Complejidad y análisis de datos para la inteligencia de negocios: una perspectiva conceptual sobre la relación entre educación superior y mercado laboral
Palabras clave:
Complejidad, análisis de datos, inteligencia de negocios, educación superior, mercado laboral
Resumen
Este artículo examina, desde una perspectiva de la complejidad, el papel del análisis de datos para la inteligencia de negocios en la relación entre educación superior y mercado laboral. Una revisión integrativa organizada en cinco núcleos relaciona los cambios ocupacionales, las competencias, la información institucional y las señales del entorno laboral. La revisión muestra que disponer de más datos no resuelve por sí mismo las dificultades para interpretar esta relación, especialmente cuando las fuentes representan dimensiones parciales y los cambios educativos y laborales ocurren en temporalidades diferentes. A partir de la literatura revisada, la articulación propuesta plantea tres cambios en la forma de abordar esta relación: analizar los indicadores considerando sus relaciones, vincular la información institucional con las señales del entorno e incorporar las consecuencias de las decisiones como nueva información para el análisis. En este planteamiento, el análisis de datos contribuye a identificar relaciones y cambios. La inteligencia de negocios incorpora esos resultados a los procesos institucionales de interpretación y decisión. Así, la información procedente del mercado laboral constituye un insumo para la deliberación académica, pero no determina por sí misma las respuestas de las instituciones educativas. Estas relaciones se plantean en un nivel conceptual y, por tanto, su aplicación deberá examinarse posteriormente mediante evidencia empírica en contextos institucionales.
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Ahumada-Tello, E., & Ramos, K. (2021). Complejidad social y educación superior. Análisis crítico basado en agentes. Revista Ciencias de la Complejidad, 2(Edición Especial), 51–59. https://doi.org/10.48168/ccee012021-006
Al-Omoush, K. S., Garcia-Monleon, F., & Mas Iglesias, J. M. (2024). Exploring the interaction between big data analytics, frugal innovation, and competitive agility: The mediating role of organizational learning. Technological Forecasting and Social Change, 200, 123188. https://doi.org/10.1016/j.techfore.2023.123188
Anderson, P. (1999). Perspective: Complexity theory and organization science. Organization Science, 10(3), 216–232. https://doi.org/10.1287/orsc.10.3.216
Ashrafi, A., Zare Ravasan, A., Trkman, P., & Afshari, S. (2019). The role of business analytics capabilities in bolstering firms’ agility and performance. International Journal of Information Management, 47, 1–15. https://doi.org/10.1016/j.ijinfomgt.2018.12.005
Atin, E., Boselli, R., Clément, F., Hauret, L., Krusell, S., Martin, L., Noja, G., Pulido, B., & Panzaru, C. (2024). Innovating the use of labour market intelligence within European universities. European Review of Applied Sociology, 17(28), 57–65. https://doi.org/10.2478/eras-2024-0005
Baig, M. I., Shuib, L., & Yadegaridehkordi, E. (2020). Big data in education: A state of the art, limitations, and future research directions. International Journal of Educational Technology in Higher Education, 17, 44. https://doi.org/10.1186/s41239-020-00223-0
Belchior-Rocha, H., Casquilho-Martins, I., & Simões, E. (2022). Transversal competencies for employability: From higher education to the labour market. Education Sciences, 12(4), 255. https://doi.org/10.3390/educsci12040255
Bone, M., González Ehlinger, E., & Stephany, F. (2025). Skills or degree? The rise of skill-based hiring for AI and green jobs. Technological Forecasting and Social Change, 214, 124042. https://doi.org/10.1016/j.techfore.2025.124042
Boshkoska, B. M., Sen, S., & Boškoski, P. (2025). Designing graduate business curricula by utilizing a market-driven skills extraction approach. Decision Sciences Journal of Innovative Education, 23(2), e70003. https://doi.org/10.1111/dsji.70003
