data (n = 75) with qualitative semi-structured interviews (n = 15) involving institutional administrators. Quantitative analysis included descriptive statistics, correlation, and regression models, while qualitative data were analyzed through thematic coding to capture decision-making dynamics and contextual insights.
Originality/Relevance: The study advances CI research by extending its application to vocational education administration and by reframing CI as a decision-support capability rather than a purely informational process. It contributes to bridging the gap between data analytics and strategic intelligence use in institutional governance.
Key findings: CI practices—particularly environmental scanning and data-driven decision-making—demonstrate strong positive effects on decision quality (r = 0.85) and competitiveness (r = 0.78). Regression results confirm CI as a significant predictor of decision effectiveness (β = 0.62), operational efficiency (β = 0.48), and competitiveness (β = 0.55). However, strategic intelligence functions such as competitor analysis and forecasting remain underutilized.
Theoretical/methodological contributions: The study positions CI as a dynamic capability embedded in decision processes and proposes a framework linking intelligence practices to data-driven governance and sustainable competitive performance.
Citas
Abdelaziz, N. M., Abdo, S. M., Naguib, S. M., & Ali, A. H. (2026). Methodological advances of AI and business intelligence in nutrition: Techniques, applications, and future directions. International Journal of Computers and Informatics (Zagazig University), 10, 56–77. https://www.ijci.zu.edu.eg/index.php/ijci/article/view/154
Adewusi, A., Okoli, U., & others. (2024). Business intelligence in the era of big data: A review of analytical tools and competitive advantage. Studies in Higher Education, 49(11), 2153–2177. https://doi.org/10.1080/03075079.2023.2293926
Andrés Puerta-Guardo, F., Cantillo-Orozco, A. S., Castillo-Loaiza, J. L., Narváez-Grisales, J. A., & Molina-Guerrero, J. (2026). Quality in higher education institutions as a transversal tool in institutional accreditation: A bibliometric review. European Journal of Educational Research, 15(1), 19. https://doi.org/10.12973/eu-jer.15.1.19
Bordeleau, F., Mosconi, E., & Santa-Eulalia, L. (2018). Business intelligence in Industry 4.0: State of the art and research opportunities. Proceedings of the Hawaii International Conference on System Sciences. https://scholarspace.manoa.hawaii.edu/bitstreams/bd2afd28-a130-4efd-aa79-2878bff08dde/download
Carvajal-Pérez, J. A. (2025). Impacto de gestión educativa fundamentada en la inteligencia competitiva. CIENCIAMATRIA, 11(1), 97–109. https://doi.org/10.35381/cm.v11i1.1533
Cruz, D. F., Sakaya, A. Y., Ferreira, M. G. G., Forcellini, F. A., Anjos, S. J. G., Abreu, A. F. de, & Cauchick Miguel, P. A. (2015). Inteligência competitiva em organizações de serviços: Uma revisão sistemática da literatura. Revista Produção Online, 15(1), 50–77. https://doi.org/10.14488/1676-1901.v15i1.1663
Dalfovo, O., Schirmann, F. R., & Correia, R. B. (2010). A utilização do observatório da educação como inteligência competitiva em uma instituição de ensino superior. Revista Eletrônica de Estratégia & Negócios, 3(2), 140–158. https://doi.org/10.19177/reen.v3e22010140-158
Ernest Mwandumbya, N. K., & Mushi, G. (2026). Artificial intelligence in hospitality and tourism training: Opportunities and challenges in Arusha’s vocational training colleges. Journal of Research Innovation and Implications in Education. https://doi.org/10.59765/qpf42
Wang, G. (2025). Performance evaluation and optimization of photovoltaic systems in urban environments. International Journal of New Developments in Engineering and Society, 9(1). https://doi.org/10.25236/ijndes.2025.090106
Garcia-Alsina, M., Cobarsí-Morales, J., & Ortoll, E. (2016). Competitive intelligence theoretical framework and practices: The case of Spanish universities. Aslib Journal of Information Management, 68(1), 57–75. https://doi.org/10.1108/AJIM-04-2015-0061
Gonçalves, C. M., Colauto, R. D., & Beuren, I. M. (2007). Proposta de indicadores para sistema de inteligência competitiva em instituição de ensino superior. Revista Produção Online, 7(1). https://doi.org/10.14488/1676-1901.v7i1.95
Hussein, R., Zink, A., Ramadan, B., Howard, F. M., Hightower, M., Shah, S., & Beaulieu-Jones, B. K. (2026). Advancing healthcare AI governance through a comprehensive maturity model based on systematic review. npj Digital Medicine, 9(1), Article 236. https://doi.org/10.1038/s41746-026-02418-7
Hair, J. F., Babin, B. J., Anderson, R. E., & Black, W. C. (2019). Multivariate data analysis (8th ed.). Cengage Learning. https://www.cengage.uk/c/multivariate-data-analysis-8e-hair-babin-anderson-black/9781473756540
Jones, J., MacDonnell, J., & Aamir, A. (2025). Mature undergraduates’ experiences of a UK university induction programme: Accruing social capital, evolving habitus and developing a sense of belonging. Innovations in Education and Teaching International. https://doi.org/10.1080/14703297.2025.2555959