Božič, K., & Dimovski, V. (2019). Business intelligence and analytics for value creation: The role of absorptive capacity. International Journal of Information Management, 46, 93–103. https://doi.org/10.1016/j.ijinfomgt.2018.11.020
Busso, M., Bassi, M., Urzúa, S., & Vargas, J. (2012). Disconnected: Skills, education, and employment in Latin America. Inter-American Development Bank. https://doi.org/10.18235/0012582
Daft, R. L., & Weick, K. E. (1984). Toward a model of organizations as interpretation systems. Academy of Management Review, 9(2), 284–295. https://doi.org/10.5465/amr.1984.4277657
Daniel, B. (2015). Big data and analytics in higher education: Opportunities and challenges. British Journal of Educational Technology, 46(5), 904–920. https://doi.org/10.1111/bjet.12230
Estrada, E. (2024). What is a complex system, after all? Foundations of Science, 29(4), 1143–1170. https://doi.org/10.1007/s10699-023-09917-w
Ferreyra, M. M., Dinarte Díaz, L., Urzúa, S., & Bassi, M. (2021). The fast track to new skills: Short-cycle higher education programs in Latin America and the Caribbean. World Bank. https://doi.org/10.1596/978-1-4648-1706-9
Fink, L., Yogev, N., & Even, A. (2017). Business intelligence and organizational learning: An empirical investigation of value creation processes. Information & Management, 54(1), 38–56. https://doi.org/10.1016/j.im.2016.03.009
Flores Sánchez, C. A., Meza Fragoso, J. A., & Lobo Rodríguez, M. O. (2024). Instituciones de educación superior, un sistema complejo en transformación digital. Revista Iberoamericana de Complejidad y Ciencias Económicas, 2(4), 53–63. https://doi.org/10.48168/ricce.v2n4p53
Holland, J. H. (2006). Studying complex adaptive systems. Journal of Systems Science and Complexity, 19(1), 1–8. https://doi.org/10.1007/s11424-006-0001-z
Ifenthaler, D., & Yau, J. Y.-K. (2020). Utilising learning analytics to support study success in higher education: A systematic review. Educational Technology Research and Development, 68(4), 1961–1990. https://doi.org/10.1007/s11423-020-09788-z
Javadian Sabet, A., Bana, S. H., Yu, R., & Frank, M. R. (2024). Course-Skill Atlas: A national longitudinal dataset of skills taught in U.S. higher education curricula. Scientific Data, 11, 1086. https://doi.org/10.1038/s41597-024-03931-8
Ladyman, J., Lambert, J., & Wiesner, K. (2013). What is a complex system? European Journal for Philosophy of Science, 3(1), 33–67. https://doi.org/10.1007/s13194-012-0056-8
Larson, D., & Chang, V. (2016). A review and future direction of agile, business intelligence, analytics and data science. International Journal of Information Management, 36(5), 700–710. https://doi.org/10.1016/j.ijinfomgt.2016.04.013
March, J. G. (1991). Exploration and exploitation in organizational learning. Organization Science, 2(1), 71–87. https://doi.org/10.1287/orsc.2.1.71
Mason, M. (2008). What is complexity theory and what are its implications for educational change? Educational Philosophy and Theory, 40(1), 35–49. https://doi.org/10.1111/j.1469-5812.2007.00413.x
Mikalef, P., Boura, M., Lekakos, G., & Krogstie, J. (2019). Big data analytics capabilities and innovation: The mediating role of dynamic capabilities and moderating effect of the environment. British Journal of Management, 30(2), 272–298. https://doi.org/10.1111/1467-8551.12343
Mikalef, P., Krogstie, J., Pappas, I. O., & Pavlou, P. A. (2020). Exploring the relationship between big data analytics capability and competitive performance: The mediating roles of dynamic and operational capabilities. Information & Management, 57(2), 103169. https://doi.org/10.1016/j.im.2019.05.004
Mikalef, P., van de Wetering, R., & Krogstie, J. (2021). Building dynamic capabilities by leveraging big data analytics: The role of organizational inertia. Information & Management, 58(6), 103412. https://doi.org/10.1016/j.im.2020.103412
Morin, E. (2007). Restricted complexity, general complexity. In C. Gershenson, D. Aerts, & B. Edmonds (Eds.), Worldviews, science and us: Philosophy and complexity (pp. 5–29). World Scientific. https://doi.org/10.1142/9789812707420_0002
OECD. (2026). Anticipating skill needs and adapting higher education: From insight to alignment. OECD Publishing. https://doi.org/10.1787/827b3ca4-en
Phillips-Wren, G., Daly, M., & Burstein, F. (2021). Reconciling business intelligence, analytics and decision support systems: More data, deeper insight. Decision Support Systems, 146, 113560. https://doi.org/10.1016/j.dss.2021.113560
Rikala, P., Braun, G., Järvinen, M., Stahre, J., & Hämäläinen, R. (2024). Understanding and measuring skill gaps in Industry 4.0—A review. Technological Forecasting and Social Change, 201, 123206. https://doi.org/10.1016/j.techfore.2024.123206
Römgens, I., Scoupe, R., & Beausaert, S. (2020). Unraveling the concept of employability, bringing together research on employability in higher education and the workplace. Studies in Higher Education, 45(12), 2588–2603. https://doi.org/10.1080/03075079.2019.1623770
Rosales Cisneros, R. F. (2025). Cambio organizacional y pensamiento complejo: Un estudio de caso de una universidad del noroeste de México. Revista Iberoamericana de Complejidad y Ciencias Económicas, 3(4), 7–19. https://doi.org/10.48168/ricce.v3n4p7
Salas-Velasco, M. (2021). Mapping the (mis)match of university degrees in the graduate labor market. Journal for Labour Market Research, 55, 14. https://doi.org/10.1186/s12651-021-00297-x
Salgado Soto, M. del C., & Parra Flores, J. M. (2021). La teoría de la complejidad y el entorno educativo. Revista Ciencias de la Complejidad, 2(Edición Especial), 37–44. https://doi.org/10.48168/ccee012021-004
Sequeira, R., Reis, A., Alves, P., & Branco, F. (2024). Roadmap for implementing business intelligence systems in higher education institutions: Systematic literature review. Information, 15(4), 208. https://doi.org/10.3390/info15040208
Simon, H. A. (1955). A behavioral model of rational choice. The Quarterly Journal of Economics, 69(1), 99–118. https://doi.org/10.2307/1884852
Sivarajah, U., Kamal, M. M., Irani, Z., & Weerakkody, V. (2017). Critical analysis of big data challenges and analytical methods. Journal of Business Research, 70, 263–286. https://doi.org/10.1016/j.jbusres.2016.08.001
Stojanov, A., & Daniel, B. K. (2024). A decade of research into the application of big data and analytics in higher education: A systematic review of the literature. Education and Information Technologies, 29(5), 5807–5831. https://doi.org/10.1007/s10639-023-12033-8
Tran, L. T., Ngo, N. T. H., Nguyen, H. T. M., Le, T. T. T., & Ho, T. T. H. (2024). “Employability in context”: Graduate employability attributes expected by employers in regional Vietnam and implications for career guidance. International Journal for Educational and Vocational Guidance, 24, 375–395. https://doi.org/10.1007/s10775-022-09560-0
Weaver, W. (1948). Science and complexity. American Scientist, 36(4), 536–544.
Weick, K. E., Sutcliffe, K. M., & Obstfeld, D. (2005). Organizing and the process of sensemaking. Organization Science, 16(4), 409–421. https://doi.org/10.1287/orsc.1050.0133
Al-Omoush, K. S., Garcia-Monleon, F., & Mas Iglesias, J. M. (2024). Exploring the interaction between big data analytics, frugal innovation, and competitive agility: The mediating role of organizational learning. Technological Forecasting and Social Change, 200, 123188. https://doi.org/10.1016/j.techfore.2023.123188
Anderson, P. (1999). Perspective: Complexity theory and organization science. Organization Science, 10(3), 216–232. https://doi.org/10.1287/orsc.10.3.216
Ashrafi, A., Zare Ravasan, A., Trkman, P., & Afshari, S. (2019). The role of business analytics capabilities in bolstering firms’ agility and performance. International Journal of Information Management, 47, 1–15. https://doi.org/10.1016/j.ijinfomgt.2018.12.005
Atin, E., Boselli, R., Clément, F., Hauret, L., Krusell, S., Martin, L., Noja, G., Pulido, B., & Panzaru, C. (2024). Innovating the use of labour market intelligence within European universities. European Review of Applied Sociology, 17(28), 57–65. https://doi.org/10.2478/eras-2024-0005
Baig, M. I., Shuib, L., & Yadegaridehkordi, E. (2020). Big data in education: A state of the art, limitations, and future research directions. International Journal of Educational Technology in Higher Education, 17, 44. https://doi.org/10.1186/s41239-020-00223-0