Júnior, C. A. C. de M., Pinto, P. A. L. de A., & Melo, F. J. C. de. (2026). Business intelligence and sustainability features in education: A systematic literature review. Sustainability, 18(4), 1954. https://doi.org/10.3390/su18041954
Li, Y.-M. (2026). Challenges and opportunities of adopting digital technology for curriculum reform. In Digital technology in management education (pp. 5–15). https://doi.org/10.4324/9781003662792-2
Mazumder, Q. H. (2014). Applying Six Sigma in higher education quality improvement. In ASEE Annual Conference and Exposition Proceedings. https://doi.org/10.18260/1-2--20082
Mgweba, C., Rawjee, V. P., & Naidoo, P. (2024). The use of competitive intelligence as a strategic tool for student recruitment in public universities. International Journal of Business Ecosystem & Strategy, 6(3), 196–203. https://doi.org/10.36096/ijbes.v6i3.523
Mohammad, A. B., Al-Okaily, M., & others. (2022). Business intelligence and analytics (BIA) usage in the banking industry sector: An application of the TOE framework. Information, 8(4), 189. https://www.mdpi.com/2199-8531/8/4/189
Naranjo, J. E., Valle, A., & Bousia, A. (2026). The use of business intelligence and analytics in electric vehicle technology: A comprehensive survey. Electronics, 15(2), 366. https://doi.org/10.3390/electronics15020366
Ojinaga, E. P., Medina, M. A. R., & Rivas, X. G. A. (2026). Competitive intelligence practices in Mexico: An updated systematic review and meta-analysis (2000–2024). International Journal of Professional Business Review, 11(1), 1. https://doi.org/10.26668/businessreview/2026.v11i1.5679
Önden, A. (2026). Integrating artificial intelligence and enterprise resource planning systems: A structured review of decision support capabilities, constraints, and governance. Management Science Advances, 3(1), 172–186. https://doi.org/10.31181/msa31202643
Pailingan, V. R., & Batmetan, J. R. (2019). How competitive intelligence can be used to improve a management vocational high school: A case from Indonesia. Journal of Intelligence Studies in Business, 9(3), 56–61. https://doi.org/10.37380/jisib.v9i3.515
Pradeepa, S. V., Singh, P., Shanmugam, R., & Suresh, N. V. (2026). Transforming business intelligence with emerging technologies in the IT industry. In Empowering inclusive innovation (pp. 733–738). Routledge. https://doi.org/10.1201/9781003753445-87
Prihatin, E., & Hartini, N. (2018). Competitive intelligence-based decision making model as a global market competitive strategy in educational institutions.
Rahmi, N., Ishak, P., & others. (2020). Understanding the relationship between competitive intelligence and strategic management of universities: A critical review. Jurnal Manajemen Bisnis. https://doi.org/10.33096/jmb.v7i2.560
Rane, N. L., Chika, O. E., & Rane, J. (2026). Business intelligence systems integrating artificial intelligence, big data analytics, machine learning, internet of things, and blockchain. International Journal of Applied Resilience and Sustainability, 2(2), 367–395. https://doi.org/10.70593/deepsci.0202014
Romero, C. T., Ortiz, J., & Khalaf, O. (2021). Business intelligence: Business evolution after Industry 4.0. Sustainability, 13(18), 10026. https://www.mdpi.com/2071-1050/13/18/10026
Roy, P. (2025). Transforming higher education libraries with data analytics, business intelligence, and business analytics: A review. Journal of Librarianship and Information Science. https://doi.org/10.1177/09610006241307028
Sahu, A., & Shrivastava, R. (2013). Critical success factors for sustainable improvement in technical education excellence: A literature review. The TQM Journal, 25(1), 62–74.
Saleem, I. (2026). Agentic artificial intelligence in business higher education: A bibliometric analysis. Higher Education, Skills and Work-Based Learning, 16(1), 219–236. https://doi.org/10.1108/HESWBL-08-2025-0330
Sanni, J. O., & Atima, M. E. (2021). Business intelligence dashboard frameworks resolving executive visibility gaps in strategic marketing governance. International Journal of Multidisciplinary Research and Growth Evaluation, 2(6), 633–646. https://doi.org/10.54660/.ijmrge.2021.2.6.633-646
Shawyun, T. (2020). Integrated electronic HEI performance management. In Encyclopedia of organizational knowledge, administration, and technology (pp. 1108–1131). https://doi.org/10.4018/978-1-7998-3473-1.ch077
Silveira Junior, R. R. da. (2015). Utilização de inteligência competitiva, da gestão de riscos e da computação aplicada para ganhos de competitividade. https://doi.org/10.26512/2015.12.D.20623
Tafuro, A., Colamartino, C., Dammacco, G., & Toma, P. (2026). Business intelligence for SMEs: A hybrid review of models, barriers, and future directions. Enterprise Information Systems, 20(1). https://doi.org/10.1080/17517575.2025.2588755
Variyar, A. R., & Karangara, R. (2026). Enhancing complex decision making in BPM through artificial intelligence: A systematic examination. ShodhAI: Journal of Artificial Intelligence, 3(1), 29–36. https://doi.org/10.29121/shodhai.v3.i1.2026.72
Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.
Derechos de autor 2026 Journal of Sustainable Competitive Intelligence