Belchior-Rocha, H., Casquilho-Martins, I., & Simões, E. (2022). Transversal competencies for employability: From higher education to the labour market. Education Sciences, 12(4), 255. https://doi.org/10.3390/educsci12040255
Bone, M., González Ehlinger, E., & Stephany, F. (2025). Skills or degree? The rise of skill-based hiring for AI and green jobs. Technological Forecasting and Social Change, 214, 124042. https://doi.org/10.1016/j.techfore.2025.124042
Boshkoska, B. M., Sen, S., & Boškoski, P. (2025). Designing graduate business curricula by utilizing a market-driven skills extraction approach. Decision Sciences Journal of Innovative Education, 23(2), e70003. https://doi.org/10.1111/dsji.70003
Božič, K., & Dimovski, V. (2019). Business intelligence and analytics for value creation: The role of absorptive capacity. International Journal of Information Management, 46, 93–103. https://doi.org/10.1016/j.ijinfomgt.2018.11.020
Busso, M., Bassi, M., Urzúa, S., & Vargas, J. (2012). Disconnected: Skills, education, and employment in Latin America. Inter-American Development Bank. https://doi.org/10.18235/0012582
Daft, R. L., & Weick, K. E. (1984). Toward a model of organizations as interpretation systems. Academy of Management Review, 9(2), 284–295. https://doi.org/10.5465/amr.1984.4277657
Daniel, B. (2015). Big data and analytics in higher education: Opportunities and challenges. British Journal of Educational Technology, 46(5), 904–920. https://doi.org/10.1111/bjet.12230
Estrada, E. (2024). What is a complex system, after all? Foundations of Science, 29(4), 1143–1170. https://doi.org/10.1007/s10699-023-09917-w
Ferreyra, M. M., Dinarte Díaz, L., Urzúa, S., & Bassi, M. (2021). The fast track to new skills: Short-cycle higher education programs in Latin America and the Caribbean. World Bank. https://doi.org/10.1596/978-1-4648-1706-9
Fink, L., Yogev, N., & Even, A. (2017). Business intelligence and organizational learning: An empirical investigation of value creation processes. Information & Management, 54(1), 38–56. https://doi.org/10.1016/j.im.2016.03.009
Flores Sánchez, C. A., Meza Fragoso, J. A., & Lobo Rodríguez, M. O. (2024). Instituciones de educación superior, un sistema complejo en transformación digital. Revista Iberoamericana de Complejidad y Ciencias Económicas, 2(4), 53–63. https://doi.org/10.48168/ricce.v2n4p53
Holland, J. H. (2006). Studying complex adaptive systems. Journal of Systems Science and Complexity, 19(1), 1–8. https://doi.org/10.1007/s11424-006-0001-z
Ifenthaler, D., & Yau, J. Y.-K. (2020). Utilising learning analytics to support study success in higher education: A systematic review. Educational Technology Research and Development, 68(4), 1961–1990. https://doi.org/10.1007/s11423-020-09788-z
Javadian Sabet, A., Bana, S. H., Yu, R., & Frank, M. R. (2024). Course-Skill Atlas: A national longitudinal dataset of skills taught in U.S. higher education curricula. Scientific Data, 11, 1086. https://doi.org/10.1038/s41597-024-03931-8
Ladyman, J., Lambert, J., & Wiesner, K. (2013). What is a complex system? European Journal for Philosophy of Science, 3(1), 33–67. https://doi.org/10.1007/s13194-012-0056-8
Larson, D., & Chang, V. (2016). A review and future direction of agile, business intelligence, analytics and data science. International Journal of Information Management, 36(5), 700–710. https://doi.org/10.1016/j.ijinfomgt.2016.04.013
March, J. G. (1991). Exploration and exploitation in organizational learning. Organization Science, 2(1), 71–87. https://doi.org/10.1287/orsc.2.1.71
Mason, M. (2008). What is complexity theory and what are its implications for educational change? Educational Philosophy and Theory, 40(1), 35–49. https://doi.org/10.1111/j.1469-5812.2007.00413.x
Mikalef, P., Boura, M., Lekakos, G., & Krogstie, J. (2019). Big data analytics capabilities and innovation: The mediating role of dynamic capabilities and moderating effect of the environment. British Journal of Management, 30(2), 272–298. https://doi.org/10.1111/1467-8551.12343
Mikalef, P., Krogstie, J., Pappas, I. O., & Pavlou, P. A. (2020). Exploring the relationship between big data analytics capability and competitive performance: The mediating roles of dynamic and operational capabilities. Information & Management, 57(2), 103169. https://doi.org/10.1016/j.im.2019.05.004
Mikalef, P., van de Wetering, R., & Krogstie, J. (2021). Building dynamic capabilities by leveraging big data analytics: The role of organizational inertia. Information & Management, 58(6), 103412. https://doi.org/10.1016/j.im.2020.103412
Morin, E. (2007). Restricted complexity, general complexity. In C. Gershenson, D. Aerts, & B. Edmonds (Eds.), Worldviews, science and us: Philosophy and complexity (pp. 5–29). World Scientific. https://doi.org/10.1142/9789812707420_0002
OECD. (2026). Anticipating skill needs and adapting higher education: From insight to alignment. OECD Publishing. https://doi.org/10.1787/827b3ca4-en
Phillips-Wren, G., Daly, M., & Burstein, F. (2021). Reconciling business intelligence, analytics and decision support systems: More data, deeper insight. Decision Support Systems, 146, 113560. https://doi.org/10.1016/j.dss.2021.113560
Rikala, P., Braun, G., Järvinen, M., Stahre, J., & Hämäläinen, R. (2024). Understanding and measuring skill gaps in Industry 4.0—A review. Technological Forecasting and Social Change, 201, 123206. https://doi.org/10.1016/j.techfore.2024.123206
Römgens, I., Scoupe, R., & Beausaert, S. (2020). Unraveling the concept of employability, bringing together research on employability in higher education and the workplace. Studies in Higher Education, 45(12), 2588–2603. https://doi.org/10.1080/03075079.2019.1623770
Rosales Cisneros, R. F. (2025). Cambio organizacional y pensamiento complejo: Un estudio de caso de una universidad del noroeste de México. Revista Iberoamericana de Complejidad y Ciencias Económicas, 3(4), 7–19. https://doi.org/10.48168/ricce.v3n4p7
Salas-Velasco, M. (2021). Mapping the (mis)match of university degrees in the graduate labor market. Journal for Labour Market Research, 55, 14. https://doi.org/10.1186/s12651-021-00297-x
Salgado Soto, M. del C., & Parra Flores, J. M. (2021). La teoría de la complejidad y el entorno educativo. Revista Ciencias de la Complejidad, 2(Edición Especial), 37–44. https://doi.org/10.48168/ccee012021-004
Sequeira, R., Reis, A., Alves, P., & Branco, F. (2024). Roadmap for implementing business intelligence systems in higher education institutions: Systematic literature review. Information, 15(4), 208. https://doi.org/10.3390/info15040208
Simon, H. A. (1955). A behavioral model of rational choice. The Quarterly Journal of Economics, 69(1), 99–118. https://doi.org/10.2307/1884852
Sivarajah, U., Kamal, M. M., Irani, Z., & Weerakkody, V. (2017). Critical analysis of big data challenges and analytical methods. Journal of Business Research, 70, 263–286. https://doi.org/10.1016/j.jbusres.2016.08.001
Stojanov, A., & Daniel, B. K. (2024). A decade of research into the application of big data and analytics in higher education: A systematic review of the literature. Education and Information Technologies, 29(5), 5807–5831. https://doi.org/10.1007/s10639-023-12033-8
Tran, L. T., Ngo, N. T. H., Nguyen, H. T. M., Le, T. T. T., & Ho, T. T. H. (2024). “Employability in context”: Graduate employability attributes expected by employers in regional Vietnam and implications for career guidance. International Journal for Educational and Vocational Guidance, 24, 375–395. https://doi.org/10.1007/s10775-022-09560-0
Weaver, W. (1948). Science and complexity. American Scientist, 36(4), 536–544.
Weick, K. E., Sutcliffe, K. M., & Obstfeld, D. (2005). Organizing and the process of sensemaking. Organization Science, 16(4), 409–421. https://doi.org/10.1287/orsc.1050.0133
Recibido:
2026-09-30
Publicado:
2026-10-01
Cómo citar
Rodríguez Aguiñaga, A., Rubio Arriaga, Z., & Salgado Soto, M. del C. (2026). Complejidad y análisis de datos para la inteligencia de negocios: una perspectiva conceptual sobre la relación entre educación superior y mercado laboral. Revista Iberoamericana De Complejidad Y Ciencias Económicas, 4(3), 115-134. Recuperado a partir de https://revistas.ulasalle.edu.pe/ricce/article/view/398
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